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No curative therapy is currently available for metastatic prostate cancer (PCa). The diverse mechanisms of progression include fibroblast growth factor (FGF) axis activation.To investigate the molecular and clinical implications of fibroblast growth factor receptor 1 (FGFR1) and its isoforms (α/β) in the pathogenesis of PCa bone metastases.In silico, in vitro, and in vivo preclinical approaches were used. RNA-sequencing and immunohistochemical (IHC) studies in human samples were conducted.In mice, bone metastases (chi-square/Fisher's test) and survival (Mantel-Cox) were assessed. In human samples, FGFR1 and ladinin 1 (LAD1) analysis associated with PCa progression were evaluated (IHC studies, Fisher's test).FGFR1 isoform expression varied among PCa subtypes. Intracardiac injection of mice with FGFR1-expressing PC3 cells reduced mouse survival (α, p 0.0001; β, p = 0.032) and increased the incidence of bone metastases (α, p 0.0001; β, p = 0.02). Accordingly, IHC studies of human castration-resistant PCa (CRPC) bone metastases revealed significant enrichment of FGFR1 expression compared with treatment-naïve, nonmetastatic primary tumors (p = 0.0007). Expression of anchoring filament protein LAD1 increased in FGFR1-expressing PC3 cells and was enriched in human CRPC bone metastases (p = 0.005).FGFR1 expression induces bone metastases experimentally and is significantly enriched in human CRPC bone metastases, supporting its prometastatic effect in PCa. LAD1 expression, found in the prometastatic PCa cells expressing FGFR1, was also enriched in CRPC bone metastases. Our studies support and provide a roadmap for the development of FGFR blockade for advanced PCa.We studied the role of fibroblast growth factor receptor 1 (FGFR1) in prostate cancer (PCa) progression. We found that PCa cells with high FGFR1 expression increase metastases and that FGFR1 expression is increased in human PCa bone metastases, and identified genes that could participate in the metastases induced by FGFR1. These studies will help pinpoint PCa patients who use fibroblast growth factor to progress and will benefit by the inhibition of this pathway.

Prostate cancer (PCa) that progresses after androgen deprivation therapy (ADT) remains incurable. The underlying mechanisms that account for the ultimate emergence of resistance to ADT, progressing to castrate-resistant prostate cancer (CRPC), include those that reactivate androgen receptor (AR), or those that are entirely independent or cooperate with androgen signaling to underlie PCa progression. The intricacy of metabolic pathways associated with PCa progression spurred us to develop a metabolism-centric analysis to assess the metabolic shift occurring in PCa that progresses with low AR expression. We used PCa patient-derived xenografts (PDXs) to assess the metabolic changes after castration of tumor-bearing mice and subsequently confirmed main findings in human donor tumor that progressed after ADT. We found that relapsed tumors had a significant increase in fatty acids and ketone body (KB) content compared with baseline. We confirmed that critical ketolytic enzymes (ACAT1, OXCT1, BDH1) were dysregulated after castrate-resistant progression. Further, these enzymes are increased in the human donor tissue after progressing to ADT. In an in silico approach, increased ACAT1, OXCT1, BDH1 expression was also observed for a subset of PCa patients that relapsed with low AR and ERG (ETS-related gene) expression. Further, expression of these factors was also associated with decreased time to biochemical relapse and decreased progression-free survival. Our studies reveal the key metabolites fueling castration resistant progression in the context of a partial or complete loss of AR dependence.

Bone hosts the 88% of Prostate Cancer (PCa) metastases and no curative therapy is currently available for this stage. Arrival of PCa cells to the bone homing organ is accompanied by a metabolic adaptation, which may be mediated by bone secreted factors. Herein, we sought to identify key metabolic genes fueling PCa bone metastasis and soluble factors secreted by bone cells leading to the metabolic rewiring of tumoral cells. By an indirect transwell co-culture system of PCa (PC3) and bone progenitor cells (MC3T3, pre-osteoblasts; or Raw264.7, pre-osteoclasts) we analyzed the transcriptome (RNA-seq) of PC3 cells modulated by soluble factors released from bone precursors. GSEA showed a strong activation of lipid metabolism, including PPAR and PI3K-Akt pathways, fat absorption and digestion. We then performed a Principal Component Analysis using transcriptomic data from human PCa and bone metastasis samples (GSE74685), showcasing that those metabolic genes that appeared significantly dysregulated in the co-culture model could accurately cluster samples by their tissue of origin in two defined groups: primary PCa and bone metastasis. This result was confirmed by an unsupervised clustering analysis, highlighting that the transcriptional metabolic profile triggered in the in vitro model has a clinical correlate in human bone metastasis samples. Interestingly, when performing a survival analysis for those genes in the SU2C-PCF dataset, we observed that 4 lipid-associated genes, PPARA, VDR, SLC16A1 and GPX1, correlated with a shorter overall survival time, and appeared as independent risk-predictors of death (HR: 4.96, 2.85, 3.93 and 3.67, respectively; P Citation Format: Pablo Sanchis, Nicolas Anselmino, Rosario Lavignolle, Agustina Sabater, Estefania Labanca, Juan Bizzotto, Sofia Lage-Vickers, Gaston Pascual, Rocio Seniuk, Ayelen Toro, Nora Navone, Javier Cotignla, Elba Vazquez, Geraldine Gueron. Early metabolic rewiring of prostate cancer cells triggered by bone progenitors defines survival of metastatic prostate cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2374.

