PCA3 and TMPRSS2-ERG: Promising Biomarkers in Prostate Cancer Diagnosis

Predicting prostate cancer progression with a Multi-lncRNA expression-based risk score and nomogram integrating ISUP grading

Prostate cancer is a highly heterogeneous disease; therefore, estimating patient prognosis accurately is challenging due to the lack of biomarkers with sufficient specificity and sensitivity. One of the current challenges lies in integrating genomic and transcriptomic data with clinico-pathological features and in incorporating their application in everyday clinical practice. Therefore, we aimed to model a risk score and nomogram containing long non-coding RNA (lncRNA) expression and clinico-pathological data to better predict the probability of prostate cancer progression. We performed bioinformatics analyses to identify lncRNAs differentially expressed across various prostate cancer stages and associated with progression-free survival. This information was further integrated into a prognostic risk score and nomogram containing transcriptomic and clinico-pathological features to estimate the risk of disease progression. We used RNA-seq data from 5 datasets from public repositories (total n = 178) comprising different stages of prostate cancer: pre-treatment primary prostate adenocarcinomas, post-treatment tumors and metastatic castration resistant prostate cancer. We found 30 lncRNAs with consistent differential expression in all comparisons made using two R-based packages. Multivariate progression-free survival analysis including the ISUP group as covariate, revealed that 7/30 lncRNAs were significantly associated with time-to-progression. Next, we combined the expression of these 7 lncRNAs into a multi-lncRNA score and dichotomized the patients into low- or high-score. Patients with a high-score showed a 4-fold risk of disease progression (HR = 4.30, 95 %CI = 2.66-6.97, p = 3.1e-9). Furthermore, we modelled a combined risk-score containing information on the multi-lncRNA score and ISUP group. We found that patients with a high-risk score had nearly 8-fold risk of progression (HR = 7.65, 95 %CI = 4.05-14.44, p = 3.4e-10). Finally, we created and validated a nomogram to help uro-oncologists to better predict patient's risk of progression at 3- and 5-years post-diagnosis. In conclusion, the integration of lncRNA expression data and clinico-pathological features of prostate tumors into predictive models might aid in tailored disease risk assessment and treatment for patients with prostate cancer.

Prognostic value of E‑26 transformation‑specific‑related gene in prostate cancer based on immunohistochemistry analysis

E-26 transformation-specific-related gene (ERG) has been implicated in prostate cancer; however, its prognostic role remains unclear. Therefore, the present study aimed to investigate the association of ERG with the prognosis after radical prostatectomy in patients with prostate cancer. Patient data were collected at the Huadong Hospital, affiliated with Fudan University, between January 2016 and March 2020. ERG protein expression was detected using immunohistochemistry. Independent-sample t-tests and χ² tests were used to evaluate prostate cancer prognosis depending on ERG levels. The Kaplan-Meier method was used to estimate biochemical failure-free survival (BFFS) and the log-rank test was used to test the distribution. Prognostic factors were determined using Cox regression analysis. The median patient age was 69 years (range, 47-82 years). The median prostate-specific antigen (PSA) and free-PSA levels before treatment were 9.58 ng/ml (range, 0.003-187.400 ng/ml) and 1.13 ng/ml (range, 0.0059-30.6100 ng/ml), respectively. ERG protein expression was positive in 43 (16.6%) and negative in 216 (83.4%) cases. The median follow-up period and BFFS were 30 and 28 months, respectively. There was a significant difference in biochemical recurrence (P=0.017) between patients with positive and negative ERG expression. Patients with positive ERG expression had significantly worse BFFS curves compared with those with negative ERG expression (P=0.0038). In the multivariate Cox regression analysis, positive ERG expression was found to be an independent prognostic factor in patients with prostate cancer who underwent radical prostatectomy (hazard ratio, 4.08; 95% confidence interval, 2.03-8.17; P=0.000074). In conclusion, positive ERG expression is an independent prognostic risk factor for prostate cancer. These findings may be valuable for improvements in the clinical application of ERG immunohistochemistry.

PCA3 and TMPRSS2: ERG Urine Level as Diagnostic Biomarker of Prostate Cancer

Background

Prostate cancer is a highly prevalent urological carcinoma with an increasing incidence in Indonesia and all around the world. Early diagnosis can greatly affect treatment outcomes and increase life expectancy. Several biomarkers for detecting prostate cancer have been studied and showed great promise.

Purpose

This study aims to analyze prostate cancer antigen 3 (PCA3) as well as transmembrane serine protease 2:ERG (TMPRSS2:ERG) for diagnosing and serving as urine biomarkers in predicting prostate cancer incidences.

