Genetic markers a landscape in prostate cancer

CYP17A1 polymorphism c.-362T>C predicts clinical outcome in metastatic castration-resistance prostate cancer patients treated with abiraterone

BACKGROUND

Abiraterone became a standard hormonal therapy for patients with metastatic castration-resistance prostate cancer (mCRPC). However, patients may experience primary resistance to treatment. To date, few predictive biomarkers of efficacy have been identified. Our aim was to investigate the association between the single nucleotide polymorphism (SNP) c.-362T>C in the CYP17A1 gene, and clinical outcome in mCRPC patients treated with abiraterone.

PATIENTS AND METHODS

mCRPC patients candidate to receive abiraterone were enrolled in the present retrospective pharmacogenetic study. Based on a literature selection, CYP17A1 rs2486758 (c.-362T > C) was selected and analysed by real-time PCR on genomic DNA extracted from whole blood. Univariate analysis was performed to test the association between the SNP and treatment-related clinical outcomes.

RESULTS

Sixty mCRPC patients were enrolled in the present study. Patients carrying the mutant CYP17A1 c.-362CT/CC genotypes showed a shorter median progression-free survival (PFS) and prostate-specific antigen-PFS (PSA-PFS) compared to patients carrying the TT genotype (10.7 vs 14.2 months and 8 vs 16 months, respectively; p = 0.04). No association between the selected SNP and the overall survival was found.

CONCLUSIONS

These findings suggest an association between CYP17A1 c.-362T>C polymorphism and poorer clinical outcome with abiraterone for mCRPC patients. However, further validations on larger cohort of patients are needed to confirm its role as a predictive biomarker for abiraterone resistance.

The effects of the genetic polymorphisms of antioxidant enzymes on susceptibility to papillary thyroid carcinoma

Several lines of evidences have indicated that inflammation play an important role in the carcinogenesis. During the inflammatory processes, free radical species are produced from oxidative stress. In normal conditions, enzymatic and nonenzymatic antioxidants remove these products. Manganese superoxide dismutase (MnSOD), glutathione peroxidase-1 (GPx-1), and catalase (CAT) are three important enzymes. Therefore, this study aimed to evaluate the effects of MnSOD (SOD2), GPX-1, and CAT genetic polymorphisms on papillary thyroid carcinoma (PTC) susceptibility. A total of 134 patients with PTC and 151 healthy controls were recruited to participate in this study. All samples were genotyped for SOD2 rs4880, GPX1 1050450, and CAT rs7943316 polymorphisms by polymerase chain reaction-restriction fragment length polymorphism method. The frequencies of the rs1050450, rs4880, and rs7943316 alleles and genotypes were not different between PTC patients and controls. However, the TC genotype of SOD2 rs4880 polymorphism was significantly higher in males compared to that in females in PTC patients (odds ratio [OR], 3.9 [95% CI, 1.5-11], p = .007). The rs4880 polymorphism was also associated with higher stages (III-IV) of PTC in dominant model. No significant correlation was found between GPX1-rs1050450 and CAT-rs7943316 polymorphisms and demographic, clinical, and pathological features of the disease. The SOD2 rs4880CT genotype was more frequent in males with PTC and patients with higher stages (III-IV) of disease (OR, 2.9 [95% CI, 1.1-7.7], p = .04). However, no significant association was found between GPX1-rs1050450 and CAT-rs7943316 variants and PTC or its demographic, clinical, and pathological features.

Expression of KIF18A Is Associated with Increased Tumor Stage and Cell Proliferation in Prostate Cancer

Background

The role of KIF18A in tumorigenesis and tumor development has been well studied in several cancers, but not in prostate cancer. In this study, we investigated the potential prognostic utility of KIF18A and its role in prostate cancer progression.

Material/Methods

We collected prostate cancer and paracancerous tissue samples from the same patient. Immunohistochemical staining was performed to investigate the KIF18A expression levels in the clinical sample. The Cancer Genome Atlas (TCGA) database was analyzed via a bioinformatics approach to gain insight into the relationship between KIF18A expression and prognosis. We examined the effect of KIF18A knockdown on PC-3 cell proliferation via colony formation and MTT assays. Flow cytometry was used to assess the effect of KIF18A knockdown on PC-3 cell apoptosis. Transwell invasion assay was performed to assess whether KIF18A affects the invasion ability of PC-3 cells.

Results

The KIF18A protein level was higher in PCa tissue than in paracancerous tissue. The In addition, upregulated KIF18A suggested a poor tumor stage and prognosis for prostate cancer patients. Our in vitro experiments demonstrated that KIF18A knockdown in PC-3 cells significantly inhibited proliferation and metastasis.

Conclusions

High KIF18A expression in prostate cancer patients predicts a poor prognosis. KIF18A knockdown inhibits prostate cell proliferation and metastasis. Therefore, this study confirms the usefulness of KIF18A as an oncological prognostic indicator and a potential therapeutic target for prostate cancer.

