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Routine tumor-node-metastasis (TNM) staging of colorectal cancer is imperfect in predicting survival due to tumor pathobiological heterogeneity and imprecise assessment of tumor spread. We leveraged Bayesian additive regression trees (BART), a statistical learning technique, to comprehensively analyze patient-specific tumor characteristics for the improvement of prognostic prediction. Of 75 clinicopathologic, immune, microbial, and genomic variables in 815 stage II–III patients within two U.S.-wide prospective cohort studies, the BART risk model identified seven stable survival predictors. Risk stratifications (low risk, intermediate risk, and high risk) based on model-predicted survival were statistically significant (hazard ratios 0.19–0.45, vs. higher risk; P < 0.0001) and could be externally validated using The Cancer Genome Atlas (TCGA) data (P = 0.0004). BART demonstrated model flexibility, interpretability, and comparable or superior performance to other machine-learning models. Integrated bioinformatic analyses using BART with tumor-specific factors can robustly stratify colorectal cancer patients into prognostic groups and be readily applied to clinical oncology practice.

Macrophages are among the most common cells in the colorectal cancer microenvironment, but their prognostic significance is incompletely understood. Using multiplexed immunofluorescence for CD68, CD86, IRF5, MAF, MRC1 (CD206), and KRT (cytokeratins) combined with digital image analysis and machine learning, we assessed the polarization spectrum of tumor-associated macrophages in 931 colorectal carcinomas. We then applied Cox proportional hazards regression to assess prognostic survival associations of intraepithelial and stromal densities of M1-like and M2-like macrophages while controlling for potential confounders, including stage and microsatellite instability status. We found that high tumor stromal density of M2-like macrophages was associated with worse cancer-specific survival, whereas tumor stromal density of M1-like macrophages was not significantly associated with better cancer-specific survival. High M1:M2 density ratio in tumor stroma was associated with better cancer-specific survival. Overall macrophage densities in tumor intraepithelial or stromal regions were not prognostic. These findings suggested that macrophage polarization state, rather than their overall density, was associated with cancer-specific survival, with M1- and M2-like macrophage phenotypes exhibiting distinct prognostic roles. These results highlight the utility of a multimarker strategy to assess the macrophage polarization at single-cell resolution within the tumor microenvironment.

Background: Myeloid cells represent an abundant yet heterogeneous cell population in the colorectal cancer microenvironment, and their roles remain poorly understood. Methods: We used multiplexed immunofluorescence combined with digital image analysis to identify CD14⁺ monocytic and CD15⁺ granulocytic cells and to evaluate their maturity (HLA-DR and CD33), immunosuppressive potential (ARG1) and proximity to cytokeratin (KRT)-positive tumor cells in 913 colorectal carcinomas. Using covariate data of 4465 incident colorectal cancers in two prospective cohort studies, the inverse probability weighting method was used with multivariable-adjusted Cox proportional hazards models to assess cancer-specific mortality according to ordinal quartiles (Q1–Q4) of myeloid cell densities. Immune cell–tumor cell proximity was measured with the nearest neighbor method and the G-cross function, which determines the likelihood of any tumor cell having at least one immune cell of the specified type within a certain radius. Results: Higher intraepithelial (Ptrend=0.0002; HR for Q4 (vs Q1), 0.48, 95% CI 0.31 to 0.76) and stromal (Ptrend <0.0001; HR for Q4 (vs Q1), 0.42, 95% CI 0.29 to 0.63) densities of CD14⁺HLA-DR⁺ cells were associated with lower colorectal cancer-specific mortality while, conversely, higher intraepithelial densities of CD14⁺HLA-DR⁻ cells were associated with higher colorectal cancer-specific mortality (Ptrend=0.0003; HR for Q4 (vs Q1), 1.78, 95% CI 1.25 to 2.55). Spatial analyses indicated that CD15⁺ cells were located closer to tumor cells than CD14⁺ cells, and CD14⁺HLA-DR⁺ cells were closer to tumor than CD14⁺HLA-DR⁻ cells (p<0.0001). The G-cross proximity measurement, evaluating the difference in the likelihood of any tumor cell being colocated with at least one CD14⁺HLA-DR⁺ cell versus CD14⁺HLA-DR⁻ cell within a 20 µm radius, was associated with lower colorectal cancer-specific mortality (Ptrend <0.0001; HR for Q4 (vs Q1), 0.37, 95% CI 0.24 to 0.5