Methods

We conducted an analytical study to assess the utility of PCA3 and TMPRSS2:ERG for detecting prostate cancer. Thirty samples were included in this study to see the utilization of PCA3 and TMPRSS2:ERG as diagnostic biomarkers of prostate cancer. A urine sample was taken and the PCA3 test was performed using the PCA3 PROGENSA test, while the TMPRSS2:ERG was performed using the chemiluminescent DNA probe method with a hybridization protection test.

Results

The average age of the subject was 61.07±8.3 years. Based on calculations using the Mann-Whitney test, there was a significant relationship between prostate-Specific Antigen (PSA) overexpression (p<0.001), TMPRSS2:ERG (p=0.001), and PCA3 (p=0.003) with prostate cancer incidence. The sensitivity of PCA3 and TMPRSS2:ERG in detecting prostate cancer was 76.9% and 92.3%, respectively. Hence, TMPRSS2:ERG and PCA3 can be used as biomarkers for the occurrence of prostate cancer. We also performed a Kruskal-Wallis test; however, there was no significant relationship between PSA (p=0.236), TMPRSS2:ERG (p=0.801), and PCA3 (p=0.091) with the Gleason score.

Conclusion

There is a significant correlation between overexpression of PSA, TMPRSS2:ERG and PCA3 with the incidence of prostate cancer, and TMPRSS2:ERG and PCA3 can be used as biomarkers of prostate cancer.

A New Era of Prostate Cancer Precision Medicine

Prostate cancer is the second most common male cancer affecting Western society. Despite substantial advances in the exploration of prostate cancer biomarkers and treatment strategies, men are over diagnosed with inert prostate cancer, while there is also a substantial mortality from the invasive disease. Precision medicine is the management of treatment profiles across different cancers predicting therapies for individual cancer patients. With strategies including individual genomic profiling and targeting specific cancer pathways, precision medicine for prostate cancer has the potential to impose changes in clinical practices. Some of the recent advances in prostate cancer precision medicine comprise targeting gene fusions, genome editing tools, non-coding RNA biomarkers, and the promise of liquid tumor profiling. In this review, we will discuss these recent scientific advances to scale up these approaches and endeavors to overcome clinical barriers for prostate cancer precision medicine.

Aptamer-Based Sandwich Assay for Measurement of Thymidine Kinase 1 in Serum of Cancerous Patients

Thymidine kinase 1 (TK1) is traditionally a serum biomarker that is elevated in the early stages of malignancies. The diagnostic and prognostic role of TK1 for screening and monitoring human malignancies has recently been investigated. Anti-human TK1 aptamers were selected through 12 iterative rounds of systematic evolution of ligands by exponential enrichment from a DNA library. The aptamer pool of round 12 was amplified, and the polymerase chain reaction product was cloned on the TA vector. Of the 85 colonies obtained, 52 were identified as positive clones. These aptamers were screened for TK1 with surface plasmon resonance, where apta37 and apta69 showed the highest affinity for TK1. The TK1_apta37 and TK1_apta69 aptamers were used in a sandwich assay platform and successfully detected TK1 in the concentration range of 54-3500 pg mL^-1. Clinical samples from 60 cancerous patients were also tested with this assay system and compared using the conventional antibody-based enzyme-linked immunosorbent assay kit. The aptamer sandwich assay demonstrated a dynamic range for TK1 at clinically relevant serum levels, covering subpicogram per milliliter concentrations. The new approach offers a simple and robust method for detecting serum biomarkers that have low and moderate abundance. The results of this study demonstrate the screening capability of the aptamer sandwich assay platform and its potential applicability to the point-of-care testing system.

STAT3-induced long noncoding RNAs in multiple myeloma cells display different properties in cancer

Interleukin-6 (IL-6)-activated Signal Transducer and Activator of Transcription 3 (STAT3) facilitates survival in the multiple myeloma cell line INA-6 and therefore represents an oncogenic key player. However, the biological mechanisms are still not fully understood. In previous studies we identified microRNA-21 as a STAT3 target gene with strong anti-apoptotic potential, suggesting that noncoding RNAs have an impact on the pathogenesis of human multiple myeloma. Here, we describe five long noncoding RNAs (lncRNAs) induced by IL-6-activated STAT3, which we named STAiRs. While STAiRs 1, 2 and 6 remain unprocessed in the nucleus and show myeloma-specific expression, STAiRs 15 and 18 are spliced and broadly expressed. Especially STAiR2 and STAiR18 are promising candidates. STAiR2 originates from the first intron of a tumor suppressor gene. Our data support a mutually exclusive expression of either STAiR2 or the functional tumor suppressor in INA-6 cells and thus a contribution of STAiR2 to tumorigenesis. Furthermore, STAiR18 was shown to be overexpressed in every tested tumor entity, indicating its global role in tumor pathogenesis. Taken together, our study reveals a number of STAT3-induced lncRNAs suggesting that the interplay between the coding and noncoding worlds represents a fundamental principle of STAT3-driven cancer development in multiple myeloma and beyond.

