Unravelling the Role of Iroquois Homeobox 4 and its Interplay with Androgen Receptor in Prostate Cancer.

Genome-wide association studies have linked Iroquois-Homeobox 4 (IRX4) as a robust expression quantitative-trait locus associated with prostate cancer (PCa) risk. However, the intricate mechanism and regulatory factors governing IRX4 expression in PCa remain poorly understood. Here, we unveil enrichment of androgen-responsive gene signatures in metastatic prostate tumors exhibiting heightened IRX4 expression. Furthermore, we uncover a novel interaction between IRX4 and the androgen receptor (AR) co-factor, FOXA1, suggesting that IRX4 modulates PCa cell behavior through AR cistrome alteration. Remarkably, we identified a distinctive short insertion-deletion polymorphism (INDEL), upstream of the IRX4 gene that differentially regulates IRX4 expression through the disruption of AR binding. This INDEL emerges as the most significant PCa risk-associated variant within the 5p15 locus, in a genetic analysis involving 82,591 PCa cases and 61,213 controls and was associated with PCa survival in patients undergoing androgen-deprivation therapy. These studies suggest the potential of this INDEL as a prognostic biomarker for androgen therapy in PCa and IRX4 as a potential therapeutic target in combination with current clinical management.

Genomic and Phenotypic Biomarkers for Precision Medicine Guidance in Advanced Prostate Cancer.

OPINION STATEMENT: Prostate cancer (PCa) is the second most diagnosed malignant neoplasm and is one of the leading causes of cancer-related death in men worldwide. Despite significant advances in screening and treatment of PCa, given the heterogeneity of this disease, optimal personalized therapeutic strategies remain limited. However, emerging predictive and prognostic biomarkers based on individual patient profiles in combination with computer-assisted diagnostics have the potential to guide precision medicine, where patients may benefit from therapeutic approaches optimally suited to their disease. Also, the integration of genotypic and phenotypic diagnostic methods is supporting better informed treatment decisions. Focusing on advanced PCa, this review discusses polygenic risk scores for screening of PCa and common genomic aberrations in androgen receptor (AR), PTEN-PI3K-AKT, and DNA damage response (DDR) pathways, considering clinical implications for diagnosis, prognosis, and treatment prediction. Furthermore, we evaluate liquid biopsy, protein biomarkers such as serum testosterone levels, SLFN11 expression, total alkaline phosphatase (tALP), neutrophil-to-lymphocyte ratio (NLR), tissue biopsy, and advanced imaging tools, summarizing current phenotypic biomarkers and envisaging more effective utilization of diagnostic and prognostic biomarkers in advanced PCa. We conclude that prognostic and treatment predictive biomarker discovery can improve the management of patients, especially in metastatic stages of advanced PCa. This will result in decreased mortality and enhanced quality of life and help design a personalized treatment regimen.

Evaluating approaches for constructing polygenic risk scores for prostate cancer in men of African and European ancestry.

Genome-wide polygenic risk scores (GW-PRSs) have been reported to have better predictive ability than PRSs based on genome-wide significance thresholds across numerous traits. We compared the predictive ability of several GW-PRS approaches to a recently developed PRS of 269 established prostate cancer-risk variants from multi-ancestry GWASs and fine-mapping studies (PRS269). GW-PRS models were trained with a large and diverse prostate cancer GWAS of 107,247 cases and 127,006 controls that we previously used to develop the multi-ancestry PRS269. Resulting models were independently tested in 1,586 cases and 1,047 controls of African ancestry from the California Uganda Study and 8,046 cases and 191,825 controls of European ancestry from the UK Biobank and further validated in 13,643 cases and 210,214 controls of European ancestry and 6,353 cases and 53,362 controls of African ancestry from the Million Veteran Program. In the testing data, the best performing GW-PRS approach had AUCs of 0.656 (95% CI = 0.635-0.677) in African and 0.844 (95% CI = 0.840-0.848) in European ancestry men and corresponding prostate cancer ORs of 1.83 (95% CI = 1.67-2.00) and 2.19 (95% CI = 2.14-2.25), respectively, for each SD unit increase in the GW-PRS. Compared to the GW-PRS, in African and European ancestry men, the PRS269 had larger or similar AUCs (AUC = 0.679, 95% CI = 0.659-0.700 and AUC = 0.845, 95% CI = 0.841-0.849, respectively) and comparable prostate cancer ORs (OR = 2.05, 95% CI = 1.87-2.26 and OR = 2.21, 95% CI = 2.16-2.26, respectively). Findings were similar in the validation studies. This investigation suggests that current GW-PRS approaches may not improve the ability to predict prostate cancer risk compared to the PRS269 developed from multi-ancestry GWASs and fine-mapping.

