Genetic characterization of pancreatic cancer patients and prediction of carrier status of germline pathogenic variants in cancer-predisposing genes

Background: National Comprehensive Cancer Network (NCCN) recently recommended germline genetic testing for all pancreatic cancer patients. However, the genes targeted by genetic testing and the feasibility of selecting patients likely to carry pathogenic variants have not been sufficiently verified....

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Main Authors: Keijiro Mizukami, Yusuke Iwasaki, Eiryo Kawakami, Makoto Hirata, Yoichiro Kamatani, Koichi Matsuda, Mikiko Endo, Kokichi Sugano, Teruhiko Yoshida, Yoshinori Murakami, Hidewaki Nakagawa, Amanda B. Spurdle, Yukihide Momozawa
Format: Article
Language:English
Published: Elsevier 2020-10-01
Series:EBioMedicine
Subjects:
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Online Access:http://www.sciencedirect.com/science/article/pii/S2352396420304096
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language English
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author Keijiro Mizukami
Yusuke Iwasaki
Eiryo Kawakami
Makoto Hirata
Yoichiro Kamatani
Koichi Matsuda
Mikiko Endo
Kokichi Sugano
Teruhiko Yoshida
Yoshinori Murakami
Hidewaki Nakagawa
Amanda B. Spurdle
Yukihide Momozawa
spellingShingle Keijiro Mizukami
Yusuke Iwasaki
Eiryo Kawakami
Makoto Hirata
Yoichiro Kamatani
Koichi Matsuda
Mikiko Endo
Kokichi Sugano
Teruhiko Yoshida
Yoshinori Murakami
Hidewaki Nakagawa
Amanda B. Spurdle
Yukihide Momozawa
Genetic characterization of pancreatic cancer patients and prediction of carrier status of germline pathogenic variants in cancer-predisposing genes
EBioMedicine
Pancreatic cancer
Pathogenic variants
Universal screening for patients
Machine learning
BRCA
ATM
author_facet Keijiro Mizukami
Yusuke Iwasaki
Eiryo Kawakami
Makoto Hirata
Yoichiro Kamatani
Koichi Matsuda
Mikiko Endo
Kokichi Sugano
Teruhiko Yoshida
Yoshinori Murakami
Hidewaki Nakagawa
Amanda B. Spurdle
Yukihide Momozawa
author_sort Keijiro Mizukami
title Genetic characterization of pancreatic cancer patients and prediction of carrier status of germline pathogenic variants in cancer-predisposing genes
title_short Genetic characterization of pancreatic cancer patients and prediction of carrier status of germline pathogenic variants in cancer-predisposing genes
title_full Genetic characterization of pancreatic cancer patients and prediction of carrier status of germline pathogenic variants in cancer-predisposing genes
title_fullStr Genetic characterization of pancreatic cancer patients and prediction of carrier status of germline pathogenic variants in cancer-predisposing genes
title_full_unstemmed Genetic characterization of pancreatic cancer patients and prediction of carrier status of germline pathogenic variants in cancer-predisposing genes
title_sort genetic characterization of pancreatic cancer patients and prediction of carrier status of germline pathogenic variants in cancer-predisposing genes
publisher Elsevier
series EBioMedicine
issn 2352-3964
publishDate 2020-10-01
description Background: National Comprehensive Cancer Network (NCCN) recently recommended germline genetic testing for all pancreatic cancer patients. However, the genes targeted by genetic testing and the feasibility of selecting patients likely to carry pathogenic variants have not been sufficiently verified. The purpose of this study was to genetically characterize Japanese patients and examine whether the current guideline is applicable in this population. Methods: Using targeted sequencing, we analyzed the coding regions of 27 cancer-predisposing genes in 1,005 pancreatic cancer patients and 23,705 controls in Japan. We compared the pathogenic variant frequency between cases and controls and documented the demographic and clinical characteristics of carrier patients. We then examined if it was possible to use machine learning to predict carrier status based on those characteristics. Findings: We identified 205 pathogenic variants across the 27 genes. Pathogenic variants in BRCA2, ATM, and BRCA1 were significantly associated with pancreatic cancer. Characteristics associated with carrier status were inconsistent with previous investigations. Machine learning classifiers had a low performance in determining the carrier status of pancreatic cancer patients, while the same classifiers, when applied to breast cancer data as a positive control, had a higher performance that was comparable to that of the NCCN guideline. Interpretation: Our findings support the clinical significance of multigene panel testing for pancreatic cancer and indicate that at least 3.4% of Japanese patients may respond to poly (ADP ribose) polymerase inhibitor treatments. The difficulty in predicting carrier status suggests that offering germline genetic testing for all pancreatic cancer patients is reasonable. Funding: AMED under Grant Number JP19kk0305010 and Australian National Health and Medical Research funding (ID177524)
