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5-2013 Genetic Imbalances in Endometriosis Detected by Oligonucleotide-Array Based Comparative Genomic Hybridization Natalie Burke East Tennessee State University
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Genetic Imbalances in Endometriosis Detected by Oligonucleotide-Array Based
Comparative Genomic Hybridization
______
A dissertation presented to
the faculty of
The Department of Biomedical Sciences
East Tennessee State University
In partial fulfillment
of the requirements for the degree
Doctor of Philosophy in Biomedical Sciences
______
by
Natalie Burke
May 2013
______
Jack Rary, Ph.D., Chair Ronald Baisden, Ph.D. Scott Champney, Ph.D. Bill Garside, Ph.D. Douglas Thewke, Ph.D.
Keywords: Endometriosis, HIC-1, Microarray, Comparative Genomic Hybridization
ABSTRACT
Genetic Imbalances in Endometriosis Detected by Oligonucleotide-Array Based
Comparative Genomic Hybridization
by
Natalie Burke
Endometriosis is one of the most common gynecological diseases as it is thought to affect up to 15% of the female population. Characterized by the growth and proliferation of endometrial tissue outside of the uterine cavity, it is a complex condition with varying degrees of severity and can affect multiple regions of the body with symptoms ranging from a total lack of symptoms to debilitating pain and infertility. The most accepted theory of how endometriosis initiates is that of retrograde menstruation; however, approximately 90% of women with unobstructed fallopian tubes are thought to have some menstrual debris in the peritoneal cavity. Therefore, this theory does not explain in full why endometriosis occurs in some but not all women who experience retrograde bleeding.
Genetic factors are thought to play a major role in the pathogenesis of endometriosis as women with a family history are 5 to 10 times more likely to develop the disease. The goal of this study was to determine if common chromosomal aberrations in the form of additions, deletions, or regions of loss of heterozygosity that may contribute to the establishment or progression of the disease are present in a population of
2 endometriosis patients. DNA was isolated from the peripheral blood of endometriosis patients and endometriosis tissue biopsies, and it was analyzed using oligonucleotide based array comparative genomic hybridization. The results suggest that an addition on chromosome 17p13.3 may play a role in the biological mechanisms involved in endometriosis as it was identified in 75% of the DNA samples obtained from the peripheral blood and 100% of the DNA samples obtained from the tissue biopsies. This chromosomal imbalance is of particular interest as it is located in a region that harbors the tumor suppressor gene, hypermethylated in cancer-1 (HIC-1), whose aberrant expression has been reported in multiple cancers.
Endometriosis has long been thought of as a benign disease despite its malignant characteristics, and individuals with endometriosis have been demonstrated to have an increased chance of developing ovarian cancer. This was the first study to examine the
DNA from endometriosis patients using oligonucleotide based array comparative genomic hybridization to investigate genetic abnormalities in endometriosis. The findings may provide a novel target for future therapeutic options as well as indicate a link between endometriosis and cancer that has not been previously reported.
3
DEDICATION
This manuscript is dedicated to my family and friends. To my mom and dad, thank you for your unconditional love and support on this journey. To my “children” Leo,
Halle, and Zev, your wagging tails and smiles brighten my life every day. Finally, to the late Dr. Sam Thatcher, thank you for introducing me to the world of reproductive medicine. Your wisdom and guidance led me to pursue what I truly believe will be a fulfilling, lifelong career.
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ACKNOWLEDGEMENTS
I would like to acknowledge the following:
Dr. Jack Rary and Pam Pippin. Dr. Rary, I could not have asked for a better
advisor, mentor, colleague, and friend. Pam, your friendship and support have been
invaluable.
My committee members Dr. Ron Baisden, Dr. Scott Champney, Dr. Bill Garside, and Dr. Doug Thewke. Thank you for your patience and guidance.
Quillen Fertility and Women’s Services, Dr. Norman Assad, Missy Assad, Diane
Love, and Robin Arning. This project would not have been possible without your tireless efforts. I look forward to working with each and every one of you in the future.
The Department of Biomedical Science. Dr. Mitch Robinson, Beverly Sherwood, and Angela Thompson. Thank you for your continuing support. Beverly, we will always have Flagler Beach.
My friends and fellow graduate students. Thank you for the advice, the memories, the laughs, and the occasional distraction from reality.
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TABLE OF CONTENTS
Page ABSTRACT………………………………….…………………………………….. 2 DEDICATION…………………………………………………………………...... 4 ACKNOWLEDGMENTS………………………………………………………….. 5 LIST OF ABBREVIATIONS…………………………………………………….... 9 LIST OF TABLES...……………………………………………………………….. 12 LIST OF FIGURES.……………………………………………………………..... 13 Chapter 1. INTRODUCTION…………………………………………………………. 15 Disease Stages……………………………………………………. 17 Proposed Methods of Pathogenesis……………………...... 21 Retrograde Menstruation………………………...... 21 Coelomic Metaplasia……………………………...... 21 Immunological Factors……………………………………. 22 Stem Cells………………………………………...... 22 Surgical Contamination…………………………...... 23 Environmental Factors…………………………...... 23 Genetic Factors…………………………………...... 23 Summary…………………………………………………... 24 A Benign Condition?...... 24 2. LITERATURE REVIEW……………………………………………….... 26 Genome-Wide Association and Linkage……………………….. 26 Comparative Genomic Hybridization Microarray...... 27 Loss of Heterozygosity…………………………...... 32 Gene Expression Microarray………………………...... 38 Summary 46 3. STUDY SUMMARY………………………………………………………. 47 Significance of Research…………………………………...... 47 Research Goals……………………………………………………. 48
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Statement of Research……………………………………...... 48 4. MATERIALS AND METHODS………………………………………...... 49 Patient Selection and Control Individuals………………...... 49 Participant Privacy………………………………………...... 50 Sample Collection……………………...... 50 Microarray Preparation and Analysis……………………………. 51 DNA Extraction from Peripheral Blood……………...... 52 DNA Extraction from Tissue Biopsy…………...... 52 DNA Purification……………………………...... 54 DNA Digestion…………………………………...... 55 Enzymatic Labeling……………………………...... 57 Microarray Hybridization and Data Analysis……………...... 57 Cell Line Preparation……………………………………...... 62 Cell Culture……………………………………...... 62 Cell Subculture………………………………………...... 62 Cell Line Cryopreservation……………………...... 63 Cell Harvest……………………………………...... 63 Karyotype Analysis……………………………………………...... 64 Slide Preparation………………………………...... 64 Slide Staining……………………………………...... 65 Karyotyping………………………………………………………… 65 5. RESULTS………………………………………………………………..... 68 CGH Microarray: 105K Platform…………………………………. 68 Peripheral Blood Samples……………………………….. 68 Chromosome 17p13.3 Addition in Peripheral Bloods: HIC-1………...... 69 Endometriosis Tissue Biopsies………………………...... 71 Chromosome 17p13.3 Addition in Tissue Biopsies: HIC-1…………………………………… 72 CGH Microarray: 180K Platform……………………………….... 74 Copy Number Variant Size Analysis…………………………..... 75
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Cell Culture…………………………………...... 78 Karyotyping……….………………………………………………... 79 6. DISCUSSION………………………………………………………...... 81 Hypermethylated in Cancer-1…………………………...... 81 Free-Circulating DNA…………………………………………...... 84 Loss of Heterozygosity……………………………………………. 85 Control Individuals………………………………………………… 87 Polyploid Cells in Culture……………………………….……...... 88 Copy Number Variant Size, Are We Missing Something?...... 89 False Positives…………………………………………………….. 91 Future Research…………………………………………………… 93 Research Conclusions and Summary…………………………... 94 BIBLIOGRAPHY………………………………………………………………...... 96 APPENDIXES…………………………………………………………………….. 110 Appendix A: IRB Approvals……………………………...... 110 Peripheral Blood Sample Approval……………………… 110 Endometriosis Biopsy Approval………………………….. 112 Endometriosis Biopsy Approval: MSHA Research Department……………………………. 114 Appendix B: Informed Consent Documents…………………..... 118 Peripheral Blood Informed Consent Document……….. 118 Endometriosis Biopsy Informed Consent Document….. 123 VITA………………………………………………………………………………... 127
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LIST OF ABBREVIATIONS
17βHSD2- 17β-hydroxysteroid dehydrogenase type-2 AIMP1: aminoacyl tRNA sythetase complex interacting multifunctional protein 1 APOA2: apolipoprotein A-II ANRIL: antisense non-coding RNA in the INK4 locus ASRM: American Society of Reproductive Medicine BAC: bacterial artificial chromosome bp: base pairs BRCA1: breast cancer 1 C: Celsius CD24: CD24 molecule, small cell lung carcinoma cluster 4 antigen cDNA-RDA: complimentary deoxyribonucleic acid representational difference analysis CDKN2: cyclin-dependent kinase inhibitor 2 CFDNA: free-circulating DNA CGH: comparative genomic hybridization CLDN11: claudin 11 CNV: copy number variant COUP-TF2: chicken ovalbumin upstream promoter transcription factor 2, see NR2F2 COX: cytochrome c oxidase CYP19: cytochrome P450 subfamily C gene DMSO: dimethyl sulfoxide DNA: deoxyribonucleic acid DPH1: diphthamide biosynthesis protein 1 dUTP: deoxyuridine triphosphate EAOC: endometriosis associated ovarian cancer ERBB3: erb-b2 erythroblastic leukemia viral oncogene homolog Fb-EM1: human endometriosis-derived permanent cell line FISH: fluorescent in situ hybridization FOS: FBJ murine osteosarcoma viral oncogene homolog
9
GALT: galactose-1-phosphate uridylyltransferase HLAI: major histocompatibility complex I HIC-1: hypermethylated in cancer-1 HOXA10: homeobox A10 HP: haptoglobin HSP90A: heat shock protein 90 alpha IL-2RG: interleukin 2 receptor gamma ISLR: immunoglobulin superfamily containing leucine-rich repeat ITGB: integrin beta IVF: in vitro fertilization JAM-1: junctional adhesion molecule 1 Kb: kilobase LAMC1: laminin, gamma 1 LCM: laser capture microscopy LOH: loss of heterozygosity LOX1: lysyl oxidase-like 1 MAT2A: methionine adenosyltransferase II, alpha Mb: megabase MCM: manual capture microscopy mg: milligram ml: milliliter mRNA: messenger ribonucleic acid MSHA: Mountain States Health Alliance NaCl: sodium chloride NR2F2: nuclear receptor subfamily 2, group F, member 2 NFE2L3: nuclear factor erythroid-derived 2-like 3 OMIM: Online Mendelian Inheritance in Man OVCA2: ovarian cancer 2 P14: see CDKNA2 P16: see CDKNA2 P43: see AIMP1
10
P450-AROM: see CYP19 PCB: polychlorinated biphenyl PCR: polymerase chain reaction PDGFA: platelet-derived growth factor receptor-α PGR: progesterone receptor PGS: prostacyclin synthase PLAII2: phospholipase A2 group IIA PTCH: patched homolog PTEN: phosphatase and tensin homolog RCA-RCA: restriction and circularization-aided rolling circle amplification RHOB: ras homolog family member B RP11: retinosa pigmentosa RPL: ribosomal protein L RPM: revolutions per minute SH3: src homolog 3 SMG8: nonsense mediated mRNA decay factor SNP: single nucleotide polymorphism TP53: tumor protein p53 ul: microliter WNT4: wingless-type MMTV integration site family, member 4
11
LIST OF TABLES
Table Page
1 Studies involving comparative genomic hybridization microarray and endometriosis………………………………………………. 28
2 Studies involving loss of heterozygosity and endometriosis……………... 33
3 Studies involving expression microarrays and endometriosis…………… 39
4 Copy number variant results from peripheral blood samples……………. 69
5 Microarray results (105K) of DNA isolated from the peripheral blood from endometriosis patients…………………………………………………. 70
6 Microarray results (105K) of DNA isolated from the peripheral blood from control individuals………………………………………………………. 71
7 Microarray results (105K) of DNA isolated from endometriosis tissue biopsies from endometriosis patients………………………………………. 73
8 Microarray results (105K) from the DNA isolated from endometriosis tissue biopsies and corresponding peripheral blood samples from endometriosis patients……………………..……………………………….... 74
9 Microarray results (180K) of DNA isolated from endometriosis tissue biopsies……………………………………………………………….………. 75
10 Total CNVs by size as detected by the 105K platform…………………… 76
11 Total CNVs by size as detected by the 180K platform…………………… 77
12 Regions of LOH as reported in the literature………………………………. 86
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LIST OF FIGURES
Figure Page
1 Female reproductive anatomy including the most common sites for
endometriosis to occur …………………………………………………….… 17
2 Raspberry endometriosis implants………………………………………….. 18
3 Powder burn endometriosis lesions………………………………………… 19
4 Hemorrhagic endometriosis lesions……………………………………….. 19
5 Chocolate endometriosis cysts……………………………………………… 20
6 Adhesions associated with endometriosis…………………………………. 20
7 Microarray workflow…………………………………………………………... 51
8 Endometriosis tissue biopsies………………………………………………. 53
9 Agilent Bioanalyzer output…………………………………………………… 56
10 GenePix 4000B scanner raw image………………………………………... 59
11 BlueFuse Multi software output, CGH view ……………………………….. 60
12 BlueFuse Multi Software output, decision tracks view …………………… 60
13 BlueFuse Multi software output, karyotype view ………………………… 61
14 BlueFuse Multi software output, chromosome view ……………………. 61
15 Ideal chromosome spread…………………………………………...………. 66
16 Complete karyotype………………………………………………………….. 67
17 Chromosome 17p13.3 addition size in endometriosis tissue versus
peripheral blood………………………………………………………………. 73
18 Total CNVs by percentage as detected by the 105K platform…………… 77
13
19 Total CNVs by percentage as detected by the 180K platform…………… 78
20 Endometriosis cell culture……………………………………………………. 79
21 Tetraploid karyotype………………………………………………………….. 80
22 Microarray runs, “noisy” versus clean………………………………………. 92
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CHAPTER 1
INTRODUCTION
Endometriosis is a disease involving the female reproductive organs. Each
month during a woman’s menstrual cycle, the uterine lining, the endometrium, grows
and thickens in order to prepare for the implantation of a fertilized oocyte. If a fertilized
oocyte does not implant, the endometrium is shed by way of menstruation. In most
women a portion of the endometrium is refluxed through the fallopian tubes and out into
the peritoneal cavity, an occurrence known as retrograde menstruation. In some
women, these misplaced cells are able to attach to nearby tissues where they mimic the
normal endometrium-growing, thickening, and shedding in response to the hormonal
fluctuations of the menstrual cycle. Whereas the menstrual debris inside of the uterus exits the body through the vagina, menstrual debris shed from the ectopic endometrium remains in the abdominal cavity. Endometriosis refers to this condition in which endometrial tissue grows and proliferates outside of the uterine cavity.