Characterisation of cell lines derived from prostate cancer patients with localised disease.

BACKGROUND: Prostate cancer is a broad-spectrum disease, spanning from indolent to a highly aggressive lethal malignancy. Prostate cancer cell lines are essential tools to understanding the basic features of this malignancy, as well as in identifying novel therapeutic strategies. However, most cell lines routinely used in prostate cancer research are derived from metastatic disease and may not fully elucidate the molecular events underlying the early stages of cancer development and progression. Thus, there is a need for new cell lines derived from localised disease to better span the disease spectrum. METHODS: Prostatic tissue from the primary site, and adjacent non-cancerous tissue was obtained from four patients with localised disease undergoing radical prostatectomy. Epithelial cell outgrowths were immortalised with human papillomavirus type 16 (HPV16) E6 and E7 to establish monoclonal cell lines. Chromosomal ploidy was imaged and STR profiles were determined. Cell morphology, colony formation and cell proliferation characteristics were assessed. Androgen receptor (AR) expression and AR-responsiveness to androgen treatment were analysed by immunofluorescence and RT-qPCR, respectively. RNA-seq analysis was performed to identify prostate lineage markers and expression of prostate cancer tumorigenesis-related genes. RESULTS: Two benign cell lines derived from non-cancer cells (AQ0420 and AQ0396) and two tumour tissue derived cancer cell lines (AQ0411 and AQ0415) were immortalised from four patients with localised prostatic adenocarcinoma. The cell lines presented an epithelial morphology and a slow to moderate proliferative rate. None of the cell lines formed anchorage independent colonies or displayed AR-responsiveness. Comparative RNA-seq expression analysis confirmed the prostatic lineage of the four cell lines, with a distinct gene expression profile from that of the metastatic prostate cancer cell lines, PC-3 and LNCaP. CONCLUSIONS: Comprehensive characterization of these cell lines may provide new in vitro tools that could bridge the current knowledge gap between benign, early-stage and metastatic disease.

Evaluating Approaches for Constructing Polygenic Risk Scores for Prostate Cancer in Men of African and European Ancestry.

Genome-wide polygenic risk scores (GW-PRS) have been reported to have better predictive ability than PRS based on genome-wide significance thresholds across numerous traits. We compared the predictive ability of several GW-PRS approaches to a recently developed PRS of 269 established prostate cancer risk variants from multi-ancestry GWAS and fine-mapping studies (PRS 269 ). GW-PRS models were trained using a large and diverse prostate cancer GWAS of 107,247 cases and 127,006 controls used to develop the multi-ancestry PRS 269 . Resulting models were independently tested in 1,586 cases and 1,047 controls of African ancestry from the California/Uganda Study and 8,046 cases and 191,825 controls of European ancestry from the UK Biobank and further validated in 13,643 cases and 210,214 controls of European ancestry and 6,353 cases and 53,362 controls of African ancestry from the Million Veteran Program. In the testing data, the best performing GW-PRS approach had AUCs of 0.656 (95% CI=0.635-0.677) in African and 0.844 (95% CI=0.840-0.848) in European ancestry men and corresponding prostate cancer OR of 1.83 (95% CI=1.67-2.00) and 2.19 (95% CI=2.14-2.25), respectively, for each SD unit increase in the GW-PRS. However, compared to the GW-PRS, in African and European ancestry men, the PRS 269 had larger or similar AUCs (AUC=0.679, 95% CI=0.659-0.700 and AUC=0.845, 95% CI=0.841-0.849, respectively) and comparable prostate cancer OR (OR=2.05, 95% CI=1.87-2.26 and OR=2.21, 95% CI=2.16-2.26, respectively). Findings were similar in the validation data. This investigation suggests that current GW-PRS approaches may not improve the ability to predict prostate cancer risk compared to the multi-ancestry PRS 269 constructed with fine-mapping.

The roles of proteases in prostate cancer.