Purpose: Although high T-cell density is a well-established favorable prognostic factor in colorectal cancer, the prognostic significance of tumor-associated plasma cells, neutrophils, and eosinophils is less well-defined. Experimental Design: We computationally processed digital images of hematoxylin and eosin (H&E)–stained sections to identify lymphocytes, plasma cells, neutrophils, and eosinophils in tumor intraepithelial and stromal areas of 934 colorectal cancers in two prospective cohort studies. Multivariable Cox proportional hazards regression was used to compute mortality HR according to cell density quartiles. The spatial patterns of immune cell infiltration were studied using the GTumor:Immune cell function, which estimates the likelihood of any tumor cell in a sample having at least one neighboring immune cell of the specified type within a certain radius. Validation studies were performed on an independent cohort of 570 colorectal cancers. Results: Immune cell densities measured by the automated classifier demonstrated high correlation with densities both from manual counts and those obtained from an independently trained automated classifier (Spearman’s ρ 0.71–0.96). High densities of stromal lymphocytes and eosinophils were associated with better cancer-specific survival [Ptrend < 0.001; multivariable HR (4th vs 1st quartile of eosinophils), 0.49; 95% confidence interval, 0.34–0.71]. High GTumor:Lymphocyte area under the curve (AUC0,20μm; Ptrend = 0.002) and high GTumor:Eosinophil AUC0,20μm (Ptrend < 0.001) also showed associations with better cancer-specific survival. High stromal eosinophil density was also associated with better cancer-specific survival in the validation cohort (Ptrend < 0.001). Conclusions: These findings highlight the potential for machine learning assessment of H&E-stained sections to provide robust, quantitative tumor-immune biomarkers for precision medicine.

Background: Histological lymphocytic reaction is regarded as an independent prognostic marker in colorectal cancer. Considering the lack of adequate statistical power, adjustment for selection bias and comprehensive tumour molecular data in most previous studies, we investigated the strengths of the prognostic associations of lymphocytic reaction in colorectal carcinoma by utilising an integrative database of two prospective cohort studies. Methods: We examined Crohn’s-like reaction, intratumoural periglandular reaction, peritumoural reaction and tumour-infiltrating lymphocytes in 1465 colorectal carcinoma cases. Using covariate data of 4420 colorectal cancer cases in total, inverse probability-weighted Cox proportional hazard regression model was used to control for selection bias (due to tissue availability) and potential confounders, including stage, MSI status, LINE-1 methylation, PTGS2 and CTNNB1 expression, KRAS, BRAF and PIK3CA mutations, and tumour neoantigen load. Results: Higher levels of each lymphocytic reaction component were associated with better colorectal cancer-specific survival (Ptrend < 0.002). Compared with cases with negative/low intratumoural periglandular reaction, multivariable-adjusted HRs were 0.55 (95% CI, 0.42–0.71) in cases with intermediate reaction and 0.20 (95% CI, 0.12–0.35) in cases with high reaction. These relationships were consistent in strata of MSI status or neoantigen loads (Pinteraction > 0.2). Conclusions: The four lymphocytic reaction components are prognostic biomarkers in colorectal carcinoma.

Accumulating evidence suggests that metabolic reprogramming has a critical role in carcinogenesis and tumor progression. The usefulness of formalin-fixed paraffin-embedded (FFPE) tissue material for metabolomics analysis as compared with fresh frozen tissue material remains unclear. LC/MS-MS–based metabolomics analysis was performed on 11 pairs of matched tumor and normal tissues in both FFPE and fresh frozen tissue materials from patients with colorectal carcinoma. Permutation t test was applied to identify metabolites with differential abundance between tumor and normal tissues. A total of 200 metabolites were detected in the FFPE samples and 536 in the fresh frozen samples. The preservation of metabolites in FFPE samples was diverse according to classes and chemical characteristics, ranging from 78% (energy) to 0% (peptides). Compared with the normal tissues, 34 (17%) and 174 (32%) metabolites were either accumulated or depleted in the tumor tissues derived from FFPE and fresh frozen samples, respectively. Among them, 15 metabolites were common in both FFPE and fresh frozen samples. Notably, branched chain amino acids were highly accumulated in tumor tissues. Using KEGG pathway analyses, glyoxylate and dicarboxylate metabolism, arginine and proline, glycerophospholipid, and glycine, serine, and threonine metabolism pathways distinguishing tumor from normal tissues were found in both FFPE and fresh frozen samples. This study demonstrates that informative data of metabolic profiles can be retrieved from FFPE tissue materials.

