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Annual Review of Pathology: Mechanisms of Disease

Volume 14, 2019

Insights into Pathogenic Interactions Among Environment, Host, and Tumor at the Crossroads of Molecular Pathology and Epidemiology

Abstract

Evidence indicates that diet, nutrition, lifestyle, the environment, the microbiome, and other exogenous factors have pathogenic roles and also influence the genome, epigenome, transcriptome, proteome, and metabolome of tumor and nonneoplastic cells, including immune cells. With the need for big-data research, pathology must transform to integrate data science fields, including epidemiology, biostatistics, and bioinformatics. The research framework of molecular pathological epidemiology (MPE) demonstrates the strengths of such an interdisciplinary integration, having been used to study breast, lung, prostate, and colorectal cancers. The MPE research paradigm not only can provide novel insights into interactions among environment, tumor, and host but also opens new research frontiers. New developments—such as computational digital pathology, systems biology, artificial intelligence, and in vivo pathology technologies—will further transform pathology and MPE. Although it is necessary to address the rarity of transdisciplinary education and training programs, MPE provides an exemplary model of integrative scientific approaches and contributes to advancements in precision medicine, therapy, and prevention.

Keyword(s): causal inference, exposome, genomics, immunity, public health, translational research
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/content/journals/10.1146/annurev-pathmechdis-012418-012818
2019-01-24
2024-04-23
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Literature Cited

  1. 1.  Jaffee EM, Dang CV, Agus DB, Alexander BM, Anderson KC et al. 2017. Future cancer research priorities in the USA: a Lancet Oncology Commission. Lancet Oncol 18:e653–706
     [Google Scholar]
  2. 2.  Meyskens FL Jr., Mukhtar H, Rock CL, Cuzick J, Kensler TW et al. 2016. Cancer prevention: obstacles, challenges and the road ahead. J. Natl. Cancer Inst. 108:djv309
     [Google Scholar]
  3. 3.  Kensler TW, Spira A, Garber JE, Szabo E, Lee JJ et al. 2016. Transforming cancer prevention through precision medicine and immune-oncology. Cancer Prev. Res. 9:2–10
     [Google Scholar]
  4. 4.  Spira A, Yurgelun MB, Alexandrov L, Rao A, Bejar R et al. 2017. Precancer Atlas to drive precision prevention trials. Cancer Res 77:1510–41
     [Google Scholar]
  5. 5.  Ogino S, Stampfer M 2010. Lifestyle factors and microsatellite instability in colorectal cancer: the evolving field of molecular pathological epidemiology. J. Natl. Cancer Inst. 102:365–67
     [Google Scholar]
  6. 6.  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
     [Google Scholar]
  7. 7.  Liu L, Nevo D, Nishihara R, Cao Y, Song M et al. 2018. Utility of inverse probability weighting in molecular pathological epidemiology. Eur. J. Epidemiol. 33:381–92
     [Google Scholar]
  8. 8.  Colussi D, Brandi G, Bazzoli F, Ricciardiello L 2013. Molecular pathways involved in colorectal cancer: implications for disease behavior and prevention. Int. J. Mol. Sci. 14:16365–85
     [Google Scholar]
  9. 9.  Dienstmann R, Vermeulen L, Guinney J, Kopetz S, Tejpar S, Tabernero J 2017. Consensus molecular subtypes and the evolution of precision medicine in colorectal cancer. Nat. Rev. Cancer 17:79–92
     [Google Scholar]
  10. 10.  Nishihara R, VanderWeele TJ, Shibuya K, Mittleman MA, Wang M et al. 2015. Molecular pathological epidemiology gives clues to paradoxical findings. Eur. J. Epidemiol. 30:1129–35
     [Google Scholar]
  11. 11.  Ogino S, Nishihara R, VanderWeele TJ, Wang M, Nishi A et al. 2016. The role of molecular pathological epidemiology in the study of neoplastic and non-neoplastic diseases in the era of precision medicine. Epidemiology 27:602–11
     [Google Scholar]
  12. 12.  Lochhead P, Chan AT, Giovannucci E, Fuchs CS, Wu K et al. 2014. Progress and opportunities in molecular pathological epidemiology of colorectal premalignant lesions. Am. J. Gastroenterol. 109:1205–14
     [Google Scholar]
