CoChat
Sign Up
Cited by 45Pancreatic and Hepatic Oncology ResearchGenetic Associations and EpidemiologyGenetic factors in colorectal cancer

Prediction model for pancreatic cancer risk in the general Japanese population

Open access
Nakatochi, Masahiro, Lin, Yingsong, Ito, Hidemi, Hara, Kazuo, Kinoshita, Fumie, Kobayashi, Yumiko, Ishii, Hiroshi, Ozaka, Masato +17 more·2018·PLOS ONE
DOI 10.1371/journal.pone.0203386PMC PMC6128543
Open this paper in CoChat — free account

Abstract

Genome-wide association studies (GWASs) have identified many single nucleotide polymorphisms (SNPs) that are significantly associated with pancreatic cancer susceptibility. We sought to replicate the associations of 61 GWAS-identified SNPs at 42 loci with pancreatic cancer in Japanese and to develop a risk model for the identification of individuals at high risk for pancreatic cancer development in the general Japanese population. The model was based on data including directly determined or imputed SNP genotypes for 664 pancreatic cancer case and 664 age- and sex-matched control subjects. Stepwise logistic regression uncovered five GWAS-identified SNPs at five loci that also showed significant associations in our case-control cohort. These five SNPs were included in the risk model and also applied to calculation of the polygenic risk score (PRS). The area under the curve determined with the leave-one-out cross-validation method was 0.63 (95% confidence interval, 0.60-0.66) or 0.61 (0.58-0.64) for versions of the model that did or did not include cigarette smoking and family history of pancreatic cancer in addition to the five SNPs, respectively. Individuals in the lowest and highest quintiles for the PRS had odds ratios of 0.62 (0.42-0.91) and 1.98 (1.42-2.76), respectively, for pancreatic cancer development compared with those in the middle quintile. We have thus developed a risk model for pancreatic cancer that showed moderately good discriminatory ability with regard to differentiation of pancreatic cancer patients from control individuals. Our findings suggest the potential utility of a risk model that incorporates replicated GWAS-identified SNPs and established demographic or environmental factors for the identification of individuals at increased risk for pancreatic cancer development.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1371/journal.pone.0203386

