Prognostic Biomarker For Prostate Cancer Research Articles

Increased α2,3-sialyl N-glycosylated prostate-specific membrane antigen (PSMA) in post-DRE urine is associated with high grade group prostate cancer.

Aberrant glycosylation of proteins is an important hallmark in multiple cancers. Prostate-specific membrane antigen (PSMA), a highly glycosylated protein with 10 N-linked glycosylation sites, is an Food and Drug Administration approved theranostic for prostate cancer. However, glycosylation changes in PSMA that are associated with prostate cancer disease progression have not been fully characterized. We investigated whether urinary PSMA sialylation correlate with high-grade prostate cancer. Urine samples were collected from men after digital rectal examination (DRE) before prostate biopsy. Lectin-antibody enzyme-linked immunoassay was used to quantify α2,3-sialyl PSMA in post-DRE urine samples from subjects with benign prostate tumors, Grade Group 1 prostate cancer and those with Grade Group ≥2 disease. There are significant increases in α2,3-sialylated PSMA in patients with Grade Group ≥2 disease compared to benign (p = 0.0009) and those with Grade Group 1 disease (p = 0.0063). There were no significant differences in α2,3-sialyl PSMA levels between Grade Group 1 and benign prostate tumors (p = 0.7947). Our study shows that there are significant differences in the abundance of α2,3-sialylated PSMA in post-DRE urines from disease stratified prostate cancer patients, and the increase is correlated with progression and disease severity. The detection of increased PSMA sialyation in post-DRE urines from patients with higher Grade Group ≥2 disease states provides novel untapped potential for the development of prognostic biomarkers for prostate cancer. Specifically, quantitation of α2,3-sialylated PSMA shows potential for discriminating between benign to intermediate grade disease, which is a significant clinical challenge in staging and risk stratification of prostate cancer.

Diagnostic and prognostic biomarkers in prostate cancer

Diagnostic and prognostic biomarkers in prostate cancer

The Suppression of the Epithelial to Mesenchymal Transition in Prostate Cancer through the Targeting of MYO6 Using MiR-145-5p.

Aberrant expression of miR-145-5p has been observed in prostate cancer where is has been suggested to play a tumor suppressor role. In other cancers, miR-145-5p acts as an inhibitor of epithelial-to-mesenchymal transition (EMT), a key molecular process for tumor progression. However, the interaction between miR-145-5p and EMT remains to be elucidated in prostate cancer. In this paper the link between miR-145-5p and EMT in prostate cancer was investigated using a combination of in silico and in vitro analyses. miR-145-5p expression was significantly lower in prostate cancer cell lines compared to normal prostate cells. Bioinformatic analysis of The Cancer Genome Atlas prostate adenocarcinoma (TCGA PRAD) data showed significant downregulation of miR-145-5p in prostate cancer, correlating with disease progression. Functional enrichment analysis significantly associated miR-145-5p and its target genes with EMT. MYO6, an EMT-associated gene, was identified and validated as a novel target of miR-145-5p in prostate cancer cells. In vitro manipulation of miR-145-5p levels significantly altered cell proliferation, clonogenicity, migration and expression of EMT-associated markers. Additional TCGA PRAD analysis suggested miR-145-5p tumor expression may be useful predictor of disease recurrence. In summary, this is the first study to report that miR-145-5p may inhibit EMT by targeting MYO6 in prostate cancer cells. The findings suggest miR-145-5p could be a useful diagnostic and prognostic biomarker for prostate cancer.

Loss of AR-regulated AFF3 contributes to prostate cancer progression and reduces ferroptosis sensitivity by downregulating ACSL4 based on single-cell sequencing analysis.

