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Cancer immunology—analysis of host and tumor factors for personalized medicine

Abstract

Immune cells in the tumor microenvironment have an important role in regulating tumor progression. Therefore, stimulating immune reactions to tumors can be an attractive therapeutic and prevention strategy. Cancer cells and host cells constantly interact with each other in the tumor microenvironment; thus, cancer immunology is an interdisciplinary area where integrated analysis of both host and tumor factors is needed. Cancer represents a heterogeneous group of diseases with different genetic and epigenetic alterations; therefore, molecular classification of cancer (for example lung, prostate and breast cancers) is an important component in clinical decision making. However, most studies on antitumor immunity and clinical outcome lack analysis of tumor molecular biomarkers. In this Review, we discuss colorectal cancer as a prototypical example of cancer. Common molecular classifiers of colon cancer include KRAS, BRAF and PIK3CA mutations, microsatellite instability, LINE-1 methylation, and CpG island methylator phenotype. Since tumor molecular features and immune reactions are inter-related, a comprehensive assessment of these factors is critical. Examining the effects of tumor–host interactions on clinical outcome and prognosis represents an evolving interdisciplinary field of molecular pathological epidemiology. Pathological immunity evaluation may provide information on prognosis and help identify patients who are more likely to benefit from immunotherapy.

Key Points

  • Cancer immunology is an interdisciplinary research area that requires integrated analysis of both host and tumor factors

  • Each tumor has its own unique set of genomic and epigenomic changes, which can influence the host immune response to tumor

  • Examining the effects of tumor–host interactions on clinical outcome and tumor growth represents an emerging interdisciplinary scientific field of molecular pathological epidemiology

  • The degree of the immune response to a tumor has been positively associated with improved survival of patients with colorectal cancer and was independent of tumor molecular features

  • Immunity evaluation in pathology practice may provide information on clinical outcome and help identify patients who are most likely to benefit from immunotherapy

  • We need to conduct comprehensive translational studies that can evaluate and validate tumor molecular characteristics, roles of subsets of immune cells, and methods to assess immune cells

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Figure 1: Various immune-cell reaction patterns can be observed upon pathologic examination of a cancer biopsy.
Figure 2: Putative inter-relationship between tumor molecular changes, host immune response, regional lymph nodes, disease stage and prognosis in colorectal cancer.

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References

  1. Paez, J. G. et al. EGFR mutations in lung cancer: correlation with clinical response to gefitinib therapy. Science 304, 1497–1500 (2004).

    Article  CAS  PubMed  Google Scholar 

  2. Lynch, T. J. et al. Activating mutations in the epidermal growth factor receptor underlying responsiveness of non-small-cell lung cancer to gefitinib. N. Engl. J. Med. 350, 2129–2139 (2004).

    Article  CAS  PubMed  Google Scholar 

  3. Markowitz, S. D. & Bertagnolli, M. M. Molecular origins of cancer: Molecular basis of colorectal cancer. N. Engl. J. Med. 361, 2449–2460 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Ogino, S. & Goel, A. Molecular classification and correlates in colorectal cancer. J. Mol. Diagn. 10, 13–27 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Pritchard, C. C. & Grady, W. M. Colorectal cancer molecular biology moves into clinical practice. Gut 60, 116–129 (2011).

    Article  CAS  PubMed  Google Scholar 

  6. Dolle, J. M. et al. Risk factors for triple-negative breast cancer in women under the age of 45 years. Cancer Epidemiol. Biomarkers Prev. 18, 1157–1166 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  7. Trivers, K. F. et al. The epidemiology of triple-negative breast cancer, including race. Cancer Causes Control 20, 1071–1082 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  8. Tomlins, S. A. et al. Recurrent fusion of TMPRSS2 and ETS transcription factor genes in prostate cancer. Science 310, 644–648 (2005).

    Article  CAS  PubMed  Google Scholar 

  9. Samuels, Y. et al. High frequency of mutations of the PIK3CA gene in human cancers. Science 304, 554 (2004).

    Article  CAS  PubMed  Google Scholar 

  10. Wood, L. D. et al. The genomic landscapes of human breast and colorectal cancers. Science 318, 1108–1113 (2007).

    Article  CAS  PubMed  Google Scholar 

  11. Esteller, M. Epigenetics in cancer. N. Engl. J. Med. 358, 1148–1159 (2008).

    Article  CAS  PubMed  Google Scholar 

  12. Zou, W. Regulatory T cells, tumour immunity and immunotherapy. Nat. Rev. Immunol. 6, 295–307 (2006).

    Article  CAS  PubMed  Google Scholar 

  13. Allen, M. & Louise Jones, J. Jekyll and Hyde: the role of the microenvironment on the progression of cancer. J. Pathol. 223, 162–176 (2011).