Since the proposition of the pro-invasive activity of proteolytic enzymes over 70 years ago, several roles for proteases in cancer progression have been established. About half of the 473 active human proteases are expressed in the prostate and many of the most well-characterized members of this enzyme family are regulated by androgens, hormones essential for development of prostate cancer. Most notably, several kallikrein-related peptidases, including KLK3 (prostate-specific antigen, PSA), the most well-known prostate cancer marker, and type II transmembrane serine proteases, such as TMPRSS2 and matriptase, have been extensively studied and found to promote prostate cancer progression. Recent findings also suggest a critical role for proteases in the development of advanced and aggressive castration-resistant prostate cancer (CRPC). Perhaps the most intriguing evidence for this role comes from studies showing that the protease-activated transmembrane proteins, Notch and CDCP1, are associated with the development of CRPC. Here, we review the roles of proteases in prostate cancer, with a special focus on their regulation by androgens.

GelMA and Biomimetic Culture Allow the Engineering of Mineralized, Adipose, and Tumor Tissue Human Microenvironments for the Study of Advanced Prostate Cancer In Vitro and In Vivo.

Increasing evidence shows bone marrow (BM)-adipocytes as a potentially important contributor in prostate cancer (PCa) bone metastases. However, a lack of relevant models has prevented the full understanding of the effects of human BM-adipocytes in this microenvironment. It is hypothesized that the combination of tunable gelatin methacrylamide (GelMA)-based hydrogels with the biomimetic culture of human cells would offer a versatile 3D platform to engineer human bone tumor microenvironments containing BM-adipocytes. Human osteoprogenitors, adipocytes, and PCa cells are individually cultured in vitro in GelMA hydrogels, leading to mineralized, adipose, and PCa tumor 3D microtissues, respectively. Osteoblast mineralization and tumor spheroid formation are tailored by hydrogel stiffness with lower stiffnesses correlating with increased mineralization and tumor spheroid size. Upon coculture with tumor cells, BM-adipocytes undergo morphological changes and delipidation, suggesting reciprocal interactions between the cell types. When brought in vivo, the mineralized and adipose microtissues successfully form a humanized fatty bone microenvironment, presenting, for the first time, with human adipocytes. Using this model, an increase in tumor burden is observed when human adipocytes are present, suggesting that adipocytes support early bone tumor growth. The advanced platform presented here combines natural aspects of the microenvironment with tunable properties useful for bone tumor research.

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.

A humanized orthotopic tumor microenvironment alters the bone metastatic tropism of prostate cancer cells.

Prostate cancer (PCa) is the second most commonly diagnosed cancer in men, and bone is the most frequent site of metastasis. The tumor microenvironment (TME) impacts tumor growth and metastasis, yet the role of the TME in PCa metastasis to bone is not fully understood. We used a tissue-engineered xenograft approach in NOD-scid IL2Rγnull (NSG) mice to incorporate two levels of humanization; the primary tumor and TME, and the secondary metastatic bone organ. Bioluminescent imaging, histology, and immunohistochemistry were used to study metastasis of human PC-3 and LNCaP PCa cells from the prostate to tissue-engineered bone. Here we show pre-seeding scaffolds with human osteoblasts increases the human cellular and extracellular matrix content of bone constructs, compared to unseeded scaffolds. The humanized prostate TME showed a trend to decrease metastasis of PC-3 PCa cells to the tissue-engineered bone, but did not affect the metastatic potential of PCa cells to the endogenous murine bones or organs. On the other hand, the humanized TME enhanced LNCaP tumor growth and metastasis to humanized and murine bone. Together this demonstrates the importance of the TME in PCa bone tropism, although further investigations are needed to delineate specific roles of the TME components in this context.

Allele-Specific MicroRNA-Mediated Regulation of a Glycolysis Gatekeeper PDK1 in Cancer Metabolism.

