The Role of Biomarkers and Genetics in the Diagnosis of Prostate Cancer

Molecular Pathology of Prostate Cancer

Molecular profiling studies have shed new light on the complex biology of prostate cancer. Genomic studies have highlighted that structural rearrangements are among the most common recurrent alterations. In addition, both germline and somatic mutations in DNA repair genes are enriched in patients with advanced disease. Primary prostate cancer has long been known to be multifocal, but recent studies demonstrate that a large fraction of prostate cancer shows evidence of multiclonality, suggesting that genetically distinct, independently arising tumor clones coexist. Metastatic prostate cancer shows a high level of morphologic and molecular diversity, which is associated with resistance to systemic therapies. The resulting high level of intratumoral heterogeneity has important implications for diagnosis and poses major challenges for the implementation of molecular studies. Here we provide a concise review of the molecular pathology of prostate cancer, highlight clinically relevant alterations, and discuss opportunities for molecular testing.

Predictive value of standard serum markers for bone metastases in prostate cancer

Background

The early detection of bone metastases is very important in prostate cancer follow-up. This study aimed to compare conventional tumor markers, namely free prostate-specific antigen (free PSA), total prostate-specific antigen (total PSA), free PSA/total PSA ratio, alkaline phosphatase (ALP) values, Gleason scores and 99 m Tc-MDP bone scintigraphy findings in the prediction of bone metastases in prostate cancer.

Methods

In total, 175 patients with prostate cancer who underwent whole-body bone scintigraphy were included in the study. All selected scintigraphic studies were reprocessed. Free PSA, total PSA, free PSA/total PSA ratio, alkaline phosphatase (ALP) values and Gleason scores of patients were recorded.

Results

The results of our study show that the presence of bone metastasis correlates very weakly with free PSA/total PSA ratio (rho = 0.179), weakly with total PSA (rho = 0.318) and Gleason score (rho = 0.382), moderately with ALP (rho = 0.539), free PSA (0.416). Only ALP variable had a diagnostic value and ALP cutoff value was 76.50 IU/L, with 80% sensitivity and 82.1% specificity.

Conclusion

According to the results of our study; the free PSA, total PSA, free PSA/total PSA ratio and Gleason score values were not considered as a reliable parameter in the prostate cancer cases follow-up for bone metastasis development. Only ALP had a diagnostic value and ALP cutoff value was 76.50 IU / L with 80% sensitivity and 82.1% specificity in predicting bone metastases in prostate cancer.

The auxiliary diagnostic value of prostate-specific antigen and α-methylacyl-CoA racemase in prostate cancer

Prostate cancer (PCa) is one of the most common types of malignant tumor, which places a major burden on the health of men, worldwide. A prerequisite to ensure good treatment outcomes for patients with PCa is an accurate diagnosis. The present study aimed to investigate the diagnostic value of prostate-specific antigen (PSA) and α-methylacyl-CoA racemase (P504S) in PCa, using the tumor-associated immunolabels. In total, clinical data was collected from 125 patients undergoing prostate biopsy or surgery between January 2015 and September 2019, and stratified into: PCa (45), benign prostatic hyperplasia (BPH) (60) and unconfirmed diagnosis (20). Immunohistochemistry analysis was performed to assess PSA and P504S expression levels in each group compared with that in the controls (the normal tissue in each group was the internal control). The results demonstrated that the expression level of P504S was significantly higher in the PCa group compared with that in the BPH group. Furthermore, no significant association was observed in the PCa group between PSA and P504S expression levels, and the Gleason grading groups. A total of 20 unconfirmed diagnoses was verified via PSA/P504S. Taken together, the results suggest that combination PSA and P504S have a positive effect in identifying prostate cancer. However, PSA and P504S still have limitations in their diagnosis and the final results need to be carefully and comprehensively analyzed, thus further studies are required to determine their diagnostic values.

