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YB-1 and MTA1 protein levels and not DNA or mRNA alterations predict for prostate cancer recurrence.

Sheridan CM, Grogan TR, Nguyen HG, Galet C, Rettig MB, Hsieh AC, Ruggero D - Oncotarget (2015)

Bottom Line: Remarkably, protein abundance, but not genomic or transcriptional alterations of YB-1 and MTA1, is predictive of disease recurrence, exhibiting a dose-dependent effect on time to PSA recurrence, an indicator of tumor relapse.Importantly, YB-1 and MTA1 protein levels significantly increase the predictive capacity of a clinical model for prostate cancer recurrence.These findings demonstrate that protein abundance of YB-1 and MTA1, irrespective of DNA or mRNA status, can predict for prostate cancer relapse and uncover a vast underappreciated repository of biomarkers regulated at the level of protein expression.

View Article: PubMed Central - PubMed

Affiliation: Department of Urology, University of California, San Francisco, CA, USA.

ABSTRACT
Attempts to identify biomarkers to detect prostate tumorigenesis, and thus minimize prostate cancer progression and inform treatment decisions have primarily focused on alterations at the DNA and mRNA levels, ignoring alterations at the level of protein synthesis control. We have previously shown that the PI3K-AKT-mTOR pathway, frequently deregulated in prostate cancer, specifically induces the synthesis of proteins that contribute to metastasis, most notably YB-1 and MTA1, without altering mRNA levels thereby demonstrating the importance of translation control in driving the expression of these genes in cancer.Here, we analyze genomic sequencing and mRNA expression databases, as well as protein expression employing an annotated tissue microarray generated from 332 prostate cancer patients with 15 years of clinical follow-up to determine the combined prognostic capability of YB-1 and MTA1 alterations in forecasting prostate cancer outcomes. Remarkably, protein abundance, but not genomic or transcriptional alterations of YB-1 and MTA1, is predictive of disease recurrence, exhibiting a dose-dependent effect on time to PSA recurrence, an indicator of tumor relapse. Moreover, high protein levels of YB-1 and MTA1 are associated with a 3-fold increased risk for requiring future hormone therapy or radiation therapy. Importantly, YB-1 and MTA1 protein levels significantly increase the predictive capacity of a clinical model for prostate cancer recurrence. These findings demonstrate that protein abundance of YB-1 and MTA1, irrespective of DNA or mRNA status, can predict for prostate cancer relapse and uncover a vast underappreciated repository of biomarkers regulated at the level of protein expression.

No MeSH data available.


Related in: MedlinePlus

The addition of the MTA1 and YB-1 biomarkers to clinical factors including the Gleason score can improve upon the predictive capacity of a clinical nomogram to forecast PSA progression after radical prostatectomy(A) Nomogram to predict 1-year and 2-year recurrence free probability. (B) C-statistics demonstrating the predictive capacity of the nomogram with clinical factors alone, clinical factors + MTA1, clinical factors + YB-1, and clinical factors + MTA1 + YB-1.
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Figure 3: The addition of the MTA1 and YB-1 biomarkers to clinical factors including the Gleason score can improve upon the predictive capacity of a clinical nomogram to forecast PSA progression after radical prostatectomy(A) Nomogram to predict 1-year and 2-year recurrence free probability. (B) C-statistics demonstrating the predictive capacity of the nomogram with clinical factors alone, clinical factors + MTA1, clinical factors + YB-1, and clinical factors + MTA1 + YB-1.

Mentions: Next, using the clinical data from the 332 patient tissue microarray database, we generated a nomogram composed of Gleason score, PSA level, extracapsular extension, surgical margin status, and seminal vesicle invasion for 1- and 2-year PSA recurrence-free probability. Using this tool, we asked if the addition of the YB-1 and MTA1 biomarkers could increase the predictive capacity of a clinically based nomogram. We evaluated the prognostic ability of the model by calculating the C-statistic, which ranges from 0.5 (not predictive) to 1 (perfectly predictive). The clinical nomogram alone had a C-statistic of 0.69 (P = 2.7e-29) (Figures 3A and 3B). Adding MTA1 or YB-1 protein levels individually to the clinical nomogram increased the C-statistic to 0.71 and 0.73, which represents a 6% (P = 1.1e-28) or 12% (P = 3.2e-28) increase in predictive capacity of the nomogram, respectively (Figure 3B). Remarkably, by combining both biomarkers in the model, the C-statistic rose to 0.76, which is a 22% (P = 6.3e-43) increase in the predictive capacity of the nomogram compared to using clinical factors alone, including the Gleason score (Figure 3B). Thus, a combinatorial approach, which includes clinical factors and translationally regulated biomarkers such as YB-1 and MTA1, represents a potentially powerful method to predict for future prostate cancer behavior after a prostatectomy.


