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Clinical cancer genomic profiling

Nature Reviews Genetics volume 22, pages 483–501 (2021)Cite this article

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Abstract

Technological innovation and rapid reduction in sequencing costs have enabled the genomic profiling of hundreds of cancer-associated genes as a component of routine cancer care. Tumour genomic profiling can refine cancer subtype classification, identify which patients are most likely to benefit from systemic therapies and screen for germline variants that influence heritable cancer risk. Here, we discuss ongoing efforts to enhance the clinical utility of tumour genomic profiling by integrating tumour and germline analyses, characterizing allelic context and identifying mutational signatures that influence therapy response. We also discuss the potential clinical utility of more comprehensive whole-genome and whole-transcriptome sequencing and ultra-sensitive cell-free DNA profiling platforms, which allow for minimally invasive, serial analyses of tumour-derived DNA in blood.

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Fig. 1: Clinical applications of tumour sequencing.
Fig. 2: Current landscape of clinical actionability.
Fig. 3: Detection of low-frequency mutations in tumour cell-free DNA.
Fig. 4: Expanding the clinical utility of tumour genomic profiling.

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References

  1. Sobin, L. H. The international histological classification of tumours. Bull. World Health Organ. 59, 813–819 (1981).

    CAS  PubMed  PubMed Central  Google Scholar 

  2. Hoadley, K. A. et al. Multiplatform analysis of 12 cancer types reveals molecular classification within and across tissues of origin. Cell 158, 929–944 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Bouwman, P. & Jonkers, J. The effects of deregulated DNA damage signalling on cancer chemotherapy response and resistance. Nat. Rev. Cancer 12, 587–598 (2012).

    Article  CAS  PubMed  Google Scholar 

  4. Yarchoan, M., Hopkins, A. & Jaffee, E. M. Tumor mutational burden and response rate to PD-1 inhibition. N. Engl. J. Med. 377, 2500–2501 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  5. Hyman, D. M. et al. Vemurafenib in multiple nonmelanoma cancers with BRAF V600 mutations. N. Engl. J. Med. 373, 726–736 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Drilon, A. et al. Efficacy of larotrectinib in TRK fusion-positive cancers in adults and children. N. Engl. J. Med. 378, 731–739 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Hyman, D. M. et al. AKT inhibition in solid tumors with AKT1 mutations. J. Clin. Oncol. 35, 2251–2259 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Hungerford, D. A. & Nowell, P. C. A minute chromosome in human chronic granulocytic leukemia. Science 132, 1497–1499 (1960).

    Google Scholar 

  9. de Klein, A. et al. A cellular oncogene is translocated to the Philadelphia chromosome in chronic myelocytic leukaemia. Nature 300, 765–767 (1982).

    Article  PubMed  Google Scholar 

  10. Kantarjian, H. et al. Improved survival in chronic myeloid leukemia since the introduction of imatinib therapy: a single-institution historical experience. Blood 119, 1981–1987 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Prasad, V. Perspective: the precision-oncology illusion. Nature 537, S63 (2016).

    Article  CAS  PubMed  Google Scholar 

  12. Hyman, D. M., Taylor, B. S. & Baselga, J. Implementing genome-driven oncology. Cell 168, 584–599 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Pan, Y. et al. ALK, ROS1 and RET fusions in 1139 lung adenocarcinomas: a comprehensive study of common and fusion pattern-specific clinicopathologic, histologic and cytologic features. Lung Cancer 84, 121–126 (2014).

    Article  PubMed  Google Scholar 

  14. Mansfield, E. A. FDA perspective on companion diagnostics: an evolving paradigm. Clin. Cancer Res. 20, 1453–1457 (2014).

    Article  CAS  PubMed  Google Scholar 

  15. Kris, M. G. et al. Using multiplexed assays of oncogenic drivers in lung cancers to select targeted drugs. JAMA 311, 1998–2006 (2014).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  16. Jordan, E. J. et al. Prospective comprehensive molecular characterization of lung adenocarcinomas for efficient patient matching to approved and emerging therapies. Cancer Discov. 7, 596–609 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Su, Z. et al. A platform for rapid detection of multiple oncogenic mutations with relevance to targeted therapy in non-small-cell lung cancer. J. Mol. Diagn. 13, 74–84 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. MacConaill, L. E. et al. Prospective enterprise-level molecular genotyping of a cohort of cancer patients. J. Mol. Diagn. 16, 660–672 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Li, T., Kung, H.-J., Mack, P. C. & Gandara, D. R. Genotyping and genomic profiling of non-small-cell lung cancer: implications for current and future therapies. J. Clin. Oncol. 31, 1039–1049 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Zehir, A. et al. Mutational landscape of metastatic cancer revealed from prospective clinical sequencing of 10,000 patients. Nat. Med. 23, 703–713 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Sholl, L. M. et al. Institutional implementation of clinical tumor profiling on an unselected cancer population. JCI Insight 1, e87062 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  22. Meric-Bernstam, F. et al. Feasibility of large-scale genomic testing to facilitate enrollment onto genomically matched clinical trials. J. Clin. Oncol. 33, 2753–2762 (2015).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  23. Stockley, T. L. et al. Molecular profiling of advanced solid tumors and patient outcomes with genotype-matched clinical trials: the Princess Margaret IMPACT/COMPACT trial. Genome Med. 8, 109 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  24. Odegaard, J. I. et al. Validation of a plasma-based comprehensive cancer genotyping assay utilizing orthogonal tissue- and plasma-based methodologies. Clin. Cancer Res. 24, 3539–3549 (2018).

    Article  CAS  PubMed  Google Scholar 

  25. Brannon, A. R. et al. Enhanced specificity of high sensitivity somatic variant profiling in cell-free DNA via paired normal sequencing: design, validation, and clinical experience of the MSK-ACCESS liquid biopsy assay. Preprint at bioRxiv https://doi.org/10.21203/rs.3.rs-120695/v1 (2020).

    Article  Google Scholar 

  26. Tao, J. J., Schram, A. M. & Hyman, D. M. Basket studies: redefining clinical trials in the era of genome-driven oncology. Annu. Rev. Med. 69, 319–331 (2018).

    Article  CAS  PubMed  Google Scholar 

  27. Redig, A. J. & Jänne, P. A. Basket trials and the evolution of clinical trial design in an era of genomic medicine. J. Clin. Oncol. 33, 975–977 (2015).

    Article  CAS  PubMed  Google Scholar 

  28. Woodcock, J. & LaVange, L. M. Master protocols to study multiple therapies, multiple diseases, or both. N. Engl. J. Med. 377, 62–70 (2017).

