Standardized decision support in next generation sequencing reports of somatic cancer variants

Molecular Oncology

Volumn 8, Issue 5, 2014, Pages 859-873

  Dienstmann, Rodrigo ^a   Dong, Fei ^a   Borger, Darrell ^b   Dias Santagata, Dora ^a   Ellisen, Leif W ^b   Le, Long P ^a   Iafrate, A John ^a  

^a MASSACHUSETTS GENERAL HOSPITAL   (United States)

^b MASSACHUSETTS GENERAL HOSPITAL CANCER CENTER   (United States)

Author keywords

Cancer; Genomics; Next generation sequencing; Report; Variant annotation

Indexed keywords

BIOINFORMATICS; CLINICAL DECISION MAKING; CLINICAL PRACTICE; CLINICAL TRIAL (TOPIC); DECISION SUPPORT SYSTEM; GENE EXPRESSION; GENETIC VARIABILITY; HIGH THROUGHPUT SEQUENCING; HUMAN; KNOWLEDGE BASE; MISSENSE MUTATION; MOLECULAR PATHOLOGY; MOLECULAR THERAPY; OFF LABEL DRUG USE; ONCOGENE; PATIENT CARE; PHARMACOGENOMICS; PREDICTION; PRIORITY JOURNAL; REVIEW; SOMATIC CANCER VARIANT; SOMATIC MUTATION; TUMOR GENE; TUMOR SUPPRESSOR GENE; GENETIC DATABASE; GENETIC SCREENING; GENETICS; GENOMICS; HUMAN GENOME; NEOPLASMS; PROCEDURES; PROGNOSIS; STANDARDS; BREAST CANCER; CANCER DIAGNOSIS; CANCER PROGNOSIS; CHRONIC MYELOID LEUKEMIA; CLASSIFICATION ALGORITHM; COLORECTAL CANCER; ENDOMETRIUM CANCER; GASTROINTESTINAL STROMAL TUMOR; GENE INACTIVATION; GENETIC POLYMORPHISM; GENOME ANALYSIS; HEAD AND NECK CANCER; INTERNET; LOSS OF FUNCTION MUTATION; LUNG ADENOCARCINOMA; LUNG CANCER; MEDICAL TERMINOLOGY; MELANOMA; MOLECULARLY TARGETED THERAPY; NEXT GENERATION SEQUENCING; NON SMALL CELL LUNG CANCER; PANCREAS CANCER; PROSTATE CANCER;

DATABASES, GENETIC; GENETIC TESTING; GENETIC VARIATION; GENOME, HUMAN; GENOMICS; HIGH-THROUGHPUT NUCLEOTIDE SEQUENCING; HUMANS; NEOPLASMS; PROGNOSIS;

AFATINIB; ANTINEOPLASTIC AGENT; CETUXIMAB; CRIZOTINIB; DABRAFENIB; DASATINIB; ERLOTINIB; FIBROBLAST GROWTH FACTOR RECEPTOR 2; HEAT SHOCK PROTEIN 90 INHIBITOR; IMATINIB; INFIGRATINIB; JANUS KINASE; LAPATINIB; MITOGEN ACTIVATED PROTEIN KINASE; MITOGEN ACTIVATED PROTEIN KINASE INHIBITOR; MITOGEN ACTIVATED PROTEIN KINASE KINASE INHIBITOR; NERATINIB; PHOSPHATIDYLINOSITOL 3 KINASE; PLATELET DERIVED GROWTH FACTOR RECEPTOR; PONATINIB; PROTEIN KINASE B INHIBITOR; PROTEIN TYROSINE KINASE; PROTEIN TYROSINE KINASE INHIBITOR; RAS PROTEIN; STAT PROTEIN; STRESS ACTIVATED PROTEIN KINASE; SUNITINIB; TRASTUZUMAB; UNINDEXED DRUG; VEMURAFENIB;

EID: 84903553673     PISSN: 15747891     EISSN: 18780261     Source Type: Journal    
DOI: 10.1016/j.molonc.2014.03.021     Document Type: Review

References (53)