Cites

1 of 1 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 34

  1. [1]Lucas AL, Malvezzi M, Carioli G, Negri E, La Vecchia C, Boffetta P, et al (2016) Global Trends in Pancreatic Cancer Mortality From 1980 Through 2013 and Predictions for 2017. Clin Gastroenterol Hepatol 14: 1452– 1462 e1454 10.1016/j.cgh.2016.05.034 27266982 PMC5028258 · DOI
  2. [2]Matsuo K, Ito H, Wakai K, Nagata C, Mizoue T, Tanaka K, et al (2011) Cigarette smoking and pancreas cancer risk: an evaluation based on a systematic review of epidemiologic evidence in the Japanese population. Jpn J Clin Oncol 41: 1292– 1302. 10.1093/jjco/hyr141 21971423 · DOI
  3. [4]Zhang M, Wang Z, Obazee O, Jia J, Childs EJ, Hoskins J, et al (2016) Three new pancreatic cancer susceptibility signals identified on chromosomes 1q32.1, 5p15.33 and 8q24.21. Oncotarget 7: 66328– 66343. doi: 10.18632/oncotarget.11041 27579533 PMC5340084 · DOI
  4. [5]Klein AP, Wolpin BM, Risch HA, Stolzenberg-Solomon RZ, Mocci E, Zhang M, et al (2018) Genome-wide meta-analysis identifies five new susceptibility loci for pancreatic cancer. Nat Commun 9: 556 10.1038/s41467-018-02942-5 29422604 PMC5805680 · DOI · Paper page
  5. [6]Amundadottir L, Kraft P, Stolzenberg-Solomon RZ, Fuchs CS, Petersen GM, Arslan AA, et al (2009) Genome-wide association study identifies variants in the ABO locus associated with susceptibility to pancreatic cancer. Nat Genet 41: 986– 990. 10.1038/ng.429 19648918 PMC2839871 · DOI
  6. [7]Petersen GM, Amundadottir L, Fuchs CS, Kraft P, Stolzenberg-Solomon RZ, Jacobs KB, et al (2010) A genome-wide association study identifies pancreatic cancer susceptibility loci on chromosomes 13q22.1, 1q32.1 and 5p15.33. Nat Genet 42: 224– 228. 10.1038/ng.522 20101243 PMC2853179 · DOI
  7. [8]Wolpin BM, Rizzato C, Kraft P, Kooperberg C, Petersen GM, Wang Z, et al (2014) Genome-wide association study identifies multiple susceptibility loci for pancreatic cancer. Nat Genet 46: 994– 1000. 10.1038/ng.3052 25086665 PMC4191666 · DOI
  8. [9]Childs EJ, Mocci E, Campa D, Bracci PM, Gallinger S, Goggins M, et al (2015) Common variation at 2p13.3, 3q29, 7p13 and 17q25.1 associated with susceptibility to pancreatic cancer. Nat Genet 47: 911– 916. 10.1038/ng.3341 26098869 PMC4520746 · DOI
  9. [10]Campa D, Rizzato C, Bauer AS, Werner J, Capurso G, Costello E, et al (2013) Lack of replication of seven pancreatic cancer susceptibility loci identified in two Asian populations. Cancer Epidemiol Biomarkers Prev 22: 320– 323. 10.1158/1055-9965.EPI-12-1182 23250936 · DOI
  10. [11]Wu C, Miao X, Huang L, Che X, Jiang G, Yu D, et al (2012) Genome-wide association study identifies five loci associated with susceptibility to pancreatic cancer in Chinese populations. Nat Genet 44: 62– 66. 22158540
  11. [12]Low SK, Kuchiba A, Zembutsu H, Saito A, Takahashi A, Kubo M, et al (2010) Genome-wide association study of pancreatic cancer in Japanese population. PLoS One 5: e11824 10.1371/journal.pone.0011824 20686608 PMC2912284 · DOI
  12. [13]Klein AP, Lindstrom S, Mendelsohn JB, Steplowski E, Arslan AA, Bueno-de-Mesquita HB, et al (2013) An absolute risk model to identify individuals at elevated risk for pancreatic cancer in the general population. PLoS One 8: e72311 10.1371/journal.pone.0072311 24058443 PMC3772857 · DOI · Paper page
  13. [14]Abe M, Ito H, Oze I, Nomura M, Ogawa Y, Matsuo K (2017) The more from East-Asian, the better: risk prediction of colorectal cancer risk by GWAS-identified SNPs among Japanese. J Cancer Res Clin Oncol 143: 2481– 2492. 10.1007/s00432-017-2505-4 28849422 PMC11818987 · DOI
  14. [15]Wen W, Shu XO, Guo X, Cai Q, Long J, Bolla MK, et al (2016) Prediction of breast cancer risk based on common genetic variants in women of East Asian ancestry. Breast Cancer Res 18: 124 10.1186/s13058-016-0786-1 27931260 PMC5146840 · DOI
  15. [16]Gail MH (2008) Discriminatory accuracy from single-nucleotide polymorphisms in models to predict breast cancer risk. J Natl Cancer Inst 100: 1037– 1041. 10.1093/jnci/djn180 18612136 PMC2528005 · DOI
  16. [17]Sueta A, Ito H, Kawase T, Hirose K, Hosono S, Yatabe Y, et al (2012) A genetic risk predictor for breast cancer using a combination of low-penetrance polymorphisms in a Japanese population. Breast Cancer Res Treat 132: 711– 721. 10.1007/s10549-011-1904-5 22160591 · DOI