  13. 13.  Lochhead P, Chan AT, Nishihara R, Fuchs CS, Beck AH et al. 2015. Etiologic field effect: reappraisal of the field effect concept in cancer predisposition and progression. Mod. Pathol. 28:14–29
     [Google Scholar]
  14. 14.  Begg CB, Orlow I, Zabor EC, Arora A, Sharma A et al. 2015. Identifying etiologically distinct sub-types of cancer: a demonstration project involving breast cancer. Cancer Med 4:1432–39
     [Google Scholar]
  15. 15.  Wang M, Spiegelman D, Kuchiba A, Lochhead P, Kim S et al. 2016. Statistical methods for studying disease subtype heterogeneity. Stat. Med. 35:782–800
     [Google Scholar]
  16. 16.  Wang M, Kuchiba A, Ogino S 2015. A meta-regression method for studying etiologic heterogeneity across disease subtypes classified by multiple biomarkers. Am. J. Epidemiol. 182:263–70
     [Google Scholar]
  17. 17.  Richiardi L, Barone-Adesi F, Pearce N 2017. Cancer subtypes in aetiological research. Eur. J. Epidemiol. 32:353–61
     [Google Scholar]
  18. 18.  Nevo D, Nishihara R, Ogino S, Wang M 2018. The competing risks Cox model with auxiliary case covariates under weaker missing-at-random cause of failure. Lifetime Data Anal 24:425–42
     [Google Scholar]
  19. 19.  Greene JA, Loscalzo J 2017. Putting the patient back together—social medicine, network medicine, and the limits of reductionism. N. Engl. J. Med. 377:2493–99
     [Google Scholar]
  20. 20.  Nishihara R, Glass K, Mima K, Hamada T, Nowak JA et al. 2017. Biomarker correlation network in colorectal carcinoma by tumor anatomic location. BMC Bioinform 18:304
     [Google Scholar]
  21. 21.  Ogino S, King EE, Beck AH, Sherman ME, Milner DA, Giovannucci E 2012. Interdisciplinary education to integrate pathology and epidemiology: towards molecular and population-level health science. Am. J. Epidemiol. 176:659–67
     [Google Scholar]
  22. 22.  Ogino S, Lochhead P, Giovannucci E, Meyerhardt JA, Fuchs CS, Chan AT 2014. Discovery of colorectal cancer PIK3CA mutation as potential predictive biomarker: power and promise of molecular pathological epidemiology. Oncogene 33:2949–55
     [Google Scholar]
  23. 23.  Ogino S 2013. Molecular pathological epidemiology (MPE): overview of its paradigm and wide applicability even without tumor tissue. Cancer Prev. Res. 6:Suppl. CN06-01 (Abstr.)
    [Google Scholar]
  24. 24.  Kuller LH, Bracken MB, Ogino S, Prentice RL, Tracy RP 2013. The role of epidemiology in the era of molecular epidemiology and genomics: summary of the 2013 AJE-sponsored Society of Epidemiologic Research Symposium. Am. J. Epidemiol. 178:1350–54
     [Google Scholar]
  25. 25.  Epplein M, Bostick RM, Mu L, Ogino S, Braithwaite D, Kanetsky PA 2014. Challenges and opportunities in international molecular cancer prevention research: an ASPO Molecular Epidemiology and the Environment and International Cancer Prevention Interest Groups report. Cancer Epidemiol. Biomark. Prev. 23:2613–17
     [Google Scholar]
  26. 26.  Ogino S, Campbell PT, Nishihara R, Phipps AI, Beck AH et al. 2015. Proceedings of the Second International Molecular Pathological Epidemiology (MPE) Meeting. Cancer Causes Control 26:959–72
     [Google Scholar]
  27. 27.  Campbell PT, Rebbeck TR, Nishihara R, Beck AH, Begg CB et al. 2017. Proceedings of the Third International Molecular Pathological Epidemiology (MPE) Meeting. Cancer Causes Control 28:167–76
     [Google Scholar]
  28. 28.  Rescigno T, Micolucci L, Tecce MF, Capasso A 2017. Bioactive nutrients and nutrigenomics in age-related diseases. Molecules 22:105
     [Google Scholar]
  29. 29.  Curtin K, Slattery ML, Samowitz WS 2011. CpG island methylation in colorectal cancer: past, present and future. Pathol. Res. Int. 2011:902674
     [Google Scholar]
  30. 30.  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. 20:6055–72
     [Google Scholar]
  31. 31.  Jiang M, Dai J, Gu D, Huang Q, Tian L 2017. Aspirin in pancreatic cancer: chemopreventive effects and therapeutic potentials. Biochim. Biophys. Acta 1866:163–76
     [Google Scholar]
  32. 32.  Martinez-Useros J, Garcia-Foncillas J 2016. Obesity and colorectal cancer: molecular features of adipose tissue. J. Transl. Med. 14:21
     [Google Scholar]
  33. 33.  Chia WK, Ali R, Toh HC 2012. Aspirin as adjuvant therapy for colorectal cancer—reinterpreting paradigms. Nat. Rev. Clin. Oncol. 9:561–70
     [Google Scholar]