Background: Smoking has been associated with worse colorectal cancer patient survival and may potentially suppress the immune response in the tumor microenvironment. We hypothesized that the prognostic association of smoking behavior at colorectal cancer diagnosis might differ by lymphocytic reaction patterns in cancer tissue. Methods: Using 1474 colon and rectal cancer patients within 2 large prospective cohort studies (Nurses’ Health Study and Health Professionals Follow-up Study), we characterized 4 patterns of histopathologic lymphocytic reaction, including tumor-infiltrating lymphocytes (TILs), intratumoral periglandular reaction, peritumoral lymphocytic reaction, and Crohn’s-like lymphoid reaction. Using covariate data of 4420 incident colorectal cancer patients in total, an inverse probability weighted multivariable Cox proportional hazards regression model was conducted to adjust for selection bias due to tissue availability and potential confounders, including tumor differentiation, disease stage, microsatellite instability status, CpG island methylator phenotype, long interspersed nucleotide element-1 methylation, and KRAS, BRAF, and PIK3CA mutations. Results: The prognostic association of smoking status at diagnosis differed by TIL status. Compared with never smokers, the multivariable-adjusted colorectal cancer–specific mortality hazard ratio for current smokers was 1.50 (95% confidence interval = 1.10 to 2.06) in tumors with negative or low TIL and 0.43 (95% confidence interval = 0.16 to 1.12) in tumors with intermediate or high TIL (2-sided Pinteraction = 0.009). No statistically significant interactions were observed in the other patterns of lymphocytic reaction. Conclusions: The association of smoking status at diagnosis with colorectal cancer mortality may be stronger for carcinomas with negative or low TIL, suggesting a potential interplay of smoking and lymphocytic reaction in the colorectal cancer microenvironment.

Fusobacterium nucleatum (F. nucleatum), which has been associated with colorectal carcinogenesis, can impair anti‐tumour immunity, and actively invade colon epithelial cells. Considering the critical role of autophagy in host defence against microorganisms, we hypothesised that autophagic activity of tumour cells might influence the amount of F. nucleatum in colorectal cancer tissue. Using 724 rectal and colon cancer cases within the Nurses‘ Health Study and the Health Professionals Follow‐up Study, we evaluated autophagic activity of tumour cells by immunohistochemical analyses of BECN1 (beclin 1), MAP1LC3 (LC3), and SQSTM1 (p62) expression. We measured the amount of F. nucleatum DNA in tumour tissue by quantitative polymerase chain reaction (PCR). We conducted multivariable ordinal logistic regression analyses to examine the association of tumour BECN1, MAP1LC3, and SQSTM1 expression with the amount of F. nucleatum, adjusting for potential confounders, including microsatellite instability status; CpG island methylator phenotype; long‐interspersed nucleotide element‐1 methylation; and KRAS, BRAF, and PIK3CA mutations. Compared with BECN1‐low cases, BECN1‐intermediate and BECN1‐high cases were associated with lower amounts of F. nucleatum with odds ratios (for a unit increase in three ordinal categories of the amount of F. nucleatum) of 0.54 (95% confidence interval, 0.29–0.99) and 0.31 (95% confidence interval, 0.16–0.60), respectively (Ptrend < 0.001 across ordinal BECN1 categories). Tumour MAP1LC3 and SQSTM1 levels were not significantly associated with the amount of F. nucleatum (Ptrend > 0.06). Tumour BECN1, MAP1LC3, and SQSTM1 levels were not significantly associated with patient survival (Ptrend > 0.10). In conclusion, tumour BECN1 expression is inversely associated with the amount of F. nucleatum in colorectal cancer tissue, suggesting a possible role of autophagy in the elimination of invasive microorganisms.