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Triple negative breast cancer (TNBC) accounts for about a fifth of all breast cancers and includes a diverse group of cancers. The heterogeneity of TNBC and the lack of target receptors on the cell surface make it difficult to develop specific therapeutic treatments. These aspects cause the high negative prognosis of patients with this type of tumor. The analysis of the molecular profiles of TNBC samples has allowed a better characterization of this tumor, supporting the search for new reliable diagnostic markers. To this end, we have developed a bioinformatic approach to integrate networks of genes differentially expressed in basal breast cancer compared to healthy tissues, with miRNAs able to regulate their expression. We studied the role of these miRNAs in TNBC subtype cell lines. We therefore identified two miRNAs, namely miR-135b and miR-365, with a central role in regulating the altered functional pathways in basal breast cancer. These two miRNAs are differentially expressed in human TNBC immunohistochemistry-selected tissues, and their modulation has been shown to play a role in the proliferation of tumor control and its migratory and invasive capacity in TNBC subtype cell lines. From the perspective of personalized medicine, we managed to modulate the expression of the two miRNAs in organotypic cultures, suggesting their possible use as diagnostic and therapeutic molecules. miR-135b and miR-365 have a key role in TNBC, controlling proliferation and invasion. Their detection could be helpful in TNBC diagnosis, while their modulation could become a new therapeutic tool for TNBC.

Human epidermal growth factor receptor 2 (HER2) is overexpressed/amplified in one third of breast cancers (BCs), and is associated with the poorer prognosis and the higher metastatic potential in BC. Emerging evidences highlight the role of microRNAs (miRNAs) in the regulation of several cellular processes, including BC., Methods: Here we identified, by in silico approach, a group of three miRNAs with central biological role (high degree centrality) in HER2+ BC. We validated their dysregulation in HER2+ BC and we analysed their functional role by in vitro approaches on selected cell lines and by in vivo experiments in an animal model., Results: We found that their expression is dysregulated in both HER2+ BC cell lines and human samples. Focusing our study on the only upregulated miRNA, miR-429 , we discovered that it acts as an oncogene and its upregulation is required for HER2+ cell proliferation. It controls the metastatic potential of HER2+ BC subtype by regulating migration and invasion of the cell., Conclusions: In HER2+ BC oncogenic miR-429 is able to regulate HIF1α pathway by directly targeting VHL mRNA, a molecule important for the degradation of HIF1α. The overexpression of miR-429 , observed in HER2+ BC, causes increased proliferation and migration of the BC cells. More important, silencing miR-429 succeeds in delaying tumor growth, thus miR-429 could be proposed as a therapeutic probe in HER2+ BC tumors., Competing Interests: Competing Interests: The authors have declared that no competing interest exists., (© The author(s).)

Personalized medicine relies on the integration and consideration of specific characteristics of the patient, such as tumor phenotypic and genotypic profiling., Background: Radiogenomics aim to integrate phenotypes from tumor imaging data with genomic data to discover genetic mechanisms underlying tumor development and phenotype., Methods: We describe a computational approach that correlates phenotype from magnetic resonance imaging (MRI) of breast cancer (BC) lesions with microRNAs (miRNAs), mRNAs, and regulatory networks, developing a radiomiRNomic map. We validated our approach to the relationships between MRI and miRNA expression data derived from BC patients. We obtained 16 radiomic features quantifying the tumor phenotype. We integrated the features with miRNAs regulating a network of pathways specific for a distinct BC subtype., Results: We found six miRNAs correlated with imaging features in Luminal A ( miR-1537 , -205 , -335 , -337 , -452 , and -99a ), seven miRNAs ( miR-142 , -155 , -190 , -190b , -1910 , -3617 , and -429 ) in HER2+, and two miRNAs ( miR-135b and -365-2 ) in Basal subtype. We demonstrate that the combination of correlated miRNAs and imaging features have better classification power of Luminal A versus the different BC subtypes than using miRNAs or imaging alone., Conclusion: Our computational approach could be used to identify new radiomiRNomic profiles of multi-omics biomarkers for BC differential diagnosis and prognosis.

Background: Modern high-throughput genomic technologies represent a comprehensive hallmark of molecular changes in pan-cancer studies. Although different cancer gene signatures have been revealed, the mechanism of tumourigenesis has yet to be completely understood. Pathways and networks are important tools to explain the role of genes in functional genomic studies. However, few methods consider the functional non-equal roles of genes in pathways and the complex gene-gene interactions in a network., Results: We present a novel method in pan-cancer analysis that identifies de-regulated genes with a functional role by integrating pathway and network data. A pan-cancer analysis of 7158 tumour/normal samples from 16 cancer types identified 895 genes with a central role in pathways and de-regulated in cancer. Comparing our approach with 15 current tools that identify cancer driver genes, we found that 35.6% of the 895 genes identified by our method have been found as cancer driver genes with at least 2/15 tools. Finally, we applied a machine learning algorithm on 16 independent GEO cancer datasets to validate the diagnostic role of cancer driver genes for each cancer. We obtained a list of the top-ten cancer driver genes for each cancer considered in this study., Conclusions: Our analysis 1) confirmed that there are several known cancer driver genes in common among different types of cancer, 2) highlighted that cancer driver genes are able to regulate crucial pathways.

