ALTERNATIVE SPLICING OF MDM4 IN HUMAN MELANOMA
A thesis submitted in partial fulfillment of
the requirements for the degree of Master of Science
By
ABDULLAH SALEM S ALATAWI
Bachelor., University of Tabuk, Saudi Arabia, 2015
______
2020
Wright State University WRIGHT STATE UNIVERSITY GRADUATE SCHOOL July 29, 2020
I HEREBY RECOMMEND THAT THE THESIS PREPARED UNDER MY SUPERVISION BY Abdullah Salem S Alatawi ENTITLED Alternative Splicing of MDM4 in Human Melanoma BE ACCEPTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF Master of Science. ______Michael Markey, Ph.D. Thesis Director
______Madhavi P. Kadakia, Ph.D. Chair, Department of Biochemistry and Molecular Biology Committee on Final Examination:
______Michael Markey, Ph.D. Research Associate Professor of Biochemistry & Molecular Biology
______Weiwen Long, Ph.D. Associate Professor of Biochemistry & Molecular Biology
______Michael Craig, Ph.D. Research Assistant Professor of Biochemistry & Molecular Biology
______Barry Milligan, Ph.D. Interim Dean of the Graduate School
ABSTRACT Alatawi, Abdullah Salem S. M.S. Department of Biochemistry and Molecular Biology, Wright State University 2020. Alternative Splicing of MDM4 in Human Melanomas
Melanoma is a potentially lethal type of skin cancer and regarded to be the third most common type of skin cancer. Although melanoma is not as common as basal cell carcinoma (BCC) and squamous cell carcinoma (SCC), it is more likely to metastasize than BCC and SCC. Interestingly, the incidence of melanoma continues to go up
(expected 2% in 2020), but the deaths continue to decrease (-5.3% in 2020) due to improvements in detection and treatment. The treatment of melanoma depends on several aspects but most importantly the tumor's stage and the location. In the early stages, melanoma can be removed via surgical operation, but in the late stages, melanoma usually treated with radiation or targeted therapy. Many factors predict the development of melanoma like skin pigmentation, age, sun exposure (UV light), and genetic mutations. The p53 protein initiates apoptosis and cell cycle arrest in response to stresses that cause DNA damage like UV light. However, mutant p53 is frequently detected in numerous cancers, including melanoma. MDM2 and MDM4 negatively regulate p53.
Notably, a study indicates that MDM4 is overexpressed in 65% of melanoma. Therefore, there is a strong rationale to target MDM4 therapeutically, but MDM4 has several spliced variants, and some variants were detected in human and murine cancers. Yet, no studies have assessed the relative levels of MDM4 splice variants in melanoma. Therefore, in this study, we aimed to identify which variants are expressed in melanoma. We collected clinical specimens and designed specific primers for each isoform by RT-PCR. We observed no expression of MDM4-211 in either malignant and nevi samples. MDM4-
iii
Alt1 was present only once in nevi samples. Other variants were similarly present in nevi and malignant samples, but MDM4-A was the most commonly expressed variant in melanoma samples. Data were also collected and analyzed from publicly available databases to examine MDM4 expression in normal skin and melanoma and the survival data associated with each isoform. The results also showed that MDM4-A is the most common isoform expressed in melanoma. In conclusion, our data suggest that aberrant splicing of MDM4 occurs early in carcinogenesis of melanoma, MDM4 is more frequently amplified than its family member MDM2, that MDM4 has more change in splicing than what is observed in MDM2, and supports the view that MDM4-A is an oncogenic variant that promotes carcinogenesis in melanoma.
iv
Table of Contents
Page
I. INTRODUCTION……………………………………………….……………..……….…. 1
A. Human Melanoma…………………………………………………...…………………….. 1
B. The Biology of Melanoma…………………………………………...……………………. 2
C. Current Treatment of Cutaneous Melanoma……………………...……………………….. 4
D. Role of p53 in melanoma…………………………………………...……………………... 6
E. The p53 Interaction with MDM2/MDM4 in Melanoma……………...……………...……. 7
F. MDM4 as a Therapeutic Target in Melanoma………………………………………..…… 11
G. Alternative Splicing in Melanoma…………………………………………………..…….. 12
H. MDM4 Splice Variants …………………………………………………………………… 12
II. MATERIALS AND METHODS……………………………………………...……………17
1. Collecting FFPE Samples…………………………………………………………………..17
2. Primer Design for MDM4 Splice Variants…………………………………………………18
3. RNA Extraction & Purification from FFPE tissues………………………………………...19
4. cDNA Synthesis and RT-PCR……………………………………………………………...20
5. MDM4 Isoforms Analysis……………………………………..………..………………….21
6. Statistical Analysis………………………………………………………………………….22
III. RESULTS…………………………………………………………………………………..23
i. Mutational Gene Analysis Pointed Out that Most Melanomas have Intact p53……………23
ii. MDM4 is More Frequently Amplified in Melanoma than MDM2………….……..…….....24 iii. The expression of MDM4 is Linked to Poor Survival in Melanoma……………….……....25
v
iv. The Expression of MDM4 Splice Variants in Sun exposed Skin Compare to Non-Sun
Exposed skin……………………………………………………..………………………….26
v. Comparing Castle Class to Isoforms Presence Statistically Showed MDM4-S is Significant in
Melanoma Samples………………………………………………………………………….27
vi. MDM4-A is The Most Common Alternative Transcript expressed In Melanoma
Samples……………………………………………………………,,……………………….28
vii. Isoform Specific Expression Analysis Showed Consistent Expression of The Alternative
Transcript MDM4-A in Melanoma Patients.…………………… ……………………,,,…..30 viii. MDM4-A Isoform Correlates with Poor Survival in Melanoma…………………,………...32
IV. DISCUSSION………………………………..……………………….…………….……….33
V. FUTURE DIRECTION……………………………………………………………………...37
VI. REFERENCES……………………………….…………………………………..………….38
vi
List of Figures
Page
Figure 1: Schematic illustration of the domain structures of p53, MDM2, and
MDM4…………………………………………………………………………………...9
Figure 2: Two Proposed Models of MDM2 and MDM4 interaction with p53………………11
Figure 3: Schematic representation of MDM4 mRNA organization in exons (according to the
GeneBank NM 002393)…………………………………………………………………16
Figure 4: Most melanomas have an intact p53 gene ……………….……………..…….24
Figure 5: MDM4 is frequently amplified in melanoma, in contrast with MDM2……....25
Figure 6: MDM4 expression does not significantly correlate with patient survival …..….26
Figure 7: MDM4 isoform expression in normal skin ………………………..…………………..…….…27
Figure 8: Statistical significance analysis of MDM4 isoforms in melanoma specimens..28
Figure 9: MDM4 isoform expression in melanocytic lesions is different from normal skin
………………………………………………………………………………………………………………………………..……..…31
Figure 10: MDM4-A isoform correlates with poor survival ………………………………………..…32
Figure 11: Model of Carcinogenesis of melanoma with timeline of MDM2/4/p53 …...…36
vii
List of Tables
Page
Table 1: Melanoma Samples…………………………………………………………………………………………….17
Table 2: Nevi Samples………………………………………………………………..…………………………………….18
Table 3: The amount of RNA in each sample…………………………………………………………………….19
Table 4: Summary of RT-PCR Results in Melanoma and Nevi samples………………..……….……29
viii
ACKNOWLEDGMENTS
I wish to express my sincere thankfulness and appreciation to my advisers Dr.
Michael P Markey, for believing in me. Thank you, Dr. Markey, for your patience, guidance, and support. Thank you, Dr. Markey, for training me on many laboratory techniques and the knowledge that I gained during my time under your supervision. I'd also like to acknowledge Dr. Nicholas Shamma, the man who made this project possible by sharing his clinical specimens with us, thank you, Dr. Shamma. I would also like to thank Dr. Weiwen Long and Dr. Michael Craig for taking the time to serve as committee members. Thank you, Dr. Long and Dr. Craig, for suggestions and everything. I was fortunate to be in the lab with someone like Stacy Simmons; she helped me many times, thank you, Stacy. I met lots of friendly and great people at the BMB Department; thank you, BMB community. Special thank goes to SACM and University of Tabuk for the scholarship and financial support.
I am grateful to my mother Munirah, my father Salem, Najwd, Omar, Jamilah,
Mohammed, and Amal, who have provided me with moral and emotional support. I am also grateful to my other family members and friends who have supported me along the way, especially Melanie Schloemer. Thank you all.
The results shown here are in whole or part based upon data generated by the TCGA
Research Network: https://www.cancer.gov/tcga.
ix
I. INTRODUCTION:
A. Human Melanomas
Melanoma is considered to be the third most widespread sort of skin carcinoma and is
responsible for many of the skin cancers fatalities in the United States (Jemal, A et al., 2011)
(Jemal, A et al., 2013) (Gruber SB et al., 2006) (The US Department of Health and Human
Services, 2014). Worldwide, the rate of melanoma occurrence has been growing
dramatically more than any other malignancy. (Ali, Z et al., 2013). Melanoma is the fifth
most common cancer among males and the seventh most common cancer among females
(Reed, K. B et al., 2012). A study performed on evaluating the gender role in the survival of
melanoma patients showed that female patients exhibit notably more prolonged survival than
male patients (Morgese, F et al., 2015). According to the U.S. Department of Health and
Human Services, melanoma incidence rates have been rising over the past 40 years in the
United States (Tripp, M. K et al., 2016). Over 63,000 people in the U.S. have melanoma,
leading to the death of approximately 9,000 people annually (U.S. Cancer Statistics Working
Group, 2014) (NPCR and SEER, 2011) (The US Department of Health and Human Services,
2014). The occurrence of malignant melanoma in non-white Americans is significantly lower
than in white Americans. According to American Cancer Society, the likelihood of
developing melanoma is nearly 2.6% (1 in 38) for white Americans compared to 0.1% (1 in
1,000) for African Americans, and 0.6% (1 in 167) for Latino Americans. However,
according to the National Cancer Institute, melanoma incidence in recent years have dropped
substantially, nearly 5.3% yearly due to advancements in melanoma therapy. Melanoma
occurs in different forms such as nodular melanoma, lentigo maligna melanoma and acral
1 lentiginous melanoma, but the typical form is cutaneous malignant Melanoma (CMM) in the white American population (Hayward N. K., 1996) (Palmer, J. S et al., 2000). Exposure to sunlight, fair skin, dysplastic nevi syndrome, and a family history of melanoma are significant risk factors for melanoma formation (Markovic, S. N et al., 2007). Additionally, several host factors influence the risk of developing melanoma, including genetic susceptibility, family history, and the number of congenital melanocytic nevi (Bauer, J., &
Garbe, C., 2003) (Hawkes, J. E et al., 2016) (reviewed in Leonardi, G. C E et al., 2018). The interactions between environmental and genetic risk factors that drive carcinogenesis are presently the area of interest of ongoing research. Avoiding sunlight and improved monitoring vulnerable of patients have the potential to lessen the burden of melanoma in the human population.
B. The Molecular Biology of Melanoma
Though over 95% of tumors are seen in the skin, melanoma is not solely a skin cancer
(Markovic, S. N et al., 2007). Melanoma can occur in multiple sites, such as the eye, mucosal tissue, GI tract, urogenital system, the brain, and lymph nodes. The role of melanocytes is well-studied and described in the skin. In the basal layer of the dermis, melanocytes form intimate connections with keratinocytes, through slender dendritic processes that shuttle of melanosomes to keratinocytes (Markovic, S. N et al., 2007). Melanoma development is the consequence of genetic alterations and tumor microenvironmental modifications, distinguished by the high expression of proteins capable of promoting tumor infiltration and invasion (Chiriboga, L et al., 2016) (Guarneri, C, L et al., 2017) (Reviewed in Leonardi, G.