Endometriosis is one of the most common gynecological diseases among
women of reproductive age. It can be a debilitating condition associated with persistent
inflammation as well as chronic pain in the pelvic region of many patients. Additional
symptoms may include dyspareunia, dysmenorrhea, dysuria, dyschezia, long or heavy
periods, and short menstrual cycles. It is a complex disease with varying degrees of
severity and can affect multiple regions of the body. Endometriosis is most often found
on the tissues surrounding the uterus (Figure 1) such as the ovaries, rectum, bladder,
and the bowels; however, cases have been reported at locations distant from the uterus
15
such as in the lymph nodes, brain, lungs, liver, and in the eyes. Between 10% and 15%
of the female population 1, 2 is thought to be affected by the disease; however, these estimates may be conservative as many women are asymptomatic or fail to seek medical treatment.
It is a major cause of discomfort as well as a common cause of infertility. Various studies suggest that the disease may compromise fertility by creating a hostile environment that affects spermatozoa, oocytes, and embryos in multiple ways.
Distortion of the female reproductive anatomy, altered folliculogenesis 3, 4, decreased
oocyte quality 5, increased production of reactive oxygen species 6, immune system
alteration 7, 8, a decrease in endometrial receptivity and oocyte implantation 9, 10,
interference with spermatozoa’s ability to fertilize an oocyte 11, 12, and dyspareunia
resulting in abstaining from sexual intercourse have all been identified as key
contributing factors to decreased fertility in patients with endometriosis.
16
Figure 1 Female reproductive anatomy including the most common sites for endometriosis to occur
Disease Stages
The American Society of Reproductive Medicine (ASRM) has established a
grading system to diagnose disease severity. Points are given based on the size,
location, and severity of the implants. A stage of I, II, III, or IV is assigned based on the
overall score with I being minimal disease and IV being the most severe. Interestingly, the stage of disease does not necessarily correlate with the level of pain experienced by the patient as cases of asymptomatic women with advanced, widespread endometriosis
17 have been reported as well as patients experiencing severe pelvic pain with minimal disease.
The physical appearance of endometriosis can vary widely and typically changes as the disease tissue ages. Small pink to red implants, powder burn spots, clusters of hemorrhagic lesions, and endometriotic cysts are the most common forms of endometriosis observed upon laparoscopic examination. Endometriosis tissue may be comprised of stroma, glandular structures, hemosiderin deposits, and fibrotic scar tissue with varying degrees of vascularization and hemorrhage.
“Raspberry” implants or small red patches or polyps of tissue are common with recent or young disease tissue or minimal cases of disease (Figure 2).
Figure 2 Raspberry endometriosis implants: (A, B) Endometriosis tissue is indicated by black arrows.
A. B.
18
Powder burn or “blueberry” lesions are the most recognizable form of
endometriosis and thus the most well documented. These spots are generally dark red,
purple, or black in color and are generally associated with moderate to severe
endometriosis (Figure 3).
Figure 3 Powder burn endometriosis lesions: (A, B) Endometriosis tissue is indicated by black arrows.
A. B.
Hemmorhagic lesions or red patches are easily recognized during certain phases of the menstrual cycle as they proliferate and shed menstrual debris with hormonal fluctuations (Figure 4).
Figure 4 Hemmorhagic endometriosis lesions: (A, B, C) Endometriosis tissue is indicated by black arrows.
A. B. C.
19
“Chocolate” cysts or endometriomas are cystic structures filled with old blood and menstrual debris which give them their characteristic color (Figure 5). These structures are generally associated with severe or advanced stages of disease and have the potential to rupture and form adhesions.
Figure 5 Chocolate endometriosis cysts: (A, B) Endometriosis cysts
A. B.
Adhesions are bands of scar tissue that form as a result of endometriosis, however, they are not considered endometriosis themselves (Figure 6). Extensive adhesion formation has the potential to cause distortion of the reproductive anatomy, pelvic pain, and infertility.
Figure 6 Adhesions associated with endometriosis: Adhesions are indicated by black arrows.
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Proposed Mechanisms of Pathogenesis
Retrograde menstruation is one of the oldest and most widely accepted
hypotheses as to how endometriosis establishes 13. Retrograde menstruation is a
phenomenon in which a portion of the uterine lining moves into the fallopian tubes and
out into the peritoneal cavity during menstruation rather than being shed through the
vagina, where it attaches and grows in various locations. This misplaced endometrial
tissue acts in the same way the normal endometrium does inside of the uterus. Over the
course of a typical menstrual cycle as hormones fluctuate, the ectopic tissue thickens in
preparation for the implantation of an embryo, and it is shed if implantation of an embryo
does not occur. The ectopic implants release menstrual debris into the peritoneal cavity
and surrounding environment until it is cleared by immunological responses or
reabsorbed into surrounding tissue. Approximately 90% of menstruating women with
unobstructed fallopian tubes have menstrual debris in the peritoneal cavity 14; however
as stated, only around 15% of women of reproductive age suffer from endometriosis.
This theory, therefore, does not explain in full why endometriosis occurs in some but not
all women who experience retrograde menstruation. Also, this does not answer the
question of how endometriosis is able to invade tissues outside of the pelvis.
Coelomic metaplasia describes a scenario in which “normal” epithelial cells transform into abnormal endometrial cells in the peritoneal cavity or elsewhere, and these cells progress into endometriosis. This hypothesis stems from the notion that the reproductive organs form from cells lining the coelomic cavity; therefore, any dedifferentiated cells or remnants of this process have the ability to become endometrial cells and eventually form endometriosis. As other hypotheses of pathogenesis rely on
21 endometrial tissue being present, this scenario is an attractive explanation as cases of endometriosis have been reported in individuals lacking uterine structures including women with agenesis reproductive organs 15 and in men with prostate cancer 16.
Immunological factors have been implicated in endometriosis as most women experience retrograde menstruation, but only some develop the disease. It is possible that an inability of the immune system either to recognize or to clear refluxed menstrual debris may contribute to disease establishment 17 as immune system alterations have been demonstrated in multiple studies 18-20. This hypothesis does not address why endometriosis patients have not been shown to experience a higher prevalence of other diseases that would be expected to result from an inefficient immune system or why endometriosis is found in regions of the body outside of the peritoneal cavity.
Stem cells have recently been implicated as a possible contributing factor to the pathogenesis of endometriosis 21-23. The endometrium is highly regenerative as the uterine lining thickens and is shed each month with the menstrual cycle. As with any tissue that undergoes rapid turnover or constant renewal, the endometrium contains a population of undifferentiated cells or stem cells. When necessary, chemical signals are sent within each microenvironment to tell these stem cells to differentiate into progenitor cells that will then further differentiate into the appropriate cell type- in this case, new endometrial lining is formed.
It has been suggested that because stem cells are able to differentiate into a variety of cell types, those in circulation throughout the body may differentiate into endometrial cells. As these endometrial cells are aberrantly placed, they have the
22 potential to grow and establish endometriosis. Such a mechanism could potentially contribute to other proposed mechanisms of pathogenesis including coelomic metaplasia as well as explain how endometriosis establishes at sites outside of the peritoneal cavity in premenarchal girls and in individuals lacking female reproductive organs.
Surgical contamination has been proposed to cause endometriosis wherein during surgical procedures involving the reproductive tract, some cells may be transferred into the abdominal or peritoneal cavity 24-27. These misplaced cells are thought to have the potential to form endometriosis lesions or implants. This mechanism cannot explain endometriosis in patients who have not had surgery involving the reproductive tract or who have never undergone surgery.
Environmental factors including exposure to dioxins and polychlorinated biphenyls (PCBs) have been suggested to be correlated with endometriosis 28. These
“organochlorines” are pollutants produced as a result of manufacturing processes and are known to accumulate in foods and are toxic at high concentrations. Some patients with endometriosis have been reported to have elevated levels of dioxins in the blood 29, plasma 30 and peritoneal fluid 31 when compared to control individuals. The mechanisms by which organochlorines may contribute to the disease remain to be elucidated at this point.
Genetic factors are thought to play a major role in the pathogenesis of the disease as women with a family history of endometriosis are 5-10 times more likely to develop the disease than those without a family history 32. Multiple studies have
23 identified chromosomal imbalances in association with the disease using array based technology 33-36 while other similar studies identified no alterations 37, 38. Linkage studies have implicated various regions in the genome including loci at 7p15.2 39 and 10q26 40, 41 with endometriosis; however, despite these studies, few commonalities have been noted. In this study we use a higher resolution platform than has been previously used to investigate the presence of genomic imbalances in the DNA from endometriosis tissue and corresponding peripheral blood samples of endometriosis patients.
Summary: It is highly likely that endometriosis is a multifactorial disease with various components that contribute to disease establishment and severity. Despite all of the hypotheses proposed, investigators agree that something is different either within the diseased individual or in the disease tissue itself which allows the ectopically placed endometrium to grow and proliferate.
A Benign Condition?
Endometriosis has long been thought of as a benign disease despite its many similarities to cancer including metastasis, tissue invasion, angiogenesis, and uncontrolled cell growth. Currently, the literature suggests that the malignant transformation of endometriosis is between 0.3% and 5% while endometriosis synchronous with ovarian cancer is around 20%. Specific criteria to qualify endometriosis as becoming malignant were put forth in 1925 by Sampson 42 and were amended in 1953 by Scott 43. These criteria are as follows and are still accepted today:
24
1) Endometriosis must be located in the vicinity of a malignant tumor
2) Malignant tissue must come directly from endometriosis tissue
3) Tissue similar in appearance to endometrial tissue surrounding
characteristic glands must be present
4) There must be histological evidence of a benign to malignant
transformation
Because the criteria to classify endometriosis as becoming cancerous are so strict, chances are the incidence of malignant transformation is grossly underestimated.
Many investigators have speculated that endometriosis patients are at a higher risk of developing certain cancers, and multiple studies have confirmed that women with endometriosis are at an increased risk of developing ovarian cancer 44-46, specifically
endometrioid, clear-cell, and low-grade serous types. One such study recently
investigated women undergoing in vitro fertilization (IVF) treatment and their incidence
of endometriosis and ovarian cancer and reported that nulliparous women with
endometriosis had a 3-fold increase in ovarian cancer incidence 47. Identifying an
increased risk of cancer as well as potential molecular and genetic similarities between
ovarian cancer and endometriosis may help explain if women with endometriosis are, in
fact, predisposed to malignancy or if endometriosis may be a precursor to ovarian
cancer.
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CHAPTER 2
LITERATURE REVIEW
Genome Wide Association and Linkage
Gene linkage studies are useful when a genetic association is suspected in a particular disease, but no information is available as to its loci. Typically, large numbers of clinical records are accessed and analyzed with various software programs to identify common genetic markers in the disease group that may serve as a directional tool for identifying a gene or group of genes responsible for disease. Although only few linkage studies have been performed on endometriosis, several potentially important susceptibility loci have been reported.
Areas of linkage on chromosome 10q26 have been reported in 2 studies 40, 41.
Painter et al. identified a linkage peak specifically within the cytochrome P450 subfamily
C gene (CYP2C19) that is of particular interest as it is involved in the production and metabolism of estrogen that is known to be associated with endometriosis. Genetic linkage has also been reported on chromosome 7p15.2 39 in a region upstream from 2 possible causative genes- NFE2L3 that is expressed in the placenta and HOXA10 which is involved in uterine development. Other areas of suggested linkage include chromosome 20p13 and areas of minor linkage on chromosomes 2, 6, 8, 12, 14, 15, and 17 40. Uno et al. reported linkage on chromosome 9p21 that includes several genes of potential importance including CDKN2BAS or ANRIL (antisense non-coding RNA in the INK4 locus) that has been reported to be altered in a variety of diseases including several cancers and P14 and P16 that are known tumor suppressors 48. In the same
26 study, 2 single nucleotide polymorphisms (SNPs) were identified on chromosome 1p36 that may be of interest as they are located within the WNT4 gene which is associated with development of the reproductive organs.
Using these studies as directional markers may be useful in discovering genetic markers or alterations that may contribute to the disease. Many of the regions reported in the aforementioned studies correlate with the typical disease state of endometriosis as it is an estrogen-dependent disease often affecting the reproductive organs.
Although no definitive genes have been discovered at this point that cause endometriosis, identifying linkage in areas associated with estrogen metabolism, the development of reproductive organs, and tumor suppressor genes may prove to be valuable pieces of the puzzle of the disease mechanism.
Comparative Genomic Hybridization Microarray
Comparative genomic hybridization (CGH) microarray is a powerful tool used to analyze the DNA from a patient paired with a known control DNA to investigate the presence of copy number variants throughout the genome. Various platforms are available for research including printed or oligo arrays that use a slide spotted with specific DNA sequences spanning the genome or fluorescent in-situ hybridization
(FISH) based platforms in which a mixture of probes is allowed to hybridize directly to metaphase chromosome spreads. In either case, hybridization of each fluorescently- labeled DNA sample is analyzed using specialized software to investigate areas of increased or decreased fluorescence that may correspond to areas of gains or losses of
27 genetic material. Different types of probes are available for use including oligonucleotide
(oligo) probes and bacterial artificial chromosome (BAC) probes. Oligos are generally around 30 base pairs in length while BACs are much larger and thus not able to detect small changes at a high resolution. Resolution refers to both the size of the probes and the distance between the probes, and it represents the smallest copy number variant size that is detectable by a platform given these 2 factors. Several studies have been performed using comparative genomic hybridization array technology to analyze the presence of copy number variants in the DNA from endometriosis patients. The most relevant are summarized in Table 1 and discussed below.
