Skip to main content

Advertisement

SpringerLink
Log in

Proceedings of the third international molecular pathological epidemiology (MPE) meeting

  • Review
  • Published:
Cancer Causes & Control Aims and scope Submit manuscript

Abstract

Molecular pathological epidemiology (MPE) is a transdisciplinary and relatively new scientific discipline that integrates theory, methods, and resources from epidemiology, pathology, biostatistics, bioinformatics, and computational biology. The underlying objective of MPE research is to better understand the etiology and progression of complex and heterogeneous human diseases with the goal of informing prevention and treatment efforts in population health and clinical medicine. Although MPE research has been commonly applied to investigating breast, lung, and colorectal cancers, its methodology can be used to study most diseases. Recent successes in MPE studies include: (1) the development of new statistical methods to address etiologic heterogeneity; (2) the enhancement of causal inference; (3) the identification of previously unknown exposure-subtype disease associations; and (4) better understanding of the role of lifestyle/behavioral factors on modifying prognosis according to disease subtype. Central challenges to MPE include the relative lack of transdisciplinary experts, educational programs, and forums to discuss issues related to the advancement of the field. To address these challenges, highlight recent successes in the field, and identify new opportunities, a series of MPE meetings have been held at the Dana–Farber Cancer Institute in Boston, MA. Herein, we share the proceedings of the Third International MPE Meeting, held in May 2016 and attended by 150 scientists from 17 countries. Special topics included integration of MPE with immunology and health disparity research. This meeting series will continue to provide an impetus to foster further transdisciplinary integration of divergent scientific fields.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Ogino S, Stampfer M (2010) Lifestyle factors and microsatellite instability in colorectal cancer: the evolving field of molecular pathological epidemiology. J Natl Cancer Inst 102:365–367

    Article  PubMed  PubMed Central  Google Scholar 

  2. Ogino S, Lochhead P, Chan AT et al (2013) Molecular pathological epidemiology of epigenetics: emerging integrative science to analyze environment, host, and disease. Mod Pathol 26:465–484

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Nishi A, Kawachi I, Koenen KC, Wu K, Nishihara R, Ogino S (2015) Lifecourse epidemiology and molecular pathological epidemiology. Am J Prev Med 48:116–119

    Article  PubMed  PubMed Central  Google Scholar 

  4. Nishi A, Milner DA Jr, Giovannucci EL et al (2016) Integration of molecular pathology, epidemiology and social science for global precision medicine. Expert Rev Mol Diagn 16:11–23

    Article  CAS  PubMed  Google Scholar 

  5. Ogino S, Chan AT, Fuchs CS, Giovannucci E (2011) Molecular pathological epidemiology of colorectal neoplasia: an emerging transdisciplinary and interdisciplinary field. Gut 60:397–411

    Article  PubMed  Google Scholar 

  6. Ogino S, Nishihara R, VanderWeele TJ et al (2016) Review article: the role of molecular pathological epidemiology in the study of neoplastic and non-neoplastic diseases in the era of precision medicine. Epidemiology 27:602–611

    Article  PubMed  Google Scholar 

  7. Curtin K, Slattery ML, Samowitz WS. (2011) CpG island methylation in colorectal cancer: past, present and future. Pathol Res Int, pp 902674.

  8. Bishehsari F, Mahdavinia M, Vacca M, Malekzadeh R, Mariani-Costantini R (2014) Epidemiological transition of colorectal cancer in developing countries: environmental factors, molecular pathways, and opportunities for prevention. World J Gastroenterol 20:6055–6072

    Article  PubMed  PubMed Central  Google Scholar 

  9. Jiang MJ, Dai JJ, Gu DN, Huang Q, Tian L (2016) Aspirin in pancreatic cancer: chemopreventive effects and therapeutic potentials. Biochim Biophys Acta 1866:163–176

    CAS  PubMed  Google Scholar 

  10. Kuipers EJ, Grady WM, Lieberman D, et al. (2015) Colorectal cancer. Nat Rev Dis Primers. 1:15065.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Martinez-Useros J, Garcia-Foncillas J (2016) Obesity and colorectal cancer: molecular features of adipose tissue. J Transl Med 14:21

    Article  PubMed  PubMed Central  Google Scholar 

  12. Kuroiwa-Trzmielina J, Wang F, Rapkins RW et al (2016) SNP rs16906252C>T is an expression and methylation quantitative trait locus associated with an increased risk of developing MGMT-methylated colorectal cancer. Clin Cancer Res 22:6266–6277

    Article  CAS  PubMed  Google Scholar 

  13. Chia WK, Ali R, Toh HC (2012) Aspirin as adjuvant therapy for colorectal cancer–reinterpreting paradigms. Nat Rev Clin Oncol 9:561–570

    Article  CAS  PubMed  Google Scholar 

  14. Hughes LA, Khalid-de Bakker CA, Smits KM, et al. (2012) The CpG island methylator phenotype in colorectal cancer: progress and problems. Biochim Biophys Acta. 1825: 77–85.