    Article  CAS  PubMed  Google Scholar 

  29. Le, D. T. et al. PD-1 blockade in tumors with mismatch-repair deficiency. N. Engl. J. Med. 372, 2509–2520 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Drilon, A. E. et al. A phase II basket study of the oral TRK inhibitor LOXO-101 in adult subjects with NTRK fusion-positive tumors. J. Clin. Oncol. 34, TPS2599–TPS2599 (2016).

    Article  Google Scholar 

  31. Berger, M. F. & Mardis, E. R. The emerging clinical relevance of genomics in cancer medicine. Nat. Rev. Clin. Oncol. 15, 353–365 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Vogelstein, B. et al. Cancer genome landscapes. Science 339, 1546–1558 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Bailey, M. H. et al. Comprehensive characterization of cancer driver genes and mutations. Cell 173, 371–385.e18 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Farmer, H. et al. Targeting the DNA repair defect in BRCA mutant cells as a therapeutic strategy. Nature 434, 917–921 (2005).

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Van Allen, E. M. et al. Somatic ERCC2 mutations correlate with cisplatin sensitivity in muscle-invasive urothelial carcinoma. Cancer Discov. 4, 1140–1153 (2014).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  37. Li, Q. et al. ERCC2 helicase domain mutations confer nucleotide excision repair deficiency and drive cisplatin sensitivity in muscle-invasive bladder cancer. Clin. Cancer Res. 25, 977–988 (2019).

    Article  CAS  PubMed  Google Scholar 

  38. Kelderman, S., Schumacher, T. N. & Kvistborg, P. Mismatch repair-deficient cancers are targets for anti-PD-1 therapy. Cancer Cell 28, 11–13 (2015).

    Article  CAS  PubMed  Google Scholar 

  39. Chang, M. T. et al. Identifying recurrent mutations in cancer reveals widespread lineage diversity and mutational specificity. Nat. Biotechnol. 34, 155–163 (2016).

    Article  CAS  PubMed  Google Scholar 

  40. Chang, M. T. et al. Accelerating discovery of functional mutant alleles in cancer. Cancer Discov. 8, 174–183 (2018).

    Article  CAS  PubMed  Google Scholar 

  41. Hanrahan, A. J. et al. Leveraging systematic functional analysis to benchmark an in silico framework distinguishes driver from passenger MEK mutants in cancer. Cancer Res. 80, 4233–301 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Hess, J. M. et al. Passenger hotspot mutations in cancer. Cancer Cell 36, 288–301.e14 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Buisson, R. et al. Passenger hotspot mutations in cancer driven by APOBEC3A and mesoscale genomic features. Science 364, eaaw2872 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Holbrook, J. A., Neu-Yilik, G., Hentze, M. W. & Kulozik, A. E. Nonsense-mediated decay approaches the clinic. Nat. Genet. 36, 801–808 (2004).

    Article  CAS  PubMed  Google Scholar 

  45. Cheung, L. W. T. et al. High frequency of PIK3R1 and PIK3R2 mutations in endometrial cancer elucidates a novel mechanism for regulation of PTEN protein stability. Cancer Discov. 1, 170–185 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Cheung, L. W. T. et al. Naturally occurring neomorphic PIK3R1 mutations activate the MAPK pathway, dictating therapeutic response to MAPK pathway inhibitors. Cancer Cell 26, 479–494 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Yao, Z. et al. BRAF mutants evade ERK-dependent feedback by different mechanisms that determine their sensitivity to pharmacologic inhibition. Cancer Cell 28, 370–383 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Zabransky, D. J. et al. HER2 missense mutations have distinct effects on oncogenic signaling and migration. Proc. Natl Acad. Sci. USA 112, E6205–E6214 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Poulikakos, P. I., Zhang, C., Bollag, G., Shokat, K. M. & Rosen, N. RAF inhibitors transactivate RAF dimers and ERK signalling in cells with wild-type BRAF. Nature 464, 427–430 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Kopetz, S. et al. Encorafenib, binimetinib, and cetuximab in BRAF V600E-mutated colorectal cancer. N. Engl. J. Med. 381, 1632–1643 (2019).

    Article  CAS  PubMed  Google Scholar 

  51. Corcoran, R. B. et al. Combined BRAF, EGFR, and MEK inhibition in patients with BRAFV600E-mutant colorectal cancer. Cancer Discov. 8, 428–443 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Gray, S. W., Hicks-Courant, K., Cronin, A., Rollins, B. J. & Weeks, J. C. Physicians’ attitudes about multiplex tumor genomic testing. J. Clin. Oncol. 32, 1317–1323 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  53. Schram, A. M. et al. Oncologist use and perception of large panel next-generation tumor sequencing. Ann. Oncol. 28, 2298–2304 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Wu, J.-Y. et al. Lung cancer with epidermal growth factor receptor exon 20 mutations is associated with poor gefitinib treatment response. Clin. Cancer Res. 14, 4877–4882 (2008).

    Article  CAS  PubMed  Google Scholar 

  55. Chakravarty, D. et al. OncoKB: a precision oncology knowledge base. JCO Precis. Oncol. https://doi.org/10.1200/PO.17.00011 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  56. Griffith, M. et al. CIViC is a community knowledgebase for expert crowdsourcing the clinical interpretation of variants in cancer. Nat. Genet. 49, 170–174 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Patterson, S. E. et al. The clinical trial landscape in oncology and connectivity of somatic mutational profiles to targeted therapies. Hum. Genomics 10, 4 (2016).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  58. Huang, L. et al. The cancer precision medicine knowledge base for structured clinical-grade mutations and interpretations. J. Am. Med. Inform. Assoc. 24, 513–519 (2017).

    Article  PubMed  Google Scholar 

  59. Tamborero, D. et al. Cancer genome interpreter annotates the biological and clinical relevance of tumor alterations. Genome Med. 10, 25 (2018).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  60. Dumbrava, E. I. & Meric-Bernstam, F. Personalized cancer therapy-leveraging a knowledge base for clinical decision-making. Cold Spring Harb. Mol. Case Stud. 4, a001578 (2018).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  61. Iyer, G. et al. Genome sequencing identifies a basis for everolimus sensitivity. Science 338, 221 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Ross, J. S. et al. Comprehensive genomic profiling of carcinoma of unknown primary site: new routes to targeted therapies. JAMA Oncol. 1, 40–49 (2015).

    Article  PubMed  Google Scholar 

  63. Richards, S. et al. 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 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  64. Li, M. M. et al. 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 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Mateo, J. et al. A framework to rank genomic alterations as targets for cancer precision medicine: the ESMO scale for clinical actionability of molecular targets (ESCAT). Ann. Oncol. 29, 1895–1902 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. AACR Project GENIE Consortium. AACR Project GENIE: powering precision medicine through an international consortium. Cancer Discov. 7, 818–831 (2017).