C E et al., 2018). Interestingly, melanomas have one of the most significant levels of somatic genetic modifications in human tumors (Vogelstein, B et al., 2013) (Akbani R et al., 2015)
2
(Reviewed in Leonardi, G. C E et al., 2018). The prevalent somatic mutations in sunlight- exposed skin in melanoma impact genes that regulate vital biological processes, such as proliferation (NRAS, BRAF, and NF1), metabolism and growth (PTEN and KIT), resistance to cell-programmed death (TP53), cell cycle arrest (CDKN2A) and replicative life cycle
(TERT) (Hodis, E et al., 2012) (Krauthammer, M et al., 2012) (Reviewed in Leonardi, G. C
E et al., 2018). These genomic changes commonly trigger the abnormal activation of two major signaling pathways in melanomas: the MAPK pathway and the PI3K pathway
(Chappell, W. H et al., 2011) (Reviewed in Leonardi, G. C E et al., 2018). The negative regulation of the MAPK pathway is observed in numerous human carcinomas, including melanoma, which commonly occurs due to genetic alterations in the RAS family genes and
B-RAF gene or other genes involved in the MAPK pathway (Davies, H et al., 2002)
(Mercer, K. E et al., 2003) (Maldonado, J. L et al., 2003) (N. Dhomen, R., 2009) (Inamdar,
G. S et al., 2010). Genetic changes in the RAF/MEK/ERK pathway influence cell growth, metastasis, and viability of melanoma cells in vitro. Thus, it is apparent that B-Raf mutation plays a central role in melanoma biology. BRAF is a serine/threonine-protein kinase with downstream signaling impacts on RTKs and RAS protein (Rother & Jones, 2009) (Staibano,
S et al., 2011). The frequent occurrence of B-Raf genetic mutations in melanoma and nevi is interesting, being observed in about 30% to 80% of melanoma cases (Thomas et al., 2006)
(Staibano, S et al., 2011). Surprisingly, BRAF mutations in melanoma cells have a different mutational spectrum than in other cancers, potentially due to the exposure to UV light
(Thomas et al., 2006) (Staibano, S et al., 2011). Amongst these single mutations, the most frequent is V600E (valine replacing glutamic acid), which makes up more than 90% of total
3
BRAF mutations. The mutation of BRAFV600E is caused by UV exposure (Meyle &
Guldberg, 2009) (Balazs, M et al., 2011).
C. Current Treatment of Cutaneous Melanoma
Cutaneous melanoma has four main subtypes: superficial spreading melanoma accounting for nearly 70% of all melanomas, nodular melanoma accounting for 15–30% of all melanomas, lentigo maligna (LM), and acral lentiginous (Evans, M. S et al., 2013). Most melanomas appear as abnormal superficial swellings on the skin and may continue for a long time in a phase known as the radial growth phase. In this phase, the melanomas are mostly curable by surgery alone. In the vertical growth phase, which is considered a step toward metastasis, measuring the thickness of the tumor is the most common method to predict melanoma prognosis (Evans, M. S et al., 2013). Surgery is still regarded as the main therapy of any primary melanoma site, and earlier detection with appropriate surgical intervention presently provides a possible cure for melanoma patients at early stages. The purpose of surgical treatment is to locally control the tumor and to secure the patient's long-term survival without functional limitation and disability. At present, effective surgery relies on accurate melanoma staging (Rutkowski, P et al., 2010). According to the Skin Cancer
Foundation, if the thickness of melanoma measures 0.8 mm or larger or has other characteristics like ulcers that cause it to be very likely increase the likelihood reaching the lymph nodes, a sentinel lymph node biopsy may be done contemporaneously with surgery.
The use of sentinel lymph node biopsy (SLNB) in melanoma treatment is well established. In stage I and II melanoma, experiments have confirmed that elective lymph node dissection has no survival advantage over nodal observation, but SLNB correlates with survival rate in patients with intermediate thickness melanoma (1–4 mm) positively compared to nodal
4 observation (Balch, C. M et al., 2000) (Wernick, B. D., 2017). As for advanced melanoma, immunotherapeutic treatments are being examined to develop targeted therapies for patients
(Kanehisa, M et al., 2017) (Rodríguez-Cerdeira, C., 2017). Melanoma metastasis is commonly linked with critical immune tolerance, which is described in part by the weak immunogenicity of melanoma antigens (Ascierto, P. A. et al., 2014) (Rodríguez-Cerdeira, C.,
2017). The Cancer Genome Atlas (TCGA) characterizes four subtypes TCGA divided melanoma based on the mutational profile of the BRAF, RAS, and NF1 genes. Hence, drugs targeting these genes have been considered as melanoma candidate treatments. Nevertheless, resistance to BRAF inhibitor drugs contributes to treatment failure. The mechanisms for drug resistance have been attributed to mutations in different genes (Rajkumar, S et al., 2016)
(Johnson, D. B et al., 2015) (Rodríguez-Cerdeira, C., 2017). Therefore, a promising therapeutic strategy for melanoma patients is multimodality therapy to inhibit several pathways concurrently, such as the MAPK (using trametinib and cobemetinib) and the BRAF
(using vemurafenib or dabrafenib) pathways, which gives a positive effect in the vast majority of melanoma patients (Johnson, D. B et al., 2014) (Rodríguez-Cerdeira, C., 2017).
Immunotherapy is a significant advantage in the treatment of advanced stages of melanoma.
Generally, immunotherapy is defined as the utilization of immune cells to eradicate cancer cells by stimulating the patient's intrinsic immune system. Immunotherapy can be classified into several groups such as cytokines (IL-2, IFN α-2b), immune checkpoint blockade (PD-1,
CTLA-4), oncolytic virus, and by transferring activated T-cells to the tumor-infiltrating lymphocytes (TILs) (TCR-engineered T cell, ACT, and CAR-T) (Yu, C et al., 2019).
Recently, immune checkpoint inhibitors have been utilized for the development of immunotherapy. For metastatic melanoma, ipilimumab, nivolumab, and pembrolizumab have
5 been approved and used for blocking cytotoxic T-lymphocyte-associated antigen 4 (CTLA-4) and programmed death-1 (PD-1). However, immunotherapies showed a limited impact on melanoma patients, and for some, resulted in severe immune-related adverse events (irAEs)
(Kitano, S et al., 2018).
D. Role of p53 in melanoma
A tumor suppressor protein that controls the cellular life cycle, DNA replication, and apoptosis during tumor development is called p53 (Luo et al., 2017) (Kanapathipillai M.
2018). If p53 is mutated, it loses its function, leading to abnormal cell growth
(Kanapathipillai M. 2018). Most human cancers carry a mutated p53 gene, implying that p53 is a critical tumor suppressor gene (Donehower, L. A et al., 1992) (Ozaki, T., & Nakagawara,
A., 2011). The p53 family of proteins share a similar structure with three domains: the sequence-specific DNA-binding domain, the transcriptional activation domain, and the tetramerization domain (Reviewed by Harms, K et al., 2006). The majority of TP53 mutations occurred in the p53 DNA binding domain. In healthy cells, p53 protein is kept at low levels via the regulation of several regulators like MDM2, a p53 ubiquitin ligase protein that capable of initiating degradation (Haupt et al., 1997) (Honda et al., 1997) (Kubbutat et al., 1997) (Kastenhuber, E. R., & Lowe, S. W. 2017). Nevertheless, in response to various biological stresses, p53 is stabilized, including DNA damage and replication stress produced by deregulated oncogenes. Mechanisms that drive p53 activation can be stimulus-dependent: for instance, DNA damage increases p53 phosphorylation, preventing MDM2-mediated degradation (Shieh, S. Y et al., 1997) (Kastenhuber, E. R., & Lowe, S. W., 2017). Promoting cell cycle arrest and apoptosis are the best understood functions of p53 protein. Indeed, fundamental studies conducted in the 90s revealed that p53 is essential for inducing the G1
6 phase checkpoint in response to reversible DNA damage (Kastan et al., 1991) (Kastenhuber,
E. R., & Lowe, S. W. 2017). In cutaneous malignant melanoma, 12-19% of cases exhibited
TP53 somatic mutations (Berger, M. F et al., 2012) (Hugo, W et al., 2016) (Hajkova, N et al.,
2018). However, nearly 90% of cutaneous melanoma cases exhibited inactivation of wild- type p53, with approximately 10% of these cases having inactivating point mutations
(Hocker, T., & Tsao, H. 2007) (Box, N. F et al., 2014). The biology that lies underneath the p53 regulation in melanoma cells and melanocytes must be understood to get a complete view of the potential activation of wild type p53 as a form of therapy. Many studies have shown that melanoma cells are moderately resistant to apoptosis induced by p53.
Furthermore, the expression of p53 protein is induced less effectively in response to UV exposure in melanocytes than in other skin cells like keratinocytes. This suggests that melanocytes' resistance to p53 expression is an intrinsic trait as melanocytes are programmed to last for the whole life of the organism, even with the induction of p53 by oxidative stress
(UV light) of melanin production (Box, N. F et al., 2014). Revealing the mechanisms that determine the low mutational rate of p53 in melanoma and wild type p53 inactivation could drive new ways to induce p53 reactivation in melanoma treatment (Box, N. F et al., 2014).
E. Negative Regulation of p53 by MDM2/MDM4
Known for its ability to negatively regulate the p53 protein is MDM2 (murine double minute
2, also known as HDM2 in humans) (Kubbutat, M. H et al., 1997) (Bohlman, S., & Manfredi,
J. J., 2014). Moreover, Mdm2 is considered to be an E3 ubiquitin ligase that binds to p53 protein to degrade it by ubiquitination (Haupt, Y et al., 1997) (Honda, R et al., 1997)
(Ponnuswamy, A et al., 2012) (Bohlman, S., & Manfredi, J. J., 2014). At the N-terminus of p53, Mdm2 can directly bind, inhibiting the transcriptional activity of p53 for anti-
7 proliferative genes (Momand, J et al., 1992) (Bohlman, S., & Manfredi, J. J., 2014). Overall,
MDM2 can repress the activity of p53 in two significant ways; one is inhibiting the p53 transactivation domain (Momand, J et al., 1992) (Oliner, J. D et al., 1993) (Shadfan, M et al.,
2012), and another way is ubiquitination of p53, which leads to proteasomal degradation
(Haupt, Y et al., 1997) (Kubbutat, M. H et al., 1997) (Shadfan, M et al., 2012). MDM2 is a potent inhibitor of p53 and oncogenic when overexpressed. MDM2 inhibition of p53 is controlled by a negative feedback loop in which p53 transcriptionally stimulates the production of the MDM2 protein, then MDM2 inhibits p53 (Fakharzadeh, S. S et al., 1991)
(Shadfan, M et al., 2012). This negative feedback loop is important for regulating the activity of p53 to prevent the harmful effects of the overactivity of p53. Mice studies have shown that knockdown of MDM2 in mice is embryonic lethal. In the absence of MDM2, p53 becomes overactive, which will lead to excessive apoptosis and eventually, cell death. In contrast, if
MDM4 overexpressed, it will inhibit the p53 function of inducing apoptosis, resulting in continuous growth of cells and eventually, cancers. Therefore, MDM2 at normal level is essential to maintain the p53 function since overexpression of MDM2 leads to carcinogenesis, and the knockdown of MDM2 leads to overactivity of p53 (Montes de Oca
Luna et al., 1995) (Jones, S. N et al., 1995) (Shadfan, M et al., 2012). In addition to its interaction with p53, MDM2 is also a key regulator of MDM4 (alternatively termed MDMX or HDM4, HDMX in humans). MDM4 (a homolog to MDM2) negatively regulates p53, and also MDM4 lacks ubiquitin ligase activity, but still able to bind p53 and suppress its transcriptional activity (Shvarts et al., 1996) (Bottger et al., 1999) (Markey, M., & Berberich,
S. J., 2008). Moreover, the overexpression of MDM4 is found in many cancers like breast cancer (Danovi et al., 2004) (Markey, M., & Berberich, S. J., 2008), uterine cancer, gastric
8 cancer, small intestine cancer, colorectal cancer, lung cancer, and skin cancer (reviewed in
Toledo and Wahl, 2006) (Markey, M., & Berberich, S. J., 2008). MDM4 is encoded on chromosome 1q32.1 in the human genome and consists of 11 exons expressed as several splice variants. MDM2 and MDM4 share a similar structure that consists of four domains: a p53-binding domain at N-terminus, a zinc finger domain, an acidic domain, and a RING domain at the c-terminus (Chen, J et al., 2012) (Haupt, S et al., 2019) (Figure 1). The significant structural difference is that MDM2 has a nuclear export signal and a nuclear localization signal where MDM4 does not (Markey, M., & Berberich, S. J., 2008).
Figure 1. Schematic illustration of the domain structures of p53, MDM2, and MDM4. (A) The domain structure of p53 consists of transactivation domain (TAD) at the N-terminus, a proline-rich domain (PR), a DNA binding core domain (DBD), an oligomerization domain (OD), and regulatory domain (RD) at the C-terminus. (B) MDM2 and MDM4 have related structures with a p53 binding domain at the N-terminus, a zinc finger motif, an acidic domain, and the RING domain at the C-terminus (the RING domain does not have an active E3 ligase activity in MDM4). Updated from (Merkel, O et al., 2017).
9
MDM2 and MDM4 can interact with each other and affect each other functionally. In vitro, homodimerization MDM2 with MDM4 can occur via their RING domains (Sharp, D.