    CAS  PubMed  Google Scholar 

  15. Buchanan DD, Win AK, Walsh MD et al (2013) Family history of colorectal cancer in BRAF p.V600E-mutated colorectal cancer cases. Cancer Epidemiol Biomarkers Prev 22:917–926

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Figueiredo JC, Lewinger JP, Song C et al (2011) Genotype-environment interactions in microsatellite stable/microsatellite instability-low colorectal cancer: results from a genome-wide association study. Cancer Epidemiol Biomark Prev 20:758–766

    Article  Google Scholar 

  17. Lee PN, Forey BA, Coombs KJ (2012) Systematic review with meta-analysis of the epidemiological evidence in the 1900s relating smoking to lung cancer. BMC Cancer 12:385

    Article  PubMed  PubMed Central  Google Scholar 

  18. Botteri E, Iodice S, Bagnardi V, Raimondi S, Lowenfels AB, Maisonneuve P (2008) Smoking and colorectal cancer: a meta-analysis. JAMA 300:2765–2778

    Article  CAS  PubMed  Google Scholar 

  19. Secretan B, Straif K, Baan R et al (2009) A review of human carcinogens–Part E: tobacco, areca nut, alcohol, coal smoke, and salted fish. Lancet Oncol 10:1033–1034

    Article  PubMed  Google Scholar 

  20. Jass JR (2007) Classification of colorectal cancer based on correlation of clinical, morphological and molecular features. Histopathology 50:113–130

    Article  CAS  PubMed  Google Scholar 

  21. Poynter JN, Haile RW, Siegmund KD et al (2009) Associations between smoking, alcohol consumption, and colorectal cancer, overall and by tumor microsatellite instability status. Cancer Epidemiol Biomark Prev 18:2745–2750

    Article  CAS  Google Scholar 

  22. Slattery ML, Curtin K, Anderson K et al (2000) Associations between cigarette smoking, lifestyle factors, and microsatellite instability in colon tumors. J Natl Cancer Inst 92:1831–1836

    Article  CAS  PubMed  Google Scholar 

  23. Limsui D, Vierkant RA, Tillmans LS et al (2010) Cigarette smoking and colorectal cancer risk by molecularly defined subtypes. J Natl Cancer Inst 102:1012–1022

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Nishihara R, Morikawa T, Kuchiba A et al (2013) A prospective study of duration of smoking cessation and colorectal cancer risk by epigenetics-related tumor classification. Am J Epidemiol 178:84–100

    Article  PubMed  PubMed Central  Google Scholar 

  25. Ogino S, Campbell PT, Nishihara R et al (2015) Proceedings of the second international molecular pathological epidemiology (MPE) meeting. Cancer Causes Control 26:959–972

    Article  PubMed  PubMed Central  Google Scholar 

  26. Curtin K, Samowitz WS, Ulrich CM et al (2011) Nutrients in folate-mediated, one-carbon metabolism and the risk of rectal tumors in men and women. Nutr Cancer 63:357–366

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. The Cancer Genome Atlas Network (2012) Comprehensive molecular characterization of human colon and rectal cancer. Nature 487:330–337

    Article  PubMed Central  Google Scholar 

  28. Giannakis M, Hodis E, Jasmine Mu X et al (2014) RNF43 is frequently mutated in colorectal and endometrial cancers. Nat Genet 46:1264–1266

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Giannakis M, Mu XJ, Shukla SA et al (2016) Genomic correlates of immune-cell infiltrates in colorectal carcinoma. Cell Rep 15:857–865

    Article  CAS  PubMed Central  Google Scholar 

  30. Howie B, Sherwood AM, Berkebile AD et al (2015) High-throughput pairing of T cell receptor alpha and beta sequences. Sci Transl Med 7:301ra131

    Article  PubMed  Google Scholar 

  31. Masugi Y, Nishihara R, Yang J et al (2016) Tumour CD274 (PD-L1) expression and T cells in colorectal cancer. Gut (in press)

  32. Mima K, Nishihara R, Nowak JA et al (2016) MicroRNA MIR21 and T Cells in Colorectal Cancer. Cancer. Immunol Res 4:33–40