  17. [18]Wacholder S, Hartge P, Prentice R, Garcia-Closas M, Feigelson HS, Diver WR, et al (2010) Performance of common genetic variants in breast-cancer risk models. N Engl J Med 362: 986– 993. 10.1056/NEJMoa0907727 20237344 PMC2921181 · DOI
  18. [19]Lin Y, Ueda J, Yagyu K, Ishii H, Ueno M, Egawa N, et al (2013) Association between variations in the fat mass and obesity-associated gene and pancreatic cancer risk: a case-control study in Japan. BMC Cancer 13: 337 10.1186/1471-2407-13-337 23835106 PMC3716552 · DOI
  19. [20]Inoue M, Tajima K, Hirose K, Hamajima N, Takezaki T, Kuroishi T, et al (1997) Epidemiological features of first-visit outpatients in Japan: comparison with general population and variation by sex, age, and season. J Clin Epidemiol 50: 69– 77. 9048692
  20. [21]Chang CC, Chow CC, Tellier LC, Vattikuti S, Purcell SM, Lee JJ, et al (2015) Second-generation PLINK: rising to the challenge of larger and richer datasets. Gigascience 4: 7 10.1186/s13742-015-0047-8 25722852 PMC4342193 · DOI · Paper page
  21. [22]Patterson N, Price AL, Reich D (2006) Population structure and eigenanalysis. PLoS Genet 2: e190 10.1371/journal.pgen.0020190 17194218 PMC1713260 · DOI · Paper page
  22. [23]Genomes Project C, Auton A, Brooks LD, Durbin RM, Garrison EP, Kang HM, et al (2015) A global reference for human genetic variation. Nature 526: 68– 74. 10.1038/nature15393 26432245 PMC4750478 · DOI · Paper page
  23. [24]Delaneau O, Zagury JF, Marchini J (2013) Improved whole-chromosome phasing for disease and population genetic studies. Nat Methods 10: 5– 6. 10.1038/nmeth.2307 23269371 · DOI
  24. [25]Das S, Forer L, Schonherr S, Sidore C, Locke AE, Kwong A, et al (2016) Next-generation genotype imputation service and methods. Nat Genet 48: 1284– 1287. 10.1038/ng.3656 27571263 PMC5157836 · DOI · Paper page
  25. [26]Welter D, MacArthur J, Morales J, Burdett T, Hall P, Junkins H, et al (2014) The NHGRI GWAS Catalog, a curated resource of SNP-trait associations. Nucleic Acids Res 42: D1001– 1006. 10.1093/nar/gkt1229 24316577 PMC3965119 · DOI · Paper page
  26. [27]Robin X, Turck N, Hainard A, Tiberti N, Lisacek F, Sanchez JC, et al (2011) pROC: an open-source package for R and S+ to analyze and compare ROC curves. BMC Bioinformatics 12: 77 10.1186/1471-2105-12-77 21414208 PMC3068975 · DOI · Paper page
  27. [28]Lee SH, Wray NR, Goddard ME, Visscher PM (2011) Estimating missing heritability for disease from genome-wide association studies. Am J Hum Genet 88: 294– 305. 10.1016/j.ajhg.2011.02.002 21376301 PMC3059431 · DOI · Paper page
  28. [29]Ferlay J, Soerjomataram I, Dikshit R, Eser S, Mathers C, Rebelo M, et al (2015) Cancer incidence and mortality worldwide: sources, methods and major patterns in GLOBOCAN 2012. Int J Cancer 136: E359– 386. 10.1002/ijc.29210 25220842 · DOI · Paper page
  29. [30]Freedman AN, Seminara D, Gail MH, Hartge P, Colditz GA, Ballard-Barbash R, et al (2005) Cancer risk prediction models: a workshop on development, evaluation, and application. J Natl Cancer Inst 97: 715– 723. 10.1093/jnci/dji128 15900041 · DOI
  30. [31]Risch HA, Yu H, Lu L, Kidd MS (2015) Detectable Symptomatology Preceding the Diagnosis of Pancreatic Cancer and Absolute Risk of Pancreatic Cancer Diagnosis. Am J Epidemiol 182: 26– 34. 10.1093/aje/kwv026 26049860 PMC4479115 · DOI · Paper page
  31. [32]Yu A, Woo SM, Joo J, Yang HR, Lee WJ, Park SJ, et al (2016) Development and Validation of a Prediction Model to Estimate Individual Risk of Pancreatic Cancer. PLoS One 11: e0146473 10.1371/journal.pone.0146473 26752291 PMC4708985 · DOI · Paper page
  32. [33]Chatterjee N, Shi J, Garcia-Closas M (2016) Developing and evaluating polygenic risk prediction models for stratified disease prevention. Nat Rev Genet 17: 392– 406. 10.1038/nrg.2016.27 27140283 PMC6021129 · DOI
  33. [34]Lu Y, Ek WE, Whiteman D, Vaughan TL, Spurdle AB, Easton DF, et al (2014) Most common ‘sporadic’ cancers have a significant germline genetic component. Hum Mol Genet 23: 6112– 6118. 10.1093/hmg/ddu312 24943595 PMC4271103 · DOI
  34. [35]Machiela MJ, Chen CY, Chen C, Chanock SJ, Hunter DJ, Kraft P (2011) Evaluation of polygenic risk scores for predicting breast and prostate cancer risk. Genet Epidemiol 35: 506– 514. 10.1002/gepi.20600 21618606 PMC4089860 · DOI