BACKGROUND: Emerging evidence has revealed that genetic variations in microRNA (miRNA) binding sites called miRSNPs can alter miRNA binding in an allele-specific manner and impart prostate cancer (PCa) risk. Two miRSNPs, rs1530865 (G > C) and rs2357637 (C > A), in the 3' untranslated region of pyruvate dehydrogenase kinase 1 (PDK1) have been previously reported to be associated with PCa risk. However, these results have not been functionally validated. METHODS: In silico analysis was used to predict miRNA-PDK1 interactions and was tested using PDK1 knockdown, miRNA overexpression and reporter gene assay. RESULTS: PDK1 expression was found to be upregulated in PCa metastasis. Further, our results show that PDK1 suppression reduced the migration, invasion, and glycolysis of PCa cells. Computational predictions showed that miR-3916, miR-3125 and miR-3928 had a higher binding affinity for the C allele than the G allele for the rs1530865 miRSNP which was validated by reporter gene assays. Similarly, miR-2116 and miR-889 had a higher affinity for the A than C allele of the rs2357637 miRSNP. Overexpression of miR-3916 and miR-3125 decreased PDK1 protein levels in cells expressing the rs1530865 SNP C allele, and miR-2116 reduced in cells with the rs2357637 SNP A allele. CONCLUSIONS: The present study is the first to report the regulation of the PDK1 gene by miRNAs in an allele-dependent manner and highlights the role of PDK1 in metabolic adaption associated with PCa progression.

In vitro engineering of a bone metastases model allows for study of the effects of antiandrogen therapies in advanced prostate cancer.

While androgen-targeted therapies are routinely used in advanced prostate cancer (PCa), their effect is poorly understood in treating bone metastatic lesions and ultimately results in the development of metastatic castrate resistant prostate cancer (mCRPC). Here, we used an all-human microtissue-engineered model of mineralized metastatic tissue combining human osteoprogenitor cells, 3D printing and prostate cancer cells, to assess the effects of the antiandrogens, bicalutamide, and enzalutamide in this microenvironment. We demonstrate that cancer/bone stroma interactions and antiandrogens drive cancer progression in a mineralized microenvironment. Probing the bone microenvironment with enzalutamide led to stronger cancer cell adaptive responses and osteomimicry than bicalutamide. Enzalutamide presented with better treatment response, in line with enzalutamide delaying time to bone-related events and enzalutamide extending survival in mCRPC. The all-human microtissue-engineered model of mineralized metastatic tissue presented here represents a substantial advance to dissect the role of the bone tumor microenvironment and responses to therapies for mCPRC.

A Suite of Activity-Based Probes To Dissect the KLK Activome in Drug-Resistant Prostate Cancer.

Kallikrein-related peptidases (KLKs) are a family of secreted serine proteases, which form a network (the KLK activome) with an important role in proteolysis and signaling. In prostate cancer (PCa), increased KLK activity promotes tumor growth and metastasis through multiple biochemical pathways, and specific quantification and tracking of changes in the KLK activome could contribute to validation of KLKs as potential drug targets. Herein we report a technology platform based on novel activity-based probes (ABPs) and inhibitors enabling simultaneous orthogonal analysis of KLK2, KLK3, and KLK14 activity in hormone-responsive PCa cell lines and tumor homogenates. Importantly, we identifed a significant decoupling of KLK activity and abundance and suggest that KLK proteolysis should be considered as an additional parameter, along with the PSA blood test, for accurate PCa diagnosis and monitoring. Using selective inhibitors and multiplexed fluorescent activity-based protein profiling (ABPP), we dissect the KLK activome in PCa cells and show that increased KLK14 activity leads to a migratory phenotype. Furthermore, using biotinylated ABPs, we show that active KLK molecules are secreted into the bone microenvironment by PCa cells following stimulation by osteoblasts suggesting KLK-mediated signaling mechanisms could contribute to PCa metastasis to bone. Together our findings show that ABPP is a powerful approach to dissect dysregulation of the KLK activome as a promising and previously underappreciated therapeutic target in advanced PCa.

KLK3 SNP-SNP interactions for prediction of prostate cancer aggressiveness.