Table 1 Studies involving comparative genomic hybridization microarray and endometriosis
Group Date DNA source Platform Areas of interest Saare et al. 2012 Blood, eutopic/ectopic Illumina Human OmniExpress None tissue BeadChip SNP arrays: oligo probes Veiga-Castelli 2010 Eutopic/ectopic tissue FISH/metaphase CGH: oligo probes 1p33-pter, 11q12-q13.1, et al. 17p11.1-p12, 17q25- qter, 19, 20q11.23-qter, and 22q11.2-qter. Zafrakas et al. 2008 Ectopic tissue Affymetrix GeneChip: BAC probes None Wu et al. 2006 Eutopic/ectopic tissue Spectral Genomics Array: BAC 1p, 5p, 6p, 6q, 11p, 16q probes Guo et al. 2004 Eutopic/ectopic tissue Spectral Genomics microarray: BAC 1p, 3p14, 10q26, 13q33, probes 22q Gogusev et al. 2000 Endometriosis cell FISH/metaphase CGH 1q, 5p, 6p, 6q, 9, 11p, line: FbEM-1 12, 13q, 17q, 18, X Gogusev et al. 1999 Ectopic tissue FISH/metaphase CGH 1p, 5p, 6q, 7p, 17q, 22q
Gogusev et al. used CGH to investigate copy number variants from 18 ectopic tissue samples of various types including peritoneal implants, nodules, and ovarian endometriomas in patients with advanced stages of disease 33. DNA was isolated from manually dissected tissue without PCR amplification. Labeled DNA was hybridized to
28
“normal” metaphase spreads, and fluorescence was assessed for variation using
appropriate software. Chromosomal imbalances were reported in 15 of 18 (83%) of the
cases analyzed. The researchers recognized that small imbalances are not able to be observed using this methodology and noted that small chromosomal changes that may
contribute to disease establishment and progression may still be present. Gains were
seen on chromosomes 6q and 17q; however, losses were noted more frequently on
chromosomes 1p, 5p, 6q, 7p, and 22q. Interestingly, many of the deletions identified
were in regions containing tumor suppressor genes, specifically those on 1p, 5p, and
6q. Of most interest was the loss on chromosome 1p found in 50% of cases that contains several tumor suppressor genes reported to be altered in various cancers
including liver, breast, and colon cancer.
In 2000, the same group used similar methodology to examine chromosomal
aberrations in an endometriosis cell line (FbEM-1) 49. The cell line was initiated from an
ovarian endometrioma from a patient with advanced endometriosis. In contrast to their
previous studies, gains were reported more often than losses. The most significant
gains were shown on chromosomes 1q, 5p, 6p, and 17q, and various oncogenes were
suggested to be involved. Losses were evident on 6q, 9, 11p, 12, 13q, 18, and X, many
in regions harboring tumor suppressor genes.
Guo et al. examined 5 endometriosis tissue samples with 5 tissue samples from women with no history of endometriosis using a BAC array from Spectral Genomics
which contained 995 BAC clones 50. Laser capture microdissection (LCM) was used to
obtain epithelial cells and whole genome amplification was performed prior to
hybridization. Genomic alterations were reported in each endometriosis tissue sample;
29
however, no commonalities were found in all samples. Additions on chromosomes
3p14, 10q26, and 13q33 and losses on chromosomes 1p and 22q were observed most frequently.
Wu et al. used a similar microarray platform to analyze eutopic and ectopic tissue
samples from 5 patients. This array contained 2,632 BAC clones with a resolution of
approximately 1 Mb 36. Laser capture microdissection was used to isolate single
endometrial epithelial cells, and whole genome amplification was performed prior to
array hybridization. Alterations in both tissues were reported for all 5 patients. Genomic
gains on chromosome 1p, 6p, 6q, and 11p, and genomic losses on 1p, 5p, 6q, and 16q
were noted most frequently. Tissues were subdivided by type/location as either
peritoneal implants or ovarian cysts. It was reported that endometriotic lesions at
different locations may contain distinct copy number variants as the 3 peritoneal
implants analyzed shared gains in 1p and both ovarian cysts shared losses in 6q, 7p,
11q, and 25q.
Zafrakas et al. examined 10 endometriotic lesions using the Affymetrix Gene
Chip, a BAC array containing 5,659 clones with a resolution of approximately 1 Mb 37.
DNA was isolated from homogenized tissue samples prior to hybridization. They found no copy number variants in any of the samples analyzed.
Veiga-Castelli et al. examined ectopic and eutopic tissue samples from 10 patients using FISH/metaphase CGH 35. Five samples showed no alterations in either
the ectopic or the eutopic tissue. One patient showed a single gain in 17p in only the
ectopic tissue sample. One patient had gains on chromosome 19 and 22 in only the
30
eutopic tissue sample. The remaining 3 patients showed chromosomal aberrations in
both tissue samples. Investigators reported “significant alterations” in the form of
chromosomal gains in regions 1p33-pter, 11q12-q13.1, 17p11.1-p12, 17q25-qter, 19,
20q11.23-qter, and 22q11.2-qter. Alterations at 11q, 17p, 17q, and 19p were observed
most frequently, and the gain at 19p was observed in 4 samples from 3 patients. As
40% of the cases presented in this study showed alterations in both eutopic and ectopic
tissue samples, it was suggested that genomic alterations which may contribute to the
disease are present not only in disease tissue but also in the eutopic endometrium and
possibly throughout the cells of an individual.
Saare et al. analyzed copy number variants in blood, eutopic, and ectopic tissue
using Illumina Human OmniExpress BeadChip SNP arrays that include a total of
733,202 SNPs spanning the genome at approximately 2.2kb intervals 38. Genomic DNA was isolated from peripheral blood and tissue following laser capture microscopy (LCM).
Researchers reported copy number variants ranging in size from 3 to 340 kb; however,
none were found to be significant. Loss of heterozygosity was also examined in this
study and reported to be of no significance.
Despite the fact that numerous studies have employed CGH technology to
investigate chromosomal changes in the DNA from endometriosis patients, the findings
thus far are unclear. The platforms used to this point identify copy number variants of a
range of sizes and are set to discard any chromosomal changes less than 200,000 base
pairs. For these reasons, it is difficult to compare the results of these studies as the
resolutions are inconsistent and potentially significant small changes such as
microadditions and microdeletions were not considered.
31
Loss of Heterozygosity
Each gene is coded for by 2 alleles at a specific chromosomal location. Loss of heterozygosity (LOH) refers to a genetic alteration in which one allele for a gene is inactivated or deleted leaving only one functional allele. When a mutation occurs in the remaining allele, the gene is rendered inactive or, in some cases, the remaining allele is duplicated resulting in 2 copies of the dysfunctional allele. In cases of uniparental disomy, 2 copies of a chromosome or a portion of a chromosome are inherited from one parent resulting in 2 identical alleles. Each of these cases results in a homozygous situation or areas of LOH. Large regions of LOH have been related to the development of various types of cancer due largely to the loss of function of tumor suppressor genes
in affected regions. Many studies have been performed to investigate the presence of
loss of heterozygosity in the blood and ectopic tissue of endometriosis patients, and
they are summarized below in Table 2.
32
Table 2 Studies involving loss of heterozygosity and endometriosis
Group Date DNA source: Isolation method Areas of interest Wang et al. 2012 Ectopic tissue- fresh tissue: LCM, MCM 9p21.3, 17q21.31 Xu et al. 2011 Ectopic tissue- paraffin embedded: MCM 9p, 10q, 13p Ali-Fehmi et al. 2006 Ectopic tissue , paraffin embedded: LCM 10q23.3 Prowse et al. 2006 Ectopic tissue- paraffin embedded: LCM 5q11.2, 6p24.3, 13q31, 17q22 Prowse et al. 2005 Ectopic tissue- formalin fixed: LCM 8p22 Bischoff et al. 2002 Ectopic tissue-fresh, paraffin-embedded, Peripheral 17q blood Goumenou et al. 2001 Ectopic/eutopic tissue- paraffin embedded: LCM 9p21 Nakayama et al. 2001 Ectopic tissue-paraffin embedded-MCM 9q22 Sato et al. 2000 Ectopic /eutopic tissue- paraffin embedded: LCM 10q23 Jiang et al. 1996 Ectopic tissue, fresh/frozen- paraffin embedded: LC M 9p, 11q, 22q
Jiang et al. evaluated 40 endometriosis samples for 15 microsatellite markers
known to be associated with various epithelial cancers 51. Cells were obtained from
either frozen or paraffin embedded samples and endometriotic glandular and stromal
cells were collected by microdissection prior to DNA extraction and PCR amplification.
Regions of loss of heterozygosity were reported in 27.5% of the samples. Chromosomal
regions 9p, 11q, and 22q were reported most often. Of particular interest was the region
of LOH on 9p21 that has been reported to be present in 50% of ovarian cancer tumors
previously.
Sato et al. examined benign endometrial cysts consistent with endometriosis as
potential precursors to endometrioid carcinomas and ovarian clear cell carcinomas by investigating loss of heterozygosity on 10q23.2 52. DNA was extracted from paraffin-
embedded tissue after LCM followed by PCR amplification. Microsatellite markers were
used for 3 sites on chromosome 10q23.3 to examine LOH in the PTEN gene as well as
regions flanking the gene. PTEN was targeted for analysis due to its known role as a
33
tumor suppressor gene that has been shown to be altered in multiple cancers. Loss of
heterozygosity was observed in 13 of 23 (57%) of the endometrial cysts. Ovarian
carcinomas and clear cell carcinomas synchronous with endometriosis were examined
and DNA from each tissue was analyzed. Ovarian carcinomas with coexisting
endometriosis displayed LOH in 3 of 5 cases while clear cell carcinomas concurrent
with endometriosis showed LOH in 3 of 7 cases in both tissues. Results of this study not
only show LOH events on 10q23.2 in regions flanking the PTEN gene in endometriosis
tissue but also in cancerous tissue associated with it.
More recently, LOH on 10q23 in endometriosis was revisited by Ali-Fehmi et al. using the same microsatellite markers as Sato’s group 53. Microscope slides of various
lesions were analyzed, and typical and atypical endometriosis cells were included for
analysis in addition to ovarian cancer cells. “Typical” endometriosis cells were defined
as having endometrial glands and stroma while “atypical” endometriosis cells were
defined as having “architectural and cytological atypia” in addition to endometrial
stroma. LOH was reported in 7 of 23 (30%) typical endometriosis cells and 3 of 12
(25%) atypical endometriosis cells compared to 8 of 20 (40%) ovarian cancer cells and
6 of 12 (50%) clear cell carcinomas. Of particular interest was the significant increase in
LOH at marker D10S608 in cancer cells versus endometriosis cells. This marker is
located in the region telomeric to the PTEN gene. This finding was not reported
previously and may be important in the transition from noncancerous to cancerous cells.
Microsatellite analysis was used by Goumenou et al. to investigate allelic
imbalance in 22 ectopic and eutopic tissue samples from patients with endometriosis 54.
DNA was obtained from microdissected paraffin-embedded samples and amplified by
34
PCR. Seventeen microsatellite markers previously reported to be associated with
ovarian neoplasms were chosen for investigation. Loss of heterozygosity was reported
in 36% of cases and most often at 9p21 in 27.3% of samples. This region is associated
with the p16Ink4 and GALT genes that have been previously associated with infertility,
ovarian dysfunction, and endometriosis and may play a role in disease establishment
and progression. Additional regions reported to show some incidence of allelic
imbalance include APOA2 and TP53 that have both been shown to occur in ovarian
cancer.
The same year, Nakayama et al. investigated the presence of LOH in 4
endometriosis tissue samples using 8 microsatellite markers in various tumor
suppressor genes 55. DNA was extracted from endometriosis cells obtained by manual capture microdissection (MCM) from formalin fixed, paraffin embedded tissue samples.
LOH was seen in only one sample in the PTCH gene, a tumor suppressor previously
reported to be altered in various cancers including basal cell carcinoma.
Due to previous reports of alterations of chromosome 17 in endometrial and
ovarian cancers and the similarities between endometriosis and cancer, Bischoff et al.
chose to examine chromosome 17 for LOH events in advanced endometriosis tissue 56.
Fresh tissue as well as archived tissue was obtained followed by DNA extraction and
PCR amplification. LOH was determined by separating alleles on a sequencing gel and
was reported to be present in 4 of 15 samples (27%). Three samples had losses at
17q22-24 and one at 17q11-12. Both regions harbor tumor suppressor genes including
BRCA1.
35
Prowse et al. investigated regions of LOH in endometriosis tissue from 17
affected patients 57. DNA was obtained from tissue blocks and LCM was used to isolate
endometriosis cells prior to extraction and PCR amplification. Twelve microsatellite
markers were chosen for analysis based on regions believed to play a role in
tumorigenesis. LOH was observed in only one sample at 8p22. The next year, the same
group expanded their study by looking for commonalities between endometriosis tissue
and endometriosis associated ovarian cancer (EAOC) using 82 microsatellite markers
spanning the autosomal chromosomes 58. Ten samples were collected from paraffin embedded endometriosis and EAOC tissue, and cells were selected for DNA extraction and PCR amplification by LCM. Twenty-two LOH events were observed in the endometriosis tissue, all of which were present in the corresponding EAOC samples indicating a possible molecular link between the 2 disease states. Alterations on
chromosomes 5q11.2, 6p24.3, 13q31, and 17q22 were reported most often.
Researchers suggested that these regions may contain tumor suppressor genes that
may play a role in the transition to cancer; however, no particular genes were identified
at the time of the study.
In an attempt to investigate the potential role of LOH in the malignant
transformation of ovarian endometriosis to ovarian cancer, Xu et al. examined the DNA
from both disease tissues 59. DNA was extracted from tissue in paraffin blocks and
manually microdissected to obtain various cell types for investigation before PCR
amplification. Thirteen microsatellite markers flanking various tumor suppressor genes
were analyzed using fluorescent-labeling techniques. Loss of heterozygosity events
were reported in 5 out of 12 ovarian endometriosis samples at locations 9p, 10q, and
36
13q. These events included regions near tumor suppressor genes p16INK4a and PTEN
that have been suggested to contribute to malignant transformation in cases of
advanced disease.
Wang et al. investigated the potential contribution of LOH in the ectopic
endometrium from 54 patients with endometriosis by looking at 15 microsatellite
markers upstream or downstream of genes that had been previously associated with
ovarian cancer 60. Cells were obtained by either LCM, MCM, or routine dissection. DNA
was extracted and amplified using restriction and circularization-aided rolling circle amplification (RCA-RCA). In samples collected by LCM, 59% showed 1 or more region of LOH, 36% showed 2 or more, and 5% showed 3 or more. Chromosomal regions showing the highest LOH frequency were 9p21.3 and 17q21.31 with 17q21.31 having the highest frequency of 24%. Both regions have been shown to be altered in multiple cancers. The region 9p21.3 contains the gene methlythioadenosine phosphorylase
(MTAP) that has been shown to be altered in endometrial cancer 61. The region
17q21.31 contains the gene ETS variant 4 (ETV4) that is altered in ovarian and prostate
cancers 62 and the ADP-ribosylation factor-like 4D (ARL4D) gene shown to be altered in
breast and ovarian cancers 63.
