The Role of Precision Medicine in the Diagnosis and Treatment of Patients with Rare Cancers

  • Michael J. DemeureEmail author
Part of the Cancer Treatment and Research book series (CTAR, volume 178)


Rare cancers pose unique challenges for patients and their physicians arising from a lack of information regarding the best therapeutic options. Very often, a lack of clinical trial data leads physicians to choose treatments based on small case series or case reports. Precision medicine based on genomic analysis of tumors may allow for selection of better treatments with greater efficacy and less toxicity. Physicians are increasingly using genetics to identify patients at high risk for certain cancers to allow for early detection or prophylactic interventions. Genomics can be used to inform prognosis and more accurately establish a diagnosis. Genomic analysis may also expose therapeutic targets for which drugs are currently available and approved for use in other cancers. Notable successes in the treatment of previously refractory cancers have resulted. New more advanced sequencing technologies, tools for interpretation, and an increasing array of targeted drugs offer additional hope, but challenges remain.


Rare cancers Kinase inhibitors Basket trials Umbrella trials Genomic analysis 



The author wishes to express his gratitude to Sourat Darabi, Ph.D. for her editorial review and assistance with creation of tables.

Supplementary material


  1. 1.
    Pillai RK, Jayasree K (2017) Rare cancers: challenges & issues. Indian J Med Res 145:17–27PubMedPubMedCentralCrossRefGoogle Scholar
  2. 2.
    Greenlee RT, Goodman MT, Lynch CF et al (2010) The occurrence of rare cancers in U.S. adults, 1995–2004. Public Health Rep 125:28–43PubMedPubMedCentralCrossRefGoogle Scholar
  3. 3.
    Tucker TC, Howe HL (2001) Measuring the quality of population-based cancer registries: the NAACR perspective. J Reg Manag 28:41–44Google Scholar
  4. 4.
    Trice Loggers E, Prigerson HG (2014) The end-of-life experience of patients with rare cancers and their caregivers. Rare Tumors 6:24–27CrossRefGoogle Scholar
  5. 5.
    DeSantis CE, Kramer JL, Jemal A (2017) The burden of rare cancers in the United States. CA Cancer J Clin 67:261–272PubMedCrossRefGoogle Scholar
  6. 6.
    Gatta C, Ciccolallo L, Kunkler I et al (2006) Survival from rare cancer in adults: a population-based study. Lancet Oncol 7:132–140PubMedCrossRefGoogle Scholar
  7. 7.
    Fassnacht M, Terzolo M, Allolio B et al (2012) Combination chemotherapy in advanced adrenocortical carcinoma. N Engl J Med 366:2189–2197PubMedCrossRefGoogle Scholar
  8. 8.
    Smith SM, Coleman J, Bridge JA, Iwenofu OH (2015) Molecular diagnostics in soft tissue sarcoma and gastrointestinal stromal tumors. J Surg Oncol 111:520–531PubMedCrossRefGoogle Scholar
  9. 9.
    Schaefer IM, Cote GM, Hornick JL (2017) Contemporary sarcoma diagnosis, genetics, and genomics. J Clin Oncol 36:101–110PubMedCrossRefGoogle Scholar
  10. 10.
    Fletcher CDM, Unni KK, Mertens F (2002) WHO classification of tumours of soft tissue and bone, 3rd edn. IARC Press, Lyon, FranceGoogle Scholar
  11. 11.
    Fletcher CD, Hogendoorn P, Mertens F, Bridge J (2013) WHO classification of tumours of soft tissue and bone, 4th edn. IARC Press, Lyon, FranceGoogle Scholar
  12. 12.
    Italiano A, Di Mauro I, Rapp J et al (2016) Clinical effect of molecular methods in sarcoma diagnosis (GENSARC): a prospective, multicenter, observational study. Lancet Oncol 17:532–538PubMedCrossRefGoogle Scholar
  13. 13.
    Joensuu H, Wardelmann E, Sihto H et al (2017) Effect of KIT and PDGFRA mutations on survival in patients with gastrointestinal stromal tumors treated with adjuvant imatinib: an exploratory analysis of a randomized clinical trial. JAMA Oncol 3:602–609PubMedPubMedCentralCrossRefGoogle Scholar
  14. 14.
    Gunawan B, Bergmann F, Höer J et al (2002) Biological and clinical significance of cytogenetic abnormalities in low-risk and high-risk gastrointestinal stromal tumors. Hum Pathol 33:316–321PubMedCrossRefGoogle Scholar
  15. 15.