Immunohistochemical biomarker validation in highly selective needle biopsy microarrays derived from mpMRI-characterized prostates

INTRODUCTION

Diagnosing prostate cancer routinely involves tissue biopsy and increasingly image guided biopsy using multiparametric MRI (mpMRI). Excess tissue after diagnosis can be used for research to improve the diagnostic pathway and the vertical assembly of prostate needle biopsy cores into tissue microarrays (TMAs) allows the parallel immunohistochemical (IHC) validation of cancer biomarkers in routine diagnostic specimens. However, tissue within a biopsy core is often heterogeneous and cancer is not uniformly present, resulting in needle biopsy TMAs that suffer from highly variable cancer detection rates that complicate parallel biomarker validation.

MATERIALS AND METHODS

The prostate cores with the highest tumor burden (in terms of Gleason score and/or maximum cancer core length) were obtained from 249 patients in the PICTURE trial who underwent transperineal template prostate mapping (TPM) biopsy at 5 mm intervals preceded by mpMRI. From each core, 2 mm segments containing tumor or benign tissue (as assessed on H&E pathology) were selected, excised and embedded vertically into a new TMA block. TMA sections were then IHC-stained for the routinely used prostate cancer biomarkers PSA, PSMA, AMACR, p63, and MSMB and assessed using the h-score method. H-scores in patient matched malignant and benign tissue were correlated with the Gleason grade of the original core and the MRI Likert score for the sampled prostate area.

RESULTS

A total of 2240 TMA cores were stained and IHC h-scores were assigned to 1790. There was a statistically significant difference in h-scores between patient matched malignant and adjacent benign tissue that is independent of Likert score. There was no association between the h-scores and Gleason grade or Likert score within each of the benign or malignant groups.

CONCLUSION

The construction of highly selective TMAs from prostate needle biopsy cores is possible. IHC data obtained through this method are highly reliable and can be correlated with imaging. IHC expression patterns for PSA, PSMA, AMACR, p63, and MSMB are distinct in malignant and adjacent benign tissue but did not correlate with mpMRI Likert score.

Identification of potential biomarkers in cervical cancer with combined public mRNA and miRNA expression microarray data analysis

Cervical cancer is the fourth most prevalent malignancy in females worldwide. Early diagnosis is key to improving survival rates. Molecular biomarkers are an important method for diagnosing a number of types of cancer, including cervical cancer. The present study utilized public data from three mRNA microarray datasets and one microRNA dataset to analyze the key genes involved in cervical cancer. The mRNA and microRNA expression profile datasets (GSE9750, GSE46857, GSE67522 and GSE30656) were downloaded from the Gene Expression Omnibus database (GEO). Differentially expressed genes (DEGs) and microRNAs (DEMs) were screened using the online tool GEO2R. By using the DEGs consistent across the three mRNA datasets, a functional and pathway enrichment analysis was performed using the Database for Annotation, Visualization and Integrated Discovery. A protein-protein interaction (PPI) network was constructed and module analysis performed using the Search Tool for the Retrieval of Interacting Genes. Validated target genes of the DEMs were identified using the miRecords website. Using the identified target genes of the DEMs, a survival analysis was performed using the OncoLnc online tool. A total of 73 DEGs and 19 DEMs were screened from the microarray expression profile datasets. ‘Integrin-mediated’, ‘proteolysis’ and ‘phosphoinositide 3 kinase-protein kinase 3’ signaling pathways were the most enriched in the DEGs. Three of the DEGs, including Ras homolog family member B (RhoB), stathmin 1 (STMN1) and cyclin D1 (CCNB1) were validated DEM target genes. The OncoLnc survival analysis identified that RhoB was associated with a significantly longer overall survival, whereas STMN1 was associated with a significantly reduced overall survival time in patients with cervical cancer. Finally, data from The Cancer Genome Atlas revealed an association between the mRNA expression levels of RhoB and STMN1, and the overall survival time for patients with cervical cancer. In conclusion, RhoB and STMN1 were identified as key genes that may provide potential targets for cervical cancer diagnosis and treatment.