Abstract C013: Spatial immune profiling of early- and late-onset colorectal cancer
Bibliographic record
Abstract
Abstract Introduction Early-onset colorectal cancer (EOCRC) frequency has increased in the last years; elucidating the immune landscape in tumor and normal appearing colon mucosa of these patients can aid to better understand the tumor immune response and develop strategies for therapy. The purpose of this study is to evaluate if EOCRC has a distinct immune landscape compared to middle-, and late-onset CRC (MOCRC and LOCRC) and normal colonic tissues. Methods We retrospectively collected FFPE biopsies tissues from patients with CRC. Fourteen TMAs were constructed with 35 normal-appearing colon mucosa (N), 66 adenocarcinomas (AC), and 45 paired N and AC. The samples were stained with PhenoCycler Fusion (PCF) panel which contains 24 biomarkers to identify T cells (CD3, CD4, CD8, FOXP3); B cells (CD20, CD21); macrophages (CD68, CD206); NK cells (CD56); epithelial cells (CK); vascular endothelial cells (CD31); and leukocytes (CD45). The panel also contains markers for checkpoint inhibitors (PD1, PDL1, CTLA4); arginase signaling (Arg-1); adenosine pathway (CD73); activation (OX40, HLA-DR); memory (CD45RO); and cytotoxicity and proliferation (GrB, Ki67). The qptiff images from PCF platform were visualized with QuPath software. Cell segmentation was performed with the StarDist deep learning algorithm. Biomarker colocalization, cell classification and density calculation were achieved with R package Phenoptr. We defined 9 major cell lineage phenotypes: epithelial cells (CK+); Treg cells(CD45+CD3+CD4+CD8-FOXP3+); T helper cells(CD45+CD3+CD4+CD8-FOXP3-); cytotoxic T cells(CD45+CD3+CD4-CD8+); NK cells(CD45+CD3-CD56+); M2 macrophages (CD45+CD68+CD206+); other macrophages/dendritic cells (CD45+CD68+CD206-); B cells(CD45+CD20+); and endothelial cells(CD45-CD31+). The T-test was used to compare differences between AC and N samples. The two-way ANOVA was applied for multiple group comparisons, and Spearman’s rank correlation test was used for correlation analysis. Results Within paired samples, cell densities of GrB expressing cytotoxic T cells (CD45+CD3+CD8+GrB+) and memory helper T cells (CD45+CD3+CD4+CD45RO+) showed positive correlation with age increase in N. Immunosuppressive and proliferating macrophages (CD68+CD73+ and CD68+Ki67+), also had an age-related increase in AC tissue. AC tissues contained significantly higher Tregs and lower NK cells (p<0.001) than their N tissue counterparts. For un-paired samples, AC tissues contained significantly higher Tregs, T helper, cytotoxic T cells (p<0.001) and marginally lower NK cells (p=0.058) than that in N tissues. Overall, AC tissues contained significantly higher PD1+ cytotoxic and helper T cells (p<0.05) than that in N tissues. In all AC tissues, LOCRC samples contained significantly higher PDL1+ helper T cells (p=0.013) and M2 macrophages (p=0.045) than that in EOCRC or MOCRC samples. Conclusion CRC tumors display age- and onset-dependent distinct immune profile in tumor and normal colon mucosa, with EOCRC and MOCRC depleted for immunosuppressive T cells and macrophages compared to LOCRC. Citation Format: Baohua Sun, Saxon Rodriguez, Shanyu Zhang, Zuzana Lutter-Berka, Yi-Qian Nancy You, Scott Kopetz, Cara Haymaker, Luisa Maren Solis Soto. Spatial immune profiling of early- and late-onset colorectal cancer [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: The Rise in Early-Onset Cancers—Knowledge Gaps and Research Opportunities; 2025 Dec 10-13; Montreal, QC, Canada. Philadelphia (PA): AACR; Clin Cancer Res 2025;31(23_Suppl):Abstract nr C013.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".