In silico analysis of prognostic and diagnostic significance of target genes from prostate cancer cell lines derived exomicroRNAs

BACKGROUND

Cancer-secreted exovesicles are important for cell-to-cell communication by altering cancer-related signalling pathways. Exovesicles-derived miRNAs (exomiRNAs)-target genes can be useful for diagnostic and prognostic purposes.

METHODS

ExomiRNA from prostate cancer (PCa) cells (PC-3 and LNCaP) were quantified by qRT-PCR and compared to the healthy cell line RWPE-1 by using miRNome PCR 752 miRNAs Panel. MiRNet database was used to predict exomiRNA-target genes. ExomiRNA-target genes pathway functional enrichment was performed by using Reactome database and Enrichr platform. Protein-protein interaction analysis was carried out by using the STRING database. RNA target-gene sequencing data from The Cancer Genome Atlas Prostate Adenocarcinoma (TCGA-PRAD) database was screened out in 465 PCa patients for candidate gene expression in prostate tumour (PT) tissue and non-pathologic prostate (N-PP) tissue. Signature gene candidates were statistically analysed for diagnosis and prognosis usefulness.

RESULTS

A total of 36 exomiRNAs were found downregulated when comparing PCa cells vs a healthy cell line; and when comparing PC-3 vs LNCaP, 14 miRNAs were found downregulated and 52 upregulated. Reactome pathway database revealed altered pathways and genes related to miRNA biosynthesis, miRNA-mediated gene silencing (TNRC6B and AGO1), and cell proliferation (CDK6), among others. Results showed that TNRC6B gene expression was up-regulated in PT tissue compared to N-PP (n = 52 paired samples) and could be useful for diagnostic purposes. Likewise, gene expression levels of CDK6, TNRC6B, and AGO1 were down-regulated in high-risk PT (n = 293) compared to low-risk PCa tissue counterparts (n = 172). When gene expression levels of CDK6, TNRC6B, and AGO1 were tested as a prognostic panel, the results showed that these improve the prognostic power of classical biomarkers.

CONCLUSION

ExomiRNAs-targets genes, TNRC6B, CDK6, and AGO1, showed a deregulated expression profile in PCa tissue and could be useful for PCa diagnosis and prognosis.

A serum metabolic biomarker panel for early rheumatoid arthritis

Objective

There is an urgent need for novel biomarkers to improve the early diagnosis of rheumatoid arthritis (ERA). Current serum biomarkers used in the management of ERA, including rheumatoid factor and anti-cyclic citrullinated peptide (ACPA), show limited specificity and sensitivity. Here, we used metabolomics to uncover new serum biomarkers of ERA.

Methods

We applied an untargeted metabolomics approach including gas chromatography time-of-flight mass spectrometry in serum samples from an ERA cohort (n=32) and healthy controls (n=19). Metabolite set enrichment analysis was performed to explore potentially important biological pathways. Partial least squares discriminant analysis and variable importance in projection analysis were performed to construct an ERA biomarker panel.

Results

Significant differences in the content of 11/81 serum metabolites were identified in patients with ERA. Receiver operating characteristic (ROC) analysis showed that a panel of only three metabolites (glyceric acid, lactic acid, and 3-hydroxisovaleric acid) could correctly classify 96.7% of patients with ERA, with an area under the ROC curve of 0.963 and with 94.4% specificity and 93.5% sensitivity, outperforming ACPA-based diagnosis by 2.9% and, thus, improving the preclinical detection of ERA. Aminoacyl-tRNA biosynthesis and serine, glycine, and phenylalanine metabolism were the most significant dysregulated pathways in patients with ERA.

Conclusion

A metabolomics serum-based biomarker panel composed of glyceric acid, lactic acid, and 3-hydroxisovaleric acid offers potential for the early clinical diagnosis of RA.

The lipidomic profile of the tumoral periprostatic adipose tissue reveals alterations in tumor cell's metabolic crosstalk

BACKGROUND

Periprostatic adipose tissue (PPAT) plays a role in prostate cancer (PCa) progression. PPAT lipidomic composition study may allow us to understand the tumor metabolic microenvironment and provide new stratification factors.

