Development and validation of a clinical decision support system based on PSA, microRNAs, and MRI for the detection of prostate cancer.

OBJECTIVES: The aims of this study are to develop and validate a clinical decision support system based on demographics, prostate-specific antigen (PSA), microRNA (miRNA), and MRI for the detection of prostate cancer (PCa) and clinical significant (cs) PCa, and to assess if this system performs better compared to MRI alone. METHODS: This retrospective, multicenter, observational study included 222 patients (mean age 66, range 46-75 years) who underwent prostate MRI, miRNA (let-7a-5p and miR-103a-3p) assessment, and biopsy. Monoparametric and multiparametric models including age, PSA, miRNA, and MRI outcome were trained on 65% of the data and then validated on the remaining 35% to predict both PCa (any Gleason grade [GG]) and csPCa (GG ≥ 2 vs GG = 1/negative). Accuracy, sensitivity, specificity, positive and negative predictive value (NPV), and area under the receiver operating characteristic curve were calculated. RESULTS: MRI outcome was the best predictor in the monoparametric model for both detection of PCa, with sensitivity of 90% (95%CI 73-98%) and NPV of 93% (95%CI 82-98%), and for csPCa identification, with sensitivity of 91% (95%CI 72-99%) and NPV of 95% (95%CI 84-99%). Sensitivity and NPV of PSA + miRNA for the detection of csPCa were not statistically different from the other models including MRI alone. CONCLUSION: MRI stand-alone yielded the best prediction models for both PCa and csPCa detection in biopsy-naïve patients. The use of miRNAs let-7a-5p and miR-103a-3p did not improve classification performances compared to MRI stand-alone results. CLINICAL RELEVANCE STATEMENT: The use of miRNA (let-7a-5p and miR-103a-3p), PSA, and MRI in a clinical decision support system (CDSS) does not improve MRI stand-alone performance in the detection of PCa and csPCa. KEY POINTS: • Clinical decision support systems including MRI improve the detection of both prostate cancer and clinically significant prostate cancer with respect to PSA test and/or microRNA. • The use of miRNAs let-7a-5p and miR-103a-3p did not significantly improve MRI stand-alone performance. • Results of this study were in line with previous works on MRI and microRNA.

Identification of a minimum number of genes to predict triple-negative breast cancer subgroups from gene expression profiles.

BACKGROUND: Triple-negative breast cancer (TNBC) is a very heterogeneous disease. Several gene expression and mutation profiling approaches were used to classify it, and all converged to the identification of distinct molecular subtypes, with some overlapping across different approaches. However, a standardised tool to routinely classify TNBC in the clinics and guide personalised treatment is lacking. We aimed at defining a specific gene signature for each of the six TNBC subtypes proposed by Lehman et al. in 2011 (basal-like 1 (BL1); basal-like 2 (BL2); mesenchymal (M); immunomodulatory (IM); mesenchymal stem-like (MSL); and luminal androgen receptor (LAR)), to be able to accurately predict them. METHODS: Lehman's TNBCtype subtyping tool was applied to RNA-sequencing data from 482 TNBC (GSE164458), and a minimal subtype-specific gene signature was defined by combining two class comparison techniques with seven attribute selection methods. Several machine learning algorithms for subtype prediction were used, and the best classifier was applied on microarray data from 72 Italian TNBC and on the TNBC subset of the BRCA-TCGA data set. RESULTS: We identified two signatures with the 120 and 81 top up- and downregulated genes that define the six TNBC subtypes, with prediction accuracy ranging from 88.6 to 89.4%, and even improving after removal of the least important genes. Network analysis was used to identify highly interconnected genes within each subgroup. Two druggable matrix metalloproteinases were found in the BL1 and BL2 subsets, and several druggable targets were complementary to androgen receptor or aromatase in the LAR subset. Several secondary drug-target interactions were found among the upregulated genes in the M, IM and MSL subsets. CONCLUSIONS: Our study took full advantage of available TNBC data sets to stratify samples and genes into distinct subtypes, according to gene expression profiles. The development of a data mining approach to acquire a large amount of information from several data sets has allowed us to identify a well-determined minimal number of genes that may help in the recognition of TNBC subtypes. These genes, most of which have been previously found to be associated with breast cancer, have the potential to become novel diagnostic markers and/or therapeutic targets for specific TNBC subsets.