  34. 34.  Campbell PT, Newton CC, Newcomb PA, Phipps AI, Ahnen DJ et al. 2015. Association between body mass index and mortality for colorectal cancer survivors: overall and by tumor molecular phenotype. Cancer Epidemiol. Biomark. Prev. 24:1229–38
     [Google Scholar]
  35. 35.  Serafino A, Sferrazza G, Colini Baldeschi A, Nicotera G, Andreola F et al. 2017. Developing drugs that target the Wnt pathway: recent approaches in cancer and neurodegenerative diseases. Expert Opin. Drug Discov. 12:169–86
     [Google Scholar]
  36. 36.  Patil H, Saxena SG, Barrow CJ, Kanwar JR, Kapat A, Kanwar RK 2017. Chasing the personalized medicine dream through biomarker validation in colorectal cancer. Drug Discov. Today 22:111–19
     [Google Scholar]
  37. 37.  Kuroiwa-Trzmielina J, Wang F, Rapkins RW, Ward RL, Buchanan DD 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. 22:6266–77
     [Google Scholar]
  38. 38.  Slattery ML, Lee FY, Pellatt AJ, Mullany LE, Stevens JR et al. 2017. Infrequently expressed miRNAs in colorectal cancer tissue and tumor molecular phenotype. Mod. Pathol. 30:1152–69
     [Google Scholar]
  39. 39.  Hughes LA, Simons CC, van den Brandt PA, van Engeland M, Weijenberg MP 2017. Lifestyle, diet, and colorectal cancer risk according to (epi)genetic instability: current evidence and future direction of molecular pathological epidemiology. Curr. Colorectal Cancer Rep. 13:455–69
     [Google Scholar]
  40. 40.  Coleman HG, Xie SH, Lagergren J 2018. The epidemiology of esophageal adenocarcinoma. Gastroenterology 154:390–405
     [Google Scholar]
  41. 41.  Carr PR, Alwers E, Bienert S, Weberpals J, Kloor M et al. 2018. Lifestyle factors and risk of sporadic colorectal cancer by microsatellite instability status: a systematic review and meta-analysis. Ann. Oncol. 29:825–34
     [Google Scholar]
  42. 42.  Galipeau PC, Oman KM, Paulson TG, Sanchez CA, Zhang Q et al. 2018. NSAID use and somatic exomic mutations in Barrett's esophagus. Genome Med 10:17
     [Google Scholar]
  43. 43.  Rajpoot M, Sharma AK, Sharma A, Gupta GK 2018. Understanding the microbiome: emerging biomarkers for exploiting the microbiota for personalized medicine against cancer. Semin. Cancer Biol. 52:Part 11–8
     [Google Scholar]
  44. 44.  Field AE, Camargo CA, Ogino S 2013. The merits of subtyping obesity: One size does not fit all. JAMA 310:2147–48
     [Google Scholar]
  45. 45.  Ogino S, Lochhead P, Chan AT, Nishihara R, Cho E et al. 2013. Molecular pathological epidemiology of epigenetics: emerging integrative science to analyze environment, host, and disease. Mod. . Pathol 26:465–84
     [Google Scholar]
  46. 46.  Ogino S, Fuchs CS, Giovannucci E 2012. How many molecular subtypes? Implications of the unique tumor principle in personalized medicine. Expert Rev. Mol. Diagn. 12:621–28
     [Google Scholar]
  47. 47.  Ogino S, Galon J, Fuchs CS, Dranoff G 2011. Cancer immunology—analysis of host and tumor factors for personalized medicine. Nat. Rev. Clin. Oncol. 8:711–19
     [Google Scholar]
  48. 48.  Cramer DW, Finn OJ 2011. Epidemiologic perspective on immune-surveillance in cancer. Curr. Opin. Immunol. 23:265–71
     [Google Scholar]
  49. 49.  Ogino S, Jhun I, Mata DA, Soong TR, Hamada T et al. 2017. Integration of pharmacology, molecular pathology, and population data science to support precision gastrointestinal oncology. NPJ Precis. Oncol. 1:40
     [Google Scholar]
  50. 50.  Drew DA, Cao Y, Chan AT 2016. Aspirin and colorectal cancer: the promise of precision chemoprevention. Nat. Rev. Cancer 16:173–86
     [Google Scholar]
  51. 51.  Benelli R, Vene R, Ferrari N 2018. Prostaglandin-endoperoxide synthase 2 (cyclooxygenase-2), a complex target for colorectal cancer prevention and therapy. Transl. Res. 196:42–61
     [Google Scholar]
  52. 52.  Chan AT, Ogino S, Fuchs CS 2007. Aspirin and the risk of colorectal cancer in relation to the expression of COX-2. N. Engl. J. Med. 356:2131–42
     [Google Scholar]
  53. 53.  Chan AT, Ogino S, Fuchs CS 2009. Aspirin use and survival after diagnosis of colorectal cancer. JAMA 302:649–58
     [Google Scholar]
  54. 54.  Gray RT, Cantwell MM, Coleman HG, Loughrey MB, Bankhead P et al. 2017. Evaluation of PTGS2 expression, PIK3CA mutation, aspirin use and colon cancer survival in a population-based cohort study. Clin. Transl. Gastroenterol. 8:e91