Prostate cancer (PCa) is one of the most common cancers affecting the health of men worldwide. Castration-resistant prostate cancer (CRPC), the advanced and refractory phase of prostate cancer, has multiple mechanisms of resistance to androgen deprivation therapy (ADT) such as AR mutations, aberrant androgen synthase, and abnormal expression of AR-related genes. Based on the research of the AR pathway, new drugs for the treatment of CRPC have been developed in clinical practice, such as Abiraterone and enzalutamide. However, many areas in this pathway are still worth exploring. In this study, single-cell sequencing analysis was utilized to scrutinize significant genes in the androgen receptor (AR) pathway related to CRPC. Our analysis of single-cell sequencing combined with bulk-cell sequencing revealed a substantial downregulation of AR-regulated AFF3 in CRPC. Overexpression of AFF3 restricted the proliferation and migration of prostate cancer cells whilst also increasing their sensitivity towards enzalutamide, while knockdown of AFF3 had the opposite effect. To elucidate the mechanism of tumor inhibition by AFF3, we applied GSVA and GSEA to investigate the metabolic pathways related to AFF3 and revealed that AFF3 had an impact on fatty acids metabolism and ferroptosis through the regulation of ACSL4 protein expression. Based on correlation analysis and flow cytometry, we can speculate that AFF3 can impact the sensitivity of the CRPC cell lines to the ferroptosis inducer (RSL3) by regulating ACSL4. Therefore, our findings may provide new insights into the mechanisms of drug resistance in CRPC, and AFF3 may serve as a novel prognostic biomarker in prostate cancer.

PTEN, ERG, SPINK1, and TFF3 Status and Relationship in a Prostate Cancer Cohort from Jordanian Arab Population.

Background and Objectives: Prognostic biomarkers in prostate cancer (PCa) include PTEN, ERG, SPINK1, and TFF3. Their relationships and patterns of expression in PCa in developing countries, including Jordan, have not yet been investigated. Materials and Methods: A tissue microarray (TMA) of PCa patients was taken from paraffin-embedded tissue blocks for 130 patients. PTEN, ERG, SPINK1, and TFF3 expression profiles were examined using immunohistochemistry (IHC) and correlated with each other and other clinicopathological factors. Results: PTEN loss of any degree was observed in 42.9% of PCa cases. ERG and TFF3 were expressed in 59.3% and 46.5% of PCa cases, respectively. SPINK1 expression was observed in 6 out of 104 PCa cases (5.4%). Among all PCa cases (n = 104), 3.8% (n = 4) showed SPINK1+/ERG+ phenotype, 1.9% (n = 2) showed SPINK1+/ERG- phenotype, 56.7% (n = 59) showed SPINK1-/ERG+ phenotype, and 37.5% showed SPINK1-/ERG- phenotype (n = 39). Among ERG positive cases (n = 63), 6.3% were SPINK1 positive. Among SPINK1 positive cases (n = 6), 66.7% were ERG positive. SPINK1 expression was predominantly observed in a subgroup of cancers that expressed TFF3 (6/6). Additionally, a statistically significant loss of PTEN expression was observed from Gleason Score 6 (GS6) (Grade Group 1 (GG1)) to GS9-10 (GG5); (p-value 0.019). Conclusions: This is the first study to look at the status of the PTEN, ERG, SPINK1, and TFF3 genes in a Jordanian Arab population. Loss of PTEN has been linked to more aggressive prostate cancer with high GSs/GGs. SPINK1 expression was predominantly observed in a subgroup of cancers that expressed TFF3. Our results call for screening these biomarkers for grading and molecular subtyping of the disease.

GLIS1, Correlated with Immune Infiltrates, Is a Potential Prognostic Biomarker in Prostate Cancer.