    Article  Google Scholar 

  67. Wagner, A. H. et al. A harmonized meta-knowledgebase of clinical interpretations of somatic genomic variants in cancer. Nat. Genet. 52, 448–457 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Ritter, D. I. et al. Somatic cancer variant curation and harmonization through consensus minimum variant level data. Genome Med. 8, 117 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  69. Center for Devices & Radiological Health. FDA recognition of public human genetic variant databases. FDA https://www.fda.gov/medical-devices/precision-medicine/fda-recognition-public-human-genetic-variant-databases (2019).

  70. Stein, E. M. et al. Enasidenib in mutant IDH2 relapsed or refractory acute myeloid leukemia. Blood 130, 722–731 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. Pollyea, D. A. et al. Enasidenib, an inhibitor of mutant IDH2 proteins, induces durable remissions in older patients with newly diagnosed acute myeloid leukemia. Leukemia 33, 2575–2584 (2019).

    Article  CAS  PubMed  Google Scholar 

  72. DiNardo, C. D. et al. Durable remissions with ivosidenib in IDH1-mutated relapsed or refractory AML. N. Engl. J. Med. 378, 2386–2398 (2018).

    Article  CAS  PubMed  Google Scholar 

  73. André, F. et al. Alpelisib for PIK3CA-mutated, hormone receptor-positive advanced breast cancer. N. Engl. J. Med. 380, 1929–1940 (2019).

    Article  PubMed  Google Scholar 

  74. Loriot, Y. et al. Erdafitinib in locally advanced or metastatic urothelial carcinoma. N. Engl. J. Med. 381, 338–348 (2019).

    Article  CAS  PubMed  Google Scholar 

  75. Abou-Alfa, G. K. et al. Pemigatinib for previously treated, locally advanced or metastatic cholangiocarcinoma: a multicentre, open-label, phase 2 study. Lancet Oncol. 21, 671–684 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  76. Drilon, A. et al. PL02.08 registrational results of LIBRETTO-001: a phase 1/2 trial of LOXO-292 in patients with RET fusion-positive lung cancers. J. Thorac. Oncol. 14, S6–S7 (2019).

    Article  Google Scholar 

  77. Wirth, L. et al. LBA93 - registrational results of LOXO-292 in patients with RET-altered thyroid cancers. Ann. Oncol. 30, v933 (2019).

    Article  Google Scholar 

  78. Litton, J. K. et al. Talazoparib in patients with advanced breast cancer and a germline BRCA mutation. N. Engl. J. Med. 379, 753–763 (2018).

    Article  CAS  PubMed  Google Scholar 

  79. Golan, T. et al. Maintenance olaparib for germline BRCA-mutated metastatic pancreatic cancer. N. Engl. J. Med. 381, 317–327 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  80. Mateo, J. et al. Olaparib in patients with metastatic castration-resistant prostate cancer with DNA repair gene aberrations (TOPARP-B): a multicentre, open-label, randomised, phase 2 trial. Lancet Oncol. 21, 162–174 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  81. Planchard, D. et al. Dabrafenib plus trametinib in patients with previously untreated BRAFV600E-mutant metastatic non-small-cell lung cancer: an open-label, phase 2 trial. Lancet Oncol. 18, 1307–1316 (2017).

    Article  CAS  PubMed  Google Scholar 

  82. Diamond, E. L. et al. 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 (2018).

    Article  PubMed  Google Scholar 

  83. Subbiah, V. et al. Dabrafenib and trametinib treatment in patients with locally advanced or metastatic BRAF V600-mutant anaplastic thyroid cancer. J. Clin. Oncol. 36, 7–13 (2018).

    Article  CAS  PubMed  Google Scholar 

  84. Goodman, A. M. et al. Tumor mutational burden as an independent predictor of response to immunotherapy in diverse cancers. Mol. Cancer Ther. 16, 2598–2608 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  85. Amado, R. G. et al. Wild-type KRAS is required for panitumumab efficacy in patients with metastatic colorectal cancer. J. Clin. Oncol. 26, 1626–1634 (2008).

    Article  CAS  PubMed  Google Scholar 

  86. De Roock, W. et al. Effects of KRAS, BRAF, NRAS, and PIK3CA mutations on the efficacy of cetuximab plus chemotherapy in chemotherapy-refractory metastatic colorectal cancer: a retrospective consortium analysis. Lancet Oncol. 11, 753–762 (2010).

    Article  PubMed  CAS  Google Scholar 

  87. Chung, V. et al. Effect of selumetinib and MK-2206 vs oxaliplatin and fluorouracil in patients with metastatic pancreatic cancer after prior therapy: SWOG S1115 study randomized clinical trial. JAMA Oncol. 3, 516–522 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  88. Jänne, P. A. et al. Selumetinib plus docetaxel compared with docetaxel alone and progression-free survival in patients with KRAS-mutant advanced non-small cell lung cancer: the SELECT-1 randomized clinical trial. JAMA 317, 1844–1853 (2017).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  89. Canon, J. et al. The clinical KRAS(G12C) inhibitor AMG 510 drives anti-tumour immunity. Nature 575, 217–223 (2019).

    Article  CAS  PubMed  Google Scholar 

  90. Tonin, P. et al. BRCA1 mutations in Ashkenazi Jewish women. Am. J. Hum. Genet. 57, 189 (1995).

    CAS  PubMed  PubMed Central  Google Scholar 

  91. Abeliovich, D. et al. The founder mutations 185delAG and 5382insC in BRCA1 and 6174delT in BRCA2 appear in 60% of ovarian cancer and 30% of early-onset breast cancer patients among Ashkenazi women. Am. J. Hum. Genet. 60, 505–514 (1997).

    CAS  PubMed  PubMed Central  Google Scholar 

  92. Newman, B., Austin, M. A., Lee, M. & King, M. C. Inheritance of human breast cancer: evidence for autosomal dominant transmission in high-risk families. Proc. Natl Acad. Sci. USA 85, 3044–3048 (1988).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  93. Hall, J. M. et al. Linkage of early-onset familial breast cancer to chromosome 17q21. Science 250, 1684–1689 (1990).

    Article  CAS  PubMed  Google Scholar 

  94. King, M.-C. ‘The race’ to clone BRCA1. Science 343, 1462–1465 (2014).

    Article  CAS  PubMed  Google Scholar 

  95. Miki, Y. et al. A strong candidate for the breast and ovarian cancer susceptibility gene BRCA1. Science 266, 66–71 (1994).

