Dataset Information

A harmonized resource of integrated prostate cancer clinical, -omic, and signature features.

ABSTRACT: Genomic and transcriptomic data have been generated across a wide range of prostate cancer (PCa) study cohorts. These data can be used to better characterize the molecular features associated with clinical outcomes and to test hypotheses across multiple, independent patient cohorts. In addition, derived features, such as estimates of cell composition, risk scores, and androgen receptor (AR) scores, can be used to develop novel hypotheses leveraging existing multi-omic datasets. The full potential of such data is yet to be realized as independent datasets exist in different repositories, have been processed using different pipelines, and derived and clinical features are often not provided or not standardized. Here, we present the curatedPCaData R package, a harmonized data resource representing >2900 primary tumor, >200 normal tissue, and >500 metastatic PCa samples across 19 datasets processed using standardized pipelines with updated gene annotations. We show that meta-analysis across harmonized studies has great potential for robust and clinically meaningful insights. curatedPCaData is an open and accessible community resource with code made available for reproducibility.

SUBMITTER: Laajala TD

PROVIDER: S-EPMC10322899 | biostudies-literature | 2023 Jul

REPOSITORIES: biostudies-literature

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A harmonized resource of integrated prostate cancer clinical, -omic, and signature features.

Laajala Teemu D TD Sreekanth Varsha V Soupir Alex C AC Creed Jordan H JH Halkola Anni S AS Calboli Federico C F FCF Singaravelu Kalaimathy K Orman Michael V MV Colin-Leitzinger Christelle C Gerke Travis T Fridley Brooke L BL Tyekucheva Svitlana S Costello James C JC

Scientific data 20230705 1

Genomic and transcriptomic data have been generated across a wide range of prostate cancer (PCa) study cohorts. These data can be used to better characterize the molecular features associated with clinical outcomes and to test hypotheses across multiple, independent patient cohorts. In addition, derived features, such as estimates of cell composition, risk scores, and androgen receptor (AR) scores, can be used to develop novel hypotheses leveraging existing multi-omic datasets. The full potentia ...[more]

PMID: 37407670

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Project description:BackgroundNeuroendocrine prostate cancer (NEPC) is an aggressive variant of prostate cancer that may arise de novo or in patients previously treated with hormonal therapies for prostate adenocarcinoma as a mechanism of resistance. Despite being important to recognise, the clinical features of NEPC are poorly defined and could help guide when to perform a biopsy to look for NEPC histologic transformation.MethodsWe reviewed baseline, treatment and outcome data of 87 patients with metastatic prostate cancer and tumour biopsy confirming NEPC histology. Forty-seven (54.0%) NEPC cases presented de novo, and 40 (46.0%) were therapy-related (t-NEPC). Thirty-six (41.4%) were classified as pure small-cell carcinoma, and 51 (58.6%) demonstrated mixed features with both small-cell carcinoma and adenocarcinoma present. Genomic data were available for 47 patients.ResultsThe median age at time of NEPC was 68.1 years, median prostate-specific antigen (PSA) was 1.20 ng/ml (0.14 ng/mL small-cell carcinoma, 1.55 ng/mL mixed carcinoma) and sites of metastases included bone (72.6%), lymph node (47.0%), and viscera (65.5%). Median time from adenocarcinoma to t-NEPC diagnosis was 39.7 months (range, 24.5-93.8) with a median of two lines of prior systemic therapy. Platinum chemotherapy was used to treat 57.5% of patients, with a median progression-free survival of 3.9 months. Small-cell carcinoma was associated with worse overall survival (OS) than mixed histology (8.9 months from NEPC diagnosis versus 26.1 months, P < 0.001). Median OS of de novo NEPC was shorter than that of t-NEPC (16.8 months from prostate cancer diagnosis versus 53.5 months, P = 0.043). An average PSA rise per month of ≤0.7 ng/ml before t-NEPC; elevated lactate dehydrogenase levels, RB1 and TP53 loss and liver metastases were poor prognostic features.ConclusionsWe describe the clinical features of a cohort of patients with NEPC. These characteristics may inform future diagnostic strategies.

Dataset Information

A harmonized resource of integrated prostate cancer clinical, -omic, and signature features.

Publications

A harmonized resource of integrated prostate cancer clinical, -omic, and signature features.

Similar Datasets

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