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Published in: International Journal of Clinical Oncology 2/2019

Open Access 01-02-2019 | Invited Review Article

Knowledge base toward understanding actionable alterations and realizing precision oncology

Authors: Shiho Takeuchi, Shujiro Okuda

Published in: International Journal of Clinical Oncology | Issue 2/2019

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Abstract

In Japan, the National Cancer Center and university hospitals have initiated next-generation sequencing-based in vitro diagnostic testing for cancer patients as a method of clinical sequencing. Based on the molecular alterations detected, physicians can provide approved targeted therapy and access to investigational drugs for cancer patients. However, interpretation of the clinical significance of genomic alterations remains the most severe bottleneck of precision medicine in cancer. Although many research institutes in the United States are developing knowledge bases for interpretation of the tumor alterations and clinical decisions, these knowledge bases are unsuited as sources of reference in Japan due to differences in the information on approved drugs and implementation of clinical trials. In this review, we introduce knowledge bases for clinical decision-making based on genomic events in cancer, and discuss the resources of additional information necessary for implementing precision medicine in Japan.
Literature
1.
go back to reference Shigematsu H, Lin L, Takahashi T et al (2005) Clinical and biological features associated with epidermal growth factor receptor gene mutations in lung cancers. J Natl Cancer Inst 97:339–346CrossRefPubMed Shigematsu H, Lin L, Takahashi T et al (2005) Clinical and biological features associated with epidermal growth factor receptor gene mutations in lung cancers. J Natl Cancer Inst 97:339–346CrossRefPubMed
2.
go back to reference Midha A, Dearden S, McCormack R (2015) EGFR mutation incidence in non-small-cell lung cancer of adenocarcinoma histology: a systematic review and global map by ethnicity (mutMapII). Am J Cancer Res 5:2892–2911PubMedPubMedCentral Midha A, Dearden S, McCormack R (2015) EGFR mutation incidence in non-small-cell lung cancer of adenocarcinoma histology: a systematic review and global map by ethnicity (mutMapII). Am J Cancer Res 5:2892–2911PubMedPubMedCentral
3.
go back to reference Mitsudomi T, Yatabe Y (2007) Mutations of the epidermal growth factor receptor gene and related genes as determinants of epidermal growth factor receptor tyrosine kinase inhibitors sensitivity in lung cancer. Cancer Sci 98:1817–1824CrossRefPubMed Mitsudomi T, Yatabe Y (2007) Mutations of the epidermal growth factor receptor gene and related genes as determinants of epidermal growth factor receptor tyrosine kinase inhibitors sensitivity in lung cancer. Cancer Sci 98:1817–1824CrossRefPubMed
4.
go back to reference Paez JG, Jänne PA, Lee JC et al (2004) EGFR mutations in lung, cancer: correlation with clinical response to gefitinib therapy. Science 302:1497–1500CrossRef Paez JG, Jänne PA, Lee JC et al (2004) EGFR mutations in lung, cancer: correlation with clinical response to gefitinib therapy. Science 302:1497–1500CrossRef
5.
go back to reference 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 350:2129–2139CrossRefPubMed 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 350:2129–2139CrossRefPubMed
6.
go back to reference Rosell R, Moran T, Queralt C et al (2009) Screening for epidermal growth factor receptor mutations in lung cancer. N Engl J Med 361:958–967CrossRefPubMed Rosell R, Moran T, Queralt C et al (2009) Screening for epidermal growth factor receptor mutations in lung cancer. N Engl J Med 361:958–967CrossRefPubMed
7.