    Article  CAS  PubMed  Google Scholar 

  96. Mandelker, D. et al. Mutation detection in patients with advanced cancer by universal sequencing of cancer-related genes in tumor and normal DNA vs guideline-based germline testing. JAMA 318, 825–835 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  97. Garofalo, A. et al. The impact of tumor profiling approaches and genomic data strategies for cancer precision medicine. Genome Med. 8, 79 (2016).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  98. Jones, S. et al. Personalized genomic analyses for cancer mutation discovery and interpretation. Sci. Transl. Med. 7, 283ra53 (2015).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  99. Zhang, J. et al. Germline mutations in predisposition genes in pediatric cancer. N. Engl. J. Med. 373, 2336–2346 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  100. Schrader, K. A. et al. Germline variants in targeted tumor sequencing using matched normal DNA. JAMA Oncol. 2, 104–111 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  101. Domchek, S. M. Germline genetic testing for breast cancer: Which patients? What genes? Genet. Med. 22, 698–700 (2020).

    Article  PubMed  Google Scholar 

  102. Konstantinopoulos, P. A. et al. Germline and somatic tumor testing in epithelial ovarian cancer: ASCO guideline. J. Clin. Oncol. 38, 1222–1245 (2020).

    Article  PubMed  Google Scholar 

  103. McLeod, H. L. Cancer pharmacogenomics: early promise, but concerted effort needed. Science 339, 1563–1566 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  104. Wang, L., McLeod, H. L. & Weinshilboum, R. M. Genomics and drug response. N. Engl. J. Med. 364, 1144–1153 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  105. Irvin, W. J. Jr. et al. Genotype-guided tamoxifen dosing increases active metabolite exposure in women with reduced CYP2D6 metabolism: a multicenter study. J. Clin. Oncol. 29, 3232–3239 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  106. Hertz, D. L. et al. CYP2C8* 3 predicts benefit/risk profile in breast cancer patients receiving neoadjuvant paclitaxel. Breast Cancer Res. Treat. 134, 401–410 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  107. Pullarkat, S. T. et al. Thymidylate synthase gene polymorphism determines response and toxicity of 5-FU chemotherapy. Pharmacogenomics J. 1, 65–70 (2001).

    Article  CAS  PubMed  Google Scholar 

  108. Coombs, C. C. et al. Therapy-related clonal hematopoiesis in patients with non-hematologic cancers is common and associated with adverse clinical outcomes. Cell Stem Cell 21, 374–382.e4 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  109. Ptashkin, R. N. et al. Prevalence of clonal hematopoiesis mutations in tumor-only clinical genomic profiling of solid tumors. JAMA Oncol. 4, 1589–1593 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  110. Razavi, P. et al. High-intensity sequencing reveals the sources of plasma circulating cell-free DNA variants. Nat. Med. 25, 1928–1937 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  111. Carpenter, E. L. & Mossé, Y. P. Targeting ALK in neuroblastoma — preclinical and clinical advancements. Nat. Rev. Clin. Oncol. 9, 391–399 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  112. Wirth, L. J. et al. 1922P Exploratory patient-reported outcomes among patients with RET-mutant medullary thyroid cancer in LIBRETTO-001: a phase I/II trial of selpercatinib (LOXO-292). Ann. Oncol. 31 (Suppl. 4), S1089 (2020).

    Article  Google Scholar 

  113. Wells, S. A. Jr. et al. Vandetanib in patients with locally advanced or metastatic medullary thyroid cancer: a randomized, double-blind phase III trial. J. Clin. Oncol. 30, 134–141 (2012).

    Article  CAS  PubMed  Google Scholar 

  114. Yurgelun, M. B. & Hampel, H. Recent advances in Lynch syndrome: diagnosis, treatment, and cancer prevention. Am. Soc. Clin. Oncol. Educ. Book 38, 101–109 (2018).

    Article  PubMed  Google Scholar 

  115. Rodrigues, M. et al. Outlier response to anti-PD1 in uveal melanoma reveals germline MBD4 mutations in hypermutated tumors. Nat. Commun. 9, 1866 (2018).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  116. Johansson, P. A. et al. Correction to: Prolonged stable disease in a uveal melanoma patient with germline MBD4 nonsense mutation treated with pembrolizumab and ipilimumab. Immunogenetics 71, 511 (2019).

    Article  PubMed  Google Scholar 

  117. Schneid, T. in Discrimination Law Issues for the Safety Professional (ed. Schneid, T.) 161–194 (CRC Press, 2011).

  118. National Human Genome Research Institute. Genetic Information Nondiscrimination Act (GINA) of 2008. NIH https://www.genome.gov/24519851/genetic-information-nondiscrimination-act-of-2008 (2008).

  119. Gniady, J. A. Regulating direct-to-consumer genetic testing: protecting the consumer without quashing a medical revolution. Fordham Law Rev. 76, 2429–2475 (2008).

    PubMed  Google Scholar 

  120. Ferreira-Gonzalez, A. et al. US system of oversight for genetic testing: a report from the Secretary’s Advisory Committee on Genetics, Health and Society. Per. Med. 5, 521–528 (2008).

    Article  PubMed  PubMed Central  Google Scholar 

  121. Lolkema, M. P. et al. Ethical, legal, and counseling challenges surrounding the return of genetic results in oncology. J. Clin. Oncol. 31, 1842–1848 (2013).

    Article  PubMed  Google Scholar 

  122. Li, M. M. et al. Points to consider for reporting of germline variation in patients undergoing tumor testing: a statement of the American College of Medical Genetics and Genomics (ACMG). Genet. Med. 22, 1142–1148 (2020).

    Article  CAS  PubMed  Google Scholar 

  123. Kurian, A. W. et al. Genetic testing and counseling among patients with newly diagnosed breast cancer. JAMA 317, 531–534 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  124. McNamara, D. Shortage of genetic counselors in face of growing need. Medscape https://www.medscape.com/viewarticle/877135 (2017).

  125. Eisen, A. et al. Genetic assessment wait time indicators in the high risk ontario breast screening program. Mol. Genet. Genomic Med. 6, 213–223 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  126. Culver, J. O., Hull, J. L., Dunne, D. F. & Burke, W. Oncologists’ opinions on genetic testing for breast and ovarian cancer. Genet. Med. 3, 120–125 (2001).

    Article  CAS  PubMed  Google Scholar 

  127. Teng, I. & Spigelman, A. Attitudes and knowledge of medical practitioners to hereditary cancer clinics and cancer genetic testing. Fam. Cancer 13, 311–324 (2014).

