Abstract PR011: Early-onset colorectal cancer is characterized by transcriptional changes indicating increased epithelial-mesenchymal transition and metastatic potential
Bibliographic record
Abstract
Abstract While the overall incidence and mortality of colorectal cancer (CRC) are declining in the U.S., the rate of early-onset CRC (EO-CRC), defined as CRC diagnosis at age <50 years, has been rising 1-3% per year, making CRC the leading and second-leading cause of cancer death in men and women under age 50, respectively. Despite EO-CRC patients receiving more chemotherapy, surgery, and radiation than patients with average-onset CRC (AO-CRC), their survival rates are lower—suggesting more aggressive and/or less responsive disease. To begin uncovering the yet-unknown mechanisms behind these clinically observed differences, we generated and analyzed a single nucleus-RNA-Seq (snRNA-Seq) atlas containing 857,789 nuclei from 54 EO- and 135 AO-CRC frozen primary tumor resections, spanning eight decades of age and with 20+ samples in most decades. As expected, we found tumor sidedness to be significantly associated with age group (FDR = 0.0038, Chi-squared test), with left-sided and rectal tumors being ∼5- and 3-fold more common in EO-CRC, respectively. Other clinical variables, including sex, treatment status, microsatellite stability status, T stage, or N stage, were not found to be significantly associated with age. Our snRNA-Seq atlas contains 727,480 nuclei from malignant epithelial cells, including subsets high in LGR5, CEACAM1, MUC2, mitochondrial genes, and enteroendocrine markers, in addition to stromal, endothelial, glial/neuronal, B, T, and myeloid cell subsets. We found that even though EO- and AO-CRC tumors share similar epithelial cell subsets and gene programs on a high level, there are key differences in gene expression and cell-cell interactions. Using a pseudobulk differential expression analysis on just the microsatellite stable (MSS) tumors, with age as a continuous variable and sidedness and treatment status as covariates, we identified genes implicated in epithelial-mesenchymal transition (EMT) and metastasis (e.g., FN1, HECW1, OSMR, BMX) to have significantly higher expression (FDR<0.05) in both LGR5+ stem-like cells and MT-Ribo-hi epithelial cells from tumors from the youngest patients. Furthermore, cell-cell interaction analysis revealed more overall interactions in EO-CRC tumors, with the greatest interaction increase occurring within stromal cells. Multiple EMT-related signaling pathways showed significantly increased interactions in EO-CRC, such as FN1, NRXN, and GDF. Notably, some interactions were cell-type specific; for example, the FN1 pathway exhibited interactions in myeloid cells only in EO-CRC tumors. Finally, compositional analysis showed that EO-CRC tumors have fewer epithelial cells than AO-CRC tumors, with higher stromal cell composition relative to epithelial cells. Our work provides a large snRNA-Seq atlas of CRC tumors, with a unique cohort of EO-CRC patients and an emphasis on malignant epithelial cells. This atlas reveals changes in gene expression within tumor cells, and cell-cell interactions across cell types, that suggest an increase in EMT and metastatic potential in EO-CRC compared to AO-CRC. Citation Format: Ana C. Anderson, Caroline B. M. Porter, Shane Murphy, Toni M. Delorey, Orr Ashenberg, Kimmie Ng, Ramnik Xavier, Elizabeth Andrews, Will Tan, Alana Gerald, Jennifer Thalappillil, Marios Giannakis, Liubou Klindziuk, Bin Shao, Ewa Sicinska. Sicinska, Liat Amir-Zilberstein, Jacques Deguine, Lauren K. Brais, Will Hwang, Emily Finan. Early-onset colorectal cancer is characterized by transcriptional changes indicating increased epithelial-mesenchymal transition and metastatic potential [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 PR011.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".