1. Abecasis G.R., Auton A., Brooks L.D., et al. An integrated map of genetic variation from 1,092 human genomes. Nature 2012, 491:56-65.
2. Adzhubei I.A., Schmidt S., Peshkin L., et al. A method and server for predicting damaging missense mutations. Nat. Methods 2010, 7:248-249.
3. Ascierto P.A., Schadendorf D., Berking C., et al. MEK162 for patients with advanced melanoma harbouring NRAS or Val600 BRAF mutations: a non-randomised, open-label phase 2 study. Lancet Oncol. 2013, 14:249-256.
4. Bose R., Kavuri S.M., Searleman A.C., et al. Activating HER2 mutations in HER2 gene amplification negative breast cancer. Cancer Discov. 2013, 3:224-237.
5. Carpten J.D., Faber A.L., Horn C., et al. A transforming mutation in the pleckstrin homology domain of AKT1 in cancer. Nature 2007, 448:439-444.
6. Carver B.S., Chapinski C., Wongvipat J., et al. Reciprocal feedback regulation of PI3K and androgen receptor signaling in PTEN-deficient prostate cancer. Cancer Cell 2011, 19:575-586.
7. Chen Z., Cheng K., Walton Z., et al. A murine lung cancer co-clinical trial identifies genetic modifiers of therapeutic response. Nature 2012, 483:613-617.
8. Cooper G.M., Shendure J. Needles in stacks of needles: finding disease-causal variants in a wealth of genomic data. Nat. Rev. Genet. 2011, 12:628-640.
9. Cortes J.E., Kantarjian H., Shah N.P., et al. Ponatinib in refractory Philadelphia chromosome-positive leukemias. New Engl. J. Med. 2012, 367:2075-2088.
10. Dahlman K.B., Xia J., Hutchinson K., et al. BRAF(L597) mutations in melanoma are associated with sensitivity to MEK inhibitors. Cancer Discov. 2012, 2:791-797.
11. Dias-Santagata D., Akhavanfard S., David S.S., et al. Rapid targeted mutational analysis of human tumours: a clinical platform to guide personalized cancer medicine. EMBO Mol. Med. 2010, 2:146-158.
12. Dienstmann R., Rodon J., Tabernero J. Biomarker-driven patient selection for early clinical trials. Curr. Opin. Oncol. 2013, 25:305-312.
13. Engelman J.A., Zejnullahu K., Mitsudomi T., et al. MET amplification leads to gefitinib resistance in lung cancer by activating ERBB3 signaling. Science 2007, 316:1039-1043.
14. Flanagan S.E., Patch A.M., Ellard S. Using SIFT and PolyPhen to predict loss-of-function and gain-of-function mutations. Genet. Test Mol Biomarkers 2010, 14:533-537.
15. Fong P.C., Boss D.S., Yap T.A., et al. Inhibition of poly(ADP-ribose) polymerase in tumors from BRCA mutation carriers. New Engl. J. Med. 2009, 361:123-134.
16. Frousios K., Iliopoulos C.S., Schlitt T., et al. Predicting the functional consequences of non-synonymous DNA sequence variants - evaluation of bioinformatics tools and development of a consensus strategy. Genomics 2013, 102:223-228.
17. Fu W., O'Connor T.D., Jun G., et al. Analysis of 6,515 exomes reveals the recent origin of most human protein-coding variants. Nature 2013, 493:216-220.
18. Garraway L.A., Lander E.S. Lessons from the cancer genome. Cell 2013, 153:17-37.
19. Gartside M.G., Chen H., Ibrahimi O.A., et al. Loss-of-function fibroblast growth factor receptor-2 mutations in melanoma. Mol. Cancer Res. 2009, 7:41-54.
20. Gnad F., Baucom A., Mukhyala K., et al. Assessment of computational methods for predicting the effects of missense mutations in human cancers. BMC Genomics 2013, 14(Suppl. 3):S7.
21. Gonzalez-Perez A., Lopez-Bigas N. Improving the assessment of the outcome of nonsynonymous SNVs with a consensus deleteriousness score, Condel. Am. J. Hum. Genet. 2011, 88:440-449.
22. Gozgit J.M., Wong M.J., Moran L., et al. Ponatinib (AP24534), a multitargeted pan-FGFR inhibitor with activity in multiple FGFR-amplified or mutated cancer models. Mol. Cancer Ther. 2012, 11:690-699.
23. Green R.C., Berg J.S., Grody W.W., et al. ACMG recommendations for reporting of incidental findings in clinical exome and genome sequencing. Genet. Med. 2013, 15:565-574.
24. Griffith M., Griffith O.L., Coffman A.C., et al. DGIdb: mining the druggable genome. Nat. Methods 2013, 10:1209-1210.
25. Guagnano V., Kauffmann A., Wohrle S., et al. FGFR genetic alterations predict for sensitivity to NVP-BGJ398, a selective pan-FGFR inhibitor. Cancer Discov. 2012, 2:1118-1133.
26. Heinrich M.C., Corless C.L., Demetri G.D., et al. Kinase mutations and imatinib response in patients with metastatic gastrointestinal stromal tumor. J. Clin. Oncol. 2003, 21:4342-4349.
27. Hofmann I., Weiss A., Elain G., et al. K-RAS mutant pancreatic tumors show higher sensitivity to MEK than to PI3K inhibition in vivo. PloS One 2012, 7:e44146.