    CAS  PubMed  Google Scholar 

  14. Disis, M. L., Bernhard, H. & Jaffee, E. M. Use of tumour-responsive T cells as cancer treatment. Lancet 373, 673–683 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Ferrone, C. & Dranoff, G. Dual roles for immunity in gastrointestinal cancers. J. Clin. Oncol. 28, 4045–4051 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Wilke, C. M., Wu, K., Zhao, E., Wang, G. & Zou, W. Prognostic significance of regulatory T cells in tumor. Int. J. Cancer 127, 748–758 (2010).

    CAS  PubMed  Google Scholar 

  17. Morikawa, T. et al. Association of CTNNB1 (beta-catenin) alterations, body mass index, and physical activity with survival in patients with colorectal cancer. JAMA 305, 1685–1694 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Kosaka, T. et al. Analysis of epidermal growth factor receptor gene mutation in patients with non-small cell lung cancer and acquired resistance to gefitinib. Clin. Cancer Res. 12, 5764–5769 (2006).

    Article  CAS  PubMed  Google Scholar 

  19. Oh, Y. H. et al. Rapid detection of the epidermal growth factor receptor mutation in non-small-cell lung cancer for analysis of acquired resistance using molecular beacons. J. Mol. Diagn. 12, 644–652 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Jones, D. et al. Laboratory practice guidelines for detecting and reporting BCR-ABL drug resistance mutations in chronic myelogenous leukemia and acute lymphoblastic leukemia: a report of the Association for Molecular Pathology. J. Mol. Diagn. 11, 4–11 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Graham, D. M. & Appelman, H. D. Crohn's-like lymphoid reaction and colorectal carcinoma: a potential histologic prognosticator. Mod. Pathol. 3, 332–335 (1990).

    CAS  PubMed  Google Scholar 

  22. Naito, Y. et al. CD8+ T cells infiltrated within cancer cell nests as a prognostic factor in human colorectal cancer. Cancer Res. 58, 3491–3494 (1998).

    CAS  PubMed  Google Scholar 

  23. Guidoboni, M. et al. Microsatellite instability and high content of activated cytotoxic lymphocytes identify colon cancer patients with a favorable prognosis. Am. J. Pathol. 159, 297–304 (2001).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Oberg, A., Samii, S., Stenling, R. & Lindmark, G. Different occurrence of CD8+, CD45R0+, and CD68+ immune cells in regional lymph node metastases from colorectal cancer as potential prognostic predictors. Int. J. Colorectal Dis. 17, 25–29 (2002).

    Article  CAS  PubMed  Google Scholar 

  25. Petty, J. K., He, K., Corless, C. L., Vetto, J. T. & Weinberg, A. D. Survival in human colorectal cancer correlates with expression of the T-cell costimulatory molecule OX-40 (CD134). Am. J. Surg. 183, 512–518 (2002).

    Article  CAS  PubMed  Google Scholar 

  26. Diederichsen, A. C., Hjelmborg, J. B., Christensen, P. B., Zeuthen, J. & Fenger, C. Prognostic value of the CD4+/CD8+ ratio of tumour infiltrating lymphocytes in colorectal cancer and HLA-DR expression on tumour cells. Cancer Immunol. Immunother. 52, 423–428 (2003).

    Article  CAS  PubMed  Google Scholar 

  27. Funada, Y. et al. Prognostic significance of CD8+ T cell and macrophage peritumoral infiltration in colorectal cancer. Oncol. Rep. 10, 309–313 (2003).

    PubMed  Google Scholar 

  28. Prall, F. et al. Prognostic role of CD8+ tumor-infiltrating lymphocytes in stage III colorectal cancer with and without microsatellite instability. Hum. Pathol. 35, 808–816 (2004).

    Article  CAS  PubMed  Google Scholar 

  29. Menon, A. G. et al. Immune system and prognosis in colorectal cancer: a detailed immunohistochemical analysis. Lab. Invest. 84, 493–501 (2004).

    Article  CAS  PubMed  Google Scholar 

  30. Chiba, T. et al. Intraepithelial CD8+ T-cell-count becomes a prognostic factor after a longer follow-up period in human colorectal carcinoma: possible association with suppression of micrometastasis. Br. J. Cancer 91, 1711–1717 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Pages, F. et al. Effector memory T cells, early metastasis, and survival in colorectal cancer. N. Engl. J. Med. 353, 2654–2666 (2005).

    Article  CAS  PubMed  Google Scholar 

  32. Baeten, C. I., Castermans, K., Hillen, H. F. & Griffioen, A. W. Proliferating endothelial cells and leukocyte infiltration as prognostic markers in colorectal cancer. Clin. Gastroenterol. Hepatol. 4, 1351–1357 (2006).

