Skip to main content

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

  • Chapter
  • First Online:
Precision Medicine in Cancer Therapy

Part of the book series: Cancer Treatment and Research ((CTAR,volume 178))

Abstract

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.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

eBook
USD 16.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 16.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 129.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Pillai RK, Jayasree K (2017) Rare cancers: challenges & issues. Indian J Med Res 145:17–27

    Article  PubMed  PubMed Central  Google Scholar 

  2. Greenlee RT, Goodman MT, Lynch CF et al (2010) The occurrence of rare cancers in U.S. adults, 1995–2004. Public Health Rep 125:28–43

    Article  PubMed  PubMed Central  Google Scholar 

  3. Tucker TC, Howe HL (2001) Measuring the quality of population-based cancer registries: the NAACR perspective. J Reg Manag 28:41–44

    Google Scholar 

  4. Trice Loggers E, Prigerson HG (2014) The end-of-life experience of patients with rare cancers and their caregivers. Rare Tumors 6:24–27

    Article  Google Scholar 

  5. DeSantis CE, Kramer JL, Jemal A (2017) The burden of rare cancers in the United States. CA Cancer J Clin 67:261–272

    Article  PubMed  Google Scholar 

  6. Gatta C, Ciccolallo L, Kunkler I et al (2006) Survival from rare cancer in adults: a population-based study. Lancet Oncol 7:132–140

    Article  PubMed  Google Scholar 

  7. Fassnacht M, Terzolo M, Allolio B et al (2012) Combination chemotherapy in advanced adrenocortical carcinoma. N Engl J Med 366:2189–2197

    Article  CAS  PubMed  Google Scholar 

  8. Smith SM, Coleman J, Bridge JA, Iwenofu OH (2015) Molecular diagnostics in soft tissue sarcoma and gastrointestinal stromal tumors. J Surg Oncol 111:520–531

    Article  PubMed  Google Scholar 

  9. Schaefer IM, Cote GM, Hornick JL (2017) Contemporary sarcoma diagnosis, genetics, and genomics. J Clin Oncol 36:101–110

    Article  CAS  PubMed  Google Scholar 

  10. Fletcher CDM, Unni KK, Mertens F (2002) WHO classification of tumours of soft tissue and bone, 3rd edn. IARC Press, Lyon, France

    Google Scholar 

  11. Fletcher CD, Hogendoorn P, Mertens F, Bridge J (2013) WHO classification of tumours of soft tissue and bone, 4th edn. IARC Press, Lyon, France

    Google Scholar 

  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 17:532–538

    Article  CAS  PubMed  Google Scholar 

  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 3:602–609

    Article  PubMed  PubMed Central  Google Scholar 

  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 33:316–321

    Article  PubMed  Google Scholar 

  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 24:2325–2331

    Article  CAS  PubMed  Google Scholar 

  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, 87–391

    Google Scholar 

  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–v88

    Article  PubMed  PubMed Central  Google Scholar 

  18. Ohgaki H, Kleihues P (2007) Genetic pathways to primary and secondary glioblastoma. Am J Pathol 170:1445–1453

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Parsons DW, Jones S, Zhang X et al (2008) An integrated genomic analysis of human glioblastoma multiforme. Science 321:1807–1812

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Yan H, Parsons W, Jim G et al (2009) IHD1 and IDH2 mutations in gliomas. N Engl J Med 360:765–773

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  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 365:1054–1061

    Article  CAS  PubMed  Google Scholar 

  22. Tam CS, Nussenzveig RM, Popat U et al (2008) The natural history and treatment outcome of blast phase BCR-ABL- myeloproliferative neoplasms. Blood 112:1628–1637

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  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 110:375–379

    Article  CAS  PubMed  Google Scholar 

  24. Vannucchi A, Kiladjian JJ, Griesshammer M et al (2015) Ruxolitinib versus standard therapy for the treatment of polycythemia vera. N Engl J Med 372:426–435

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  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 144:377–392