PURPOSE Prostate cancer (PCa) is the second most common type of cancer in men and the sixth leading cause of cancer-related death in men worldwide. The discovery of new therapeutic avenues in PCa, and the development of effective drugs in the era of personalized medicine, would greatly benefit from the field of proteomics. We have previously shown the anti-tumoral role of Heme oxygenase 1 (HO-1) in PCa. METHODS In this work, we undertook a mass spectrometry-based proteomics study to assess whether in PCa cells and under oxidative stress conditions, HO-1 could interact with proteins previously documented to have nuclear localization. RESULTS Among the HO-1 interactors, we identified 11 proteins with nuclear localization. Significant and positive correlation between HMOX1 and six of those genes was observed, using the GSE70770 dataset. Alternatively, HMOX1 and YWHAZ showed negative correlation. High expression of HNRNPA2B1, HSPB1, NPM1, DDB1, HMGA1, ZC3HAV1, and HMOX1 was associated with an increased relapse-free survival (RFS) in PCa patients through univariable analyses. Further, PCa patients with high HSPB1/HMOX1, DDB1/HMOX1, and YWHAZ/HMOX1 showed a worse RFS compared with patients with lower ratios. Moreover, by using a prognostic risk score model, a decrease in RFS for patients with higher scores of this signature was observed. However, the only factor significantly associated with a higher risk of relapse was high YWHAZ. HSPB1, DDB1 and YWHAZ independence from PCa clinic-pathological parameters was confirmed through multivariable analyses. Moreover, co-immunoprecipitation analysis in PCa cells ascertained HO-1/14-3-3ζ/δ (YWHAZ encoding gene) interaction. CONCLUSION Herein, we report novel interactions between HO-1 and HSPB1, DDB1 and 14-3-3ζ/δ, highlighting their clinical relevance in PCa.

PURPOSE Prostate cancer stem cells enhance the tumor's capacity to proliferate, metastasize, and to resist therapies. Thus, stemness represents a therapeutic challenge in prostate cancer (PCa). We have previously reported a strong anti-tumoral effect of heme oxygenase 1 (HO-1) in prostate carcinogenesis in vivo and in vitro. However, its association with metastasis-stemness is still poorly elucidated. Thus, we aimed at describing the effects of HO-1 overexpression on metastasis/stemness processes in PCa, by also identifying key HO-1-modulated genes. METHODS We performed clonogenic assays to evaluate the effect of HO-1 pharmacological induction on the stem properties of PC3-cells. We carried out an RNA-seq analysis to assess the transcriptional differences of 144 metastasis/stemness/STAT3-signature genes after HO-1 induction. The clinical significance of HO-1-modulated genes was assessed by comprehensive bioinformatics analyses using public data repositories with gene expression and survival data of PCa patients (Oncomine, n = 1,128; TCGA-PRAD, n = 565). RNA-seq results were validated by RT-qPCR. RESULTS Clonogenic assays results showed a significant reduction in colony formation efficiency after HO-1 pharmacological induction with hemin ( P ≤ .01). Transcriptomics profiling by RNA-seq evidenced a significant modulation of 32 key markers related to metastasis/stemness/STAT3-signature under HO-1 induction. Further, 15 HO-1-modulated genes were differentially expressed in PCa vs. normal prostate gland (Oncomine) and HO-1 induction reverted the expression profile observed for these genes. We next used the TCGA-PRAD dataset which revealed that ADAM15, BCL2L1, LTBR, MBNL2 and SPINT1 had the same expression profile as in Oncomine. Additionally, PCa patients with high MBNL2 expression showed a longer disease progression-free survival, which is interesting as it is upregulated in PC3-cells overexpressing HO-1, as validated by RT-qPCR. CONCLUSION Here, we propose a potential mechanism by which HO-1 could inhibit metastasis/stemness by modulating relevant genes in PCa progression. This study may cast a new light on PCa treatment, highlighting HO-1 modulation of cell plasticity, supporting it as a potential therapeutic target for the disease.