Gene Expression Signature Predictive of Neuroendocrine Transformation in Prostate Adenocarcinoma.

Neuroendocrine prostate cancer (NEPC) can arise de novo, but much more commonly occurs as a consequence of a selective pressure from androgen deprivation therapy or androgen receptor antagonists used for prostate cancer (PCa) treatment. The process is known as neuroendocrine transdifferentiation. There is little molecular characterization of NEPCs and consequently there is no standard treatment for this kind of tumors, characterized by highly metastases rates and poor survival. For this purpose, we profiled 54 PCa samples with more than 10-years follow-up for gene and miRNA expression. We divided samples into two groups (NE-like vs. AdenoPCa), according to their clinical and molecular features. NE-like tumors were characterized by a neuroendocrine fingerprint made of known neuroendocrine markers and novel molecules, including long non-coding RNAs and components of the estrogen receptor signaling. A gene expression signature able to predict NEPC was built and tested on independently published datasets. This study identified molecular features (protein-coding, long non-coding, and microRNAs), at the time of surgery, that may anticipate the NE transformation process of prostate adenocarcinoma. Our results may contribute to improving the diagnosis and treatment of this subgroup of tumors for which traditional therapy regimens do not show beneficial effects.

Circulating microRNAs combined with PSA for accurate and non-invasive prostate cancer detection.

The dosage of prostate-specific antigen (PSA), an easily evaluable and non-invasive biomarker, has made early detection of prostate cancer (PCa) possible. However, it leads to high percentages of unnecessary biopsies and may miss aggressive tumors in men with PSA levels below 4 ng/ml. Therefore, we propose to combine circulating microRNAs (miRs) with PSA, to improve the diagnostic route for PCa. Plasma miR profiling identified candidate diagnostic miRs in a discovery cohort of 60 tumors and 60 controls (men with benign prostatic hyperplasia or healthy donors). Linear models with an empirical Bayesian approach and multivariate penalized logistic regression were applied to select tumor-associated miRs and/or clinical variables. A classifier was developed and tested on a validation cohort of 68 tumors and 174 controls consecutively collected, where miRs were evaluated by quantitative real-time polymerase chain reaction. A classifier based on miR-103a-3p, let-7a-5p and PSA could detect both overall and clinically significant tumors better than PSA alone, even in 50-69 years aged men with PSA ≤ 4 ng/ml. Even in the validation cohort, the classifier performed better than PSA alone in terms of specificity and positive predictive value, allowing to correctly identify eight out of nine tumors undetected by PSA, including three high-risk and three tumors in 50-69 years old men. Of carriers of non-malignant lesions with PSA in the 4-16 ng/ml interval, who may avoid unnecessary biopsies, 34% were correctly identified. Coupling two circulating miRs with PSA could be a useful strategy to diagnose clinically significant PCa and avoid an important fraction of unnecessary biopsies.

iASPP/p63 autoregulatory feedback loop is required for the homeostasis of stratified epithelia.

iASPP, an inhibitory member of the ASPP (apoptosis stimulating protein of p53) family, is an evolutionarily conserved inhibitor of p53 which is frequently upregulated in human cancers. However, little is known about the role of iASPP under physiological conditions. Here, we report that iASPP is a critical regulator of epithelial development. We demonstrate a novel autoregulatory feedback loop which controls crucial physiological activities by linking iASPP to p63, via two previously unreported microRNAs, miR-574-3p and miR-720. By investigating its function in stratified epithelia, we show that iASPP participates in the p63-mediated epithelial integrity program by regulating the expression of genes essential for cell adhesion. Silencing of iASPP in keratinocytes by RNA interference promotes and accelerates a differentiation pathway, which also affects and slowdown cellular proliferation. Taken together, these data reveal iASPP as a key regulator of epithelial homeostasis.

Differential angiogenesis of bone and muscle endothelium in aging and inflammatory processes.