    CAS  Google Scholar 

  33. Mima K, Sukawa Y, Nishihara R et al (2015) Fusobacterium nucleatum and T Cells in Colorectal Carcinoma. JAMA Oncol 1:653–661

    Google Scholar 

  34. Ogino S, Galon J, Fuchs CS, Dranoff G (2011) Cancer immunology–analysis of host and tumor factors for personalized medicine. Nat Rev Clin Oncol 8:711–719

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Song M, Nishihara R, Wang M et al (2016) Plasma 25-hydroxyvitamin D and colorectal cancer risk according to tumour immunity status. Gut 65:296–304

    Article  CAS  PubMed  Google Scholar 

  36. Hanyuda A, Ogino S, Qian ZR et al (2016) Body mass index and risk of colorectal cancer according to tumor lymphocytic infiltrate. Int J Cancer 139:854–868

    Article  CAS  PubMed  Google Scholar 

  37. Song M, Nishihara R, Cao Y et al (2016) Marine omega-3 polyunsaturated fatty acid intake and risk of colorectal cancer characterized by tumor-infiltrating T cells. JAMA Oncol 2:1197–1206

    Article  PubMed  Google Scholar 

  38. Tan DS, Mok TS, Rebbeck TR (2016) Cancer Genomics: Diversity and Disparity Across Ethnicity and Geography. J Clin Oncol 34:91–101

    Article  CAS  PubMed  Google Scholar 

  39. Almendro V, Cheng YK, Randles A, et al. (2014) Inference of tumor evolution during chemotherapy by computational modeling and in situ analysis of genetic and phenotypic cellular diversity. Cell Rep 6:514–527.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Almendro V, Kim HJ, Cheng YK et al (2014) Genetic and phenotypic diversity in breast tumor metastases. Cancer Res 74:1338–1348

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Janiszewska M, Liu L, Almendro V et al (2015) In situ single-cell analysis identifies heterogeneity for PIK3CA mutation and HER2 amplification in HER2-positive breast cancer. Nat Genet 47:1212–1219

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Bogdanov AA Jr, Dixon AJ, Gupta S et al (2016) Synthesis and testing of modular dual-modality nanoparticles for magnetic resonance and multispectral photoacoustic imaging. Bioconjug Chem 27:383–390

    Article  CAS  PubMed  Google Scholar 

  43. Begg CB, Orlow I, Zabor EC, et al. (2015) Identifying etiologically distinct sub-types of cancer: a demonstration project involving breast cancer. Cancer Med 4:1432–1439.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. VanderWeele TJ, Robins JM (2007) The identification of synergism in the sufficient-component-cause framework. Epidemiology 18:329–339

    Article  PubMed  Google Scholar 

  45. VanderWeele TJ (2009) Sufficient cause interactions and statistical interactions. Epidemiology 20:6–13

    Article  PubMed  Google Scholar 

  46. Vanderweele TJ (2010) Sufficient cause interactions for categorical and ordinal exposures with three levels. Biometrika 97:647–659

    Article  PubMed  PubMed Central  Google Scholar 

  47. Glass K, Quackenbush J, Spentzos D, Haibe-Kains B, Yuan GC (2015) A network model for angiogenesis in ovarian cancer. BMC Bioinform 16:115

    Article  Google Scholar 

  48. Jaffe AE, Irizarry RA (2014) Accounting for cellular heterogeneity is critical in epigenome-wide association studies. Genome Biol 15:R31

    Article  PubMed  PubMed Central  Google Scholar 

  49. Huttenhower C, Knight R, Brown CT et al (2014) Advancing the microbiome research community. Cell 159:227–230

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Dubin N, Pasternack BS (1986) Risk assessment for case-control subgroups by polychotomous logistic regression. Am J Epidemiol 123:1101–1117

    CAS  PubMed  Google Scholar 

  51. Begg CB, Zabor EC, Bernstein JL, Bernstein L, Press MF, Seshan VE (2013) A conceptual and methodological framework for investigating etiologic heterogeneity. Stat Med 32:5039–5052

    Article  PubMed  PubMed Central  Google Scholar 

  52. Chatterjee N, Sinha S, Diver WR, Feigelson HS (2010) Analysis of cohort studies with multivariate and partially observed disease classification data. Biometrika 97:683–698

    Article  PubMed  PubMed Central  Google Scholar 

  53. Wang M, Kuchiba A, Ogino S (2015) A meta-regression method for studying etiological heterogeneity across disease subtypes classified by multiple biomarkers. Am J Epidemiol 182:263–270

    Article  PubMed  PubMed Central  Google Scholar 

  54. Rosner B, Glynn RJ, Tamimi RM et al (2013) Breast cancer risk prediction with heterogeneous risk profiles according to breast cancer tumor markers. Am J Epidemiol 178:296–308