     [Google Scholar]
  55. 55.  Sepulveda AR, Hamilton SR, Allegra CJ, Grody W, Cushman-Vokoun AM et al. 2017. Molecular biomarkers for the evaluation of colorectal cancer: guideline from the American Society for Clinical Pathology, College of American Pathologists, Association for Molecular Pathology, and the American Society of Clinical Oncology. J. Clin. Oncol. 35:1453–86
     [Google Scholar]
  56. 56.  Inamura K 2018. Colorectal cancers: an update on their molecular pathology. Cancers 10:26
     [Google Scholar]
  57. 57.  Umar A, Steele VE, Menter D, Hawk ET 2016. Mechanisms of non-steroidal anti-inflammatory drugs (NSAIDs) in cancer prevention. Semin. Oncol. 43:67–77
     [Google Scholar]
  58. 58.  Greenhough A, Smartt HJ, Moore AE, Roberts HR, Williams AC et al. 2009. The COX-2/PGE2 pathway: key roles in the hallmarks of cancer and adaptation to the tumour microenvironment. Carcinogenesis 30:377–86
     [Google Scholar]
  59. 59.  Liao X, Lochhead P, Nishihara R, Morikawa T, Kuchiba A et al. 2012. Aspirin use, tumor PIK3CA mutation status, and colorectal cancer survival. N. Engl. J. Med. 367:1596–606
     [Google Scholar]
  60. 60.  Reimers MS, Bastiaannet E, Langley RE, van Eijk R, van Vlierberghe RL et al. 2014. Expression of HLA class I antigen, aspirin use, and survival after a diagnosis of colon cancer. JAMA Intern. Med. 174:732–39
     [Google Scholar]
  61. 61.  Domingo E, Church DN, Sieber O, Ramamoorthy R, Yanagisawa Y et al. 2013. Evaluation of PIK3CA mutation as a predictor of benefit from NSAID therapy in colorectal cancer. J. Clin. Oncol. 31:4297–305
     [Google Scholar]
  62. 62.  Kothari N, Kim R, Jorissen RN, Desai J, Tie J et al. 2015. Impact of regular aspirin use on overall and cancer-specific survival in patients with colorectal cancer harboring a PIK3CA mutation. Acta Oncol 54:487–92
     [Google Scholar]
  63. 63.  Paleari L, Puntoni M, Clavarezza M, DeCensi M, Cuzick J, DeCensi A 2016. PIK3CA mutation, aspirin use after diagnosis and survival of colorectal cancer: a systematic review and meta-analysis of epidemiological studies. Clin. Oncol. 28:317–26
     [Google Scholar]
  64. 64.  Murphy C, Turner N, Wong HL, Sinnathamby M, Tie J et al. 2017. Examining the impact of regular aspirin use and PIK3CA mutations on survival in stage 2 colon cancer. Intern. Med. J. 47:88–98
     [Google Scholar]
  65. 65.  Turturro SB, Najor MS, Ruby CE, Cobleigh MA, Abukhdeir AM 2016. Mutations in PIK3CA sensitize breast cancer cells to physiologic levels of aspirin. Breast Cancer Res. Treat. 156:33–43
     [Google Scholar]
  66. 66.  Zumwalt TJ, Wodarz D, Komarova NL, Toden S, Turner J et al. 2017. Aspirin-induced chemoprevention and response kinetics are enhanced by PIK3CA mutations in colorectal cancer cells. Cancer Prev. Res. 10:208–18
     [Google Scholar]
  67. 67.  Gu M, Nishihara R, Chen Y, Li W, Shi Y et al. 2017. Aspirin exerts high anti-cancer activity in PIK3CA-mutant colon cancer cells. Oncotarget 8:87379–89
     [Google Scholar]
  68. 68.  Reimers MS, Zeestraten EC, Kuppen PJ, Liefers GJ, van de Velde CJH 2013. Biomarkers in precision therapy in colorectal cancer. Gastroenterol. Rep. 1:166–83
     [Google Scholar]
  69. 69.  Michel P, Boige V, Andre T, Aparicio T, Bachet JB et al. 2018. Aspirin versus placebo in stage III or high-risk stage II colon cancer with PIK3CA mutation: a French randomised double-blind phase III trial (PRODIGE 50-ASPIK). Dig. Liver Dis. 50:305–7
     [Google Scholar]
  70. 70.  Zelenay S, van der Veen AG, Bottcher JP, Snelgrove KJ, Rogers N et al. 2015. Cyclooxygenase-dependent tumor growth through evasion of immunity. Cell 162:1257–70
     [Google Scholar]
  71. 71.  Wang D, DuBois RN 2016. The role of prostaglandin E2 in tumor-associated immunosuppression. Trends Mol. Med. 22:1–3
     [Google Scholar]
  72. 72.  Hamada T, Cao Y, Qian ZR, Masugi Y, Nowak JA et al. 2017. Aspirin use and colorectal cancer survival according to tumor CD274 (programmed cell death 1 ligand 1) expression status. J. Clin. Oncol. 35:1836–44
     [Google Scholar]
  73. 73.  Cao Y, Nishihara R, Wu K, Wang M, Ogino S et al. 2016. Population-wide impact of long-term use of aspirin and the risk for cancer. JAMA Oncol 2:762–69