    Article  CAS  PubMed  Google Scholar 

  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 347:481–487

    Article  CAS  PubMed  Google Scholar 

  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 92:1173–1179

    Article  CAS  PubMed  Google Scholar 

  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 15:473–478

    Article  CAS  Google Scholar 

  29. Tefferi A, Gotlib J, Pardanani A (2010) Hypereosinophilic syndrome and clonal eosinophilia: point-of-care diagnostic algorithm and treatment update. Mayo Clin Proc 85:158–164

    Article  PubMed  PubMed Central  Google Scholar 

  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 50:128–134

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Lovly CM, Gupta A, Lipson D et al (2014) Inflammatory myofibroblastic tumors harbor multiple potentially actionable kinase fusions. Cancer Discov 4:889–895

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Kwak EL, Bang YJ, Camidge Dr et al (2010) Anaplastic lymphoma kinase inhibition in non-small-cell lung cancer. N Engl J Med 363:1693–1703

    Google Scholar 

  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 35:3215–3221

    Article  PubMed  PubMed Central  Google Scholar 

  34. Maddocks K, Jones JA (2016) Bruton tyrosine kinase inhibition in chronic lymphocytic leukemia. Semin Oncol 43:251–259

    Article  CAS  PubMed  Google Scholar 

  35. Byrd MC, Furman RR, Coutre SE et al (2013) Targeting BTK with ibrutinib in relapsed chronic lymphocytic leukemia. N Engl J Med 369:32–42

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Seymour JF, Kipps TJ, Eichhorst B et al (2018) Venetoclax–rituximab in relapsed or refractory chronic lymphocytic leukemia. N Engl J Med 378:1107–1120

    Article  CAS  PubMed  Google Scholar 

  37. Chen JK, Taipale J, Cooper MK et al (2002) Inhibition of hedgehog signaling by direct binding of cyclopamine to smoothened. Genes Dev 16:2743–2748

    Article  CAS  Google Scholar 

  38. Tremblay MR, Nevalainen M, Nair SJ et al (2008) Semisynthetic cyclopamine analogues as potent and orally bioavailable hedgehog pathway antagonists. J Med Chem 51:6646–6649

    Article  CAS  PubMed  Google Scholar 

  39. Gould SE, Low JA, Marsters JC Jr et al (2014) Discovery and preclinical development of vismodegib. Expert Opin Drug Discov 9:969–984

    Article  CAS  PubMed  Google Scholar 

  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 361:1164–1172

    Article  Google Scholar 

  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 17:332–341

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  42. Pfeiffer P, Hansen RO, Rose C (1990) Systemic cytotoxic therapy of basal cell carcinoma: a review of the literature. Eur J Cancer 26:73–77

    Article  CAS  PubMed  Google Scholar 

  43. Raffel C, Jenkins RB, Frederick L et al (1997) Sporadic medulloblastomas contain PTCH mutations. Cancer Res 57:842–845

    CAS  PubMed  Google Scholar 

  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 17:832–845

    Google Scholar 

  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 33:2646–2654

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  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 2:1–5

    Article  Google Scholar 

  47. Iyer G, Hanrahan AJ, Milowsky MI et al (2012) Genome sequencing identifies a basis for everolimus sensitivity. Science 338:221–223

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  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):4235–49

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  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 371:2167–2177

    Article  CAS  PubMed  Google Scholar 

  50. Shaw AT, Kim DW, Nakagawa K et al (2013) Crizotinib versus chemotherapy in advanced ALK-positive lung cancer. N Engl J Med 368:2385–2394

    Article  CAS  PubMed  Google Scholar 

  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 38:1296–1305

    Article  PubMed  Google Scholar 

  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 111:4233–4238

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Stransky N, Cerami E, Schalm S, Kim JL, Lengauer C (2014) The landscape of kinase fusions in cancer. Nature Commun 5:4846. https://doi.org/10.1038/ncomms5846