    Raut CP et al (2006) Surgical management of advanced gastrointestinal stromal tumors after treatment with targeted systemic therapy using kinase inhibitors. J Clin Oncol 24:2325–2331PubMedCrossRefGoogle Scholar
  16. 16.
    Gorthi A, Romero JC, Loranc E et al (2018) EWS-FL11 increases transcription to cause R-loops and block BRCA repair in Ewing sarcoma. Nature, 87–391Google Scholar
  17. 17.
    Ostrom QT, Gittleman H, Liao P et al (2017) CBTRUS statistical report: primary brain and other central nervous system tumors diagnosed in the United States in 2010–2014. Neuro-Oncology 19(supp 5): v1–v88PubMedPubMedCentralCrossRefGoogle Scholar
  18. 18.
    Ohgaki H, Kleihues P (2007) Genetic pathways to primary and secondary glioblastoma. Am J Pathol 170:1445–1453PubMedPubMedCentralCrossRefGoogle Scholar
  19. 19.
    Parsons DW, Jones S, Zhang X et al (2008) An integrated genomic analysis of human glioblastoma multiforme. Science 321:1807–1812PubMedPubMedCentralCrossRefGoogle Scholar
  20. 20.
    Yan H, Parsons W, Jim G et al (2009) IHD1 and IDH2 mutations in gliomas. N Engl J Med 360:765–773PubMedPubMedCentralCrossRefGoogle Scholar
  21. 21.
    Baxter EJ, Scott LM, Campbell PJ et al (2005) Cancer genome project: acquired mutation of the tyrosine kinase JAK2 in human myeloproliferative disorders. Lancet 365:1054–1061PubMedCrossRefGoogle Scholar
  22. 22.
    Tam CS, Nussenzveig RM, Popat U et al (2008) The natural history and treatment outcome of blast phase BCR-ABL- myeloproliferative neoplasms. Blood 112:1628–1637PubMedPubMedCentralCrossRefGoogle Scholar
  23. 23.
    Theocharides A, Boissinot M, Girodon F et al (2007) Leukemic blasts in transformed JAK2-V617F-positive myeloproliferative disorders are frequently negative for the JAK2-V617F mutation. Blood 110:375–379PubMedCrossRefGoogle Scholar
  24. 24.
    Vannucchi A, Kiladjian JJ, Griesshammer M et al (2015) Ruxolitinib versus standard therapy for the treatment of polycythemia vera. N Engl J Med 372:426–435PubMedPubMedCentralCrossRefGoogle Scholar
  25. 25.
    Vega F, Medeiros LJ, Bueso-Ramos CE et al (2015) Hematolymphoid neoplasms associated with rearrangements of PDGFRA, PDGFRB, and FGFR1. Am J Clin Path 144:377–392PubMedCrossRefGoogle Scholar
  26. 26.
    Apperley JF, Gardembs M, Melo JC et al (2002) Response to imatinib mesylate in patients with chronic myeloproliferative diseases with rearrangements of the platelet-derived growth factor receptor beta. N Engl J Med 347:481–487PubMedCrossRefGoogle Scholar
  27. 27.
    Baccarani M, Cilloni D, Rondoni M et al (2007) The efficacy of imatinib mesylate in patients with FIP1L1-PDGFRalpha-positive hypereosinophilic syndrome. Results of a multicenter prospective study. Haematologica 92:1173–1179PubMedCrossRefGoogle Scholar
  28. 28.
    Klion AD, Robyn J, Akin C et al (2004) Molecular remission and reversal of myelofibrosis in response to imatinib mesylate treatment in patients with the myeloproliferative variant of hypereosinophilic syndrome. Blood 15:473–478CrossRefGoogle Scholar
  29. 29.
    Tefferi A, Gotlib J, Pardanani A (2010) Hypereosinophilic syndrome and clonal eosinophilia: point-of-care diagnostic algorithm and treatment update. Mayo Clin Proc 85:158–164PubMedPubMedCentralCrossRefGoogle Scholar
  30. 30.
    Wright D, McKeever P, Carter R (1997) Childhood non-Hodgkin lymphomas in the United Kingdom: findings from the UK Children’s Cancer Study Group. J Clin Pathol 50:128–134PubMedPubMedCentralCrossRefGoogle Scholar
  31. 31.
    Lovly CM, Gupta A, Lipson D et al (2014) Inflammatory myofibroblastic tumors harbor multiple potentially actionable kinase fusions. Cancer Discov 4:889–895PubMedPubMedCentralCrossRefGoogle Scholar
  32. 32.
    Kwak EL, Bang YJ, Camidge Dr et al (2010) Anaplastic lymphoma kinase inhibition in non-small-cell lung cancer. N Engl J Med 363:1693–1703Google Scholar
  33. 33.
