Abstract 3019: Density of T cell subsets in colorectal cancer in relation to disease-specific survival
Bibliographic record
Abstract
Abstract Background. Prior studies have demonstrated that the overall density of T cells in colorectal tumors is favorably associated with colorectal cancer (CRC) survival; however, few studies have considered the potentially distinct roles of heterogeneous T cell subsets in different tissue regions in relation to CRC outcomes. Methods. We used data and colorectal tumor specimens from a subset of participants in three studies (total N=878). We profiled the in situ T cell landscape of CRC using digital imaging, machine learning, and a customized 9-plex multiplexed immunofluoresence panel with antibodies directed against CD3, CD4, CD8, CD45RA, CD45RO, FOXP3, and MKI67. This allowed us to determine the density of T cell subsets defined according to marker co-localization and according to tissue region (i.e., epithelial, stromal). We used Cox proportional hazards models to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for the associations of T cell subset densities in CRC with disease-specific survival, adjusting for age, sex, tumor site, microsatellite instability status, CpG island methylator phenotype status, status of somatic mutations in BRAF and KRAS, stage, and study. Results. Overall, the densities of CD3+CD4+ helper T cells and CD3+CD8+ cytotoxic T cells in CRC were favorably associated with CRC-specific survival. However, in analyses stratified by tissue region, the association of CD3+CD4+ helper T cell density with survival was limited to density in stromal regions (HR for highest vs. lowest density quartile=0.40, 95% CI: 0.26-0.63, ptrend<0.001), whereas the association with CD3+CD8+ cytotoxic T cells was limited to density in epithelial regions (HR=0.48, 95% CI: 0.31-0.76, ptrend=0.001). These significant associations persisted after mutually adjusting region-specific CD3+CD4+ and CD3+CD8+ T cell densities for each other. Associations of memory T cell subsets (i.e., CD3+CD4+CD45RO+ and CD3+CD8+ CD45RO+ T cells) with survival were more modest than associations with overall CD3+CD4+ and CD3+CD8+ T cell densities, and were similar in magnitude across stromal and epithelial tissue regions. Conclusions. The density of T cells in CRC tissue is significantly associated with CRC survival, independent of stage at diagnosis and other evaluated tumor markers; however, the T cell subsets that are associated with CRC outcomes differ according to tissue region. These findings highlight the differing roles of distinct T cell subsets in CRC with regard to cancer outcomes, and support the need for additional work identifying factors that contribute to T cell response profiles in CRC. Citation Format: Amanda I. Phipps, Jonathan Nowak, Yasutoshi Takashima, Daniel Buchanan, Andressa Dias Costa, Steven Gallinger, Jeroen Huyghe, Li Hsu, Conghui Qu, Claire Thomas, Sushma Thomas, Tomotaka Ugai, Ulrike Peters, Shuji Ogino. Density of T cell subsets in colorectal cancer in relation to disease-specific survival [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3019.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".