Abstract
Prostate cancer continues to be a major cause of morbidity and mortality in men, but a method for accurate prognosis in these patients is yet to be developed. The recent discovery of altered endosomal biogenesis in prostate cancer has identified a fundamental change in the cell biology of this cancer, which holds great promise for the identification of novel biomarkers that can predict disease outcomes. Here we have identified significantly altered expression of endosomal genes in prostate cancer compared to non-malignant tissue in mRNA microarrays and confirmed these findings by qRT-PCR on fresh-frozen tissue. Importantly, we identified endosomal gene expression patterns that were predictive of patient outcomes. Two endosomal tri-gene signatures were identified from a previously published microarray cohort and had a significant capacity to stratify patient outcomes. The expression of APPL1, RAB5A, EEA1, PDCD6IP, NOX4 and SORT1 were altered in malignant patient tissue, when compared to indolent and normal prostate tissue. These findings support the initiation of a case-control study using larger cohorts of prostate tissue, with documented patient outcomes, to determine if different combinations of these new biomarkers can accurately predict disease status and clinical progression in prostate cancer patients.
Highlights
Prostate cancer is the second most commonly diagnosed cancer in males [1], and the incidence of this disease is predicted to double globally by 2030 (WCRF prostate cancer statistics; http://globocan.iarc.fr, accessed May 2014)
The expression of RAB4A was significantly decreased in primary prostate cancer when compared to prostatic intraepithelial neoplasia (PIN) tissue (P ≤ 0.05; Figure 1) and there was a significant reduction of RAB4A expression in metastatic prostate tissue when compared to both non-malignant prostate cancer (P ≤ 0.01) and PIN tissue (P ≤ 0.0001; Figure 1)
Cathepsin B (CTSB) expression was significantly reduced in both primary cancer tissue and metastatic cancer tissue when compared to non-malignant prostate tissue (P ≤ 0.01; Figure 1)
Summary
Prostate cancer is the second most commonly diagnosed cancer in males [1], and the incidence of this disease is predicted to double globally by 2030 (WCRF prostate cancer statistics; http://globocan.iarc.fr, accessed May 2014). The PSA biomarker neither discriminates between patients who are at a higher risk of progressive disease/mortality and those who have a more favorable prognosis, nor can it adequately distinguish between prostate cancer and benign pathologies [2, 3]. Gene expression profiles that compare prostate cancer to benign prostatic hyperplasia (BPH), prostatic intraepithelial neoplasia (PIN) and normal prostate tissue have been generated from microarray data [4]. This approach has been utilized to identify the enzyme α-methylacyl-CoA racemase (AMACR), which was highly expressed in prostate cancer and may have value as a prognostic marker for the disease [7]. Signatures incorporating multiple genes may be required to improve the accuracy of prostate cancer prognosis
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