    Mossé YP, Voss SD, Lim MS et al (2017) Targeting ALK with crizotinib in pediatric anaplastic large cell lymphoma and inflammatory myofibroblastic tumor: A Children’s Oncology Group Study. J Clin Oncol 35:3215–3221PubMedPubMedCentralCrossRefGoogle Scholar
  34. 34.
    Maddocks K, Jones JA (2016) Bruton tyrosine kinase inhibition in chronic lymphocytic leukemia. Semin Oncol 43:251–259PubMedCrossRefGoogle Scholar
  35. 35.
    Byrd MC, Furman RR, Coutre SE et al (2013) Targeting BTK with ibrutinib in relapsed chronic lymphocytic leukemia. N Engl J Med 369:32–42PubMedPubMedCentralCrossRefGoogle Scholar
  36. 36.
    Seymour JF, Kipps TJ, Eichhorst B et al (2018) Venetoclax–rituximab in relapsed or refractory chronic lymphocytic leukemia. N Engl J Med 378:1107–1120PubMedCrossRefGoogle Scholar
  37. 37.
    Chen JK, Taipale J, Cooper MK et al (2002) Inhibition of hedgehog signaling by direct binding of cyclopamine to smoothened. Genes Dev 16:2743–2748CrossRefGoogle Scholar
  38. 38.
    Tremblay MR, Nevalainen M, Nair SJ et al (2008) Semisynthetic cyclopamine analogues as potent and orally bioavailable hedgehog pathway antagonists. J Med Chem 51:6646–6649PubMedCrossRefPubMedCentralGoogle Scholar
  39. 39.
    Gould SE, Low JA, Marsters JC Jr et al (2014) Discovery and preclinical development of vismodegib. Expert Opin Drug Discov 9:969–984PubMedCrossRefPubMedCentralGoogle Scholar
  40. 40.
    Von Hoff DD, LoRusso PM, Rudin CM et al (2009) Inhibition of the hedgehog pathway in advanced basal-cell carcinoma. N Engl J Med 361:1164–1172CrossRefGoogle Scholar
  41. 41.
    Sekulic A, Migden MR, Basset-Sequin N et al (2017) Long-term safety and efficacy of vismodegib in patients with advanced basal cell carcinoma: final update of the pivotal ERIVANCE BCC study. BMC Cancer 17:332–341PubMedPubMedCentralCrossRefGoogle Scholar
  42. 42.
    Pfeiffer P, Hansen RO, Rose C (1990) Systemic cytotoxic therapy of basal cell carcinoma: a review of the literature. Eur J Cancer 26:73–77PubMedCrossRefGoogle Scholar
  43. 43.
    Raffel C, Jenkins RB, Frederick L et al (1997) Sporadic medulloblastomas contain PTCH mutations. Cancer Res 57:842–845PubMedGoogle Scholar
  44. 44.
    Zeltzer PM, Boyett JM, Finlay JL et al (1999) Metastasis stage, adjuvant treatment, and residual tumor are prognostic factors for medulloblastoma in children: conclusions From the Children’s Cancer Group 921 randomized phase III study 17:832–845Google Scholar
  45. 45.
    Robinson GW, Orr BA, Wu G et al (2015) Vismodegib exerts targeted efficacy against recurrent sonic hedgehog-subgroup medulloblastoma: Results from phase II pediatric brain tumor consortium studies PBTC-025B and PBTC-032. J Clin Oncol 33:2646–2654PubMedPubMedCentralCrossRefGoogle Scholar
  46. 46.
    Henkin RI, Hosein S, Stateman WA, Knoppel AB (2016) Sonic Hedgehog in nasal mucous is a biomarker for smell loss in patients with hyposmia. Cell Mol Med 2:1–5CrossRefGoogle Scholar
  47. 47.
    Iyer G, Hanrahan AJ, Milowsky MI et al (2012) Genome sequencing identifies a basis for everolimus sensitivity. Science 338:221–223PubMedPubMedCentralCrossRefGoogle Scholar
  48. 48.
    López-Lago MA, Okada T, Murillo MM et al (2009) Loss of the tumor suppressor gene NF2, encoding merlin, constitutively activates integrin-dependent mTORC1 signaling. Mol Cell Biol 29(15):4235–49PubMedPubMedCentralCrossRefGoogle Scholar
  49. 49.
    Solomon BJ, Mok T, Kim D-W et al (2014) First-Line crizotinib versus chemotherapy in ALK-positive lung cancer. N Engl J Med 371:2167–2177CrossRefGoogle Scholar
  50. 50.
