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A robust blood gene expression-based prognostic model for castration-resistant prostate cancer.

ABSTRACT: BACKGROUND:Castration-resistant prostate cancer (CRPC) is associated with wide variations in survival. Recent studies of whole blood mRNA expression-based biomarkers strongly predicted survival but the genes used in these biomarker models were non-overlapping and their relationship was unknown. We developed a biomarker model for CRPC that is robust, but also captures underlying biological processes that drive prostate cancer lethality. METHODS:Using three independent cohorts of CRPC patients, we developed an integrative genomic approach for understanding the biological processes underlying genes associated with cancer progression, constructed a novel four-gene model that captured these changes, and compared the performance of the new model with existing gene models and other clinical parameters. RESULTS:Our analysis revealed striking patterns of myeloid- and lymphoid-specific distribution of genes that were differentially expressed in whole blood mRNA profiles: up-regulated genes in patients with worse survival were overexpressed in myeloid cells, whereas down-regulated genes were noted in lymphocytes. A resulting novel four-gene model showed significant prognostic power independent of known clinical predictors in two independent datasets totaling 90 patients with CRPC, and was superior to the two existing gene models. CONCLUSIONS:Whole blood mRNA profiling provides clinically relevant information in patients with CRPC. Integrative genomic analysis revealed patterns of differential mRNA expression with changes in gene expression in immune cell components which robustly predicted the survival of CRPC patients. The next step would be validation in a cohort of suitable size to quantify the prognostic improvement by the gene score upon the standard set of clinical parameters.

SUBMITTER: Wang L

PROVIDER: S-EPMC4546313 | biostudies-literature | 2015 Aug

REPOSITORIES: biostudies-literature

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A robust blood gene expression-based prognostic model for castration-resistant prostate cancer.

Wang Li L Gong Yixuan Y Chippada-Venkata Uma U Heck Matthias Michael MM Retz Margitta M Nawroth Roman R Galsky Matthew M Tsao Che-Kai CK Schadt Eric E de Bono Johann J Olmos David D Zhu Jun J Oh William K WK

BMC medicine 20150821

<h4>Background</h4>Castration-resistant prostate cancer (CRPC) is associated with wide variations in survival. Recent studies of whole blood mRNA expression-based biomarkers strongly predicted survival but the genes used in these biomarker models were non-overlapping and their relationship was unknown. We developed a biomarker model for CRPC that is robust, but also captures underlying biological processes that drive prostate cancer lethality.<h4>Methods</h4>Using three independent cohorts of CR ...[more]

PMID: 26297150

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Project description:BACKGROUND:Biomarkers are urgently needed to dissect the heterogeneity of prostate cancer between patients to improve treatment and accelerate drug development. We analysed blood mRNA expression arrays to identify patients with metastatic castration-resistant prostate cancer with poorer outcome. METHODS:Whole blood was collected into PAXgene tubes from patients with castration-resistant prostate cancer and patients with prostate cancer selected for active surveillance. In stage I (derivation set), patients with castration-resistant prostate cancer were used as cases and patients under active surveillance were used as controls. These patients were recruited from The Royal Marsden Hospital NHS Foundation Trust (Sutton, UK) and The Beatson West of Scotland Cancer Centre (Glasgow, UK). In stage II (validation-set), patients with castration-resistant prostate cancer recruited from the Memorial Sloan-Kettering Cancer Center (New York, USA) were assessed. Whole-blood RNA was hybridised to Affymetrix U133plus2 microarrays. Expression profiles were analysed with Bayesian latent process decomposition (LPD) to identify RNA expression profiles associated with castration-resistant prostate cancer subgroups; these profiles were then confirmed by quantative reverse transcriptase (qRT) PCR studies and correlated with overall survival in both the test-set and validation-set. FINDINGS:LPD analyses of the mRNA expression data divided the evaluable patients in stage I (n=94) into four groups. All patients in LPD1 (14 of 14) and most in LPD2 (17 of 18) had castration-resistant prostate cancer. Patients with castration-resistant prostate cancer and those under active surveillance comprised LPD3 (15 of 31 castration-resistant prostate cancer) and LDP4 (12 of 21 castration-resistant prostate cancer). Patients with castration-resistant prostate cancer in the LPD1 subgroup had features associated with worse prognosis and poorer overall survival than patients with castration-resistant prostate cancer in other LPD subgroups (LPD1 overall survival 10·7 months [95% CI 4·1-17·2] vs non-LPD1 25·6 months [18·0-33·4]; p<0·0001). A nine-gene signature verified by qRT-PCR classified patients into this LPD1 subgroup with a very low percentage of misclassification (1·2%). The ten patients who were initially unclassifiable by the LPD analyses were subclassified by this signature. We confirmed the prognostic utility of this nine-gene signature in the validation castration-resistant prostate cancer cohort, where LPD1 membership was also associated with worse overall survival (LPD1 9·2 months [95% CI 2·1-16·4] vs non-LPD1 21·6 months [7·5-35·6]; p=0·001), and remained an independent prognostic factor in multivariable analyses for both cohorts. INTERPRETATION:Our results suggest that whole-blood gene profiling could identify gene-expression signatures that stratify patients with castration-resistant prostate cancer into distinct prognostic groups. FUNDING:AstraZeneca, Experimental Cancer Medicine Centre, Prostate Cancer Charity, Prostate Cancer Foundation.