The Labyrinth of Product Development and Regulatory Approvals in Liquid Biopsy Diagnostics

The evolution of chemistries and instrument platforms for next‐generation sequencing has led to sequencing of genomic variants in both tumor biopsies as well as in circulating tumor cells (CTCs) and cell‐free DNA liquid biopsies. The transition of these analytical platforms into clinical ones has led to challenges in product development as well as regulatory strategies for the approval of diagnostic products with these platforms. Regulatory strategies for liquid biopsy diagnostics depend on a framework that has been developed over the past few years by the US Food and Drug Administration (FDA). This framework includes both guidances that cover enrichment biomarkers and companion diagnostics, as well as regulatory approval precedents, which can be used to design regulatory strategies for new liquid biopsy diagnostic products. However, the regulatory paths for these liquid biopsy diagnostics can also be tortuous, as is the example of CTC—platform liquid biopsies. The ultimate success of regulatory pathways of liquid biopsy diagnostics has been driven by the incremental value of FDA approval for Clinical Laboratory Improvement Amendment (CLIA)‐developed tests and by the inherent complexity of these diagnostics, which are practical barriers for the widespread replication of these tests throughout CLIA laboratories. The framework for FDA approval of sequence information from these liquid biopsies has been focused on single‐site approvals of diagnostics where sequencing information is considered at different diagnostic risk levels, ranging from novel or follow‐on companion diagnostics to variant calls in genomic targets considered independently valuable for therapeutic decision making.

Data analysis algorithm for the development of extracellular miRNA-based diagnostic systems for prostate cancer

Urine of prostate cancer (PCa) carries miRNAs originated from prostate cancer cells as a part of both nucleoprotein complexes and cell-secreted extracellular vesicles. The analysis of such miRNA-markers in urine can be a convenient option for PCa screening. The aims of this study were to reveal miRNA–markers of PCa in urine and design a robust and precise diagnostic test, based on miRNA expression analysis. The expression analysis of the 84 miRNAs in paired urine extracellular vesicles (EVs) and cell free urine supernatant samples from healthy donors, patients with benign and malignant prostate tumours was done using miRCURY LNA miRNA qPCR Panels (Exiqon, Denmark). Sets of miRNAs differentially expressed between the donor groups were found in urine EVs and urine supernatant. Diagnostically significant miRNAs were selected and algorithm of data analysis, based on expression data on 24-miRNA in urine and obtained using 17 analytical systems, was designed. The developed algorithm of data analysis describes a series of steps necessary to define cut-off values and sequentially analyze miRNA expression data according to the cut-offs to facilitate classification of subjects in case/control groups and allows to detect PCa patients with 97.5% accuracy.

Reasons for Discontinuing Active Surveillance: Assessment of 21 Centres in 12 Countries in the Movember GAP3 Consortium

BACKGROUND

Careful assessment of the reasons for discontinuation of active surveillance (AS) is required for men with prostate cancer (PCa).

OBJECTIVE

Using Movember's Global Action Plan Prostate Cancer Active Surveillance initiative (GAP3) database, we report on reasons for AS discontinuation.

DESIGN, SETTING, AND PARTICIPANTS

We compared data from 10296 men on AS from 21 centres across 12 countries.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Cumulative incidence methods were used to estimate the cumulative incidence rates of AS discontinuation.

RESULTS AND LIMITATIONS

During 5-yr follow-up, 27.5% (95% confidence interval [CI]: 26.4-28.6%) men showed signs of disease progression, 12.8% (95% CI: 12.0-13.6%) converted to active treatment without evidence of progression, 1.7% (95% CI: 1.5-2.0%) continued to watchful waiting, and 1.7% (95% CI: 1.4-2.1%) died from other causes. Of the 7049 men who remained on AS, 2339 had follow-up for >5yr, 4561 had follow-up for <5yr, and 149 were lost to follow-up. Cumulative incidence of progression was 27.5% (95% CI: 26.4-28.6%) at 5yr and 38.2% (95% CI: 36.7-39.9%) at 10yr. A limitation is that not all centres were included due to limited information on the reason for discontinuation and limited follow-up.

CONCLUSIONS

Our descriptive analyses of current AS practices worldwide showed that 43.6% of men drop out of AS during 5-yr follow-up, mainly due to signs of disease progression. Improvements in selection tools for AS are thus needed to correctly allocate men with PCa to AS, which will also reduce discontinuation due to conversion to active treatment without evidence of disease progression.

PATIENT SUMMARY

Our assessment of a worldwide database of men with prostate cancer (PCa) on active surveillance (AS) shows that 43.6% drop out of AS within 5yr, mainly due to signs of disease progression. Better tools are needed to select and monitor men with PCa as part of AS.

High Expression of KIF22/Kinesin-Like DNA Binding Protein (Kid) as a Poor Prognostic Factor in Prostate Cancer Patients

Background

Kid (kinesin-like DNA binding protein), a member of microtubule-dependent molecular motor proteins, also known as KIF22, is reported to be associated with carcinogenesis and cancer progression in different types of malignant tumor, but the biologic behavior and clinical outcome of KIF22 in prostate cancer (PCa) has not been well studied. This study aimed to analyze the association between KIF22 and clinical outcome in PCa patients.

Material/Methods

The expression of KIF22 in tumor specimens compared with paired paracancerous tissue from 114 patients undergoing radical prostatectomy was detected by immunohistochemistry; results were verified using The Cancer Genome Atlas (TCGA) database. Subsequently, the relationship between KIF22 expression and clinical prognosis of PCa patients was then statistically analyzed.

Results

Both immunohistochemistry and database analysis showed that KIF22 was obviously overexpressed in PCa tissues compared with paracancerous tissue. The overexpression of KIF22 at the protein level was significantly related to higher clinical stage (P=0.025), Gleason score (P=0.002), seminal vesicle invasion (P=0.007), and lymph node metastasis (P=0.009). Furthermore, with the overexpression of KIF22 mRNA level in PCa patients, the oncological prognosis of PCa patients was much poorer.

Conclusions

High-level expression of KIF22 was related to both tumor progression and adverse clinical outcome. For this reason, KIF22 may become a potential prognostic factor for PCa.