  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 2016

    Article  PubMed  PubMed Central  Google Scholar 

  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 22:1–8

    Article  Google Scholar 

  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 28:4877–4883

    Article  CAS  Google Scholar 

  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 13:108–119

    Article  Google Scholar 

  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. 19:4–23

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Rowley JD, Golomb HM, Dougherty C (1977) 15/17 translocation, a consistent chromosomal change in acute promyelocytic leukaemia. Lancet 309:549–550

    Article  Google Scholar 

  60. Wang YZ, Chen Z (2008) Acute promyelocytic leukemia: from highly fatal to highly curable. Blood 111:2505–2515

    Article  CAS  PubMed  Google Scholar 

  61. Redig AJ, Jänne PA (2015) Basket trials and the evolution of clinical trial design in an era of genomic medicine. J Clin Oncol 33:975–977

    Article  CAS  PubMed  Google Scholar 

  62. Dangi-Garimella S (2017) Innovative approach to precision medicine trial: NCI-MATCH and Beat AML. Am J Manag Care 23:sp32–sp33

    Google Scholar 

  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, TPS2606

    Google Scholar 

  64. Cunanan KM, Gonen M, Shen R et al (2017) Basket trials in oncology: a trade-off between complexity and efficiency. J Clin Oncol 35:271–275

    Article  PubMed  Google Scholar 

  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 4:384–388

    Article  PubMed  Google Scholar 

  66. Hyman DM, Puzanov I, Subbiah C et al (2015) Vemurafenib in multiple nonmelanoma cancers with BRAF V600 mutations. N Engl J Med 373:726–736

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  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 120:2700–2703

    Article  CAS  PubMed  Google Scholar 

  68. Kim ES, Herbst RS, Wistuba II et al (2011) The BATTLE trial: personalizing therapy for lung cancer. Cancer Discov 1:44–53

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  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):1000–1007

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  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 33:3817–3825

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. Zhang J, Walsh MF, Wu G et al (2015) Germline mutations in predisposition genes in pediatric cancer. N Engl J Med 373:2336–2346

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  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 4493

    Google Scholar 

  73. Schrader KA, Cheng DT, Joseph V et al (2016) Germline variants in targeted tumor sequencing using matched normal DNA. JAMA Oncol 2:104–111

    Article  PubMed  PubMed Central  Google Scholar 

  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. https://doi.org/10.1126/scitranslmed.aaa7161

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  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 375:443–453

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  76. Mateo J, Carreira S, Sandhu S et al (2015) DNA-repair defects and olaparib in metastatic prostate cancer. N Engl J Med 373:1697–1708

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  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 69:992–995

    Article  CAS  PubMed  Google Scholar 

  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 90:606–611

    Article  CAS  PubMed  Google Scholar 

  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 122:3673–3681

    Article  CAS  PubMed  Google Scholar 

  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 3:1634

    Article  PubMed  Google Scholar 

  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. 17:287–294

    Article  Google Scholar 

  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 3:1640

    Article  Google Scholar 

  83. Williams ED (1966) Histogenesis of medullary carcinoma of the thyroid. J Clin Pathol 19:114–118

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  84. Al-Rawi M, Wheeler MH (2006) Medullary thyroid cancer: update and present management controversies. Ann R Coll Surg Engl 88:433–438

    Article  PubMed  PubMed Central  Google Scholar 

  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 220:237–250

    Article  PubMed  PubMed Central  Google Scholar 

  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 106:29–34

    Article  CAS  PubMed  Google Scholar 

  87. Wells SA Jr, Asa SL, Dralle H et al (2015) Revised American Thyroid Association guidelines for the management of medullary thyroid carcinoma. Thyroid 25:567–610

    Article  PubMed  PubMed Central  Google Scholar 

  88. Hansford S, Kaurah P, Li-Chang H et al (2015) Hereditary diffuse gastric cancer syndrome: CDH1 mutations and beyond. JAMA Oncol 1:23–32