Prostate cancer (PCa) is a prevalent malignant disease and the primary reason for cancer-related mortality among men globally. GLIS1 (GLIS family zinc finger 1) is a key regulator in various pathologies. However, the expression pattern, clinical relevance, and immunomodulatory function of GLIS1 in PCa remain unclear. In this study, GLIS1 was discovered to serve as a key gene in PCa by integrating mRNA and miRNA expression profiles from GEO database. We systematically explored the expression and prognostic values of GLIS1 in cancers using multiple databases. Additionally, we examined the functions of GLIS1 and the relationship between GLIS1 expression levels and immune infiltration in PCa. Results showed that GLIS1 was differentially expressed between normal and tumor tissues in various cancer types and was significantly low-expressed in PCa. Low GLIS1 expression was associated with poor PCa prognosis. GLIS1 was also involved in the activation, proliferation, differentiation, and migration of immune cells, and its expression showed a positive correlation with the infiltration of various immune cells. Moreover, GLIS1 expression was positively associated with various chemokines/chemokine receptors, indicating the involvement in regulating immune cell migration. In summary, GLIS1 is a potential prognostic biomarker and a therapeutic target to modulate anti-tumor immune response in PCa.

A scalable approach to characterize pleiotropy across thousands of human diseases and complex traits using GWAS summary statistics

Genome-wide association studies (GWASs) across thousands of traits have revealed the pervasive pleiotropy of trait-associated genetic variants. While methods have been proposed to characterize pleiotropic components across groups of phenotypes, scaling these approaches to ultra-large-scale biobanks has been challenging. Here, we propose FactorGo, a scalable variational factor analysis model to identify and characterize pleiotropic components using biobank GWAS summary data. In extensive simulations, we observe that FactorGo outperforms the state-of-the-art (model-free) approach tSVD in capturing latent pleiotropic factors across phenotypes while maintaining a similar computational cost. We apply FactorGo to estimate 100 latent pleiotropic factors from GWAS summary data of 2,483 phenotypes measured in European-ancestry Pan-UK BioBank individuals (N= 420,531). Next, we find that factors from FactorGo are more enriched with relevant tissue-specific annotations than those identified by tSVD (p= 2.58E-10) and validate our approach by recapitulating brain-specific enrichment for BMI and the height-related connection between reproductive system and muscular-skeletal growth. Finally, our analyses suggest shared etiologies between rheumatoid arthritis and periodontal condition in addition to alkaline phosphatase as a candidate prognostic biomarker for prostate cancer. Overall, FactorGo improves our biological understanding of shared etiologies across thousands of GWASs.

Multi-omics approach for identifying CNV-associated lncRNA signatures with prognostic value in prostate cancer

BackgroundProstate cancer, the second most prevalent malignancy among men, poses a significant threat to affected patients’ well-being due to its poor prognosis. Novel biomarkers are required to enhance clinical outcomes and tailor personalized treatments. Herein, we describe our research to explore the prognostic value of long non-coding RNAs (lncRNAs) deregulated by copy number variations (CNVs) in prostate cancer. MethodsThe study employed an integrative multi-omics data analysis of the prostate cancer transcriptomic, CNV and methylation datasets to identify prognosis-related subtypes. Subtype-specific expression profiles of protein-coding genes (PCGs) and lncRNAs were determined. We analysed CNV patterns of lncRNAs across the genome to identify subtype-specific lncRNAs with CNV changes. LncRNAs exhibiting significant amplification or deletion and a positive correlation were designated CNV-deregulated lncRNAs. A prognostic risk score model was subsequently developed using these CNV-driven lncRNAs. ResultsSix molecular subtypes of prostate cancer were identified, demonstrating significant differences in prognosis (P = 0.034). The CNV profiles of subtype-specific lncRNAs were examined, revealing their correlation with CNV amplification or deletion. Six lncRNAs (CCAT2, LINC01593, LINC00276, GACAT2, LINC00457, LINC01343) were selected based on significant CNV amplifications or deletions using a rigorous univariate Cox proportional risk regression model. A robust risk score model was developed, stratifying patients into high-risk and low-risk categories. Notably, our prognostic model based on these six lncRNAs exhibited exceptional predictive capabilities for recurrence-free survival (RFS) in prostate cancer patients (P = 0.024). ConclusionsOur study successfully identified a prognostic risk score model comprising six CNV-driven lncRNAs that could potentially be prognostic biomarkers for prostate cancer. These lncRNA signatures are closely associated with RFS, providing promising prospects for improved patient prognostication and personalized therapeutic strategies for novel prostate cancer treatment.