topic Pancreatic cancer
Pathogenic variants
Universal screening for patients
Machine learning
BRCA
ATM
url http://www.sciencedirect.com/science/article/pii/S2352396420304096
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spelling doaj-6a8653e9cd964434b6a9a795a05beced2020-11-25T03:53:05ZengElsevierEBioMedicine2352-39642020-10-0160103033Genetic characterization of pancreatic cancer patients and prediction of carrier status of germline pathogenic variants in cancer-predisposing genesKeijiro Mizukami0Yusuke Iwasaki1Eiryo Kawakami2Makoto Hirata3Yoichiro Kamatani4Koichi Matsuda5Mikiko Endo6Kokichi Sugano7Teruhiko Yoshida8Yoshinori Murakami9Hidewaki Nakagawa10Amanda B. Spurdle11Yukihide Momozawa12Laboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa 230-0045, JapanLaboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa 230-0045, JapanMedical Sciences Innovation Hub Program, RIKEN, Yokohama, Kanagawa, Japan; Artificial Intelligence Medicine, Graduate School of Medicine, Chiba University, Chiba, JapanInstitute of Medical Science, The University of Tokyo, Tokyo, Japan; Department of Genetic Medicine and Services, National Cancer Center Hospital, Tokyo JapanGraduate School of Frontier Sciences, The University of Tokyo, Tokyo, JapanGraduate School of Frontier Sciences, The University of Tokyo, Tokyo, JapanLaboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa 230-0045, JapanDepartment of Genetic Medicine and Services, National Cancer Center Hospital, Tokyo Japan; Division of Cancer Prevention and Genetic Counseling, Genome Center, Tochigi Cancer Center, JapanDepartment of Genetic Medicine and Services, National Cancer Center Hospital, Tokyo JapanInstitute of Medical Science, The University of Tokyo, Tokyo, JapanLaboratory for Cancer Genomics, RIKEN Center for Integrative Medical Sciences, Yokohama, JapanDivision of Genetics and Population Health, QIMR Berghofer Medical Research Institute, Brisbane, AustraliaLaboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan; Corresponding author.Background: National Comprehensive Cancer Network (NCCN) recently recommended germline genetic testing for all pancreatic cancer patients. However, the genes targeted by genetic testing and the feasibility of selecting patients likely to carry pathogenic variants have not been sufficiently verified. The purpose of this study was to genetically characterize Japanese patients and examine whether the current guideline is applicable in this population. Methods: Using targeted sequencing, we analyzed the coding regions of 27 cancer-predisposing genes in 1,005 pancreatic cancer patients and 23,705 controls in Japan. We compared the pathogenic variant frequency between cases and controls and documented the demographic and clinical characteristics of carrier patients. We then examined if it was possible to use machine learning to predict carrier status based on those characteristics. Findings: We identified 205 pathogenic variants across the 27 genes. Pathogenic variants in BRCA2, ATM, and BRCA1 were significantly associated with pancreatic cancer. Characteristics associated with carrier status were inconsistent with previous investigations. Machine learning classifiers had a low performance in determining the carrier status of pancreatic cancer patients, while the same classifiers, when applied to breast cancer data as a positive control, had a higher performance that was comparable to that of the NCCN guideline. Interpretation: Our findings support the clinical significance of multigene panel testing for pancreatic cancer and indicate that at least 3.4% of Japanese patients may respond to poly (ADP ribose) polymerase inhibitor treatments. The difficulty in predicting carrier status suggests that offering germline genetic testing for all pancreatic cancer patients is reasonable. Funding: AMED under Grant Number JP19kk0305010 and Australian National Health and Medical Research funding (ID177524)http://www.sciencedirect.com/science/article/pii/S2352396420304096Pancreatic cancerPathogenic variantsUniversal screening for patientsMachine learningBRCAATM