A et al., 1999) (Pei, D., Zhang et al., 2012) Studies have shown that MDM4 stabilizes
MDM2 by interfering with its self-ubiquitination. Nevertheless, some studies suggest MDM2 can also ubiquitinate MDM4 and degrade it (Pan, Y., & Chen, J., 2003) (Pei, D., Zhang, et al., 2012). Other studies indicate that MDM4 competes with MDM2 for the p53 binding site preventing it from degrading p53, leading to the accumulation of p53 (Sharp, D. A et al.,
1999) (Stad, R et al., 2000) (Pei, D., Zhang et al., 2012). In a heteroduplex form, MDM2 and
MDM4 proteins are predominantly found in cells (Kawai, H et al., 2007) (Pei, D., Zhang et al., 2012), implying the heteroduplex form is favored over the homoduplexes form
(Reviewed in Marine, J. C et al., 2006) (Pei, D., Zhang, et al., 2012). MDM2 and MDM4 are both essential for the cell survival, several studies have been performed to determine whether
MDM2 and MDM4 are required or not because each proteins has different role in the regulation of p53, or because both must function as one heterocomplex together (Shadfan, M et al., 2012) (Figure 2). MDM2 and MDM4 are overexpressed in many cancers, including melanoma (Reviewed in Wade, M et al., 2013) (Mrkvová, Z et al., 2019).
10
Figure 2. Two Proposed Models of MDM2 and MDM4 interaction with p53. In the first model, both MDM2 and MDM4 are necessary for inhibiting p53 function because both have a different mechanism by which it represses p53. While MDM2 is responsible for ubiquitination, leading to changes in localization and degradation of p53, MDM4 is required for suppressing p53 by inhibiting the transactivation domain (TAD) of p53. In the other model, MDM2 and MDM4 together form complex for inhibiting p53. In this model, MDM2 and MDM4 are reliant on one another for p53 inhibition. Updated from (Shadfan, M et al., 2012).
F. MDM4 as a Therapeutic Target in Melanoma
In the majority of cutaneous melanomas, the p53 pathway is inactivated due to the overexpression of MDM4 (Reviewed in Marine & Jochemsen, 2005) (Toledo, F., & Wahl,
G. M., 2006) (Gembarska, A et al.,2012). MDM4 is considered oncogenic in melanomas and other cancers due to its role in inhibiting the p53 pathway (Reviewed in Marine, J et al.,
2006) (AbuHammad, S et al., 2019). Interestingly, MDM4 overexpression is observed in roughly 65% of all melanomas (Mrkvová, Z et al., 2019) (Gembarska, A et al.,2012).
Disrupting the MDM4-p53 interaction inhibits the tumorigenesis of melanoma cells
11
(Gembarska, A et al., 2012). A recent study argues that MDM4 inhibition is a more reasonable and less risky strategy than MDM2 inhibition for restoring p53 activity
(Gembarska, A et al.,2012). Targeting MDM4-p53 interaction may have therapeutics potential to enhance BRAF inhibitor therapy. Importantly, targeting MDM4-p53 interaction can be an effective treatment in melanoma when resistance to BRAF inhibitors arises (ibid).
G. Alternative Splicing in Melanoma
Alternative RNA splicing plays a vital part in controlling protein diversity by skipping particular exons and promoting intron retention, leading to the expression of different isoforms with premature stop codons (Reviewed in Graveley, B. R., 2001) (Bardot, B., &
Toledo, F., 2017). Additionally, alternative splicing is a critical process that regulates gene expression (Grellscheid, S et al., 2011) (Ge, Y. et al., 2013) (Bardot, B., & Toledo, F., 2017).
Some previous studies have shown that abnormal splicing promotes cancer (Karni, R et al.,
2007) (Reviewed in Fackenthal, J. D., & Godley, L. A., 2008) (Izaguirre, D. I et al., 2012)
(Ma, F. C et al., 2019). Moreover, altered splicing may generate oncogenic transcript variants. Several studies have identified specific isoforms with clinical utility as that mRNA splicing shows prognostic biomarkers in the lung (Li, Y et al., 2017) (Ma, F. C et al., 2019), ovarian (Zhu, J., Chen, Z., & Yong, L., 2018) (Ma, F. C et al., 2019), breast (Suo, C et al.,
2015) (Ma, F. C et al., 2019), and brain cancers (Pal, S et al., 2014) (Ma, F. C et al., 2019).
However, the need for survival analysis of alternative splicing of MDM4 in melanoma is urgent since no previous studies have assessed MDM4 isoform levels in melanoma (Ma, F. C et al., 2019).
H. MDM4 Splice Variants
12
Studies conducted on human cancers have shown that the abnormal expression of MDM4 in several tumors is associated with WT-p53, suggesting MDM4 may have a vital role in regulating the p53 pathway in cancerous cells. The amplification of the MDM4 gene is frequent in human cancers (Toledo, F., & Wahl, G. M., 2006) (Mancini, F et al., 2009).
Besides the full-length of MDM4 (MDM4-FL), at least five shorter forms of MDM4 have been observed in 31 cancer cell lines (Ramos, Y. F et al., 2001) (Mancini, F et al., 2009).
Only one of these forms has been detected in healthy melanocytes, supporting the theory that the other MDM4 isoforms occur in tumor cells specifically. Since that time, seven shorter
MDM4 isoforms have been identified. All of these variants resulted from alternative splicing
(Figure 3) (Mancini, F et al., 2009).
The first transcript variant discovered in mice and in human cells was MDM4-S
(Rallapalli, R et al., 1999) (Mancini, F et al., 2009). Human MDM4-S arises from an internal deletion of 68 base pairs in exon 6. This deletion changes the reading frame following codon
114 and introduces a new termination codon after amino acid 140, resulting in a truncated protein that harbors the first 114 amino acids of the MDM4-FL (the whole p53 binding domain), so MDM4-S can interact with p53 ( Reviewed in Marine, J. C., & Jochemsen, A.
G., 2005) (Mancini, F et al., 2009). MDM4-S affinity toward p53 is around 10-fold higher than MDM4-FL. As a result, MDM4-S is a more powerful suppressor of the transcriptional activity of p53. A nuclear and cytosolic fractions analysis suggests that endogenous MDM4-
S is located inside the nucleus. Interestingly, it has been hypothesized that the transcriptional repression of p53 by MDM4-S is the reason for its oncogenic potential (Rallapalli, R et al.,
1999) (Rallapalli, R et al., 2003) (Mancini, F et al., 2009).
13
MDM4-A has no acidic domain due to the deletion of 225-274 amino acids. As a consequence, MDM4-A is suspected to have a strong susceptibility to being degraded by
MDM2, suggesting the importance of the acidic domain in MDM4-FL stability. Although comprehensive studies are needed to elucidate the mechanism that causes MDM4-A destabilization, it has been shown that the MDM4 acidic region may mask the MDM2 acidic region and repress its ubiquitination activity, particularly toward p53, which also relies on the existence of the acidic domain. Therefore, MDM4-A may have oncogenic function by degrading MDM2 (de Graaf, P et al., 2003) (Mancini, F et al., 2009).
The isoform MDM4-G lacks the p53-binding domain due to an in-frame deletion of
27-124 amino acids. However, MDM4-G lacks the p53-binding domain, but can still inhibit p53 activity by stabilizing MDM2 levels, but this inhibition is less pronounced than the inhibition by MDM4-FL (Mancini, F et al., 2009).
MDM4-211 is an isoform of MDM4 reported in a thyroid tumor cell line which results from an aberrant splicing event between the exon two donor site and exon eleven acceptor site of the full-length MDM4. This variant harbors the first 26 amino acids and the last 138 amino acids of MDM4-FL. Moreover, MDM4-211 lacks the p53 binding domain, so it does not bind p53. Instead, MDM4-211 is able to bind MDM2 at the C-terminus and maintains MDM2 protein stability by boosting the half-life of the protein. In particular,
MDM4-211 appears to be capable of inhibiting MDM2 degradation function, prompting stabilization of p53 (Giglio, S et al., 2005) (Mancini, F et al., 2009).
In 2006, Lozano’s group discovered in some human tumor cell lines two splice variants of MDM4, named ALT1 and ALT2 (Chandler, D. S et al., 2006) (Mancini, F et al.,
2009). Both ALT1 and ALT2 derive from a splicing event, but in ALT1, the event takes
14 place between exon five and exon ten wherein ALT2, it happens between exon three and exon ten. ALT1 maintains the p53 binding domain, so presumably it can inhibit the p53 function. In contrast, ALT2 lacks the p53 binding domain and maintains the COOH-terminal
RING finger domain. MDM4-ALT2 may bind MDM2 or MDM4-FL and modulate their role.
An analogous isoform to MDM4-ALT2 that has been identified as MDM2-ALT2. (Chandler,
D. S et al., 2006) (Mancini, F et al., 2009). No protein product has been detected for ALT1 or
ALT2. Responding to DNA damage agents cisplatin and doxorubicin, a study revealed that
MDM4-FL mRNA decreased in vivo and in vitro. Presumably, this decrease was not a result of changes in promoter activity but was corresponding with an increase in the splice variant
ALT2. ALT1 showed no change in response to DNA damage (Reviewed in Markey., 2011).
No study has thus far determined what actual splice variants of MDM4 are expressed in melanoma. Because different variants contain different exons, splicing of MDM4 in melanoma may be important in designing molecules targeted to the MDM4 protein.
Interestingly, we found that MDM4-A is commonly expressed in melanoma cases and has the potential to cause melanogenesis.
15
Figure 3. Schematic representation of MDM4 mRNA organization in exons (according to the GeneBank NM 002393). (A) paralleled the structure of the MDM4 protein regions. Exons are numbered consecutively and boxed in approximate scale (B) MDM4 alternative transcripts. represents the forward primer used in these studies. The reverse primer is represented as . Dashed lines span novel exon junctions. RT-PCR amplicon sizes are indicated at right. Primers not drawn to scale. Adapted from (MDM4 (MDMX) and its Transcript Variants, Siebring-van Olst et al., Current Genomics, 2009,10:42-50).
16
II. MATERIAL AND METHODS
1. Collecting FFPE Samples.
A total of 40 formalin-fixed, paraffin-embedded (FFPE) specimens (30 malignant
melanomas and 10 benign melanocytic nevi) were collected from American
Dermatopathology Laboratory. For melanoma samples (case 1 to 30), clinical diagnostic
details concerning melanoma patients were provided by American Dermatopathology
Laboratory, including the patient's age at diagnosis, the patient's sex, the biopsy site, Breslow
thickness, the tumor staging, nevus association, and the Castle Class (Table 1). For the
benign nevi, clinical information about the patients was obtained from American
Dermatopathology Laboratory, including the patient's age at diagnosis, patient's gender, and
biopsy site (Table 2).
Table 1: Melanoma samples. Cases listed with patients’ age, gender, biopsy site, size, staging, associated nevus, and Castle Class. Castle's DecisionDx-Melanoma test is a 31-gene expression profile that determines a patient's risk for metastatic disease using tissue from the primary melanoma. The tool classifies patients as having a tumor with low or high risk for developing metastasis within five years of diagnosis (Castle Bioscience). The TNM is a universally accepted standard for classifying the degree of cancer spreading (NIH). Breslow thickness is a prognostic factor in melanoma used to determine the depth of tumor invasion (Breslow Alexander., 1970).
17
Cases Patient Age Patient Sex Biopsy Site Breslow Thickness TNM Staging Assoc. Nevus (Y or N) Castle Class # Case 1 49 M Right Upper Back PS 0.5mm pT1a, Nx, Mx; STAGE IA Y 1A Case 2 55 M Right Back 1.5mm pT2a, Nx, Mx; STAGE IB N 1B Case 3 67 M Left Ear 1.6mm pT2a, Nx, Mx; STAGE IB N 1A Case 4 50 M Left Medial Calf 2.5mm pT3b, Nx, Mx; STAGE IIB N 2B Case 5 53 M Right Superior Upper Back 0.4mm pT1a, Nx, Mx; STAGE IA N 1A Case 6 33 F Left Posterior Shoulder 0.4mm pT1a, Nx, Mx; STAGE IA Y 1A Case 7 53 M Right Inner Thigh 0.8mm pT1b, Nx, Mx; STAGE IB N 1B Case 8 68 M Nose 0.5mm pT1b, Nx, Mx; STAGE IB N 2A Case 9 64 M Right Calf 0.6mm pT1b, Nx, Mx; STAG IB N 1B Case 10 74 M Left Forearm Proximal 2.1mm pT3b, Nx, Mx; STAGE IIB N 2B Case 11 70 M Left Upper Arm 0.3mm pT1a, Nx, Mx; STAGE IA N 1A Case 12 71 M Right Posterior Shoulder 0.3mm pT1A, Nx, Mx; STAGE IA N 1A Case 13 71 M Left Forearm 1.5mm pT2a, Nx, Mx; STAGE IB N 2B Case 14 29 F Right Upper Helix 0.5mm pT1a, Nx, Mx; STAGE IA N 1A Case 15 39 M Right Anterior Deltoid 1.1mm pT2a, Nx, Mx; STAGE IB Y 1A Case 16 58 F Left Upper Arm 0.9mm pT1b, Nx, Mx; CLINICAL STAGE IB N 1A Case 17 63 F Left Upper Arm 0.9mm pT1b, Nx, Mx; STAGE IB Y 1A Case 18 83 M Scalp 1.7mm pT2a, Nx, Mx; STAGE IB N 2A Case 19 73 M Vertex 0.5mm pT1a, Nx, Mx; STAGE IA N 1A Case 20 67 M Right Arm 0.4mm pT1a, Nx, Mx; STAGE IA Y 1A Case 21 43 F Right Abdomen 0.4mm pT1a, Nx, Mx; STAGE IA Y 1A Case 22 61 F Right Thigh 0.9mm pT1b, Nx, Mx; STAGE IB Y 1A Case 23 68 F Left Ant. Prox. Thigh 0.7mm pT1a, Nx, Mx; STAGE IA N 1A Case 24 73 F Right Upper Post. Arm 2.5mm pT3b, Nx, Mx; STAGE IIB N 2B Case 25 71 F Left Post. Shoulder 0.4mm pT1a, Nx, Mx; STAGE IA N 1A Case 26 79 M Right Post. Calf 1.2mm pT2b, Nx, Mx; STAGE IIA N 2A Case 27 57 F Left Post. Deltoid 0.5mm pT1a, Nx, Mx; Stage IA N 1A Case 28 47 F Top Scalp 4.1mm pT4b, Nx, Mx; Stage IIC N 2B Case 29 70 M Right Lower Leg 0.8mm pT1b, Nx, Mx; STAGE IB N 1A Case 30 77 M Back of Neck 5.0mm pT4b, Nx, Mx; STAGE IIC N 2B
Table 2: Nevi samples. Cases listed with patients’ age, gender, the biopsy site.