    Article  CAS  PubMed  Google Scholar 

  33. Galon, J. et al. Type, density, and location of immune cells within human colorectal tumors predict clinical outcome. Science 313, 1960–1964 (2006).

    Article  CAS  PubMed  Google Scholar 

  34. Zlobec, I. et al. Multimarker phenotype predicts adverse survival in patients with lymph node-negative colorectal cancer. Cancer 112, 495–502 (2008).

    Article  PubMed  Google Scholar 

  35. Zlobec, I. et al. Two-marker protein profile predicts poor prognosis in patients with early rectal cancer. Br. J. Cancer 99, 1712–1717 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Sinicrope, F. A. et al. Intraepithelial effector (CD3+)/regulatory (FoxP3+) T-cell ratio predicts a clinical outcome of human colon carcinoma. Gastroenterology 137, 1270–1279 (2009).

    Article  CAS  PubMed  Google Scholar 

  37. Laghi, L. et al. CD3+ cells at the invasive margin of deeply invading (pT3-T4) colorectal cancer and risk of post-surgical metastasis: a longitudinal study. Lancet Oncol. 10, 877–884 (2009).

    Article  CAS  PubMed  Google Scholar 

  38. Frey, D. M. et al. High frequency of tumor-infiltrating FOXP3(+) regulatory T cells predicts improved survival in mismatch repair-proficient colorectal cancer patients. Int. J. Cancer 126, 2635–2643 (2009).

    Google Scholar 

  39. Salama, P. et al. Tumor-infiltrating FOXP3+ T regulatory cells show strong prognostic significance in colorectal cancer. J. Clin. Oncol. 27, 186–192 (2009).

    Article  PubMed  Google Scholar 

  40. Pages, F. et al. In situ cytotoxic and memory T cells predict outcome in patients with early-stage colorectal cancer. J. Clin. Oncol. 27, 5944–5951 (2009).

    Article  CAS  PubMed  Google Scholar 

  41. Deschoolmeester, V. et al. Tumor infiltrating lymphocytes: an intriguing player in the survival of colorectal cancer patients. BMC Immunol. 11, 19 (2010).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  42. Suzuki, H. et al. Intratumoral CD8+ T/FOXP3+ cell ratio is a predictive marker for survival in patients with colorectal cancer. Cancer Immunol. Immunother. 59, 653–661 (2010).

    Article  CAS  PubMed  Google Scholar 

  43. Correale, P. et al. Regulatory (FoxP3+) T-cell tumor infiltration is a favorable prognostic factor in advanced colon cancer patients undergoing chemo or chemoimmunotherapy. J. Immunother. 33, 435–441 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  44. Lee, W. S., Park, S., Lee, W. Y., Yun, S. H. & Chun, H. K. Clinical impact of tumor-infiltrating lymphocytes for survival in stage II colon cancer. Cancer 116, 5188–5199 (2010).

    Article  PubMed  Google Scholar 

  45. Nosho, K. et al. Tumour-infiltrating T-cell subsets, molecular changes in colorectal cancer and prognosis: cohort study and literature review. J. Pathol. 222, 350–366 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  46. Ropponen, K. M., Eskelinen, M. J., Lipponen, P. K., Alhava, E. & Kosma, V. M. Prognostic value of tumour-infiltrating lymphocytes (TILs) in colorectal cancer. J. Pathol. 182, 318–324 (1997).

    Article  CAS  PubMed  Google Scholar 

  47. Morris, M., Platell, C. & Iacopetta, B. Tumor-infiltrating lymphocytes and perforation in colon cancer predict positive response to 5-fluorouracil chemotherapy. Clin. Cancer Res. 14, 1413–1417 (2008).

    Article  CAS  PubMed  Google Scholar 

  48. Mlecnik, B. et al. Histopathologic-based prognostic factors of colorectal cancers are associated with the state of the local immune reaction. J. Clin. Oncol. 29, 610–618 (2011).

    Article  PubMed  Google Scholar 

  49. Ogino, S. et al. Lymphocytic reaction to colorectal cancer is associated with longer survival, independent of lymph node count, microsatellite instability, and CpG island methylator phenotype. Clin. Cancer Res. 15, 6412–6420 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Tosolini, M. et al. Clinical impact of different classes of infiltrating T cytotoxic and helper cells (Th1, Th2, Treg, Th17) in patients with colorectal cancer. Cancer Res. 71, 1263–1271 (2011).

