New strategy for the identification of prostate cancer: The combination of Proclarix and the prostate health index

Endoplasmic reticulum stress-related genes as prognostic and immunogenic biomarkers in prostate cancer

BACKGROUND

The metastasis and aggressive nature of prostate cancer (PCa) has become a major malignancy related threat that concerns men's health. The efficacy of immune monotherapy against PCa is questionable due to its lymphocyte-suppressive nature.

METHOD

Endoplasmic reticulum stress- (ERS-) and PCa-prognosis-related genes were obtained from the Molecular Signatures Database and the Cancer Genome Atlas database. The expression, prognosis and immune infiltration values of key genes were explored by "survival R package", "rms", "xCELL algorithm", and univariate-multivariate Cox and LASSO regression analyses. The "consensus cluster plus R package" was used for cluster analysis.

RESULT

As ERS-related genes, ERLIN2 and CDK5RAP3 showed significant expressional, prognostic and clinic-pathologic values. They were defined as the key genes significantly correlated with immune infiltration and response. The nomogram was constructed with T-stage and primary treatment outcome, and the risk-prognostic model was constructed in the following way: Riskscore = (- 0.1918) * ERLIN2 + (0.5254) * CDK5RAP3. Subsequently, prognostic subgroups based on key genes classified the high-risk group as a pro-cancer subgroup that had lower mutation rates of critical genes (SPOP and MUC16), multiple low-expression immune-relevant molecules, and differences in macrophages (M1 and M2) expressions. Finally, ERLIN2 as an anti-oncogene and CDK5RAP3 as a pro-oncogene were further confirmed by cell phenotype assays and immunohistochemistry.

CONCLUSION

We identified ERLIN2 and CDK5RAP3 as ERS-related genes with important prognostic and immunologic values, and classified patients between high- and low-risk subgroups, which provided new prognostic markers, immunotherapeutic targets, and basis for prognostic assessments.

Evaluation of Proclarix in the diagnostic work-up of prostate cancer

Objectives

The use of multiparametric magnetic resonance imaging (mpMRI) has been widely adopted in the diagnostic work-up for suspicious prostate cancer (PCa) and is recommended in most current guidelines. However, mpMRI lesions are often indeterminate and/or turn out to be false-positive on prostate biopsy. The aim of this work was to evaluate Proclarix, a biomarker test for the detection of relevant PCa, regarding its diagnostic value in all men before biopsy and in men with indeterminate lesions on mpMRI (PI-RADS 3) during work-up for PCa.

Materials and Methods

Men undergoing mpMRI-targeted and systematic biopsy of the prostate were prospectively enrolled. The Proclarix test was evaluated for the detection accuracy of clinically significant PCa (csPCa) defined as Grade Group ≥ 2 and its association to mpMRI results. Further, Proclarix's performance was also tested when adapted to prostate volume (Proclarix density) and performance compared to PSA density (PSAD).

Results

A total of 150 men with a median age of 65 years and median PSA of 5.8 ng/mL were included in this study. CsPCa was diagnosed in 65 (43%) men. Proclarix was significantly associated with csPCa and higher PI-RADS score (p < 0.001). At the pre-defined cut-off of 10%, Proclarix's sensitivity for csPCa was 94%, specificity 19%, negative predictive value 80% and positive predictive value 47%. Proclarix density showed the highest AUC for the detection of csPCa of 0.77 (95%CI: 0.69-0.85) compared to PSA, PSAD and Proclarix alone. Proclarix was able to identify all six csPCa in men with PI-RADS 3 lesions (n = 28), whereas PSAD missed two out of six. At optimized cut-offs, Proclarix density outperformed PSAD by potentially avoiding 41% of unnecessary biopsies.

Conclusion

Proclarix demonstrates high sensitivity in detecting csPCa but may still result in unnecessary biopsies. However, Proclarix density was able to outperform PSAD and Proclarix and was found to be useful in men with PI-RADS 3 findings by safely avoiding unnecessary biopsies without missing csPCa.

How to Integrate Prostate Cancer Biomarkers in Urology Clinical Practice: An Update

Nowadays, the management of prostate cancer has become more and more challenging due to the increasing number of available treatment options, therapeutic agents, and our understanding of its carcinogenesis and disease progression. Moreover, currently available risk stratification systems used to facilitate clinical decision-making have limitations, particularly in providing a personalized and patient-centered management strategy. Although prognosis and prostate cancer-specific survival have improved in recent years, the heterogenous behavior of the disease among patients included in the same risk prognostic group negatively impacts not only our clinical decision-making but also oncological outcomes, irrespective of the treatment strategy. Several biomarkers, along with available tests, have been developed to help clinicians in difficult decision-making scenarios and guide management strategies. In this review article, we focus on the scientific evidence that supports the clinical use of several biomarkers considered by professional urological societies (and included in uro-oncological guidelines) in the diagnosis process and specific difficult management strategies for clinically localized or advanced prostate cancer.

