Evaluation of protein biomarkers of prostate cancer aggressiveness

Abstract

Background: Prognostic multibiomarker signatures in prostate cancer (PCa) may improve patient management and provide a bridge for developing novel therapeutics and imaging methods. Our objective was to evaluate the association between expression of 33 candidate protein biomarkers and time to biochemical failure (BF) after prostatectomy.

Methods: PCa tissue microarrays were constructed representing 160 patients for whom clinicopathologic features and follow-up data after surgery were available. Immunohistochemistry for each of 33 proteins was quantified using automated digital pathology techniques. Relationships between clinicopathologic features, staining intensity, and time to BF were assessed. Predictive modeling using multiple imputed datasets was performed to identify the top biomarker candidates.

Results: In univariate analyses, lymph node positivity, surgical margin positivity, non-localized tumor, age at prostatectomy, and biomarkers CCND1, HMMR, IGF1, MKI67, SIAH2, and SMAD4 in malignant epithelium were significantly associated with time to BF. HMMR, IGF1, and SMAD4 remained significantly associated with BF after adjusting for clinicopathologic features while additional associations were observed for HOXC6 and MAP4K4 following adjustment. In multibiomarker predictive models, 3 proteins including HMMR, SIAH2, and SMAD4 were consistently represented among the top 2, 3, 4, and 5 most predictive biomarkers, and a signature comprised of these proteins best predicted BF at 3 and 5 years.

Conclusions: This study provides rationale for investigation of HMMR, HOXC6, IGF1, MAP4K4, SIAH2, and SMAD4 as biomarkers of PCa aggressiveness in larger cohorts.

Figure 1

Immunohistochemistry of candidate biomarkers in prostate cancer. Representative immunohistochemical staining of ACPP, ADAM9, ALDH1A2, CASR, CCND1, CCPG1, CD34, CD44, CD44v6, CHGA, CHMP1A, EI24, ENO2, GADD45B, HA, HAS2, HES6, HMMR, HOXC6, HYAL1, IGF1, IQCK, MAP4K4, MKI67, PAGE4, PLIN2, PTEN, SIAH2, SMAD4, SOX9, SPP1, SYP, and TP53 from prostate cancer tissue microarrays. Scale bar represents 50 μm.

Figure 2

Image analysis workflow for immunohistochemical staining quantification. (A-D) Prostate cancer tissue microarrays were stained by immunohistochemistry. The method of image analysis performed independently for each marker was dependent on the staining pattern: default malignant epithelial area (A), malignant epithelial nuclei (B), tumor-associated stromal area (C), or tumor-associated vasculature (D). (E-G) Genie Histology Pattern Recognition software (Aperio) subclassified tumor areas into malignant epithelium (dark blue), stroma (yellow), and glass (light blue). (H) Markers with heterogeneous positivity were evaluated by Color Deconvolution (Aperio) to quantify staining within malignant epithelial areas. (I) Markers with predominantly nuclear localization (CCND1, MKI67, SIAH2, and TP53) were evaluated by the Nuclear algorithm (Aperio) to quantify staining within nuclei of malignant epithelium. (J) Markers with significant stromal positivity (EI24 and HA) were evaluated by Color Deconvolution (Aperio) to quantify staining within tumor-associated stroma. (K) The microvascular marker (CD34) was evaluated by the Microvessel algorithm (Aperio) to quantify additional metrics including average vessel area, average vessel perimeter, average lumen area, average vascular area, and microvessel density. Scale bars represent 50 μm.

Figure 3

Kaplan-Meier curve demonstrating the time to biochemical failure for the sample population.