YB-1 and MTA1 protein levels and not DNA or mRNA alterations predict for prostate cancer recurrence.

Sheridan CM, Grogan TR, Nguyen HG, Galet C, Rettig MB, Hsieh AC, Ruggero D - Oncotarget (2015)

The addition of the MTA1 and YB-1 biomarkers to clinical factors including the Gleason score can improve upon the predictive capacity of a clinical nomogram to forecast PSA progression after radical prostatectomy(A) Nomogram to predict 1-year and 2-year recurrence free probability. (B) C-statistics demonstrating the predictive capacity of the nomogram with clinical factors alone, clinical factors + MTA1, clinical factors + YB-1, and clinical factors + MTA1 + YB-1.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4480693&req=5

Figure 3: The addition of the MTA1 and YB-1 biomarkers to clinical factors including the Gleason score can improve upon the predictive capacity of a clinical nomogram to forecast PSA progression after radical prostatectomy(A) Nomogram to predict 1-year and 2-year recurrence free probability. (B) C-statistics demonstrating the predictive capacity of the nomogram with clinical factors alone, clinical factors + MTA1, clinical factors + YB-1, and clinical factors + MTA1 + YB-1.
Mentions: Next, using the clinical data from the 332 patient tissue microarray database, we generated a nomogram composed of Gleason score, PSA level, extracapsular extension, surgical margin status, and seminal vesicle invasion for 1- and 2-year PSA recurrence-free probability. Using this tool, we asked if the addition of the YB-1 and MTA1 biomarkers could increase the predictive capacity of a clinically based nomogram. We evaluated the prognostic ability of the model by calculating the C-statistic, which ranges from 0.5 (not predictive) to 1 (perfectly predictive). The clinical nomogram alone had a C-statistic of 0.69 (P = 2.7e-29) (Figures 3A and 3B). Adding MTA1 or YB-1 protein levels individually to the clinical nomogram increased the C-statistic to 0.71 and 0.73, which represents a 6% (P = 1.1e-28) or 12% (P = 3.2e-28) increase in predictive capacity of the nomogram, respectively (Figure 3B). Remarkably, by combining both biomarkers in the model, the C-statistic rose to 0.76, which is a 22% (P = 6.3e-43) increase in the predictive capacity of the nomogram compared to using clinical factors alone, including the Gleason score (Figure 3B). Thus, a combinatorial approach, which includes clinical factors and translationally regulated biomarkers such as YB-1 and MTA1, represents a potentially powerful method to predict for future prostate cancer behavior after a prostatectomy.

Bottom Line: Remarkably, protein abundance, but not genomic or transcriptional alterations of YB-1 and MTA1, is predictive of disease recurrence, exhibiting a dose-dependent effect on time to PSA recurrence, an indicator of tumor relapse.Importantly, YB-1 and MTA1 protein levels significantly increase the predictive capacity of a clinical model for prostate cancer recurrence.These findings demonstrate that protein abundance of YB-1 and MTA1, irrespective of DNA or mRNA status, can predict for prostate cancer relapse and uncover a vast underappreciated repository of biomarkers regulated at the level of protein expression.

View Article: PubMed Central - PubMed

Affiliation: Department of Urology, University of California, San Francisco, CA, USA.

ABSTRACT
Attempts to identify biomarkers to detect prostate tumorigenesis, and thus minimize prostate cancer progression and inform treatment decisions have primarily focused on alterations at the DNA and mRNA levels, ignoring alterations at the level of protein synthesis control. We have previously shown that the PI3K-AKT-mTOR pathway, frequently deregulated in prostate cancer, specifically induces the synthesis of proteins that contribute to metastasis, most notably YB-1 and MTA1, without altering mRNA levels thereby demonstrating the importance of translation control in driving the expression of these genes in cancer.Here, we analyze genomic sequencing and mRNA expression databases, as well as protein expression employing an annotated tissue microarray generated from 332 prostate cancer patients with 15 years of clinical follow-up to determine the combined prognostic capability of YB-1 and MTA1 alterations in forecasting prostate cancer outcomes. Remarkably, protein abundance, but not genomic or transcriptional alterations of YB-1 and MTA1, is predictive of disease recurrence, exhibiting a dose-dependent effect on time to PSA recurrence, an indicator of tumor relapse. Moreover, high protein levels of YB-1 and MTA1 are associated with a 3-fold increased risk for requiring future hormone therapy or radiation therapy. Importantly, YB-1 and MTA1 protein levels significantly increase the predictive capacity of a clinical model for prostate cancer recurrence. These findings demonstrate that protein abundance of YB-1 and MTA1, irrespective of DNA or mRNA status, can predict for prostate cancer relapse and uncover a vast underappreciated repository of biomarkers regulated at the level of protein expression.

No MeSH data available.


Related in: MedlinePlus