go back to reference Paz-Ares L, Tan E-H, O’Byrne K et al (2017) Afatinib versus gefitinib in patients with EGFR mutation-positive advanced non-small-cell lung cancer: overall survival data from the phase IIb LUX-Lung 7 trial. Ann Oncol 28:270–277CrossRefPubMedPubMedCentral Paz-Ares L, Tan E-H, O’Byrne K et al (2017) Afatinib versus gefitinib in patients with EGFR mutation-positive advanced non-small-cell lung cancer: overall survival data from the phase IIb LUX-Lung 7 trial. Ann Oncol 28:270–277CrossRefPubMedPubMedCentral
8.
go back to reference Yang JCH, Sequist LV, Geater SL et al (2015) Clinical activity of afatinib in patients with advanced non-small-cell lung cancer harbouring uncommon EGFR mutations: a combined post-hoc analysis of LUX-Lung 2, LUX-Lung 3, and LUX-Lung 6. Lancet Oncol 16:830–838CrossRefPubMed Yang JCH, Sequist LV, Geater SL et al (2015) Clinical activity of afatinib in patients with advanced non-small-cell lung cancer harbouring uncommon EGFR mutations: a combined post-hoc analysis of LUX-Lung 2, LUX-Lung 3, and LUX-Lung 6. Lancet Oncol 16:830–838CrossRefPubMed
9.
go back to reference Soria J-C, Felip E, Cobo M et al (2015) Afatinib versus erlotinib as second-line treatment of patients with advanced squamous cell carcinoma of the lung (LUX-Lung 8): an open-label randomised controlled phase 3 trial. Lancet Oncol 16:897–907CrossRefPubMed Soria J-C, Felip E, Cobo M et al (2015) Afatinib versus erlotinib as second-line treatment of patients with advanced squamous cell carcinoma of the lung (LUX-Lung 8): an open-label randomised controlled phase 3 trial. Lancet Oncol 16:897–907CrossRefPubMed
10.
go back to reference Yang JC-H, Shih J-Y, Su W-C et al (2012) Afatinib for patients with lung adenocarcinoma and epidermal growth factor receptor mutations (LUX-Lung 2): a phase 2 trial. Lancet Oncol 13:539–548CrossRefPubMed Yang JC-H, Shih J-Y, Su W-C et al (2012) Afatinib for patients with lung adenocarcinoma and epidermal growth factor receptor mutations (LUX-Lung 2): a phase 2 trial. Lancet Oncol 13:539–548CrossRefPubMed
11.
12.
go back to reference Pao W, Miller VA, Politi KA et al (2005) Acquired resistance of lung adenocarcinomas to gefitinib or erlotinib is associated with a second mutation in the EGFR kinase domain. PLoS Med 2:e73CrossRefPubMedPubMedCentral Pao W, Miller VA, Politi KA et al (2005) Acquired resistance of lung adenocarcinomas to gefitinib or erlotinib is associated with a second mutation in the EGFR kinase domain. PLoS Med 2:e73CrossRefPubMedPubMedCentral
13.
go back to reference Yu HA, Arcila ME, Rekhtman N et al (2013) Analysis of tumor specimens at the time of acquired resistance to EGFR-TKI therapy in 155 patients with EGFR-mutant lung cancers. Clin Cancer Res 19:2240–2247CrossRefPubMedPubMedCentral Yu HA, Arcila ME, Rekhtman N et al (2013) Analysis of tumor specimens at the time of acquired resistance to EGFR-TKI therapy in 155 patients with EGFR-mutant lung cancers. Clin Cancer Res 19:2240–2247CrossRefPubMedPubMedCentral
14.
go back to reference Campo M, Gerber D, Gainor JF et al (2016) Acquired resistance to first-line afatinib and the challenges of prearranged progression biopsies. J Thorac Oncol 11:2022–2026CrossRefPubMed Campo M, Gerber D, Gainor JF et al (2016) Acquired resistance to first-line afatinib and the challenges of prearranged progression biopsies. J Thorac Oncol 11:2022–2026CrossRefPubMed
15.
go back to reference Sequist LV, Waltman BA, Dias-Santagata D et al (2011) Genotypic and histological evolution of lung cancers acquiring resistance to EGFR inhibitors. Sci Transl Med 3:75ra26CrossRefPubMedPubMedCentral Sequist LV, Waltman BA, Dias-Santagata D et al (2011) Genotypic and histological evolution of lung cancers acquiring resistance to EGFR inhibitors. Sci Transl Med 3:75ra26CrossRefPubMedPubMedCentral
16.
