Abstract 1177: Genomic characteristics and clinical outcomes of early onset colorectal cancer (EOCRC): Findings from AACR Project GENIE Biopharma Collaborative registry
Notice bibliographique
Résumé
Abstract Background: By 2030, the incidence of EOCRC is predicted to increase by more than 140%. A better understanding of the molecular features of EOCRC is needed. Methods: The AACR GENIE Biopharma Collaborative CRC 1.2-consortium dataset consists of clinical and genomic data from a cohort of CRC patients (pts) with next generation tumor sequencing (55-500 genes) from 2015 to 2017 at three academic centers. Imaging reports and medical oncology notes were retrospectively curated. EOCRC was defined as age at diagnosis < 50 years; while later onset CRC (LOCRC) as ≥ 50 years. Association with clinical variables was analyzed using Chi-Square or Fisher’s exact test. Associations with genomic alterations were analyzed using the Benjamini-Hochberg procedure for multiple testing; the associations were evaluated among the overall study population and by stage. Kaplan-Meier method was used to estimate the median overall survival (OS) and was adjusted to left truncation bias introduced by the inclusion criteria for this project. Results: A total of 1507 pts with CRC, 519 (34%) with EOCRC, were analyzed. EOCRC pts were more likely to be diagnosed with Stage IV than LOCRC (51% vs 44%, p<0.01). Left-sided primary tumors were more frequent in EOCRC (73% vs 57%, p<0.01). Among stage I-III, EOCRC was associated with longer OS compared to LOCRC (HR:1.43, 95%CI 1.07-1.91, p=0.01). Among stage IV CRC, no differences were observed in OS between EOCRC and LOCRC in a multivariate analysis including RAS/BRAF mutation (mt), MSI and liver, lung and peritoneal metastasis (HR: 1.01, 95% CI 0.8-1.28, p=0.92). The proportion of BRAF mt was higher in LOCRC (15 vs 7%, p<0.01), mainly in stage I-III (17% vs 7%, p=0.01). This association is significant after adjusting for tumor sidedness (OR: 1.77 95% CI 1.19-2.63, p<0.01). BRAF V600E mt is more frequent in LOCRC (11 vs 3%, p<0.01). APC and PI3KCA mt are more common in EOCRC, but only among right-sided tumors. There were not significant differences in copy number alterations or structural variants. APC, TP53, KRAS, BRAF and PI3KCA were analyzed according to stage. Among EOCRC, TP53 mt was more frequent in stage IV vs I-III (79 vs 70%, p=0.02). In LOCRC, both TP53 (76% vs 69%, p=0.01) and KRAS mt (47 vs 38%, p<0.01) were more frequent in stage IV vs I-III. Effect modification of the association between these genes and OS by age of onset was explored using an interaction test in stage IV and I-III. APC mt in stage I-III conferred better prognosis in EOCRC (HR 0.31 (0.18-0.51) for EOCRC; HR 0.72 (0.51-1.01) for LOCRC; interaction p<0.01). Conclusions: EOCRC does not show significant genomic differences from LOCRC except for lower frequency of BRAF mt. For right-sided tumors, APC and PI3KCA mt are more common in EOCRC. APC mt in stage I-III is associated with a better prognosis in EOCRC. Further characterization of the biology of EOCRC beyond genomic profiling is needed. Citation Format: Enrique Sanz Garcia, Eric Chen, Marios Giannakis, Gregory J. Riely, Jeremy L. Warner, Michele L. LeNoue-Newton, Jessica Weiss, Katrina Hueniken, Kenneth L. Kehl, Deborah Schrag, Andrea Cercek, Kimmie Ng, AACR GENIE BPC Core Team . Genomic characteristics and clinical outcomes of early onset colorectal cancer (EOCRC): Findings from AACR Project GENIE Biopharma Collaborative registry [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 1177.
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 | 0,002 | 0,008 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,004 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,001 |
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 ».