Long Chain Non-Coding RNA MSC-AS1 Promote Invasion and Migration of Prostate Cancer Through Regulating microRNA-190a-3p

We investigated the role of the lncRNA MSC-AS1 in prostate cancer (PCa) by analyzing its expression in 56 pairs of PCa tissues and adjacent tissues. We examined the relationship between MSC-AS1 expression, clinicopathological indicators, and patient prognosis. In PCa cell lines, we overexpressed or knocked down MSC-AS1 and assessed its impact on cell function using transwell assays and wound healing tests. We explored the interaction between MSC-AS1 and miR-190a-3p using luciferase reporter assays. Our findings showed significantly higher MSC-AS1 expression in PCa tumor specimens compared to adjacent tissues. High MSC-AS1 expression correlated with increased incidence of lymph node and distant metastasis. Overexpressing MSC-AS1 reduced cell invasiveness and migration, while knocking it down enhanced these abilities. We observed decreased miR-190a-3p expression in PCa tissues, negatively correlating with MSC-AS1 expression. Modulating miR-190a-3p expression counteracted the effects of MSC-AS1 on cell invasiveness and migration. In conclusion, our study highlights the association of MSC-AS1 with metastasis and poor prognosis in PCa patients, suggesting its involvement in the malignant progression of the disease via miR-190a-3p modulation. MSC-AS1 holds potential as a prognostic biomarker for PCa and a therapeutic target for novel treatment strategies. Further research is needed to understand the underlying mechanisms and validate the clinical implications of targeting MSC-AS1 and miR-190a-3p in PCa management.

Targeting of AKT1 by miR-143-3p Suppresses Epithelial-to-Mesenchymal Transition in Prostate Cancer.

An altered expression of miR-143-3p has been previously reported in prostate cancer where it is purported to play a tumor suppressor role. Evidence from other cancers suggests miR-143-3p acts as an inhibitor of epithelial-to-mesenchymal transition (EMT), a key biological process required for metastasis. However, in prostate cancer the interaction between miR-143-3p and EMT-associated mechanisms remains unclear. Therefore, this paper investigated the link between miR-143-3p and EMT in prostate cancer using in vitro and in silico analyses. PCR detected that miR-143-3p expression was significantly decreased in prostate cancer cell lines compared to normal prostate cells. Bioinformatic analysis of The Cancer Genome Atlas Prostate Adenocarcinoma (TCGA PRAD) data showed a significant downregulation of miR-143-3p in prostate cancer, correlating with pathological markers of advanced disease. Functional enrichment analysis confirmed the significant association of miR-143-3p and its target genes with EMT. The EMT-linked gene AKT1 was subsequently shown to be a novel target of miR-143-3p in prostate cancer cells. The in vitro manipulation of miR-143-3p levels significantly altered the cell proliferation, clonogenicity, migration and expression of EMT-associated markers. Further TCGA PRAD analysis suggested miR-143-3p tumor expression may be a useful predictor of disease recurrence. In summary, this is the first study to report that miR-143-3p overexpression in prostate cancer may inhibit EMT by targeting AKT1. The findings suggest miR-143-3p could be a useful diagnostic and prognostic biomarker for prostate cancer.

In Silico Bioinformatics Analysis on the Role of Long Non-Coding RNAs as Drivers and Gatekeepers of Androgen-Independent Prostate Cancer Using LNCaP and PC-3 Cells.