    Shaw AT, Kim DW, Nakagawa K et al (2013) Crizotinib versus chemotherapy in advanced ALK-positive lung cancer. N Engl J Med 368:2385–2394CrossRefGoogle Scholar
  51. 51.
    Demeure MJ, Aziz M, Rosenberg R, Gurley SD, Bussey KJ, Carpten JD (2014) Whole-genome sequencing of an aggressive BRAF wild-type papillary thyroid cancer identified EML4-ALK translocation as a therapeutic target. World J Surg 38:1296–1305PubMedCrossRefGoogle Scholar
  52. 52.
    Kelly LM, Barila G, Liu P et al (2014) Identification of the transforming STRN-ALK fusion as a potential therapeutic target in the aggressive forms of thyroid cancer. Proc Natl Acad Sci 111:4233–4238PubMedCrossRefGoogle Scholar
  53. 53.
    Stransky N, Cerami E, Schalm S, Kim JL, Lengauer C (2014) The landscape of kinase fusions in cancer. Nature Commun 5:4846.
  54. 54.
    Amatu A, Sartore-Bianchi A, Siena S (2016) NTRK gene fusions as novel targets of cancer therapy across multiple tumour types. ESMO Open.1:e000023. eCollection 2016PubMedPubMedCentralCrossRefGoogle Scholar
  55. 55.
    Kato S, Kurasaki K, Ikeda S, Kurzrock R (2017) Rare Tumor Clinic: The University of California San Diego Moores Cancer Center experience with precision medicine approach. Oncologist 22:1–8CrossRefGoogle Scholar
  56. 56.
    Von Hoff DD, Stephenson JJ Jr, Rosen P et al (2010) Pilot study using molecular profiling of patients’ tumors to find potential targets and select treatments for their refractory cancers. J Clin Oncol 28:4877–4883CrossRefGoogle Scholar
  57. 57.
    Haslem DS, Van Norman SB, Fulde G et al (2017) A retrospective analysis of precision medicine outcomes in patients with advanced cancer reveals improved progression-free survival without increased health care costs. J Oncol Pract 13:108–119CrossRefGoogle Scholar
  58. 58.
    Li MM, Datto M, Duncavage EJ et al (2017) standards and guidelines for the interpretation and reporting of sequence variants in cancer: a joint consensus recommendation of the Association for Molecular Pathology, American Society of Clinical Oncology, and College of American Pathologists. J Mol Diagn. 19:4–23PubMedPubMedCentralCrossRefGoogle Scholar
  59. 59.
    Rowley JD, Golomb HM, Dougherty C (1977) 15/17 translocation, a consistent chromosomal change in acute promyelocytic leukaemia. Lancet 309:549–550CrossRefGoogle Scholar
  60. 60.
    Wang YZ, Chen Z (2008) Acute promyelocytic leukemia: from highly fatal to highly curable. Blood 111:2505–2515PubMedCrossRefGoogle Scholar
  61. 61.
    Redig AJ, Jänne PA (2015) Basket trials and the evolution of clinical trial design in an era of genomic medicine. J Clin Oncol 33:975–977PubMedCrossRefGoogle Scholar
  62. 62.
    Dangi-Garimella S (2017) Innovative approach to precision medicine trial: NCI-MATCH and Beat AML. Am J Manag Care 23:sp32–sp33Google Scholar
  63. 63.
    Conley BA, Chen AP, O’Dwyer PJ et al (2016) NCI-MATCH (Molecular Analysis for Therapy Choice): a national signal finding trial. J Clin Oncol 34:15_suppl, TPS2606Google Scholar
  64. 64.
    Cunanan KM, Gonen M, Shen R et al (2017) Basket trials in oncology: a trade-off between complexity and efficiency. J Clin Oncol 35:271–275PubMedCrossRefGoogle Scholar
  65. 65.
    Diamond EL, Subbiah B, Lockhart AC et al (2018) Vemurafenib for BRAF V600–mutant Erdheim-Chester disease and Langerhans cell histiocytosis: Analysis of data from the histology-independent, phase 2, open-label VE-BASKET study. JAMA Oncol 4:384–388CrossRefGoogle Scholar
  66. 66.
    Hyman DM, Puzanov I, Subbiah C et al (2015) Vemurafenib in multiple nonmelanoma cancers with BRAF V600 mutations. N Engl J Med 373:726–736PubMedPubMedCentralCrossRefGoogle Scholar
  67. 67.
    Haroche J, Charlotte F, Arnaud L et al (2012) High prevalence of BRAF V600E mutations in Erdheim-Chester disease but not in other non-Langerhans cell histiocytoses. Blood 120:2700–2703PubMedCrossRefGoogle Scholar
  68. 68.