METHODS

We used ultra-high-performance liquid chromatography-mass spectrometry-based non-targeted lipidomics to profile lipids in the PPAT of 40 patients with PCa (n = 20 with low-risk and n = 20 high-risk). Partial least squares-discriminant analysis (PLS-DA) and variable importance in projection (VIP) analysis were used to identify the most relevant features of PPAT between low- and high-risk PCa, and metabolite set enrichment analysis was used to detect disrupted metabolic pathways. Metabolic crosstalk between PPAT and PCa cell lines (PC-3 and LNCaP) was studied using ex vivo experiments. Lipid uptake and lipid accumulation were measured. Lipid metabolic-related genes (SREBP1, FASN, ACACA, LIPE, PPARG, CD36, PNPLA2, FABP4, CPT1A, FATP5, ADIPOQ), inflammatory markers (IL-6, IL-1B, TNFα), and tumor-related markers (ESRRA, MMP-9, TWIST1) were measured by RT-qPCR.

RESULTS

Significant differences in the content of 67 lipid species were identified in PPAT samples between high- and low-risk PCa. PLS-DA and VIP analyses revealed a discriminating lipidomic panel between low- and high-risk PCa, suggesting the occurrence of disordered lipid metabolism in patients related to PCa aggressiveness. Functional analysis revealed that alterations in fatty acid biosynthesis, linoleic acid metabolism, and β-oxidation of very long-chain fatty acids had the greatest impact in the PPAT lipidome. Gene analyses of PPAT samples demonstrated that the expression of genes associated with de novo fatty acid synthesis such as FASN and ACACA were significantly lower in PPAT from high-risk PCa than in low-risk counterparts. This was accompanied by the overexpression of inflammatory markers (IL-6, IL-1B, and TNFα). Co-culture of PPAT explants with PCa cell lines revealed a reduced gene expression of lipid metabolic-related genes (CD36, FASN, PPARG, and CPT1A), contrary to that observed in co-cultured PCa cell lines. This was followed by an increase in lipid uptake and lipid accumulation in PCa cells. Tumor-related genes were increased in co-cultured PCa cell lines.

CONCLUSIONS

Disturbances in PPAT lipid metabolism of patients with high-risk PCa are associated with tumor cell metabolic changes.

A Serum Biomarker Panel of exomiR-451a, exomiR-25-3p and Soluble TWEAK for Early Diagnosis of Rheumatoid Arthritis

Background

The etiology of rheumatoid arthritis (RA) remains poorly understood. Early and accurate diagnosis still difficult to achieve. Inflammatory related molecules released into the circulation such cytokines and exosome-derived microRNAs (exomiRNAs) could be good candidates for early diagnosis of autoimmune diseases. We sought to discover a serum biomarker panel for the early detection of RA based on exomiRNAs and inflammatory markers.

Methods

A 179 miRNAs-microarray panel was analyzed in a pilot study (4 early RA and 4 controls). Validation of deregulated exomiRNAs was performed in a larger cohort (24 patients with early RA and 24 controls). miRNet software was used to predict exomiRNA gene-targets interactions. Potentially altered pathways were analyzed by Reactome pathway database search. STRING database was used to predict protein-protein interaction networks. Enzyme-linked immunosorbent assay was used to measure serum levels of sTWEAK and sCD163. Signature biomarker candidates were statistical analyzed.

Results

We detected 11 differentially expressed exomiRNAs in early RA pilot study. Validation analysis revealed that 6/11 exomiRNAs showed strong agreement with the pilot microarray data (exomiR-144-3p, -25-3p, -15a-5p, -451a, -107 and -185-5p). sTWEAK and sCD163 biomarkers were significantly elevated in the serum of patients with early RA. Receiver operating characteristic (ROC) analysis showed that the best panel to diagnose early RA contained exomiR-451a, exomiR-25-3p and sTWEAK, and could correctly classify 95.6% of patients, with an area under the ROC curve of 0.983 and with 100% specificity and 85.7% sensitivity. The YWHAB gene was identified as a common target of the putative miRNA-regulated pathways.