Low PCA3 expression is a marker of poor differentiation in localized prostate tumors: exploratory analysis from 12,076 patients

Background

Prostate cancer antigen 3 (PCA3) is a prostate cancer diagnostic biomarker that has been clinically validated. The limitations of the diagnostic role of PCA3 in initial biopsy and the prognostic role are not well established. Here, we elucidate the limitations of tissue PCA3 to predict high grade tumors in initial biopsy.

Results

PCA3 has a bimodal distribution in both biopsy and radical prostatectomy (RP) tissues, where low PCA3 expression was significantly associated with high grade disease (p<0.001). PCA3 had a poor performance of predicting high grade disease in initial biopsy (GS≥8) with 55% sensitivity and high false negative rates; 42% of high Gleason (≥8) samples had low PCA3. In RP, low PCA3 is associated with adverse pathological features, clinical recurrence outcome and greater probability of metastatic progression (p<0.001).

Materials and Methods

A total of 1,694 expression profiles from biopsy and 10,382 from RP patients with high risk tumors were obtained from the Decipher Genomic Resource Information Database (GRIDTM)prostate cancer database. The primary clinical endpoint was distant metastasis-free survival for RP and high Gleason grade for biopsy. Logistic regression analyses and Cox proportional hazards models were used to evaluate the association of PCA3 with clinical variables and risk of metastasis.

Conclusions

There is high prevalence of high grade tumors with low PCA3 expression in the biopsy setting. Therefore, urologists should be warned that using PCA3 as stand-alone test may lead to high rate of under-diagnosis of high grade disease in initial biopsy setting.

Aptamer-based Sandwich Assay and its Clinical Outlooks for Detecting Lipocalin-2 in Hepatocellular Carcinoma (HCC)

We validated a single-stranded, DNA aptamer-based, diagnostic method capable of detecting Lipocalin-2 (LCN2), a biomarker from clinically relevant hepatocellular carcinoma (HCC) patient serum, in the sandwich assay format. Nine aptamers (LCN2_apta1 to LCN2_apta9) for LCN2 were screened with SELEX processes, and a sandwich pair (LCN2_apta2 and LCN2_apta4) was finally chosen using surface plasmon resonance (SPR) and dot blotting analysis. The result of the proposed aptamer sandwich construction shows that LCN2 was sensitively detected in the concentration range of 2.5–500 ng mL⁻¹ with a limit of detection of 0.6 ng mL⁻¹. Quantitative measurement tests in HCC patients were run on straight serum and were compared with the performance of the conventional antibody-based ELISA kit. The aptamer sandwich assay demonstrated an excellent dynamic range for LCN2 at clinically relevant serum levels, covering sub-nanogram per mL concentrations. The new approach offers a simple and robust method for detecting serum biomarkers that have low and moderate abundance. It consists of functionalization, hybridization and signal read-out, and no dilution is required. The results of the study demonstrate the capability of the aptamer sandwich assay platform for diagnosing HCC and its potential applicability to the point-of-care testing (POCT) system.

Molecular and Clinicopathological Aspects of Prostate Cancer in Bulgarian Probands

To correlate the molecular data to the clinicopathological parameters in Bulgarian prostate cancer patients. PCA3 overexpression, TMPRSS2-ERG gene fusion, GSTP1 promoter hypermethylation, somatic mutations in the AR gene and the IVS1-27G > A polymorphism in the KLF6 gene were studied. A total of 148 patients were analyzed: 16 aggressive PCa, 83 non-aggressive PCa, 25 BPH and 24 chronic inflammatory diseases. Real-time RT-PCR, DNA sequencing, and bisulfite conversion of DNA, were applied. All cases with aggressive PCa before treatment were tested positive for PCA3 overexpression, expression of a T2-ERG gene fusion product and GSTP1 promoter hypermethylation. No somatic mutations were detected in the AR gene and all patients showed normal KLF6-IVS1-27G > A genotype. The TMPRSS2-ERG positive status correlates with moderate to poorly differentiated prostate tumors and it is considered as unfavorable disease predictor. Positive GSTP1 promoter hypermethylation seems to be highly specific and the earliest epigenetic change in the prostate gland, which indicates the beginning of the pathological process. The appearance of positive molecular markers in blood was considered as a predictor of PCa dissemination. GSTP1 promoter hypermethylation was found as the earliest and a long-lasting epigenetic marker in blood samples of PCa patients, which makes it suitable as a marker for treatment follow-up. The molecular profile of prostate cancer needs to be strictly monitored during the course of disease treatment, which is of a great help in determining the patient's individual therapy response.