Response Assessment With Molecular Characterization of Circulating Tumor Cells and Plasma MicroRNA Profiling in Patients With Locally Advanced Breast Cancer During Neoadjuvant Chemotherapy

Exploring the Potential Role of Circulating microRNAs as Biomarkers for Predicting Clinical Response to Neoadjuvant Therapy in Breast Cancer

Breast cancer (BC) is a leading cause of cancer-related deaths among women worldwide. Neoadjuvant therapy (NAT) is increasingly being used to reduce tumor burden prior to surgical resection. However, current techniques for assessing tumor response have significant limitations. Additionally, drug resistance is commonly observed, raising a need to identify biomarkers that can predict treatment sensitivity and survival outcomes. Circulating microRNAs (miRNAs) are small non-coding RNAs that regulate gene expression and have been shown to play a significant role in cancer progression as tumor inducers or suppressors. The expression of circulating miRNAs has been found to be significantly altered in breast cancer patients. Moreover, recent studies have suggested that circulating miRNAs can serve as non-invasive biomarkers for predicting response to NAT. Therefore, this review provides a brief overview of recent studies that have demonstrated the potential of circulating miRNAs as biomarkers for predicting the clinical response to NAT in BC patients. The findings of this review will strengthen future research on developing miRNA-based biomarkers and their translation into medical practice, which could significantly improve the clinical management of BC patients undergoing NAT.

The Long Noncoding RNA MEG3 Retains Epithelial-Mesenchymal Transition by Sponging miR-146b-5p to Regulate SLFN5 Expression in Breast Cancer Cells

More and more studies have shown that long noncoding RNAs (lncRNAs) play essential roles in malignant tumors. The lncRNA MEG3 serves as a crucial molecule in breast cancer development, but the specific molecular mechanism needs to be further explored. We previously reported that Schlafen family member 5 (SLFN5) inhibits breast cancer malignant development by regulating epithelial-mesenchymal transition (EMT), invasion, and proliferation/apoptosis. Herein, we demonstrated that MEG3 was downregulated in pan-cancers and correlated with SLFN5 expression positively in breast cancer by bioinformatics analysis of TCGA and UCSC Xena data. Intervention with MEG3 positively affected SLFN5 expression in breast cancer cells. MEG3 repressed EMT and migration/invasion, similar to our previously reported functions of SLFN5 in breast cancer. Through bioinformatics analysis of starBase and LncBase data, 12 miRNAs were found to regulate both SLFN5 and MEG3, in which miR-146b-5p was confirmed to be regulated by MEG3 using MEG3 siRNA and overexpression method. MiR-146b-5p could bind to both SLFN5 3′UTR and MEG3, and inhibit their expression in a competing endogenous RNA mechanism, assayed by luciferase reporter and RNA pull down methods. Therefore, we conclude that MEG3 positively modulates SLFN5 expression by sponging miR-146b-5p and inhibits breast cancer development.

Predictive biomarkers for personalized medicine in breast cancer

Breast cancer is one of the most frequent malignancies among women worldwide. Based on clinical and molecular features of breast tumors, patients are treated with chemotherapy, hormonal therapy and/or radiotherapy and more recently with immunotherapy or targeted therapy. These different therapeutic options have markedly improved patient outcomes. However, further improvement is needed to fight against resistance to treatment. In the rapidly growing area of research for personalized medicine, predictive biomarkers - which predict patient response to therapy - are essential tools to select the patients who are most likely to benefit from the treatment, with the aim to give the right therapy to the right patient and avoid unnecessary overtreatment. The search for predictive biomarkers is an active field of research that includes genomic, proteomic and/or machine learning approaches. In this review, we describe current strategies and innovative tools to identify, evaluate and validate new biomarkers. We also summarize current predictive biomarkers in breast cancer and discuss companion biomarkers of targeted therapy in the context of precision medicine.

Clinical utility of liquid biopsy in breast cancer: A systematic review

Advancements in genetic sequencing techniques along with the identification of specific mutations and structural changes in multiple cancer genes, make it possible to identify circulating tumor cells and cell free nucleic acids as blood-based biomarkers, serving as a liquid biopsy (LB) with great utility for the diagnosis, treatment and follow-up of patients with neoplasms. This systematic review focuses on the clinical utility of LB in patients with breast cancer (BC). Articles published between 1990 and 2021 were included. Databases searched: Trip Database, WoS, EMBASE, PubMed, SCOPUS, and Clinical Keys. Variables studied: Publication year, country, number of cases, primary study design, LB detection methods, genes found, overall survival, disease-free survival, stage, response to treatment, clinical utility, BC molecular type, systemic treatment and methodological quality of primary studies. Of 2619 articles, 74 were retained representing 12 658 patients, mainly cohort studies (66.2%), the majority were from China (15%) and Japan (12.2%). All primary studies described clinical stage and type of systemic treatment used. Most used biomarker detection method: DNA (52.7%) and type of analysis: quantification of total cfDNA (35.1%). PIK3CA mutation was most frequent (62.9%). Evidence suggests clinically useful applications of BC. Though heterogeneous, publications suggest that LB will constitute part of the standard diagnostic-therapeutic process of BC.