Chromosome 9p was identified as having regions of LOH in 50% of the studies
summarized. This area is of particular interest as it has been associated with multiple
carcinomas including ovarian cancer. Aberrations on chromosome 17 were reported in
one-third of the studies. LOH may imply that a portion of DNA has been deleted leaving
only one allele. If this is the case, study methods such as comparative genomic
hybridization may be able to detect the aberration. LOH can occur without a change in
37 copy number wherein an allele is deleted followed by the duplication of its sister allele or in cases of uniparental disomy. Study methods such as SNP arrays that are capable of recognizing balanced alterations are necessary to identify such regions. Regions of
LOH have been linked to cancer, in addition, current research suggests a correlation between endometriosis and malignancy. Examining the link between loss of heterozygosity and endometriosis may fill in the mechanistic blanks between endometriosis and its potential role in cancer.
Gene Expression Microarray
Expression microarrays employ much of the same technology as DNA microarrays except that they measure the mRNA levels of multiple genes rather than looking at the genes themselves. Various studies have been performed on endometriosis blood and tissue to investigate the up- or down-regulation of various genes in an attempt to gain a better understanding of the disease (Table 3). More of these types of studies have been performed than in any other area to date as DNA microarrays and LOH platforms are currently being optimized.
38
Table 3 Studies involving expression microarrays and endometriosis
Authors Date RNA Source Findings Chen et al. 2012 Eutopic endometrial tissue -Up-regulation of 10 genes (MAP2A) Kahn et al. 2012 Eutopic and ectopic tissue -Increasing number of down-regulated genes with advancing stages of disease -Common expression alterations in both tissues, down-regulation of genes associated with immune response, cell cycle control, and DNA repair
Sundqvist et al. 2012 Eutopic endometrial tissue from -Down-regulation of ApoE, JAM-1, disease/nondisease patients and LAMCI ectopic tissue -Genes altered related to adhesion, cell proliferation, and survival
Gentilini et al. 2011 Peripheral blood before and after -Up-regulation of 26 genes (FOS, surgical intervention RHOB) -Down-regulation of 15 genes -Genes altered related to inflammatory response Zafrakas et al. 2008 Eutopic and ectopic tissue -Up-regulation of 56 genes (immune response, tumor suppressors) -Down-regulation of 75 genes (cell cycle control and homeostasis) Eyster et al. 2007 Eutopic and ectopic tissue -717 differentially expressed genes Mettler et al. 2007 Eutopic and ectopic tissue -Up-regulation of ISLR, p450arom, HLA, SH3 -Down-regulation of KCC, COX, RPL, p43 Flores et al. 2006 Peripheral blood lymphocytes -Up-regulation of IL-2RG -Down-regulation of LOX-L1 Matsuzaki et al. 2006 Eutopic and ectopic tissue -Up-regulation of17βHSD2, COUP-TF2, HSP90A, PDGFA, Matsuzaki et al. 2005 Eutopic and ectopic tissue -Up-regulation of genes implicating RAS/RAF/MAPK pathway
It has recently been suggested that the “normal” endometrium of women with endometriosis may share genetic alterations with endometriosis tissue 35, 64, 65, 65. If this is true, the “normal” endometrium of endometriosis patients may differ from the endometrium of women without the disease. To investigate this hypothesis, Matsuzaki et al. examined the gene expression in the endometrium from 12 endometriosis patients and 12 control individuals 66. As different genes are expressed at different levels
39
depending on the stage of the menstrual cycle 67, stromal and endometrial biopsies
were obtained from women during the late proliferative, and early, mid, and late
secretory stages of the menstrual cycle. Of 1,176 genes investigated, none were found
to be differentially expressed in both sets of tissues during all stages; however, several
genes were found to be up-regulated in the epithelial cells in the late secretory phase of
the menstrual cycle of women with the disease. The results implicated molecular
pathways that may contribute to the disease state including the RAS/RAF/MAPK
pathway that is involved in antiapoptotic activity within the cell.
In 2006, the same group used similar methodology to investigate the expression
levels of 12 genes in ovarian endometriosis that had been found to be aberrantly
expressed in deep infiltrating endometriosis 68. It has been suggested that different
forms of endometriosis may represent different disease entities, so comparing the
profiles between types of endometriosis may provide valuable information into the
intricacies of the disease. Twelve patients were included, half of which were in the
proliferative and half in the secretory phase of the menstrual cycle. Multiple similarities
were found between deep infiltrating endometriosis and ovarian endometriosis when
compared to “normal” endometrium. Increases in both platelet-derived growth factor receptor alpha (PDGFA) and heat-shock protein 90 alpha (HSP90A) in both ectopic tissues might make them attractive targets for future therapies. Differences between the tissues included an increase in nuclear receptor superfamily 2 (COUP-TF2) and 17β- hydroxysteroid dehydrogenase type-2 (17βHSD2) both of which contribute to suppressing estrogen production. These observations may indicate that estrogen levels
40 in ovarian endometriosis are lower than those observed in deep infiltrating endometriosis possibly indicating different disease mechanisms.
In an attempt find molecular markers for diagnostic testing of endometriosis,
Flores et al. investigated differences in gene expression in the peripheral blood from 6 endometriosis patients with various stages of disease and compared them to the peripheral blood from 5 control individuals 69. Of approximately 15,000 genes examined,
2 genes were shown to be differentially expressed at a significant level. Common gamma chain (IL-2RG), which is involved in the initiation of immune response, was up- regulated. This finding had been shown previously in animal models of endometriosis and may indicate an elevated immune response in endometriosis patients. Lysyl oxidase-like 1 (LOXL1), which is involved in collagen metabolism, was down-regulated.
As LOXL1 is a tumor-suppressor gene, its decrease in endometriosis may contribute to uncontrolled cellular growth and tumor formation that are associated with the disease.
Mettler et al. studied the expression profiles of both eutopic and ectopic endometrium samples from women during the proliferative phase of the menstrual cycle
70. Of 1,176 genes, 9 were up-regulated and 4 were down-regulated in ectopic tissue.
Up-regulated genes that were suspected to contribute to disease include immunoglobulin superfamily containing leucine-rich repeat (ISLR) that is involved in cell adhesion, aromatase p450 (p450-AROM) that aids in the synthesis of estrogen, major histocompatibility antigen class I (HLA) that is involved in immune response, and src homology 3 (SH3) which plays a role in folliculogenesis and development. Down- regulated genes of importance included K-Cl cotransporter that has been linked to reproductive function as well as cytochrome c oxidase (COX), ribosomal protein L
41
(RPL35), and tRNA synthetase complex-interacting multifunctional protein-1 (p43) whose functions in endometriosis are currently unknown.
Later the same year, Eyster et al. expanded on the expression profiles previously done by examining 53,000 mRNA products in eutopic and ectopic endometrial tissue from 11 patients with endometriosis 71. Nine of the women were in the proliferative phase when biopsies were collected, one was in early secretory phase, and one had an inactive endometrium due to drug treatment. Seven-hundred seventeen genes were shown to be differentially expressed in endometriosis tissue when compared to corresponding “normal” endometrium. Of the genes reported, many were involved in processes that were thought to contribute to the establishment and progression of endometriosis. The most dramatic changes were seen in phospholipase A2 group IIA
(PLAII2) that was increased by 153-fold, claudin 11 (CLDN11) that was increased by
32-fold, haptoglobin (Hp) that was increased by 29-fold, and prostacyclin synthase
(PGS) that was increased by 27-fold. Genes involved in immune and inflammatory response, cell adhesion, cytoskeletal organization, extracellular matrix remodeling, signal transduction, and embryonic development were all reported to be expressed at aberrant levels in ectopic endometrium.
Investigating the molecular similarities between endometriosis and cancer,
Zafrakas et al. examined 10 tissues from endometriosis patients with moderate to severe stages of disease in the proliferative phase of the menstrual cycle and compared them to eutopic endometrium biopsies from the same patients 37. The platform used covered over 40,000 genes and identified 56 up-regulated genes involved mainly in immune response and in tumor suppressor genes as well as 75 down-regulated genes
42
involved in cell cycle control and homeostasis. These results suggest that endometriosis
may not be a precursor to cancer as previously suggested 72.
Chen et al. used cDNA representational difference analysis (cDNA-RDA) to
examine the gene expression in endometrial tissue samples from 40 women with
endometriosis and 40 “control” women with no gynecological issues. This technique had not been previously used in this area of research 73. All samples were collected during the secretory phase of the menstrual cycle. Ten genes were reported to be up- regulated, 4 of which have been reported previously. Genes associated with adhesion, cell growth, and apoptosis were reported to have altered expression with the most significant change in methionine adenosyltransferase II, alpha (MAT2A). Up-regulation
of MAT2A has been associated with various cancers and is of great interest as
endometriosis has many malignant characteristics.
Investigating the gene expression profile before and after surgical intervention for
endometriosis, Gentilini et al. used a microarray platform with 17, 665 probes spanning
the genome 74. Four patients with severe endometriosis were included and 41 genes
were identified as being differentially expressed including 26 up-regulated genes and 15
down-regulated genes. Of interest was the up-regulation of FBJ murine osteosarcoma
viral oncogene homolog (FOS) that functions as an oncogene and transcriptional
regulator and ras homolog family member b (RHOB) that functions as a transcriptional
regulator and mediator of apoptosis. Other genes associated with inflammatory
response were shown to be altered supporting the theory that endometriosis is an
inflammatory-associated disease. This study was the first of its kind that indicates
surgical treatment may alter gene expression associated with disease.
43
Fassbender et al. combined proteomics and expression array analysis to
examine gene expression in eutopic and ectopic endometrial tissue samples from 31
women with endometriosis and eutopic endometrial tissue from 18 control individuals 75.
Women in both menstrual and the early and late luteal phases of the cycle were included. No changes in expression were reported in the eutopic endometrium from either group between cycle phases. There were significant changes in the expression of
683 genes in the endometriosis tissue in the menstrual phase compared to the early
secretory phase of controls, whereas 242 genes were expressed differentially between
phases in endometriosis tissue. Several important pathways were identified as being
potentially altered including those involved in extracellular matrix remodeling,
coagulation, and cell renewal. Of particular interest was the decrease in fibrinogen beta
chain identified in endometriosis patients, although its potential role in the disease
process is unclear.
Khan et al. investigated the difference in gene expression in fertile Indian women
with various stages of endometriosis in both the proliferative and secretory stages of the
cycle 65. Eutopic and ectopic tissue samples were obtained from 18 women with ovarian
endometriosis and analyzed with an expression array covering 44,000 gene products.
They reported an increase in the number of down-regulated genes as disease stage
became more advanced. In addition, a large number of genes were silenced in ectopic
tissue from stage 4 endometriosis when compared to ectopic tissue from stage 3
endometriosis. Genes involved in steroidogenesis were shown to be upregulated in
ectopic tissue samples. A portion of genes demonstrated to be involved in immune
response were shown to be expressed differentially in both eutopic and ectopic
44
endometrial tissue samples. In addition, differential expression of erb-b2 erythroblastic leukemia viral oncogene homolog 3 (ERBB3) and progesterone receptor (PGR) in both tissues was noted. These results suggest that both the eutopic and ectopic endometrium of women with endometriosis may harbor similar genetic alterations, thus if the eutopic endometrium from an individual with endometriosis is misplaced by way of retrograde menstruation or other means, it may have the potential to form endometriosis.
In an attempt to gain a more clear understanding of the disease mechanisms involved in endometriosis, Sundqvist et al. examined the mRNA levels of 6 genes
thought to be vital to disease progression 76. Eutopic endometrium from control
individuals and from endometriosis patients and endometriomal biopsies were obtained
from women in the proliferative and secretory phases of the menstrual cycle.
Expression of ApoE, ITGB2, ITGB7, LAMC1, CD24, and JAM-1 were investigated in
each sample. ApoE and JAM-1 were found to be down-regulated in endometrium of
endometriosis patients in both phases examined while LAMC1 was down-regulated in
the proliferative phase only. ApoE has been shown to be involved in cell proliferation
and lesion survival. CD24 was expressed differentially between the endometrium of
endometriosis patients and endometriomas, as was ITGB2 in the endometrium of
controls versus endometriosis patients in the secretory phase. Altered expression of
these genes may affect cellular processes involved in the development of endometriosis
including cellular adhesion and migration, lesion formation and survival, and immune
response. Additionally, aberrant expression of ApoE, CD24, and JAM1 has been
reported previously in ovarian and endometrial cancer.
45
While these studies can be informative, results can be difficult to interpret as the endometrium and endometriosis tissue are constantly proliferating and genes are expressed differentially depending on what stage of menstrual cycle the patient is in at the time of biopsy. Patient selection, sample size, controls, histological versus visual confirmation of disease tissue, sample type, and array bias are just a few of the factors that may explain the inconsistencies observed in the studies summarized. It should be noted that many of the genes reported to be aberrantly expressed in endometriosis have previously been shown to be differentially expressed in various cancers including ovarian cancer. In addition, mRNA levels of genes involved in many processes thought to be vital to the development and progression of endometriosis were shown to be expressed differentially in disease patients including those involved in immune response, cell cycle control, inflammation, DNA repair, cellular adhesion and attachment, cell proliferation and survival, and tumor suppression.
Summary
Many studies have been done to attempt to identify genes involved in the pathogenesis of endometriosis. As our knowledge on the genetics of the disease expands, the biological mechanisms will become more apparent. The literature thus far supports the hypothesis of a genetic component to the disease and also suggests a link to cancer as most implicate the loss of tumor suppressor genes or alterations in genes known to be associated with various cancers. This correlation to malignancy may be clinically important as endometriosis is thought to be a benign disease despite the fact that research may imply it to be a precursor to cancer.
46
CHAPTER 3
PROJECT SUMMARY
Significance of Research
The Endometriosis Association estimates that 5.5 million women and girls in
North America alone suffer from endometriosis, although the exact number is difficult to calculate as some women are asymptomatic or fail to seek medical treatment. The reality is that the actual number of those with the disease may be much higher. Little has been established regarding the pathophysiology of endometriosis. The lack of findings in this area may be due to small numbers of participants, to the novelty of the technology, to high cost of methods, or to a combination of these factors. An attempt at the initiation of an endometriosis cell line to be submitted to the NIH repository will be made in order to facilitate future research endeavors. This is a vital part in furthering research as there are currently no cell lines of this kind available in the United States.
As this is a unique area of research, negative findings would also be valuable as ruling out chromosomal aberrations would allow investigators to eliminate this as a probable cause and look into other potentially productive areas. By using a variety of tests and keeping in mind existing research, we are hoping to find a definitive answer to whether or not chromosomal imbalances are involved in the development or progression of endometriosis. A finding in this area would provide insight into the disease mechanism and may aid in the development of future treatments and diagnostic tools.