28. Iyer G., Hanrahan A.J., Milowsky M.I., et al. Genome sequencing identifies a basis for everolimus sensitivity. Science 2012, 338:221.
29. Jo H., Lo P.K., Li Y., et al. Deactivation of Akt by a small molecule inhibitor targeting pleckstrin homology domain and facilitating Akt ubiquitination. Proc. Natl. Acad. Sci. U. S. A. 2011, 108:6486-6491.
30. Kumar P., Henikoff S., Ng P.C. Predicting the effects of coding non-synonymous variants on protein function using the SIFT algorithm. Nat. Protoc. 2009, 4:1073-1081.
31. Lawrence M.S., Stojanov P., Mermel C.H., et al. Discovery and saturation analysis of cancer genes across 21 tumour types. Nature 2014, 505:495-501.
32. Lawrence M.S., Stojanov P., Polak P., et al. Mutational heterogeneity in cancer and the search for new cancer-associated genes. Nature 2013, 499:214-218.
33. Lubin I.M., Caggana M., Constantin C., et al. Ordering molecular genetic tests and reporting results: practices in laboratory and clinical settings. J. Mol. Diagn. 2008, 10:459-468.
34. Mitsudomi T., Hamajima N., Ogawa M., et al. Prognostic significance of p53 alterations in patients with non-small cell lung cancer: a meta-analysis. Clin. Cancer Res. 2000, 6:4055-4063.
35. Mogi A., Kuwano H. TP53 mutations in nonsmall cell lung cancer. J. Biomed. Biotechnol. 2011, 2011:583929.
36. Prahallad A., Sun C., Huang S., et al. Unresponsiveness of colon cancer to BRAF(V600E) inhibition through feedback activation of EGFR. Nature 2012, 483:100-103.
37. Reva B., Antipin Y., Sander C. Predicting the functional impact of protein mutations: application to cancer genomics. Nucl. Acids Res. 2011, 39:e118.
38. Scoccianti C., Vesin A., Martel G., et al. Prognostic value of TP53, KRAS and EGFR mutations in nonsmall cell lung cancer: the EUELC cohort. Eur. Resp J. 2012, 40:177-184.
39. Sen B., Peng S., Tang X., et al. Kinase-impaired BRAF mutations in lung cancer confer sensitivity to dasatinib. Sci. Transl Med. 2012, 4:136ra170.
40. Sequist L.V., Soria J.-C., Gadgeel S.M., et al. First-in-human evaluation of CO-1686, an irreversible, selective, and potent tyrosine kinase inhibitor of EGFR T790M. J. Clin. Oncol. 2013, 31. abstract 2524.
41. Serra V., Vivancos A., Puente X.S., et al. Clinical response to a Lapatinib-based therapy for a Li-Fraumeni syndrome patient with a novel HER2V659E mutation. Cancer Discov. 2013, 3:1238-1244.
42. Shi H., Moriceau G., Kong X., et al. Preexisting MEK1 exon 3 mutations in V600E/KBRAF melanomas do not confer resistance to BRAF inhibitors. Cancer Discov. 2012, 2:414-424.
43. Stone A., Sutherland R.L., Musgrove E.A. Inhibitors of cell cycle kinases: recent advances and future prospects as cancer therapeutics. Crit. Rev. Oncog. 2012, 17:175-198.
44. Tran B., Brown A.M., Bedard P.L., et al. Feasibility of real time next generation sequencing of cancer genes linked to drug response: results from a clinical trial. Int. J. Cancer 2013, 132:1547-1555.
45. Van Allen E.M., Wagle N., Levy M.A. Clinical analysis and interpretation of cancer genome data. J. Clin. Oncol. 2013, 31:1825-1833.
46. Vogelstein B., Papadopoulos N., Velculescu V.E., et al. Cancer genome landscapes. Science 2013, 339:1546-1558.
47. Wagle N., Berger M.F., Davis M.J., et al. High-throughput detection of actionable genomic alterations in clinical tumor samples by targeted, massively parallel sequencing. Cancer Discov. 2012, 2:82-93.
48. Wagle N., Emery C., Berger M.F., et al. Dissecting therapeutic resistance to RAF inhibition in melanoma by tumor genomic profiling. J. Clin. Oncol. 2011, 29:3085-3096.
49. Watt S., Jiao W., Brown A.M., et al. Clinical genomics information management software linking cancer genome sequence and clinical decisions. Genomics 2013, 102:140-147.
50. Whittaker S.R., Theurillat J.P., Van Allen E., et al. A genome-scale RNA interference screen implicates NF1 loss in resistance to RAF inhibition. Cancer Discov. 2013, 3:350-362.
51. Wong W.C., Kim D., Carter H., et al. CHASM and SNVBox: toolkit for detecting biologically important single nucleotide mutations in cancer. Bioinformatics 2011, 27:2147-2148.
52. Yeh P., Chen H., Andrews J., et al. DNA-Mutation Inventory to Refine and Enhance Cancer Treatment (DIRECT): a catalog of clinically relevant cancer mutations to enable genome-directed anticancer therapy. Clin. Cancer Res. 2013, 19:1894-1901.
53. Zhang J., Liu J., Sun J., et al. Identifying driver mutations from sequencing data of heterogeneous tumors in the era of personalized genome sequencing. Brief Bioinform. 2014, 15:244-255.