go back to reference Cross DAE, Ashton SE, Ghiorghiu S et al (2014) AZD9291, an irreversible EGFR TKI, overcomes T790M-mediated resistance to EGFR inhibitors in lung cancer. Cancer Discov 4:1046–1061CrossRefPubMedPubMedCentral Cross DAE, Ashton SE, Ghiorghiu S et al (2014) AZD9291, an irreversible EGFR TKI, overcomes T790M-mediated resistance to EGFR inhibitors in lung cancer. Cancer Discov 4:1046–1061CrossRefPubMedPubMedCentral
17.
go back to reference Ou SHI, Agarwal N, Ali SM (2016) High MET amplification level as a resistance mechanism to osimertinib (AZD9291) in a patient that symptomatically responded to crizotinib treatment post-osimertinib progression. Lung Cancer 98:59–61CrossRefPubMed Ou SHI, Agarwal N, Ali SM (2016) High MET amplification level as a resistance mechanism to osimertinib (AZD9291) in a patient that symptomatically responded to crizotinib treatment post-osimertinib progression. Lung Cancer 98:59–61CrossRefPubMed
18.
go back to reference Planchard D, Loriot Y, André F et al (2015) EGFR-independent mechanisms of acquired resistance to AZD9291 in EGFR T790M-positive NSCLC patients. Ann Oncol 26:2073–2078CrossRefPubMed Planchard D, Loriot Y, André F et al (2015) EGFR-independent mechanisms of acquired resistance to AZD9291 in EGFR T790M-positive NSCLC patients. Ann Oncol 26:2073–2078CrossRefPubMed
19.
go back to reference Venderbosch S, Nagtegaal ID, Maughan TS et al (2014) Mismatch repair status and BRAF mutation status in metastatic colorectal cancer patients: a pooled analysis of the CAIRO, CAIRO2, COIN, and FOCUS studies. Clin Cancer Res 20:5322–5330CrossRefPubMedPubMedCentral Venderbosch S, Nagtegaal ID, Maughan TS et al (2014) Mismatch repair status and BRAF mutation status in metastatic colorectal cancer patients: a pooled analysis of the CAIRO, CAIRO2, COIN, and FOCUS studies. Clin Cancer Res 20:5322–5330CrossRefPubMedPubMedCentral
20.
go back to reference Safaee Ardekani G, Jafarnejad SM, Tan L et al (2012) The prognostic value of BRAF mutation in colorectal cancer and melanoma: a systematic review and meta-analysis. PLoS One 7:e47054CrossRefPubMedPubMedCentral Safaee Ardekani G, Jafarnejad SM, Tan L et al (2012) The prognostic value of BRAF mutation in colorectal cancer and melanoma: a systematic review and meta-analysis. PLoS One 7:e47054CrossRefPubMedPubMedCentral
21.
go back to reference Pietrantonio F, Petrelli F, Coinu A et al (2015) Predictive role of BRAF mutations in patients with advanced colorectal cancer receiving cetuximab and panitumumab: a meta-analysis. Eur J Cancer 51:587–594CrossRefPubMed Pietrantonio F, Petrelli F, Coinu A et al (2015) Predictive role of BRAF mutations in patients with advanced colorectal cancer receiving cetuximab and panitumumab: a meta-analysis. Eur J Cancer 51:587–594CrossRefPubMed
22.
go back to reference Jørgensen JT (2016) Companion and complementary diagnostics: clinical and regulatory perspectives. Trends Cancer 2(12):706–712CrossRefPubMed Jørgensen JT (2016) Companion and complementary diagnostics: clinical and regulatory perspectives. Trends Cancer 2(12):706–712CrossRefPubMed
23.
go back to reference Food and Drug Administration (2017) Summary of safety and effectiveness data (SSED). Food and Drug Administration, Silver Spring Food and Drug Administration (2017) Summary of safety and effectiveness data (SSED). Food and Drug Administration, Silver Spring
24.
go back to reference Forbes SA, Beare D, Gunasekaran P et al (2015) COSMIC: exploring the world’s knowledge of somatic mutations in human cancer. Nucleic Acids Res 43:D805–D811CrossRefPubMed Forbes SA, Beare D, Gunasekaran P et al (2015) COSMIC: exploring the world’s knowledge of somatic mutations in human cancer. Nucleic Acids Res 43:D805–D811CrossRefPubMed
25.
go back to reference Rehm HL, Berg JS, Plon SE (2018) ClinGen and ClinVar—enabling genomics in precision medicine. Hum Mutat 39:1473–1475CrossRef Rehm HL, Berg JS, Plon SE (2018) ClinGen and ClinVar—enabling genomics in precision medicine. Hum Mutat 39:1473–1475CrossRef
26.
