Abstract 4542: Early detection of clinically significant prostate cancer at diagnosis: A prospective study using a novel panel of TMPRSS2:ETS fusion gene markers
Notice bibliographique
Résumé
Abstract Background and objectives: The fusion of TMPRSS2 gene to an oncogenic ETS transcription factor gene (e.g. ERG) is both prevalent and unique to prostate cancer (PCa). We previously reported a panel of TMPRSS2:ERG fusion subtype markers for urine-based PCa detection with high specificity and sensitivity. Our current objectives are to investigate prospectively the sensitivity of a new panel of both common and low-prevalent TMPRSS2:ETS fusion gene markers for urine-based PCa detection, and to develop individualized molecular scores to predict the risk of cancer occurrence or the risk of aggressive cancer in PSA-screened patients at diagnostic biopsy. Participants and methods: A total of 92 subjects who were PSA screened and scheduled for diagnostic biopsy were enrolled from a prostate biopsy clinic at MUHC to form a pre-biopsy cohort. This cohort was designed for prospective molecular diagnosis of PCa using a panel of molecular markers in urine. Urine was collected after attentive digital rectal exam prior to biopsy and was coded for blind laboratory tests. RNA from urine sediments was analyzed using a panel of cancer-specific markers consisting of 6 TMPRSS2:ETS (i.e. ERG, ETV1, ETV4, ETV5) fusion genes/subtypes and 5 additional markers using established qPCR methods. Results: The pathology reported 39 biopsy-positive cases from 92 patients, a 42% biopsy-positive rate. In urine test, 10 unique combinations of fusion genes/subtypes or “fusion-types” were detected in 32 of 92 (34.8%) pre-biopsy samples. We identified a novel combination of fusion-types, termed Fx (III, V, ETS), that had a sensitivity of 51.3%, a specificity of 90.6% and an odds ratio of 10.1 in detecting PCa on biopsy. By incorporating the fusion-types Fx (III, V, ETS) with urine PCA3 and serum PSA, a regression model was developed to calculate individualized molecular scores for significantly improved prediction of biopsy outcomes and for stratification of pre-biopsy patients into distinct risk groups. As such, the sensitivity of PCa detection was 81% in a high risk group but only 16% in a low risk group. On the other hand, the overexpression profiles of the same set of informative fusion markers were shown to be significantly associated with high-grade cancers (Gleason > 6) and used to develop a novel regression model to predict the risk of aggressive cancer when coupled with PSA density. We demonstrated that the molecular scores for aggressiveness were highly correlated with Gleason scores (r = 0.64, p < 0.0001), the number of positive cores (r = 0.48, p < 0.01) and the % of cancer involvement (r = 0.59, p < 0.0001) in 39 PCa patients. Conclusions: We have identified multiple alternative fusion-types very specific to clinically significant prostate cancer in urine and developed highly effective regression models to predict the risk of cancer occurrence or the risk of aggressive cancer at diagnosis. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 4542. doi:1538-7445.AM2012-4542
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 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».