Different tissues have different endothelial features, however, the implications of this heterogeneity in pathological responses are not clear yet. "Inflamm-aging" has been hypothesized as a possible trigger of diseases, including osteoarthritis (OA) and sarcopenia, often present in the same patient. To highlight a possible contribution of organ-specific endothelial cells (ECs), we compare ECs derived from bone and skeletal muscle of the same OA patients. OA bone ECs show a pro-inflammatory signature and higher angiogenic sprouting as compared to muscle ECs, in control conditions and stimulated with TNFα. Furthermore, growth of muscle but not bone ECs decreases with increasing patient age and systemic inflammation. Overall, our data demonstrate that inflammatory conditions in OA patients differently affect bone and muscle ECs, suggesting that inflammatory processes increase angiogenesis in subchondral bone while associated systemic low-grade inflammation impairs angiogenesis in muscle, possibly highlighting a vascular trigger linking OA and sarcopenia.

Plasma microRNA ratios associated with breast cancer detection in a nested case-control study from a mammography screening cohort.

Mammographic breast cancer screening is effective in reducing breast cancer mortality. Nevertheless, several limitations are known. Therefore, developing an alternative or complementary non-invasive tool capable of increasing the accuracy of the screening process is highly desirable. The objective of this study was to identify circulating microRNA (miRs) ratios associated with BC in women attending mammography screening. A nested case-control study was conducted within the ANDROMEDA cohort (women of age 46-67 attending BC screening). Pre-diagnostic plasma samples, information on life-styles and common BC risk factors were collected. Small-RNA sequencing was carried out on plasma samples from 65 cases and 66 controls. miR ratios associated with BC were selected by two-sample Wilcoxon test and lasso logistic regression. Subsequent assessment by RT-qPCR of the miRs contained in the selected miR ratios was carried out as a platform validation. To identify the most promising biomarkers, penalised logistic regression was further applied to candidate miR ratios alone, or in combination with non-molecular factors. Small-RNA sequencing yielded 20 candidate miR ratios associated with BC, which were further assessed by RT-qPCR. In the resulting model, penalised logistic regression selected seven miR ratios (miR-199a-3p_let-7a-5p, miR-26b-5p_miR-142-5p, let-7b-5p_miR-19b-3p, miR-101-3p_miR-19b-3p, miR-93-5p_miR-19b-3p, let-7a-5p_miR-22-3p and miR-21-5p_miR-23a-3p), together with body mass index (BMI), menopausal status (MS), the interaction term BMI * MS, life-style score and breast density. The ROC AUC of the model was 0.79 with a sensitivity and specificity of 71.9% and 76.6%, respectively. We identified biomarkers potentially useful for BC screening measured through a widespread and low-cost technique. This is the first study reporting circulating miRs for BC detection in a screening setting. Validation in a wider sample is warranted.Trial registration: The Andromeda prospective cohort study protocol was retrospectively registered on 27-11-2015 (NCT02618538).

Mechanisms of antiviral activity of the new hDHODH inhibitor MEDS433 against respiratory syncytial virus replication.

Human respiratory syncytial virus (RSV) is an important cause of acute lower respiratory infections, for which no effective drugs are currently available. The development of new effective anti-RSV agents is therefore an urgent priority, and Host-Targeting Antivirals (HTAs) can be considered to target RSV infections. As a contribution to this antiviral avenue, we have characterized the molecular mechanisms of the anti-RSV activity of MEDS433, a new inhibitor of human dihydroorotate dehydrogenase (hDHODH), a key cellular enzyme of de novo pyrimidine biosynthesis. MEDS433 was found to exert a potent antiviral activity against RSV-A and RSV-B in the one-digit nanomolar range. Analysis of the RSV replication cycle in MEDS433-treated cells, revealed that the hDHODH inhibitor suppressed the synthesis of viral genome, consistently with its ability to specifically target hDHODH enzymatic activity. Then, the capability of MEDS433 to induce the expression of antiviral proteins encoded by Interferon-Stimulated Genes (ISGs) was identified as a second mechanism of its antiviral activity against RSV. Indeed, MEDS433 stimulated secretion of IFN-ß and IFN-λ1 that, in turn, induced the expression of some ISG antiviral proteins, such as IFI6, IFITM1 and IRF7. Singly expression of these ISG proteins reduced RSV-A replication, thus likely contributing to the overall anti-RSV activity of MEDS433. Lastly, MEDS433 proved to be effective against RSV-A replication even in a primary human small airway epithelial cell model. Taken as a whole, these observations provide new insights for further development of MEDS433, as a promising candidate to develop new strategies for treatment of RSV infections.