    Article  PubMed  Google Scholar 

  128. Teer, J. K. et al. Evaluating somatic tumor mutation detection without matched normal samples. Hum. Genomics 11, 22 (2017).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  129. Damodaran, S., Berger, M. F. & Roychowdhury, S. Clinical tumor sequencing: opportunities and challenges for precision cancer medicine. Am. Soc. Clin. Oncol. Educ. Book 35, e175–e182 (2015).

    Article  Google Scholar 

  130. Robinson, D. R. et al. Integrative clinical genomics of metastatic cancer. Nature 548, 297–303 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  131. Van Allen, E. M. et al. Whole-exome sequencing and clinical interpretation of formalin-fixed, paraffin-embedded tumor samples to guide precision cancer medicine. Nat. Med. 20, 682–688 (2014).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  132. Van Allen, E. M. et al. A comparative assessment of clinical whole exome and transcriptome profiling across sequencing centers: implications for precision cancer medicine. Oncotarget 7, 52888–52899 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  133. Robbe, P. et al. Clinical whole-genome sequencing from routine formalin-fixed, paraffin-embedded specimens: pilot study for the 100,000 Genomes Project. Genet. Med. 20, 1196–1205 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  134. Staaf, J. et al. Whole-genome sequencing of triple-negative breast cancers in a population-based clinical study. Nat. Med. 25, 1526–1533 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  135. ICGC/TCGA Pan-Cancer Analysis of Whole Genomes Consortium. Pan-cancer analysis of whole genomes. Nature 578, 82–93 (2020).

    Article  CAS  Google Scholar 

  136. Conesa, A. et al. A survey of best practices for RNA-seq data analysis. Genome Biol. 17, 13 (2016).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  137. Zheng, Z. et al. Anchored multiplex PCR for targeted next-generation sequencing. Nat. Med. 20, 1479–1484 (2014).

    Article  CAS  PubMed  Google Scholar 

  138. Cieslik, M. et al. The use of exome capture RNA-seq for highly degraded RNA with application to clinical cancer sequencing. Genome Res. 25, 1372–1381 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  139. Capper, D. et al. DNA methylation-based classification of central nervous system tumours. Nature 555, 469–474 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  140. Miller, A. M. et al. Tracking tumour evolution in glioma through liquid biopsies of cerebrospinal fluid. Nature 565, 654–658 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  141. Goto, K. et al. Epidermal growth factor receptor mutation status in circulating free DNA in serum: from IPASS, a phase III study of gefitinib or carboplatin/paclitaxel in non-small cell lung cancer. J. Thorac. Oncol. 7, 115–121 (2012).

    Article  CAS  PubMed  Google Scholar 

  142. Husain, H. et al. Cell-free DNA from ascites and pleural effusions: molecular insights into genomic aberrations and disease biology. Mol. Cancer Ther. 16, 948–955 (2017).

    Article  CAS  PubMed  Google Scholar 

  143. Chang, H. W. et al. Urinary cell-free DNA as a potential tumor marker for bladder cancer. Int. J. Biol. Markers 22, 287–294 (2007).

    Article  CAS  PubMed  Google Scholar 

  144. Diehl, F. et al. Circulating mutant DNA to assess tumor dynamics. Nat. Med. 14, 985–990 (2008).

    Article  CAS  PubMed  Google Scholar 

  145. Bettegowda, C. et al. Detection of circulating tumor DNA in early- and late-stage human malignancies. Sci. Transl. Med. 6, 224ra24 (2014).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  146. Lecomte, T. et al. Detection of free-circulating tumor-associated DNA in plasma of colorectal cancer patients and its association with prognosis. Int. J. Cancer 100, 542–548 (2002).

    Article  CAS  PubMed  Google Scholar 

  147. Murtaza, M. et al. Non-invasive analysis of acquired resistance to cancer therapy by sequencing of plasma DNA. Nature 497, 108–112 (2013).

    Article  CAS  PubMed  Google Scholar 

  148. Dawson, S.-J. et al. Analysis of circulating tumor DNA to monitor metastatic breast cancer. N. Engl. J. Med. 368, 1199–1209 (2013).

    Article  CAS  PubMed  Google Scholar 

  149. Garcia-Murillas, I. et al. Mutation tracking in circulating tumor DNA predicts relapse in early breast cancer. Sci. Transl. Med. 7, 302ra133 (2015).

    Article  PubMed  Google Scholar 

  150. Kinde, I., Wu, J., Papadopoulos, N., Kinzler, K. W. & Vogelstein, B. Detection and quantification of rare mutations with massively parallel sequencing. Proc. Natl Acad. Sci. USA 108, 9530–9535 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  151. Oxnard, G. R. et al. Association between plasma genotyping and outcomes of treatment with osimertinib (AZD9291) in advanced non-small-cell lung cancer. J. Clin. Oncol. 34, 3375–3382 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  152. Shaw, J. A. et al. Mutation analysis of cell-free DNA and single circulating tumor cells in metastatic breast cancer patients with high circulating tumor cell counts. Clin. Cancer Res. 23, 88–96 (2017).

    Article  CAS  PubMed  Google Scholar 

  153. Goodall, J. et al. Circulating cell-free DNA to guide prostate cancer treatment with PARP inhibition. Cancer Discov. 7, 1006–1017 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  154. Reinert, T. et al. Analysis of plasma cell-free DNA by ultradeep sequencing in patients with stages I to III colorectal cancer. JAMA Oncol. 5, 1124–1131 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  155. Christensen, E. et al. Early detection of metastatic relapse and monitoring of therapeutic efficacy by ultra-deep sequencing of plasma cell-free DNA in patients with urothelial bladder carcinoma. J. Clin. Oncol. 37, 1547–1557 (2019).

    Article  CAS  PubMed  Google Scholar 

  156. Coombes, R. C. et al. Personalized detection of circulating tumor DNA antedates breast cancer metastatic recurrence. Clin. Cancer Res. 25, 4255–4263 (2019).

    Article  CAS  PubMed  Google Scholar 

  157. Hao, X. et al. DNA methylation markers for diagnosis and prognosis of common cancers. Proc. Natl Acad. Sci. USA 114, 7414–7419 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  158. Nowell, P. C. The clonal evolution of tumor cell populations. Science 194, 23–28 (1976).

