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(12) United States Patent (10) Patent No.: US 9,309,564 B2 Depinho Et Al USOO93 09564B2 (12) United States Patent (10) Patent No.: US 9,309,564 B2 DePinho et al. (45) Date of Patent: Apr. 12, 2016 (54) COMPOSITIONS, KITS, AND METHODS FOR FOREIGN PATENT DOCUMENTS IDENTIFICATION, ASSESSMENT, WO WO-O2/O71928 9, 2002 PREVENTION, AND THERAPY OF CANCER WO WO-2004/082571 9, 2004 WO WO-2005/118869 12/2005 (75) Inventors: Ronald A. DePinho, Houston, TX (US); WO WO-2006/089087 8, 2006 Kenneth C. Anderson, Wellesley, MA (US); Ruben D. Carrasco, Brookline, OTHER PUBLICATIONS MA (US); Giovanni Tonon, Cernusco Lorenzo etal (Drug Resistance Updates, 2003, 6:329-339).* sul Naviglio (IT): Cameron Brennan, Mitsiades et al (Blood, 2006, 107:1092-1 100, published online Oct. Haworth, NJ (US); John D. 18, 2005).* Shaughnessy, Jr., Roland, AR (US); Chauhan et al (Blood, 2003, 101:3606-3614).* Lynda Chin, Houston, TX (US) Huang etal (Drug Discovery Today, 2003, 8:356-363).* ADAPT. Paterson Institute for Cancer Research, probesets for (73) Assignees: Dana-Farber Cancer Institute, Inc., PRKCi, printed Jan. 15, 2014.* ADAPT. Paterson Institute for Cancer Research, probesets for Boston, MA (US); Board of Trustees of SEMA4A, printed Jan. 15, 2014.* the University of Arkansas, Little Rock, ADAPT. Paterson Institute for Cancer Research, probesets for AR (US) DHX36, printed Jan. 15, 2014.* Zhou et al (British Journal of Haematology, 2005, 128:636-644).* (*) Notice: Subject to any disclaimer, the term of this Tassone et al (Clinical Cancer Research, 2005, 11:4251-4258).* patent is extended or adjusted under 35 Nietal (British Journal of Haematology, 2003, 121:849-856).* U.S.C. 154(b) by 0 days. Abdelhaleem, M., “Do human RNA helicases have a role in cancer?” Biochim Biophys Acta 1704:37-46 (2004). Aguirre et al., “High-resolution characterization of the pancreatic (21) Appl. No.: 13/473,969 adenocarcinoma genome.” Proc Natl Acad Sci USA 101:9067-9072 (2004). Armengol, G., et al., “DNA Copy Number Changes and Evaluation (22) Filed: May 17, 2012 of MYC, IGFIR, and FES Amplification in Xenografts of Pancreatic Andenocarcinoma.” Cancer Genet Cytogenet 1 16:133-41 (2000). (65) Prior Publication Data Avet-Loiseau et al., “Molecular Cytogenetic Abnormalities in Mul tiple Myeloma and Plasma Cell Leukemia Measured Using Com US 2013 FOOT2392 A1 Mar. 21, 2013 parative Genomic Hybridization.” Genes Chromosomes Cancer 19:124-133 (1997). Balsara, B. R. & Testa, J. R., "Chromosomal imbalances in human Related U.S. Application Data lung cancer.” Oncogene 21:6877-83 (2002). Bardi, G., et al., "Karyotypic abnormalities in tumours of the pan (62) Division of application No. 1 1/706,155, filed on Feb. creas.” BrJ Cancer 67: 1106-1112 (1993). 13, 2007, now Pat. No. 8,211,634. Barlogie et al., “Thalidomide and Hematopoietic-Cell Transplanta tion for Multiple Myeloma.” N Engl J Med 354: 1021-1030 (2006). (60) Provisional application No. 60/773,072, filed on Feb. Barlogie et al., “Treatment of multiple myeloma.” Blood 103, 20-32 14, 2006. (2004). Bergsagel et al., “Cyclin D dysregulation: an early and unifying pathogenic event in multiple myeloma.” Blood 106:296-303 (2005). (51) Int. Cl. Bergsagel and Kuehl. “Chromosome translocations in multiple GOIN33/574 (2006.01) myeloma.” Oncogene 20:5611-5622 (2001). CI2O I/68 (2006.01) Bergsagel and Kuehl. “Molecular Pathogenesis and a Consequent (52) U.S. Cl. Classification of Multiple Myeloma.” J Clin Oncol 23:6333-6338 CPC ............ CI2O I/6837 (2013.01): CI2O I/6841 (2005). (2013.01); C12O 1/6886 (2013.01); C12O Bjorkavist, A.M., et al. "Comparison of DNA copy number changes 2600/106 (2013.01); C12O 2600/118 (2013.01); in malignant mesothelioma, adenocarcinoma and large-cell C12O 2600/136 (2013.01); C12O 2600/1 78 anaplastic carcinoma of the lung.” Br J Cancer 77(2):260-9 (1998). (2013.01) (Continued) (58) Field of Classification Search None Primary Examiner — Laura B Goddard See application file for complete search history. (74) Attorney, Agent, or Firm — Foley Hoag LLP (57) ABSTRACT (56) References Cited The invention relates to compositions, kits, and methods for U.S. PATENT DOCUMENTS detecting, characterizing, preventing, and treating human cancer. A variety of chromosomal regions (MCRs) and mark 6,423,491 B1 7/2002 Howe et al. ers corresponding thereto, are provided, wherein alterations 7,189,507 B2 3/2007 Macket al. 8,278,038 B2 * 10/2012 Bryant et al. .................. 435, 6.1 in the copy number of one or more of the MCRs and/or 2003/0O87250 A1 5, 2003 Monahan et al. alterations in the amount, structure, and/or activity of one or 2004.0002082 A1 1/2004 Feinberg more of the markers is correlated with the presence of cancer. 2004/0014049 A1 1/2004 Cowsert et al. ................... 435/6 2004/OO52782 A1 3/2004 Kikutani et al. 10 Claims, 16 Drawing Sheets US 9,309,564 B2 Page 2 (56) References Cited Ghadimi. B. M., et al., “Specific Chromosomal Aberrations and Amplification of the AIB1 Nuclear Receptor Coactivator Gene in OTHER PUBLICATIONS Pancreatic Carcinomas.” Am J Pathol 154:525-36 (1999). Brennan et al., “High-Resolution Global Profiling of Genomic Alter Ginzinger, D. G., “Gene quantification using real-time quantitative ations with Long Oligonucleotide Microarray.” Cancer Res 64:4744 PCR: An emerging technology hits the mainstream.” Exp Hematol 4748 (2004). 30:503-12 (2002). Brummelkamp et al., "Loss of the cylindromatosis tumour Suppres Giuliani et al., “Angiogenic Switch in Multiple Myeloma.” Hematol sor inhibits apoptosis by activating NF-kB.” Nature 424:797-801 ogy 9:377-381 (2004). (2003). Golub, T. R., et al., “Molecular Classification of Cancer: Class Dis Brunet et al., “Metagenes and molecular pattern discovery using covery and Class Prediction by Gene Expression Monitoring.” Sci matrix factorization.” Proc Natl Acad Sci USA 101:4164-4169 ence 286:531-7 (1999). (2004). Gorunova, L., et al., "Cytogenetic Analysis of Pancreatic Carcino Castro et al., “The anaphase-promoting complex: a key factor in the mas: Intratumor Heterogeneity and Nonrandom Pattern of Chromo regulation of cell cycle.” Oncogene 24:314-325 (2005). some Aberrations.” Genes, Chromosomes & Cancer 23:81-99 Chang et al., “Analysis of PTEN deletions and mutations in multiple (1998). myeloma.” Leuk Res 30:262-265 (2006). Gorunova, L., et al., “Massive Cytogenetic Heterogeneity in a Pan Chen, B.H., “Monoclonal gammopathy of undetermined signifi creatic Carcinoma: Fifty-Four Karyotypically Unrelated Clones.” cance: new insights.” CMAJ 166(10): 1309 (2002). Genes Chromosomes Cancer 14:259-266 (1995). Cheng et al., “The RAB25 Small GTPase determines aggressiveness Griffin, C. A., et al., "Chromosome Abnormalities in Pancreatic of ovarian and breast cancers.” Nat Med 10:1251-1256 (2004). Adenocarcinoma.” Genes Chromosomes Cancer 9:93-100 (1994). Chng et al., “A validated FISH trisomy index demonstrates the Griffin, C. A., et al., “Consistent Chromosome Abnormalities in hyperdiploid and nonhyperdiploid dichotomy in MGUS. Blood Adenocarcinoma of the Pancreas.” Cancer Res 55:2394-9 (1995). 