    Article  CAS  PubMed  Google Scholar 

  51. Zlobec, I. et al. TIA-1 cytotoxic granule-associated RNA binding protein improves the prognostic performance of CD8 in mismatch repair-proficient colorectal cancer. PLoS ONE 5, e14282 (2010).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  52. Dahlin, A. M. et al. Colorectal cancer prognosis depends on T-cell infiltration and molecular characteristics of the tumor. Mod. Pathol. 24, 671–682 (2011).

    Article  CAS  PubMed  Google Scholar 

  53. Linnebacher, M. et al. Frameshift peptide-derived T-cell epitopes: a source of novel tumor-specific antigens. Int. J. Cancer 93, 6–11 (2001).

    Article  CAS  PubMed  Google Scholar 

  54. Saeterdal, I. et al. Frameshift-mutation-derived peptides as tumor-specific antigens in inherited and spontaneous colorectal cancer. Proc. Natl Acad. Sci. USA 98, 13255–13260 (2001).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Schwitalle, Y. et al. Immune response against frameshift-induced neopeptides in HNPCC patients and healthy HNPCC mutation carriers. Gastroenterology 134, 988–997 (2008).

    Article  CAS  PubMed  Google Scholar 

  56. Speetjens, F. M. et al. Prediction of the immunogenic potential of frameshift-mutated antigens in microsatellite instable cancer. Int. J. Cancer 123, 838–845 (2008).

    Article  CAS  PubMed  Google Scholar 

  57. Tougeron, D. et al. Tumor-infiltrating lymphocytes in colorectal cancers with microsatellite instability are correlated with the number and spectrum of frameshift mutations. Mod. Pathol. 22, 1186–1195 (2009).

    Article  CAS  PubMed  Google Scholar 

  58. Chan, A. T., Ogino, S. & Fuchs, C. S. Aspirin and the risk of colorectal cancer in relation to the expression of COX-2. N. Engl. J. Med. 356, 2131–2142 (2007).

    Article  CAS  PubMed  Google Scholar 

  59. McLean, M. H. et al. The inflammatory microenvironment in colorectal neoplasia. PLoS ONE 6, e15366 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Suehiro, Y. et al. Epigenetic-genetic interactions in the APC/WNT, RAS/RAF, and p53 pathways in colorectal carcinoma. Clin. Cancer Res. 14, 2560–2569 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Chapman, M. A. et al. Initial genome sequencing and analysis of multiple myeloma. Nature 471, 467–472 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  PubMed  PubMed Central  Google Scholar 

  63. Ogino, S., Chan, A. T., Fuchs, C. S. & Giovannucci, E. Molecular pathological epidemiology of colorectal neoplasia: an emerging transdisciplinary and interdisciplinary field. Gut 60, 397–411 (2011).

    Article  PubMed  Google Scholar 

  64. Ogino, S. et al. Cohort study of fatty acid synthase expression and patient survival in colon cancer. J. Clin. Oncol. 26, 5713–5720 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Chan, A. T., Ogino, S. & Fuchs, C. S. Aspirin use and survival after diagnosis of colorectal cancer. JAMA 302, 649–658 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Walther, A. et al. Genetic prognostic and predictive markers in colorectal cancer. Nat. Rev. Cancer 9, 489–499 (2009).

    Article  CAS  PubMed  Google Scholar 

  67. Hamilton, S. R. Targeted therapy of cancer: new roles for pathologists in colorectal cancer. Mod. Pathol. 21 (Suppl. 2), S23–S30 (2008).

    Article  CAS  PubMed  Google Scholar 

  68. Popat, S., Hubner, R. & Houlston, R. S. Systematic review of microsatellite instability and colorectal cancer prognosis. J. Clin. Oncol. 23, 609–618 (2005).

    Article  CAS  PubMed  Google Scholar 

  69. Samowitz, W. et al. Evaluation of a large, population-based sample supports a CpG island methylator phenotype in colon cancer. Gastroenterology 129, 837–845 (2005).

    Article  CAS  PubMed  Google Scholar 

  70. Ogino, S. et al. CpG island methylator phenotype (CIMP) of colorectal cancer is best characterised by quantitative DNA methylation analysis and prospective cohort studies. Gut 55, 1000–1006 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. Nosho, K. et al. Comprehensive biostatistical analysis of CpG island methylator phenotype in colorectal cancer using a large population-based sample. PLoS ONE 3, e3698 (2008).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  72. Ogino, S. et al. LINE-1 hypomethylation is inversely associated with microsatellite instability and CpG methylator phenotype in colorectal cancer. Int. J. Cancer 122, 2767–2773 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  73. Kawasaki, T. et al. Correlation of beta-catenin localization with cyclooxygenase-2 expression and CpG island methylator phenotype (CIMP) in colorectal cancer. Neoplasia 9, 569–577 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  74. Goel, A. et al. The CpG island methylator phenotype and chromosomal instability are inversely correlated in sporadic colorectal cancer. Gastroenterology 132, 127–138 (2007).