    Kim ES, Herbst RS, Wistuba II et al (2011) The BATTLE trial: personalizing therapy for lung cancer. Cancer Discov 1:44–53PubMedPubMedCentralCrossRefGoogle Scholar
  69. 69.
    Lopez-Chavez A, Thomas A, Rajan A et al (2015) Molecular profiling and targeted therapy for advanced thoracic malignancies: a biomarker-derived, multiarm, multihistology phase II basket trial. J Clin Oncol 33(9):1000–1007PubMedPubMedCentralCrossRefGoogle Scholar
  70. 70.
    Schwaederle M, Zhao M, Lee JJ et al (2015) Impact of precision medicine in diverse cancers: a meta-analysis of phase II clinical trials. J Clin Oncol 33:3817–3825PubMedPubMedCentralCrossRefGoogle Scholar
  71. 71.
    Zhang J, Walsh MF, Wu G et al (2015) Germline mutations in predisposition genes in pediatric cancer. N Engl J Med 373:2336–2346PubMedPubMedCentralCrossRefGoogle Scholar
  72. 72.
    Krishnan S, Basu G, Gonzalez-Malerva L et al (2016) Germline findings in targeted tumor sequencing using matched normal DNA. Cancer Res 76(14 Suppl), Abstract nr 4493Google Scholar
  73. 73.
    Schrader KA, Cheng DT, Joseph V et al (2016) Germline variants in targeted tumor sequencing using matched normal DNA. JAMA Oncol 2:104–111PubMedPubMedCentralCrossRefGoogle Scholar
  74. 74.
    Jones S, Anagnostou V, Lytle K et al (2015) Personalized genomic analyses for cancer mutation discovery and interpretation. Sci Transl Med 7(283):283ra53. Scholar
  75. 75.
    Pritchard CC, Mateo J, Walsh MF et al (2016) Inherited DNA-repair gene mutations in men with metastatic prostate cancer. N Engl J Med 375:443–453PubMedPubMedCentralCrossRefGoogle Scholar
  76. 76.
    Mateo J, Carreira S, Sandhu S et al (2015) DNA-repair defects and olaparib in metastatic prostate cancer. N Engl J Med 373:1697–1708PubMedPubMedCentralCrossRefGoogle Scholar
  77. 77.
    Cheng HH, Pritchard CC, Boyd T, Nelson PS, Montgomery B (2016) Biallelic inactivation of BRCA2 in platinum-sensitive metastatic castration-resistant prostate cancer. Eur Urol 69:992–995PubMedCrossRefGoogle Scholar
  78. 78.
    Hisada M, Garber JE, Fung CY, Fraumeni JF Jr, Li FP (1998) Multiple primary cancers in families with Li-Fraumeni syndrome. J Natl Cancer Inst 90:606–611PubMedCrossRefGoogle Scholar
  79. 79.
    Mai PL, Best AF, Peters JA et al (2016) Risks of first and subsequent cancers among TP53 mutation carriers in the national cancer institute Li-Fraumeni syndrome cohort. Cancer 122:3673–3681PubMedPubMedCentralCrossRefGoogle Scholar
  80. 80.
    Ballinger ML, Best A, Pai ML et al (2017) Baseline surveillance in Li-Faumeni syndrome using whole-body magnetic resonance imaging: a meta-analysis. JAMA Oncol 3:1634PubMedPubMedCentralCrossRefGoogle Scholar
  81. 81.
    Bojadzieva J, Amini B, Day SF et al (2018) Whole body magnetic resonance imaging (WB-MRI) and brain MRI baseline surveillance in TP53 germline mutation carriers: experience from the Li-Fraumeni syndrome education and early detection (LEAD) clinic. Fam Cancer. 17:287–294CrossRefGoogle Scholar
  82. 82.
    Pai ML, Kincha PP, Toud JT et al (2017) Prevalence of cancer at baseline screening in the national cancer institute Li-Fraumeni syndrome cohort. JAMA Oncol 3:1640CrossRefGoogle Scholar
  83. 83.
    Williams ED (1966) Histogenesis of medullary carcinoma of the thyroid. J Clin Pathol 19:114–118PubMedPubMedCentralCrossRefGoogle Scholar
  84. 84.
    Al-Rawi M, Wheeler MH (2006) Medullary thyroid cancer: update and present management controversies. Ann R Coll Surg Engl 88:433–438PubMedPubMedCentralCrossRefGoogle Scholar
  85. 85.
