Abstract B098: Genomic variations associated with prostate cancer in large cohort of African American men
Notice bibliographique
Résumé
Abstract Background: Racial disparities in prostate cancer (PCa) incidence and mortality are well known. PCa is known to be more aggressive in African American men (AAM) compared to European American men (EAM) in terms of higher incidence and mortality rates. Here we validate a tumor gene expression pan-cancer race model in men with PCa and further characterize genomic differences that may contribute to disparate clinical outcomes. Methods: We obtained deidentified genome-wide expression profiles from clinical use of the Decipher RP test in 9,953 men from the GRID registry database. A subset of men (n=313) had known race status. A pan-cancer race model, developed to predict patient AAM race from analysis of gene expression patterns in 4,162 tumors from retrospective cohorts with known race status, was applied to the prospective cohort for race prediction. Hallmarks of cancer, immune modulators, AR activity, and prognostic gene signatures available in the GRID were used to gain a molecular perspective on PCa racial disparities. Results: The race model was independently validated in the subset of men with known race and had an AUC of 0.98 for differentiating AAM from EAM. The model was then applied to the 9,640 GRID patients with unknown race status and classified 6,831 as EAM, 1,058 as AAM, and 1,751 as having indeterminate race. Characterizing the molecular subtypes, we found known and predicted AAM to be enriched with SPINK1+ tumors (21% and 24%, respectively) compared to predicted EAM (8%). In contrast, while ERG+ was found 22% and 19% in known and predicted AAM, respectively, compared to 46% in predicted EAM. Based on PAM50 prostate cancer classifier, 61% of AAM were classified as basal-like tumors, whereas 41% were basal-like in EAM. Similarly, 28% of AAM had low AR-A while only 11% of EAM had low AR-A. AAM tumors had higher levels of immune infiltration signatures as well as higher scores for inflammatory and interferon gamma responses, NF-KB mediated tumor necrosis factor (TNF) activity, and interleukin 6 (IL6) signaling activity scores. AAM had lower DNA repair glycolysis scores compared to EAM. Conclusion: Known and predicted AAM were enriched with SPINK1+ tumors, higher immune infiltration and activation but lower ERG+, DNA repair, and AR activity tumors. Using such large GRID data with known race, we will further understand the underlying causes associated with prostate cancer racial disparities. Citation Format: Walter Rayford, Jennifer Jordan, Mandeep Takhar, Mohammed Alshalalfa, Darlene Dai, Nicholas Erho, Mark D. Greenberger, Elai Davicioni. Genomic variations associated with prostate cancer in large cohort of African American men [abstract]. In: Proceedings of the AACR Special Conference: Prostate Cancer: Advances in Basic, Translational, and Clinical Research; 2017 Dec 2-5; Orlando, Florida. Philadelphia (PA): AACR; Cancer Res 2018;78(16 Suppl):Abstract nr B098.
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 | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 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 ».