A three‐protein biomarker panel assessed in diagnostic tissue predicts death from prostate cancer for men with localized disease

Severi, Gianluca; FitzGerald, Liesel M.; Muller, David C.; Pedersen, John; Longano, Anthony; Southey, Melissa C.; Hopper, John L.; English, Dallas R.; Giles, Graham G.; Mills, John

doi:10.1002/cam4.281

Cited by 21 publications

(21 citation statements)

References 31 publications

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“…MUC1 upregulation weakly correlates with shortening in disease‐free survival (DFS) and overall survival (OS) (Eminaga et al ., 2016) and associates with adverse histopathology following RP (Durrani et al ., 2015). A 3‐protein panel (AZGP1, MUC1, and p53) is related to poor prognosis in men with local PC (Severi et al ., 2014). Increases in MUC1 mRNA expression were detected in metastatic PC.…”

Section: Introductionmentioning

confidence: 99%

Construction of a set of novel and robust gene expression signatures predicting prostate cancer recurrence

Jiang

Mei

et al. 2018

Molecular Oncology

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We report here numerous novel genes and multiple new signatures which robustly predict prostate cancer (PC) recurrence. We extracted 696 differentially expressed genes relative to a reported PC signature from the TCGA dataset (n = 492) and built a 15‐gene signature (SigMuc1NW) using Elastic‐net with 10‐fold cross‐validation through analyzing their expressions at 1.5 standard deviation/SD below and 2 SD above a population mean. SigMuc1NW predicts biochemical recurrence (BCR) following surgery with 56.4% sensitivity, 72.6% specificity, and 63.24 median months disease free (MMDF) (P = 1.12e‐12). The prediction accuracy is improved with the use of SigMuc1NW's cutpoint (P = 3e‐15) and is further enhanced (sensitivity 67%, specificity 75.7%, MMDF 45.2, P = 0) when all 15 genes were analyzed through their cutpoints instead of their SDs. These genes individually associate with BCR using either SD or cutpoint as the cutoff points. Eight of 15 genes are individual risk factors after adjusting for age at diagnosis, Gleason score, surgical margin, and tumor stage. Eleven of 15 genes are novel to PC. SigMuc1NW discriminates BCR with time‐dependent AUC (tAUC) values of 76.6% at 11.5 months (76.6%–11.5 m), 73.8%‐22.3 m, 78.5%‐32.1 m, and 76.4%–48.4 m. SigMuc1NW is correlated with adverse features of PC, high Gleason scores (odds ratio/OR 1.48, P < 2e‐16), and advanced tumor stages (OR 1.33, P = 4.37e‐13). SigMuc1NW remains an independent risk factor of BCR (HR 2.44, 95% CI 1.53–3.87, P = 1.62e‐4) after adjusting for age at diagnosis, Gleason score, surgical margin, and tumor stage. In an independent PC (MSKCC) cohort (n = 140), these 15 genes were altered in PC vs normal tissue, metastatic PCs vs primary PCs, and recurrent PCs vs nonrecurrent PCs. Importantly, a 10‐gene subsignature SigMuc1NW1 predicts BCR in MSKCC (P = 3.11e‐15) and TCGA (P = 3.13e‐12); SigMuc1NW1 discriminates BCR at 18.4 m with tAUC as 82.5%. Collectively, our analyses support SigMuc1NW as a novel and robust signature in predicting BCR of PC.

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Section: Introductionmentioning

confidence: 99%

Construction of a set of novel and robust gene expression signatures predicting prostate cancer recurrence

Jiang

Mei

et al. 2018

Molecular Oncology

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“…In CaP, MUC1 over-expression has been associated with increased risk of recurrence and adverse pathological findings in patients undergoing radical prostatectomy [5, 17–19]. We have developed a multi-institutional Tissue Microarray Resource of radical prostatectomy samples for definitive validation of biomarkers of prognosis that are independent of clinical and pathological features [20].…”