Prostate cancer (PC) includes several phenotypes, from indolent to highly aggressive cancer. Actual diagnostic and prognostic tools have several limitations, and there is a need for new biomarkers to stratify patients and assign them optimal therapies by taking into account potential genetic and epigenetic differences. MicroRNAs (miRNAs) are small sequences of non-coding RNA regulating specific genes involved in the onset and development of PC. Stable miRNAs have been found in biofluids, such as serum and plasma; thus, the measurement of PC-associated miRNAs is emerging as a non-invasive tool for PC detection and monitoring. In this study, we conduct an in-depth literature review focusing on miRNAs that may contribute to the diagnosis and prognosis of PC. The role of miRNAs as a potential theranostic tool in PC is discussed. Using a meta-analysis approach, we found a group of 29 miRNAs with diagnostic properties and a group of seven miRNAs with prognostic properties, which were found already expressed in both biofluids and PC tissues. We tested the two miRNA groups on The Cancer Genome Atlas dataset of PC tissue samples with a machine-learning approach. Our results suggest that these 29 miRNAs should be considered as potential panel of biomarkers for the diagnosis of PC, both as in vivo non-invasive test and ex vivo confirmation test.

Dysregulation of microRNAs (miRNAs) has a fundamental role in the initiation, development and progression of several human cancers, including breast cancer (BC), since strong evidence has shown that miRNAs can regulate the expression of oncogenes or tumor suppressor genes. A possible role of miRNAs in the diagnosis in BC has been demonstrated. As miRNAs has been found stable in biofluids, extracellular multiple miRNA profiles have been proposed as diagnostic tools, showing better diagnostic performance than individual miRNAs in BC. In this paper, based on the current literature, we present the role of microRNAs in the diagnosis and therapy monitoring of BC. Furthermore, we report new miRNA-based drugs that could be turned into promising therapy for BC, alone or in combination with conventional therapy. We also discuss how extracellular miRNAs could become new, easily accessible, affordable, non-invasive tools for BC patients.

Dysregulation of microRNAs (miRNAs) is involved in the initiation and progression of several human cancers, including breast cancer (BC), as strong evidence has been found that miRNAs can act as oncogenes or tumor suppressor genes. This review presents the state of the art on the role of miRNAs in the diagnosis, prognosis, and therapy of BC. Based on the results obtained in the last decade, some miRNAs are emerging as biomarkers of BC for diagnosis (i.e., miR-9, miR-10b, and miR-17-5p), prognosis (i.e., miR-148a and miR-335), and prediction of therapeutic outcomes (i.e., miR-30c, miR-187, and miR-339-5p) and have important roles in the control of BC hallmark functions such as invasion, metastasis, proliferation, resting death, apoptosis, and genomic instability. Other miRNAs are of interest as new, easily accessible, affordable, non-invasive tools for the personalized management of patients with BC because they are circulating in body fluids (e.g., miR-155 and miR-210). In particular, circulating multiple miRNA profiles are showing better diagnostic and prognostic performance as well as better sensitivity than individual miRNAs in BC. New miRNA-based drugs are also promising therapy for BC (e.g., miR-9, miR-21, miR34a, miR145, and miR150), and other miRNAs are showing a fundamental role in modulation of the response to other non-miRNA treatments, being able to increase their efficacy (e.g., miR-21, miR34a, miR195, miR200c, and miR203 in combination with chemotherapy).

Defining the aggressiveness and growth rate of a malignant cell population is a key step in the clinical approach to treating tumor disease. The correct grading of breast cancer (BC) is a fundamental part in determining the appropriate treatment. Biological variables can make it difficult to elucidate the mechanisms underlying BC development. To identify potential markers that can be used for BC classification, we analyzed mRNAs expression profiles, gene copy numbers, microRNAs expression and their association with tumor grade in BC microarray-derived datasets. From mRNA expression results, we found that grade 2 BC is most likely a mixture of grade 1 and grade 3 that have been misclassified, being described by the gene signature of either grade 1 or grade 3. We assessed the potential of the new approach of integrating mRNA expression profile, copy number alterations, and microRNA expression levels to select a limited number of genomic BC biomarkers. The combination of mRNA profile analysis and copy number data with microRNA expression levels led to the identification of two gene signatures of 42 and 4 altered genes (FOXM1, KPNA4, H2AFV and DDX19A) respectively, the latter obtained through a meta-analytical procedure. The 42-based gene signature identifies 4 classes of up- or down-regulated microRNAs (17 microRNAs) and of their 17 target mRNA, and the 4-based genes signature identified 4 microRNAs (Hsa-miR-320d, Hsa-miR-139-5p, Hsa-miR-567 and Hsa-let-7c). These results are discussed from a biological point of view with respect to pathological features of BC. Our identified mRNAs and microRNAs were validated as prognostic factors of BC disease progression, and could potentially facilitate the implementation of assays for laboratory validation, due to their reduced number.