Prostate cancer (PCa) is the leading cancer in men globally. The association between PCa and long non-coding RNAs (lncRNAs) has been reported. Aberrantly expressed lncRNAs have been documented in each of the cancer "hallmarks". Androgen signaling plays an important role in PCa progression. This study aimed to profile the aberrantly expressed lncRNAs in androgen-dependent (LNCaP) PCa compared to androgen-independent (PC-3) PCa cells. This was achieved by using a 384-well plate of PCa lncRNA gene panel. Differential expression of ±2 up or downregulation was determined using the CFX Maestro software v2.1. LncSEA and DIANA-miRPath were used to identify the enriched pathways. Telomerase RNA component (TERC) lncRNA was illustrated to participate in various tumourigenic classes by in silico bioinformatics analysis and was thus selected for validation using RT-qPCR. Further bioinformatics analysis revealed the involvement of differentially expressed lncRNAs in oncogenic pathways. Some lncRNAs undergo hypermethylation, others are encapsulated by exosomes, while others interact with several microRNAs (miRNAs), favouring tumourigenic pathways. Notably, TERC lncRNA was shown to interact with tumour-suppressor miRNAs hsa-miR-4429 and hsa-miR-320b. This interaction in turn activates TGF-β-signaling and ECM-receptor interaction pathways, favouring the progression of PCa. Understanding lncRNAs as competitive endogenous RNA molecules and their interactions with miRNAs may aid in the identification of novel prognostic PCa biomarkers and therapeutic targets.

MFast-SeqS-based aneuploidy score in circulating cell-free DNA is a prognostic biomarker in prostate cancer.

Multiple prognostic biomarkers, including circulating tumour cell (CTC) counts, exist in metastatic castration-resistant prostate cancer (mCRPC) patients, but none of them have been implemented into daily clinical care. The modified fast aneuploidy screening test-sequencing system (mFast-SeqS), which yields a genome-wide aneuploidy score, is able to reflect the fraction of cell-free tumour DNA (ctDNA) within cell-free DNA (cfDNA) and may be a promising biomarker in mCRPC. In this study, we investigated the prognostic value of dichotomized aneuploidy scores (< 5 vs. ≥ 5) as well as CTC counts (< 5 vs. ≥ 5) in 131 mCRPC patients prior to treatment with cabazitaxel. We validated our findings in an independent cohort of 50 similarly treated mCRPC patients. We observed that, similar to the dichotomized CTC count [HR: 2.92; 95% confidence interval (CI);1.84-4.62], dichotomized aneuploidy scores (HR: 3.24; CI: 2.12-4.94) significantly correlated with overall survival in mCRPC patients. We conclude that a dichotomized aneuploidy score from cfDNA is a prognostic marker for survival in mCRPC patients within our discovery cohort and in an independent mCRPC validation cohort. Therefore, this easy and robust minimally-invasive assay can be readily implemented as a prognostic marker in mCRPC. A dichotomized aneuploidy score might also be used as a stratification factor in clinical studies to account for tumour load.

High SLC20A1 Expression Indicates Poor Prognosis in Prostate Cancer.

High expression of solute carrier family 20 member 1 (SLC20A1) indicates poor clinical outcomes for patients with breast cancer subtypes treated with endocrine therapy and radiotherapy. However, the association between SLC20A1 expression and clinical outcomes in prostate cancer remains to be determined. Open-source datasets (The Cancer Genome Atlas prostate, Stand Up to Cancer-Prostate Cancer Foundation Dream Team, and The Cancer Genome Atlas PanCancer Atlas) were downloaded and analyzed. SLC20A1 expression was analyzed in prostate cancer and normal prostate tissue. Survival analysis using Kaplan-Meier curves and Cox regression analysis were performed to examine patient prognosis, as well as the effects of endocrine therapy and radiotherapy on high SLC20A1 expression in patients with prostate cancer. SLC20A1 was higher in prostate cancer than in normal prostate tissues. High SLC20A1 expression predicted poor disease-free and progression-free survival. Following endocrine therapy, no significant difference in prognosis was observed between patients with high SLC20A1 and those with low SLC20A1 expression. However, following radiotherapy, high SLC20A1 expression tended to be associated with a poor clinical outcome. SLC20A1 may serve as a prognostic biomarker for prostate cancer, and the recommended treatment for patients with high SLC20A1 expression is endocrine therapy.

Comprehensive analysis the diagnosis, malignant progression and immune infiltrate of ANXA6 in prostate cancer.

