Association of PTEN expression with biochemical recurrence in prostate cancer: results based on previous reports

Correlation of integrated ERG/PTEN assessment with biochemical recurrence in prostate cancer

INTRODUCTION

Prostate cancer is a heterogeneous disease, with a complex molecular landscape that evolves throughout disease progression. Common alterations in genes such as ERG and PTEN have been attributed to worse prognosis. This study aimed to further examine the clinical relevance of PTEN and ERG expression in a cohort of patients with prostate cancer post radical prostatectomy.

METHODS

Tissue microarrays were constructed from 132 patients with prostate cancer from the Irish Prostate Cancer Research Consortium and University Hospital of Orebro, Sweden. Patients were divided into three groups - Group 1: biochemical recurrence, Group 2: no biochemical recurrence and Group 3: immediate progression after surgery. PTEN and ERG immunohistochemical analysis was performed and the association between expression levels and clinical parameters were compared.

RESULTS

Pathological stage pT3 tumours were more common at borderline significantly higher levels amongst patients who biochemically recurred when compared to patients who did not recur after radical prostatectomy (p = 0.05). ERG and PTEN expression levels were compared separately and concurrently across all three patient groups. Lack of ERG expression was strongly associated with immediate progression after surgery (p = 0.029). Loss of/low PTEN trended towards an association with immediate progression, however this was not statistically significant (p = 0.066).

CONCLUSION

In this study, negative ERG expression was strongly associated with immediate biochemical progression after radical prostatectomy. Moreover, a trend towards a relationship between aberrant PTEN expression and progression was observed. Additional studies with long-term follow up data may provide further clinical insight into the genomic heterogeneity in this population.

Tissue- and Liquid-Based Biomarkers in Prostate Cancer Precision Medicine

Worldwide, prostate cancer (PC) is the second-most-frequently diagnosed male cancer and the fifth-most-common cause of all cancer-related deaths. Suspicion of PC in a patient is largely based upon clinical signs and the use of prostate-specific antigen (PSA) levels. Although PSA levels have been criticised for a lack of specificity, leading to PC over-diagnosis, it is still the most commonly used biomarker in PC management. Unfortunately, PC is extremely heterogeneous, and it can be difficult to stratify patients whose tumours are unlikely to progress from those that are aggressive and require treatment intensification. Although PC-specific biomarker research has previously focused on disease diagnosis, there is an unmet clinical need for novel prognostic, predictive and treatment response biomarkers that can be used to provide a precision medicine approach to PC management. In particular, the identification of biomarkers at the time of screening/diagnosis that can provide an indication of disease aggressiveness is perhaps the greatest current unmet clinical need in PC management. Largely through advances in genomic and proteomic techniques, exciting pre-clinical and clinical research is continuing to identify potential tissue, blood and urine-based PC-specific biomarkers that may in the future supplement or replace current standard practices. In this review, we describe how PC-specific biomarker research is progressing, including the evolution of PSA-based tests and those novel assays that have gained clinical approval. We also describe alternative diagnostic biomarkers to PSA, in addition to biomarkers that can predict PC aggressiveness and biomarkers that can predict response to certain therapies. We believe that novel biomarker research has the potential to make significant improvements to the clinical management of this disease in the near future.

Precise Immunodetection of PTEN Protein in Human Neoplasia

PTEN is a major tumor-suppressor protein whose expression and biological activity are frequently diminished in sporadic or inherited cancers. PTEN gene deletion or loss-of-function mutations favor tumor cell growth and are commonly found in clinical practice. In addition, diminished PTEN protein expression is also frequently observed in tumor samples from cancer patients in the absence of PTEN gene alterations. This makes PTEN protein levels a potential biomarker parameter in clinical oncology, which can guide therapeutic decisions. The specific detection of PTEN protein can be achieved by using highly defined anti-PTEN monoclonal antibodies (mAbs), characterized with precision in terms of sensitivity for the detection technique, specificity for PTEN binding, and constraints of epitope recognition. This is especially relevant taking into consideration that PTEN is highly targeted by mutations and posttranslational modifications, and different PTEN protein isoforms exist. The precise characterization of anti-PTEN mAb reactivity is an important step in the validation of these reagents as diagnostic and prognostic tools in clinical oncology, including their routine use in analytical immunohistochemistry (IHC). Here, we review the current status on the use of well-defined anti-PTEN mAbs for PTEN immunodetection in the clinical context and discuss their potential usefulness and limitations for a more precise cancer diagnosis and patient benefit.

Identification of Potential miRNAs Biomarkers for High-Grade Prostate Cancer by Integrated Bioinformatics Analysis

The increasing number of datasets available in the GEO database offers a new approach to identify new miRNAs related to PCa. The aim of our study was to suggest a miRNA signature for the detection of high-grade PCa (Gleason score ≥ 7) using bioinformatics tools. Three mRNA datasets (GSE26022, GSE30521, GSE46602) were selected to identify the differentially expressed genes (DEGs) in high-grade PCa. Furthermore, two miRNA datasets (GSE45604, GSE46738) were analyzed to select the differentially expressed miRNAs (DEMs). Functional and pathway enrichment analysis was performed using DAVID and a protein-protein interaction network (PPI) was constructed through STRING. Besides, miRNAs which regulate hub genes were predicted using microRNA.org . A total of 973 DEGs were identified after the analyses of the mRNA datasets, enriched in key mechanisms underlying PCa development. Furthermore, we identified 10 hub genes (EGFR, VEGFA, IGF1, PIK3R1, CD44, ITGB4, ANXA1, BCL2, LPAR3, LPAR1). The most significant KEGG Pathway was PI3K-Akt signaling pathway, involved in cell proliferation and survival. Moreover, we identified 30 common miRNAs between significant DEMs and the predicted hub gene regulators. Twelve of these miRNAs (miR-1, -365, -132, -195, -133a, -133b, -200c, -339, -222, -21, -221, -708) regulate two or more hub genes identified in our study. We suggested a signature including these 12 miRNAs for high-grade PCa detection. These miRNAs have been associated with aggressive PCa, poor survival and resistance to treatment in the last years.

Emerging biomarkers in the diagnosis of prostate cancer

Prostate cancer (PCa) is the second most common cancer in men worldwide. A large proportion of PCa are latent, never destined to progress or affect the patients’ life. It is of utmost importance to identify which PCa are destined to progress and which would benefit from an early radical treatment. Prostate-specific antigen (PSA) remains the most used test to detect PCa. Its limited specificity and an elevated rate of overdiagnosis are the main problems associated with PSA testing. New PCa biomarkers have been proposed to improve the accuracy of PSA in the management of early PCa. Commercially available biomarkers such as PCA3 score, Prostate Health Index (PHI), and the four-kallikrein panel are used with the purpose of reducing the number of unnecessary biopsies and providing information related to the aggressiveness of the tumor. The relationship with PCa aggressiveness seems to be confirmed by PHI and the four-kallikrein panel, but not by the PCA3 score. In this review, we also summarize new promising biomarkers, such as PSA glycoforms, TMPRSS2:ERG fusion gene, microRNAs, circulating tumor cells, androgen receptor variants, and PTEN gene. All these emerging biomarkers could change the management of early PCa, offering more accurate results than PSA. Nonetheless, large prospective studies comparing these new biomarkers among them are required to know their real value in PCa detection and prognosis.