KLK3 and TMPRSS2 for molecular lymph-node staging in prostate cancer patients undergoing radical prostatectomy

The prognostic value of Dickkopf-3 (Dkk3), TGFB1 and ECM-1 in prostate cancer

Prostate cancer (PCa) is considered one of the most common cancers worldwide. Despite advances in patient diagnosis, management, and risk stratification, 10%-20% of patients progress to castration-resistant disease. Our previous report highlighted a protective role of Dickkopf-3 (DKK3) in PCa stroma. This role was proposed to be mediated through opposing extracellular matrix protein 1 (ECM-1) and TGF-β signalling activity. However, a detailed analysis of the prognostic value of DKK3, ECM-1 and members of the TGF-β signalling pathway in PCa was not thoroughly investigated. In this study, we explored the prognostic value of DKK3, ECM-1 and TGFB1 using a bioinformatical approach through analysis of large publicly available datasets from The Cancer Genome Atlas Program (TGCA) and Pan-Cancer Atlas databases. Our results showed a significant gradual loss of DKK3 expression with PCa progression (p < 0.0001) associated with increased DNA methylation in its promoter region (p < 1.63E-12). In contrast, patients with metastatic lesions showed significantly higher levels of TGFB1 expression compared to primary tumours (p < 0.00001). Our results also showed a marginal association between more advanced tumour stage presented as positive lymph node involvement and low DKK3 mRNA expression (p = 0.082). However, while ECM1 showed no association with tumour stage (p = 0.773), high TGFB1 expression showed a significant association with more advanced stage presented as advanced T3 stage compared to patients with low TGFB1 mRNA expression (p < 0.001). Interestingly, while ECM1 showed no significant association with patient outcome, patients with high DKK3 mRNA expression showed a significant association with favourable outcomes presented as prolonged disease-specific (p = 0.0266), progression-free survival (p = 0.047) and disease-free (p = 0.05). In contrast, high TGFB1 mRNA expression showed a significant association with poor patient outcomes presented as shortened progression-free (p = 0.00032) and disease-free survival (p = 0.0433). Moreover, DKK3, TGFB1 and ECM1 have acted as immune-associated genes in the PCa tumour microenvironment. In conclusion, our findings showed a distinct prognostic value for this three-gene signature in PCa. While both DKK3 and TGFB1 showed a potential role as a clinical marker for PCa stratification, ECM1 showed no significant association with the majority of clinicopathological parameters, which reduce its clinical significance as a reliable prognostic marker.

Remodelling of the tumour microenvironment by the kallikrein-related peptidases

Kallikrein-related peptidases (KLKs) are critical regulators of the tumour microenvironment. KLKs are proteolytic enzymes regulating multiple functions of bioactive molecules including hormones and growth factors, membrane receptors and the extracellular matrix architecture involved in cancer progression and metastasis. Perturbations of the proteolytic cascade generated by these peptidases, and their downstream signalling actions, underlie tumour emergence or blockade of tumour growth. Recent studies have also revealed their role in tumour immune suppression and resistance to cancer therapy. Here, we present an overview of the complex biology of the KLK family and its context-dependent nature in cancer, and discuss the different therapeutic strategies available to potentially target these proteases.

Molecular Characterization of Membrane Steroid Receptors in Hormone-Sensitive Cancers

Cancer is one of the most common causes of death worldwide, and its development is a result of the complex interaction of genetic factors, environmental cues, and aging. Hormone-sensitive cancers depend on the action of one or more hormones for their development and progression. Sex steroids and corticosteroids can regulate different physiological functions, including metabolism, growth, and proliferation, through their interaction with specific nuclear receptors, that can transcriptionally regulate target genes via their genomic actions. Therefore, interference with hormones’ activities, e.g., deregulation of their production and downstream pathways or the exposition to exogenous hormone-active substances such as endocrine-disrupting chemicals (EDCs), can affect the regulation of their correlated pathways and trigger the neoplastic transformation. Although nuclear receptors account for most hormone-related biologic effects and their slow genomic responses are well-studied, less-known membrane receptors are emerging for their ability to mediate steroid hormones effects through the activation of rapid non-genomic responses also involved in the development of hormone-sensitive cancers. This review aims to collect pre-clinical and clinical data on these extranuclear receptors not only to draw attention to their emerging role in cancer development and progression but also to highlight their dual role as tumor microenvironment players and potential candidate drug targets.

Artificial Intelligence Combined With Big Data to Predict Lymph Node Involvement in Prostate Cancer: A Population-Based Study

Background

A more accurate preoperative prediction of lymph node involvement (LNI) in prostate cancer (PCa) would improve clinical treatment and follow-up strategies of this disease. We developed a predictive model based on machine learning (ML) combined with big data to achieve this.