Project description:BackgroundWe previously identified a blood RNA transcript-based model consisting of six immune or inflammatory response genes (ABL2, SEMA4D, ITGAL, C1QA, TIMP1, and CDKN1A) that was prognostic for survival in cohorts of men with castration-resistant prostate cancer (CRPC). We investigated whether inherited variation in these six genes was associated with overall survival (OS) in men with CRPC.MethodsThe test cohort comprised 600 patients diagnosed with CRPC between 1996 and 2011 at Dana-Farber Cancer Institute. Genotyping of 66 tagging single nucleotide polymorphisms (SNPs) spanning the six genes was performed on blood derived DNAs. For the top four SNPs (P < 0.05), validation was conducted in an independent cohort of 223 men diagnosed with CRPC between 2000 and 2014. Multivariable Cox regression adjusting for known prognostic factors estimated hazard ratios (HR) and 95% confidence intervals (CI) of the association of genetic variants with OS.ResultsTwo thirds of patients in both cohorts had metastases at CRPC diagnosis. Median OS from CRPC diagnosis was 3.6 (95%CI 3.3-4.0) years in the test cohort and 4.6 (95%CI 3.8-5.2) years in the validation cohort. Fifty-nine SNPs in Hardy-Weinberg equilibrium were analyzed. The major alleles of rs1318056 and rs1490311 in ABL2, and the minor alleles of rs2073917 and rs3764322 in ITGAL were associated with increased risk of death in the test cohort (adjusted-HRs 1.27-1.39; adjusted-p <0.05; false discovery rate <0.35). In the validation cohort, a similar association with OS was observed for rs1318056 in ABL2 (adjusted-HR 1.44; 95%CI 0.89-2.34) and rs2073917 in ITGAL (adjusted-HR 1.41; 95%CI 0.82-2.42). The associations did not reach statistical significance most likely due to the small sample size of the validation cohort (adjusted-p = 0.142 and 0.209, respectively). Additional eQTL analysis indicated that minor alleles of rs1318056 and rs1490311 in ABL2 are associated with a lower ABL2 expression in blood.ConclusionsThese findings corroborate our initial work on the RNA expression of genes involved in immunity and inflammation from blood and clinical outcome and suggest that germline polymorphisms in ABL2 and ITGAL may be associated with the risk of death in men with CRPC. Further studies are needed to validate these findings and to explore their functional mechanisms.

Dataset Information

A robust blood gene expression-based prognostic model for castration-resistant prostate cancer.

Publications

A robust blood gene expression-based prognostic model for castration-resistant prostate cancer.

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