RESUMO

Prostate cancer is a highly heterogeneous disease; therefore, estimating patient prognosis accurately is challenging due to the lack of biomarkers with sufficient specificity and sensitivity. One of the current challenges lies in integrating genomic and transcriptomic data with clinico-pathological features and in incorporating their application in everyday clinical practice. Therefore, we aimed to model a risk score and nomogram containing long non-coding RNA (lncRNA) expression and clinico-pathological data to better predict the probability of prostate cancer progression. We performed bioinformatics analyses to identify lncRNAs differentially expressed across various prostate cancer stages and associated with progression-free survival. This information was further integrated into a prognostic risk score and nomogram containing transcriptomic and clinico-pathological features to estimate the risk of disease progression. We used RNA-seq data from 5 datasets from public repositories (total n = 178) comprising different stages of prostate cancer: pre-treatment primary prostate adenocarcinomas, post-treatment tumors and metastatic castration resistant prostate cancer. We found 30 lncRNAs with consistent differential expression in all comparisons made using two R-based packages. Multivariate progression-free survival analysis including the ISUP group as covariate, revealed that 7/30 lncRNAs were significantly associated with time-to-progression. Next, we combined the expression of these 7 lncRNAs into a multi-lncRNA score and dichotomized the patients into low- or high-score. Patients with a high-score showed a 4-fold risk of disease progression (HR = 4.30, 95 %CI = 2.66-6.97, p = 3.1e-9). Furthermore, we modelled a combined risk-score containing information on the multi-lncRNA score and ISUP group. We found that patients with a high-risk score had nearly 8-fold risk of progression (HR = 7.65, 95 %CI = 4.05-14.44, p = 3.4e-10). Finally, we created and validated a nomogram to help uro-oncologists to better predict patient's risk of progression at 3- and 5-years post-diagnosis. In conclusion, the integration of lncRNA expression data and clinico-pathological features of prostate tumors into predictive models might aid in tailored disease risk assessment and treatment for patients with prostate cancer.

RESUMO

Interferon gamma (IFN-γ) may be potential adjuvant immunotherapy for COVID-19 patients. In this work, we assessed gene expression profiles associated with the IFN-γ pathway in response to SARS-CoV-2 infection. Employing a case-control study from SARS-CoV-2-positive and -negative patients, we identified IFN-γ-associated pathways to be enriched in positive patients. Bioinformatics analyses showed upregulation of MAP2K6, CBL, RUNX3, STAT1, and JAK2 in COVID-19-positive vs. -negative patients. A positive correlation was observed between STAT1/JAK2, which varied alongside the patient's viral load. Expression of MX1, MX2, ISG15, and OAS1 (four well-known IFN-stimulated genes (ISGs)) displayed upregulation in COVID-19-positive vs. -negative patients. Integrative analyses showcased higher levels of ISGs, which were associated with increased viral load and STAT1/JAK2 expression. Confirmation of ISGs up-regulation was performed in vitro using the A549 lung cell line treated with Poly (I:C), a synthetic analog of viral double-stranded RNA; and in different pulmonary human cell lines and ferret tracheal biopsies infected with SARS-CoV-2. A pre-clinical murine model of Coronavirus infection confirmed findings displaying increased ISGs in the liver and lungs from infected mice. Altogether, these results demonstrate the role of IFN-γ and ISGs in response to SARS-CoV-2 infection, highlighting alternative druggable targets that can boost the host response.

Assuntos

RESUMO

Metastatic prostate cancer (PCa) cells soiling in the bone require a metabolic adaptation. Here, we identified the metabolic genes fueling the seeding of PCa in the bone niche. Using a transwell co-culture system of PCa (PC3) and bone progenitor cells (MC3T3 or Raw264.7), we assessed the transcriptome of PC3 cells modulated by soluble factors released from bone precursors. In a Principal Component Analysis using transcriptomic data from human PCa samples (GSE74685), the altered metabolic genes found in vitro were able to stratify PCa patients in two defined groups: primary PCa and bone metastasis, confirmed by an unsupervised clustering analysis. Thus, the early transcriptional metabolic profile triggered in the in vitro model has a clinical correlate in human bone metastatic samples. Further, the expression levels of five metabolic genes (VDR, PPARA, SLC16A1, GPX1 and PAPSS2) were independent risk-predictors of death in the SU2C-PCF dataset and a risk score model built using this lipid-associated signature was able to discriminate a subgroup of bone metastatic PCa patients with a 23-fold higher risk of death. This signature was validated in a PDX pre-clinical model when comparing MDA-PCa-183 growing intrafemorally vs. subcutaneously, and appears to be under the regulatory control of the Protein Kinase A (PKA) signaling pathway. Secretome analyses of conditioned media showcased fibronectin and type-1 collagen as critical bone-secreted factors that could regulate tumoral PKA. Overall, we identified a novel lipid gene signature, driving PCa aggressive metastatic disease pointing to PKA as a potential hub to halt progression.

