Amanda I Phipps1, Elizabeth Alwers2, Tabitha Harrison3, Barbara Banbury3, Hermann Brenner4, Peter T Campbell5, Jenny Chang-Claude6, Daniel Buchanan7, Andrew T Chan8, Alton B Farris9, Jane C Figueiredo10, Steven Gallinger11, Graham G Giles12, Mark Jenkins13, Roger L Milne12, Polly A Newcomb14, Martha L Slattery15, Mingyang Song16, Shuji Ogino17, Syed H Zaidi18, Michael Hoffmeister2, Ulrike Peters14. 1. Epidemiology Department, University of Washington, Seattle, Washington; Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington. Electronic address: aphipps@fhcrc.org. 2. Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany. 3. Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington. 4. Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany; Division of Preventive Oncology, German Cancer Research Center (DKFZ), National Center for Tumor Diseases (NCT), Heidelberg, Germany; German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ) Heidelberg, Germany. 5. Behavioral and Epidemiology Research Group, American Cancer Society, Atlanta, Georgia. 6. Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany; Cancer Epidemiology Group, University Medical Center Hamburg-Eppendorf, University Cancer Center Hamburg, Hamburg, Germany. 7. Department of Clinical Pathology, Colorectal Oncogenomics Group, The University of Melbourne, Parkville, Victoria, Australia. 8. Clinical and Translational Epidemiology Unit, Department of Medicine, and Division of Gastroenterology, Massachusetts General Hospital, Boston, Massachusetts; Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts. 9. Department of Pathology, Emory University, Atlanta, Georgia. 10. Department of Medicine, Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, California. 11. Lunenfeld Tanenbaum Research Institute, Mount Sinai Hospital, University of Toronto, Toronto, Ontario, Canada. 12. Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Australia; Centre for Epidemiology and Biostatistics, School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia; Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia. 13. Centre for Epidemiology and Biostatistics, School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia. 14. Epidemiology Department, University of Washington, Seattle, Washington; Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington. 15. Department of Internal Medicine, University of Utah, Salt Lake City, Utah. 16. Clinical and Translational Epidemiology Unit, Department of Medicine, and Division of Gastroenterology, Massachusetts General Hospital, Boston, Massachusetts; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts; Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts. 17. Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts; Program in Molecular Pathological Epidemiology, Department of Pathology, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts; Broad Institute of MIT and Harvard, Cambridge, Massachusetts. 18. Ontario Institute for Cancer Research, Toronto, Ontario, Canada.
Abstract
BACKGROUND AND AIMS: The heterogeneity among colorectal tumors is probably due to differences in developmental pathways and might associate with patient survival times. We studied the relationship among markers of different subtypes of colorectal tumors and patient survival. METHODS: We pooled data from 7 observational studies, comprising 5010 patients with colorectal cancer. All the studies collected information on microsatellite instability (MSI), CpG island methylator phenotype (CIMP), and mutations in KRAS and BRAF in tumors. Tumors with complete marker data were classified as type 1 (MSI-high, CIMP-positive, with pathogenic mutations in BRAF but not KRAS), type 2 (not MSI-high, CIMP-positive, with pathogenic mutations in BRAF but not KRAS), type 3 (not MSI-high or CIMP, with pathogenic mutations in KRAS but not BRAF), type 4 (not MSI-high or CIMP, no pathogenic mutations in BRAF or KRAS), or type 5 (MSI-high, no CIMP, no pathogenic mutations in BRAF or KRAS). We used Cox regression to estimate hazard ratios (HR) and 95% confidence intervals (CIs) for associations of these subtypes and tumor markers with disease-specific survival (DSS) and overall survival times, adjusting for age, sex, stage at diagnosis, and study population. RESULTS: Patients with type 2 colorectal tumors had significantly shorter time of DSS than patients with type 4 tumors (HRDSS 1.66; 95% CI 1.33-2.07), regardless of sex, age, or stage at diagnosis. Patients without MSI-high tumors had significantly shorter time of DSS compared with patients with MSI-high tumors (HRDSS 0.42; 95% CI 0.27-0.64), regardless of other tumor markers or stage, or patient sex or age. CONCLUSIONS: In a pooled analysis of data from 7 observational studies of patients with colorectal cancer, we found that tumor subtypes, defined by combinations of 4 common tumor markers, were associated with differences in survival time. Colorectal tumor subtypes might therefore be used in determining patients' prognoses.
BACKGROUND AND AIMS: The heterogeneity among colorectal tumors is probably due to differences in developmental pathways and might associate with patient survival times. We studied the relationship among markers of different subtypes of colorectal tumors and patient survival. METHODS: We pooled data from 7 observational studies, comprising 5010 patients with colorectal cancer. All the studies collected information on microsatellite instability (MSI), CpG island methylator phenotype (CIMP), and mutations in KRAS and BRAF in tumors. Tumors with complete marker data were classified as type 1 (MSI-high, CIMP-positive, with pathogenic mutations in BRAF but not KRAS), type 2 (not MSI-high, CIMP-positive, with pathogenic mutations in BRAF but not KRAS), type 3 (not MSI-high or CIMP, with pathogenic mutations in KRAS but not BRAF), type 4 (not MSI-high or CIMP, no pathogenic mutations in BRAF or KRAS), or type 5 (MSI-high, no CIMP, no pathogenic mutations in BRAF or KRAS). We used Cox regression to estimate hazard ratios (HR) and 95% confidence intervals (CIs) for associations of these subtypes and tumor markers with disease-specific survival (DSS) and overall survival times, adjusting for age, sex, stage at diagnosis, and study population. RESULTS: Patients with type 2 colorectal tumors had significantly shorter time of DSS than patients with type 4 tumors (HRDSS 1.66; 95% CI 1.33-2.07), regardless of sex, age, or stage at diagnosis. Patients without MSI-high tumors had significantly shorter time of DSS compared with patients with MSI-high tumors (HRDSS 0.42; 95% CI 0.27-0.64), regardless of other tumor markers or stage, or patient sex or age. CONCLUSIONS: In a pooled analysis of data from 7 observational studies of patients with colorectal cancer, we found that tumor subtypes, defined by combinations of 4 common tumor markers, were associated with differences in survival time. Colorectal tumor subtypes might therefore be used in determining patients' prognoses.
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