    Article  PubMed  PubMed Central  Google Scholar 

  55. Schildkraut JM, Iversen ES, Akushevich L et al (2013) Molecular signatures of epithelial ovarian cancer: analysis of associations with tumor characteristics and epidemiologic risk factors. Cancer Epidemiol Biomark Prev 22:1709–1721

    Article  Google Scholar 

  56. Nevo D, Zucker DM, Tamimi RM, Wang M (2016) Accounting for measurement error in biomarker data and misclassification of subtypes in the analysis of tumor data. Stat Med 35:5686–5700

    Article  PubMed  Google Scholar 

  57. Wang M, Spiegelman D, Kuchiba A et al (2016) Statistical methods for studying disease subtype heterogeneity. Stat Med 35:782–800

    Article  PubMed  Google Scholar 

  58. The Cancer Genome Atlas Network (2012) Comprehensive molecular portraits of human breast tumours. Nature 490:61–70

    Article  PubMed Central  Google Scholar 

  59. Dorman SN, Baranova K, Knoll JH et al (2016) Genomic signatures for paclitaxel and gemcitabine resistance in breast cancer derived by machine learning. Mol Oncol 10:85–100

    Article  CAS  PubMed  Google Scholar 

  60. Chan AT, Ogino S, Fuchs CS (2009) Aspirin use and survival after diagnosis of colorectal cancer. JAMA 302:649–658

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Reimers MS, Bastiaannet E, Langley RE, et al. (2014) Expression of HLA class I antigen, aspirin use, and survival after a diagnosis of colon cancer. JAMA Intern Med 174:732–739.

    Article  PubMed  Google Scholar 

  62. Domingo E, Church DN, Sieber O et al (2013) Evaluation of PIK3CA mutation as a predictor of benefit from nonsteroidal anti-inflammatory drug therapy in colorectal cancer. J Clin Oncol 31:4297–4305

    Article  CAS  PubMed  Google Scholar 

  63. Cao Y, Nishihara R, Qian ZR et al (2016) Regular aspirin use associates with lower risk of colorectal cancers with low numbers of tumor-infiltrating lymphocytes. Gastroenterology 151:879–892

    Article  CAS  PubMed  Google Scholar 

  64. Campbell PT, Deka A, Briggs P et al (2014) Establishment of the cancer prevention study II nutrition cohort colorectal tissue repository. Cancer Epidemiol Biomark Prev 23:2694–2702

    Article  CAS  Google Scholar 

  65. Campbell PT, Jacobs ET, Ulrich CM et al (2010) Case-control study of overweight, obesity, and colorectal cancer risk, overall and by tumor microsatellite instability status. J Natl Cancer Inst 102:391–400

    Article  PubMed  PubMed Central  Google Scholar 

  66. Campbell PT, Newton CC, Newcomb PA et al (2015) Association between body mass index and mortality for colorectal cancer survivors: overall and by tumor molecular phenotype. Cancer Epidemiol Biomark Prev 24:1229–1238

    Article  CAS  Google Scholar 

  67. Newcomb PA, Baron J, Cotterchio M et al (2007) Colon Cancer Family Registry: an international resource for studies of the genetic epidemiology of colon cancer. Cancer Epidemiol Biomark Prev 16:2331–2343

    Article  Google Scholar 

  68. Phipps AI, Ahnen DJ, Campbell PT et al (2014) Family history of colorectal cancer is not associated with colorectal cancer survival regardless of microsatellite instability status. Cancer Epidemiol Biomark Prev 23:1700–1704

    Article  Google Scholar 

Download references

Acknowledgments

Grant support: NIH R13 CA203287 (to S.O.: supported by the National Cancer Institute, National Human Genome Research Institute, and National Institute of Environmental Health Sciences). R35 CA197735 (to S.O.). P30 CA006516 (Dana–Farber Harvard Cancer Center Support Grant; to E.J. Benz;). Nodal Award (to S.O.) from Dana–Farber Harvard Cancer Center.