    Article  PubMed  Google Scholar 

  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 52:361–74

    Google Scholar 

  90. Blair V, Martin I, Shaw D et al (2006) Hereditary diffuse gastric cancer: diagnosis and management. Clin Gastroenterol Hepatol 4(3):262–75

    Article  CAS  PubMed  Google Scholar 

  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 47:436–444

    Article  CAS  PubMed  Google Scholar 

  92. Montgomery ND, Selitsky SR, Patel NM et al (2018) Identification of germline variants in tumor Genomic sequencing analysis. J Mol Diagn 20:123–125

    Article  PubMed  Google Scholar 

  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. https://doi.org/10.1371/journal.pcbi.1005965

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  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 15:565–574

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  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 17:68–69

    Article  Google Scholar 

  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 19:249–255

    Google Scholar 

  97. Garraway LA, Lander ES (2013) Lessons from the cancer genome. Cell 153:17–37

    Article  CAS  PubMed  Google Scholar 

  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 47:106–114

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  99. Nakagawa H, Fujita M (2018) Whole genome sequencing analysis for cancer genomics and precision medicine. Cancer Sci 109:513–522

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  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 48:500–509

    Article  CAS  PubMed  Google Scholar 

  101. Sung WK, Zheng H, Li S et al (2012) Genome-wide survery of recurrent HBV integration in hepatocellular carcinoma. Nat Genet 44:765–769

    Article  CAS  PubMed  Google Scholar 

  102. Ojesina AI, Lichtenstein L, Freeman SS et al (2014) Landscape of genomic alterations in cervical carcinomas. Nature 506:371–375

    Article  CAS  PubMed  Google Scholar 

  103. Tewhey R, Kotliar D, Park DS et al (2016) Direct identification of hundreds of expression-modifying variants using a multiplexed reporter assay. Cell 165:1519–1529

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  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 50:613–620

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  105. Johannessen CM, Boehm JS (2017) Progress toward precision functional genomics in cancer. Curr Opinion in Sys Biol 2:74–83

    Article  Google Scholar 

  106. Alexandrov LB, Nik-Zainal S, Wedge DC et al (2013) Signatures of mutational processes in human cancer. Nature 500:415–421

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  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 8:48794–48806

    Article  PubMed  Google Scholar 

  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 361:123–134

    Article  CAS  PubMed  Google Scholar 

  109. Wagner AH, Coffman AC, Ainscough BJ et al (2016) DGIdb 2.0: mining clinically relevant drug-gene interactions. Nucleic Acids Res 44:D1036–D1044

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  110. Scharovsky OG, Mainetti LE, Rozados VR (2009) Metronomic chemotherapy: changing the paradigm that more is better. Curr Oncol 16:7–15

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  111. Hartwell LH, Szankasi P, Robets CJ, Murray AW, Friend SH (1997) Integrating genetic approaches into the discovery of anticancer drugs. Science 278:1064–1068

    Article  CAS  PubMed  Google Scholar 

  112. Ye H, Zhang X, Chen Y, Liu Q, Wei J (2016) Ranking novel cancer driving synthetic lethal gene pairs using TCGA data. Oncotarget 7:55352–55367

    PubMed  PubMed Central  Google Scholar 

  113. Patel SJ, Sanjana NE, Kishton RJ et al (2017) Identification of essential genes for cancer immunotherapy. Nature, 537–545

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  114. Fortier MH, Caron E, Hardy MP et al (2008) The MHC class I peptide repertoire is molded by the transcriptome. J Exp Med 205:595–610

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  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 108:170–177

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  116. Wirth TC, Kühnel (2017) Neoantigen targeting—dawn of a new era in cancer immunotherapy. Front Immunol 8:1–16

    Google Scholar 

  117. Phillips KA, Deverka PA, Trosman JR et al (2017) Payer coverage policies for multigene tests. Nat Biotechnol 35:614–617

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  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 35:2232–2239

    Article  PubMed  PubMed Central  Google Scholar 

  119. Merchant GE, Lindor RA (2013) Personalized medicine and genetic malpractice. Genet Med 15:921–922. https://doi.org/10.1038/gim.2013.142

