Abstract 3419: Demographic, health history, and lifestyle factors in association with biomarkers of colorectal cancer prognosis: A pilot study
Notice bibliographique
Résumé
Abstract Background/Objectives: Multiple demographic, health history, and lifestyle factors have been associated with prognosis of colorectal cancer (CRC), but the mechanisms underlying these associations remain poorly understood. Knowledge of these mechanisms could reveal new strategies to improve outcomes among CRC patients. The primary objective of this project was to explore the association of these factors, which were assessed pre-diagnostically, with expression of two biomarkers in CRC tumors, SPARC and PD-L1, for which lower and higher levels of expression, respectively, have been previously associated with poorer CRC prognosis. Methods: Participants were drawn from the British Columbia Generations Project (BCGP). At the time of recruitment, they completed a detailed questionnaire that ascertained demographic factors (e.g., biological sex and household income), health history (e.g., personal history of CRC screening), and lifestyle factors (daily fruit and vegetable consumption and alcohol consumption). Formalin-fixed paraffin-embedded blocks (FFPE) with adequate volumes of tumor were obtained for 49 incident CRC cases diagnosed within the BCGP. Cores were extracted from the blocks to create tumor tissue microarrays (TMAs). Slides created from thin sections of the TMAs were stained with SPARC and PD-L1 antibodies and then imaged and analyzed to calculate H-scores as measures of expression in both epithelial and non-epithelial tissues. Linear regression analyses were conducted to evaluate associations between the various factors and ln-transformed H-scores. Results: Compared to non-smokers, smokers, on average, had 47% lower SPARC H-scores (p=0.05) in the epithelial tissues of their CRC tumors. Individuals with incomes higher than $74,999/year had 33% higher SPARC H-scores (p=0.04) in their CRC tumor non-epithelial tissues than those who earned less than $74 999/year. Females had 2.8-fold greater PD-L1 H-scores (p=0.005) in their CRC tumor epithelial tissues than males. Compared to those without a history of CRC screening, those with a history of CRC screening had 2.2 and 2.0-fold greater PD-L1 H-scores in their epithelial and non-epithelial CRC tumor tissues, respectively. Conclusion: Larger-scale studies with prognostic data are needed to confirm our findings, but our results suggest that differences in the expression of SPARC and PDL-1 may contribute to the previously observed impacts of some demographic, healthy history, and lifestyle factors on CRC prognosis. Citation Format: Umaimah Zanif, Isabella Tai, Stephen Yip, Sindy Babinszky, Katy Milne, Peter Watson, Rachel Murphy, Parveen Bhatti. Demographic, health history, and lifestyle factors in association with biomarkers of colorectal cancer prognosis: A pilot study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3419.
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 | 0,001 | 0,002 |
| 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 | 0,001 | 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) | 0,004 | 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 ».