Patient Patient Cases Age Sex Bioposy Site Case 31 14 F Right T4 Case 32 32 F Left temple Case 33 34 F Right antecubital Case 34 60 F Left mid. Lat. Low. Extremity Case 35 2 M Might medial forearm Case 36 49 F Left medial thigh Case 37 41 F Right mid. Inframammary fold Case 38 54 F right alar crease Case 39 15 F right dorsal forearm Case 40 25 F Right posterior thigh
2. Primer Design for MDM4 splice variants
The sequence of MDM4 isoforms obtained from the Ensembl genome browser was used for primer design. The transcript sequences were as follows (Forward): MDM4-Fl, 5′-
18
AGATGCTGCTCAGACTCTCG -3′. MDM4-211, 5′- CTCCTGGACAAATCAATCAGGAAA -
3′. MDM4-Alt1, 5′- CAGGTGCGCAAGGTGAAATG -3′. MDM4-Alt2, 5′-
ACTGTTAAAGAGGTGATTGAAGTGG -3′. MDM4-A, 5′- CACACTGCCTACCTCAGAGC -
3′. MDM4-G, 5′- CCTGGACAAATCAATCAGGATCAC -3′. MDM4-S, 5′-
CAGCAGGTGCGCAAGGTGAA -3′. B-Actin (negative control), 5′-
TTCCTATGTGGGCGACGAG -3′. The reverse primers were as the following: MDM4-Fl, 5′-
TCAGGATGTGGGTACTGCCA -3′. MDM4-211, 5′- TGATCCCTGCAACTCAGTGG -3′.
MDM4-Alt1, 5′- ACTACAGGTGATTGAAGTGGGA -3′. MDM4-Alt2, 5′-
TGATCCCTGCAACTCAGTGG -3′. MDM4-A, 5′- GACAAATCAGGTGATTGAAGTGGG -
3′. MDM4-G, 5′- TATCCCCACACTGCCTACCT -3′. MDM4-S, 5′-
CACTGCTACTACAGCAAAGTG -3′. B-Actin, 5′- CGTGTGGCTCCCGAGGA -3′.
3. RNA Extraction & Purification from FFPE tissues
RNA was extracted from FFPE specimens using the truXTRAC FFPE RNA Kit (Covaris,
Woburn, MA) and a M220 System and following the manufacturer's protocol. All 40 samples
were treated with RNA Lysis, RNA Wash, RNA Elution, B1 Buffer, DNase Buffer, DNase I,
PK Solution, MnCl2 Solution, Ethanol (>96%), and nuclease free water. All samples were
incubated in a dry heat block for two phases, wherein the first phase (proteinase K digestion
at 56°C) samples were incubated for 15 minutes, the second phase (crosslink reversal at
80°C) samples were heated for 60 minutes. All samples were centrifuged. Once the RNA
purification process was completed, sample RNA was quantified by Nanodrop (Table 3) and
stored immediately at -80°C.
Table 3: The amount of RNA in each sample after RNA extraction and purification process. RT stands for reverse transcriptase, an enzyme that generates complementary strand
19
(cDNA) from RNA. The first two cases were transcribed with Oligod(T) primers and the rest with Random Hexamer.
4. cDNA Synthesis and RT-PCR
500 ng of RNA was reverse transcribed with 50 ng/µl random hexamers or 500 ng/µl Oligo
d(T) primer using The SuperScript IV CellsDirect cDNA Synthesis Kit (Applied
Biosystems). The first two samples were transcribed with 50 uM Oligo d(T), but the rest
were transcribed with 50 ng/µl random hexamers. We switched from Oligo d(T) to random
hexamers because Oligo d(T) highly specific and cDNA synthesis has to start from the 3′ end
where to random hexamers is more effective reliable for our FFPE samples since its capable
to prime the fragmented mRNA. However, the reverse transcription of the first two samples
worked successfully and showed that we have long mRNA from our FFPE samples. For the
RT-products, each product was prepared in accordance to Promega’s instructions for a 25 µ/l
reaction volume [12.5 µl GoTaq® Green Master Mix, 1 µl upstream primer, 1 µl
20 downstream primer, 2 µl DNA template, and 8.5 µl Nuclease-Free water] and PCR was performed for 2 minutes at 95°C (the initial denaturation); 30 sec at 95°C; 30 sec at 55°C; 30 sec at 73°C; 5 minutes at 73°C (a final extension) (Applied Biosystems). Then, RT- products were placed on a 2% agarose TBE gel, 2 µl of SYBR safe stain was added, 5 µl of 50bp ladder (Manufacturer, City) was loaded, gels were run on 100 V constant for approximately
60 minutes. Gels imaged on Amersham™ Imager 600 (Manufacturer, City).
5. MDM4 Isoform Analysis
Gene mutation frequency in melanoma obtained from the data set “skin cutaneous melanoma” (SKCM-US), a 466 subject study of melanoma patients in the United States
(Akbani et al., 2015) and analyzed using the International Cancer Genome Consortium data portal (Lawrence et al., 2013, p. 217). The results presented here are based upon data obtained from the TCGA Research Network: https://www.cancer.gov/tcga. TCGA copy number data for SKCM were analyzed using Oncomine (Rhodes, 2020). TCGA survival data for SKCM were analyzed using OncoLnc (Anaya, 2016). Isoform-specific expression data for MDM4 in normal skin were analyzed in Genotype-Tissue Expression (GTEx) data portal.
The data used for the analyses detailed in this manuscript were obtained from the GTEx
Portal and dbGaP accession number phs000424.v8.p2 on 5/29/2020. For melanoma, isoform-specific expression data were obtained from the Patient Derived Model Database
(PDMDB). TPM isoform data were filtered for disease body location “skin” plus CTEP SDC description “melanoma”. UCSC Genome Browser isoform identifiers were matched to transcripts modeled in Ensembl in order to compare with GTEx data. Kaplan-Meier analysis of TCGA data for specific isoforms of MDM4 was performed using Psichomics (Saraiva-
21
Agostinho N et al., 2019) in Bioconductor. TCGA exon expression and survival data were interpreted commensurate with the inclusion of MDM4 exon 9 and the skipping of exon 9.
6. Statistical Analysis
An unpaired t-test was performed to assess the statistical significance in comparing Castle
Class versus isoform presence in the 30 melanoma specimens. P (two-tailed) values of less than 0.05 of MDM4 isoforms in the 30 melanoma samples were considered statistically significant.
22
III. RESULTS
i. Mutational gene analysis indicates that most melanomas have intact p53
Mutations in the p53 protein are frequent genetic alterations seen in human tumors (Rady et
al., 1992) (Greenblatt et al., 1994) (Hollstein et al., 1994) (Hollstein et al., 1996) (Hainaut et
al., 1997) (Zerp, S et al., 1999). The p53 protein is associated with several biological
processes that control the proliferation and survival of cells. Amplifications in the p53
protein frequently occur in skin cancers (Brash et al., 1991) (Rady et al., 1992) (Campbell et
al., 1993) (Moles et al., 1993) (Zeigler et al., 1993) (Zerp, S et al., 1999). Several data have
revealed that genetic alterations in the p53 gene happen onset of carcinogenesis. Moreover,
studies conducted in animal models showed frequent mutations of the p53 gene in animal
tumors generated by UV-B treatment (Kanjilal et al., 1993) (van Kranen et al., 1995) (Zerp, S
et al., 1999). Some data suggest that the occurrence of p53 mutations in primary melanomas
is more frequent than in metastases (Zerp, S et al., 1999). Several genetic mutations are
involved in tumorigenesis of melanoma, and one way to understand the genetics of
melanoma is by determining the frequency of genes mutated in it. Therefore, we collected
data from the TCGA project to investigate the frequency of genes mutated in melanoma.
Surprisingly, we found that around 90% of melanoma subjects possess an intact p53 gene
and 50% of melanoma subjects have BRAF mutation (Figure 4). p53 mutations were more
commonly found in BRAF tumors than in Triple-WT, in which MDM2 amplification was
more common (TCGA., 2015). Next, we wanted to compare the amplification of both
MDM2 and MDM4 in melanoma to normal cells since both are negative regulators of p53.
23
Figure 4. Most melanomas have an intact p53 gene. Tumors from 466 melanoma subjects in the United States were tested for simple somatic mutations as part of the TCGA study SKCM-US (Akbani et al., 2015). Genes were ranked by the frequency of mutation. The top 20 results are shown. ii. MDM4 is more frequently amplified in melanoma than MDM2
MDM2 is commonly overexpressed in several cancers like gliomas, melanomas, sarcomas,
hematological malignancies, and carcinomas. Similarly, MDM4 is also largely overexpressed
in many human cancers (Li, Q., & Lozano, G., 2013). The amplification and the
overexpression of MDM4 were observed in different cancers such as melanoma, glioma,
squamous carcinoma, soft tissue sarcoma, retinoblastoma, and breast cancer (Li, Q., &
Lozano, G., 2013). We wanted to compare the amplification of MDM2 to the amplification
of MDM4 in melanoma. In that, we obtained copy number variation data again from TCGA
for the genes MDM2 and MDM4. The blood samples are normal karyotypes for patients,
which were compared to melanomas. Figure.5 shows the relative change in copy number
versus normal. Interestingly, MDM2 copy number in melanoma was very similar to copy
number in blood, suggesting that MDM2 is poorly amplified in melanoma (Figure 5A).
Conversely, the copy number of MDM4 in melanoma was higher, indicating that MDM4 is
24
amplified in melanoma (Figure 5B). This data suggests that MDM4 amplification is more
frequent than MDM2 amplification in melanoma and emphasizes on the importance of
MDM4 in melanoma. This brings up the question if the amplification of MDM4 have clinical
significance or not.
Figure 5. MDM4 is frequently amplified in melanoma, in contrast with MDM2. Skin cutaneous melanoma data from TCGA with copy number data available for tumor and matched normal tissue (blood) were analyzed for amplification or deletion of the genes MDM2 (a) and MDM4 (b). Log2 copy number is normalized to the copy number in blood. iii. The expression of MDM4 and survival in melanoma
To investigate whether or not MDM4 expression contributes to the poor survival in
melanoma cells, we collected TCGA survival data for melanoma and performed Kaplan-
Meier analysis to determine the impact of MDM4 expression in melanoma. The expression
of MDM4 separated into two groups: red group (the upper quartile of MDM4 expression)
and blue group (the lowest quartile of MDM4 expression), as shown the Figure 6 below.
Interestingly, total MDM4 expression as measured here did not correlate with survival.
25
Figure 6. MDM4 expression does not significantly correlate with patient survival. TCGA survival data for skin cutaneous melanoma were separated by expression of MDM4. The “High” group (red) had expression of MDM4 in the top 25% of available subjects. “Low” (blue) subjects were in the bottom 25% of expression for MDM4. N for each group is 114 subjects. Kaplan-Meier analysis indicates not significant difference in, log rank p-value = 0.247. iv. The expression of MDM4 splice variants in sun exposed skin is similar in non-sun exposed skin.
Before looking into our melanoma and nevi samples, we wanted to look into normal skin
data to compare later the results of normal skin to cancerous skin. We used publicly available
GTEx portal data to compare the expression of the MDM4 isoforms between sun-exposed
and not sun-exposed. Interestingly, expression of all MDM4 isoforms was very similar
between sun-exposed and non-sun exposed skin. MDM4-A was absent in both exposed and
non-exposed sun skin (Figure 7).