Risk classification for prostate cancer (PCa) aggressiveness and underlying mechanisms remain inadequate. Interactions between single nucleotide polymorphisms (SNPs) may provide a solution to fill these gaps. To identify SNP-SNP interactions in the four pathways (the angiogenesis-, mitochondria-, miRNA-, and androgen metabolism-related pathways) associated with PCa aggressiveness, we tested 8587 SNPs for 20,729 cases from the PCa consortium. We identified 3 KLK3 SNPs, and 1083 (P < 3.5 × 10-9) and 3145 (P < 1 × 10-5) SNP-SNP interaction pairs significantly associated with PCa aggressiveness. These SNP pairs associated with PCa aggressiveness were more significant than each of their constituent SNP individual effects. The majority (98.6%) of the 3145 pairs involved KLK3. The 3 most common gene-gene interactions were KLK3-COL4A1:COL4A2, KLK3-CDH13, and KLK3-TGFBR3. Predictions from the SNP interaction-based polygenic risk score based on 24 SNP pairs are promising. The prevalence of PCa aggressiveness was 49.8%, 21.9%, and 7.0% for the PCa cases from our cohort with the top 1%, middle 50%, and bottom 1% risk profiles. Potential biological functions of the identified KLK3 SNP-SNP interactions were supported by gene expression and protein-protein interaction results. Our findings suggest KLK3 SNP interactions may play an important role in PCa aggressiveness.

SWATH-MS Based Proteomic Profiling of Prostate Cancer Cells Reveals Adaptive Molecular Mechanisms in Response to Anti-Androgen Therapy.

Prostate cancer (PCa) is the second most common cancer affecting men worldwide. PCa shows a broad-spectrum heterogeneity in its biological and clinical behavior. Although androgen targeted therapy (ATT) has been the mainstay therapy for advanced PCa, it inevitably leads to treatment resistance and progression to castration resistant PCa (CRPC). Thus, greater understanding of the molecular basis of treatment resistance and CRPC progression is needed to improve treatments for this lethal phenotype. The current study interrogated both proteomics and transcriptomic alterations stimulated in AR antagonist/anti-androgen (Bicalutamide and Enzalutamide) treated androgen-dependent cell model (LNCaP) in comparison with androgen-independent/castration-resistant cell model (C4-2B). The analysis highlighted the activation of MYC and PSF/SFPQ oncogenic upstream regulators in response to the anti-androgen treatment. Moreover, the study revealed anti-androgen induced genes/proteins related to transcription/translation regulation, energy metabolism, cell communication and signaling cascades promoting tumor growth and proliferation. In addition, these molecules were found dysregulated in PCa clinical proteomic and transcriptomic datasets, suggesting their potential involvement in PCa progression. In conclusion, our study provides key molecular signatures and associated pathways that might contribute to CRPC progression despite treatment with anti-androgens. Such molecular signatures could be potential therapeutic targets to improve the efficacy of existing therapies and/or predictive/prognostic value in CRPC for treatment response.

Trans-ancestry genome-wide association meta-analysis of prostate cancer identifies new susceptibility loci and informs genetic risk prediction.

Prostate cancer is a highly heritable disease with large disparities in incidence rates across ancestry populations. We conducted a multiancestry meta-analysis of prostate cancer genome-wide association studies (107,247 cases and 127,006 controls) and identified 86 new genetic risk variants independently associated with prostate cancer risk, bringing the total to 269 known risk variants. The top genetic risk score (GRS) decile was associated with odds ratios that ranged from 5.06 (95% confidence interval (CI), 4.84-5.29) for men of European ancestry to 3.74 (95% CI, 3.36-4.17) for men of African ancestry. Men of African ancestry were estimated to have a mean GRS that was 2.18-times higher (95% CI, 2.14-2.22), and men of East Asian ancestry 0.73-times lower (95% CI, 0.71-0.76), than men of European ancestry. These findings support the role of germline variation contributing to population differences in prostate cancer risk, with the GRS offering an approach for personalized risk prediction.

KLK4 Induces Anti-Tumor Effects in Human Xenograft Mouse Models of Orthotopic and Metastatic Prostate Cancer.

Recent reports have suggested the role of kallikrein-related peptidase 4 (KLK4) to be that of remodeling the tumor microenvironment in many cancers, including prostate cancer. Notably, these studies have suggested a pro-tumorigenic role for KLK4, especially in prostate cancer. However, these have been primarily in vitro studies, with limited in vivo studies performed to date. Herein, we employed an orthotopic inoculation xenograft model to mimic the growth of primary tumors, and an intracardiac injection to induce metastatic dissemination to determine the in vivo tumorigenic effects of KLK4 overexpressed in PC3 prostate cancer cells. Notably, we found that these KLK4-expressing cells gave rise to smaller localized tumors and decreased metastases than the parent PC-3 cells. To our knowledge, this is the first report of an anti-tumorigenic effect of KLK4, particularly in prostate cancer. These findings also provide a cautionary tale of the need for in vivo analyses to substantiate in vitro experimental data.

