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BackgroundIntra-tumoral lymphocytes hold prognostic and predictive significance in colorectal cancer (CRC). The internationally validated Immunoscore™ predicts CRC survival risk by averaging percentile scores of tumor-associated CD3+ and CD8+ cell densities, but is limited by increased cost, intra-tumoral heterogeneity and omission of other immunologic variables of importance. To address these limitations, we sought to explore alternative prognostic markers based on CD3+ and CD8+ quantification in CRC.Methods201 resected CRCs were subjected to quantitative CD3/CD8 immunohistochemistry, from which percentile cell counts were averaged (“I-score”) in a manner analogous to the Immunoscore™. I-score and exploratory endpoints, including CD3+ and CD8+ cell densities/percentiles, CD3+-CD8+ density/percentile differences, and CD3+:CD8+ density/percentile ratios were tested for association with clinicopathologic and genomic correlates and disease-specific survival (DSS).ResultsCD3+ density among CRCs was right-skewed and potentially bimodal, while CD8+ density was right-skewed. Density and intra-tumoral variability for CD3+ and CD8+, as well as combination metrics including I-score, CD3+-CD8+ density/percentile differences, and CD3+-CD8+ density/percentile ratios showed distinct clinicopathologic and genomic associations, suggesting that each may hold unique biological significance. CD3+ density, CD8+ density/percentile, I-score and CD3+:CD8+ percentile ratio were associated with DSS; only CD3+:CD8+ percentile ratio was pTNM stage-independent on multivariable analysis. Independently, CD8+ density was as prognostic as I-score, questioning the necessity of CD3, or a combination metric.ConclusionsI-score, in our study, was closely associated with potentially confounding biologic variables such as sex, active smoking, pTNM stage, and mutations in BRAF, and MMR genes. More precise and biologically relevant biomarkers can be achieved by using data-driven CD3+/CD8+ density cutoffs and ratios, while controlling for important clinicopathologic and molecular variables in CRC. Independent validation and inclusion of other relevant immunocyte types could bring these findings closer to clinical utility in CRC.

ABSTRACT The use of sterile swabs is a convenient and common way to collect microbiome samples, and many studies have shown that the effects of room-temperature storage are smaller than physiologically relevant differences between subjects. However, several bacterial taxa, notably members of the class Gammaproteobacteria, grow at room temperature, sometimes confusing microbiome results, particularly when stability is assumed. Although comparative benchmarking has shown that several preservation methods, including the use of 95% ethanol, fecal occult blood test (FOBT) and FTA cards, and Omnigene-GUT kits, reduce changes in taxon abundance during room-temperature storage, these techniques all have drawbacks and cannot be applied retrospectively to samples that have already been collected. Here we performed a meta-analysis using several different microbiome sample storage condition studies, showing consistent trends in which specific bacteria grew (i.e., “bloomed”) at room temperature, and introduce a procedure for removing the sequences that most distort analyses. In contrast to similarity-based clustering using operational taxonomic units (OTUs), we use a new technique called “Deblur” to identify the exact sequences corresponding to blooming taxa, greatly reducing false positives and also dramatically decreasing runtime. We show that applying this technique to samples collected for the American Gut Project (AGP), for which participants simply mail samples back without the use of ice packs or other preservatives, yields results consistent with published microbiome studies performed with frozen or otherwise preserved samples. IMPORTANCE In many microbiome studies, the necessity to store samples at room temperature (i.e., remote fieldwork) and the ability to ship samples without hazardous materials that require special handling training, such as ethanol (i.e., citizen science efforts), is paramount. However, although room-temperature storage for a few days has been shown not to obscure physiologically relevant microbiome differences between comparison groups, there are still changes in specific bacterial taxa, notably, in members of the class Gammaproteobacteria, that can make microbiome profiles difficult to interpret. Here we identify the most problematic taxa and show that removing sequences from just a few fast-growing taxa is sufficient to correct microbiome profiles.