Epidermal Growth Factor Receptor (EGFR) mutation analysis, gene expression profiling and EGFR protein expression in primary prostate cancer.

BACKGROUND: Activating mutations of the epidermal growth factor receptor (EGFR) confer sensitivity to the tyrosine kinase inhibitors (TKi), gefitinib and erlotinib. We analysed EGFR expression, EGFR mutation status and gene expression profiles of prostate cancer (PC) to supply a rationale for EGFR targeted therapies in this disease. METHODS: Mutational analysis of EGFR TK domain (exons from 18 to 21) and immunohistochemistry for EGFR were performed on tumour tissues derived from radical prostatectomy from 100 PC patients. Gene expression profiling using oligo-microarrays was also carried out in 51 of the PC samples. RESULTS: EGFR protein overexpression (EGFRhigh) was found in 36% of the tumour samples, and mutations were found in 13% of samples. Patients with EGFRhigh tumours experienced a significantly increased risk of biochemical relapse (hazard ratio-HR 2.52, p=0.02) compared with patients with tumours expressing low levels of EGFR (EGFRlow). Microarray analysis did not reveal any differences in gene expression between EGFRhigh and EGFRlow tumours. Conversely, in EGFRhigh tumours, we were able to identify a 79 gene signature distinguishing mutated from non-mutated tumours. Additionally, 29 genes were found to be differentially expressed between mutated/EGFRhigh (n=3) and mutated/EGFRlow tumours (n=5). Four of the down-regulated genes, U19/EAF2, ABCC4, KLK3 and ANXA3 and one of the up-regulated genes, FOXC1, are involved in PC progression. CONCLUSIONS: Based on our findings, we hypothesize that accurate definition of the EGFR status could improve prognostic stratification and we suggest a possible role for EGFR-directed therapies in PC patients. Having been generated in a relatively small sample of patients, our results warrant confirmation in larger series.

Two Novel Ceramide-Like Molecules and miR-5100 Levels as Biomarkers Improve Prediction of Prostate Cancer in Gray-Zone PSA.

Reliable liquid biopsy-based tools able to accurately discriminate prostate cancer (PCa) from benign prostatic hyperplasia (BPH), when PSA is within the "gray zone" (PSA 4-10), are still urgent. We analyzed plasma samples from a cohort of 102 consecutively recruited patients with PSA levels between 4 and 16 ng/ml, using the SANIST-Cloud Ion Mobility Metabolomic Mass Spectrometry platform, combined with the analysis of a panel of circulating microRNAs (miR). By coupling CIMS ion mobility technology with SANIST, we were able to reveal three new structures among the most differentially expressed metabolites in PCa vs. BPH. In particular, two were classified as polyunsaturated ceramide ester-like and one as polysaturated glycerol ester-like. Penalized logistic regression was applied to build a model to predict PCa, using six circulating miR, seven circulating metabolites, and demographic/clinical variables, as covariates. Four circulating metabolites, miR-5100, and age were selected by the model, and the corresponding prediction score gave an AUC of 0.76 (C.I. = 0.66-0.85). At a specified cut-off, no high-risk tumor was misclassified, and 22 out of 53 BPH were correctly identified, reducing by 40% the false positives of PSA. We developed and applied a novel, minimally invasive, liquid biopsy-based powerful tool to characterize novel metabolites and identified new potential non-invasive biomarkers to better predict PCa, when PSA is uninformative as a tool for precision medicine in genitourinary cancers.

Castration-Induced Downregulation of SPARC in Stromal Cells Drives Neuroendocrine Differentiation of Prostate Cancer.

