Abstract C011: Distinct peripheral immune signatures in early-onset colorectal cancer reveal candidate biomarkers for risk stratification
Notice bibliographique
Résumé
Abstract Colorectal cancer (CRC) is the second leading cause of cancer-related mortality worldwide. While screening strategies have reduced incidence in older adults, early-onset CRC (EOCRC; <50 years) continues to rise. The Immunoscore, based on intratumoral T cell density, is a validated biomarker of recurrence and survival. However, little is known about peripheral immune alterations in EOCRC, which may provide complementary information for early detection and prognostication. We conducted an immune profiling study in age-defined cohorts of EOCRC and late-onset CRC (LOCRC) patients, matched by sex and tumor location. Peripheral blood mononuclear cells (PBMCs) and plasma were analyzed by multiparametric flow cytometry and Luminex to assess T cell polarization, innate-like lymphocytes, cytokine secretion, and metabolic activity. HLA typing was performed with HLA-ABCDRB1DQ RealAmp kit. Our analyses revealed striking differences in systemic immunity between EOCRC and LOCRC. EOCRC patients displayed a skewing toward proinflammatory Th9/Th17 and Th22 responses, accompanied by enhanced IL-13 secretion and increased NKT-like cells, whereas LOCRC was characterized by reduced effector activity and hallmarks of immune aging. In addition, metabolic profiling of PBMCs identified increased glucose uptake in EOCRC, supporting a heightened but potentially inefficient immune activation state. Plasma chemokine analyses further pointed to distinct cytokine milieus discriminating the two age groups. Notably, alleles within the B15/B17/B5 group were overrepresented in EOCRC compared to LOCRC and controls, suggesting a genetic contribution to early-onset disease. This enrichment may reflect distinct HLA-driven antigen presentation patterns that favor chronic immune activation or inefficient tumor surveillance in younger patients, thereby contributing to EOCRC pathogenesis. In conclusion, EOCRC is associated with a unique systemic immune profile that contrasts with the immunosenescence observed in LOCRC. Key alterations in Th22, CD8+ Tγδ cells, and NKT-like cells, together with enrichment of specific HLA-B allele groups that may modulate antigen presentation and anti-tumor immunity, emerge as candidate biomarkers to refine Immunoscore-based stratification. These candidates could help guide the development of more specific immunotherapeutic approaches for younger CRC patients. Overall, our results support a model in which both immune dysregulation and inherited genetic predisposition cooperate to shape EOCRC, supporting the development of risk stratification and preventive strategies based on HLA typing. Citation Format: Maria Gonzalez-Sanmartin, Clara Sanchez-Menendez, Valentina Leguizamon, Elena Mateos, Edurne Alvaro, Gonzalo Sanz, Jorge Martinez Laso, Montserrat Torres, Mayte Coiras, Jose Perea. Distinct peripheral immune signatures in early-onset colorectal cancer reveal candidate biomarkers for risk stratification [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 C011.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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 tête enseignante, 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 ».