microRNA Expression Profile in Single Hormone Receptor-Positive Breast Cancers is Mainly Dependent on HER2 Status-A Pilot Study

Deregulated miRNA Expression in Triple-Negative Breast Cancer of Ancestral Genomic-Characterized Latina Patients

Among patients with triple-negative breast cancer (TNBC), several studies have suggested that deregulated microRNA (miRNA) expression may be associated with a more aggressive phenotype. Although tumor molecular signatures may be race- and/or ethnicity-specific, there is limited information on the molecular profiles in women with TNBC of Hispanic and Latin American ancestry. We simultaneously profiled TNBC biopsies for the genome-wide copy number and miRNA global expression from 28 Latina women and identified a panel of 28 miRNAs associated with copy number alterations (CNAs). Four selected miRNAs (miR-141-3p, miR-150-5p, miR-182-5p, and miR-661) were validated in a subset of tumor and adjacent non-tumor tissue samples, with miR-182-5p being the most discriminatory among tissue groups (AUC value > 0.8). MiR-141-3p up-regulation was associated with increased cancer recurrence; miR-661 down-regulation with larger tumor size; and down-regulation of miR-150-5p with larger tumor size, high p53 expression, increased cancer recurrence, presence of distant metastasis, and deceased status. This study reinforces the importance of integration analysis of CNAs and miRNAs in TNBC, allowing for the identification of interactions among molecular mechanisms. Additionally, this study emphasizes the significance of considering the patients ancestral background when examining TNBC, as it can influence the relationship between intrinsic tumor molecular characteristics and clinical manifestations of the disease.

Extracellular Vesicles and Their Zeta Potential as Future Markers Associated with Nutrition and Molecular Biomarkers in Breast Cancer

A nutritional intervention promotes the loss of body and visceral fat while maintaining muscle mass in breast cancer patients. Extracellular vesicles (EVs) and their characteristics can be potential biomarkers of disease. Here, we explore the changes in the Zeta potential of EVs; the content of miRNA-30, miRNA-145, and miRNA-155; and their association with body composition and biomarkers of metabolic risk in breast cancer patients, before and 6 months after a nutritional intervention. Clinicopathological data (HER2neu, estrogen receptor, and Ki67), anthropometric and body composition data, and plasma samples were available from a previous study. Plasma EVs were isolated and characterized in 16 patients. The expression of miRNA-30, miRNA-145, and miRNA-155 was analyzed. The Zeta potential was associated with HER2neu (β = 2.1; p = 0.00), Ki67 (β = -1.39; p = 0.007), estrogen positive (β = 1.57; p = 0.01), weight (β = -0.09; p = 0.00), and visceral fat (β = 0.004; p = 0.00). miRNA-30 was associated with LDL (β = -0.012; p = 0.01) and HDL (β = -0.02; p = 0.05). miRNA-155 was associated with visceral fat (β = -0.0007; p = 0.05) and Ki67 (β = -0.47; p = 0.04). Our results reveal significant associations between the expression of miRNA-30 and miRNA-155 and the Zeta potential of the EVs with biomarkers of metabolic risk and disease prognosis in women with breast cancer; particularly, the Zeta potential of EVs can be a new biomarker sensitive to changes in the nutritional status and breast cancer progression.

DisiMiR: Predicting Pathogenic miRNAs Using Network Influence and miRNA Conservation

MiRNAs have been shown to play a powerful regulatory role in the progression of serious diseases, including cancer, Alzheimer's, and others, raising the possibility of new miRNA-based therapies for these conditions. Current experimental methods, such as differential expression analysis, can discover disease-associated miRNAs, yet many of these miRNAs play no functional role in disease progression. Interventional experiments used to discover disease causal miRNAs can be time consuming and costly. We present DisiMiR: a novel computational method that predicts pathogenic miRNAs by inferring biological characteristics of pathogenicity, including network influence and evolutionary conservation. DisiMiR separates disease causal miRNAs from merely disease-associated miRNAs, and was accurate in four diseases: breast cancer (0.826 AUC), Alzheimer's (0.794 AUC), gastric cancer (0.853 AUC), and hepatocellular cancer (0.957 AUC). Additionally, DisiMiR can generate hypotheses effectively: 78.4% of its false positives that are mentioned in the literature have been confirmed to be causal through recently published research. In this work, we show that DisiMiR is a powerful tool that can be used to efficiently and flexibly to predict pathogenic miRNAs in an expression dataset, for the further elucidation of disease mechanisms, and the potential identification of novel drug targets.

miR-30d-5p: A Non-Coding RNA With Potential Diagnostic, Prognostic and Therapeutic Applications

Cancer is a great challenge facing global public health. Scholars have made plentiful efforts in the research of cancer therapy, but the results are still not satisfactory. In relevant literature, the role of miRNA in cancer has been widely concerned. MicroRNAs (miRNAs) are a non-coding, endogenous, single-stranded RNAs that regulate a variety of biological functions. The abnormal level of miR-30d-5p, a type of miRNAs, has been associated with various human tumor types, including lung cancer, colorectal cancer, esophageal cancer, prostate cancer, liver cancer, cervical cancer, breast cancer and other types of human tumors. This reflects the vital function of miR-30d-5p in tumor prognosis. miR-30d-5p can be identified either as an inhibitor hindering the development of, or a promoter accelerating the occurrence of tumors. In addition, the role of miR-30d-5p in cell proliferation, motility, apoptosis, autophagy, tumorigenesis, and chemoresistance are also noteworthy. The multiple roles of miR-30d-5p in human cancer suggest that it has broad feasibility as a biomarker and therapeutic target. This review describes the connection between miR-30d-5p and the clinical indications of tumors, and summarizes the mechanisms by which miR-30d-5p mediates cancer progression.

Lost but Not Least-Novel Insights into Progesterone Receptor Loss in Estrogen Receptor-Positive Breast Cancer

Estrogen receptor α (ERα) and progesterone receptor (PgR) are crucial prognostic and predictive biomarkers that are usually co-expressed in breast cancer (BC). However, 12-24% of BCs present ERα(+)/PgR(-) phenotype at immunohistochemical evaluation. In fact, BC may either show primary PgR(-) status (in chemonaïve tumor sample), lose PgR expression during neoadjuvant treatment, or acquire PgR(-) phenotype in local relapse or metastasis. The loss of PgR expression in ERα(+) breast cancer may signify resistance to endocrine therapy and poorer outcomes. On the other hand, ERα(+)/PgR(-) BCs may have a better response to neoadjuvant chemotherapy than double-positive tumors. Loss of PgR expression may be a result of pre-transcriptional alterations (copy number loss, mutation, epigenetic modifications), decreased transcription of the PGR gene (e.g., by microRNAs), and post-translational modifications (e.g., phosphorylation, sumoylation). Various processes involved in the down-regulation of PgR have distinct consequences on the biology of cancer cells. Occasionally, negative PgR status detected by immunohistochemical analysis is paradoxically associated with enhanced transcriptional activity of PgR that might be inhibited by antiprogestin treatment. Identification of the mechanism of PgR loss in each patient seems challenging, yet it may provide important information on the biology of the tumor and predict its responsiveness to the therapy.