26
Figure 7. MDM4 isoform expression in normal skin. Non-sun exposed (suprapubic) skin specimen data from 604 subjects and sun-exposed (lower leg) skin specimens from 701 subjects were analyzed in the GTEx data portal. Normalized reads x100 for each indicated isoform of MDM4 are displayed. Isoforms are labeled using their common names. The Transcript Support Level (TSL) is designed to highlight the well-supported and poorly supported transcript patterns. Ensembl transcript evidence level 1 (TSL1) transcripts are in bold. *This Ensembl transcript shares a name with the transcript commonly called MDM4-211. **Two transcripts encode MDM4-S. v. Comparing Castle Class to isoforms presence statistically showed MDM4-S is significant in melanoma samples
We collected a total of 40 samples (30 melanoma + 10 nevi). In melanoma specimens, 18 out
of 30 were classified as 1A, 3 patients’ samples were on level 1B, 4 cases diagnosed as 2A,
and lastly, the remaining 6 were classified as 2B. MDM4-A was the most common isoform
to be expressed in patients that were diagnosed as 1A Castle Class as we compared the
isoform presence to the castle class. We performed an unpaired t-test to assess the statistical
significance of MDM4 isoforms, and we found MDM4-S was significantly the highest
(Figure 8).
27
Figure 8. Statistical significance analysis of MDM4 isoforms in melanoma specimens. Castle Class did not vary significantly by MDM4 isoform expression (p>0.05). MDM4-211 was not detected in our samples. vi. MDM4-A is the most common alternative transcript expressed in melanoma samples Previous studies have shown that amplification and overexpression of MDM4 is typically
observed with suppression of the p53 pathway in human tumors (Riemenschneider, M. J et
al., 2003) (Wasylishen, A. R et al., 2016) (Pant, V et al., 2017). Additionally, some studies
have pointed to the MDM4 spliced variant expression in several cancers, especially in
melanoma (Bartel, F et al., 2005; Mancini, F et al., 2009; as cited in Pant, V et al., 2017),
where MDM4 observed a high level of expression in about 65% of cases (Gembarska, A et
al.,2012). However, no work thus far has been conducted on what spliced variants of MDM4
are expressed in melanomas. Therefore, we sought to determine which variants are expressed
in our FFPE samples, so we performed RT-PCR for each sample. The full-length MDM4
mRNA (MDM4-FL) was expressed in about 53% of melanoma samples and 40% of normal
skin (nevi or benign). The alternative transcripts MDM4-G and MDM4-S were similarly
28 expressed but not signifcantly more in the nevi specimens than in malignant specimens. By contrast, the splice variant MDM4-Alt2 was frequently expressed in melanoma specimens and less so in nevi samples. The expression of the isoform MDM4-211 was not detected in either our melanomas or benign specimens. Moreover, the alternative transcript MDM4-Alt1 was expressed in only one sample of benign melanocytic nevus. MDM4-A was the most common transcript expressed in malignant melanoma. All the results of the FFPE samples are shown in the below Table 4.
Table 4: Summary of RT-PCR results in melanoma and nevi samples. The First 30 cases are for melanoma patients and cases from 31 through 40 are nevi. (-) means no expression was detected. (+) means expression was detected. The details for each case were provided in Table 1 and Table 2.
Cases MDM4-G MDM4-A MDM4-S XAlt1 XAlt2 MDM4 -211 FL Case 1 + + + - + - + Case 2 - + + - + - + Case 3 + + + - + - + Case 4 + + + - + - + Case 5 - + + - + - + Case 6 - - + - + - + Case 7 - + + - + - + Case 8 + + + - + - + Case 9 - + + - + - + Case 10 - + + - + - + Case 11 - + + - + - + Case 12 + + + - + - + Case 13 + + + - + - + Case 14 - + + - + - + Case 15 - + + - + - + Case 16 - + - - - - - Case 17 - + + - + - + Case 18 - + + - + - - Case 19 + + + - - - - Case 20 + + + - + - -
29
Case 21 - + + - - - - Case 22 - + + - - - - Case 23 + + + - - - - Case 24 + + + - - - - Case 25 - - - - + - - Case 26 - + + - - - - Case 27 - + + - - - - Case 28 - + + - - - - Case 29 - + - - - - - Case 30 - + + - - - - Case 31 + + + - - - - Case 32 - - + - + - - Case 33 + + + - + - + Case 34 + + + - + - + Case 35 + + + - - - + Case 36 + + + - + - + Case 37 + + + - + - - Case 38 - + - - - - - Case 39 + + + + - - - Case 40 - + + - + - - vii. Isoform specific expression analysis showed consistent expression of the alternative transcript MDM4-A. The Patient-Derived Model Database (PDMDB) is a database containing expression data for
various tumor types, including melanoma. Data obtained from PDMDB were analyzed and
found MDM4-211 and MDM4-A in addition to the full-length MDM4 expressed in
melanoma patients. The MDM4-FL was expressed in 43% of melanoma patients. MDM4-
211 was expressed in about 0.0046% of melanoma patients, which correlates with our FFPE
biopsy results. MDM4-A was the most common isoform expressed by in 57% of melanomas
(Figure 9A). In contrast, the full length MDM2 (isoform MDM2-A here) was the almost
exclusively detected in the PDMDB database (Figure 9B). Both PDMDB data and FFPE
specimens’ results (Figure 9C) suggest that MDM4-A may act as an oncogene.
30
Figure 9. MDM4 isoform expression in melanocytic lesions is different from normal skin. Isoform-specific expression data were compared for 120 patient-derived xenografts. The percentage of total MDM4 transcripts represented by each isoform is indicated. (a) Expression of the alternative transcript MDM4-A is significantly more common than expression of the full length MDM4 transcript in these specimens (students t-test p-value
31
= 1.386 x10-13). (b) In contrast, MDM2 expression is almost entirely the full-length transcript designated MDM2-A. (c) Analysis of 30 clinical melanoma specimens and 10 melanocytic benign nevi by isoform-specific RT-PCR. viii. MDM4-A isoform correlates with poor survival in melanoma Here, we wanted to test whether MDM4-A correlates to melanoma survival. We used TCGA
samples with exon expression data and survival data to investigate the correlation of MDM4-
A with survivorship in melanoma. Our analysis was based on including MDM4 exon 9 and
skipping of exon 9 (MDM4-A skips exon 9). Significantly, the survival of cases where
MDM4-A represented ≥80% of transcripts had notably higher survival than cases where
≥80% of transcripts lacked exon 9, suggesting that MDM4-A correlates with reduced
survivorship in melanoma (Figure 10).
Figure 10. MDM4-A isoform correlates with poor survival. TCGA samples with exon expression data and survival data were analyzed based on inclusion of MDM4 exon 9. Skipping of exon 9 indicates MDM4-A. The survival of subjects with an exon 9 percent spliced in (PSI) greater than 0.8 (indicating inclusion of exon 9 seen in ≥80% of transcripts) had significantly higher survival than subjects where ≥80% of transcripts skipped exon 9 (log-rank p-value = 0.00472).
32
IV. DISCUSSION
Many environmental and genetic factors influence the tumorigenesis of melanoma, including
sun exposure, which is the most significant environmental risk factor for melanoma
development because it damages the DNA (Landi, M. T et al., 2020). The p53 pathway
becomes activated in response to DNA damage (Luo et al. 2004) (Williams, A. B., &
Schumacher, B., 2016). Other risk factors that give rise to melanoma development are family
history, skin color, and many freckles and moles on the skin (Landi, M. T et al., 2020).
Melanoma development and progression are recognized by chromosomal deletions,
proliferation, and gene alterations (Chin et al., 2006) (Staibano, S et al., 2011). Studies on
gene expression of melanomas showed that melanomas have many genetic mutations.
(Fecher et al., 2007) (Ryu et al., 2007) (Staibano, S et al., 2011), including BRAF mutations,
KIT mutations, and Plexin B1 mutations (Staibano, S et al., 2011). In addition to these
mutations, the p53 pathway inactivation found to be a common theme in melanoma,
considering 90% of melanoma cases retain WT p53 (Hocker, T., & Tsao, H. 2007) (Box, N.
F et al., 2014). The p53 pathway is negatively regulated by MDM2 and its homolog MDM4
in many cancers, including melanoma (Reviewed in Wade, M et al., 2013) (Mrkvová, Z et
al., 2019). Our data showed that most melanoma patients have a high percentage of intact
p53, as shown in (Figure 4).
A study reported that MDM4 is overexpressed in about 65% of melanoma cases
(Gembarska, A et al.,2012), pointing to the importance of studying MDM4 overexpression in
melanoma. Additionally, MDM4 can suppress the p53 activity solely by indirect negative
regulation or by heterodimerization with MDM2. However, we found that the MDM4 gene is
more amplified than MDM2 in melanoma (Figure 5). Our analysis of MDM4 isoforms in
33 normal skin showed no MDM4-A expression (Figure 7). However, and to date, no previous studies have been performed on determining which isoforms are expressed in melanoma cells.
We found that our melanoma and nevi specimens appear remarkably similar in their
MDM4 isoforms profiles. Two of the alternative transcripts of MDM4 were expressed frequently in 90% of our samples (Table 4). MDM4-ALT1 and MDM4-211 transcripts were not seen in melanoma cases. Importantly, among all MDM4 isoforms, MDM4-A was the most common isoform expressed in our melanoma samples (Figure 9). We performed analyses that suggested that MDM4-A was linked to poor survival of melanoma (Figure 10), even though total MDM4 expression was not (Figure 6). Together, our results suggest a model where aberrant splicing of MDM4 occurs early in carcinogenesis, MDM4 is more commonly amplified than its homolog MDM2, that splicing changes of MDM4 are more observed in early stages than MDM2 splicing, and that supports the likelihood that MDM4-A is an oncogenic variant that promotes oncogenesis (Figure 11).
It is interesting that the unexpressed transcripts in melanoma samples, Alt1 and 211, have some of the least evidence for their role in cancer. Currently, ALT1, in response to
DNA damage, might limit the activity of p53 (Mancini, F et al., 2009). MDM4-211 is linked to cancer formation in the presence of p53 and MDM2 (Reviewed in Markey M. P., 2011). It is more important to note that our results are based on qualitative analysis (what is isoform expressed) but not quantitative analysis (how much is expressed). Although we attempted quantitative PCR analysis on one sample, we found the quantitative approach using FFPE samples to be noisy. Therefore, it may be that some of these variants are expressed more highly than others, which is suggested by MDM4-G consistently giving a faint band. The
34 expression of MDM-G and MDM4-Alt2 is particularly interesting because these two lack the full p53 domain. The first two samples, primed with oligo-d(T) primers, produced RT-PCR results despite the primers binding far upstream of the 3’ poly-A tail. This suggests a minimum length of approximately 10kb that must be present in the purified mRNA. This raises the possibility of using long-read sequencing (such as Oxford Nanopore sequencing) to quantify specific transcripts. This would also have the advantage of identifying novel transcripts not previously reported. This remains an important future direction.
The value of this study is to highlight the importance of isoforms expression on melanoma to improve the treatment of melanoma. The drug vemurafenib has been used to cure metastatic melanoma and showed some success in curing melanoma. However, this drug only functions effectively in patients who have BRAF mutations (Gembarska, A et al.,2012).
Recently, some melanoma patients manifested resistance to vemurafenib, highlighting the urgent need for new strategies to treat melanoma (Gembarska, A et al.,2012). Our data suggest that MDM4-A may correlate with the oncogenesis of melanoma, and considering
MDM4-A as a therapeutic target in melanoma could drive to positive clinical outcomes
(Figure 11). Further study is needed to determine how highly this isoform is expressed in melanoma cells compared to normal skin and precancerous lesions.
35
Figure 11. Model of Carcinogenesis of melanoma with timeline of MDM2/4/p53 changes. Acral melanoma has some initiating event besides UV light. Throughout progression from normal skin to metastatic disease, most cases retain wild type p53 and demonstrate normal splicing and normal copy numbers of MDM2. In contrast, changes in MDM4 splicing are already in place in melanocytic nevi. MDM4 tends to be amplified in melanomas, and the profile of mRNA isoforms expressed is different from normal skin. MDM2 is relatively unchanged. This emphasizes the importance of MDM4 in melanoma.
36
V. FUTURE DIRECTIONS
The project MDM4 alternative splicing may need an increase in the number of specimens,
especially to compare the expression of MDM4-A in melanoma samples to nevi samples.
Since we did not detect the presence of MDM4-211, it would be suited to have a positive
control for it. Also, a survival analysis of MDM4-G is warranted because there is some
apparent difference in its presence between the melanoma and nevi specimens. Other MDM4
isoforms such as MDM4-B and MDM4-C can be tested for presence in melanoma and nevi
specimens. Additionally, we will use expression and mutation data of genes in the MDM4
regulatory axis to determine which mechanisms control p53 activity in melanoma. Exon
expression and splice junction data could be used to predict the function of observed MDM4
transcript variants and identify novel transcripts. Direct cDNA sequencing analysis could be
performed with long-read sequencing and analyzed with tools such as TALON to annotate
and quantify the known and novel alternative mRNA transcripts of the gene MDM4 in
cancer.