Conclusion

A novel serum biomarker panel composed of exomiR-451a, exomiR-25-3p and serum levels of sTWEAK may have use in the early clinical diagnosis of RA. A new predicted exomiRNA-target gene YHWAB has been identified and may have a relevant role in the development of RA.

Serum Levels of the Cytokine TWEAK Are Associated with Metabolic Status in Patients with Prostate Cancer and Modulate Cancer Cell Lipid Metabolism In Vitro

Simple Summary

TWEAK is an inflammatory cytokine related to prostate cancer (PCa) progression that exerts its effects by engaging its cognate receptor Fn14. A soluble form of TWEAK (sTWEAK) has been detected in the PCa microenvironment. Altered levels of circulating sTWEAK are associated with aberrant glucose metabolism. We show that reduced serum levels of sTWEAK are associated with the metabolic status in patients with PCa and that the treatment of PC-3 cells with sTWEAK enhances the expression of genes related to lipid, but not to glucose, metabolism. sTWEAK also increases the lipid uptake and lipid accumulation in PC-3 cells. We corroborated that the observed effects were due to TWEAK/Fn14 engagement by silencing Fn14 expression, which attenuated the aberrant gene and protein expression. Additionally, we observed that the phosphorylation of ERK1/2 and AKT (ser473) were required for TWEAK/Fn14 actions. Thus, the contribution of the sTWEAK/Fn14 axis on PCa metabolism supports its potential as a therapeutic target for PCa.

Abstract

Soluble TWEAK (sTWEAK) has been proposed as a prognostic biomarker of prostate cancer (PCa). We found that reduced serum levels of sTWEAK, together with higher levels of prostate-specific antigen and a higher HOMA-IR index, are independent predictors of PCa. We also showed that sTWEAK stimulus failed to alter the expression of glucose transporter genes (SLC2A4 and SLC2A1), but significantly reduced the expression of glucose metabolism-related genes (PFK, HK1 and PDK4) in PCa cells. The sTWEAK stimulation of PC-3 cells significantly increased the expression of the genes related to lipogenesis (ACACA and FASN), lipolysis (CPT1A and PNPLA2), lipid transport (FABP4 and CD36) and lipid regulation (SREBP-1 and PPARG) and increased the lipid uptake. Silencing the TWEAK receptor (Fn14) in PC-3 cells confirmed the observed lipid metabolic effects, as shown by the downregulation of ACACA, FASN, CPT1A, PNPLA2, FABP4, CD36, SREBP-1 and PPARG expression, which was paralleled by a reduction of FASN, CPT1A and FABP4 protein expression. Specific-signaling inhibitor assays show that ERK1/2 and AKT (ser473) phosphorylation can regulate lipid metabolism-related genes in PCa cells, pointing to the AKT locus as a possible target for PCa. Overall, our data support sTWEAK/Fn14 axis as a potential therapeutic target for PCa.

Liquid Biopsy-Based Exo-oncomiRNAs Can Predict Prostate Cancer Aggressiveness

Liquid biopsy-based biomarkers, including microRNAs packaged within extracellular vesicles, are promising tools for patient management. The cytokine tumor necrosis factor-like weak inducer of apoptosis (TWEAK) is related to PCa progression and is found in the semen of patients with PCa. TWEAK can induce the transfer of exo-oncomiRNAs from tumor cells to body fluids, and this process might have utility in non-invasive PCa prognosis. We investigated TWEAK-regulated exo-microRNAs in semen and in post-digital rectal examination urine from patients with different degrees of PCa aggressiveness. We first identified 14 exo-oncomiRNAs regulated by TWEAK in PCa cells in vitro, and subsequently validated those using liquid biopsies from 97 patients with PCa. Exo-oncomiR-221-3p, -222-3p and -31-5p were significantly higher in the semen of high-risk patients than in low-risk peers, whereas exo-oncomiR-193-3p and -423-5p were significantly lower in paired samples of post-digital rectal examination urine. A panel of semen biomarkers comprising exo-oncomiR-221-3p, -222-3p and TWEAK was designed that could correctly classify 87.5% of patients with aggressive PCa, with 85.7% specificity and 76.9% sensitivity with an area under the curve of 0.857. We additionally found that TWEAK modulated two exo-oncomiR-221-3p targets, TCF12 and NLK. Overall, we show that liquid biopsy detection of TWEAK-regulated exo-oncomiRNAs can improve PCa prognosis prediction.