    Wells SA Jr, Chi DD, Toshima K et al (1994) Predictive DNA testing and prophylactic thyroidectomy in patients at risk for Multiple Endocrine Neoplasia Type 2A. Ann Surg 220:237–250PubMedPubMedCentralCrossRefGoogle Scholar
  86. 86.
    Wells SA Jr, Skinner MA (1998) Prophylactic thyroidectomy, based on direct genetic testing, in patients at risk for the multiple endocrine neoplasia type 2 syndromes. Exp Clin Endocrinol Diabetes 106:29–34PubMedCrossRefGoogle Scholar
  87. 87.
    Wells SA Jr, Asa SL, Dralle H et al (2015) Revised American Thyroid Association guidelines for the management of medullary thyroid carcinoma. Thyroid 25:567–610PubMedPubMedCentralCrossRefGoogle Scholar
  88. 88.
    Hansford S, Kaurah P, Li-Chang H et al (2015) Hereditary diffuse gastric cancer syndrome: CDH1 mutations and beyond. JAMA Oncol 1:23–32PubMedCrossRefGoogle Scholar
  89. 89.
    van der Post RS, Vogelaar IP, Carneiro F et al (2015) Hereditary diffuse gastric cancer: updated clinical guidelines with an emphasis on germline CDH1 mutation carriers. J Med Genet 52:361–74Google Scholar
  90. 90.
    Blair V, Martin I, Shaw D et al (2006) Hereditary diffuse gastric cancer: diagnosis and management. Clin Gastroenterol Hepatol 4(3):262–75PubMedCrossRefGoogle Scholar
  91. 91.
    Fitzgerald RC, Hardwick R, Huntsman D et al (2010) Hereditary diffuse gastric cancer: updated consensus guidelines for clinical management and directions for future research. J Med Genet 47:436–444PubMedPubMedCentralCrossRefGoogle Scholar
  92. 92.
    Montgomery ND, Selitsky SR, Patel NM et al (2018) Identification of germline variants in tumor Genomic sequencing analysis. J Mol Diagn 20:123–125PubMedCrossRefGoogle Scholar
  93. 93.
    Sun JX, He Y, Sanford E et al (2018 Feb 7) A computational approach to distinguish somatic vs. germline origin of genomic alterations from deep sequencing of cancer specimens without a matched normal. PLOS Comput Biol. Scholar
  94. 94.
    Green RC, Berg JS, Grody WW et al (2013) ACMG recommendations for reporting of incidental findings in clinical exome and genome sequencing. Genet Med 15:565–574PubMedPubMedCentralCrossRefGoogle Scholar
  95. 95.
    ACMG Board of Directors (2015) ACMG policy statement: updated recommendations regarding analysis and reporting of secondary findings in clinical genome-scale sequencing. Genet Med 17:68–69CrossRefGoogle Scholar
  96. 96.
    Kalia SS, Adelman K, Bale SJ et al (2017) Recommendations for reporting of secondary findings in clinical exome and genome sequencing, 2016 update (ACMG SF v2.0): a policy statement of the American College of Medical Genetics and Genomics. Genet Med 19:249–255Google Scholar
  97. 97.
    Garraway LA, Lander ES (2013) Lessons from the cancer genome. Cell 153:17–37PubMedCrossRefGoogle Scholar
  98. 98.
    Leiserson MD, Vandin F, Wu H et al (2015) Pan-cancer network analysis identifies combinations of rare somatic mutations across pathways and protein complexes. Nat Genet 47:106–114PubMedPubMedCentralCrossRefGoogle Scholar
  99. 99.
    Nakagawa H, Fujita M (2018) Whole genome sequencing analysis for cancer genomics and precision medicine. Cancer Sci 109:513–522PubMedPubMedCentralCrossRefGoogle Scholar
  100. 100.
    Fujimoto A, Furuta M, Totoki Y et al (2016) Whole genome mutational landscape and characterization of non-coding and structural mutations in liver cancer. Nat Genet 48:500–509PubMedCrossRefGoogle Scholar
  101. 101.
    Sung WK, Zheng H, Li S et al (2012) Genome-wide survery of recurrent HBV integration in hepatocellular carcinoma. Nat Genet 44:765–769PubMedCrossRefGoogle Scholar
  102. 102.
    Ojesina AI, Lichtenstein L, Freeman SS et al (2014) Landscape of genomic alterations in cervical carcinomas. Nature 506:371–375PubMedCrossRefGoogle Scholar
  103. 103.
    Tewhey R, Kotliar D, Park DS et al (2016) Direct identification of hundreds of expression-modifying variants using a multiplexed reporter assay. Cell 165:1519–1529PubMedPubMedCentralCrossRefGoogle Scholar
  104. 104.