    Article  Google Scholar 

  120. Cerami et al (2012 May) The cBio cancer genomics portal: an open platform for exploring multidimensional cancer genomics data. Cancer Discov 2:401

    Google Scholar 

  121. Surveillance, Epidemiology, and End Results (SEER) Program populations (1969–2016) (www.seer.cancer.gov/popdata). National Cancer Institute, DCCPS, Surveillance Research Program, released December 2017

  122. Cancer Genome Atlas Research Network (2011) Integrated genomic analyses of ovarian carcinoma. Nature 474(7353):609

    Google Scholar 

  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):43653–43661

    Google Scholar 

  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):87–97

    Article  CAS  PubMed  Google Scholar 

  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. 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):1656–1663

    Article  PubMed  Google Scholar 

  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):651

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  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), dju089

    Google Scholar 

  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):2154–2164

    Article  CAS  PubMed  Google Scholar 

  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):1949–1961

    Google Scholar 

  131. Toss A, Cortesi L (2013) Molecular mechanisms of PARP inhibitors in BRCA-related ovarian cancer. J Cancer Sci Therapy 5(11):409–416

    Google Scholar 

  132. Albertson DG (2006) Gene amplification in cancer. Trends Genet 22:447–455

    Article  CAS  PubMed  Google Scholar 

  133. Jorde, LB, Carey, JC, Bamshad MJ (2015) Medical genetics e-Book. Elsevier Health Sciences (Page 324)

    Google Scholar 

  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. Latysheva NS, Babu MM (2016) Discovering and understanding oncogenic gene fusions through data intensive computational approaches. Nucleic Acids Res 44:4487–4503

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  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 350:2129–2139

    Article  CAS  PubMed  Google Scholar 

  137. Nussbaum RL, McInnes RR, Willard HF (2016) Thompson & Thompson genetics in medicine, 8th edn. Elsevier Health Sciences, Philadephia, pp 314–502

    Google Scholar 

  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. 17:405–424

    Article  PubMed  PubMed Central  Google Scholar 

  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):789–796

    Article  PubMed  PubMed Central  Google Scholar 

  140. Tiacci E, Trifonov V, Schiavoni G et al (2011) BRAF mutations in hairy-cell leukemia. N Engl J Med 364:2305–2315

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

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

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Michael J. Demeure .

Editor information

Editors and Affiliations

Appendices

A Case Report from a Rare Cancer Precision Medicine Tumor Board

A 41-year-old woman with no family history of cancer was diagnosed with moderately differentiated serous adenocarcinoma of ovary. She underwent a radical hysterectomy with tumor debulking, followed by chemotherapy with carboplatin and paclitaxel (paclitaxel/carboplatin). The patient later developed recurrence of her cancer and was treated with carboplatin heated intraperitoneal chemotherapy.

A comprehensive somatic 592-gene sequencing panel tumor profiling (Caris Life Sciences, Phoenix AZ) was performed on the patient’s tumor. The results showed no microsatellite instability (MSI), proficient mismatch repair by immunohistochemistry, estrogen receptor positive immunostaining, and a pathogenic variant in BRCA1 gene, p.K1254fs (Table 3.4). The gene encodes BRCA1 protein that is involved in DNA damage repair. Pathogenic variants in this gene have been associated with increased risk of several types of cancer, including hereditary breast and ovarian cancer. Somatic BRCA1 mutations are illustrated in Fig. 3.1 with 63 truncating mutations from The Cancer Genome Atlas (TCGA) [120]. The specific loss of function BRCA1 mutation identified in this patient’s tumor could be a potential germline variant, so referral to a genetic counselor and germline testing is recommended. Individuals who harbor germline mutations in BRCA1 are at increased risk for cancers of the breast, ovary, prostate, pancreas, and possibly colon and other cancers.