Methods

Clinicopathological characteristics of 2,884 PCa patients who underwent extended pelvic lymph node dissection (ePLND) were collected from the U.S. National Cancer Institute’s Surveillance, Epidemiology, and End Results (SEER) database from 2010 to 2015. Eight variables were included to establish an ML model. Model performance was evaluated by the receiver operating characteristic (ROC) curves and calibration plots for predictive accuracy. Decision curve analysis (DCA) and cutoff values were obtained to estimate its clinical utility.

Results

Three hundred and forty-four (11.9%) patients were identified with LNI. The five most important factors were the Gleason score, T stage of disease, percentage of positive cores, tumor size, and prostate-specific antigen levels with 158, 137, 128, 113, and 88 points, respectively. The XGBoost (XGB) model showed the best predictive performance and had the highest net benefit when compared with the other algorithms, achieving an area under the curve of 0.883. With a 5%~20% cutoff value, the XGB model performed best in reducing omissions and avoiding overtreatment of patients when dealing with LNI. This model also had a lower false-negative rate and a higher percentage of ePLND was avoided. In addition, DCA showed it has the highest net benefit across the whole range of threshold probabilities.

Conclusions

We established an ML model based on big data for predicting LNI in PCa, and it could lead to a reduction of approximately 50% of ePLND cases. In addition, only ≤3% of patients were misdiagnosed with a cutoff value ranging from 5% to 20%. This promising study warrants further validation by using a larger prospective dataset.

Concomitant High Apoptosis Inhibitor of Macrophage (AIM) and Low Prostate-Specific Antigen (PSA) Indicates Activated T Cell-Mediated Anticancer Immunity, Enhance Sensitivity to Pembrolizumab, and Elicit Good Prognosis in Prostate Cancer

BACKGROUND

Despite its widespread use, the use of prostate-specific antigen (PSA) alone as a screening biomarker for prostate cancer (PCa) leads often to unwarranted prostate biopsy, over-diagnosis, and consequently, over-treatment, because of its limited specificity. There are reports that the apoptosis inhibitor of macrophage (AIM), secreted mainly by macrophages and epithelial cells, is upregulated during inflammation and facilitates immune recognition of cancerous cells by blocking human regulator of complement activation.

OBJECTIVE

These controversies around the PSA utility necessitate a reexamination of its use as a screening tool. More so, despite the suggested implication of AIM in anticancer immunosurveillance, there is a dearth of information on its role in therapy response, disease progression, and clinical outcomes of patients with PCa. These inform the present study to probe the nature and role of AIM/PSA signaling in anticancer immunity and prognosis in PCa.

METHODS

A combination of bioinformatics-aided statistical analyses, gene function annotation, and immune infiltrate analyses, coupled with tissue staining, and function assays, namely migration, invasion, and clonogenicity assays, we employed.

RESULTS

We demonstrated that AIM and PSA expression levels are inversely correlated in PCa clinical samples and cell lines, with AIM^lowPSA^high defining PCa, compared to AIM^highPSA^low in normal samples. Concomitant aberrant PSA and significantly suppressed AIM expression levels positively correlated with high-grade disease and characterized by advanced stage prostate cancer, regardless of mutation status. We found that a high PSA/AIM ratio is associated with disease recurrence in patients with prostate cancer but is equivocal for overall survival. In addition, PSA-associated AIM suppression is implicated in the enhanced 'metastability' of PCa and a high AIM/PSA ratio is associated with strong castration-induced regression. CRISPR-mediated AIM knockout was associated with higher PSA expression while ectopic expression of AIM significantly attenuated the migration and invasive capability of PC3 and DU145 cells. Interestingly, compared to normal samples, we observed that AIM, biomarkers of T-cell activation and M1 phenotype markers are co-suppressed in PCa samples.

CONCLUSION

Herein, we demonstrate that AIM/CD5L binds to PSA and that a high PSA/AIM ratio defines advanced stage PCa (regardless of mutation status), is implicated in enhanced metastability, and associated with disease recurrence, while a high AIM/PSA ratio is associated with strong castration-induced regression. More so, the ectopic expression of AIM significantly enhances the anticancer effect of Pembrolizumab and elicits an increased CD8+ T-cell count in AIM^hiPSA^loPDL1+ PCa cases that are respondent to Pembrolizumab treatment.