PURPOSE The arrival of metastatic prostate cancer (PCa) tumor cells to the bone niche requires a metabolic adaptation. We sought to identify metabolic dysregulations fueling PCa metastasis, modulated by bone secreted factors. METHODS By an indirect co-culture system of PCa (PC3) and bone progenitors (MC3T3, pre-osteoblasts, or Raw 264.7, pre-osteoclasts) we assessed the transcriptome of PC3 cells modulated by soluble factors released from bone precursors. We validated the transcriptional profile of metabolic genes in open-access transcriptomic datasets. We performed an Ingenuity Pathway Analysis (IPA) to delineate the regulators of these metabolic genes. Bone secretome was profiled on the conditioned media (CM) by ESI-MS/MS. RESULTS PC3 cells co-cultured with bone progenitors displayed an activation of lipidic categories, including PPAR-signaling and fat absorption/digestion. Principal Component and Unsupervised Clustering analyses using transcriptomic data from human PCa and bone metastatic samples (GSE74685) showed that the metabolic genes deregulated in PC3 accurately clustered samples in primary tumor or bone metastasis. Moreover, four lipid-associated genes, PPARA, VDR, SLC16A1 and GPX1, were associated with a shorter survival time (SU2C-PCF dataset), and were independent risk-predictors of death ( P < .05). An IPA revealed that these genes are regulated by the Protein Kinase A (PKA). Accordingly, PC3 cells treated with the CM of the co-culture presented a decreased ATP content compared to the treatment with the CM of PC3 grown alone, which was restored upon PKA inhibition. Finally, the secretome analysis revealed soluble factors secreted by bone progenitors (Col1a1, Fn1) which could regulate PKA activity. CONCLUSION We identified a novel lipid-associated gene signature important for metastatic PCa, triggered by the dialogue with bone cells. Moreover, PKA could regulate this signature in response to bone-secreted factors reprogramming the metabolic phenotype of metastatic cells, emerging as a potential druggable target for this disease.

PURPOSE Prostate cancer (PCa) is a progressive disease involving multiple molecular alterations. The Gleason Grade (GG) is used as an aid for physicians to evaluate the prognosis of men with PCa using samples from prostate tissues. However, some PCa that are histo-pathologically grouped in the same GGs can differ significantly in outcome. The aim of this study was to identify molecular biomarkers that could behave independently from GG and other clinical-pathological variables (age, GG and TMPRSS2-ERG fusion status) that can improve risk prediction of PCa. METHODS An in-depth proteomics analysis (LC/ESI-MS/MS) was performed on human prostate adenocarcinoma and benign prostate hyperplasia (BPH) tissues. Protein candidates enriched in PCa vs BPH were further evaluated in-silico using a custom-made pipeline. For this purpose, seven publicly available transcriptomic PCa datasets (ntotal = 875) were selected, and differential expression analyses were performed in R. A Shiny-based tool was then built to execute the search and to allow visualization across multiple datasets. Further multivariable analyses were performed using clinical-pathological parameters as covariates. RESULTS Proteomics analysis yielded a list of 89 proteins enriched in PCa compared with BPH. 58 showed high expression in PCa datasets and nine of those, showed significant association with higher risk of death. Further, when performing a multivariable Cox proportional-hazard model including age, GG and TMPRSS2-ERG fusion status, PPP1R12B, FBLN5, CRIP2, and POSTN displayed associations with poor prognosis, independently from the other co-variates (HR = 1.5, P = .0084; HR = 1.34, P = .035; HR = 1.36, P = .016 and HR = 1.4, P = .0028, respectively). CONCLUSION PPP1R12B, FBLN5, CRIP2, and POSTN proteins were enriched in PCa human tissues. Our custom pipeline revealed increased expression of these genes across multiple PCa datasets and significant association with increased risk of death, independent from known risk factors and predictors of PCa prognosis. Thus, these factors rise as potential prognostic markers.