    Article  CAS  PubMed  Google Scholar 

  159. McGranahan, N. et al. Clonal neoantigens elicit T cell immunoreactivity and sensitivity to immune checkpoint blockade. Science 351, 1463–1469 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  160. Landau, D. A. et al. Evolution and impact of subclonal mutations in chronic lymphocytic leukemia. Cell 152, 714–726 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  161. Carter, S. L. et al. Absolute quantification of somatic DNA alterations in human cancer. Nat. Biotechnol. 30, 413–421 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  162. Shen, R. & Seshan, V. E. FACETS: allele-specific copy number and clonal heterogeneity analysis tool for high-throughput DNA sequencing. Nucleic Acids Res. 44, e131 (2016).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  163. Tarabichi, M. et al. A practical guide to cancer subclonal reconstruction from DNA sequencing. Nat. Methods 18, 144–155 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  164. Gerlinger, M. et al. Intratumor heterogeneity and branched evolution revealed by multiregion sequencing. N. Engl. J. Med. 366, 883–892 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  165. Voss, M. H. et al. Tumor genetic analyses of patients with metastatic renal cell carcinoma and extended benefit from mTOR inhibitor therapy. Clin. Cancer Res. 20, 1955–1964 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  166. Hyman, D. M. et al. HER kinase inhibition in patients with HER2- and HER3-mutant cancers. Nature 554, 189–194 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  167. Bielski, C. M. et al. Widespread selection for oncogenic mutant allele imbalance in cancer. Cancer Cell 34, 852–862.e4 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  168. Jones, P. A. & Baylin, S. B. The fundamental role of epigenetic events in cancer. Nat. Rev. Genet. 3, 415–428 (2002).

    Article  CAS  PubMed  Google Scholar 

  169. Vasan, N. et al. Double PIK3CA mutations in cis increase oncogenicity and sensitivity to PI3Kα inhibitors. Science 366, 714–723 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  170. Paraiso, K. H. T. et al. PTEN loss confers BRAF inhibitor resistance to melanoma cells through the suppression of BIM expression. Cancer Res. 71, 2750–2760 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  171. Xing, F. et al. Concurrent loss of the PTEN and RB1 tumor suppressors attenuates RAF dependence in melanomas harboring (V600E)BRAF. Oncogene 31, 446–457 (2012).

    Article  CAS  PubMed  Google Scholar 

  172. Whittaker, S. R. et al. A genome-scale RNA interference screen implicates NF1 loss in resistance to RAF inhibition. Cancer Discov. 3, 350–362 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  173. Nissan, M. H. et al. Loss of NF1 in cutaneous melanoma is associated with RAS activation and MEK dependence. Cancer Res. 74, 2340–2350 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  174. Alexandrov, L. B. & Stratton, M. R. Mutational signatures: the patterns of somatic mutations hidden in cancer genomes. Curr. Opin. Genet. Dev. 24, 52–60 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  175. Alexandrov, L. B. et al. Signatures of mutational processes in human cancer. Nature 500, 415–421 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  176. Alexandrov, L. B. et al. The repertoire of mutational signatures in human cancer. Nature 578, 94–101 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  177. Niu, B. et al. MSIsensor: microsatellite instability detection using paired tumor-normal sequence data. Bioinformatics 30, 1015–1016 (2014).

    Article  CAS  PubMed  Google Scholar 

  178. Escudié, F. et al. MIAmS: microsatellite instability detection on NGS amplicons data. Bioinformatics https://doi.org/10.1093/bioinformatics/btz797 (2019).

    Article  PubMed  Google Scholar 

  179. Huang, M. N. et al. MSIseq: software for assessing microsatellite instability from catalogs of somatic mutations. Sci. Rep. 5, 13321 (2015).

    Article  CAS  PubMed  Google Scholar 

  180. Abida, W. et al. Analysis of the prevalence of microsatellite instability in prostate cancer and response to immune checkpoint blockade. JAMA Oncol. 5, 471–478 (2019).

    Article  PubMed  Google Scholar 

  181. Wu, Y.-M. et al. Inactivation of CDK12 delineates a distinct immunogenic class of advanced prostate cancer. Cell 173, 1770–1782.e14 (2018).

    Article  CAS  PubMed  Google Scholar 

  182. Wang, Y. K. et al. Genomic consequences of aberrant DNA repair mechanisms stratify ovarian cancer histotypes. Nat. Genet. 49, 856–865 (2017).

    Article  CAS  PubMed  Google Scholar 

  183. Taylor-Weiner, A. et al. Genomic evolution and chemoresistance in germ-cell tumours. Nature 540, 114–118 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  184. Angus, L. et al. The genomic landscape of metastatic breast cancer highlights changes in mutation and signature frequencies. Nat. Genet. 51, 1450–1458 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  185. Salgado, R. et al. Addressing the dichotomy between individual and societal approaches to personalised medicine in oncology. Eur. J. Cancer 114, 128–136 (2019).

    Article  PubMed  Google Scholar 

  186. Salgado, R. et al. How current assay approval policies are leading to unintended imprecision medicine. Lancet Oncol. 21, 1399–1401 (2020).

    Article  PubMed  Google Scholar 

  187. Rosell, R. et al. Erlotinib versus standard chemotherapy as first-line treatment for European patients with advanced EGFR mutation-positive non-small-cell lung cancer (EURTAC): a multicentre, open-label, randomised phase 3 trial. Lancet Oncol. 13, 239–246 (2012).

    Article  CAS  PubMed  Google Scholar 

  188. Mok, T. S. et al. Gefitinib or carboplatin-paclitaxel in pulmonary adenocarcinoma. N. Engl. J. Med. 361, 947–957 (2009).

    Article  CAS  PubMed  Google Scholar 

  189. Fukuoka, M. et al. Multi-institutional randomized phase II trial of gefitinib for previously treated patients with advanced non-small-cell lung cancer (The IDEAL 1 Trial) [corrected]. J. Clin. Oncol. 21, 2237–2246 (2003).

    Article  CAS  PubMed  Google Scholar 

  190. Kris, M. G. et al. Efficacy of gefitinib, an inhibitor of the epidermal growth factor receptor tyrosine kinase, in symptomatic patients with non-small cell lung cancer: a randomized trial. JAMA 290, 2149–2158 (2003).

    Article  CAS  PubMed  Google Scholar 

  191. Paez, J. G. et al. EGFR mutations in lung cancer: correlation with clinical response to gefitinib therapy. Science 304, 1497–1500 (2004).

    Article  CAS  PubMed  Google Scholar 

  192. Lynch, T. J. et al. 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 (2004).

    Article  CAS  PubMed  Google Scholar 

  193. Pao, W. et al. EGF receptor gene mutations are common in lung cancers from ‘never smokers’ and are associated with sensitivity of tumors to gefitinib and erlotinib. Proc. Natl Acad. Sci. USA 101, 13306–13311 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  194. Hann, C. L. & Brahmer, J. R. ‘Who should receive epidermal growth factor receptor inhibitors for non-small cell lung cancer and when?’. Curr. Treat. Options Oncol. 8, 28–37 (2007).