Fatal neuroendocrine differentiation (NED) of castration-resistant prostate cancer is a recurrent mechanism of resistance to androgen deprivation therapies (ADT) and antiandrogen receptor pathway inhibitors (ARPI) in patients. The design of effective therapies for neuroendocrine prostate cancer (NEPC) is complicated by limited knowledge of the molecular mechanisms governing NED. The paucity of acquired genomic alterations and the deregulation of epigenetic and transcription factors suggest a potential contribution from the microenvironment. In this context, whether ADT/ARPI induces stromal cells to release NED-promoting molecules and the underlying molecular networks are unestablished. Here, we utilized transgenic and transplantable mouse models and coculture experiments to unveil a novel tumor-stroma cross-talk that is able to induce NED under the pressure of androgen deprivation. Castration induced upregulation of GRP78 in tumor cells, which triggers miR29-b-mediated downregulation of the matricellular protein SPARC in the nearby stroma. SPARC downregulation enabled stromal cells to release IL6, a known inducer of NED. A drug that targets GRP78 blocked NED in castrated mice. A public, human NEPC gene expression dataset showed that Hspa5 (encoding for GRP78) positively correlates with hallmarks of NED. Finally, prostate cancer specimens from patients developing local NED after ADT showed GRP78 upregulation in tumor cells and SPARC downregulation in the stroma. These results point to GRP78 as a potential therapeutic target and to SPARC downregulation in stromal cells as a potential early biomarker of tumors undergoing NED. SIGNIFICANCE: Tumor-stroma cross-talk promotes neuroendocrine differentiation in prostate cancer in response to hormone therapy via a GRP78/SPARC/IL6 axis, providing potential therapeutic targets and biomarkers for neuroendocrine prostate cancer.

AKR1C3 is a biomarker and druggable target for oropharyngeal tumors.

PURPOSE: Oropharynx squamous cell carcinoma (OPSCC) is a subtype of head and neck squamous cell carcinoma (HNSCC) arising from the base of the tongue, lingual tonsils, tonsils, oropharynx or pharynx. The majority of HPV-positive OPSCCs has a good prognosis, but a fraction of them has a poor prognosis, similar to HPV-negative OPSCCs. An in-depth understanding of the molecular mechanisms underlying OPSCC is mandatory for the identification of novel prognostic biomarkers and/or novel therapeutic targets. METHODS: 14 HPV-positive and 15 HPV-negative OPSCCs with 5-year follow-up information were subjected to gene expression profiling and, subsequently, compared to three extensive published OPSCC cohorts to define robust biomarkers for HPV-negative lesions. Validation of Aldo-keto-reductases 1C3 (AKR1C3) by qRT-PCR was carried out on an independent cohort (n = 111) of OPSCC cases. In addition, OPSCC cell lines Fadu and Cal-27 were treated with Cisplatin and/or specific AKR1C3 inhibitors to assess their (combined) therapeutic effects. RESULTS: Gene set enrichment analysis (GSEA) on the four datasets revealed that the genes down-regulated in HPV-negative samples were mainly involved in immune system, whereas those up-regulated mainly in glutathione derivative biosynthetic and xenobiotic metabolic processes. A panel of 30 robust HPV-associated transcripts was identified, with AKR1C3 as top-overexpressed transcript in HPV-negative samples. AKR1C3 expression in 111 independent OPSCC cases positively correlated with a worse survival, both in the entire cohort and in HPV-positive samples. Pretreatment with a selective AKR1C3 inhibitor potentiated the effect of Cisplatin in OPSCC cells exhibiting higher basal AKR1C3 expression levels. CONCLUSIONS: We identified AKR1C3 as a potential prognostic biomarker in OPSCC and as a potential drug target whose inhibition can potentiate the effect of Cisplatin.

Gene expression profiling and prediction of response to hormonal neoadjuvant treatment with anastrozole in surgically resectable breast cancer.

Aromatase inhibition (AI) is the most effective endocrine treatment for breast cancer in post-menopausal patients, but a percentage of hormone receptor-positive cancers do not benefit from such therapy: for example, about 20% of patients treated with anastrozole do not respond and it is still impossible to accurately predict sensitivity. Our main goal was to identify a robust expression signature predictive of response to neoadjuvant treatment with anastrozole in patients with ER+ breast cancer. At the same time, we addressed the question of delineating treatment effects and possible mechanisms of intrinsic resistance occurring in non-responder patients. We analyzed the transcriptome of 17 tru-cut biopsies before treatment and 13 matched surgical samples after 3 months treatment with anastrozole taken from ER+ breast tumors. Molecular profiles were related to clinical response data. Treatment with anastrozole was associated with a decreased expression of genes relating to cell proliferation and an increased expression of genes relating to inflammatory processes. There was also an enrichment of induction of T-cell anergy, positive regulation of androgen signalling, synaptic transmission and vesicle trafficking in non-responders, and of cell cycle inhibition and induction of immune response in responders. We identified an expression signature of 77 probes (54 genes) that predicted response in 100% of our cases. Five of them were able to accurately predict response on an independent dataset (P = 0.0056) of 52 ER+ breast cancers treated with letrozole. Ten fixed independent samples from the anastrozole study were also used for RT-qPCR validations. This study suggests that a relative small number of genes analysed in a pre-treatment biopsy may identify patients likely to respond to AI neoadjuvant treatment. This may have practical utility translatable to the clinics. Furthermore, it delineates novel mechanisms of intrinsic resistance to AI therapy that could be further investigated in order to explore circumventing treatments.