    Zhang W, Bojorquez-Gomez A, Velez DO et al (2018) A global transcriptional network connecting noncoding mutations to changes in tumor gene expression. Nat Genet 50:613–620PubMedPubMedCentralCrossRefGoogle Scholar
  105. 105.
    Johannessen CM, Boehm JS (2017) Progress toward precision functional genomics in cancer. Curr Opinion in Sys Biol 2:74–83CrossRefGoogle Scholar
  106. 106.
    Alexandrov LB, Nik-Zainal S, Wedge DC et al (2013) Signatures of mutational processes in human cancer. Nature 500:415–421PubMedPubMedCentralCrossRefGoogle Scholar
  107. 107.
    Engert F, Kovac M, Baumhoer D, Nathrath M, Fuida S (2017) Osteosarcoma cells with genetic signatures of BRCAness are susceptible to the PARP inhibitor talazoparib alone or in combination with chemotherapeutics. Oncotarget 8:48794–48806PubMedCrossRefGoogle Scholar
  108. 108.
    Fong PC, Boss DS, Yap TA et al (2009) Inhibition of poly(ADP-ribose) polymerase in tumors from BRCA mutation carriers. N Engl J Med 361:123–134CrossRefGoogle Scholar
  109. 109.
    Wagner AH, Coffman AC, Ainscough BJ et al (2016) DGIdb 2.0: mining clinically relevant drug-gene interactions. Nucleic Acids Res 44:D1036–D1044PubMedPubMedCentralCrossRefGoogle Scholar
  110. 110.
    Scharovsky OG, Mainetti LE, Rozados VR (2009) Metronomic chemotherapy: changing the paradigm that more is better. Curr Oncol 16:7–15PubMedPubMedCentralCrossRefGoogle Scholar
  111. 111.
    Hartwell LH, Szankasi P, Robets CJ, Murray AW, Friend SH (1997) Integrating genetic approaches into the discovery of anticancer drugs. Science 278:1064–1068PubMedCrossRefPubMedCentralGoogle Scholar
  112. 112.
    Ye H, Zhang X, Chen Y, Liu Q, Wei J (2016) Ranking novel cancer driving synthetic lethal gene pairs using TCGA data. Oncotarget 7:55352–55367PubMedPubMedCentralGoogle Scholar
  113. 113.
    Patel SJ, Sanjana NE, Kishton RJ et al (2017) Identification of essential genes for cancer immunotherapy. Nature, 537–545PubMedPubMedCentralCrossRefGoogle Scholar
  114. 114.
    Fortier MH, Caron E, Hardy MP et al (2008) The MHC class I peptide repertoire is molded by the transcriptome. J Exp Med 205:595–610PubMedPubMedCentralCrossRefGoogle Scholar
  115. 115.
    Karasaki T, Nagayama K, Kuwano K et al (2017) Prediction and prioritization of neoantigens: intergration of RNA sequencing data with whole-exome sequencing. Cancer Sci 108:170–177PubMedPubMedCentralCrossRefGoogle Scholar
  116. 116.
    Wirth TC, Kühnel (2017) Neoantigen targeting—dawn of a new era in cancer immunotherapy. Front Immunol 8:1–16Google Scholar
  117. 117.
    Phillips KA, Deverka PA, Trosman JR et al (2017) Payer coverage policies for multigene tests. Nat Biotechnol 35:614–617PubMedPubMedCentralCrossRefGoogle Scholar
  118. 118.
    Kurian AW, Li Y, Hamilton AS et al (2017) Gaps in incorporating germline genetic testing into treatment decision-making for early-stage breast cancer. J Clin Oncol 35:2232–2239PubMedPubMedCentralCrossRefGoogle Scholar
  119. 119.
    Merchant GE, Lindor RA (2013) Personalized medicine and genetic malpractice. Genet Med 15:921–922. Scholar
  120. 120.
    Cerami et al (2012 May) The cBio cancer genomics portal: an open platform for exploring multidimensional cancer genomics data. Cancer Discov 2:401Google Scholar
  121. 121.
    Surveillance, Epidemiology, and End Results (SEER) Program populations (1969–2016) ( National Cancer Institute, DCCPS, Surveillance Research Program, released December 2017
  122. 122.
    Cancer Genome Atlas Research Network (2011) Integrated genomic analyses of ovarian carcinoma. Nature 474(7353):609Google Scholar
  123. 123.
    Dougherty BA, Lai Z, Hodgson DR, Orr MC, Hawryluk M, Sun J … Fielding A (2017) Biological and clinical evidence for somatic mutations in BRCA1 and BRCA2 as predictive markers for olaparib response in high-grade serous ovarian cancers in the maintenance setting. Oncotarget 8(27):43653–43661Google Scholar
  124. 124.