Annexins (ANXAs) play a crucial role in the development and progression of tumors. However, their specific involvement in prostate cancer (PCa) remains unclear. To investigate the function and clinical significance of key ANXAs in PCa. Multiple databases were used to analyze the expression levels, genetic variations, potential prognostic value and clinical significance of ANXAs in PCa. Then, the co-expressed genes of ANXA6 were identified, and the correlation between ANXA6 and immune cell infiltration was validated using the Tumor Immune Estimation Resource (TIMER) database. Additionally, in vitro assays such as Cell Counting Kit-8 (CCK-8), Colony Formation, Transwell and T-cell Chemotaxis assays were conducted to validate the functions of ANXA6. Moreover, multiple types of in vivo assays were performed to further validate the identified ANXA6 functions. The results demonstrated that ANXA2, ANXA6 and ANXA8 were significantly downregulated in PCa. ANXA6 upregulation was significantly associated with improved PCa patients' overall survival. Enrichment analysis revealed that ANXA6 and its co-expressed genes were involved in tumor progression, and ANXA6 overexpression could effectively inhibit the proliferation, migration and invasion of PC-3 cells. In vivo studies also demonstrated that ANXA6 overexpression suppressed tumor growth. Importantly, ANXA6 was found to promote the chemotaxis of CD4+ T cells and CD8+ T cells towards PC-3 cells, and the overexpression of ANXA6 in PC-3 cells promoted the polarization of macrophages into M1 macrophages in the supernatant of PCa cells. ANXA6 demonstrated promising potential for consideration as a prognostic biomarker in PCa as it was found to play key roles in regulating immune cell infiltration and the malignant progression to PCa.

Abstract 25: Competing Endogenous RNA (ceRNA) Networks Implicated in Prostate Cancer Progression to Castration Resistance Identified Through Bioinformatics Analyses

Abstract Purpose: Long non-coding RNAs (lncRNAs) regulate several biochemical pathways and contribute to the pathophysiology of cancer. In previous analyses, we identified 27 lncRNAs whose expression respond to hormone therapy in prostate cancer patients. Furthermore, in castration-resistant prostate cancer (CRPC), their levels were restored to those observed in therapy-naïve primary tumors. Nevertheless, lncRNAs contribution in tumorigenesis is still not understood. Since one mechanism of action of lncRNAs is acting as sponges of miRNAs, our main goal was to identify lncRNA-miRNA-mRNA networks altered during prostate cancer progression. Methods: We performed a bioinformatics-based analysis using public datasets comprising 40 primary prostate tumors (11 paired pre- and post-androgen deprivation therapy (ADT) and 29 pre-ADT) and 8 CRPC. We used miRNet (a miRNA-centric network visual analytics platform) to seek miRNAs that target both lncRNAs and mRNAs, and constructed ceRNA networks. Results: We identified 105 mRNAs differentially expressed in both post- vs pre-ADT primary tumors and CRPC vs post-ADT. We found that PCGEM1 (lncRNA) expression correlates with ASPM (mRNA) expression (r=0.51, p=8.2E-13), and these two RNAs have target sequences for the binding of hsa-miR-506-3p and hsa-miR-124-3p. These results identified a possible PCGEM1-hsa-miR-506-3p/hsa-miR-124-3p-ASPM ceRNA involved in prostate cancer progression to castration resistance. Other ceRNAs identified included RAB3B mRNA (RAS oncogene family) and are: PCGEM1-hsa-miR-124-3p-RAB3B, LINC01087-hsa-miR-130a-3p-RAB3B, and LINC01671-hsa-miR-145-5p-RAB3B. Conclusion: These results give new insights in ceRNA dysregulation in prostate cancer; and ultimately, they might help to identify new prognostic biomarkers for prostate cancer and new druggable targets for avoiding/delaying progression to CRPC. Citation Format: Sabrina Ledesma-Bazan, Florencia Cascardo, Juan Bizzotto, María Sol Ruiz, Elba Vazquez, Geraldine Gueron, Javier Cotignola. Competing Endogenous RNA (ceRNA) Networks Implicated in Prostate Cancer Progression to Castration Resistance Identified Through Bioinformatics Analyses [abstract]. In: Proceedings of the 11th Annual Symposium on Global Cancer Research; Closing the Research-to-Implementation Gap; 2023 Apr 4-6. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2023;32(6_Suppl):Abstract nr 25.