    Article  CAS  PubMed  Google Scholar 

  75. Teodoridis, J. M., Hardie, C. & Brown, R. CpG island methylator phenotype (CIMP) in cancer: Causes and implications. Cancer Lett. 268, 177–186 (2008).

    Article  CAS  PubMed  Google Scholar 

  76. Curtin, K., Slattery, M. L. & Samowitz, W. S. CpG island methylation in colorectal cancer: past, present and future. Patholog. Res. Int. 2011, 902674 (2011).

    PubMed  PubMed Central  Google Scholar 

  77. van Engeland, M., Derks, S., Smits, K. M., Meijer, G. A. & Herman, J. G. Colorectal cancer epigenetics: Complex simplicity. J. Clin. Oncol. 29, 1382–1391 (2011).

    Article  PubMed  Google Scholar 

  78. Hinoue, T. et al. Genome-scale analysis of aberrant DNA methylation in colorectal cancer. Genome Res. doi:10.1101/gr.117523.110.

    Article  PubMed  CAS  Google Scholar 

  79. Ogino, S. et al. CpG island methylator phenotype, microsatellite instability, BRAF mutation and clinical outcome in colon cancer. Gut 58, 90–96 (2009).

    Article  PubMed  Google Scholar 

  80. Alexander, J. et al. Histopathological identification of colon cancer with microsatellite instability. Am. J. Pathol. 158, 527–535 (2001).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  81. Shia, J. et al. Value of histopathology in predicting microsatellite instability in hereditary nonpolyposis colorectal cancer and sporadic colorectal cancer. Am. J. Surg. Pathol. 27, 1407–1417 (2003).

    Article  PubMed  Google Scholar 

  82. Ogino, S. et al. Correlation of pathologic features with CpG island methylator phenotype (CIMP) by quantitative DNA methylation analysis in colorectal carcinoma. Am. J. Surg. Pathol. 30, 1175–1183 (2006).

    Article  PubMed  Google Scholar 

  83. Michel, S. et al. High density of FOXP3-positive T cells infiltrating colorectal cancers with microsatellite instability. Br. J. Cancer 99, 1867–1873 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  84. Markowitz, S. et al. Inactivation of the type II TGF-beta receptor in colon cancer cells with microsatellite instability. Science 268, 1336–1338 (1995).

    Article  CAS  PubMed  Google Scholar 

  85. Becker, C. et al. TGF-beta suppresses tumor progression in colon cancer by inhibition of IL-6 trans-signaling. Immunity 21, 491–501 (2004).

    Article  CAS  PubMed  Google Scholar 

  86. Yang, L. et al. Abrogation of TGF beta signaling in mammary carcinomas recruits Gr-1+CD11b+ myeloid cells that promote metastasis. Cancer Cell 13, 23–35 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  87. Bierie, B. et al. Transforming growth factor-beta regulates mammary carcinoma cell survival and interaction with the adjacent microenvironment. Cancer Res. 68, 1809–1819 (2008).

    Article  CAS  PubMed  Google Scholar 

  88. Yang, L. TGFβ and cancer metastasis: an inflammation link. Cancer Metastasis Rev. 29, 263–271 (2010).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  89. Meulmeester, E. & Ten Dijke, P. The dynamic roles of TGF-beta in cancer. J. Pathol. 223, 205–218 (2011).

    Article  CAS  PubMed  Google Scholar 

  90. Morikawa, T. et al. STAT3 expression, molecular features, inflammation patterns and prognosis in a database of 724 colorectal cancers. Clin. Cancer Res. 17, 1452–1462 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  91. Bedel, R. et al. Novel role for STAT3 in transcriptional regulation of NK immune cell targeting receptor MICA on cancer cells. Cancer Res. 71, 1615–1626 (2011).

    Article  CAS  PubMed  Google Scholar 

  92. Sidler, D. et al. Colon cancer cells produce immunoregulatory glucocorticoids. Oncogene 30, 2411–2419 (2011).

    Article  CAS  PubMed  Google Scholar 

  93. Walther, A., Houlston, R. & Tomlinson, I. Association between chromosomal instability and prognosis in colorectal cancer: a meta-analysis. Gut 57, 941–950 (2008).

    Article  CAS  PubMed  Google Scholar 

  94. Sinicrope, F. A. et al. Prognostic impact of microsatellite instability and DNA ploidy in human colon carcinoma patients. Gastroenterology 131, 729–737 (2006).