     [Google Scholar]
  74. 74.  Nan H, Hutter CM, Lin Y, Jacobs EJ, Ulrich CM et al. 2015. Association of aspirin and NSAID use with risk of colorectal cancer according to genetic variants. JAMA 313:1133–42
     [Google Scholar]
  75. 75.  Nan H, Morikawa T, Suuriniemi M, Imamura Y, Werner L et al. 2013. Aspirin use, 8q24 single nucleotide polymorphism rs6983267, and colorectal cancer according to CTNNB1 alterations. J. Natl. Cancer Inst. 105:1852–61
     [Google Scholar]
  76. 76.  Myung SJ, Rerko RM, Yan M, Platzer P, Guda K et al. 2006. 15-Hydroxyprostaglandin dehydrogenase is an in vivo suppressor of colon tumorigenesis. PNAS 103:12098–102
     [Google Scholar]
  77. 77.  Fink SP, Yamauchi M, Nishihara R, Jung S, Kuchiba A et al. 2014. Aspirin and the risk of colorectal cancer in relation to the expression of 15-hydroxyprostaglandin dehydrogenase (HPGD). Sci. Transl. Med. 6:233re2
     [Google Scholar]
  78. 78.  Galon J, Mlecnik B, Bindea G, Angell HK, Berger A et al. 2014. Towards the introduction of the ‘Immunoscore’ in the classification of malignant tumors. J. Pathol. 232:199–209
     [Google Scholar]
  79. 79.  Basile D, Garattini SK, Bonotto M, Ongaro E, Casagrande M et al. 2017. Immunotherapy for colorectal cancer: Where are we heading?. Expert Opin. Biol. Ther. 17:709–21
     [Google Scholar]
  80. 80.  Grizzi F, Basso G, Borroni EM, Cavalleri T, Bianchi P et al. 2018. Evolving notions on immune response in colorectal cancer and their implications for biomarker development. Inflamm. Res. 67:375–89
     [Google Scholar]
  81. 81.  Ogino S, Nowak JA, Hamada T, Phipps AI, Peters U et al. 2018. Integrative analysis of exogenous, endogenous, tumour, and immune factors for precision medicine. Gut 67:1168–80
     [Google Scholar]
  82. 82.  Ogino S, Giannakis M 2018. Immunoscore for (colorectal) cancer precision medicine. Lancet 391:2084–86
     [Google Scholar]
  83. 83.  Fletcher R, Wang YJ, Schoen RE, Finn OJ, Yu J, Zhang L 2018. Colorectal cancer prevention: immune modulation taking the stage. Biochim. Biophys. Acta 1869:138–48
     [Google Scholar]
  84. 84.  Hanyuda A, Ogino S, Qian ZR, Nishihara R, Song M et al. 2016. Body mass index and risk of colorectal cancer according to tumor lymphocytic infiltrate. Int. J. Cancer 139:854–68
     [Google Scholar]
  85. 85.  Rozek LS, Schmit SL, Greenson JK, Tomsho LP, Rennert HS et al. 2016. Tumor-infiltrating lymphocytes, Crohn's-like lymphoid reaction, and survival from colorectal cancer. J. Natl. Cancer Inst. 108:djw027
     [Google Scholar]
  86. 86.  Giannakis M, Mu XJ, Shukla SA, Qian ZR, Cohen O et al. 2016. Genomic correlates of immune-cell infiltrates in colorectal carcinoma. Cell Rep 15:857–65
     [Google Scholar]
  87. 87.  Song M, Nishihara R, Cao Y, Chun E, Qian ZR et al. 2016. Marine ω-3 polyunsaturated fatty acid intake and risk of colorectal cancer characterized by tumor-infiltrating T cells. JAMA Oncol 2:1197–206
     [Google Scholar]
  88. 88.  Cao Y, Nishihara R, Qian ZR, Song M, Mima K et al. 2016. Regular aspirin use associates with lower risk of colorectal cancers with low numbers of tumor-infiltrating lymphocytes. Gastroenterology 151:879–92
     [Google Scholar]
  89. 89.  Prizment AE, Vierkant RA, Smyrk TC, Tillmans LS, Nelson HH et al. 2017. Cytotoxic T-cells and granzyme B associated with improved colorectal cancer survival in a prospective cohort of older women. Cancer Epidemiol. Biomark. Prev. 26:622–31
     [Google Scholar]
  90. 90.  Song M, Chan AT, Fuchs CS, Ogino S, Hu FB et al. 2014. Dietary intake of fish, ω-3 and ω-6 fatty acids and risk of colorectal cancer: a prospective study in U.S. men and women. Int. J. Cancer 135:2413–23
     [Google Scholar]
  91. 91.  Shen XJ, Zhou JD, Dong JY, Ding WQ, Wu JC 2012. Dietary intake of n-3 fatty acids and colorectal cancer risk: a meta-analysis of data from 489 000 individuals. Br. J. Nutr. 108:1550–56
     [Google Scholar]
  92. 92.  Calder PC 2015. Marine omega-3 fatty acids and inflammatory processes: effects, mechanisms and clinical relevance. Biochim. Biophys. Acta 1851:469–84
     [Google Scholar]
  93. 93.  Dou R, Ng K, Giovannucci EL, Manson JE, Qian ZR, Ogino S 2016. Vitamin D and colorectal cancer: molecular, epidemiological and clinical evidence. Br. J. Nutr. 115:1643–60
