Prognostic Genomic Biomarkers in Patients With Localized Prostate Cancer: Is Rising Utilization Justified by Evidence?

Evaluation of HNF1B, KLK3, ELAC2, TMPRSS2-ERG, and CTNNB1 polymorphisms associated with prostate cancer in samples of patients from HUPE-UERJ

PURPOSE

Prostate cancer (PCa) is the leading cause of death among men in 48 countries. Genetic alterations play a significant role in PCa carcinogenesis. For the hypothesis of this research, five unique polymorphisms (SNP) were investigated in different genes that showed to be associated in different ways with PCa: rs4430796, rs2735839, rs4792311, rs12329760, and rs28931588, respectively for the genes HNF1B, KLK3, ELAC2, TMPRSS2-ERG, and CTNNB1.

PATIENTS AND METHODS

Blood samples from 426 subjects were evaluated: 290 controls (161 females and 129 males) and 136 PCa patients. SNP were determined by real-time polymerase chain reaction. TaqMan SNP genotyping assay. In the control samples, the SNPs were defined in association with the self-reported ethnicity, and in 218 control samples with markers with ancestry indicators. The genes were in Hardy-Weinberg equilibrium. One hundred and seventy control samples were matched by ethnicity for comparison with the PCa samples.

RESULTS

The G allele at rs28931588 was monomorphic in both patients and controls studied. Significant differences were observed in allelic and genotypic frequencies between the control and Pca samples in rs2735839 (KLK3; p = 0.002 and χ2  = 8.73 and p = 0.01, respectively), by the global frequency and in the dominant model rs2735839_GG (odds ratio [OR] = 0.51, p = 0.02). AA and GA genotypes at rs4792311 (ELAC2) were more frequent in patients with Gleason 7(4 + 3), 8, and 9 (n = 37%-59.7%) compared to patients with Gleason 6 and 7(3 + 4) (n = 26%-40.0%) conferring a protective effect on the GG genotype (OR = 0.45, p = 0.02). The same genotype showed an OR = 2.71 (p = 0.01) for patients with low severity. The HNF1B-KLK3-ELAC2-TMPRSS2-ERG haplotypes: GAAT, AAAT, GAGT, and AAGT were more frequent in patients with Pca with OR ranging from 4.65 to 2.48.

CONCLUSIONS

Higher frequencies of risk alleles were confirmed in the SNPs, KLK3 rs2735839_A, ELAC2 rs4792311_A, and TMPRSS2 rs12329760_T in patients with Pca. Rs2735839_A was associated with risk of Pca and rs4792311_A with severity and Gleason score of 7(4 + 3) or greater. There is a need for careful observation of rs2735839 and rs4792311 in association with the prostatic biopsy due to the increased risk of Pca.

Protein signatures to distinguish aggressive from indolent prostate cancer

BACKGROUND

Distinguishing men with aggressive from indolent prostate cancer is critical to decisions in the management of clinically localized prostate cancer. Molecular signatures of aggressive disease could help men overcome this major clinical challenge by reducing unnecessary treatment and allowing more appropriate treatment of aggressive disease.

METHODS

We performed a mass spectrometry-based proteomic analysis of normal and malignant prostate tissues from 22 men who underwent surgery for prostate cancer. Prostate cancer samples included Grade Groups (3-5), with 8 patients experiencing recurrence and 14 without evidence of recurrence with a mean of 6.8 years of follow-up. To better understand the biological pathways underlying prostate cancer aggressiveness, we performed a systems biology analysis and gene enrichment analysis. Proteins that distinguished recurrent from nonrecurrent cancer were chosen for validation by immunohistochemical analysis on tissue microarrays containing samples from a larger cohort of patients with recurrent and nonrecurrent prostate cancer.

RESULTS

In all, 24,037 unique peptides (false discovery rate < 1%) corresponding to 3,313 distinct proteins were identified with absolute abundance ranges spanning seven orders of magnitude. Of these proteins, 115 showed significantly (p < 0.01) different levels in tissues from recurrent versus nonrecurrent cancers. Analysis of all differentially expressed proteins in recurrent and nonrecurrent cases identified several protein networks, most prominently one in which approximately 24% of the proteins in the network were regulated by the YY1 transcription factor (adjusted p < 0.001). Strong immunohistochemical staining levels of three differentially expressed proteins, POSTN, CALR, and CTSD, on a tissue microarray validated their association with shorter patient survival.

CONCLUSIONS

The protein signatures identified could improve understanding of the molecular drivers of aggressive prostate cancer and be used as candidate prognostic biomarkers.