    Article  CAS  PubMed  Google Scholar 

  95. Samowitz, W. S. et al. Poor survival associated with the BRAF V600E mutation in microsatellite-stable colon cancers. Cancer Res. 65, 6063–6069 (2005).

    Article  CAS  PubMed  Google Scholar 

  96. Dahlin, A. M. et al. The role of the CpG island methylator phenotype in colorectal cancer prognosis depends on microsatellite instability screening status. Clin. Cancer Res. 16, 1845–1855 (2010).

    Article  CAS  PubMed  Google Scholar 

  97. Kim, J. H., Shin, S. H., Kwon, H. J., Cho, N. Y. & Kang, G. H. Prognostic implications of CpG island hypermethylator phenotype in colorectal cancers. Virchow. Arch. 455, 485–494 (2009).

    Article  CAS  Google Scholar 

  98. Barault, L. et al. Hypermethylator phenotype in sporadic colon cancer: study on a population-based series of 582 cases. Cancer Res. 68, 8541–8546 (2008).

    Article  CAS  PubMed  Google Scholar 

  99. French, A. J. et al. Prognostic significance of defective mismatch repair and BRAF V600E in patients with colon cancer. Clin. Cancer Res. 14, 3408–3415 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  100. Zlobec, I., Bihl, M. P., Schwarb, H., Terracciano, L. & Lugli, A. Clinicopathological and protein characterization of BRAF- and K-RAS-mutated colorectal cancer and implications for prognosis. Int. J. Cancer 127, 367–380 (2010).

    Article  CAS  PubMed  Google Scholar 

  101. Roth, A. D. et al. Prognostic role of KRAS and BRAF in stage II and III resected colon cancer: results of the translational study on the PETACC-3, EORTC 40993, SAKK 60–00 trial. J. Clin. Oncol. 28, 466–474 (2010).

    Article  CAS  PubMed  Google Scholar 

  102. Souglakos, J. et al. Prognostic and predictive value of common mutations for treatment response and survival in patients with metastatic colorectal cancer. Br. J. Cancer 101, 465–472 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  103. Farina-Sarasqueta, A. et al. The BRAF V600E mutation is an independent prognostic factor for survival in stage II and stage III colon cancer patients. Ann. Oncol. 21, 2396–2402 (2010).

    Article  CAS  PubMed  Google Scholar 

  104. Ferracin, M. et al. The methylator phenotype in microsatellite stable colorectal cancers is characterized by a distinct gene expression profile. J. Pathol. 214, 594–602 (2008).

    Article  CAS  PubMed  Google Scholar 

  105. Saridaki, Z. et al. BRAF mutations, microsatellite instability status and cyclin D1 expression predict metastatic colorectal patients' outcome. Br. J. Cancer 102, 1762–1768 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  106. Ogino, S. et al. PIK3CA mutation is associated with poor prognosis among patients with curatively resected colon cancer. J. Clin. Oncol. 27, 1477–1484 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  107. He, Y. et al. PIK3CA mutations predict local recurrences in rectal cancer patients. Clin. Cancer Res. 15, 6956–6962 (2009).

    Article  CAS  PubMed  Google Scholar 

  108. Kato, S. et al. PIK3CA mutation is predictive of poor survival in patients with colorectal cancer. Int. J. Cancer 121, 1771–1778 (2007).

    Article  CAS  PubMed  Google Scholar 

  109. Ogino, S. et al. A cohort study of tumoral LINE-1 hypomethylation and prognosis in colon cancer. J. Natl Cancer Inst. 100, 1734–1738 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  110. Frigola, J. et al. Differential DNA hypermethylation and hypomethylation signatures in colorectal cancer. Hum. Mol. Genet. 14, 319–326 (2005).

    Article  CAS  PubMed  Google Scholar 

  111. Ahn, J. B. et al. DNA methylation predicts recurrence from resected stage III proximal colon cancer. Cancer 117, 1847–1854 (2011).

    Article  CAS  PubMed  Google Scholar 

  112. Gryfe, R. et al. Tumor microsatellite instability and clinical outcome in young patients with colorectal cancer. N. Engl. J. Med. 342, 69–77 (2000).

    Article  CAS  PubMed  Google Scholar 

  113. Barratt, P. L. et al. DNA markers predicting benefit from adjuvant fluorouracil in patients with colon cancer: a molecular study. Lancet 360, 1381–1391 (2002).

    Article  CAS  PubMed  Google Scholar 

  114. Ribic, C. M. et al. Tumor microsatellite-instability status as a predictor of benefit from fluorouracil-based adjuvant chemotherapy for colon cancer. N. Engl. J. Med. 349, 247–257 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  115. Samowitz, W. S. et al. Microsatellite instability in sporadic colon cancer is associated with an improved prognosis at the population level. Cancer Epidemiol. Biomarkers Prev. 10, 917–923 (2001).

