Abstract 3509: Racial variation in molecularly-defined prostate cancer subtypes
Notice bibliographique
Résumé
Abstract Background: Socioeconomic, environmental, and healthcare utilization factors are likely drivers of the persistent prostate cancer disparities between African-American (AA) and European-American (EA) men. Tumor molecular heterogeneity may also contribute, and Eurocentric studies and initiatives have the potential to widen disparities through the development of prognostic signatures and targeted therapeutics that do not account for genetic diversity. Methods: The Decipher Genomics Resource Information Database (GRID) contains tumor mRNA expression and clinical data generated through use of the Decipher test to predict prostate cancer prognosis. We matched 426 AA and 426 EA patients with localized prostate cancer using a propensity score accounting for age and tumor clinicopathological factors. We then applied five validated prostate cancer molecular subtype classifiers by Alshalalfa et al (Neuroendocrine, Adenocarcinoma), Kamoun et al (S1-S3), Tomlins et al(ERG+, ETS+, SPINK1+, ERG-/ETS-/SPINK1-), You et al (PCS1-PCS3), and Zhang et al (Basal, Luminal) to assign tumor subtypes. Heterogeneity in subtype frequency by self-identified race (SIR) was evaluated using chi-squared tests. Differences in subtype prognostic value by SIR were evaluated in logistic regression models using a high Decipher tumor genomic risk score of ≥0.6 as a surrogate for higher risk of metastases. Results: AA men were more likely to have a Decipher score ≥0.6 than EA men (25.6% vs. 20.0%, p<0.001). Subtypes reflecting SPINK1 overexpression were more frequent among AA men, while subtypes reflecting the presence of ERG or ETS fusions were more common among EA men (all p<0.001). The distribution of Basal vs. Luminal tumors did not differ by SIR (p=0.19), nor did Neuroendocrine vs. Adenocarcinoma (p=0.14). Across SIR groups, the ERG+, Basal, PCS1, and Neuroendocrine tumors were the most likely to have high Decipher scores, while the S2 subtype was associated with a lower Decipher score. However, associations between subtypes and the Decipher score differed by SIR for three of five classifiers. The ERG+ subtype (relative to ERG-/ETS-/SPINK1-) was associated with a higher risk of metastases in AA men (OR=3.18 95% CI 1.59-6.37), but not in EA men (OR=0.69, 95% CI 0.39-1.24, p-het=0.002). A similar pattern was observed in the PCS3 subtype, which is also characterized by the presence of ERG or ETS fusions (p-het=0.003). The hypothesized low-risk S2 subtype was associated with lower risk of metastases (relative to S1) among EA men (OR=0.31, 95% CI 0.15-0.61), but not among AA men (OR=0.99, 95% CI 0.39-2.49, p-het=0.001). The Zhang (p-het=0.36) and Alshalalfa (p-het=0.85) classifiers did not show heterogeneous associations between subtype and Decipher score by SIR. Conclusions: Prostate cancer molecular subtype distributions differed by SIR, with AA men generally more likely to have aggressive subtypes across classification schemes. Furthermore, AA and EA had a heterogeneous risk of metastases (defined by Decipher genomic risk score) for several subtypes. Further research is needed to better define subtyping classifiers and the prognostic value thereof in AA men. Citation Format: Kevin H. Kensler, Mohamed Alshalalfa, Brandon A. Mahal, Yang Liu, Elai Davicioni, Shivanshu Awasthi, Kosj Yamoah, Timothy R. Rebbeck. Racial variation in molecularly-defined prostate cancer subtypes [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 3509.
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 | 0,001 | 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) | 0,005 | 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 ».