RESUMO

Prostate cancer (PCa) cells display abnormal expression of proteins resulting in an augmented capacity to resist chemotherapy and colonize distant organs. We have previously shown the anti-tumoral role of heme oxygenase 1 (HO-1) in this disease. In this work, we undertook a mass spectrometry-based proteomics study to identify HO-1 molecular interactors that might collaborate with its modulatory function in PCa. Among the HO-1 interactors, we identified proteins with nuclear localization. Correlation analyses, using the PCa GSE70770 dataset, showed a significant and positive correlation between HMOX1 and 6 of those genes. Alternatively, HMOX1 and YWHAZ showed a negative correlation. Univariable analyses evidenced that high expression of HNRNPA2B1, HSPB1, NPM1, DDB1, HMGA1, ZC3HAV1, and HMOX1 was associated with increased relapse-free survival (RFS) in PCa patients. Further, PCa patients with high HSPB1/HMOX1, DDB1/HMOX1, and YWHAZ/HMOX1 showed a worse RFS compared with patients with lower ratios. Moreover, a decrease in RFS for patients with higher scores of this signature was observed using a prognostic risk score model. However, the only factor significantly associated with a higher risk of relapse was high YWHAZ. Multivariable analyses confirmed HSPB1, DDB1, and YWHAZ independence from PCa clinic-pathological parameters. In parallel, co-immunoprecipitation analysis in PCa cells ascertained HO-1/14-3-3ζ/δ (protein encoded by YWHAZ) interaction. Herein, we describe a novel protein interaction between HO-1 and 14-3-3ζ/δ in PCa and highlight these factors as potential therapeutic targets.

RESUMO

Prostate cancer (PCa) is the second most diagnosed malignancy and the fifth leading cause of cancer associated death in men worldwide. Dysregulation of cellular energetics has become a hallmark of cancer, evidenced by numerous connections between signaling pathways that include oncoproteins and key metabolic enzymes. We previously showed that heme oxygenase 1 (HO-1), a cellular homeostatic regulator counteracting oxidative and inflammatory damage, exhibits anti-tumoral activity in PCa cells, inhibiting cell proliferation, migration, tumor growth and angiogenesis. The aim of this study was to assess the role of HO-1 on the metabolic signature of PCa. After HO-1 pharmacological induction with hemin, PC3 and C4-2B cells exhibited a significantly impaired cellular metabolic rate, reflected by glucose uptake, ATP production, lactate dehydrogenase (LDH) activity and extracellular lactate levels. Further, we undertook a bioinformatics approach to assess the clinical significance of LDHA, LDHB and HMOX1 in PCa, identifying that high LDHA or low LDHB expression was associated with reduced relapse free survival (RFS). Interestingly, the shortest RFS was observed for PCa patients with low HMOX1 and high LDHA, while an improved prognosis was observed for those with high HMOX1 and LDHB. Thus, HO-1 induction causes a shift in the cellular metabolic profile of PCa, leading to a less aggressive phenotype of the disease.

RESUMO

Differential gene expression analysis is widely used to study changes in gene expression profiles between two or more groups of samples (e.g., physiological versus pathological conditions, pre-treatment versus post-treatment, and infected versus non-infected tissues). This protocol aims to identify gene expression changes in a pre-selected set of genes associated with severe acute respiratory syndrome coronavirus 2 viral infection and host cell antiviral response, as well as subsequent gene expression association with phenotypic features using samples deposited in public repositories. For complete details on the use and outcome of this informatics analysis, please refer to Bizzotto et al. (2020).