106:2156-2161 (2005). Grunicke, H.H., et al., “Regulation of cell survival by atypical protein Cigudosa et al., Characterization of Nonrandom Chromosomal Gains kinase C isozymes.” Advan. Enzyme Regul. 43:213-28 (2003). and Losses in Multiple Myeloma by Comparative Genomic Hybrid Hahn, S.A., et al., “Allelotype of Pancreatic Adenocarcinoma Using Xenograft Enrichment.” Cancer Res 55:4670-5 (1995). ization Blood 91:3007-3010 (1998). Harrington, C., et al., “The Identification and Characterization of a Colgan et al., “Cyclophilin A-Deficient Mice Are Resistant to G4-DNA Resolvase Activity.” Sep. 26. The Journal of Biological Immunosuppression by Cyclosporine.” J Immunol 174:6030-6038 Chemistry 272(39):24631-24636 (1997). (2005). He et al., “A microRNA polycistron as a potential human oncogene.” Collier et al., "Cancer gene discovery in Solid tumours using Nature 435:828-833 (2005). transposon-based somatic mutagenesis in the mouse.” Nature 436, Hideshima et al., “Advances in biology of multiple myeloma: clinical 272-276 (2005). applications.” Blood 104(3):607-618 (2004). Cremer et al., “Delineation of Distinct Subgroups of Multiple Hyman, E., et al., “Impact of DNA Amplification on Gene Expression Myeloma and a Model for Clonal Evolution Based on Interphase Patterns in Breast Cancer.” Cancer Res 62, 6240-5 (2002). Cytogenetics.” Genes Chromosomes Cancer 44:194-203 (2005). Isler et al., “Evidence for transcriptional repression of SPARC-like 1. Curtis, L.J., et al., “Amplification of DNA Sequences from Chromo a gene downregulated in human lung tumors.” Int J Oncol 25:1073 some 19q13.1 in Human Pancreatic Cell Lines.” Genomics 53:42-55 1079 (2004). (1998). Johansson, B., et al., “Nonrandom Chromosomal Rearrangements in Dai et al., “The kinase haspin is required for mitotic histone H3 and Pancreatic Carcinomas.” Cancer 69:1674-81 (1992). Thr 3 phosphorylation and normal metaphase chromosome align Kanamorietal. “The PDZ Protein Tax-interacting Protein-1 Inhibits ment.” Genes Dev 19:472-488 (2005). B-Catenin Transcriptional Activity and Growth of Colorectal Cancer Debes-Marun et al., “Chromosome abnormalities clustering and its Cells,” J Biol Chem 278:38758-38764 (2003). Katoh, M., “Molecular cloning and characterization of ST7R (ST7 implications for pathogenesis and prognosis in myeloma. Leukemia like, ST7L) on human chromosome 1 p13, a novel gene homologous 17:427-436 (2003). to tumor Suppressor gene ST7 on human chromosome 7q31.” Int J Eder, A.M., “Atypical PKC, contributed to poor prognosis through Oncol 20:1247-1253 (2002). loss of apical-basal polarity and Cyclin E overexpression in ovarian Kawasaki, Ket al., “11 q23-24 loss is associated with chromosomal cancer.” Proc Natl Acad Sci U S A.102(35): 12519-24 (2005). instability in endometrial cancer.” Int J Mol Med. 12(5):727-3531 Elnenaei et al., “Delineation of the Minimal Region of Loss at 13q14 (2003). in Multiple Myeloma.” Genes Chromosomes Cancer 36:99-106 Kikutani, H., “Semaphorins in interactions between T cells and anti (2003).
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