     [Google Scholar]
  94. 94.  Song M, Nishihara R, Wang M, Chan AT, Qian ZR et al. 2016. Plasma 25-hydroxyvitamin D and colorectal cancer risk according to tumour immunity status. Gut 65:296–304
     [Google Scholar]
  95. 95.  Sigmundsdottir H, Pan J, Debes GF, Alt C, Habtezion A et al. 2007. DCs metabolize sunlight-induced vitamin D3 to ‘program’ T cell attraction to the epidermal chemokine CCL27. Nat. Immunol. 8:285–93
     [Google Scholar]
  96. 96.  Edfeldt K, Liu PT, Chun R, Fabri M, Schenk M et al. 2010. T-cell cytokines differentially control human monocyte antimicrobial responses by regulating vitamin D metabolism. PNAS 107:22593–98
     [Google Scholar]
  97. 97.  Liu L, Nishihara R, Qian ZR, Tabung FK, Nevo D et al. 2017. Association between inflammatory diet pattern and risk of colorectal carcinoma subtypes classified by immune responses to tumor. Gastroenterology 153:1517–30
     [Google Scholar]
  98. 98.  Hamada T, Keum N, Nishihara R, Ogino S 2017. Molecular pathological epidemiology: new developing frontiers of big data science to study etiologies and pathogenesis. J. Gastroenterol. 52:265–75
     [Google Scholar]
  99. 99.  O'Keefe SJ, Li JV, Lahti L, Ou J, Carbonero F et al. 2015. Fat, fibre and cancer risk in African Americans and rural Africans. Nat. Commun. 6:6342
     [Google Scholar]
  100. 100.  O'Keefe SJ 2016. Diet, microorganisms and their metabolites, and colon cancer. Nat. Rev. Gastroenterol. Hepatol. 13:691–706
     [Google Scholar]
  101. 101.  Mima K, Ogino S, Nakagawa S, Sawayama H, Kinoshita K et al. 2017. The role of intestinal bacteria in the development and progression of gastrointestinal tract neoplasms. Surg. Oncol. 26:368–76
     [Google Scholar]
  102. 102.  Chen J, Domingue JC, Sears CL 2017. Microbiota dysbiosis in select human cancers: evidence of association and causality. Semin. Immunol. 32:25–34
     [Google Scholar]
  103. 103.  Zitvogel L, Pietrocola F, Kroemer G 2017. Nutrition, inflammation and cancer. Nat. Immunol. 18:843–50
     [Google Scholar]
  104. 104.  Drewes JL, Housseau F, Sears CL 2016. Sporadic colorectal cancer: microbial contributors to disease prevention, development and therapy. Br. J. Cancer 115:273–80
     [Google Scholar]
  105. 105.  Chen J, Pitmon E, Wang K 2017. Microbiome, inflammation and colorectal cancer. Semin. Immunol. 32:43–53
     [Google Scholar]
  106. 106.  Kostic AD, Gevers D, Pedamallu CS, Michaud M, Duke F et al. 2012. Genomic analysis identifies association of Fusobacterium with colorectal carcinoma. Genome Res 22:292–98
     [Google Scholar]
  107. 107.  Castellarin M, Warren RL, Freeman JD, Dreolini L, Krzywinski M et al. 2012. Fusobacterium nucleatum infection is prevalent in human colorectal carcinoma. Genome Res 22:299–306
     [Google Scholar]
  108. 108.  Rubinstein MR, Wang X, Liu W, Hao Y, Cai G, Han YW 2013. Fusobacterium nucleatum promotes colorectal carcinogenesis by modulating E-cadherin/β-catenin signaling via its FadA adhesin. Cell Host Microbe 14:195–206
     [Google Scholar]
  109. 109.  Kostic AD, Chun E, Robertson L, Glickman JN, Gallini CA et al. 2013. Fusobacterium nucleatum potentiates intestinal tumorigenesis and modulates the tumor–immune microenvironment. Cell Host Microbe 14:207–15
     [Google Scholar]
  110. 110.  Dejea CM, Wick EC, Hechenbleikner EM, White JR, Mark Welch JL et al. 2014. Microbiota organization is a distinct feature of proximal colorectal cancers. PNAS 111:18321–26
     [Google Scholar]
  111. 111.  Yang Y, Weng W, Peng J, Hong L, Yang L et al. 2017. Fusobacterium nucleatum increases proliferation of colorectal cancer cells and tumor development in mice by activating Toll-like receptor 4 signaling to nuclear factor-κB, and up-regulating expression of microRNA-21. Gastroenterology 152:851–66.e24
     [Google Scholar]
  112. 112.  Ye X, Wang R, Bhattacharya R, Boulbes D, Fan F et al. 2017. Fusobacterium nucleatum subspecies animalis influences pro-inflammatory cytokine expression and monocyte activation in human colorectal tumors. Cancer Prev. Res. 10:398–409
     [Google Scholar]
  113. 113.  Hussan H, Clinton SK, Roberts K, Bailey MT 2017. Fusobacterium’s link to colorectal neoplasia sequenced: a systematic review and future insights. World J. Gastroenterol. 23:8626–50