Author information

Authors and Affiliations

  1. Epidemiology Research Program, American Cancer Society, 250 Williams Street NW, Atlanta, GA, 30303, USA

    Peter T. Campbell

  2. Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA

    Timothy R. Rebbeck, Daniel Nevo, Elizabeth M. Poole, Stephanie A. Smith-Warner, Tyler J. VanderWeele, Molin Wang & Shuji Ogino

  3. Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA

    Timothy R. Rebbeck, Reiko Nishihara, Gordon J. Freeman, Zhi Rong Qian & Shuji Ogino

  4. Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA

    Reiko Nishihara, Yin Cao, Stephanie A. Smith-Warner & Mingyang Song

  5. Cancer Research Institute, Beth Israel Deaconess Cancer Center, Boston, MA, USA

    Andrew H. Beck & Yujing J. Heng

  6. Department of Pathology, Harvard Medical School, Beth Israel Deaconess Medical Center, Boston, MA, USA

    Andrew H. Beck & Yujing J. Heng

  7. Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA

    Colin B. Begg & Emily C. Zabor

  8. Department of Radiology, University of Massachusetts Medical School, Worcester, MA, USA

    Alexei A. Bogdanov

  9. Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA

    Yin Cao & Mingyang Song

  10. Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA

    Yin Cao

  11. Epidemiology and Health Services Research Group, Centre for Public Health, Queens University Belfast, Belfast, Northern Ireland

    Helen G. Coleman

  12. Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA

    Curtis Huttenhower, Rafael A. Irizarry, Franziska Michor, Daniel Nevo & John Quackenbush

  13. Microbial Systems and Communities, Genome Sequencing and Analysis Program, The Broad Institute, Cambridge, MA, USA

    Curtis Huttenhower

  14. Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA, USA

    Rafael A. Irizarry, Franziska Michor & John Quackenbush

  15. Laboratory Medicine and Pathology, Geisinger Health System, Danville, PA, USA

    N. Sertac Kip

  16. Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA

    Ulrike Peters, Amanda I. Phipps & Harlan Robins

  17. Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA, USA

    Ulrike Peters & Amanda I. Phipps

  18. Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA

    Elizabeth M. Poole & Xuehong Zhang

  19. Department of Biochemistry, University of Western Ontario, London, Canada

    Peter K. Rogan

  20. University of Utah School of Medicine, Salt Lake City, UT, USA

    Martha L. Slattery

  21. Department of Pathology, Brigham and Women’s Hospital, Boston, MA, USA

    Daniel Xia

  22. Division of MPE Molecular Pathological Epidemiology, Department of Pathology, Brigham and Women’s Hospital and Harvard Medical School, 450 Brookline Ave, Room SM1036, Boston, MA, 02215, USA

    Shuji Ogino

  23. Department of Oncologic Pathology, Dana-Farber Cancer Institute, Boston, MA, USA

    Shuji Ogino

Authors
  1. Peter T. Campbell
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Timothy R. Rebbeck
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Reiko Nishihara
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Andrew H. Beck
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Colin B. Begg
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Alexei A. Bogdanov
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Yin Cao
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Helen G. Coleman
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Gordon J. Freeman
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Yujing J. Heng
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Curtis Huttenhower
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Rafael A. Irizarry
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. N. Sertac Kip
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Franziska Michor
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. Daniel Nevo
    View author publications

    You can also search for this author in PubMed Google Scholar

  16. Ulrike Peters
    View author publications

    You can also search for this author in PubMed Google Scholar

  17. Amanda I. Phipps
    View author publications

    You can also search for this author in PubMed Google Scholar

  18. Elizabeth M. Poole
    View author publications

    You can also search for this author in PubMed Google Scholar

  19. Zhi Rong Qian
    View author publications

    You can also search for this author in PubMed Google Scholar

  20. John Quackenbush
    View author publications

    You can also search for this author in PubMed Google Scholar

  21. Harlan Robins
    View author publications

    You can also search for this author in PubMed Google Scholar

  22. Peter K. Rogan
    View author publications

    You can also search for this author in PubMed Google Scholar

  23. Martha L. Slattery
    View author publications

    You can also search for this author in PubMed Google Scholar

  24. Stephanie A. Smith-Warner
    View author publications

    You can also search for this author in PubMed Google Scholar

  25. Mingyang Song
    View author publications

    You can also search for this author in PubMed Google Scholar

  26. Tyler J. VanderWeele
    View author publications

    You can also search for this author in PubMed Google Scholar

  27. Daniel Xia
    View author publications

    You can also search for this author in PubMed Google Scholar

  28. Emily C. Zabor
    View author publications

    You can also search for this author in PubMed Google Scholar

  29. Xuehong Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  30. Molin Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  31. Shuji Ogino
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to Peter T. Campbell or Shuji Ogino.

Additional information

P. T. Campbell and S. Ogino contributed equally to this work.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Campbell, P.T., Rebbeck, T.R., Nishihara, R. et al. Proceedings of the third international molecular pathological epidemiology (MPE) meeting. Cancer Causes Control 28, 167–176 (2017). https://doi.org/10.1007/s10552-016-0845-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10552-016-0845-z

Keywords

Search

Navigation