Abstract PR011: Early-onset colorectal cancer is characterized by transcriptional changes indicating increased epithelial-mesenchymal transition and metastatic potential
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,008 | 0,003 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».