GNL3 and PA2G4 as Prognostic Biomarkers in Prostate Cancer.

Prostate cancer is a multifocal and heterogeneous disease common in males and remains the fifth leading cause of cancer-related deaths worldwide. The prognosis of prostate cancer is variable and based on the degree of cancer and its stage at the time of diagnosis. Existing biomarkers for the prognosis of prostate cancer are unreliable and lacks specificity and sensitivity in guiding clinical decision. There is need to search for novel biomarkers having prognostic and predictive capabilities in guiding clinical outcomes. Using a bioinformatics approach, we predicted GNL3 and PA2G4 as biomarkers of prognostic significance in prostate cancer. A progressive increase in the expression of GNL3 and PA2G4 was observed during cancer progression having significant association with poor survival in prostate cancer patients. The Receiver Operating Characteristics of both genes showed improved area under the curve against sensitivity versus specificity in the pooled samples from three different GSE datasets. Overall, our analysis predicted GNL3 and PA2G4 as prognostic biomarkers of clinical significance in prostate cancer.

Prognostic impact of kallikrein-related peptidase transcript levels in prostate cancer.

We aimed to study mRNA levels and prognostic impact of all 15 human kallikrein-related peptidases (KLKs) and their targets, proteinase-activated receptors (PARs), in surgically treated prostate cancer (PCa). Seventy-nine patients with localized grade group 2-4 PCas represented aggressive cases, based on metastatic progression during median follow-up of 11 years. Eighty-six patients with similar baseline characteristics, but no metastasis during follow-up, were assigned as controls. Transcript counts were detected with nCounter technology. KLK12 protein expression was investigated with immunohistochemistry. The effects of KLK12 and KLK15 were studied in LNCaP cells using RNA interference. KLK3, -2, -4, -11, -15, -10 and -12 mRNA, in decreasing order, were expressed over limit of detection (LOD). The expression of KLK2, -3, -4 and -15 was decreased and KLK12 increased in aggressive cancers, compared to controls (P < .05). Low KLK2, -3 and -15 expression was associated with short metastasis-free survival (P < .05) in Kaplan-Meier analysis. PAR1 and -2 were expressed over LOD, and PAR1 expression was higher, and PAR2 lower, in aggressive cases than controls. Together, KLKs and PARs improved classification of metastatic and lethal disease over grade, pathological stage and prostate-specific antigen combined, in random forest analyses. Strong KLK12 immunohistochemical staining was associated with short metastasis-free and PCa-specific survival in Kaplan-Meier analysis (P < .05). Knock-down of KLK15 reduced colony formation of LNCaP cells grown on Matrigel basement membrane preparation. These results support the involvement of several KLKs in PCa progression, highlighting, that they may serve as prognostic PCa biomarkers.

Integrative multi-omics and drug–response characterization of patient-derived prostate cancer primary cells

Prostate cancer (PCa) is the second most prevalent malignancy in males across the world. A greater knowledge of the relationship between protein abundance and drug responses would benefit precision treatment for PCa. Herein, we establish 35 Chinese PCa primary cell models to capture specific characteristics among PCa patients, including gene mutations, mRNA/protein/surface protein distributions, and pharmaceutical responses. The multi-omics analyses identify Anterior Gradient 2 (AGR2) as a pre-operative prognostic biomarker in PCa. Through the drug library screening, we describe crizotinib as a selective compound for malignant PCa primary cells. We further perform the pharmacoproteome analysis and identify 14,372 significant protein-drug correlations. Surprisingly, the diminished AGR2 enhances the inhibition activity of crizotinib via ALK/c-MET-AKT axis activation which is validated by PC3 and xenograft model. Our integrated multi-omics approach yields a comprehensive understanding of PCa biomarkers and pharmacological responses, allowing for more precise diagnosis and therapies.