47
Research Goals
• Collect and analyze 20 blood samples from endometriosis patients using the
105K oligo-CGH platform.
• Collect and analyze 10 endometriosis tissue samples using the 105K oligo-CGH
platform.
• Analyze 10 samples for regions of loss of heterozygosity using the 180K oligo-
CGH microarray platform.
• Initiate endometriosis cell lines and submit to a repository for use in future
research.
• Send samples for targeted sequencing to confirm copy number variants.
Statement of Research
The goal of this research is to determine if common chromosomal aberrations in the form of additions, deletions, or regions of loss of heterozygosity are present in a population of endometriosis patients that may contribute to the establishment or progression of the disease.
48
CHAPTER 4
MATERIALS AND METHODS
Patient Selection and Control Individuals
Approval for this study was obtained from the Institutional Review Board of East
Tennessee State University (IRB#0311.4s, IRB#0511.3) as well as the Mountain States
Health Alliance Research Department (MSHA Protocol # 2011-027NB). Informed consent was given by each of the participants prior to the study. For the portion of the study in which blood samples were drawn for microarray analysis, all patients diagnosed with endometriosis by the attending physician were eligible for participation regardless of age or stage of disease. Control participants were eligible for participation if they were over the age of 30 with no history of endometriosis, no family history of endometriosis, and no history of infertility as evidenced by having 2 or more children.
One individual, age 24, did not meet all of the criteria but was included as she had undergone multiple examinations without diagnosis of the disease. Even with these criteria, any of the control individuals could potentially have endometriosis because, as stated, many women are asymptomatic. For the portion of the study in which tissue biopsies were collected for microarray analysis, all patients diagnosed with endometriosis by laparoscopy were eligible for participation regardless of age or stage of disease. Only biopsies that were confirmed positive for endometriosis by Dr. Norman
Assad and Watauga Pathology, Board Certified Pathologists were analyzed and included in the study.
49
Participant Privacy
Researchers had no immediate access to patient records. Each patient sample was assigned a numerical label at the clinic at the time of collection, and the sample was stripped of all patient identifiers. In the event a patient needed to be contacted in regards to a sample, the attending physician was notified and given the associated numerical label and was able to identify the patient. Informed consent forms were kept in a locked cabinet at the participating clinic. All patient results were saved with numerical labels on a study database at East Tennessee State University in Stanton
Gerber Hall, Lab 124A. This database was password protected and the lab was locked any time study personnel were not present.
Sample Collection
Whole blood was collected from patients with visually confirmed endometriosis of various stages of severity by laparoscopic examination at the participating clinic.
Approximately 5 mL of blood was obtained by venipuncture and stored in a sodium heparin tube at 4° until DNA extraction. The endometriosis patients ranged in age from
24 to 44 years with a mean age of 32.4±5.5. The age of control individuals ranged from
24 to 64 years with a mean age of 46.9±12.9.
Tissue samples were collected from endometriosis patients who were undergoing laparoscopic surgery for treatment of the disease. Biopsies were placed in a sterile container by the physician with approximately 20 mL of Hank’s Balanced Salt
Solution (Life Technologies) at 4° until they were to be processed. Samples were
50 included in the study after they were confirmed positive for endometriosis by visual inspection by the operating physician and by histological examination from Watauga
Pathology, Board Certified Pathologists. Controls for the tissue samples consisted of blood matches from the same patient which allowed investigators to compare the tissues and look for variation between them.
Microarray Preparation and Analysis
The summary of the microarray workflow is depicted in Figure 7.
Figure 7 Microarray Workflow: Peripheral blood or tissue samples are obtained from the participating clinic. DNA is extracted from the sample followed by DNA purification. A restriction enzyme digest is performed, and fragment size is checked using the Agilent Bioanalyzer. DNA samples are fluorescently labeled and hybridized to microarray slides. The slides are scanned and analyzed using BlueFuse software.
51
DNA Extraction from Peripheral Blood
Genomic DNA was extracted from 200 µ whole blood with the QIAamp DNA
Blood Mini Kit (Qiagen). Proteinase K (20µ, 45 mAU/mg protein) was added to whole
blood in a 1.5 mL tube followed by RNase A (4µ, 100mg/ml). Samples were vortexed
briefly, centrifuged, and allowed to incubate for 2 minutes at room temperature. Lysis
Buffer was added (200µ) and samples were vortexed for 15 seconds, centrifuged, and
incubated for 10 minutes at 56°C. Ethanol was added (200µ, 96%-100%) and samples
were vortexed for 15 seconds, centrifuged, and added to a QIAamp Mini spin column.
Samples were centrifuged for 1 minute at 8,000 rpm. Columns were washed with a
series of wash buffers and dried by centrifugation for 1 minute at 14,000 rpm. Tris-
EDTA (200µ, Fluka) was applied to the column and allowed to incubate at room
temperature for 5 minutes. DNA was eluted by centrifuging columns for 1 minute at
8,000. DNA purity and concentration was measured using the Nanodrop 2000
Spectrophotometer (Thermo Fisher Scientific).
DNA Extraction from Tissue Biopsy
Genomic DNA was extracted from approximately 25mg of endometriosis tissue
with the QIAamp DNA Mini Kit (Qiagen). Each biopsy was removed from its sterile
container and put in a 35x10mm petri dish with Tissue Lysis Buffer (180µ). Biopsies
were photographed (Figure 8) and minced using sterile instruments prior to DNA
extraction. The mixture was added to a 1.5 mL tube with Proteinase K (20µ) and
incubated for up to 24 hours at 56°C to allow lysis to occur, vortexing often. RNase A
52
(20µ, 100mg/ml) was added and allowed to incubate for 2 minutes at room temperature.
Samples were vortexed briefly, centrifuged, and allowed to sit for 2 minutes at room temperature. Lysis Buffer was added (200µ) and samples were vortexed for 15 seconds, centrifuged, and incubated for 10 minutes at 56°C. Ethanol was added (200µ,
96-100%) and samples were vortexed for 15 seconds, centrifuged, and added to a
QIAamp Mini spin column. Samples were centrifuged for 1 minute at 8,000 rpm.
Columns were washed with a series of wash buffers and dried by centrifugation for 1 minute at 14,000 rpm. Tris-EDTA (200µ, Fluka) was applied to the column and allowed to incubate at room temperature for 5 minutes. DNA was eluted by centrifuging columns for 1 minute at 8,000 rpm. DNA purity and concentration was measured using the
Nanodrop 2000 Spectrophotometer (Thermo Fisher Scientific)
Figure 8 Endometriosis tissue biopsies: Biopsy size and appearance varied depending on location, severity of disease, and stage of the menstrual cycle in which they were collected. Typical indications of necrotic tissue were noted as bubbles or blebbing under 10x magnification in type II and type III biopsies (A) Type I biopsy: Unpigmented tissue generally has a smooth appearance and is associated with early stages of disease and/or menstrual cycle stage and contain mainly living cells (B, C)Type I biopsy under 10x magnification. Tissue appears to be made up of living cells with no necrotic blebbing (D) Type II biopsy: Unpigmented biopsy with dark, pigmented regions generally has a smooth appearance with necrotic blebbing. This type of biopsy is associated with moderate stages of disease and/or menstrual cycle stage and contains a mixture of living cells and necrotic cells (E,F) Type II biopsy under 10x magnification. Tissue appears to be composed of a mixture of living cells and necrotic bubbles (G) Type III biopsy: Dark pink to red in color with hemosiderin deposits throughout with a necrotic appearance and generally associated with moderate to late stages of disease and/or menstrual cycle stage containing mainly necrotic cells (H, I) Type III biopsy under 10x magnification. Tissue appears to be composed of mainly necrotic bubbles
53
Figure 8 continued
A. B. C.
D. E. F.
G. H. I.
DNA Purification
DNA was purified with the Wizard Clean-up Kit (Promega). DNA in approximately
200µ of Tris-EDTA (Fluka) was added to DNA Clean-Up Resin (1 mL) and mixed by
54 inversion. A minicolumn was attached to a syringe barrel and the mixture was applied. A vacuum was applied to draw the solution through the minicolumn where the DNA remained bound. The vacuum was broken. Isopropanol (2 mL, 80%) was added to each sample and drawn through the minicolumn into a reservoir where it was discarded after an additional 20 seconds of drying. The minicolumn was centrifuged at 14,000 rpm for 2 minutes to prevent carryover of isopropanol. Prewarmed Tris-EDTA (50µ, 65-70°C) was added to the column and allowed to incubate at room temperature for 1 minute before elution by centrifugation for 30 seconds at 14,000 rpm. DNA purity and concentration was measured using the Nanodrop 2000 Spectrophotometer.
DNA Digestion
Normal female control DNA was purchased from Promega (Madison, Wisconsin).
A concentration of approximately 0.075 ug/ul of each DNA sample was obtained, and a restriction digestion was performed on each by adding endonucleases Alu I (10U/ul) and Rsa I (10U/µ) (Promega) to purified DNA and acetylated bovine serum albumin
(10mg/ml, Promega). The restriction enzyme recognition sites are provided below.
Alu I: Rsa I: 5’…AG^CT…3’ 5’…GT^AC…3’ 3’…TC^GA…5’ 3’…CA^TG…5’
The mixture was incubated at 37°C for 2 hours followed by incubation at 65°C for 10 minutes. Successful digestion was assessed using the Agilent 2100 Bioanalyzer
(Agilent Technologies-Santa Clara, California). A gel matrix containing DMSO was
55 prepared by adding 15µ of fluorescent dye to the gel. The mixture was added to a spin column and spun at 6,000 rpm for 10 minutes and stored protected from light at 4°C. A
DNA1000 chip (Agilent Technologies) was placed on a priming station and 9µ of gel matrix was added to the appropriate well. The chip was pressurized and the gel matrix was spread by depressing the plunger on the priming station for 60 seconds before releasing. A DNA ladder (Agilent Technologies) was added to the appropriate well.
Upper and lower markers, 1,500 and 15 base pairs in length were added to each well followed by 1µ of each sample to be analyzed. The loaded chip was vortexed at 2,400 rpm for 60 seconds, placed in the Agilent Bioanalyzer, and analyzed using 2100 Expert software (Agilent Technologies). A successful digestion was evident when the majority of fragments were between 200 and 600 base pairs in length (Figure 9). As each lane was read, information was provided as to the concentration and size of DNA fragments detected.
Figure 9 Agilent Bioanalyzer Output: Successful digestion is indicated by a smear pattern (lanes 1-4) as well as clean “blank” lanes (lane 5).
56
Enzymatic Labeling
Sample DNA and control DNA were labeled with Cy3 and Cy5 fluorophores
(dUTP/oligo, Bluegnome, Cambridge, UK). Random primers were added to each
sample, and all were incubated at 95°C for 5 minutes followed by incubation at 4°C for 5
minutes. Klenow fragment of DNA Polymerase I and 10xdNTP were added followed by dUTP-Cy3 to the sample DNA and dUTP-Cy5 to the control DNA. Samples were transferred to a thermocycler and incubated at 37°C for 2 hours followed by incubation at 65°C for 10 minutes. Excess label was removed from each sample by washing with
Tris-EDTA buffer solution (pH 7.4, Sigma) and filtering using Amicon Ultracel-30K membrane filters (EMD Millipore). DNA yield, purity, and dye incorporation were
measured for each sample using the Nanodrop 2000 Spectrophotometer (Thermo
Fisher Scientific- Waltham, Massachusetts). Each patient sample was combined with its
corresponding control and stored protected from light at 4°C until further processing.
Microarray Hybridization and Data Analysis
Hi-RPM-2x hybridization buffer and blocking agents including human COT DNA
(1.0 mg/ml, Invitrogen) were added to the labeled DNA to minimize the binding of
repetitive sequences. The solution was incubated at 95°C for 3 minutes followed by
incubation at 37°C for 30 minutes then cooled to room temperature. The solution was
dispensed onto a gasket slide and microarray slides (CytoChip Oligo 2x105K or
Cytochip SNP 4X180K: Bluegnome) were placed. Slides were incubated in hybridization
chambers at 65°C for 24 (Cytochip Oligo 4x180K) or 40 hours (Cytochip 2x105K). The
57 hybridization chambers were disassembled in Agilent Oligo aCGH/ChIP-on-Chip Wash buffer 1 (Agilent Technologies) and washed for 5 minutes. The slides were transferred to a 37°C bath of Agilent Oligo aCGH/ChIP-on Chip Wash buffer 2 (Agilent
Technologies) for 1 minute and then allowed to air dry.
Microarray slides were scanned using a GenePix 4000B scanner (Molecular
Devices) and an image was created using GenePix software (Figure 10). The images were analyzed with BlueFuse Multi software (Bluegnome) and information on any copy number variants was provided including size, location, possible affected genes, known pathogenesis, and relevant publications (Figures 11 and 12). Each copy number variant
(CNV) was investigated further using the Ensembl, Online Mendelian Inheritance in Man
(OMIM), and UCSC Genome Bioinformatics browsers.
Two microarray platforms were used in this study. The Cytochip 2x105K platform includes105,000 probes while the Cytochip SNP 4x180K platform includes 180,000 probes spanning the genome at approximately every 30,000 base pairs but at higher densities in disease prone regions. Both platforms identify copy number variants, however, the Cytochip SNP 4x180K platform has an additional 27,000 probes for single nucleotide polymorphisms which allow for the identification of regions of LOH. The
BlueFuse Multi software is designed with an algorithm that recognizes variations in hybridization by identifying differences in fluorescence between the patient and the control DNA and flagging those that are within array parameters set by the user. Array parameters for the current study were set to zero base pairs so as not to eliminate any additions or deletions based on size allowing for the most detailed analysis possible. An example of the output for a patient with trisomy X is shown below (Figures 13 and 14)
58 and has been flagged as such. The Database of Genomic Variants 77 was used to eliminate any known copy number variants from the results.
Figure 10 GenePix 4000B Scanner Raw Image: Equal hybridization of both patient and control DNA indicated by yellow spots while control spots with no hybridization of DNA are indicated by blank spots A. Cytochip Oligo 2x105K scan B. Cytochip SNP 4x180K scan C. Increased hybridization of patient DNA representative of a gain indicated by green spot and green arrow D. Decreased hybridization of patient DNA representative of a deletion indicated by a red spot and red arrow.
A. B. C. D.
59
Figure 11 BlueFuse Multi Software Output, CGH View: Copy number variants are identified and information regarding known pathogenicity, size, and location is provided.