    CAS  PubMed  Google Scholar 

  116. Ward, R. L. et al. Adverse prognostic effect of methylation in colorectal cancer is reversed by microsatellite instability. J. Clin. Oncol. 21, 3729–3736 (2003).

    Article  CAS  PubMed  Google Scholar 

  117. Bertagnolli, M. M. et al. Microsatellite instability predicts improved response to adjuvant therapy with irinotecan, fluorouracil, and leucovorin in stage III colon cancer: Cancer and Leukemia Group B Protocol 89803. J. Clin. Oncol. 27, 1814–1821 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  118. Jenkins, M. A. et al. Pathology features in Bethesda guidelines predict colorectal cancer microsatellite instability: a population-based study. Gastroenterology 133, 48–56 (2007).

    Article  CAS  PubMed  Google Scholar 

  119. Chirieac, L. R., Shen, L., Catalano, P. J., Issa, J. P. & Hamilton, S. R. Phenotype of microsatellite-stable colorectal carcinomas with CpG island methylation. Am. J. Surg. Pathol. 29, 429–436 (2005).

    Article  PubMed  Google Scholar 

  120. Ogino, S. et al. Sensitive sequencing method for KRAS mutation detection by Pyrosequencing. J. Mol. Diagn. 7, 413–421 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  121. Packham, D., Ward, R. L., Ap Lin, V., Hawkins, N. J. & Hitchins, M. P. Implementation of novel pyrosequencing assays to screen for common mutations of BRAF and KRAS in a cohort of sporadic colorectal cancers. Diagn. Mol. Pathol. 18, 62–71 (2009).

    Article  CAS  PubMed  Google Scholar 

  122. Tsiatis, A. C. et al. Comparison of Sanger sequencing, pyrosequencing, and melting curve analysis for the detection of KRAS mutations: diagnostic and clinical implications. J. Mol. Diagn. 12, 425–432 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  123. Monzon, F. A. et al. The role of KRAS mutation testing in the management of patients with metastatic colorectal cancer. Arch. Pathol. Lab. Med. 133, 1600–1606 (2009).

    Article  CAS  PubMed  Google Scholar 

  124. Irahara, N. et al. Precision of Pyrosequencing assay to measure LINE-1 methylation in colon cancer, normal colonic mucosa and peripheral blood cells. J. Mol. Diagn. 12, 177–183 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  125. Szczepanik, A. M. et al. T-regulatory lymphocytes in peripheral blood of gastric and colorectal cancer patients. World J. Gastroenterol. 17, 343–348 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  126. Kononen, J. et al. Tissue microarrays for high-throughput molecular profiling of tumor specimens. Nat. Med. 4, 844–847 (1998).

    Article  CAS  PubMed  Google Scholar 

  127. Camp, R. L., Charette, L. A. & Rimm, D. L. Validation of tissue microarray technology in breast carcinoma. Lab. Invest. 80, 1943–1949 (2000).

    Article  CAS  PubMed  Google Scholar 

  128. Perrone, E. E. et al. Tissue microarray assessment of prostate cancer tumor proliferation in African-American and white men. J. Natl Cancer Inst. 92, 937–939 (2000).

    Article  CAS  PubMed  Google Scholar 

  129. Sherman, M. E. et al. Molecular pathology in epidemiologic studies: a primer on key considerations. Cancer Epidemiol. Biomarkers Prev. 19, 966–972 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  130. Chaput, N. et al. Identification of CD8+CD25+Foxp3+ suppressive T cells in colorectal cancer tissue. Gut 58, 520–529 (2009).

    Article  CAS  PubMed  Google Scholar 

  131. Le Gouvello, S. et al. High prevalence of Foxp3 and IL17 in MMR-proficient colorectal carcinomas. Gut 57, 772–779 (2008).

    Article  CAS  PubMed  Google Scholar 

  132. Curiel, T. J. Tregs and rethinking cancer immunotherapy. J. Clin. Invest. 117, 1167–1174 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  133. Blatner, N. R. et al. In colorectal cancer mast cells contribute to systemic regulatory T-cell dysfunction. Proc. Natl Acad. Sci. USA 107, 6430–6435 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  134. Rubin, M. A. et al. Quantitative determination of expression of the prostate cancer protein alpha-methylacyl-CoA racemase using automated quantitative analysis (AQUA): a novel paradigm for automated and continuous biomarker measurements. Am. J. Pathol. 164, 831–840 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  135. Chang, G. J., Rodriguez-Bigas, M. A., Skibber, J. M. & Moyer, V. A. Lymph node evaluation and survival after curative resection of colon cancer: systematic review. J. Natl Cancer Inst. 99, 433–441 (2007).