Prostate cancer (PCa) that progresses after androgen deprivation therapy (ADT) remains incurable. The intricacy of metabolic pathways associated with PCa progression spurred us to develop a metabolism-centric analysis. Using PCa patient-derived xenografts (PDXs) we assessed the metabolic changes after castration of tumor-bearing mice. We found that relapsed tumors had a significant increase in fatty acids and ketone body content compared with baseline. We confirmed that critical ketogenic/ketolytic enzymes (ACAT1, OXCT1, BDH1) were significantly augmented after castrate-resistant progression. Further, these enzymes are increased in the human donor tissue after progressing to ADT.Increased ACAT1 and OXCT1 was also observed for a subset of PCa patients that relapsed with low AR and ERG expression. These factors were associated with decreased biochemical relapse and progression free survival. In summary, our studies reveal the key metabolites fueling castration resistant progression in the context of a partial or complete loss of AR dependence.

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.

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. Fil: Anselmino, Nicolás. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales; Argentina Fil: Bizzotto, Juan Antonio. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales; Argentina Fil: Sanchis, Pablo Antonio. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales; Argentina Fil: Lage Vickers, Sofia. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales; Argentina Fil: Ortiz, Emiliano Germán. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales; Argentina Fil: Valacco, Maria Pia. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales; Argentina Fil: Paez, Alejandra. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Oncología "Ángel H. Roffo"; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Labanca, Estefania. University of Texas; Estados Unidos Fil: Meiss, Roberto. Academia Nacional de Medicina de Buenos Aires; Argentina Fil: Navone, Nora. University of Texas; Estados Unidos Fil: Cotignola, Javier Hernan. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales; Argentina Fil: Vazquez, Elba Susana. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales; Argentina Fil: Gueron, Geraldine. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales; Argentina

Prostate cancer (PCa) that progresses after androgen deprivation therapy (ADT) remains incurable. The intricacy of metabolic pathways associated with PCa progression spurred us to develop a metabolism-centric analysis. Using PCa patient-derived xenografts (PDXs) we assessed the metabolic changes after castration of tumor-bearing mice. We found that relapsed tumors had a significant increase in fatty acids and ketone body content compared with baseline. We confirmed that critical ketogenic/ketolytic enzymes (ACAT1, OXCT1, BDH1) were significantly augmented after castrate-resistant progression. Further, these enzymes are increased in the human donor tissue after progressing to ADT. Increased ACAT1 and OXCT1 was also observed for a subset of PCa patients that relapsed with low AR and ERG expression. These factors were associated with decreased biochemical relapse and progression free survival. In summary, our studies reveal the key metabolites fueling castration resistant progression in the context of a partial or complete loss of AR dependence. Citation Format: Estefania Labanca, Juan Bizzotto, Jun Yang, Pablo Sanchis, Peter Shepherd, Alejandra Paez, Valeria Antico-Arciuch, Nicolas Anselmino, Sofia Lage-Vickers, Anh Hoang, Mark Tituts, Eleni Efstathiou, Javier Cotignola, Christopher Logothetis, Elba Vazquez, Nora Navone, Geraldine Gueron. Prostate cancer castrate resistant progression usage of non-canonical androgen receptor signaling and ketone body fuel [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2346.