Assuntos

RESUMO

Some prostate cancers (PCas) are histo-pathologically grouped within the same Gleason Grade (GG), but can differ significantly in outcome. Herein, we aimed at identifying molecular biomarkers that could improve risk prediction in PCa. LC ESI-MS/MS was performed on human PCa and benign prostatic hyperplasia (BPH) tissues and peptide data was integrated with omic analyses. We identified high YWHAZ and NDRG1 expression to be associated with poor PCa prognosis considering all Gleason scores (GS). YWHAZ and NDRG1 defined two subpopulations of PCa patients with high and intermediate risk of death. Multivariable analyses confirmed their independence from GS. ROC analysis unveiled that YWHAZ outperformed GS beyond 60 months post-diagnosis. The genomic analysis of PCa patients with YWHAZ amplification, or increased mRNA or protein levels, revealed significant alterations in key DNA repair genes. We hereby state the relevance of YWHAZ in PCa, showcasing its role as an independent strong predictor of aggressiveness.

Assuntos

RESUMO

In a published case-control study (GSE152075) from SARS-CoV-2-positive (n = 403) and -negative patients (n = 50), we analyzed the response to infection assessing gene expression of host cell receptors and antiviral proteins. The expression analysis associated with reported risk factors for COVID-19 was also assessed. SARS-CoV-2 cases had higher ACE2, but lower TMPRSS2, BSG/CD147, and CTSB expression compared with negative cases. COVID-19 patients' age negatively affected ACE2 expression. MX1 and MX2 were higher in COVID-19 patients. A negative trend for MX1 and MX2 was observed as patients' age increased. Principal-component analysis determined that ACE2, MX1, MX2, and BSG/CD147 expression was able to cluster non-COVID-19 and COVID-19 individuals. Multivariable regression showed that MX1 expression significantly increased for each unit of viral load increment. Altogether, these findings support differences in ACE2, MX1, MX2, and BSG/CD147 expression between COVID-19 and non-COVID-19 patients and point out to MX1 as a critical responder in SARS-CoV-2 infection.

RESUMO

The inflammatory tumor microenvironment is a fertile niche accelerating prostate cancer (PCa). We have reported that heme-oxygenase (HO-1) had a strong anti-tumoral effect in PCa. We previously undertook an in-depth proteomics study to build the HO-1 interactome in PCa. In this work, we used a bioinformatics approach to address the biological significance of HO-1 interactors. Open-access PCa datasets were mined to address the clinical significance of the HO-1 interactome in human samples. HO-1 interactors were clustered into groups according to their expression profile in PCa patients. We focused on the myxovirus resistance gene (MX1) as: (1) it was significantly upregulated under HO-1 induction; (2) it was the most consistently downregulated gene in PCa vs. normal prostate; (3) its loss was associated with decreased relapse-free survival in PCa; and (4) there was a significant positive correlation between MX1 and HMOX1 in PCa patients. Further, MX1 was upregulated in response to endoplasmic reticulum stress (ERS), and this stress triggered apoptosis and autophagy in PCa cells. Strikingly, MX1 silencing reversed ERS. Altogether, we showcase MX1 as a novel HO-1 interactor and downstream target, associated with ERS in PCa and having a high impact in the clinical setting.

Assuntos

RESUMO

BACKGROUND: Prostate cancer (PCa) dissemination shows a tendency to develop in the bone, where heme oxygenase 1 (HO-1) plays a critical role in bone remodeling. Previously by LC/ESI-MSMS, we screened for HO-1 interacting proteins and identified annexin 2 (ANXA2). The aim of this study was to analyze the relevance of ANXA2/HO-1 in PCa and bone metastasis. METHODS: We assessed ANXA2 levels using a co-culture transwell system of PC3 cells (pre-treated or not with hemin, an HO-1 specific inducer) and the pre-osteoclastic Raw264.7 cell line. RESULTS: Under co-culture conditions, ANXA2 mRNA levels were significantly modulated in both cell lines. Immunofluorescence analysis unveiled a clear ANXA2 reduction in cell membrane immunostaining for Raw264.7 under the same conditions. This effect was supported by the detection of a decrease in Ca2+ concentration in the conditioned medium. HO-1 induction in tumor cells prevented both, the ANXA2 intracellular relocation and the decrease in Ca2+ concentration. Further, secretome analysis revealed urokinase (uPA) as a key player in the communication between osteoclast progenitors and PC3 cells. To assess the clinical significance of ANXA2/HO-1, we performed a bioinformatics analysis and identified that low expression of each gene strongly associated with poor prognosis in PCa regardless of the clinico-pathological parameters assessed. Further, these genes appear to behave in a dependent manner. CONCLUSIONS: ANXA2/HO-1 rises as a critical axis in PCa.

Assuntos