    Article  PubMed  Google Scholar 

  195. Soda, M. et al. Identification of the transforming EML4-ALK fusion gene in non-small-cell lung cancer. Nature 448, 561–566 (2007).

    Article  CAS  PubMed  Google Scholar 

  196. Davies, K. D. et al. Identifying and targeting ROS1 gene fusions in non-small cell lung cancer. Clin. Cancer Res. 18, 4570–4579 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  197. Takeuchi, K. et al. RET, ROS1 and ALK fusions in lung cancer. Nat. Med. 18, 378–381 (2012).

    Article  CAS  PubMed  Google Scholar 

  198. Gautschi, O. et al. Targeted therapy for patients with BRAF-mutant lung cancer: results from the European EURAF cohort. J. Thorac. Oncol. 10, 1451–1457 (2015).

    Article  CAS  PubMed  Google Scholar 

  199. Stephens, P. et al. Lung cancer: intragenic ERBB2 kinase mutations in tumours. Nature 431, 525–526 (2004).

    Article  CAS  PubMed  Google Scholar 

  200. Shimamura, T. et al. Non-small-cell lung cancer and Ba/F3 transformed cells harboring the ERBB2 G776insV_G/C mutation are sensitive to the dual-specific epidermal growth factor receptor and ERBB2 inhibitor HKI-272. Cancer Res. 66, 6487–6491 (2006).

    Article  CAS  PubMed  Google Scholar 

  201. The Cancer Genome Atlas Research Network. Comprehensive molecular profiling of lung adenocarcinoma. Nature 511, 543–550 (2014).

    Article  PubMed Central  CAS  Google Scholar 

  202. Paik, P. K. et al. Response to MET inhibitors in patients with stage IV lung adenocarcinomas harboring MET mutations causing exon 14 skipping. Cancer Discov. 8, 842–849 (2015).

    Article  CAS  Google Scholar 

  203. Govindan, R. et al. Genomic landscape of non-small cell lung cancer in smokers and never-smokers. Cell 150, 1121–1134 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  204. Douillard, J.-Y. et al. Randomized, phase III trial of panitumumab with infusional fluorouracil, leucovorin, and oxaliplatin (FOLFOX4) versus FOLFOX4 alone as first-line treatment in patients with previously untreated metastatic colorectal cancer: the PRIME study. J. Clin. Oncol. 28, 4697–4705 (2010).

    Article  CAS  PubMed  Google Scholar 

  205. Bokemeyer, C. et al. Efficacy according to biomarker status of cetuximab plus FOLFOX-4 as first-line treatment for metastatic colorectal cancer: the OPUS study. Ann. Oncol. 22, 1535–1546 (2011).

    Article  CAS  PubMed  Google Scholar 

  206. Joseph, E. W. et al. The RAF inhibitor PLX4032 inhibits ERK signaling and tumor cell proliferation in a V600E BRAF-selective manner. Proc. Natl Acad. Sci. USA 107, 14903–14908 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  207. Su, F. et al. RAS mutations in cutaneous squamous-cell carcinomas in patients treated with BRAF inhibitors. N. Engl. J. Med. 366, 207–215 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  208. Callahan, M. K. et al. Progression of RAS-mutant leukemia during RAF inhibitor treatment. N. Engl. J. Med. 367, 2316–2321 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  209. Sanchez-Laorden, B. et al. BRAF inhibitors induce metastasis in RAS mutant or inhibitor-resistant melanoma cells by reactivating MEK and ERK signaling. Sci. Signal. 7, ra30 (2014).

    Article  PubMed  CAS  Google Scholar 

  210. Samstein, R. M. et al. Tumor mutational load predicts survival after immunotherapy across multiple cancer types. Nat. Genet. 51, 202–206 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  211. Marabelle, A. et al. Association of tumour mutational burden with outcomes in patients with advanced solid tumours treated with pembrolizumab: prospective biomarker analysis of the multicohort, open-label, phase 2 KEYNOTE-158 study. Lancet Oncol. 21, 1353–1365 (2020).

    Article  CAS  PubMed  Google Scholar 

  212. Hellmann, M. D. et al. Tumor mutational burden and efficacy of nivolumab monotherapy and in combination with ipilimumab in small-cell lung cancer. Cancer Cell 33, 853–861.e4 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  213. Marabelle, A. et al. 1192O - Association of tumour mutational burden with outcomes in patients with select advanced solid tumours treated with pembrolizumab in KEYNOTE-158. Ann. Oncol. 30, v477–v478 (2019).

    Article  Google Scholar 

  214. Graff, J. N. et al. A phase II single-arm study of pembrolizumab with enzalutamide in men with metastatic castration-resistant prostate cancer progressing on enzalutamide alone. J Immunother. Cancer 8, e000642 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  215. O’Reilly, E. M. et al. Durvalumab with or without tremelimumab for patients with metastatic pancreatic ductal adenocarcinoma: a phase 2 randomized clinical trial. JAMA Oncol. 5, 1431–1438 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  216. Spranger, S., Bao, R. & Gajewski, T. F. Melanoma-intrinsic β-catenin signalling prevents anti-tumour immunity. Nature 523, 231–235 (2015).

    Article  CAS  PubMed  Google Scholar 

  217. Xiao, Q. et al. DKK2 imparts tumor immunity evasion through β-catenin-independent suppression of cytotoxic immune-cell activation. Nat. Med. 24, 262–270 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  218. Harding, J. J. et al. Prospective genotyping of hepatocellular carcinoma: clinical implications of next-generation sequencing for matching patients to targeted and immune therapies. Clin. Cancer Res. 25, 2116–2126 (2019).

    Article  CAS  PubMed  Google Scholar 

  219. Peters, S. et al. Phase II trial of atezolizumab as first-line or subsequent therapy for patients with programmed death-ligand 1-selected advanced non–small-cell lung cancer (BIRCH). J. Clin. Oncol. 35, 2781–2789 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  220. Haratani, K. et al. Tumor immune microenvironment and nivolumab efficacy in EGFR mutation-positive non-small-cell lung cancer based on T790M status after disease progression during EGFR-TKI treatment. Ann. Oncol. 28, 1532–1539 (2017).

    Article  CAS  PubMed  Google Scholar 

  221. Chowell, D. et al. Patient HLA class I genotype influences cancer response to checkpoint blockade immunotherapy. Science 359, 582–587 (2018).