    Oza AM, Cibula D, Benzaquen AO, Poole C, Mathijssen RH, Sonke GS, … Mahner S (2015) Olaparib combined with chemotherapy for recurrent platinum-sensitive ovarian cancer: a randomised phase 2 trial. Lancet Oncol 16(1):87–97PubMedCrossRefGoogle Scholar
  125. 125.
    Cortesi L, Toss A, Cucinotto I (2018) Parp inhibitors for the treatment of ovarian cancer. Current cancer drug targets. (Epub ahead of print)Google Scholar
  126. 126.
    Balmana J, Tung NM, Isakoff SJ, Grana B, Ryan PD, Saura C, … Garber JE (2014) Phase I trial of olaparib in combination with cisplatin for the treatment of patients with advanced breast, ovarian and other solid tumors. Ann Oncol 25(8):1656–1663PubMedCrossRefGoogle Scholar
  127. 127.
    Del Conte G, Sessa C, Von Moos R, Vigano L, Digena T, Locatelli A … Gianni L (2014) Phase I study of olaparib in combination with liposomal doxorubicin in patients with advanced solid tumours. Br J Cancer 111(4):651PubMedPubMedCentralCrossRefGoogle Scholar
  128. 128.
    Lee JM, Hays JL, Annunziata CM, Noonan AM, Minasian L, Zujewski J A … Figg WD (2014) Phase I/Ib study of olaparib and carboplatin in BRCA1 or BRCA2 mutation-associated breast or ovarian cancer with biomarker analyses. J Natl Cancer Inst 106(6), dju089Google Scholar
  129. 129.
    Mirza MR, Monk BJ, Herrstedt J, Oza AM, Mahner S, Redondo A, Fabbro M et al (2016) Niraparib maintenance therapy in platinum-sensitive, recurrent ovarian cancer. N Engl J Med 375(22):2154–2164PubMedCrossRefGoogle Scholar
  130. 130.
    Coleman RL, Oza AM, Lorusso D, Aghajanian C, Oaknin A, Dean A, … Leary A (2017) Rucaparib maintenance treatment for recurrent ovarian carcinoma after response to platinum therapy (ARIEL3): a randomised, double-blind, placebo-controlled, phase 3 trial. The Lancet 390(10106):1949–1961Google Scholar
  131. 131.
    Toss A, Cortesi L (2013) Molecular mechanisms of PARP inhibitors in BRCA-related ovarian cancer. J Cancer Sci Therapy 5(11):409–416Google Scholar
  132. 132.
    Albertson DG (2006) Gene amplification in cancer. Trends Genet 22:447–455PubMedCrossRefGoogle Scholar
  133. 133.
    Jorde, LB, Carey, JC, Bamshad MJ (2015) Medical genetics e-Book. Elsevier Health Sciences (Page 324)Google Scholar
  134. 134.
    Laskar BZ, Majumder S (2017) Gene expression programming. In: Bio-inspired computing for information retrieval applications. IGI Global, pp 269–292 (Page 270)Google Scholar
  135. 135.
    Latysheva NS, Babu MM (2016) Discovering and understanding oncogenic gene fusions through data intensive computational approaches. Nucleic Acids Res 44:4487–4503PubMedPubMedCentralCrossRefGoogle Scholar
  136. 136.
    Lynch TJ, Bell DW, Sordella R et al (2004) Activating mutations in the epidermal growth factor receptor underlying responsiveness of non-small-cell lung cancer to gefitinib. N Engl J Med 350:2129–2139CrossRefGoogle Scholar
  137. 137.
    Nussbaum RL, McInnes RR, Willard HF (2016) Thompson & Thompson genetics in medicine, 8th edn. Elsevier Health Sciences, Philadephia, pp 314–502Google Scholar
  138. 138.
    Richards S, Aziz N, Bale S et al (2015) Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genet Med. 17:405–424PubMedPubMedCentralCrossRefGoogle Scholar
  139. 139.
    Rizvi S, Borad MJ (2016) The rise of the FGFR inhibitor in advanced biliary cancer: the next cover of time magazine? J Gastrointest Oncol. 7(5):789–796PubMedPubMedCentralCrossRefGoogle Scholar
  140. 140.
    Tiacci E, Trifonov V, Schiavoni G et al (2011) BRAF mutations in hairy-cell leukemia. N Engl J Med 364:2305–2315PubMedPubMedCentralCrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Hoag Family Cancer InstituteNewport BeachUSA
  2. 2.Translational Genomics Research InstitutePhoenixUSA

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