NUSAP1 Binds ILF2 to Modulate R-Loop Accumulation and DNA Damage in Prostate Cancer.

Increased expression of NUSAP1 has been identified as a robust prognostic biomarker in prostate cancer and other malignancies. We have previously shown that NUSAP1 is positively regulated by E2F1 and promotes cancer invasion and metastasis. To further understand the biological function of NUSAP1, we used affinity purification and mass spectrometry proteomic analysis to identify NUSAP1 interactors. We identified 85 unique proteins in the NUSAP1 interactome, including ILF2, DHX9, and other RNA-binding proteins. Using proteomic approaches, we uncovered a function for NUSAP1 in maintaining R-loops and in DNA damage response through its interaction with ILF2. Co-immunoprecipitation and colocalization using confocal microscopy verified the interactions of NUSAP1 with ILF2 and DHX9, and RNA/DNA hybrids. We showed that the microtubule and charged helical domains of NUSAP1 were necessary for the protein-protein interactions. Depletion of ILF2 alone further increased camptothecin-induced R-loop accumulation and DNA damage, and NUSAP1 depletion abolished this effect. In human prostate adenocarcinoma, NUSAP1 and ILF2 mRNA expression levels are positively correlated, elevated, and associated with poor clinical outcomes. Our study identifies a novel role for NUSAP1 in regulating R-loop formation and accumulation in response to DNA damage through its interactions with ILF2 and hence provides a potential therapeutic target.

Comprehensive analysis of the FOXA1-related ceRNA network and identification of the MAGI2-AS3/DUSP2 axis as a prognostic biomarker in prostate cancer.

Prostate cancer (PCa) is the second most common cause of cancer-related deaths in American men. Even though increasing evidence has disclosed the competitive endogenous RNA (ceRNA) regulatory networks among cancers, the complexity and behavior characteristics of the ceRNA network in PCa remain unclear. Our study aimed to investigate the forkhead box A1 (FOXA1)-related ceRNA regulatory network and ascertain potential prognostic markers associated with PCa. RNA sequence profiles downloaded from The Cancer Genome Atlas (TCGA) were analyzed to recognize differentially expressed genes (DEGs) derived from tumor and non-tumor adjacent samples as well as FOXA1low and FOXA1high tumor samples. The enrichment analysis was conducted for the dysregulated mRNAs. The network for the differentially expressed long non-coding RNA (lncRNA)-associated ceRNAs was then established. Survival analysis and univariate Cox regression analysis were executed to determine independent prognostic RNAs associated with PCa. The correlation between DUSP2 and immune cell infiltration level was analyzed. Tissue and blood samples were collected to verify our network. Molecular experiments were performed to explore whether DUSP2 is involved in the development of PCa. A ceRNA network related to FOXA1 was constructed and comprised 18 lncRNAs, 5 miRNAs, and 44 mRNAs. The MAGI2-AS3~has-mir-106a/has-mir-204~DUSP2 ceRNA regulatory network relevant to the prognosis of PCa was obtained by analysis. We markedly distinguished the MAGI2-AS3/DUSP2 axis in the ceRNA. It will most likely become a clinical prognostic model and impact the changes in the tumor immune microenvironment of PCa. The abnormal MAGI2-AS3 expression level from the patients' blood manifested that it would be a novel potential diagnostic biomarker for PCa. Moreover, down-expressed DUSP2 suppressed the proliferation and migration of PCa cells. Our findings provide pivotal clues to understanding the role of the FOXA1-concerned ceRNA network in PCa. Simultaneously, this MAGI2-AS3/DUSP2 axis might be a new significant prognostic factor associated with the diagnosis and prognosis of PCa.