Cancer is a risk factor for SARS-CoV-2 infection. Recent reports have shown that prostate cancer (PCa) patients undergoing androgen-deprivation therapies (ADT) were partially protected from COVID-19. The human myxovirus resistance gene 1 (MX1) is expressed in many tissues, including prostate, and we have previously demonstrated its antitumoral activity in PCa. This protein participates in the antiviral response and it is an IFN-stimulated gene (ISGs), especially during influenza virus infection. There are ongoing clinical trials for COVID-19 prevention and/or treatment using type I or III interferons. However, IFN administration could enhance a "cytokine-storm" causing a hyper-inflammatory response and contributing to organ failure. In this work, we performed bioinformatics analyses in a case-control study from SARS-CoV-2 positive (n=403) and negative (n=50) patients. We analyzed the response to infection assessing gene expression profiles in nasopharyngeal swabs of key host cell receptors (ACE2, TMPRSS2, BSG/CD147, CTSB, CTSL, ADAM17) and antiviral proteins (MX1, MX2, NRF2, IRF3, HIF1A, HMOX1).SARS-CoV-2 positive cases had higher ACE2, but lower TMPRSS2, BSG/CD147 and CTSB expression. Patient age negatively affected ACE2 expression. MX1 and MX2 were higher in SARS-CoV-2 positive individuals, and negative trends were observed as patients' age increased. Principal Component Analysis determined that ACE2, MX1, MX2 and BSG/CD147 expressions were 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.Given that MX1 was differentially expressed between COVID-19 and non-COVID-19 patients, we evaluated MX1 expression in A549 and Calu3 lung cell lines. MX1 was significantly up-regulated upon infection with SARS-CoV-2.Since ADT reduces SARS-CoV-2 infection incidence, we aim to study MX1 regulation by dihydrotestosterone (DHT). We browsed publicly available ChIP-seq experiments evaluating androgen receptor (AR) binding sites in different PCa cell lines under DHT stimulation. Results indicated enriched AR binding sites on the MX1 sequence. Therefore, we treated LNCaP cells with DHT, observing a significant decrease in MX1 mRNA levels. Accordingly, we observed a significant increase of MX1 gene expression in PCa patients after ADT treatment.In summary, our study 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. Furthermore, we demonstrated MX1 modulation by ADT. Taking into consideration the fact that PCa patients that underwent ADT were less prone to present the infection, we propose this gene as an alternative druggable target for COVID-19 patients, especially those with PCa as a previous condition. Citation Format: Juan Antonio Bizzotto, Pablo Sanchis, Sofia Lage-Vickers, Rosario Lavignolle, Agustina Sabater, Mercedes Abbate, Ayelen Toro, Florencia Cascardo, Santiago Olszevicki, Nicolas Anselmino, Estefania Labanca, Emiliano Ortiz, Elba Vazquez, Javier Cotignola, Geraldine Gueron. Androgen-deprivation therapy boosts MX1 expression, a silent effector against COVID-19 [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 710.

Proteomics represents an important tool for the identification of new molecular targets for prostate cancer (PCa) tailored therapy. Innovative high-throughput proteomic platforms are now identifying and quantifying new specific and sensitive biomarkers for PCa detection, stratification, and treatment. Formalin-fixed and paraffin-embedded (FF-PE) sections mounted on microscope slides are hard to achieve given the low peptide yield obtained from the slides. Here we performed an innovative protocol for an in-depth quantitative mass spectrometry-based proteomics analysis of FF-PE PCa and benign prostate hyperplasia (BPH) sections, using phase-transfer surfactant-aided extraction/tryptic digestion of FF-PE proteins. Results yielded a list of 50 differential proteins only expressed in PCa samples. Of note, apolipoprotein E (APOE) was highly present in carcinoma samples. Furthermore, to evaluate the clinical significance of APOE in PCa we performed a bioinformatics analysis using the Oncomine database. We identified 16 publicly available gene expression microarray datasets comparing prostate adenocarcinoma versus normal prostate, which met our eligibility criteria. We carried out meta-analysis combining the data from the independent datasets. APOE was ranked by its P-value for every analysis scoring a gene rank and then we obtained a median rank (median P-value rank across datasets). APOE showed a significant upregulation (fold change >1.5, P Citation Format: Juan Bizzotto, Sofia Lage Vickers, Alejandra Paez, Carlos Scorticati, Javier Cotignola, Pia Valacco, Osvaldo Mazza, Elba Vazquez, Geraldine Gueron. Mass spectrometry-based proteomics study makes apolipoprotein E a potential risk factor for prostate cancer [abstract]. In: Proceedings of the AACR Special Conference: Prostate Cancer: Advances in Basic, Translational, and Clinical Research; 2017 Dec 2-5; Orlando, Florida. Philadelphia (PA): AACR; Cancer Res 2018;78(16 Suppl):Abstract nr A064.