    Article  CAS  PubMed  Google Scholar 

  222. Gopalakrishnan, V. et al. Gut microbiome modulates response to anti-PD-1 immunotherapy in melanoma patients. Science 359, 97–103 (2018).

    Article  CAS  PubMed  Google Scholar 

  223. D’Angelo, S. P. et al. Avelumab in patients with previously treated metastatic Merkel cell carcinoma: long-term data and biomarker analyses from the single-arm phase 2 JAVELIN Merkel 200 trial. J. Immunother. Cancer 8, e000674 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  224. Janjigian, Y. Y. et al. Genetic predictors of response to systemic therapy in esophagogastric cancer. Cancer Discov. 8, 49–58 (2018).

    Article  CAS  PubMed  Google Scholar 

  225. Kim, S. T. et al. Comprehensive molecular characterization of clinical responses to PD-1 inhibition in metastatic gastric cancer. Nat. Med. 24, 1449–1458 (2018).

    Article  CAS  PubMed  Google Scholar 

  226. Ott, P. A. et al. An immunogenic personal neoantigen vaccine for patients with melanoma. Nature 547, 217–221 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  227. Keskin, D. B. et al. Neoantigen vaccine generates intratumoral T cell responses in phase Ib glioblastoma trial. Nature 565, 234–239 (2019).

    Article  CAS  PubMed  Google Scholar 

  228. Wang, R. F. & Rosenberg, S. A. Human tumor antigens for cancer vaccine development. Immunol. Rev. 170, 85–100 (1999).

    Article  CAS  PubMed  Google Scholar 

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Acknowledgements

The authors thank M. F. Berger, H. Al-Ahmadie, C. Ho, S. Sethi, A. Zehir and S. Nandakumar for their invaluable contributions to the figures. They are also grateful to the Molecular Diagnostics Service and the OncoKB team, particularly M. Ladanyi, H. Zhang and R. Kundra, for their assistance and insightful suggestions.

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Authors and Affiliations

  1. Kravis Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, USA

    Debyani Chakravarty & David B. Solit

  2. Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY, USA

    Debyani Chakravarty

  3. Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA

    David B. Solit

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The authors contributed equally to all aspects of the article.

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Correspondence to David B. Solit.

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Competing interests

D.B.S. serves on the Scientific Advisory Board for Loxo Oncology at Eli Lilly, Pfizer, Scorpion Therapeutics, BridgeBio and Vividion Therapeutics, owned stock at Loxo Oncology at Eli Lilly and Scorpion Therapeutics, and received honoraria from Illumina and Eli Lilly. D.C. declares no competing interests.

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Glossary

Precision oncology

The process of using molecular data from the analysis of a patient’s tumour or healthy cells to inform treatment selection.

Companion diagnostics

Within the context of precision oncology, companion diagnostics are medical devices designed to identify the subset of patients most likely to respond to and benefit from a targeted or other systemic or local therapy.

Next-generation sequencing

(NGS). Massively parallel high-throughput sequencing methods designed to analyse DNA or RNA more rapidly and at higher resolution than older methods such as Sanger sequencing.

Cell-free DNA

(cfDNA). In the context of this article, circulating tumour DNA, that is, DNA fragments shed by the tumour into the blood.

Basket trials

A clinical trial design that prospectively accrues patients with a specific molecular alteration irrespective of tumour type.

Mutational signatures

Patterns of base pair substitutions or structural abnormalities that are often characteristic of exogenous or endogenous mutational processes (such as tobacco smoking or DNA repair pathway mutations).

Somatic mutations

Non-heritable mutations that may arise in any cell except germ cells (sperm or ova). Although somatic mutations have classically been defined as those found specifically in tumour but not in healthy cells, accumulation of somatic mutations is common in non-transformed, histologically normal-appearing cells as patients age.

Drivers

Mutations that enhance tumour cell fitness by providing a growth or survival advantage.

Passengers

Biologically inert mutations with no impact on tumour cell fitness.

Clinically actionable mutations

A subset of driver mutations that are predictive biomarkers of drug response or resistance.

Synthetic lethal mechanism

An interaction between two genes whereby loss of function of both (due to mutation, epigenetic silencing or drug inhibition) results in tumour cell death, whereas loss of function or inhibition of either individual gene does not.

Mutational hotspots

Mutations identified in a population of patients with cancer more frequently than expected by chance.

Germline variants

Heritable mutations that were present in germ cells and consequently found in all cells of the descendants.

Resistance mutations

Mutations that increase tumour cell fitness under the selective pressure of a systemic therapy.

Penetrance

A measure of the proportion of individuals with a mutant allele in a defined population who manifest the associated phenotype. For germline variants associated with increased cancer predisposition, the penetrance is the proportion of patients who develop the associated cancer type.

Whole-exome sequencing

(WES). Sequencing of all protein-coding regions (or exons) in the genome.

Whole-genome sequencing

(WGS). Sequencing of the entire genome including non-coding sequences.

Clonal haematopoiesis

The acquisition of somatic genomic alterations in haematopoietic stem and/or progenitor cells, resulting in clonal expansion.

Capture-based DNA sequencing

A method for selectively sequencing targeted regions of the genome using baits that hybridize with specific regions of DNA.

Clonal mutations

Mutations present in all of a patient’s cancer cells.

Subclonal mutations

Mutations present in only a fraction of a patient’s cancer cells.

Cancer cell fraction

The estimated fraction of cancer cells that harbour a specific mutation.

Variant allele frequency

The fraction of mutant versus total sequencing reads at the mutation locus.

Allelic configuration

The number of mutant and wild-type alleles, which because of copy number gain or loss can be less than or greater than two.

Knudsen’s two-hit hypothesis

The hypothesis, proposed by Alfred Knudsen in 1971, that for tumour suppressor genes that are recessive in nature, in order for a phenotype to manifest, both alleles must be inactivated (biallelic inactivation). This may be achieved through multiple mechanisms including deletions (either chromosomal or subchromosomal), epigenetic silencing or mutation.

Loss of heterozygosity

A common form of allelic imbalance in which a heterozygous somatic alteration becomes homozygous following loss of the wild-type allele.

Clonal fitness

The relative growth, survival or metastatic potential advantage of a cancer cell clone over other cancer cells within the tumour or non-cancer cells. The term fitness here derives its origins from the concept of natural selection in evolutionary biology.

Integer copy number

The copy number of a gene or localized DNA segment represented as an integer value. For missense mutations, the number of mutated and wild-type alleles in the cell.

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Chakravarty, D., Solit, D.B. Clinical cancer genomic profiling. Nat Rev Genet 22, 483–501 (2021). https://doi.org/10.1038/s41576-021-00338-8

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