     [Google Scholar]
  114. 114.  Ito M, Kanno S, Nosho K, Sukawa Y, Mitsuhashi K et al. 2015. Association of Fusobacterium nucleatum with clinical and molecular features in colorectal serrated pathway. Int. J. Cancer 137:1258–68
     [Google Scholar]
  115. 115.  Park CH, Han DS, Oh YH, Lee AR, Lee YR, Eun CS 2016. Role of Fusobacteria in the serrated pathway of colorectal carcinogenesis. Sci. Rep. 6:25271
     [Google Scholar]
  116. 116.  Mima K, Cao Y, Chan AT, Qian ZR, Nowak JA et al. 2016. Fusobacterium nucleatum in colorectal carcinoma tissue according to tumor location. Clin. Transl. Gastroenterol. 7:e200
     [Google Scholar]
  117. 117.  Li YY, Ge QX, Cao J, Zhou YJ, Du YL et al. 2016. Association of Fusobacterium nucleatum infection with colorectal cancer in Chinese patients. World J. Gastroenterol. 22:3227–33
     [Google Scholar]
  118. 118.  Yamaoka Y, Suehiro Y, Hashimoto S, Hoshida T, Fujimoto M et al. 2018. Fusobacterium nucleatum as a prognostic marker of colorectal cancer in a Japanese population. J. Gastroenterol. 53:517–52
     [Google Scholar]
  119. 119.  Mima K, Nishihara R, Qian ZR, Cao Y, Sukawa Y et al. 2016. Fusobacterium nucleatum in colorectal carcinoma tissue and patient prognosis. Gut 65:1973–80
     [Google Scholar]
  120. 120.  Flanagan L, Schmid J, Ebert M, Soucek P, Kunicka T et al. 2014. Fusobacterium nucleatum associates with stages of colorectal neoplasia development, colorectal cancer and disease outcome. Eur. J. Clin. Microbiol. Infect. Dis. 33:1381–90
     [Google Scholar]
  121. 121.  Mima K, Sukawa Y, Nishihara R, Qian ZR, Yamauchi M et al. 2015. Fusobacterium nucleatum and T cells in colorectal carcinoma. JAMA Oncol 1:653–61
     [Google Scholar]
  122. 122.  Nosho K, Sukawa Y, Adachi Y, Ito M, Mitsuhashi K et al. 2016. Association of Fusobacterium nucleatum with immunity and molecular alterations in colorectal cancer. World J. Gastroenterol. 22:557–66
     [Google Scholar]
  123. 123.  Park HE, Kim JH, Cho NY, Lee HS, Kang GH 2017. Intratumoral Fusobacterium nucleatum abundance correlates with macrophage infiltration and CDKN2A methylation in microsatellite-unstable colorectal carcinoma. Virchows Arch 471:329–36
     [Google Scholar]
  124. 124.  Tahara T, Yamamoto E, Suzuki H, Maruyama R, Chung W et al. 2014. Fusobacterium in colonic flora and molecular features of colorectal carcinoma. Cancer Res 74:1311–18
     [Google Scholar]
  125. 125.  Yu T, Guo F, Yu Y, Sun T, Ma D et al. 2017. Fusobacterium nucleatum promotes chemoresistance to colorectal cancer by modulating autophagy. Cell 170:548–63.e16
     [Google Scholar]
  126. 126.  Johnson CH, Spilker ME, Goetz L, Peterson SN, Siuzdak G 2016. Metabolite and microbiome interplay in cancer immunotherapy. Cancer Res 76:6146–52
     [Google Scholar]
  127. 127.  Nagarsheth N, Wicha MS, Zou W 2017. Chemokines in the cancer microenvironment and their relevance in cancer immunotherapy. Nat. Rev. Immunol. 17:559–72
     [Google Scholar]
  128. 128.  Lin JH, Giovannucci E 2014. Environmental exposure and tumor heterogeneity in colorectal cancer risk and outcomes. Curr. Colorectal Cancer Rep. 10:94–104
     [Google Scholar]
  129. 129.  Marley AR, Nan H 2016. Epidemiology of colorectal cancer. Int. J. Mol. Epidemiol. Genet. 7:105–14
     [Google Scholar]
  130. 130.  Song M, Garrett WS, Chan AT 2015. Nutrients, foods, and colorectal cancer prevention. Gastroenterology 148:1244–60.e16
     [Google Scholar]
  131. 131.  Mehta RS, Nishihara R, Cao Y, Song M, Mima K et al. 2017. Association of dietary patterns with risk of colorectal cancer subtypes classified by Fusobacterium nucleatum in tumor tissue. JAMA Oncol 3:921–27
     [Google Scholar]
  132. 132.  Curtius K, Wright NA, Graham TA 2018. An evolutionary perspective on field cancerization. Nat. Rev. Cancer 18:19–32
     [Google Scholar]
  133. 133.  Ericsson AC, Akter S, Hanson MM, Busi SB, Parker TW et al. 2015. Differential susceptibility to colorectal cancer due to naturally occurring gut microbiota. Oncotarget 6:33689–704
     [Google Scholar]
  134. 134.  Gupta S, Sun H, Yi S, Storm J, Xiao G et al. 2014. Molecular markers of carcinogenesis for risk stratification of individuals with colorectal polyps: a case–control study. Cancer Prev. Res. 7:1023–34