Figure 12 BlueFuse Multi Software Output, Decision Tracks View: Trisomy X is indicated by the flagging of the X chromosome in green in the “Current” output. Information is provided on previous publications including the area of interest. Genes located in the region are listed as well as diseases previously reported to be associated with the loss or gain of the gene. Available probes for FISH studies are also listed for follow-up confirmation.
60
Figure 13 BlueFuse Multi Software Output, Karyotype View: Additions are flagged in green to the right of the chromosome (chromosome 15, 17, X and Y) and deletions are flagged in red to the left of the chromosome (chromosome 10). The presence of an extra X chromosome, trisomy X (47, XXX) is indicated. The Y chromosome shows a gain which is the result of homologous DNA sequences on the X and Y chromosomes. This observation is a common occurance in nearly all samples analyzed.
Figure 14 BlueFuse Multi Software Output, Chromosome View: (A) A normal female (46, XX) indicated by the majority of probes for the X chromosome inside the standard deviation limits indicated by the left red line and the right green line. (B) A trisomy X female (47, XXX) indicated by the majority of probes being skewed to the right, outside of the standard deviation limits.
A. B.
61
Cell Line Preparation
Cell Culture
Tissue biopsies were obtained as previously described and placed in a sterile container with approximately 20ml of Hank’s Balanced Salt Solution (Life Technologies).
Biopsies were stored at 4°C until cultures were set up. Aseptic technique was used in all aspects of cell culture preparation. Amniomax media (8ml: Gibco, Life Technologies) was added to the appropriate number of culture flasks based on biopsy size and number. Biopsies were placed in 35x10mm petri dishes, diced, suspended in culture media (4ml, Amniomax-II Complete: Life Technologies), and divided into the appropriate number of culture flasks. Flasks were incubated at 37°C, 7.5% CO2, and 75% humidity until the cultures reached approximately 75% confluency at which time cells were either subcultured, harvested, or cryopreserved.
Cell Subculture
Culture media from each flask was poured off and discarded. To remove any serum present in the culture and to aid in releasing cells trypsin was added (4ml, 0.05%
Trypsin EDTA (1X): Life Technologies) and was immediately poured off. Three additional milliliters of trypsin was added and the flasks were incubated for 4 minutes at
37°C. Cultures were observed under magnification to ensure the majority of cells were released from the flask. Culture media (12ml, Amniomax-II Complete: Life
Technologies) was added, and cells were suspended by pipetting. The mixture was removed from the original flask and divided into the appropriate number of new sterile
62
flasks. Additional culture media was added to each flask to bring the volume to
approximately 10ml. Cultures were returned to the incubator with the temperature
maintained at 37°C.
Cell Line Cryopreservation
Cells were released from the culture flask using trypsin as described above. The
suspended cells were dispensed into 15ml conical tubes and pelleted by centrifugation
for 4 minutes at 1000 rpm. The supernatant was discarded, and freezing media (1ml,
Cell Freezing Medium –DMSO (1X): Sigma Aldrich) was added to each cell pellet
dropwise and mixed by pipetting. Cells were aliquoted into cryopreservation vials and
placed in a freezing container at -80°C for approximately 24 hours where cells were
cooled by 1°C per minute. Vials were then transferred to liquid nitrogen for long-term storage.
Cell Harvest
When cells reached approximately 75% confluency, colcemid (0.2ml, Karyomax:
Life Technologies) was added to each culture flask and incubated for 3-4 hours at 37°C.
Culture media was poured off into 15ml conical tubes. Trypsin was added (4ml) and
immediately poured off followed by the addition of 3ml of trypsin. Flasks were incubated
for 4 minutes at 37°C. Each culture was checked under magnification for the release of
the cells from the flask. Hank’s Balanced Salt Solution (12ml: Life Technologies) was
63 added to each culture and the cell mixture was poured into a 15ml conical tube. After centrifugation for 4 minutes at 1000 rpm, the supernatant was removed leaving a cell pellet. After vortexing briefly, the cells were incubated in a hypotonic solution (10 ml:
NaCl) for 15 minutes at room temperature. The cells were centrifuged for 4 minutes at
1000 rpm, the supernatant was removed, and the pellet was vortexed briefly. The cells were then washed in a fixative solution (10ml, 75% methanol, 25% glacial acetic acid) and centrifuged for 4 minutes at 1000 rpm. Washing was repeated 3-4 times. The cells were then stored in fixative solution at room temperature until use.
Karyotype Analysis
Slide Preparation
Harvested cells the tubes were centrifuged for 4 minutes at 1000 rpm, and the supernatant was removed. Fresh fixative solution (0.25-0.5 ml) was added to each pellet, and the pellet was disrupted with the tip of a glass pipet. Cells were aspirated and dropped onto slides wetted in chilled, distilled water. Slides were dried on a damp paper towel on a slide warmer and then baked in an 85-90°C oven for 2-24 hours before staining.
64
Slide Staining
A series of coplin jars were prepared containing the following:
1. 50ml 0.9% NaCl+2.5ml Trypsin (Life Technolgies)
2. 50ml 0.9% NaCl
3. 50ml 0.9% NaCl
4. 49ml Gurr’s buffer + 3ml Giemsa stain (KaryoMax, Life Technologies) + 1ml
Acetone
5. 50ml Gurr’s buffer
6. 50ml Gurr’s buffer
Slides were dipped briefly in jars 1, 2, and 3 and in jar 4 for 2-4 minutes. Slides were rinsed through jars 5 and 6 for several seconds and allowed to dry on a slide warmer before viewing with oil immersion microscopy.
Karyotyping
Chromosome spreads were visualized and ideal spreads with clear banding and few overlaps were photographed (Figure 15). Images were manipulated in Adobe
Photoshop and printed for karyotyping. Each chromosome was cut out and positioned according to size and banding pattern on a karyotype sheet (Figure 16).
65
Figure 15 Ideal chromosome spread
66
Figure 16 Complete Karyotype
67
CHAPTER 5
RESULTS
CGH Microarray: 105K Platform
Peripheral Blood Samples
Genomic DNA from the peripheral blood of 32 endometriosis patients and 20
control individuals was analyzed by oligo-comparative genomic hybridization for
chromosomal imbalances. All patients included in the study were confirmed as having
the disease by laparoscopy performed by Dr. Norman Assad. Array data were analyzed
using BlueFuse Multi software. The array parameters were set with no minimum
deletion or addition size so as not to eliminate any copy number variants on the basis of
size alone. All CNVs reported were initially considered as potential pathogenic markers
and were entered into a spreadsheet to track any recurring CNVs in each group. The
Database for Genomic Variants 77 was used to eliminate common polymorphisms. After
common polymorphisms were eliminated, CNVs that appeared at a higher frequency in
the patient group than the control group were analyzed for their potential to contributing
to the pathogenesis of endometriosis.
Copy number variants of various sizes and in multiple locations were detected in
30 of 32 endometriosis patients and in 18 of 20 control individuals. A total of 125
different copy number variants were reported including 63 losses and 62 additions.
Losses were detected on all chromosomes except for chromosome 13. Gains were detected on all chromosomes except for chromosomes 18, 20, and 21. The mean
number of copy number variants detected in the DNA from endometriosis patients was
68
5.6±3.2 and a range from 0 to 12. The mean number of additions was 3.0 and the mean number of deletions was 2.6. Control individuals had a mean of 6.7±3.8 with a range from 0 to 14. The mean number of additions detected was 3.3 and the mean number of deletions was 3.4. This information is summarized in Table 4.
Table 4 Copy number variant results from peripheral blood samples Endometriosis Patients Controls Minimum/Maximum CNVs 0/12 0/14 Mean number of gains 3.0 3.3 Mean number of losses 2.6 3.4 Mean of total CNVs 5.6 6.7
Chromosome 17p13.3 Addition in Peripheral Bloods: HIC-1
Analysis of the microarray data indicated the presence of one potentially significant addition on chromosome 17. This addition was the only copy number variant reported at a higher frequency in the patient group than the control group. The addition ranged in size from 39 to 624 base pairs on 17p13.3 in 75% of endometriosis patients but only 50% of control individuals. The additions had varying start positions depending on the CNV size, but all had the same end position at 17:1,959,650. The addition is located in the hypermethylated in cancer-1 gene (HIC-1). The microarray data from the blood samples are shown below in Tables 5 and 6.
69
Table 5 Microarray results (105K) of DNA isolated from the peripheral blood from endometriosis patients.
Peripheral Blood Samples from Endometriosis Patients: 105K Platform Patient Age Disease Stage Number of CNVs Additions Deletions 17p Addition? Addition Size ID (base pairs) 1005 35 I-II 8 3 5 No 0 1008 26 I-II 2 2 0 Yes 57 1009 38 III-IV 4 2 2 Yes 77 1010 35 III-IV 6 1 5 No 0 1011 44 I-II 8 4 4 Yes 39 1012 30 III-IV 5 3 2 Yes 77 1013 32 I-II 1 0 1 No 0 1015 35 III-IV 5 3 2 Yes 77 1016 34 III-IV 12 1 11 Yes 77 1017 25 I-II 8 5 3 Yes 39 1018 33 I-II 11 9 2 Yes 77 1019 44 III-IV 9 7 2 Yes 121 1020 34 I-II 11 5 6 Yes 121 1021 30 I-II 5 4 1 Yes 121 1022 33 III-IV 8 3 5 Yes 77 1023 28 Unspecified 5 2 3 Yes 39 1026 33 Unspecified 7 4 3 Yes 121 1028 34 Unspecified 8 4 4 Yes 77 1029 31 III-IV 0 0 0 No 0 1030 28 I-II 5 4 1 Yes 77 1031 24 I-II 8 3 5 Yes 121 1033 32 I-II 5 1 4 yes 39 1034 27 I-II 3 2 1 No 0 1036 44 I-II 0 0 0 No 0 1039 24 I-II 1 1 0 Yes 624 1050 31 I-II 5 1 4 No 0 1051 29 I-II 3 3 0 Yes 77 1056 37 I-II 3 2 1 No 0 1059 27 III-IV 9 4 5 Yes 39 1060 28 I-II 3 3 0 Yes 77 1063 31 I-II 4 3 1 Yes 77 1064 40 I-II 8 8 0 Yes 77
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Table 6 Microarray results (105K) of DNA isolated from the peripheral blood from control individuals
Peripheral Blood Samples from Control Individuals: 105K Platform Patient ID Age Number of Additions Deletions 17p Addition? Addition Size CNVs (base pairs) 0001 24 1 1 0 No 0 0003 64 5 3 2 Yes 39 0004 50 9 6 9 Yes 39 0005 57 6 3 3 No 0 0006 56 3 2 1 No 0 0007 44 6 1 5 No 0 0008 58 5 3 2 No 0 0009 30 7 3 4 No 0 0010 43 16 9 6 No 0 0011 35 5 2 3 Yes 121 0012 35 4 2 2 Yes 39 0013 31 5 4 1 Yes 77 0014 53 10 4 6 Yes 39 0015 60 2 2 0 No 0 0016 61 13 1 12 No 0 0017 64 11 8 3 Yes 39 0018 30 3 1 2 No 0 0020 36 7 3 4 Yes 77 0021 56 5 1 4 Yes 39 0022 50 10 7 3 Yes 121
Endometriosis Tissue Biopsies
Genomic DNA from endometriosis tissue biopsies from 10 endometriosis patients
was analyzed by oligo-comparative genomic hybridization microarray for chromosomal
imbalances. All patients included in this portion of the study were confirmed as having
endometriosis by Dr. Norman Assad after laparoscopic examination and by Watauga
Pathology, Board Certified Pathologists by histological examination. Copy number
variants were detected in all samples. The mean number of copy number variants
71 detected was 4.1±2.3 and a range from 1 to 7. The mean number of additions was 3.2 and the mean number of deletions was 0.9. Of the 10 tissues obtained, 4 were taken from the ovary and 6 were taken from the peritoneum in various locations. Disease severity was reported as being mild to moderate (stage I-II) in 8 cases analyzed and moderate to severe (stage III-IV) in 3 cases analyzed.
Chromosome 17p13.3 Addition in Tissue Biopsies: HIC-1
Analysis of the microarray data indicated the presence of the addition on chromosome 17p13.3 reported previously in 100% of the DNA samples obtained from the endometriosis tissue biopsies. The addition was of the same size range and location as reported in the DNA obtained from the blood samples with a range of 39 to 624 base pairs and an end point of 17:1,959,650.
The results from the tissue biopsies with their corresponding peripheral blood samples are included in Table 8. Only 6 of the 10 corresponding peripheral blood samples shared the addition on chromosome17p13.3 that was found in the tissue samples. The addition size was the same in the peripheral blood and tissue from 3 subjects, larger in the blood of 2 subjects, and larger in the tissue of 1 subject (Figure
17, Table 8).
72
Figure 17 Chromosome 17p13.3 addition size in endometriosis tissue versus peripheral blood
Addition Size in Tissue versus Peripheral Blood 700
600
500
400
300 Tissue
200 Blood Addition Size (bp) Size Addition 100
0 1029 1030 1034 1036 1039 1051 1056 1059 1060 1063 Patient ID
Table 7 Microarray results (105K) of DNA isolated from endometriosis tissue biopsies from endometriosis patients
Tissue Samples from Endometriosis Patients: 105K Platform Patient Age Biopsy Disease Number Additions Deletions 17p13.3 ID Location Stage of CNVs Addition Size (base pairs) 1029 31 Ovary III-IV 2 2 0 555 1030 27 Ovary III-IV 6 3 3 76 1034 28 Ovary I-II 6 4 2 56 1036 37 Ovary I 6 5 1 39 1039 27 Peritoneum II 1 1 0 39 1051 40 Peritoneum II 6 4 2 76 1056 24 Peritoneum I-II 2 2 0 624 1059 43 Peritoneum I-II 3 3 0 120 1060 26 Peritoneum I 2 2 0 76 1063 29 Peritoneum I 7 6 1 76
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Table 8 Microarray results (105K) from the DNA isolated from endometriosis tissue biopsies and corresponding peripheral blood samples from endometriosis patients
Tissue Samples with Corresponding Peripheral Bloods from Endometriosis Patients: 105K Platform Patient ID Age Biopsy Location Disease Stage Addition Size in Tissue Addition Size in Blood (base pairs) (base pairs) 1029 31 Ovary III 555 0 1030 27 Ovary III 77 39 1034 28 Ovary I-II 57 77 1036 37 Ovary I 39 0 1039 27 Peritoneum II 39 77 1051 40 Peritoneum II 77 77 1056 24 Peritoneum I-II 624 624 1059 43 Peritoneum I-II 121 0 1060 26 Peritoneum I 77 0 1063 29 Peritoneum I 77 77
CGH Microarray: 180K Platform
The DNA from the endometriosis tissue biopsies was examined on an additional
microarray platform to investigate potential regions of loss of heterozygosity as well as
additional CNVs. This platform had a greater number of oligos in addition to 27,000
single nucleotide polymorphisms that allow the identification of LOH. As expected, this platform revealed a greater total number of CNVs than the previous platform with an average of 10.8±7.3 CNVs and a range of 1 to 23. The average number of additions
identified was 8.5, and the average number of deletions identified was 2.3. No additional
CNVs were identified with this platform.