Erratum: Mapelli, S.N., et al. A Novel Prostate Cell Type-Specific Gene Signature to Interrogate Prostate Tumor Differentiation Status and Monitor Therapeutic Response (Running Title: Phenotypic Classification of Prostate Tumors). Cancers 2020, 12, 176.

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A Novel Prostate Cell Type-Specific Gene Signature to Interrogate Prostate Tumor Differentiation Status and Monitor Therapeutic Response (Running Title: Phenotypic Classification of Prostate Tumors).

In this study, we extracted prostate cell-specific gene sets (metagenes) to define the epithelial differentiation status of prostate cancers and, using a deconvolution-based strategy, interrogated thousands of primary and metastatic tumors in public gene profiling datasets. We identified a subgroup of primary prostate tumors with low luminal epithelial enrichment (LumElow). LumElow tumors were associated with higher Gleason score and mutational burden, reduced relapse-free and overall survival, and were more likely to progress to castration-resistant prostate cancer (CRPC). Using discriminant function analysis, we generate a predictive 10-gene classifier for clinical implementation. This mini-classifier predicted with high accuracy the luminal status in both primary tumors and CRPCs. Immunohistochemistry for COL4A1, a low-luminal marker, sustained the association of attenuated luminal phenotype with metastatic disease. We found also an association of LumE score with tumor phenotype in genetically engineered mouse models (GEMMs) of prostate cancer. Notably, the metagene approach led to the discovery of drugs that could revert the low luminal status in prostate cell lines and mouse models. This study describes a novel tool to dissect the intrinsic heterogeneity of prostate tumors and provide predictive information on clinical outcome and treatment response in experimental and clinical samples.

The IKK/NF-κB signaling pathway requires Morgana to drive breast cancer metastasis.

NF-κB is a transcription factor involved in the regulation of multiple physiological and pathological cellular processes, including inflammation, cell survival, proliferation, and cancer cell metastasis. NF-κB is frequently hyperactivated in several cancers, including triple-negative breast cancer. Here we show that NF-κB activation in breast cancer cells depends on the presence of the CHORDC1 gene product Morgana, a previously unknown component of the IKK complex and essential for IκBα substrate recognition. Morgana silencing blocks metastasis formation in breast cancer mouse models and this phenotype is reverted by IκBα downregulation. High Morgana expression levels in cancer cells decrease recruitment of natural killer cells in the first phases of tumor growth and induce the expression of cytokines able to attract neutrophils in the primary tumor, as well as in the pre-metastatic lungs, fueling cancer metastasis. In accordance, high Morgana levels positively correlate with NF-κB target gene expression and poor prognosis in human patients.

A promoter-proximal transcript targeted by genetic polymorphism controls E-cadherin silencing in human cancers.

Long noncoding RNAs are emerging players in the epigenetic machinery with key roles in development and diseases. Here we uncover a complex network comprising a promoter-associated noncoding RNA (paRNA), microRNA and epigenetic regulators that controls transcription of the tumour suppressor E-cadherin in epithelial cancers. E-cadherin silencing relies on the formation of a complex between the paRNA and microRNA-guided Argonaute 1 that, together, recruit SUV39H1 and induce repressive chromatin modifications in the gene promoter. A single nucleotide polymorphism (rs16260) linked to increased cancer risk alters the secondary structure of the paRNA, with the risk allele facilitating the assembly of the microRNA-guided Argonaute 1 complex and gene silencing. Collectively, these data demonstrate the role of a paRNA in E-cadherin regulation and the impact of a noncoding genetic variant on its function. Deregulation of paRNA-based epigenetic networks may contribute to cancer and other diseases making them promising targets for drug discovery.

lncRNAs as Novel Indicators of Patients' Prognosis in Stage I Epithelial Ovarian Cancer: A Retrospective and Multicentric Study.