Table 3.4 Highlights of patient’s tumor profiling results
Fig. 3.1
figure 1

Spectrum of reported BRCA1 truncating mutations in cBIo portal [120]. The blue arrow indicates the approximate region where the p.K1254fs variant identified in this patient occurred. The horizontal axis displays the identified truncating mutations in 1754 samples (from three different TCGA datasets), and the boxes are BRCA1 domains. The vertical axis indicates the frequency of the identified variants

Ovarian cancer is estimated to be responsible for approximately 2.3% of all cancer deaths in the USA in 2018 [121]. Approximately half of tumors in patients with high-grade serous ovarian cancer have homologous recombination repair deficiencies, which are most often caused by pathogenic mutations in the BRCA1 or BRCA2 genes [122]. Germline mutations in BRCA1 and BRCA2 are also frequently seen in patients with high-grade serous ovarian cancer [123]. Homologous recombination repair deficiencies lead to insufficient double-stranded DNA breaks repair [124]. Poly (ADP-ribose) polymerase (PARP) enzymes repair single-stranded DNA breaks with a mechanism called base excision repair (BER). Inhibition of PARP in tumors with homologous recombination repair deficiencies causes inaccurate DNA repair leading to cell cycle arrest and apoptosis, as it is illustrated in Fig. 3.2 [124, 125].

Fig. 3.2
figure 2

Molecular mechanism of PARP inhibition (PARPi). Single-strand break (SSB) DNA repair is carried by mismatch repair (MMR), nucleic acid excision repair (NER), and base excision repair (BER) mechanisms. PARPi impairs BER, so an SSB becomes a double-strand break (DSB). Non-homologous end joining (NHEJ) and homologous recombination (HR) mechanisms are involved in DSB repair. When PARP inhibition occurs in a patient who has a homologous recombination repair (HR) deficiency, due to a BRCA mutation, then a DSB cannot be repaired and cell death or apoptosis results [125, 131]

Olaparib is a PARP inhibitor and is approved to treat patients with ovarian cancer that harbor BRCA1 or BRCA2 mutations. Patients with platinum-sensitive high-grade serous ovarian cancer and somatic or germline BRCA1/2 mutations benefit similarly from olaparib treatment; progression-free survival (PFS) is illustrated in Fig. 3.3 [123]. A combination of olaparib with chemotherapy (carboplatin and paclitaxel) in patients with an advanced breast and ovarian cancer showed significant results [126–128]. There are other PARP inhibitors on the market such as niraparib and rucaparib. In a randomized, placebo control phase III clinical trial, niraparib increased PFS in patients with recurrent ovarian cancer [129]. The AREL3 study, a randomized, placebo control double-blinded phase III study, showed rucaparib in patients with platinum-sensitive ovarian cancer improved PFS [130].

Fig. 3.3
figure 3

Progression-free survival of patients with BRCA1/2 somatic mutations compared with the ones with germline mutations treated with olaparib or placebo. The blue line is the group treated with olaparib, and the black line is for the placebo group (from Dougherty [123])

Thus, the results from tumor profiling, along with the outcomes from several clinical trials, provide valuable information to help clinicians offer a personalized precision care for this patient. If the BRCA1 mutation proves to be a germline mutation, then family members should be referred for genetic counseling as well.

Take Home Points

  1. (1)

    Referral to genetic counseling for germline testing is recommended based on the tumor profiling results;

  2. (2)

    Consider PARPi to treat the patient according to the data, showing the efficacy of PARPi in patients with BRCA mutations.

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Demeure, M.J. (2019). The Role of Precision Medicine in the Diagnosis and Treatment of Patients with Rare Cancers. In: Von Hoff, D., Han, H. (eds) Precision Medicine in Cancer Therapy . Cancer Treatment and Research, vol 178. Springer, Cham. https://doi.org/10.1007/978-3-030-16391-4_3

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-16391-4_3

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-16390-7

  • Online ISBN: 978-3-030-16391-4

  • eBook Packages: MedicineMedicine (R0)

Publish with us

Policies and ethics