37
VI. REFERENCES:
AbuHammad, S., Cullinane, C., Martin, C., Bacolas, Z., Ward, T., Chen, H., Slater, A.,
Ardley, K., Kirby, L., Chan, K. T., Brajanovski, N., Smith, L. K., Rao, A. D., Lelliott,
E. J., Kleinschmidt, M., Vergara, I. A., Papenfuss, A. T., Lau, P., Ghosh, P., Haupt,
S., … Sheppard, K. E. (2019). Regulation of PRMT5-MDM4 axis is critical in the
response to CDK4/6 inhibitors in melanoma. Proceedings of the National Academy of
Sciences of the United States of America, 116(36), 17990–18000.
https://doi.org/10.1073/pnas.1901323116
Akbani, R., Akdemir, K. C., Aksoy, B. A., Albert, M., Ally, A., Amin, S. B., … Zou, L.
(2015). Genomic Classification of Cutaneous Melanoma. Cell, 161(7), 1681–1696.
https://doi.org/10.1016/j.cell.2015.05.044
Ali, Z., Yousaf, N., & Larkin, J. (2013). Melanoma epidemiology, biology and prognosis.
EJC supplements : EJC : official journal of EORTC, European Organization for
Research and Treatment of Cancer ... [et al.], 11(2), 81–91.
https://doi.org/10.1016/j.ejcsup.2013.07.012
Anaya, J. (2016, June 13). OncoLnc: linking TCGA survival data to mRNAs, miRNAs, and
lncRNAs. Retrieved from https://peerj.com/articles/cs-67/
Ascierto, P. A., Grimaldi, A. M., Anderson, A. C., Bifulco, C., Cochran, A., Garbe, C.,
Eggermont, A. M., Faries, M., Ferrone, S., Gershenwald, J. E., Gajewski, T. F.,
Halaban, R., Hodi, F. S., Kefford, R., Kirkwood, J. M., Larkin, J., Leachman, S.,
Maio, M., Marais, R., Masucci, G., … Thurin, M. (2014). Future perspectives in
melanoma research: meeting report from the "Melanoma Bridge", Napoli, December
38
5th-8th 2013. Journal of translational medicine, 12, 277.
https://doi.org/10.1186/s12967-014-0277-z
Balazs, M., Ecsedi, S., Vizkeleti, L., & Begany, A. (2011b). Genomics of Human Malignant
Melanoma. Breakthroughs in Melanoma Research. https://doi.org/10.5772/21339
Balch, C. M., Soong, S., Ross, M. I., Urist, M. M., Karakousis, C. P., Temple, W. J., Mihm,
M. C., Barnhill, R. L., Jewell, W. R., Wanebo, H. J., & Harrison, R. (2000). Long-
term results of a multi-institutional randomized trial comparing prognostic factors and
surgical results for intermediate thickness melanomas (1.0 to 4.0 mm). Intergroup
Melanoma Surgical Trial. Annals of surgical oncology, 7(2), 87–97.
https://doi.org/10.1007/s10434-000-0087-9
Bardot, B., & Toledo, F. (2017). Targeting MDM4 Splicing in Cancers. Genes, 8(2), 82.
https://doi.org/10.3390/genes8020082
Bartel, F., Schulz, J., Böhnke, A., Blümke, K., Kappler, M., Bache, M., Schmidt, H., Würl,
P., Taubert, H., & Hauptmann, S. (2005). Significance of HDMX-S (or MDM4)
mRNA splice variant overexpression and HDMX gene amplification on primary soft
tissue sarcoma prognosis. International journal of cancer, 117(3), 469–475.
https://doi.org/10.1002/ijc.21206
Bauer, J., & Garbe, C. (2003). Acquired melanocytic nevi as risk factor for melanoma
development. A comprehensive review of epidemiological data. Pigment cell
research, 16(3), 297–306. https://doi.org/10.1034/j.1600-0749.2003.00047.x
Berger, M. F., Hodis, E., Heffernan, T. P., Deribe, Y. L., Lawrence, M. S., Protopopov, A.,
Ivanova, E., Watson, I. R., Nickerson, E., Ghosh, P., Zhang, H., Zeid, R., Ren, X.,
Cibulskis, K., Sivachenko, A. Y., Wagle, N., Sucker, A., Sougnez, C., Onofrio, R.,
39
Ambrogio, L., … Garraway, L. A. (2012). Melanoma genome sequencing reveals
frequent PREX2 mutations. Nature, 485(7399), 502–506.
https://doi.org/10.1038/nature11071
Bohlman, S., & Manfredi, J. J. (2014). p53-independent effects of Mdm2. Sub-cellular
biochemistry, 85, 235–246. https://doi.org/10.1007/978-94-017-9211-0_13
Böttger, V., Böttger, A., Garcia-Echeverria, C., Ramos, Y. F., van der Eb, A. J., Jochemsen,
A. G., & Lane, D. P. (1999). Comparative study of the p53-mdm2 and p53-MDMX
interfaces. Oncogene, 18(1), 189–199. https://doi.org/10.1038/sj.onc.1202281
Box, N. F., Vukmer, T. O., & Terzian, T. (2014). Targeting p53 in melanoma. Pigment cell
& melanoma research, 27(1), 8–10. https://doi.org/10.1111/pcmr.12180
Cancer Genome Atlas Network (2015). Genomic Classification of Cutaneous Melanoma.
Cell, 161(7), 1681–1696. https://doi.org/10.1016/j.cell.2015.05.044
Chandler, D. S., Singh, R. K., Caldwell, L. C., Bitler, J. L., & Lozano, G. (2006). Genotoxic
stress induces coordinately regulated alternative splicing of the p53 modulators
MDM2 and MDM4. Cancer research, 66(19), 9502–9508.
https://doi.org/10.1158/0008-5472.CAN-05-4271
Chappell, W. H., Steelman, L. S., Long, J. M., Kempf, R. C., Abrams, S. L., Franklin, R. A.,
Bäsecke, J., Stivala, F., Donia, M., Fagone, P., Malaponte, G., Mazzarino, M. C.,
Nicoletti, F., Libra, M., Maksimovic-Ivanic, D., Mijatovic, S., Montalto, G., Cervello,
M., Laidler, P., Milella, M., … McCubrey, J. A. (2011). Ras/Raf/MEK/ERK and
PI3K/PTEN/Akt/mTOR inhibitors: rationale and importance to inhibiting these
pathways in human health. Oncotarget, 2(3), 135–164.
https://doi.org/10.18632/oncotarget.240
40
Chen, J., Zhang, D., Zhang, Y., & Li, G. (2012). Computational studies of difference in
binding modes of peptide and non-peptide inhibitors to MDM2/MDMX based on
molecular dynamics simulations. International journal of molecular sciences, 13(2),
2176–2195. https://doi.org/10.3390/ijms13022176
Chiriboga, L., Meehan, S., Osman, I., Glick, M., de la Cruz, G., Howell, B. S., Friedman-
Jiménez, G., Schneider, R. J., & Jamal, S. (2016). Endothelin-1 in the tumor
microenvironment correlates with melanoma invasion. Melanoma research, 26(3),
236–244. https://doi.org/10.1097/CMR.0000000000000235
Danovi, D., Meulmeester, E., Pasini, D., Migliorini, D., Capra, M., Frenk, R., de Graaf, P.,
Francoz, S., Gasparini, P., Gobbi, A., Helin, K., Pelicci, P. G., Jochemsen, A. G., &
Marine, J. C. (2004). Amplification of Mdmx (or Mdm4) directly contributes to
tumor formation by inhibiting p53 tumor suppressor activity. Molecular and cellular
biology, 24(13), 5835–5843. https://doi.org/10.1128/MCB.24.13.5835-5843.2004
Davies, H., Bignell, G., Cox, C. et al. Mutations of the BRAF gene in human cancer. Nature
417, 949–954 (2002). https://doi.org/10.1038/nature00766 de Graaf, P., Little, N. A., Ramos, Y. F., Meulmeester, E., Letteboer, S. J., & Jochemsen, A.
G. (2003). Hdmx protein stability is regulated by the ubiquitin ligase activity of
Mdm2. The Journal of biological chemistry, 278(40), 38315–38324.
https://doi.org/10.1074/jbc.M213034200
Donehower, L. A., Harvey, M., Slagle, B. L., McArthur, M. J., Montgomery, C. A., Jr, Butel,
J. S., & Bradley, A. (1992). Mice deficient for p53 are developmentally normal but
susceptible to spontaneous tumours. Nature, 356(6366), 215–221.
https://doi.org/10.1038/356215a0
41
Evans, M. S., Madhunapantula, S. V., Robertson, G. P., & Drabick, J. J. (2013). Current and
future trials of targeted therapies in cutaneous melanoma. Advances in experimental
medicine and biology, 779, 223–255. https://doi.org/10.1007/978-1-4614-6176-0_10
Fackenthal, J. D., & Godley, L. A. (2008). Aberrant RNA splicing and its functional
consequences in cancer cells. Disease models & mechanisms, 1(1), 37–42.
https://doi.org/10.1242/dmm.000331
Fakharzadeh, S. S., Trusko, S. P., & George, D. L. (1991). Tumorigenic potential associated
with enhanced expression of a gene that is amplified in a mouse tumor cell line. The
EMBO journal, 10(6), 1565–1569.
Ge, Y., & Porse, B. T. (2013). The functional consequences of intron retention: Alternative
splicing coupled to NMD as a regulator of gene expression. BioEssays, 36(3), 236–
243. https://doi.org/10.1002/bies.201300156
Gembarska, A., Luciani, F., Fedele, C., Russell, E. A., Dewaele, M., Villar, S., Zwolinska,
A., Haupt, S., de Lange, J., Yip, D., Goydos, J., Haigh, J. J., Haupt, Y., Larue, L.,
Jochemsen, A., Shi, H., Moriceau, G., Lo, R. S., Ghanem, G., Shackleton, M., …
Marine, J. C. (2012). MDM4 is a key therapeutic target in cutaneous melanoma.
Nature medicine, 18(8), 1239–1247. https://doi.org/10.1038/nm.2863
Giglio, S., Mancini, F., Gentiletti, F., Sparaco, G., Felicioni, L., Barassi, F., Martella, C.,
Prodosmo, A., Iacovelli, S., Buttitta, F., Farsetti, A., Soddu, S., Marchetti, A., Sacchi,
A., Pontecorvi, A., & Moretti, F. (2005). Identification of an aberrantly spliced form
of HDMX in human tumors: a new mechanism for HDM2 stabilization. Cancer
research, 65(21), 9687–9694. https://doi.org/10.1158/0008-5472.CAN-05-0450
42
Graveley, B. R. (2001). Alternative splicing: increasing diversity in the proteomic world.
Trends in Genetics, 17(2), 100–107. https://doi.org/10.1016/s0168-9525(00)02176-4
Grellscheid, S., Dalgliesh, C., Storbeck, M., Best, A., Liu, Y., Jakubik, M., Mende, Y.,
Ehrmann, I., Curk, T., Rossbach, K., Bourgeois, C. F., Stévenin, J., Grellscheid, D.,
Jackson, M. S., Wirth, B., & Elliott, D. J. (2011). Identification of evolutionarily
conserved exons as regulated targets for the splicing activator tra2β in development.
PLoS genetics, 7(12), e1002390. https://doi.org/10.1371/journal.pgen.1002390
Gruber SB, Armstrong BK. Cutaneous and ocular melanoma. In: Schottenfeld D, Fraumeni
JF, editors. Cancer Epidemiology and Prevention. New York, NY: Oxford University
Press; 2006. pp. 1196–1229.
Guarneri, C., Bevelacqua, V., Polesel, J., Falzone, L., Cannavò, P. S., Spandidos, D. A.,
Malaponte, G., & Libra, M. (2017). NF-κB inhibition is associated with OPN/MMP-9
downregulation in cutaneous melanoma. Oncology reports, 37(2), 737–746.
https://doi.org/10.3892/or.2017.5362
Hajkova, N., Hojny, J., Nemejcova, K., Dundr, P., Ulrych, J., Jirsova, K., Glezgova, J., &
Ticha, I. (2018). Germline mutation in the TP53 gene in uveal melanoma. Scientific
reports, 8(1), 7618. https://doi.org/10.1038/s41598-018-26040-0
Harms, K., Chen, X. The functional domains in p53 family proteins exhibit both common
and distinct properties. Cell Death Differ 13, 890–897 (2006).
https://doi.org/10.1038/sj.cdd.4401904
Haupt, S., Mejía-Hernández, J. O., Vijayakumaran, R., Keam, S. P., & Haupt, Y. (2019). The
long and the short of it: the MDM4 tail so far. Journal of molecular cell biology,
11(3), 231–244. https://doi.org/10.1093/jmcb/mjz007
43
Haupt, Y., Maya, R., Kazaz, A., & Oren, M. (1997). Mdm2 promotes the rapid degradation
of p53. Nature, 387(6630), 296–299. https://doi.org/10.1038/387296a0
Hawkes, J. E., Truong, A., & Meyer, L. J. (2016). Genetic predisposition to melanoma.