The Potential of Extracellular Matrix- and Integrin Adhesion Complex-Related Molecules for Prostate Cancer Biomarker Discovery

Prostate cancer is among the top five cancer types according to incidence and mortality. One of the main obstacles in prostate cancer management is the inability to foresee its course, which ranges from slow growth throughout years that requires minimum or no intervention to highly aggressive disease that spreads quickly and resists treatment. Therefore, it is not surprising that numerous studies have attempted to find biomarkers of prostate cancer occurrence, risk stratification, therapy response, and patient outcome. However, only a few prostate cancer biomarkers are used in clinics, which shows how difficult it is to find a novel biomarker. Cell adhesion to the extracellular matrix (ECM) through integrins is among the essential processes that govern its fate. Upon activation and ligation, integrins form multi-protein intracellular structures called integrin adhesion complexes (IACs). In this review article, the focus is put on the biomarker potential of the ECM- and IAC-related molecules stemming from both body fluids and prostate cancer tissue. The processes that they are involved in, such as tumor stiffening, bone turnover, and communication via exosomes, and their biomarker potential are also reviewed.

Identification of differentially expressed circRNAs in prostate cancer of different clinical stages by RNA sequencing

Circular RNAs (circRNAs) are linked to cancer, but it's still not clear what role they play in prostatic cancer. Through high-throughput sequencing, the goal of this study was to compare how circRNAs are expressed at different stages of prostate cancer. 12 patients attending the Department of Urology at the Second Affiliated Hospital of Nanchang University between June 2020 and October 2021 were used for RNA sequencing, and 14 patients were used for real-time fluorescent quantitative PCR (qRT-PCR). The expression profiles of prostate cancer circRNAs were constructed by sequencing with the help of next-generation high-throughput sequencing technology, and the differentially expressed circRNAs were analyzed by targeting microRNA (miRNA) loci and Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of the genes from which circRNAs originated. Finally, the expression of target circRNAs in two prostate tissues was verified by qRT-PCR. Following high-throughput sequencing, 13,047 circRNAs were identified, and 605 circRNAs with significant differential expression were identified, of which 361 circRNAs were up-regulated, and 244 circRNAs were down-regulated. Analysis of circRNA-originated genes using GO and the KEGG enrichment analysis showed that circRNA host genes can regulate and influence multiple signaling pathways in prostate cancer with important biological functions. And the circRNA-miRNA network was constructed. The highest number of differentially expressed circRNA-binding miRNAs were: hsa_circ_000 7582 (52), hsa_circ_000 6198 (37), hsa_circ_000 6759 (28), hsa_circ_000 5675 (25), and hsa_circ_000 2172 (22). Moreover, we further screened out the circRNA (hsa_circ_0005692) that was significantly differentially expressed and common to all groups and verified by qRT-PCR that the expression of the target circRNA (hsa_circ_0005692) was significantly downregulated in prostate cancer compared with benign prostatic hyperplasia (BPH) tissues.

PPARG is a potential target of Tanshinone IIA in prostate cancer treatment: a combination study of molecular docking and dynamic simulation based on transcriptomic bioinformatics

Tanshinone IIA is a lipophilic organic compound from the root of Danshen (Salvia miltiorrhiza) and is one of the most well-known Tanshinone molecules by pharmacologists. In recent years, in addition to effects of anti-cardiovascular and neurological diseases, Tanshinone IIA has also shown some degrees of anti-prostate cancer potential. Although they do have some studies focusing on the molecular mechanism of Tanshinone IIA's anti-prostate cancer effects, a further understanding on the transcriptomic and structural level is still lacking. In this study, transcriptomic sequencing technology and computer technology were employed to illustrate the effects of Tanshinone IIA on prostate cancer through bioinformatic analysis and molecular dynamics simulation, and PPARG was considered to be one of the targets for Tanshinone IIA according to docking scoring and dynamic calculation. Our study provides a novel direction to further understand the mechanism of the effects of Tanshinone IIA on prostate cancer, and further molecular biological studies need to be carried on to further investigate the molecular mechanism of Tanshinone IIA's anti-prostate cancer effect through PPARG.

Beyond blood biomarkers: the role of SelectMDX in clinically significant prostate cancer identification

INTRODUCTION

New potential biomarkers to pre-intervention identification of a clinically significant prostate cancer (csPCa) will prevent overdiagnosis and overtreatment and limit quality of life impairment of PCa patients.

AREAS COVERED

We have developed a comprehensive review focusing our research on the increasing knowledge of the role of SelectMDX® in csPCa detection. Areas identified as clinically relevant are the ability of SelectMDX® to predict csPCa in active surveillance setting, its predictive ability when combined with multiparametric MRI and the role of SelectMDX® in the landscape of urinary biomarkers.