An integrative multi-omics analysis to identify candidate DNA methylation biomarkers related to prostate cancer risk.

It remains elusive whether some of the associations identified in genome-wide association studies of prostate cancer (PrCa) may be due to regulatory effects of genetic variants on CpG sites, which may further influence expression of PrCa target genes. To search for CpG sites associated with PrCa risk, here we establish genetic models to predict methylation (N = 1,595) and conduct association analyses with PrCa risk (79,194 cases and 61,112 controls). We identify 759 CpG sites showing an association, including 15 located at novel loci. Among those 759 CpG sites, methylation of 42 is associated with expression of 28 adjacent genes. Among 22 genes, 18 show an association with PrCa risk. Overall, 25 CpG sites show consistent association directions for the methylation-gene expression-PrCa pathway. We identify DNA methylation biomarkers associated with PrCa, and our findings suggest that specific CpG sites may influence PrCa via regulating expression of candidate PrCa target genes.

The effect of sample size on polygenic hazard models for prostate cancer.

We determined the effect of sample size on performance of polygenic hazard score (PHS) models in prostate cancer. Age and genotypes were obtained for 40,861 men from the PRACTICAL consortium. The dataset included 201,590 SNPs per subject, and was split into training and testing sets. Established-SNP models considered 65 SNPs that had been previously associated with prostate cancer. Discovery-SNP models used stepwise selection to identify new SNPs. The performance of each PHS model was calculated for random sizes of the training set. The performance of a representative Established-SNP model was estimated for random sizes of the testing set. Mean HR98/50 (hazard ratio of top 2% to average in test set) of the Established-SNP model increased from 1.73 [95% CI: 1.69-1.77] to 2.41 [2.40-2.43] when the number of training samples was increased from 1 thousand to 30 thousand. Corresponding HR98/50 of the Discovery-SNP model increased from 1.05 [0.93-1.18] to 2.19 [2.16-2.23]. HR98/50 of a representative Established-SNP model using testing set sample sizes of 0.6 thousand and 6 thousand observations were 1.78 [1.70-1.85] and 1.73 [1.71-1.76], respectively. We estimate that a study population of 20 thousand men is required to develop Discovery-SNP PHS models while 10 thousand men should be sufficient for Established-SNP models.

The molecular function of kallikrein-related peptidase 14 demonstrates a key modulatory role in advanced prostate cancer.

Kallikrein-related peptidase 14 (KLK14) is one of the several secreted KLK serine proteases involved in prostate cancer (PCa) pathogenesis. While relatively understudied, recent reports have identified KLK14 as overexpressed during PCa development. However, the modulation of KLK14 expression during PCa progression and the molecular and biological functions of this protease in the prostate tumor microenvironment remain unknown. To determine the modulation of KLK14 expression during PCa progression, we analyzed the expression levels of KLK14 in patient samples using publicly available databases and immunohistochemistry. In order to delineate the molecular mechanisms involving KLK14 in PCa progression, we integrated proteomic, transcriptomic, and in vitro assays with the goal to identify substrates, related-signaling pathways, and functional roles of this protease. We showed that KLK14 expression is elevated in advanced PCa, and particularly in metastasis. Additionally, KLK14 levels were found to be decreased in PCa tissues from patients responsive to neoadjuvant therapy compared to untreated patients. Furthermore, we also identified that KLK14 expression reoccurred in patients who developed castrate-resistant PCa. The combination of proteomic and transcriptomic analysis as well as functional assays revealed several new KLK14 substrates (agrin, desmoglein 2, vitronectin, laminins) and KLK14-regulated genes (Interleukin 32, midkine, SRY-Box 9), particularly an involvement of the mitogen-activated protein kinase 1 and interleukin 1 receptor pathways, and an involvement of KLK14 in the regulation of cellular migration, supporting its involvement in aggressive features of PCa progression. In conclusion, our work showed that KLK14 expression is associated with the development of aggressive PCa suggesting that targeting this protease could offer a novel route to limit the progression of prostate tumors. Additional work is necessary to determine the benefits and implications of targeting/cotargeting KLK14 in PCa as well as to determine the potential use of KLK14 expression as a predictor of PCa aggressiveness or response to treatment.