Cited by

Sorted by citations

Authors
Nakatochi, M., Lin, Y., Ito, H., Hara, K., Kinoshita, F., Kobayashi, Y., Ishii, H., Ozaka, M., Sasaki, T., Sasahira, N., Morimoto, M., Kobayashi, S., Ueno, M., Ohkawa, S., Egawa, N., Kuruma, S., Mori, M., Nakao, H., Wang, C., Nishiyama, T., Kawaguchi, T., Takahashi, M., Matsuda, F., Kikuchi, S., & Matsuo, K.
Affiliations
  • Nagoya University Hospital (JP)
  • Aichi Medical University (JP)
  • Aichi Cancer Center (JP)
  • Shikoku Cancer Center (JP)
  • The Cancer Institute Hospital (JP)
  • Kanagawa Cancer Center (JP)
  • Tokyo Metropolitan Hiroo Hospital (JP)
  • Tokyo Metropolitan Komagome Hospital (JP)
  • Hokkaido Chitose College of Rehabilitation (JP)
  • Nagoya City University (JP)
  • Kyoto University (JP)
Corresponding author
Lin, Yingsong
ORCID
Venue
PLOS ONE
Publisher
Public Library of Science (PLoS)
Published
2018-09-07
Volume
13
Issue
9
Pages
e0203386
ISSN
1932-6203 (ISSN-L)
DOI
10.1371/journal.pone.0203386
PMC
PMC6128543
OpenAlex
W2891825751
Cited by
45
References
1
Citations by year
2026: 2 · 2025: 8 · 2024: 8 · 2023: 9 · 2022: 4 · 2021: 2 · 2020: 7 · 2019: 5
FWCI
1.32
Type
journal article
Language
en
Open access
Licence
Locations
  • PLoS ONE (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Institutional Repositories DataBase (IRDB) (submittedVersion, other-oa)
  • RePEc: Research Papers in Economics (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • Figshare (submittedVersion, cc-by)
  • Kyoto University Research Information Repository (Kyoto University) (submittedVersion, cc-by)
Funders
  • Ministry of Health, Labour and Welfare (H21-11-1)
  • Japan Society for the Promotion of Science (16H06277, 17K09095, 26253041, 17015018)
Topics
  • Health Sciences › Medicine › Oncology › Pancreatic and Hepatic Oncology Research
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
  • Health Sciences › Medicine › Pathology and Forensic Medicine › Genetic factors in colorectal cancer
Keywords
pancreatic cancer, cancer risk prediction model, polygenic risk score, single nucleotide polymorphisms, genetic susceptibility, Japanese population, cigarette smoking, family history of cancer, risk stratification
MeSH terms
Aged, Alleles, Female, Gene Frequency, Genotype, Humans, Japan, Male, Middle Aged, Models, Genetic, Pancreatic Neoplasms, Risk Factors, Cohort Studies, Logistic Models, Case-Control Studies, Genetic Predisposition to Disease, Polymorphism, Single Nucleotide, Asian People, Genome-Wide Association Study

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review