Purpose: Stage I epithelial ovarian cancer (EOC) represents about 10% of all EOCs and is characterized by good prognosis with fewer than 20% of patients relapsing. As it occurs less frequently than advanced-stage EOC, its molecular features have not been thoroughly investigated. We have demonstrated that in stage I EOC miR-200c-3p can predict patients' outcome. In the present study, we analyzed the expression of long non-coding RNAs (lncRNA) to enable potential definition of a non-coding transcriptional signature with prognostic relevance for stage I EOC.Experimental Design: 202 snap-frozen stage I EOC tumor biopsies, 47 of which relapsed, were gathered together from three independent tumor tissue collections and subdivided into a training set (n = 73) and a validation set (n = 129). Median follow up was 9 years. LncRNAs' expression profiles were correlated in univariate and multivariate analysis with overall survival (OS) and progression-free survival (PFS).Results: The expression of lnc-SERTAD2-3, lnc-SOX4-1, lnc-HRCT1-1, and PVT1 was associated in univariate and multivariate analyses with relapse and poor outcome in both training and validation sets (P < 0.001). Using the expression profiles of PVT1, lnc-SERTAD2-3, and miR-200c-3p simultaneously, it was possible to stratify patients into high and low risk. The OS for high- and low-risk individuals are 36 and 123 months, respectively (OR, 15.55; 95% confidence interval, 3.81-63.36).Conclusions: We have identified a non-coding transcriptional signature predictor of survival and biomarker of relapse for stage I EOC. Clin Cancer Res; 23(9); 2356-66. ©2016 AACR.

Dual tumor suppressing and promoting function of Notch1 signaling in human prostate cancer.

Adenocarcinomas of the prostate arise as multifocal heterogeneous lesions as the likely result of genetic and epigenetic alterations and deranged cell-cell communication. Notch signaling is an important form of intercellular communication with a role in growth/differentiation control and tumorigenesis. Contrasting reports exist in the literature on the role of this pathway in prostate cancer (PCa) development. We show here that i) compared to normal prostate tissue, Notch1 expression is significantly reduced in a substantial fraction of human PCas while it is unaffected or even increased in others; ii) acute Notch activation both inhibits and induces process networks associated with prostatic neoplasms; iii) down-modulation of Notch1 expression and activity in immortalized normal prostate epithelial cells increases their proliferation potential, while increased Notch1 activity in PCa cells suppresses growth and tumorigenicity through a Smad3-dependent mechanism involving p21WAF1/CIP1; iv) prostate cancer cells resistant to Notch growth inhibitory effects retain Notch1-induced upregulation of pro-oncogenic genes, like EPAS1 and CXCL6, also overexpressed in human PCas with high Notch1 levels. Taken together, these results reconcile conflicting data on the role of Notch1 in prostate cancer.

MicroRNA-424 impairs ubiquitination to activate STAT3 and promote prostate tumor progression.

Mutations and deletions in components of ubiquitin ligase complexes that lead to alterations in protein turnover are important mechanisms in driving tumorigenesis. Here we describe an alternative mechanism involving upregulation of the microRNA miR-424 that leads to impaired ubiquitination and degradation of oncogenic transcription factors in prostate cancers. We found that miR-424 targets the E3 ubiquitin ligase COP1 and identified STAT3 as a key substrate of COP1 in promoting tumorigenic and cancer stem-like properties in prostate epithelial cells. Altered protein turnover due to impaired COP1 function led to accumulation and enhanced basal and cytokine-induced activity of STAT3. We further determined that loss of the ETS factor ESE3/EHF is the initial event that triggers the deregulation of the miR-424/COP1/STAT3 axis. COP1 silencing and STAT3 activation were effectively reverted by blocking of miR-424, suggesting a possible strategy to attack this key node of tumorigenesis in ESE3/EHF-deficient tumors. These results establish miR-424 as an oncogenic effector linked to noncanonical activation of STAT3 and as a potential therapeutic target.