Seminars in oncology, 43(5), 591–597.
https://doi.org/10.1053/j.seminoncol.2016.08.003
Hayward N. K. (1996). The current situation with regard to human melanoma and genetic
inferences. Current opinion in oncology, 8(2), 136–142.
https://doi.org/10.1097/00001622-199603000-00011
Hocker, T., & Tsao, H. (2007). Ultraviolet radiation and melanoma: a systematic review and
analysis of reported sequence variants. Human mutation, 28(6), 578–588.
https://doi.org/10.1002/humu.20481
Hodis, E., Watson, I. R., Kryukov, G. V., Arold, S. T., Imielinski, M., Theurillat, J. P.,
Nickerson, E., Auclair, D., Li, L., Place, C., Dicara, D., Ramos, A. H., Lawrence, M.
S., Cibulskis, K., Sivachenko, A., Voet, D., Saksena, G., Stransky, N., Onofrio, R. C.,
Winckler, W., … Chin, L. (2012). A landscape of driver mutations in melanoma.
Cell, 150(2), 251–263. https://doi.org/10.1016/j.cell.2012.06.024
Honda, R., Tanaka, H., & Yasuda, H. (1997). Oncoprotein MDM2 is a ubiquitin ligase E3 for
tumor suppressor p53. FEBS letters, 420(1), 25–27. https://doi.org/10.1016/s0014-
5793(97)01480-4
Hugo, W., Zaretsky, J. M., Sun, L., Song, C., Moreno, B. H., Hu-Lieskovan, S., Berent-
Maoz, B., Pang, J., Chmielowski, B., Cherry, G., Seja, E., Lomeli, S., Kong, X.,
Kelley, M. C., Sosman, J. A., Johnson, D. B., Ribas, A., & Lo, R. S. (2016). Genomic
44
and Transcriptomic Features of Response to Anti-PD-1 Therapy in Metastatic
Melanoma. Cell, 165(1), 35–44. https://doi.org/10.1016/j.cell.2016.02.065
Inamdar, G. S., Madhunapantula, S. V., & Robertson, G. P. (2010). Targeting the MAPK
pathway in melanoma: why some approaches succeed and other fail. Biochemical
pharmacology, 80(5), 624–637. https://doi.org/10.1016/j.bcp.2010.04.029
Izaguirre, D. I., Zhu, W., Hai, T., Cheung, H. C., Krahe, R., & Cote, G. J. (2012). PTBP1-
dependent regulation of USP5 alternative RNA splicing plays a role in glioblastoma
tumorigenesis. Molecular carcinogenesis, 51(11), 895–906.
https://doi.org/10.1002/mc.20859
Jemal, A., Saraiya, M., Patel, P., Cherala, S. S., Barnholtz-Sloan, J., Kim, J., Wiggins, C. L.,
& Wingo, P. A. (2011). Recent trends in cutaneous melanoma incidence and death
rates in the United States, 1992-2006. Journal of the American Academy of
Dermatology, 65(5 Suppl 1), S17–25.e253. https://doi.org/10.1016/j.jaad.2011.04.032
Jemal, A., Simard, E. P., Dorell, C., Noone, A. M., Markowitz, L. E., Kohler, B., Eheman,
C., Saraiya, M., Bandi, P., Saslow, D., Cronin, K. A., Watson, M., Schiffman, M.,
Henley, S. J., Schymura, M. J., Anderson, R. N., Yankey, D., & Edwards, B. K.
(2013). Annual Report to the Nation on the Status of Cancer, 1975-2009, featuring
the burden and trends in human papillomavirus(HPV)-associated cancers and HPV
vaccination coverage levels. Journal of the National Cancer Institute, 105(3), 175–
201. https://doi.org/10.1093/jnci/djs491
Johnson, D. B., & Puzanov, I. (2015). Treatment of NRAS-mutant melanoma. Current
treatment options in oncology, 16(4), 15. https://doi.org/10.1007/s11864-015-0330-z
45
Johnson, D. B., Smalley, K. S., & Sosman, J. A. (2014). Molecular pathways: targeting
NRAS in melanoma and acute myelogenous leukemia. Clinical cancer research : an
official journal of the American Association for Cancer Research, 20(16), 4186–
4192. https://doi.org/10.1158/1078-0432.CCR-13-3270
Jones, S. N., Roe, A. E., Donehower, L. A., & Bradley, A. (1995). Rescue of embryonic
lethality in Mdm2-deficient mice by absence of p53. Nature, 378(6553), 206–208.
https://doi.org/10.1038/378206a0
Kanapathipillai M. (2018). Treating p53 Mutant Aggregation-Associated Cancer. Cancers,
10(6), 154. https://doi.org/10.3390/cancers10060154
Kanehisa, M., Furumichi, M., Tanabe, M., Sato, Y., & Morishima, K. (2017). KEGG: new
perspectives on genomes, pathways, diseases and drugs. Nucleic acids research,
45(D1), D353–D361. https://doi.org/10.1093/nar/gkw1092
Karni, R., de Stanchina, E., Lowe, S. W., Sinha, R., Mu, D., & Krainer, A. R. (2007). The
gene encoding the splicing factor SF2/ASF is a proto-oncogene. Nature structural &
molecular biology, 14(3), 185–193. https://doi.org/10.1038/nsmb1209
Kastan, M. B., Onyekwere, O., Sidransky, D., Vogelstein, B., & Craig, R. W. (1991).
Participation of p53 protein in the cellular response to DNA damage. Cancer research,
51(23 Pt 1), 6304–6311.
Kastenhuber, E. R., & Lowe, S. W. (2017). Putting p53 in Context. Cell, 170(6), 1062–1078.
https://doi.org/10.1016/j.cell.2017.08.028
Kawai, H., Lopez-Pajares, V., Kim, M. M., Wiederschain, D., & Yuan, Z. M. (2007). RING
domain-mediated interaction is a requirement for MDM2's E3 ligase activity. Cancer
research, 67(13), 6026–6030. https://doi.org/10.1158/0008-5472.CAN-07-1313
46
Kitano, S., Nakayama, T., & Yamashita, M. (2018). Biomarkers for Immune Checkpoint
Inhibitors in Melanoma. Frontiers in oncology, 8, 270.
https://doi.org/10.3389/fonc.2018.00270
Krauthammer, M., Kong, Y., Ha, B. H., Evans, P., Bacchiocchi, A., McCusker, J. P., Cheng,
E., Davis, M. J., Goh, G., Choi, M., Ariyan, S., Narayan, D., Dutton-Regester, K.,
Capatana, A., Holman, E. C., Bosenberg, M., Sznol, M., Kluger, H. M., Brash, D. E.,
Stern, D. F., … Halaban, R. (2012). Exome sequencing identifies recurrent somatic
RAC1 mutations in melanoma. Nature genetics, 44(9), 1006–1014.
https://doi.org/10.1038/ng.2359
Kubbutat, M. H., Jones, S. N., & Vousden, K. H. (1997). Regulation of p53 stability by
Mdm2. Nature, 387(6630), 299–303. https://doi.org/10.1038/387299a0
Landi, M. T., Bishop, D. T., MacGregor, S., Machiela, M. J., Stratigos, A. J., Ghiorzo, P.,
Brossard, M., Calista, D., Choi, J., Fargnoli, M. C., Zhang, T., Rodolfo, M., Trower,
A. J., Menin, C., Martinez, J., Hadjisavvas, A., Song, L., Stefanaki, I., Scolyer, R.,
Yang, R., … Law, M. H. (2020). Genome-wide association meta-analyses combining
multiple risk phenotypes provide insights into the genetic architecture of cutaneous
melanoma susceptibility. Nature genetics, 52(5), 494–504.
https://doi.org/10.1038/s41588-020-0611-8
Lawrence, M. S., Stojanov, P., Polak, P., Kryukov, G. V., Cibulskis, K., Sivachenko, A., …
Getz, G. (2013). Mutational heterogeneity in cancer and the search for new cancer-
associated genes. Nature, 499(7457), 214–218. https://doi.org/10.1038/nature12213
Leonardi, G. C., Falzone, L., Salemi, R., Zanghì, A., Spandidos, D. A., Mccubrey, J. A.,
Candido, S., & Libra, M. (2018). Cutaneous melanoma: From pathogenesis to therapy
47
(Review). International journal of oncology, 52(4), 1071–1080.
https://doi.org/10.3892/ijo.2018.4287
Li, Q., & Lozano, G. (2013). Molecular pathways: targeting Mdm2 and Mdm4 in cancer
therapy. Clinical cancer research : an official journal of the American Association
for Cancer Research, 19(1), 34–41. https://doi.org/10.1158/1078-0432.CCR-12-0053
Li, Y., Sun, N., Lu, Z., Sun, S., Huang, J., Chen, Z., & He, J. (2017). Prognostic alternative
mRNA splicing signature in non-small cell lung cancer. Cancer letters, 393, 40–51.
https://doi.org/10.1016/j.canlet.2017.02.016
Luo, Q., Beaver, J., Liu, Y., & Zhang, Z. (2017). Dynamics of p53: A Master Decider of Cell
Fate. Genes, 8(2), 66. https://doi.org/10.3390/genes8020066
Luo, Y., Lin, F. T., & Lin, W. C. (2004). ATM-mediated stabilization of hMutL DNA
mismatch repair proteins augments p53 activation during DNA damage. Molecular
and cellular biology, 24(14), 6430–6444. https://doi.org/10.1128/MCB.24.14.6430-
6444.2004
Ma, F. C., He, R. Q., Lin, P., Zhong, J. C., Ma, J., Yang, H., Hu, X. H., & Chen, G. (2019).
Profiling of prognostic alternative splicing in melanoma. Oncology letters, 18(2),
1081–1088. https://doi.org/10.3892/ol.2019.10453
Maldonado, J. L., Fridlyand, J., Patel, H., Jain, A. N., Busam, K., Kageshita, T., Ono, T.,
Albertson, D. G., Pinkel, D., & Bastian, B. C. (2003). Determinants of BRAF
mutations in primary melanomas. Journal of the National Cancer Institute, 95(24),
1878–1890. https://doi.org/10.1093/jnci/djg123
48
Mancini, F., Di Conza, G., & Moretti, F. (2009). MDM4 (MDMX) and its Transcript
Variants. Current genomics, 10(1), 42–50.
https://doi.org/10.2174/138920209787581280
Marine, J. C., Francoz, S., Maetens, M., Wahl, G., Toledo, F., & Lozano, G. (2006). Keeping
p53 in check: essential and synergistic functions of Mdm2 and Mdm4. Cell death and
differentiation, 13(6), 927–934. https://doi.org/10.1038/sj.cdd.4401912
Marine, J.-C., & Jochemsen, A. G. (2005). Mdmx as an essential regulator of p53 activity.
Biochemical and Biophysical Research Communications, 331(3), 750–760.
https://doi.org/10.1016/j.bbrc.2005.03.151
Markey M. P. (2011). Regulation of MDM4. Frontiers in bioscience (Landmark edition), 16,
1144–1156. https://doi.org/10.2741/3780
Markey, M., & Berberich, S. J. (2008). Full-length hdmX transcripts decrease following
genotoxic stress. Oncogene, 27(52), 6657–6666.
https://doi.org/10.1038/onc.2008.266
Markovic, S. N., Erickson, L. A., Rao, R. D., Weenig, R. H., Pockaj, B. A., Bardia, A.,
Vachon, C. M., Schild, S. E., McWilliams, R. R., Hand, J. L., Laman, S. D.,
Kottschade, L. A., Maples, W. J., Pittelkow, M. R., Pulido, J. S., Cameron, J. D.,
Creagan, E. T., & Melanoma Study Group of the Mayo Clinic Cancer Center (2007).
Malignant melanoma in the 21st century, part 1: epidemiology, risk factors,
screening, prevention, and diagnosis. Mayo Clinic proceedings, 82(3), 364–380.
https://doi.org/10.4065/82.3.364
49
Mercer, K. E., & Pritchard, C. A. (2003). Raf proteins and cancer: B-Raf is identified as a
mutational target. Biochimica et biophysica acta, 1653(1), 25–40.
https://doi.org/10.1016/s0304-419x(03)00016-7
Merkel, O & Taylor, N & Prutsch, N & Staber, Philipp & Moriggl, Richard & Turner,
Suzanne & Kenner, Lukas. (2017). When the guardian sleeps: Reactivation of the p53
pathway in cancer. 10.17863/CAM.10629.