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Eight of 10 samples displayed regions of LOH on various chromosomes including
2, 4, 5, 6, 10, 11, 12, 13, and X chromosomes (Table 9).Only 1 common region of LOH was reported in 2 cases on chromosome 4q33.
Table 9 Microarray results (180K) of DNA isolated from endometriosis tissue biopsies
Tissue Samples from Endometriosis Patients: 180K Platform Patient Age Biopsy Location Disease Number Additions Deletions Regions of LOH ID Stage of CNVs 1029 31 Ovary III 6 6 0 2: Chr5q23, Chr11q14 1030 27 Ovary III 17 16 1 2: Chr4q33, Chr12p12 1034 28 Ovary I-II 1 0 1 3: Chr2q24, ChrXp11, ChrXp21 1036 37 Ovary I-II 10 8 2 1: Chr10q21 1039 27 Peritoneum I-II 23 21 2 1: Chr11p12 1051 40 Peritoneum I-II 2 2 0 0 1056 24 Peritoneum I-II 4 2 2 0 1059 43 Peritoneum I-II 17 10 7 1: Chr13q22 1060 26 Peritoneum I-II 14 9 5 1: Chr4q33 1063 29 Peritoneum I-II 14 11 3 1: Chr6p23
Copy Number Variant Size Analysis
Microarray platforms used by other researchers to this point have been relatively low resolution and generally not programmed to identify CNVs under 200,000 base pairs in length. To identify what percentage of CNVs we were able to pick up that were smaller than 200,000 base pairs, all of the CNVs from the 62 samples run on the 105K platform were collected and graphed. A total of 354 CNVs were identified with a mean
75
size of 300,632±625,329 and a range from 14 to 5,237,976 base pairs. The majority of
CNVs reported are considered microadditions or microdeletions with 76% of them less
than 200,000 base pairs in length (Table 10, Figure 18). A total of 114 CNVs from 10
samples run on the 180K platform were also graphed. The mean size detected was
790,839±227,534,853 with range from 163 to 2,231,000,700. Fifty-four percent of the
CNVs reported were less than 200,000 base pairs in length (Table 11, Figure 19).
Table 10 Total CNVs by size as detected by the 105K platform
Total CNVs: 105K Platform Number of Base Pairs CNV Number Percent 1-1,000 69 19% 1,001-5,000 3 1% 5,001-10,000 0 0% 10,001-50,000 20 6% 50,001-100,000 106 30% 100,001-199,999 71 20% 200,000-500,000 39 11% 500,001-1,000,000 11 3% 1,000,001-2,000,000 17 5% 2,000,000+ 18 5% Total: 354 100%
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Figure 18 Total CNVs by percentage as detected by the 105K platform
CNV Size by Percent: 105K Platform
1,000,001- 2,000,000 2,000,000+ 5% 5%
500,001-1,000,000 1,001-5,000 3% 1% 1-1,000 19% 5,001-10,000 200,000-500,000 0% 11% 10,001-50,000 6% 100,001-199,999 20% 50,001-100,000 30%
Table 11 Total CNVs by size as detected by the 180K platform
Total CNVs: 180K Platform Number of Base Pairs CNV Number Percent 1-1000 3 3% 1001-5,000 6 5% 5001-10,000 2 2% 10,001-50,000 14 12% 50,001-100,000 17 15% 100,001-199,999 19 17% 200,000-500,000 17 15% 500,000-1,000,000 17 15% 1,000,001-2,000,000 5 4% 200,000,000+ 14 12% Total: 114 100%
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Figure 19 Total CNVs by percentage as detected by the 180K platform
CNV Size by Percent: 180K Platform 1-1000 200,000,000+ 1001-5,000 3% 12% 5% 5001-10,000 2% 1,000,001- 2,000,000 4% 10,001-50,000 12% 500,000- 1,000,000 15% 50,001-100,000 15%
200,000- 500,000 15% 100,001-199,999 17%
Cell Culture
Cell culture of endometriosis tissue is problematic as biopsy size obtained from laparoscopic surgery paired with ablation treatment is generally very small and depending on the location or stage of disease, few viable cells are present. Ten tissues pathologically confirmed for endometriosis were obtained for study, and 2 were successfully cultured including biopsies from patients 1029 and 1051. Biopsy 1029 was taken from the ovary of a patient with advanced stage III-IV endometriosis, and biopsy
1051 was taken from peritoneum of a patient with moderate stage I-II of the disease.
The cultured cells had consistent morphology and no indications of senescence. Culture media was changed approximately every 48 hours and subcultured when each neared
78
confluency. Routine observation of the primary cultures revealed that the majority of
metaphase cells (approximately 90%) were unusually large potentially indicating polyploid cells (Figure 20). To further investigate this possibility, cultures were harvested for karyotyping.
Figure 20 Endometriosis cell culture: Cells from an endometriosis tissue biopsy obtained from endometriosis patient number 1029. Green arrows indicate normal metaphase cells while red arrows indicate enlarged, potentially polyploid cells.
Karyotyping
Cultured cells from patient number 1029 were split 6 times prior to being harvested. Slides were prepared, and G-banding of the chromosomes was done for karyotyping. Of 100 cells visualized and counted, 76 were diploid (46,XX) and 24 were tetraploid (92,XXXX) as shown in Figure 21. It is difficult to obtain pure endometriosis cells in culture as often a portion of each biopsy contains a mixture of cells from both
79 disease and nondisease tissue. For this reason, karyotyping can result in a normal
46,XX result even if the pure endometriosis cells are tetraploid. It is also possible that the endometriosis cells are evolving from diploid 46,XX to tetraploid, 92,XXXX which may yield similar results.
Figure 21 Tetraploid karyotype: Obtained from harvested metaphase cells in cell culture 1029
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CHAPTER 6
DISCUSSION
To our knowledge, this study was the first to examine the presence of chromosomal imbalances in the form of microadditions, microdeletions, or regions of loss of heterozygosity in the DNA from endometriosis tissue with the corresponding peripheral blood from the same patients using oligonucleotide based array comparative genomic hybridization. The results suggest that copy number variants may play a role in
the establishment and progression of the disease as hypothesized.
Currently, there is no biomarker for endometriosis and making visual confirmation
by way of laparoscopy followed by histological confirmation is the accepted method for
diagnosis. In this study we have identified an addition on chromosome 17p13.3 present
in the blood and tissue from endometriosis patients that may serve as a genetic marker
for the disease allowing for the development of a less invasive option for diagnosis as
well as target for the development of a new therapeutic option.
Hypermethylated in Cancer-1
The addition located on chromosome 17p13.3 is located within the gene
hypermethylated in cancer-1 (HIC-1). HIC-1 is expressed throughout the body but at the
highest concentrations in the lung, colon, prostate, thymus, testis, and ovaries. It is a
tumor suppressor gene that, as the name implies, has been shown to be
hypermethylated in cancer as well as many precancerous tissues. This epigenetic
81
modification results in the down-regulation of gene expression by blocking the binding of
transcription factors to the DNA and by modifying chromatin structure by way of methyl-
binding domain proteins 78. The HIC-1 gene and its function have been shown to be altered in cancer by various mechanisms including hypermethylation of the promoter region of the gene but also by deletion of the gene or regions of the chromosome containing the gene and losses of heterozygosity. These alterations often result in a reduction in gene expression or total gene silencing that may result in uncontrolled cell
growth, tumor formation, and the development of certain cancers.
A lack of or a decrease in HIC-1 expression associated with hypermethylation of
the promoter region of the gene has been identified in lung squamous cell carcinoma
and lung adenocarcinoma 79, head and neck squamous cell carcinoma 80,
choriocarcinoma 81, ependymomas 82, medulloblastomas 83, breast cancer 84, prostate
cancer 85, 86, cervical cancer 87, gastric cancer 88, hepatocellular cancer 89, and colorectal
cancer 90. As methylation is an epigenetic modification that may occupy the DNA at
varying densities, gene expression may be altered to different degrees from a reduction
to a total lack of gene expression. Identification of “hemi-methylated” regions in the
normal tissue when compared to dense hypermethylation in cancer tissue may indicate
that the degree of methylation of one or both alleles may be directly correlated to gene
expression thus the severity or presence of disease 84, 91. Hypermethlyation has also
been shown to occur in various precancerous tissues 81, 85, 88, 89 which strengthens the
notion that methylation may play a role in disease development and progression. In
other words, patients with one hypermethylated allele may be predisposed to
developing cancer if and when the other allele becomes either hypermethylated or
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inactivated by other means. Administration of demethylating drugs has been shown to
restore HIC-1 expression and function in some disease patients 80, 90, 92 and may be an
option for endometriosis therapy if future studies support our findings.
Reduced expression of HIC-1 by mechanisms other than promoter
hypermethylation has also been reported. Deletions of all or part of chromosome 17
containing the HIC-1 gene have been shown to occur in a variety of cancers including
acute myeloid leukemia cell lines 93, mantle cell lymphomas 94, medulloblastomas 91,
ovarian cancer 95, and esophageal cancer 96. Regions of LOH associated with the HIC-1
gene have been detected in breast cancer 84, 92, gastric cancer 88, 97, hepatocellular
cancer 89, ovarian cancer 95, esophageal cancer 96, ependymomas 82, and
medulloblastomas 91. It has been suggested that these alterations are related as LOH has been thought to be a potential consequence of DNA hypermethylation. This post
translational modification may make chromatin more susceptible to structural changes
resulting in loss of heterozygosity and a reduction or loss in gene function 98. In either
case, the loss of function of HIC-1 function contributes to tumor formation and possibly
cancer development.
Changes in the HIC-1 gene may play a role in the development of disease, but it
is also located just upstream and downstream of other potentially pathogenic genes100.
HIC-1 resides approximately 13,000 base pairs from the ovarian cancer tumor suppressor gene (OVCA2) that has been demonstrated to be aberrantly expressed in ovarian cancer 99 and approximately 10,000 base pairs from diphthamide biosynthesis
protein 1 (DPH1) that is a tumor suppressor involved in cell cycle control in ovarian
cells. Patients with endometriosis have an increased chance of developing ovarian
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cancer, and the distinction between the 2 diseases becomes progressively unclear as we continually reveal similarities between them. It has yet to be elucidated if a mutation in HIC-1 gene could be affecting either OVCA2 or DPH1 therefore contributing to disease state. Other genes in the vicinity of HIC-1 include nonsense mediated mRNA decay factor (SMG8) that is involved in eliminating premature stop codons, CTD-
254H1.2 which is associated with the abnormal growth of blood vessels in the eye in
Coates disease, and retinitis pigmentosa (RP11), which is associated with a degenerative disease of the eye.
It is unclear at this point how the addition of a portion of HIC-1 may play a role in the pathogenesis of endometriosis. The addition may disrupt the reading frame resulting in altered gene expression or create an alternative splice site resulting in an abnormal or inactive gene or gene product. The region of interest is GC rich as approximately
73% of the base pairs being either guanine or cytosine in the 624 base pair region based on the predicted sequence. It is possible that additional methylation sites have
been created in this GC rich region resulting in further suppression of HIC-1.
Additionally, if the duplication being reported is a result of a translocation of the genetic
material to another region in the genome, other genes may be potentially affected
depending on the locus of the translocation.
Free-Circulating DNA
The addition on chromosome 17p13.3 was identified in 100% of the DNA
samples extracted from the endometriosis tissue but only in 75% of the DNA samples
84 extracted from the peripheral bloods. This may be due to free-circulating DNA (CFDNA) from the disease tissue cells in the blood. The concept of CFDNA is not a new one.
CFDNA of cancerous tumors as well as the CFDNA of an unborn fetus in the peripheral blood and serum of its mother can be detected in affected individuals and is now being used as a minimally invasive technique to detect multiple diseases. This is possible because CFDNA in many cancer patients has been demonstrated to harbor the same genetic alterations as the cancer tissue itself including hypermethylation, LOH, and copy number changes. In addition, the amount of CFDNA detected in these patients has been shown to be directly correlated with disease stage and severity. Two mechanisms have been postulated for how tumor CFDNA is released into the blood including apoptosis or necrosis and lysis of cells following their dissemination from disease tissue
101. This is an interesting concept to consider in endometriosis as the disease tissue has been demonstrated to appear and proliferate in locations distant from the peritoneal cavity. This may be due to the transport of the disease cells to other regions of the body via the circulatory system. Further research involving the addition on chromosome
17p13.3 in endometriosis patients is critical as a biomarker for the disease has yet to be identified and may allow for the development of a diagnostic test.
Loss of Heterozygosity
Each region of LOH detected by the 180K platform was further investigated to see if any had been previously reported as being associated with conditions potentially related to endometriosis. All locations investigated had been previously reported in
85 cancer or other disease conditions as shown in Table 12. Of particular interest were regions of LOH on chromosomes 12p12, 13q22, and Xp21 which were shown to be present in ovarian cancer. The platform used in the current study detected only one common region of LOH in 2 patients on chromosome 4q33. This may be due to the small number of SNP probes included in this oligo/SNP combination type microarray relative to arrays designed to detect SNPs alone. Additional research using high resolution SNP arrays to investigate regions of LOH in endometriosis is necessary for a better understanding of these genetic alterations and their potential involvement in the disease process.
Table 12 Regions of LOH as reported in the literature
Region of LOH Disease Group 2q24 Atherosclerosis Flouris et al. Colon cancer Peng et al. 4q33 Breast cancer Shivapurkar et al. Colon cancer Shivapurkar et al. Distal stomach cancer Xu et al. 5q23 Colon cancer Csiszar et al. Esophageal cancer Attaran-Bandarabadi et al. Lung cancer Shin et al. Pharyngeal epithelial cancer Grati et al. 6p23 B-cell non-Hodgkin's lymphoma Nagai et al. Cervical cancer Zhang et al. Nasopharyngeal carcinoma Shao et al. Pulmonary sarcoidosis Demopoulos et al. 10q21 Breast cancer Leighton et al. Colon cancer Fawole et al. Head and neck squamous cell carcinoma Beder et al. Lung cancer Petersen et al. Medulloblastoma Langdon et al. Meningioma Krupp et al. Osteosarcoma Smida et al. Prostate cancer Srivastava et al.