Biofluid quantification of TWEAK/Fn14 axis in combination with a selected biomarker panel improves assessment of prostate cancer aggressiveness

Background

Conventional clinical biomarkers cannot accurately differentiate indolent from aggressive prostate cancer (PCa). We investigated the usefulness of a biomarker panel measured exclusively in biofluids for assessment of PCa aggressiveness.

Methods

We collected biofluid samples (plasma/serum/semen/post-prostatic massage urine) from 98 patients that had undergone radical prostatectomy. Clinical biochemistry was performed and several cytokines/chemokines including soluble(s) TWEAK, sFn14, sCD163, sCXCL5 and sCCL7 were quantified by ELISA in selected biofluids. Also, the expression of KLK2, KLK3, Fn14, CD163, CXCR2 and CCR3 was quantified by real-time PCR in semen cell sediment. Univariate, logistic regression, and receiver operating characteristic (ROC) analyses were used to assess the predictive ability of the selected biomarker panel in conjunction with clinical and metabolic variables for the evaluation of PCa aggressiveness.

Results

Total serum levels of prostate-specific antigen (PSA), semen levels of sTWEAK, fasting glycemia and mRNA levels of Fn14, KLK2, CXCR2 and CCR3 in semen cell sediment constituted a panel of markers that was significantly different between patients with less aggressive tumors [International Society of Urological Pathology (ISUP) grade I and II] and those with more aggressive tumors (ISUP grade III, IV and V). ROC curve analysis showed that this panel could be used to correctly classify tumor aggressiveness in 90.9% of patients. Area under the curve (AUC) analysis revealed that this combination was more accurate [AUC = 0.913 95% confidence interval (CI) 0.782–1] than a classical non-invasive selected clinical panel comprising age, tumor clinical stage (T-classification) and total serum PSA (AUC = 0.721 95% CI 0.613–0.830).

Conclusions

TWEAK/Fn14 axis in combination with a selected non-invasive biomarker panel, including conventional clinical biochemistry, can improve the predictive power of serum PSA levels and could be used to classify PCa aggressiveness.

Altered Expression of miR-181a-5p and miR-23a-3p Is Associated With Obesity and TNFα-Induced Insulin Resistance

CONTEXT

The proinflammatory cytokine TNFα is a key player in insulin resistance (IR). The role of miRNAs in inflammation associated with IR is poorly understood.

OBJECTIVE

To investigate miR-181a-5p and miR-23a-3p expression profiles in obesity and to study their role in TNFα-induced IR in adipocytes.

DESIGN

Two separate cohorts were used. Cohort 1 was used in adipose tissue (AT) expression studies and included 28 subjects with body mass index (BMI) <30 kg/m2 and 30 with BMI ≥30 kg/m2. Cohort 2 was used in circulating serum miRNA studies and included 101 subjects with 4 years of follow-up (48 case subjects and 53 control subjects). miR-181a-5p and miR-23a-3p expression was assessed in subcutaneous and visceral AT. Functional analysis was performed in adipocytes, using miRNA mimics and inhibitors. Key molecules of the insulin pathway, AKT, PTEN, AS160, and S6K, were analyzed.

RESULTS

Expression of miR-181a-5p and miR-23a-3p was reduced in adipose tissue from obese and diabetic subjects and was inversely correlated to adiposity and homeostasis model assessment of IR index. Overexpression of miR-181a-5p and miR-23a-3p in adipocytes upregulated insulin-stimulated AKT activation and reduced TNFα-induced IR, regulating PTEN and S6K expression. Serum levels of miR-181a-5p were reduced in case vs control subjects at baseline, suggesting a prognostic value. Variable importance in projection scores revealed miR-181a-5p had more effect on the model than insulin or glucose at 120 minutes.

CONCLUSION

miR-181a-5p and miR-23a-3p may prevent TNFα-induced IR in adipocytes through modulation of PTEN and S6K expression.