go back to reference Madhavan S, Ritter D, Micheel C et al (2018) ClinGen Cancer Somatic Working Group—standardizing and democratizing access to cancer molecular diagnostic data to drive translational research. Pac Symp Biocomput 23:247–258PubMedPubMedCentral Madhavan S, Ritter D, Micheel C et al (2018) ClinGen Cancer Somatic Working Group—standardizing and democratizing access to cancer molecular diagnostic data to drive translational research. Pac Symp Biocomput 23:247–258PubMedPubMedCentral
29.
go back to reference Ritter DI, Roychowdhury S, Roy A et al (2016) Somatic cancer variant curation and harmonization through consensus minimum variant level data. Genome Med 8:1–9CrossRef Ritter DI, Roychowdhury S, Roy A et al (2016) Somatic cancer variant curation and harmonization through consensus minimum variant level data. Genome Med 8:1–9CrossRef
32.
go back to reference Huang L, Fernandes H, Zia H et al (2017) The cancer precision medicine knowledge base for structured clinical-grade mutations and interpretations. J Am Med Inform Assoc 24:513–519PubMed Huang L, Fernandes H, Zia H et al (2017) The cancer precision medicine knowledge base for structured clinical-grade mutations and interpretations. J Am Med Inform Assoc 24:513–519PubMed
33.
34.
go back to reference Vanderbilt-Ingram Cancer Center (2010) My cancer genome. Cancer Genet 207:289 Vanderbilt-Ingram Cancer Center (2010) My cancer genome. Cancer Genet 207:289
36.
go back to reference Tamborero D, Rubio-Perez C, Deu-Pons J et al (2018) Cancer genome interpreter annotates the biological and clinical relevance of tumor alterations. Genome Med 10:25CrossRefPubMedPubMedCentral Tamborero D, Rubio-Perez C, Deu-Pons J et al (2018) Cancer genome interpreter annotates the biological and clinical relevance of tumor alterations. Genome Med 10:25CrossRefPubMedPubMedCentral
38.
go back to reference Griffith M, Spies NC, Krysiak K et al (2017) CIViC is a community knowledgebase for expert crowdsourcing the clinical interpretation of variants in cancer. Nat Genet 49:170–174CrossRefPubMedPubMedCentral Griffith M, Spies NC, Krysiak K et al (2017) CIViC is a community knowledgebase for expert crowdsourcing the clinical interpretation of variants in cancer. Nat Genet 49:170–174CrossRefPubMedPubMedCentral
39.
go back to reference Rosales RA, Drummond RD, Valieris R et al (2016) CIViC: a knowledgebase for expert-crowdsourcing the clinical interpretation of variants in cancer. Nature 23:1–19 Rosales RA, Drummond RD, Valieris R et al (2016) CIViC: a knowledgebase for expert-crowdsourcing the clinical interpretation of variants in cancer. Nature 23:1–19
40.
go back to reference Danos AM, Ritter DI, Wagner AH et al (2018) Adapting crowdsourced clinical cancer curation in CIViC to the ClinGen minimum variant level data community-driven standards. Hum Mutat 39:1721–1732CrossRefPubMedPubMedCentral Danos AM, Ritter DI, Wagner AH et al (2018) Adapting crowdsourced clinical cancer curation in CIViC to the ClinGen minimum variant level data community-driven standards. Hum Mutat 39:1721–1732CrossRefPubMedPubMedCentral
44.
go back to reference Sunami K, Takahashi H, Tsuchihara K et al (2018) Clinical practice guidance for next-generation sequencing in cancer diagnosis and treatment (edition 1.0). Cancer Sci 109:2980–2985CrossRefPubMedPubMedCentral Sunami K, Takahashi H, Tsuchihara K et al (2018) Clinical practice guidance for next-generation sequencing in cancer diagnosis and treatment (edition 1.0). Cancer Sci 109:2980–2985CrossRefPubMedPubMedCentral
Metadata
Title
Knowledge base toward understanding actionable alterations and realizing precision oncology
Authors
Shiho Takeuchi
Shujiro Okuda
Publication date
01-02-2019
Publisher
Springer Singapore
Published in
International Journal of Clinical Oncology / Issue 2/2019
Print ISSN: 1341-9625
Electronic ISSN: 1437-7772
DOI
https://doi.org/10.1007/s10147-018-1378-0

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