Section: Introductionmentioning

confidence: 99%

MUC1 Expression by Immunohistochemistry Is Associated with Adverse Pathologic Features in Prostate Cancer: A Multi-Institutional Study

et al. 2016

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BackgroundThe uncertainties inherent in clinical measures of prostate cancer (CaP) aggressiveness endorse the investigation of clinically validated tissue biomarkers. MUC1 expression has been previously reported to independently predict aggressive localized prostate cancer. We used a large cohort to validate whether MUC1 protein levels measured by immunohistochemistry (IHC) predict aggressive cancer, recurrence and survival outcomes after radical prostatectomy independent of clinical and pathological parameters.Material and MethodsMUC1 IHC was performed on a multi-institutional tissue microarray (TMA) resource including 1,326 men with a median follow-up of 5 years. Associations with clinical and pathological parameters were tested by the Chi-square test and the Wilcoxon rank sum test. Relationships with outcome were assessed with univariable and multivariable Cox proportional hazard models and the Log-rank test.ResultsThe presence of MUC1 expression was significantly associated with extracapsular extension and higher Gleason score, but not with seminal vesicle invasion, age, positive surgical margins or pre-operative serum PSA levels. In univariable analyses, positive MUC1 staining was significantly associated with a worse recurrence free survival (RFS) (HR: 1.24, CI 1.03–1.49, P = 0.02), although not with disease specific survival (DSS, P>0.5). On multivariable analyses, the presence of positive surgical margins, extracapsular extension, seminal vesicle invasion, as well as higher pre-operative PSA and increasing Gleason score were independently associated with RFS, while MUC1 expression was not. Positive MUC1 expression was not independently associated with disease specific survival (DSS), but was weakly associated with overall survival (OS).ConclusionIn our large, rigorously designed validation cohort, MUC1 protein expression was associated with adverse pathological features, although it was not an independent predictor of outcome after radical prostatectomy.

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“…Because data showing that MUC1 and ZAG expression have opposite predictive values of similar magnitude [10,35], we substituted data from biopsies where only one We also assessed the utility of IHC expression of MUC1 and ZAG by constructing a receiver operating characteristic (ROC) curve. An ROC curve comparing the percentage of biopsy staining for MUC1 with the finding of a high-risk tumor after RPx showed the area under the curve (AUC) of 0.58 (95%CI 0.51-0.64), confirming the at least modest predictive utility of assessing the expression of this protein.…”

Section: Resultsmentioning

confidence: 99%

“…Because of the "molecular" heterogeneity of prostate cancers, IHC has the advantage of assessing protein expression throughout the tumor, in contrast to "molecular" methods which only sample a small part of any cancer [42]. In a separate, large cohort of prostate cancer patients, we have investigated a panel of protein biomarkers assessed by IHC, including MUC1 and ZAG; these data showed improved prediction of cancer-specific mortality beyond "conventional" metrics with this protein panel, including MUC1 and ZAG [35]. These data support the results of the present study into MUC1 and ZAG staining by IHC.…”

Section: Discussionmentioning

confidence: 99%

Assessing Expression of MUC1 and ZAG Protein Biomarkers in Prostate Biopsies Improves Prediction of Adverse Pathology Following Radical Prostatectomy

Durrani¹,

Waldron²,

Cherry³

et al. 2015

TOPCANJ

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Abstract:Objectives: To determine whether assessing expression of MUC1 and ZAG proteins in prostate biopsies, by immunohistochemistry, improves prediction of radical prostatectomy histopathology, which in turn predicts longer-term outcomes. Methods:We studied 231 consecutive patients managed by two experienced urologic surgeons (MF, LH). Each patient had prostate biopsies revealing cancer followed by a radical prostatectomy. Expression of MUC1 and ZAG in biopsy tissue was assessed by immunohistochemistry, masked to the radical prostatectomy histopathology. Data were analysed by Chi-square, Fischer exact test & Mann Whitney U test followed by multivariate analysis using binary logistic regression.Results: By univariate analysis, MUC1 expression in prostate biopsies was associated with worse histopathology in the radical prostatectomy specimen (p<0.023), while ZAG expression was associated with better pathology (p=0.03). By multivariate analysis decreased expression of ZAG in biopsies (p=0.02), but not MUC1 expression, improved prediction of high-risk radical prostatectomy pathology beyond conventional biopsy variables; neither MUC1 nor ZAG staining improved prediction of minimal-risk cancers.Conclusions: Assessment of ZAG expression in prostate biopsies, and possibly MUC1 expression, may improve knowledge of prostate cancers in vivo or after radical prostatectomy.

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A three‐protein biomarker panel assessed in diagnostic tissue predicts death from prostate cancer for men with localized disease

Cited by 21 publications

References 31 publications

Construction of a set of novel and robust gene expression signatures predicting prostate cancer recurrence

Construction of a set of novel and robust gene expression signatures predicting prostate cancer recurrence

MUC1 Expression by Immunohistochemistry Is Associated with Adverse Pathologic Features in Prostate Cancer: A Multi-Institutional Study

Assessing Expression of MUC1 and ZAG Protein Biomarkers in Prostate Biopsies Improves Prediction of Adverse Pathology Following Radical Prostatectomy

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