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Table 12 Continued 11p12 Brain cancer Hu et al. Lung cancer Iizuka et al. Prostate cancer Dahiya et al. 11q14 Brain cancer Hu et al. Gastric cancer D'Adda et al. Lung cancer Iizuka et al. Neuroblastoma Carr et al. Oral squamous cell carcinoma Zhou et al. Squamous cell carcinoma of the head and Glavac et al. neck 12p12 Acute lymphoblastic leukaemia Baccichet et al. Colon cancer Wan et al. Ovarian cancer Hatta et al. Prostate cancer Kibel et al. 13q22 Gastric cancer Jiao et al. Nasopharyngeal carcinoma Zhou et al. Ovarian/fallopian tube cancer Jongsma et al. Testicular teratoma Jones et al. Xp11 Neuroendocrine lung carcinoma D'Adda et al. Xp21 Duchenne muscular dystrophy Fonseca-Mendoza et al. Neuroendocrine lung carcinoma D'Adda et al. Ovarian cancer Yang-Feng et al.
Control Individuals
To this point, genetic studies investigating endometriosis have been limited as ideal control individuals are difficult to obtain. It is likely that some of the “normal” control individuals used in this and other studies either have endometriosis and are asymptomatic or will develop the disease at some point in their lifetime. The criteria for inclusion in this study was that the individuals were over 30 years of age with no history of infertility as evidenced by having 2 or more children and no known family history of endometriosis. None of the controls were examined laparoscopically prior to this study.
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The reality is that not all women who have endometriosis are infertile and many are
asymptomatic and may not know they have the disease. This may account, in part, for
the high number of controls that appear to have the additions of interest. Instead of attempting to include appropriate controls, most studies have looked for commonalities in the disease group of patients that have not been previously reported as being associated with another condition. The possible existence of microscopic endometriosis
141-143 further complicates the issue. Microscopic endometriosis has been suggested to
be present in physically normal, healthy tissue and is unable to be visualized without
microscopy making even the standard laparoscopy a flawed diagnostic tool. Simply
stated, physicians cannot diagnose, surgically remove, or treat what they cannot see;
therefore, choosing the appropriate controls for studies involving endometriosis remains
problematic at best.
Polyploid Cells in Culture
It was noted that the primary cell cultures from patient 1029 contained
approximately 90% oversized metaphase cells, and subsequent karyotyping revealed
24% of the metaphase spreads to be tetraploid. After initial observations were made on
the aberrant metaphase cells, the cells were subcultured 5 times and frozen for later
investigation. For karyotyping, the cells were thawed and cultured to the desired
confluency before harvesting for karyotype analysis. The reduction in the number of
polyploid cells with subculturing has been well documented and various mechanisms as
to how it occurs have been put forth. Tetraploidy can occur as a result of several
88 mechanisms including cell fusion, mitotic slippage, and a failure of a cell to undergo cytokinesis 144, 145. Previous studies demonstrate that cells in culture tend to select against nondiploid cells 144, 146 reducing the number of aneuploid cells with each passage. A “G1 tetraploidy checkpoint” has been shown to act as a surveillance mechanism resulting in either cell cycle arrest or apoptosis of aneuploid cells 147 causing a decrease with each subsequent division. In addition, cell division time for tetraploid cells is greater than that of diploid cells resulting in fewer tetraploid cells over a given period.
It is well known that aneuploidy is common in precancerous and cancerous tissues, and it has been demonstrated that women with ovarian endometriosis have an increased chance of developing ovarian cancer. In addition, studies indicate that ovarian endometriosis may be a precursor to ovarian cancer due to molecular similarities between the 2 disease states 148. The cells investigated in this portion of the study were obtained from endometriosis tissue of the ovary from a woman with stage III of the disease. The observation that the majority of metaphase cells in the primary culture appear to be tetraploid and that 24% remained tetraploid after 6 passages supports the notion that endometriosis is molecularly similar to cancer and may indicate ovarian endometriosis as a precursor to ovarian cancer.
Copy Number Variant Size, Are We Missing Something?
Many microarray analysis software programs allow the user to select a CNV cut- off point in which the software will only report CNVs above the specified size. For many
89
high resolution platforms, the default cut-off size is approximately 200,000 base pairs.
This reduces the CNV output as well as removes many polymorphisms simplifying the analysis; however, it eliminates small changes that may be of importance. To evaluate
the potential significance of this observation, copy number variants for all patients in this
study were recorded, and it was found that the majority of CNVs identified by the
BlueFuse software were less than 200,000 base pairs in length. This is a vital piece of
information as the majority of current studies use platforms that are not equipped to
identify small chromosomal changes and may be missing critical pieces of information
related to disease. Of the 7 studies summarized in the literature review that used
microarray analysis to investigate CNVs in endometriosis patients, 3 used BAC probes,
3 used FISH/metaphase CGH, and the most recent used a BeadChip SNP array. BAC
probes are generally over 100,000 base pairs in length and depending on the platform
used, require multiple probes to be “out of range” to identify a gain or loss. FISH or
metaphase CGH detects differences in fluorescence of probes hybridized directly to
normal metaphase spreads and its resolution varies depending on the sensitivity of the
software used to analyze the spreads. The Illumina HumanOmniExpressBeadchip used
in the most recent publication on CGH in endometriosis has roughly 733,000 SNP
probes spanning the genome at approximately every 2.2kb. In all cases, CNVs under
several hundred thousand base pairs in length are unable to be detected.
This observation is not only important in relation to endometriosis but to all
diseases in which CGH microarray technology is being used to look for genetic markers,
genetic causes, or genetic links to disease. It has been well established that small
genetic changes can be responsible for the development of disease such as in sickle
90
cell anemia wherein a single adenine to thymine change results in an altered gene
product and disease onset. For this reason, we must question the findings of the studies
in the literature that claim no genetic relationship to a specific disease based on low
resolution platforms. Pathogenic microadditions and microdeletions may be present and
overlooked in many cases due to technological shortcomings. As technology advances,
more accurate and affordable testing is becoming available to researchers and many
diseases need to be reassessed in terms of genetic alterations as causative agents.
False Positives
Array CGH has been observed to produce false-positives under certain
conditions that may make interpretation of results difficult 149, 150. The conditions most
often associated with the identification of false positives include probe coverage in G-C
rich regions of the genome and “noisy arrays” that can result from the nonspecific
hybridization of very small DNA fragments to random oligos. The region on 17p is considered G-C rich with 73% of the 624 base pair region containing guanines and cytosines based on the predicted sequence. Unfortunately, there is no way to control for false-positives based on nucleotide content except for keeping in mind false-positive prone regions reported in the literature that include chromosomes 1p, 16p, 19, and 22
35.
Also associated with false positives are “noisy” arrays in which DNA fragment
sizes are too small to be sequence specific and bind to random locations throughout
91 the genome (Figure 22A). This may be caused by mishandling of DNA samples or
DNA overdigestion. In this study, this issue was avoided by both confirming the DNA fragment size prior to hybridization using the Agilent Bioanalyzer and by viewing array parameters after each microarray run. “Noisy” arrays are identified by many probes outside of the accepted standard deviations identified by the red and green vertical lines in each array in Figure 22A. Any arrays with this type of appearance were discarded and the samples were rerun. Clean arrays are identified by the majority of probes inside of these lines as shown in Figure 22B.
Figure 22 Microarray Runs, “Noisy” versus Clean…A. Noisy arrays are identified by the majority of probes outside of the accepted standard deviations B. Clean arrays are identified by the majority of probes inside of the accepted standard deviations
A. B.
92
Future Research
As this project progressed, a multitude of research projects have emerged that should be investigated in order to gain a clear understanding of the genetics of endometriosis. Sequencing the HIC-1 gene is imperative to our understanding of how it is involved in the disease mechanism. However, our attempts to sequence the HIC-1 microaddition have so far been unsuccessful. Six DNA samples from endometriosis patients were sent to 2 sequencing facilities for targeted sequencing of the region containing the addition of interest. Neither was able to sequence the samples. It may be necessary to use more advanced methods of sequencing better suited for sequencing of G-C rich regions of the genome. Exome sequencing or whole genome sequencing should also be carried out as each would provide genome-wide sequence information including balanced changes in the DNA that cannot be identified by the platform utilized in this study.
The confirmation of the addition may be accomplished using polymerase chain reaction (PCR) and the Agilent Bioanalyzer. Isolation and amplification of a fragment obtained by using appropriate primers up- and downstream of the region of interest with
PCR followed by analysis of fragment size using the Agilent Bioanalyzer may be informative. The fragment size should be larger than the predicted size reflecting the additions reported in this study.
The use of methylation arrays would reveal if HIC-1 is methylated or hypermethylated in endometriosis as expected. These arrays concentrate on G-C rich regions of the genome known to be methylated in a variety of cancers and are able to
93
identify single methylation sites. By examining DNA from both the blood and tissue from
endometriosis patients, we may be able to gain a more clear understanding of how this
epigenetic modification is involved in the disease mechanism of endometriosis.
Research Conclusions and Summary
In this study we used oligonucleotide-array based comparative genomic
hybridization to reveal an addition present on chromosome 17p13.3 in100% of
endometriosis tissue samples assayed and in 75% of the peripheral blood samples from
corresponding patients. This addition is located in the hypermethylated in cancer-1 gene
and has not been previously associated with endometriosis.
To this point, no definite genetic markers of endometriosis have been identified in
either the blood or tissue of endometriosis patients leaving laparoscopy followed by
pathological confirmation based on histology the most common method for diagnosis of
the disease. If a genetic alteration is confirmed to be the cause or play a role in the
development of the disease, women who are asymptomatic are unknowingly passing
the disease gene to future generations. The discovery of a biomarker would allow for
early detection of the disease resulting in a more accurate calculation of the number of
women afflicted as well as the opportunity to avoid complications such as infertility with
the proper medical intervention.
It has been widely suggested that endometriosis is a multifactorial disease with proposed pathogenic mechanisms including retrograde menstruation, coelomic
metaplasia, immunological factors, stem cells, surgical contamination, environmental
94 factors, and faulty genetics. While each of these mechanisms has convincing components, they are each lacking in some way. The majority of women experience retrograde bleeding, but why do only a portion develop endometriosis? Coelomic metaplasia may occur, but what initiates this cellular transformation? Is there a defect in the immune system that renders it unable to recognize or eliminate misplaced endometrium? If stem cells in circulation are totipotent, why would they necessarily become endometrial cells, and if they do become endometrial cells, why isn’t the immune system able to eradicate them? Why would environmental factors cause the development of disease in only certain exposed individuals? Regardless of which hypothesis you buy into, it is certain that something is different either in the disease tissue itself or within the affected individual that allows endometriosis cells to attach, proliferate, and establish as disease. It is probable that there are multiple explanations for what causes endometriosis; however, genetics is likely the underlying factor. In this study, we may have discovered a novel genetic aberration linked to endometriosis that may be useful in developing future diagnostic tests and treatments for the disease.
95
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APPENDIXES
APPENDIX A: IRB APPROVALS
Peripheral Blood Sample Approval
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Endometriosis Biopsy Approval
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Endometriosis Biopsy Approval: MSHA Research Department
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APPENDIX B: INFORMED CONSENT DOCUMENTS
Peripheral Blood Informed Consent Document
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Endometriosis Biopsy Informed Consent Document
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VITA
NATALIE J. BURKE
Personal Data: Date of Birth: May 23, 1987 Place of Birth: Elizabethton, Tennessee Marital Status: Single
Education: 2010-present Quillen College of Medicine: Johnson City, TN • Doctoral Candidate in the Biomedical Sciences Program, Graduate Research Assistant • Perform testing in a clinical genetics laboratory 2009-2010 East Tennessee State University: Johnson City, TN • Graduate Student in Master’s Degree Program in Biology, Graduate Research Assistant • Funded through HHMI Grant • Funded through NSF Grant:GK-12 Program 2005-2009 East Tennessee State University: Johnson City, TN • B.S. in Biological Sciences • Graduated Magna Cum Laude 2001-2005 David Crockett High School: Jonesborough, TN • Diploma, 4.0+ GPA
Professional Experience: 2011-Present Quillen Fertility and Women’s Services: Johnson City, TN • Andrologist/Junior Embryologist o Sperm preparations on both partner and donor sperm specimen for intrauterine insemination, in vitro fertilization, and intracytoplasmic sperm injection o Cryopreservation of sperm o Media preparation for oocyte retrieval, in vitro fertilization, intracytoplasmic sperm injection, embryo culture, and embryo transfer o Quality control and maintenance of laboratory o Entering laboratory data into databases to generate patient reports o Maintenance and reporting of clinic IVF data and success rates to SART
2010-Present Quillen College of Medicine: Johnson City, TN • Research Assistant in a clinical genetics laboratory o All aspects of comparative genomic hybridization microarray preparation, procedures, and analysis o DNA extraction from blood, tissue, and cell culture o Peripheral blood culture and harvest o Amniotic fluid culture and harvest o Tissue culture and harvest
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o Slide preparation for karyotype analysis o Karyotype cutting o Fluorescent in situ hybridization o Agilent Bioanalyzer o Nanodrop 2000 Spectrophotometer o Quality control and maintenance of laboratory
2009-2010 East Tennessee State University: Johnson City, TN • Research Assistant o Lab research involving the isolation of biogenic amines in the central nervous system of S. crassipalpis to examine diapause • Developed/created scientific learning aids to be included in future biology courses for undergraduates at ETSU • Supported by an NSF grant in the GK-12 program to develop curriculum at North Side Elementary School that is focused around science and mathematics
2009-2010 Center for Applied Reproductive Science: Johnson City, TN • Intern/Andrologist • Performed procedures in an andrology lab, including: o Sperm preparations on both partner and donor sperm specimen for intrauterine insemination o Cryopreservation of sperm o Quality control and maintenance of laboratory o Operating Cholestech o Entering laboratory data into databases to generate patient reports o Observed in the embryology laboratory including minimal hands on training in sperm preparation for IVF and ICSI and stripping oocytes
Professional Activities: 2011-present Member of American Society of Human Genetics
2011-present Member of American Society of Reproductive Medicine
October 2012 American Society of Human Genetics Meeting • San Francisco, California
March 2011 CGH Microarray Training and Troubleshooting Workshop • Bluegnome, Cambridge, UK
October 2011 International Congress of Human Genetics Meeting • Montreal, Canada
October 2011 American Society of Reproductive Medicine Meeting • Orlando, Florida
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