On the probability of lymph node negativity in pN0-staged prostate cancer-a theoretically derived rule of thumb for adjuvant needs

Purpose

The extent of lymphadenectomy and clinical features influence the risk of occult nodes in node-negative prostate cancer. We derived a simple estimation model for the negative predictive value (npv) of histopathologically node-negative prostate cancer patients (pN0) to guide adjuvant treatment.

Methods

Approximations of sensitivities in detecting lymph node metastasis from current publications depending on the number of removed lymph nodes were used for a theoretical deduction of a simplified formulation of npv assuming a false node positivity of 0.

Results

A theoretical formula of npv = p(N0IpN0) = (100 − prevalence) / (100 − sensitivity × prevalence) was calculated (sensitivity and preoperative prevalence in %). Depending on the number of removed lymph nodes (nLN), the sensitivity of pN0-staged prostate cancer was derived for three sensitivity levels accordingly: sensitivity = f(nLN) = 9 × nLN /100 for 0 ≤ nLN ≤ 8 and f(nLN) = (nLN + 70) /100 for 9 ≤ nLN ≤ 29 and f(nLN) = 1 for nLN ≥ 30.

Conclusion

We developed a theoretical formula for estimation of the npv in pN0-staged prostate cancer patients. It is a sine qua non to use the formula in a clinically experienced context before deciding to electively irradiate pelvic lymph nodes or to intensify adjuvant systemic treatment.

Clinical significance of STEAP1 extracellular vesicles in prostate cancer

BACKGROUND

Extracellular vesicles (EVs) are cell-derived lipid bilayer enclosed structures shed from the plasma membrane by all cell types. Evidence of EV presence in biological fluids has led to considerable efforts focused on identifying their cargo and determining their utility as a non-invasive diagnostic platform for cancer. In this study, we identify circulating STEAP1 (six-transmembrane epithelial antigen of the prostate 1)-positive EVs in the plasma of healthy males and prostate cancer patients and evaluate its diagnostic and prognostic significance.

METHODS

STEAP1 was identified on EVs in prostate cancer patient plasma. EVs were validated using electron microscopy, Western blot, nanoparticle tracking analysis, and nanoscale flow cytometry. STEAP1-positive EVs were quantified for 121 males with prostate cancer and 55 healthy age-matched control males. An evaluation of STEAP1 in prostate cancer tissue was also performed using established prostate cancer cohort data (TCGA, MSKCC, and SU2C/PCF Dream Team).

RESULTS

Evaluation of STEAP1-positive EVs by nanoscale flow cytometry identified a significant increase in prostate cancer patient plasma compared to healthy males. However, no association was found between total STEAP1 EV levels and disease recurrence or overall survival. Cohort data from prostate cancer tissue also found STEAP1 to be elevated in prostate cancer while no significant association with recurrence or overall survival was identified.

CONCLUSIONS

STEAP1 is known to be enriched on the cells of the prostate with potential clinical significance in prostate cancer. Our results identify and quantitate STEAP1-positive EVs in plasma and provide rationale for a STEAP1 EV-based liquid biopsy as a diagnostic strategy in prostate cancer.

Evaluation of Fast Molecular Detection of Lymph Node Metastases in Prostate Cancer Patients Using One-Step Nucleic Acid Amplification (OSNA)

Background: In clinical routine, only fractions of lymph nodes (LNs) are examined histopathologically, often resulting in missed (micro-)metastases and incorrect staging of prostate cancer (PCa). One-step nucleic acid amplification (OSNA) analyzes the entire LN by detecting cytokeratin 19 (CK19) mRNA as a surrogate for LN metastases requiring less effort than conventional biomolecular techniques. We aimed to evaluate performance of OSNA in detecting sentinel LN (SLN) metastases in PCa. Methods: SLNs (n = 534) of 64 intermediate- or high-risk PCa patients undergoing radical prostatectomy with extended and sentinel-guided lymphadenectomy were cut into slices and alternatingly assigned to OSNA and histopathology (hematoxylin-eosin staining, CK19, and CK AE1/AE3 immunohistochemistry). Sensitivity and specificity of OSNA and concordance and measure of agreement (Cohen's kappa (κ)) between OSNA and histopathology were assessed. Results: Histopathology revealed metastases in 76 SLNs. Sensitivity and specificity of OSNA were 84.2% and 96.1%, respectively. Discordant results were recorded for 30 of 534 SLNs, revealing high concordance (94.4%). Twenty-four discordant cases were classified as micrometastases, indicating a possible allocation bias. In 18 cases, positive results were conferred only by OSNA resulting in seven LN-positive patients who were missed by histopathology. Overall, the level of agreement was high (κ = 0.78). Conclusions: OSNA provided a diagnosis that was as least as accurate as detailed histological examination and might improve LN staging in PCa.