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2. Calcium intake and genetic variants in the calcium sensing receptor in relation to colorectal cancer mortality: an international consortium study of 18,952 patients

5. Allometric versus traditional body-shape indices and risk of colorectal cancer: a Mendelian randomization analysis

6. Folate intake and colorectal cancer risk according to genetic subtypes defined by targeted tumor sequencing

8. Combining Asian and European genome-wide association studies of colorectal cancer improves risk prediction across racial and ethnic populations

9. Body size and risk of colorectal cancer molecular defined subtypes and pathways: Mendelian randomization analyses

10. Genome-wide association study identifies tumor anatomical site-specific risk variants for colorectal cancer survival

11. Association between circulating inflammatory markers and adult cancer risk: a Mendelian randomization analysis

12. Prognostic role of detailed colorectal location and tumor molecular features: analyses of 13,101 colorectal cancer patients including 2994 early-onset cases

13. Elucidating the Risk of Colorectal Cancer for Variants in Hereditary Colorectal Cancer Genes

14. Landscape of somatic single nucleotide variants and indels in colorectal cancer and impact on survival.

17. Identifying colorectal cancer caused by biallelic MUTYH pathogenic variants using tumor mutational signatures

18. Association between germline variants and somatic mutations in colorectal cancer

19. Associations between pathological features and risk of metachronous colorectal cancer.

22. Characteristics and diagnostic performance of pathologists who enjoy interpreting melanocytic lesions

23. Supplementary Table S1 from Use of Deep Learning to Evaluate Tumor Microenvironmental Features for Prediction of Colon Cancer Recurrence

24. TABLE 2 from Use of Deep Learning to Evaluate Tumor Microenvironmental Features for Prediction of Colon Cancer Recurrence

25. FIGURE 2 from Use of Deep Learning to Evaluate Tumor Microenvironmental Features for Prediction of Colon Cancer Recurrence

26. FIGURE 1 from Use of Deep Learning to Evaluate Tumor Microenvironmental Features for Prediction of Colon Cancer Recurrence

27. TABLE 1 from Use of Deep Learning to Evaluate Tumor Microenvironmental Features for Prediction of Colon Cancer Recurrence

28. TABLE 3 from Use of Deep Learning to Evaluate Tumor Microenvironmental Features for Prediction of Colon Cancer Recurrence

29. Data from Use of Deep Learning to Evaluate Tumor Microenvironmental Features for Prediction of Colon Cancer Recurrence

31. Supplemental Table 1 from Epidemiologic Factors in Relation to Colorectal Cancer Risk and Survival by Genotoxic Colibactin Mutational Signature

32. Supplemental Table 2 from Epidemiologic Factors in Relation to Colorectal Cancer Risk and Survival by Genotoxic Colibactin Mutational Signature

33. Data from Epidemiologic Factors in Relation to Colorectal Cancer Risk and Survival by Genotoxic Colibactin Mutational Signature

34. Supplementary Methods from Genome-Wide Gene–Environment Interaction Analyses to Understand the Relationship between Red Meat and Processed Meat Intake and Colorectal Cancer Risk

35. Supplementary Table 2 from Genome-Wide Gene–Environment Interaction Analyses to Understand the Relationship between Red Meat and Processed Meat Intake and Colorectal Cancer Risk

36. Supplementary Figure 4 from Genome-Wide Gene–Environment Interaction Analyses to Understand the Relationship between Red Meat and Processed Meat Intake and Colorectal Cancer Risk

37. Data from Genome-Wide Gene–Environment Interaction Analyses to Understand the Relationship between Red Meat and Processed Meat Intake and Colorectal Cancer Risk

38. Supplementary Table 1 from Genome-Wide Gene–Environment Interaction Analyses to Understand the Relationship between Red Meat and Processed Meat Intake and Colorectal Cancer Risk

39. Supplementary Figure 1 from Genome-Wide Gene–Environment Interaction Analyses to Understand the Relationship between Red Meat and Processed Meat Intake and Colorectal Cancer Risk

40. Supplementary Figure 2 from Genome-Wide Gene–Environment Interaction Analyses to Understand the Relationship between Red Meat and Processed Meat Intake and Colorectal Cancer Risk

41. Supplementary Figure 3 from Genome-Wide Gene–Environment Interaction Analyses to Understand the Relationship between Red Meat and Processed Meat Intake and Colorectal Cancer Risk

42. Supplementary Figure 5 from Genome-Wide Gene–Environment Interaction Analyses to Understand the Relationship between Red Meat and Processed Meat Intake and Colorectal Cancer Risk

43. Sleep quality, duration, and breast cancer aggressiveness

44. Validity of self-reported sleep duration in the Cancer Prevention Study– 3.

45. Evaluation of oral herpes simplex virus shedding among solid organ transplant recipients: A pilot study.

46. Genetic Variant Associated With Survival of Patients With Stage II-III Colon Cancer

48. Epidemiologic Factors in Relation to Colorectal Cancer Risk and Survival by Genotoxic Colibactin Mutational Signature

50. Association between circulating inflammatory markers and adult cancer risk: a Mendelian randomization analysis

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