    Article  PubMed  Google Scholar 

  136. Johnson, P. M., Porter, G. A., Ricciardi, R. & Baxter, N. N. Increasing negative lymph node count is independently associated with improved long-term survival in stage IIIB and IIIC colon cancer. J. Clin. Oncol. 24, 3570–3575 (2006).

    Article  PubMed  Google Scholar 

  137. George, S. et al. Will Rogers revisited: prospective observational study of survival of 3592 patients with colorectal cancer according to number of nodes examined by pathologists. Br. J. Cancer 95, 841–847 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  138. Ogino, S. et al. Negative lymph node count is associated with survival of colorectal cancer patients, independent of tumoral molecular alterations and lymphocytic reaction. Am. J. Gastroenterol. 105, 420–433 (2010).

    Article  PubMed  Google Scholar 

  139. McShane, L. M. et al. REporting recommendations for tumor MARKer prognostic studies (REMARK). Nat. Clin. Pract. Oncol. 2, 416–422 (2005).

    CAS  PubMed  Google Scholar 

  140. Small, E. J. et al. Placebo-controlled phase III trial of immunologic therapy with sipuleucel-T (APC8015) in patients with metastatic, asymptomatic hormone refractory prostate cancer. J. Clin. Oncol. 24, 3089–3094 (2006).

    Article  CAS  PubMed  Google Scholar 

  141. Kantoff, P. W. et al. Sipuleucel-T immunotherapy for castration-resistant prostate cancer. N. Engl. J. Med. 363, 411–422 (2010).

    Article  CAS  PubMed  Google Scholar 

  142. Kantoff, P. W. et al. Overall survival analysis of a phase II randomized controlled trial of a Poxviral-based PSA-targeted immunotherapy in metastatic castration-resistant prostate cancer. J. Clin. Oncol. 28, 1099–1105 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  143. Schwartzentruber, D. J. et al. gp100 peptide vaccine and interleukin-2 in patients with advanced melanoma. N. Engl. J. Med. 364, 2119–2127 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  144. Hodi, F. S. et al. Improved survival with ipilimumab in patients with metastatic melanoma. N. Engl. J. Med. 363, 711–723 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  145. Brahmer, J. R. et al. Phase I study of single-agent anti-programmed death-1 (MDX-1106) in refractory solid tumors: safety, clinical activity, pharmacodynamics, and immunologic correlates. J. Clin. Oncol. 28, 3167–3175 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  146. Berger, R. et al. Phase I safety and pharmacokinetic study of CT-011, a humanized antibody interacting with PD-1, in patients with advanced hematologic malignancies. Clin. Cancer Res. 14, 3044–3051 (2008).

    Article  CAS  PubMed  Google Scholar 

  147. Sinicrope, F. A. & Sargent, D. J. Clinical implications of microsatellite instability in sporadic colon cancers. Curr. Opin. Oncol. 21, 369–373 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  148. Sargent, D. J. et al. Defective mismatch repair as a predictive marker for lack of efficacy of fluorouracil-based adjuvant therapy in colon cancer. J. Clin. Oncol. 28, 3219–3226 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  149. Kim, G. P. et al. Prognostic and predictive roles of high-degree microsatellite instability in colon cancer: a National Cancer Institute-National Surgical Adjuvant Breast and Bowel Project Collaborative Study. J. Clin. Oncol. 25, 767–772 (2007).

    Article  CAS  PubMed  Google Scholar 

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Acknowledgements

This work was supported by grants from the US NIH (R01 CA151993 [to S. Ogino], P50 CA127003 [DF/HCC GI SPORE to C. S. Fuchs], DF/HCC GI SPORE Developmental Project Award [to S. Ogino], and R01 CA143083 [to G. Dranoff]). The content is solely the responsibility of the authors and does not necessarily represent the official views of NCI or NIH. Funding agencies did not have any role in the decision to submit the manuscript for publication, or the writing of the manuscript.

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All authors contributed to researching the article and discussion of the content. S. Ogino and G. Dranoff significantly contributed to the writing of the article and all authors edited the manuscript prior to submission.

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Correspondence to Shuji Ogino.

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Supplementary Table 1

Examples of studies on immune cells in colorectal cancer tissue and clinical outcome (DOC 302 kb)

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Ogino, S., Galon, J., Fuchs, C. et al. Cancer immunology—analysis of host and tumor factors for personalized medicine. Nat Rev Clin Oncol 8, 711–719 (2011). https://doi.org/10.1038/nrclinonc.2011.122

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