Meyle, K. D., & Guldberg, P. (2009). Genetic risk factors for melanoma. Human genetics,
126(4), 499–510. https://doi.org/10.1007/s00439-009-0715-9
Momand, J., Zambetti, G. P., Olson, D. C., George, D., & Levine, A. J. (1992). The mdm-2
oncogene product forms a complex with the p53 protein and inhibits p53-mediated
transactivation. Cell, 69(7), 1237–1245. https://doi.org/10.1016/0092-8674(92)90644-
r
Montes de Oca Luna, R., Wagner, D. S., & Lozano, G. (1995). Rescue of early embryonic
lethality in mdm2-deficient mice by deletion of p53. Nature, 378(6553), 203–206.
https://doi.org/10.1038/378203a0
Morgese, F., Berardi, R., Sampaolesi, C., Torniai, M., Marcantognini, G., Giacchetti, A.,
Serresi, S., Onofri, A., Bittoni, A., Pilone, A., Ricotti, G., & Cascinu, S. (2015).
Gender differences and outcome of melanoma patients. Journal of Translational
Medicine, 13(Suppl 1), P13. https://doi.org/10.1186/1479-5876-13-S1-P13
Mrkvová, Z., Uldrijan, S., Pombinho, A., Bartůněk, P., & Slaninová, I. (2019).
Benzimidazoles Downregulate Mdm2 and MdmX and Activate p53 in MdmX
Overexpressing Tumor Cells. Molecules (Basel, Switzerland), 24(11), 2152.
https://doi.org/10.3390/molecules24112152
50
N. Dhomen, R. MaraisBRAF signaling and targeted therapies in melanomaHematol Oncol
Clin North Am, 23 (2009), pp. 529-545. https://doi.org/10.1016/j.hoc.2009.04.001
National Program of Cancer Registries (NPCR) and Surveillance, Epidemiology, and End
Results (SEER) Program. Atlanta, GA: Bethesda, MD: Centers for Disease Control
and Prevention; National Cancer Institute; Data from 2007–2011.
Oliner, J. D., Pietenpol, J. A., Thiagalingam, S., Gyuris, J., Kinzler, K. W., & Vogelstein, B.
(1993). Oncoprotein MDM2 conceals the activation domain of tumour suppressor
p53. Nature, 362(6423), 857–860. https://doi.org/10.1038/362857a0
Ozaki, T., & Nakagawara, A. (2011). Role of p53 in Cell Death and Human Cancers.
Cancers, 3(1), 994–1013. https://doi.org/10.3390/cancers3010994
Pal, S., Bi, Y., Macyszyn, L., Showe, L. C., O'Rourke, D. M., & Davuluri, R. V. (2014).
Isoform-level gene signature improves prognostic stratification and accurately
classifies glioblastoma subtypes. Nucleic acids research, 42(8), e64.
https://doi.org/10.1093/nar/gku121
Palmer, J. S., Duffy, D. L., Box, N. F., Aitken, J. F., O'Gorman, L. E., Green, A. C.,
Hayward, N. K., Martin, N. G., & Sturm, R. A. (2000). Melanocortin-1 receptor
polymorphisms and risk of melanoma: is the association explained solely by
pigmentation phenotype?. American journal of human genetics, 66(1), 176–186.
https://doi.org/10.1086/302711
Pan, Y., & Chen, J. (2003). MDM2 promotes ubiquitination and degradation of MDMX.
Molecular and cellular biology, 23(15), 5113–5121.
https://doi.org/10.1128/mcb.23.15.5113-5121.2003
51
Pant, V., Larsson, C. A., Aryal, N., Xiong, S., You, M. J., Quintas-Cardama, A., & Lozano,
G. (2017). Tumorigenesis promotes Mdm4-S overexpression. Oncotarget, 8(16),
25837–25847. https://doi.org/10.18632/oncotarget.15552
Pei, D., Zhang, Y., & Zheng, J. (2012). Regulation of p53: a collaboration between Mdm2
and Mdmx. Oncotarget, 3(3), 228–235. https://doi.org/10.18632/oncotarget.443
Ponnuswamy, A., Hupp, T., & Fåhraeus, R. (2012). Concepts in MDM2 Signaling: Allosteric
Regulation and Feedback Loops. Genes & cancer, 3(3-4), 291–297.
https://doi.org/10.1177/1947601912454140
Rajkumar, S., & Watson, I. R. (2016). Molecular characterisation of cutaneous melanoma:
creating a framework for targeted and immune therapies. British journal of cancer,
115(2), 145–155. https://doi.org/10.1038/bjc.2016.195
Rallapalli, R., Strachan, G., Cho, B., Mercer, W. E., & Hall, D. J. (1999). A novel MDMX
transcript expressed in a variety of transformed cell lines encodes a truncated protein
with potent p53 repressive activity. The Journal of biological chemistry, 274(12),
8299–8308. https://doi.org/10.1074/jbc.274.12.8299
Rallapalli, R., Strachan, G., Tuan, R. S., & Hall, D. J. (2003). Identification of a domain
within MDMX-S that is responsible for its high affinity interaction with p53 and
high-level expression in mammalian cells. Journal of cellular biochemistry, 89(3),
563–575. https://doi.org/10.1002/jcb.10535
Ramos, Y. F., Stad, R., Attema, J., Peltenburg, L. T., van der Eb, A. J., & Jochemsen, A. G.
(2001). Aberrant expression of HDMX proteins in tumor cells correlates with wild-
type p53. Cancer research, 61(5), 1839–1842.
52
Reed, K. B., Brewer, J. D., Lohse, C. M., Bringe, K. E., Pruitt, C. N., & Gibson, L. E. (2012).
Increasing incidence of melanoma among young adults: an epidemiological study in
Olmsted County, Minnesota. Mayo Clinic proceedings, 87(4), 328–334.
https://doi.org/10.1016/j.mayocp.2012.01.010
Rhodes, D. R. (2020, July 12). ONCOMINE: A Cancer Microarray Database and Integrated
Data-Mining Platform. Retrieved from https://pubmed.ncbi.nlm.nih.gov/15068665/
Riemenschneider, M. J., Knobbe, C. B., & Reifenberger, G. (2003). Refined mapping of
1q32 amplicons in malignant gliomas confirms MDM4 as the main amplification
target. International journal of cancer, 104(6), 752–757.
https://doi.org/10.1002/ijc.11023
Rodríguez-Cerdeira, C., Carnero Gregorio, M., López-Barcenas, A., Sánchez-Blanco, E.,
Sánchez-Blanco, B., Fabbrocini, G., Bardhi, B., Sinani, A., & Guzman, R. A. (2017).
Advances in Immunotherapy for Melanoma: A Comprehensive Review. Mediators of
inflammation, 2017, 3264217. https://doi.org/10.1155/2017/3264217
Rutkowski, P., Zdzienicki, M., Nowecki, Z. I., & Van Akkooi, A. C. (2010). Surgery of
primary melanomas. Cancers, 2(2), 824–841. https://doi.org/10.3390/cancers2020824
Saraiva-Agostinho N, Barbosa-Morais NL (2019). “psichomics: graphical application for
alternative splicing quantification and analysis.” Nucleic Acids Research, 47(2), e7.
https://doi.org/10.1093/nar/gky888.
Shadfan, M., Lopez-Pajares, V., & Yuan, Z. M. (2012). MDM2 and MDMX: Alone and
together in regulation of p53. Translational cancer research, 1(2), 88–89.
Shadfan, M., Lopez-Pajares, V., & Yuan, Z. M. (2012). MDM2 and MDMX: Alone and
together in regulation of p53. Translational cancer research, 1(2), 88–89.
53
Sharp, D. A., Kratowicz, S. A., Sank, M. J., & George, D. L. (1999). Stabilization of the
MDM2 Oncoprotein by Interaction with the Structurally Related MDMX Protein.
Journal of Biological Chemistry, 274(53), 38189–38196.
https://doi.org/10.1074/jbc.274.53.38189
Shieh, S. Y., Ikeda, M., Taya, Y., & Prives, C. (1997). DNA damage-induced
phosphorylation of p53 alleviates inhibition by MDM2. Cell, 91(3), 325–334.
https://doi.org/10.1016/s0092-8674(00)80416-x
Shvarts, A., Steegenga, W. T., Riteco, N., van Laar, T., Dekker, P., Bazuine, M., van Ham,
R. C., van der Houven van Oordt, W., Hateboer, G., van der Eb, A. J., & Jochemsen,
A. G. (1996). MDMX: a novel p53-binding protein with some functional properties
of MDM2. The EMBO journal, 15(19), 5349–5357.
Stad, R., Ramos, Y. F., Little, N., Grivell, S., Attema, J., van Der Eb, A. J., & Jochemsen, A.
G. (2000). Hdmx stabilizes Mdm2 and p53. The Journal of biological chemistry,
275(36), 28039–28044. https://doi.org/10.1074/jbc.M003496200
Staibano, S., Mascolo, M., Siano, M., Ilardi, G., & Rosa, G. D. (2011, September 12).
Genetic, Epigenetic and Molecular Changes in Melanoma: A New Paradigm for
Biological Classification. Retrieved from
https://www.intechopen.com/books/research-on-melanoma-a-glimpse-into-current-
directions-and-future-trends/genetic-epigenetic-and-molecular-changes-in-melanoma-
a-new-paradigm-for-biological-classification
Suo, C., Hrydziuszko, O., Lee, D., Pramana, S., Saputra, D., Joshi, H., Calza, S., & Pawitan,
Y. (2015). Integration of somatic mutation, expression and functional data reveals
54
potential driver genes predictive of breast cancer survival. Bioinformatics (Oxford,
England), 31(16), 2607–2613. https://doi.org/10.1093/bioinformatics/btv164
Toledo, F., & Wahl, G. M. (2006). Regulating the p53 pathway: in vitro hypotheses, in vivo
veritas. Nature reviews. Cancer, 6(12), 909–923. https://doi.org/10.1038/nrc2012
Tripp, M. K., Watson, M., Balk, S. J., Swetter, S. M., & Gershenwald, J. E. (2016). State of
the science on prevention and screening to reduce melanoma incidence and mortality:
The time is now. CA: a cancer journal for clinicians, 66(6), 460–480.
https://doi.org/10.3322/caac.21352
Tsao, H., Chin, L., Garraway, L. A., & Fisher, D. E. (2012). Melanoma: from mutations to
medicine. Genes & development, 26(11), 1131–1155.
https://doi.org/10.1101/gad.191999.112
U.S. Cancer Statistics Working Group. United States Cancer Statistics: 1999–2010 Incidence
and Mortality Web-based report. Atlanta, GA: Centers for Disease Control and
Prevention, U.S. Dept of Health and Human Services and National Cancer Institute,
National Institutes of Health; 2013. [January 20, 2014]. http://www.cdc.gov/uscs.
US Department of Health and Human Services. The Surgeon General's Call to Action to
Prevent Skin Cancer. Washington (DC): Office of the Surgeon General (US); 2014.
Skin Cancer as a Major Public Health Problem. Available from:
https://www.ncbi.nlm.nih.gov/books/NBK247164/
Vogelstein, B., Papadopoulos, N., Velculescu, V. E., Zhou, S., Diaz, L. A., Jr, & Kinzler, K.
W. (2013). Cancer genome landscapes. Science (New York, N.Y.), 339(6127), 1546–
1558. https://doi.org/10.1126/science.1235122
55
Wade, M., Li, Y. C., & Wahl, G. M. (2013). MDM2, MDMX and p53 in oncogenesis and
cancer therapy. Nature reviews. Cancer, 13(2), 83–96.
https://doi.org/10.1038/nrc3430
Wasylishen, A. R., & Lozano, G. (2016). Attenuating the p53 Pathway in Human Cancers:
Many Means to the Same End. Cold Spring Harbor perspectives in medicine, 6(8),
a026211. https://doi.org/10.1101/cshperspect.a026211
Wernick, B. D., Goel, N., Zih, F. S., & Farma, J. M. (2017). A surgical perspective report on
melanoma management. Melanoma management, 4(2), 105–112.
https://doi.org/10.2217/mmt-2016-0031
Williams, A. B., & Schumacher, B. (2016). p53 in the DNA-Damage-Repair Process. Cold
Spring Harbor perspectives in medicine, 6(5), a026070.
https://doi.org/10.1101/cshperspect.a026070
Yu, C., Liu, X., Yang, J., Zhang, M., Jin, H., Ma, X., & Shi, H. (2019). Combination of
Immunotherapy With Targeted Therapy: Theory and Practice in Metastatic
Melanoma. Frontiers in immunology, 10, 990.
https://doi.org/10.3389/fimmu.2019.00990
Zerp, S., Elsas, A., Peltenburg, L. et al. p53 mutations in human cutaneous melanoma
correlate with sun exposure but are not always involved in melanomagenesis. Br J
Cancer 79, 921–926 (1999). https://doi.org/10.1038/sj.bjc.669014
Zhu, J., Chen, Z., & Yong, L. (2018). Systematic profiling of alternative splicing signature
reveals prognostic predictor for ovarian cancer. Gynecologic oncology, 148(2), 368–
374. https://doi.org/10.1016/j.ygyno.2017.11.028
56
57