     [Google Scholar]
  135. 135.  Roy HK, Turzhitsky V, Wali R, Radosevich AJ, Jovanovic B et al. 2017. Spectral biomarkers for chemoprevention of colonic neoplasia: a placebo-controlled double-blinded trial with aspirin. Gut 66:285–92
     [Google Scholar]
  136. 136.  Wennersten C, Andersson G, Boman K, Nodin B, Gaber A, Jirstrom K 2014. Incident urothelial cancer in the Malmö Diet and Cancer Study: cohort characteristics and further validation of ezrin as a prognostic biomarker. Diagn. Pathol. 9:189
     [Google Scholar]
  137. 137.  Yamauchi M, Lochhead P, Morikawa T, Huttenhower C, Chan AT et al. 2012. Colorectal cancer: a tale of two sides or a continuum?. Gut 61:794–97
     [Google Scholar]
  138. 138.  Yamauchi M, Morikawa T, Kuchiba A, Imamura Y, Qian ZR et al. 2012. Assessment of colorectal cancer molecular features along bowel subsites challenges the conception of distinct dichotomy of proximal versus distal colorectum. Gut 61:847–54
     [Google Scholar]
  139. 139.  Rosty C, Young JP, Walsh MD, Clendenning M, Sanderson K et al. 2013. PIK3CA activating mutation in colorectal carcinoma: associations with molecular features and survival. PLOS ONE 8:e65479
     [Google Scholar]
  140. 140.  Phipps AI, Buchanan DD, Makar KW, Burnett-Hartman AN, Coghill AE et al. 2012. BRAF mutation status and survival after colorectal cancer diagnosis according to patient and tumor characteristics. Cancer Epidemiol. Biomark. Prev. 21:1792–98
     [Google Scholar]
  141. 141.  Phipps AI, Chan AT, Ogino S 2013. Anatomic subsite of primary colorectal cancer and subsequent risk and distribution of second cancers. Cancer 119:3140–47
     [Google Scholar]
  142. 142.  Jess P, Hansen IO, Gamborg M, Jess T 2013. A nationwide Danish cohort study challenging the categorisation into right-sided and left-sided colon cancer. BMJ Open 3:e002608
     [Google Scholar]
  143. 143.  Loree JM, Pereira AA, Lam M, Willauer AN, Raghav K et al. 2018. Classifying colorectal cancer by tumor location rather than sidedness highlights a continuum in mutation profiles and consensus molecular subtypes. Clin. Cancer Res. 24:1062–72
     [Google Scholar]
  144. 144.  Ogino S, Nishihara R 2016. All biomedical and health science researchers, including laboratory physicians and scientists, need adequate education and training in study design and statistics. Clin. Chem. 62:1039–40
     [Google Scholar]
  145. 145.  Bromham L, Dinnage R, Hua X 2016. Interdisciplinary research has consistently lower funding success. Nature 534:684–87
     [Google Scholar]
  146. 146.  Nishi A, Kawachi I, Koenen KC, Wu K, Nishihara R, Ogino S 2015. Lifecourse epidemiology and molecular pathological epidemiology. Am. J. Prev. Med. 48:116–19
     [Google Scholar]
  147. 147.  Nishi A, Milner DA, Giovannucci EL, Nishihara R, Tan AS et al. 2016. Integration of molecular pathology, epidemiology, and social science for global precision medicine. Expert Rev. Mol. Diagn. 16:11–23
     [Google Scholar]
  148. 148.  Louis DN, Feldman M, Carter AB, Dighe AS, Pfeifer JD et al. 2016. Computational pathology: a path ahead. Arch. Pathol. Lab. Med. 140:41–50
     [Google Scholar]
  149. 149.  Takeda K, Kudo SE, Mori Y, Misawa M, Kudo T et al. 2017. Accuracy of diagnosing invasive colorectal cancer using computer-aided endocytoscopy. Endoscopy 49:798–802
     [Google Scholar]
  150. 150.  Tearney GJ, Kang D 2017. Introduction to biomedical optical imaging. Lasers Surg. Med. 49:214
     [Google Scholar]
  151. 151.  Ioannidis JP, Greenland S, Hlatky MA, Khoury MJ, Macleod MR et al. 2014. Increasing value and reducing waste in research design, conduct, and analysis. Lancet 383:166–75
     [Google Scholar]
/content/journals/10.1146/annurev-pathmechdis-012418-012818
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Insights into Pathogenic Interactions Among Environment, Host, and Tumor at the Crossroads of Molecular Pathology and Epidemiology
Annual Review of Pathology: Mechanisms of Disease 14, 83 (2019); https://doi.org/10.1146/annurev-pathmechdis-012418-012818
/content/journals/10.1146/annurev-pathmechdis-012418-012818
/content/journals/10.1146/annurev-pathmechdis-012418-012818
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