Current approaches in proteomics techniques and MS systems have revived the quest for novel biomarkers in prostate cancer (PCa) boosting the molecular characterization of the disease. To reveal fundamental differences between benign and malignant growth of prostate cells, we combined a new protein extraction procedure that disrupts the crosslinked proteins from the previously formaldehyde-fixed, paraffin-embedded tissue samples with in-depth proteomic analysis (ESI-MS/MS). Human PCa and benign prostatic hyperplasia (BPH) tissue samples were obtained using phase-transfer surfactant-aided extraction/tryptic digestion of formalin-fixed and paraffin-embedded sections mounted on microscope slides. Data analysis was based on label-free spectral counting, identifying with a minimum of two peptides, 1331 and 1239 proteins in PCa and BPH tissue proteomes, respectively. 71 proteins were exclusively present in PCa samples, while 122 proteins where exclusively present in BPH samples. In order to prioritize candidate markers for PCa, we compared protein expression based on normalized spectral counts between tissue samples. We set as cut-offs proteins that were found with a minimum of three peptides within the PCa and BPH proteomes. This filter resulted in the selection of two clusters of 11 and 16 proteins, respectively. The data sets highlighted distinct proteins that were previously studied in the context of prostate cancer progression, including SSBP1, GDF15, NDRG1, C4A, and APOE for PCa and DUSP3, MME, SRI, and DSG1 for BPH, thus providing further confirmation for the robustness of our quantification method. We next subjected our candidate list to bioinformatics analysis (Oncomine). Accordingly, the 5 proteins mentioned for PCa were significantly upregulated (fold change >1.5, P≤0.05) in prostate adenocarcinoma vs. normal prostate gland. Whole-exome analysis (cBioportal) revealed amplification as the most frequent genetic alteration and RNASeq data also confirmed a significant upregulation for these proteins (P≤0.05). Strikingly, proteins associated with BPH were significantly downregulated (fold change >1.5, P≤0.05) across the same comparison and RNA-seq data also confirmed a significant downregulation for these proteins (P≤0.05). This report showcases significant and extensive differences in protein expression patterns between BPH and prostate carcinoma. Proteome analysis of prostate tissues should help to disclose the molecular mechanisms underlying prostate malignant growth, resulting in new sets of biomarkers for diagnostic, prognostic, and therapeutic use. Citation Format: Sofia Lage Vickers, Juan Antonio Bizzotto, Alejandra Paez, Javier Cotignola, Carlos Scorticati, Osvaldo Mazza, Pia Valacco, Geraldine Gueron, Elba Vazquez. Integrative prostate cancer tissue proteomics dissects clear and distinct proteomes for human prostate cancer and benign prostatic hyperplasia [abstract]. In: Proceedings of the AACR Special Conference: Prostate Cancer: Advances in Basic, Translational, and Clinical Research; 2017 Dec 2-5; Orlando, Florida. Philadelphia (PA): AACR; Cancer Res 2018;78(16 Suppl):Abstract nr A058.

Although it is well known that prostate cancer (PCa) is a progressive disease involving multiple gene alterations, little is known at the proteome level. Most of the functional information of the cancer-associated genes relies in the proteome, an exceptionally complex biological system involving several proteins that function through dynamic protein-protein interactions and post-translational modifications. To identify potential PCa protein biomarkers, we carried out an in depth proteomic analysis (ESI-MS/MS) using human PCa and BPH tissue. Samples were obtained using phase-transfer surfactant-aided extraction/tryptic digestion of formalin-fixed and paraffin-embedded sections mounted on microscope slides. We identified 1331 and 1239 proteins in PCa and BPH tissue proteomes respectively. 71 proteins were present in at least 50% of PCa samples and not in BPH samples, while 122 proteins where present in at least 50% of BPH samples and not in carcinoma samples. In order to prioritize candidate markers for PCa, we compared the differential protein expression based on normalized spectral counts between tissue samples. We set as cut-offs proteins that were found with a minimum of three peptides within our PCa proteomes. This filter resulted in the selection of 11 proteins. The list contained proteins that were previously studied in the context of prostate cancer progression, including SSBP1, GDF15, NDRG1, C4A & APOE, thus providing further confirmation for the robustness of our quantification method. Bioinformatics analysis (Oncomine) showed that the proteins aforementioned were significant up-regulated (fold change >1.5, P≤0.05) in prostate adenocarcinoma vs. normal prostate gland. Whole exome analysis (cBioportal), revealed amplification as the most frequent genetic alteration and RNASeq data also confirmed a significant up-regulation for these proteins (P≤0.05). To contextualize the proteomic data, we utilized protein complexes information from CORUM database. Utilizing biological complexes as a cluster vector, we calculate a Proteomics Signature Profile (PSP) for each sample based on the hit rates of its reported proteins, against the cluster vector. We identified 25 complexes differentially expressed between PCa and BPH. Among those, the top ranked cluster upregulated in PCa was EIF3 (p-value= 4,37x10-5), a protein complex that functions during the initiation phase of eukaryotic translation, composed of EIF3B, EIF3J and EIF3I. We hereby report and offer a new set of biomarkers in addition to the existing diagnostic tests that could significantly improve sensitivity and specificity in PCa diagnosis. Citation Format: Sofia Lage Vickers, Juan Bizzotto, Emiliano Ortiz, Alejandra Paez, Nicolás Anselmino, Javier Brandani, Mercedes Abbate, Javier Cotignola, Maria Pía Valacco, Elba Vazquez, Geraldine Gueron. A high through approach to delineate protein complexes in adenocarcinoma tissues [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 1293.