EXPERT OPINION

Several PCa biomarkers have been developed either alone or in combination with clinical variables to improve csPCa detection. SelectMDX® score includes genomic markers, age, PSA, prostate volume, and digital rectal examination. Several studies have shown consistency in the ability to improve detection of csPCa, avoidance of unnecessary prostate biopsies, helpful in decision-making for clinical benefit of PCa patients with future well designed, and impactful studies.

Relationship between Proclarix and the Aggressiveness of Prostate Cancer

INTRODUCTION

Proclarix is a CE-marked test that provides the risk of clinically significant prostate cancer (csPCa), ranging from 0% to 100%, based on the serum measurement of Thrombospondin-1, cathepsin D, prostate-specific antigen (PSA), and percentage of free PSA in addition to age. We hypothesize that Proclarix could be correlated with PCa aggressiveness. We analyzed the association of this new biomarker with four surrogates of aggressiveness: grade group (GG) in the biopsy, clinical stage, risk of biochemical recurrence after primary treatment of localized PCa, and pathology in the surgical specimen.

MATERIAL AND METHODS

This is a retrospective study from 606 men with suspicion of PCa [PSA of ≥ 3.0 ng/mL and/or abnormal digital rectal examination (DRE)], in whom Proclarix was assessed (0-100%). The GG was defined by the International Society of Urological Pathology categories. The TNM was used for clinical staging (cT based on DRE, whereas cN and cM were established with computed tomography and 99-technetium bone scintigraphy). The risk of biochemical recurrence of localized PCa after primary treatment was defined by combining PSA, GG, and cT. Finally, an unfavorable pathology in a surgical specimen was defined as GG > 2 or pT ≥ 3.

RESULTS

The median age of the cohort was 67 years old, with a median PSA of 7 ng/mL and a rate of abnormal DRE of 23.3%. CsPCa was detected in 254 men (41.9%), with a median Proclarix of 60.1% compared with 37.3% obtained in patients with insignificant PCa and 20.7% in men without PCa. Among patients with GG > 3, Proclarix was significantly higher (58.2%) than in those with GG of 3 or lower (33.1%, p < 0.001). Men with localized tumors exhibited a Proclarix median of 37.3% compared with those with advanced disease (60.1%, p < 0.001). Proclarix levels among 197 patients with low and intermediate risk of biochemical recurrence were 24.9% and 35.0%, respectively, significantly lower compared with patients with high-risk disease (58.7%, p < 0.001). Unfavorable pathology was observed in 35 patients out of the 79 who underwent radical prostatectomy, with a Proclarix median of 35.7% compared with 23.7% obtained in patients with favorable pathology (p = 0.013). Proclarix and magnetic resonance imaging were independent predictors of the four surrogates of aggressiveness analyzed.

CONCLUSION

There is a correlation between Proclarix and the aggressiveness of PCa.

A Neural Network Model Combining [-2]proPSA, freePSA, Total PSA, Cathepsin D, and Thrombospondin-1 Showed Increased Accuracy in the Identification of Clinically Significant Prostate Cancer

BACKGROUND

The Prostate Health Index (PHI) and Proclarix (PCLX) have been proposed as blood-based tests for prostate cancer (PCa). In this study, we evaluated the feasibility of an artificial neural network (ANN)-based approach to develop a combinatorial model including PHI and PCLX biomarkers to recognize clinically significant PCa (csPCa) at initial diagnosis.

METHODS

To this aim, we prospectively enrolled 344 men from two different centres. All patients underwent radical prostatectomy (RP). All men had a prostate-specific antigen (PSA) between 2 and 10 ng/mL. We used an artificial neural network to develop models that can identify csPCa efficiently. As inputs, the model uses [-2]proPSA, freePSA, total PSA, cathepsin D, thrombospondin, and age.

RESULTS

The output of the model is an estimate of the presence of a low or high Gleason score PCa defined at RP. After training on a dataset of up to 220 samples and optimization of the variables, the model achieved values as high as 78% for sensitivity and 62% for specificity for all-cancer detection compared with those of PHI and PCLX alone. For csPCa detection, the model showed 66% (95% CI 66-68%) for sensitivity and 68% (95% CI 66-68%) for specificity. These values were significantly different compared with those of PHI (p < 0.0001 and 0.0001, respectively) and PCLX (p = 0.0003 and 0.0006, respectively) alone.

CONCLUSIONS

Our preliminary study suggests that combining PHI and PCLX biomarkers may help to estimate, with higher accuracy, the presence of csPCa at initial diagnosis, allowing a personalized treatment approach. Further studies training the model on larger datasets are strongly encouraged to support the efficiency of this approach.