MicroRNA in diagnosis and therapy monitoring of early-stage triple-negative breast cancer

A panel of miRNAs as prognostic markers for African-American patients with triple negative breast cancer

BACKGROUND

To investigate the global expression profile of miRNAs, their impact on cellular signaling pathways, and their association with poor prognostic parameters in African-American (AA) patients with triple negative breast cancer (TNBC).

METHODS

Twenty-five samples of AA TNBC patients were profiled for global miRNA expression and stratified considering three clinical-pathological parameters: tumor size, lymph node (LN), and recurrence (REC) status. Differential miRNA expression analysis was performed for each parameter, and their discriminatory power was determined by Receiver Operating Characteristic (ROC) curve analysis. KMplotter was assessed to determine the association of the miRNAs with survival, and functional enrichment analysis to determine the main affected pathways and miRNA/mRNA target interactions.

RESULTS

A panel of eight, 23 and 27 miRNAs were associated with tumor size, LN, and REC status, respectively. Combined ROC analysis of two (miR-2117, and miR-378c), seven (let-7f-5p, miR-1255b-5p, miR-1268b, miR-200c-3p, miR-520d, miR-527, and miR-518a-5p), and three (miR-1200, miR-1249-3p, and miR-1271-3p) miRNAs showed a robust discriminatory power based on tumor size (AUC = 0.917), LN (AUC = 0.945) and REC (AUC = 0.981) status, respectively. Enrichment pathway analysis revealed their involvement in proteoglycans and glycan and cancer-associated pathways. Eight miRNAs with deregulated expressions in patients with large tumor size, positive LN metastasis, and recurrence were significantly associated with lower survival rates. Finally, the construction of miRNA/mRNA networks based in experimentally validated mRNA targets, revealed nodes of critical cancer genes, such as AKT1, BCL2, CDKN1A, EZR and PTEN.

CONCLUSIONS

Altogether, our data indicate that miRNA deregulated expression is a relevant biological factor that can be associated with the poor prognosis in TNBC of AA patients, by conferring to their TNBC cells aggressive phenotypes that are reflected in the clinical characteristics evaluated in this study.

Triple-negative breast cancer: A run-through of features, classification and current therapies

Breast cancer is the most prevalent cancer in women worldwide. Triple-negative breast cancer (TNBC) is characterized by the lack of expression of estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2. It is the most aggressive subtype of breast cancer and accounts for 12-20% of all breast cancer cases. TNBC is associated with younger age of onset, greater metastatic potential, higher incidence of relapse, and lower overall survival rates. Based on molecular phenotype, TNBC has been classified into six subtypes (BL1, BL2, M, MES, LAR, and IM). TNBC treatment is challenging due to its heterogeneity, highly invasive nature, and relatively poor therapeutics response. Chemotherapy and radiotherapy are conventional strategies for the treatment of TNBC. Recent research in TNBC and mechanistic understanding of disease pathogenesis using cutting-edge technologies has led to the unfolding of new lines of therapies that have been incorporated into clinical practice. Poly (ADP-ribose) polymerase and immune checkpoint inhibitors have made their way to the current TNBC treatment paradigm. This review focuses on the classification, features, and treatment progress in TNBC. Histological subtypes connected to recurrence, molecular classification of TNBC, targeted therapy for early and advanced TNBC, and advances in non-coding RNA in therapy are the key highlights in this review.

Early detection breast cancer: role of circulating plasma miRNA-21 expression as a potential screening biomarker

Aim

To explore the potential of the circulating plasma miRNA-21 as an early detection biomarker by comparing early-stage breast cancer (BG) and healthy control (HG) in Indonesian population.

Materials and methods

The enlisted patients were 26 adult female early-stage breast cancer patients (stage 1A, 1B, 2A, and 2B) of Airlangga University Hospital from August 2019 to October 2019. Sixteen volunteers were recruited as matching healthy subjects. MiRNA-21 expression was quantified by plasma qRT-PCR. Data analysis performed using IBM SPSS Statistics v.24 (IBM Corp., Armonk, NY, USA). MiRNA-21 cut-off, sensitivity, and specificity were analyzed using receiver operating characteristic (ROC) curve.

Results

The study included 26 BG and 16 HG subjects. The miRNA-21 expression in BG group was 3.933 (1.181-11.794) and 0.905 (0.164-4.532) in HG group (4.34 folds; P = 0.001), with 1.66 cut-off (92.3% sensitivity; 81.2% specificity). MiRNA-21 expression separated analysis in HG showed a 0.578 times lower expression in menopause subjects [0.651 (0.164-0.414)], compared to premenopause ones [(1.123 (0.758 - 4.532); P = 0.031]. Yet, in BG group, 1.729 times higher miRNA-21 expression was observed in menopause subjects (6.021 ± 3.583), compared to premenopause ones (3.500 ± 1.517; P = 0.022).

Conclusions

Circulating miRNA-21 expression is a potential biomarker for early detection of breast cancer and might act as a breast cancer risk predictor.

Development of a microRNA Panel for Classification of Abnormal Mammograms for Breast Cancer

Simple Summary

Breast cancer screening by mammography suffers from high rates of false positivity, resulting in unnecessary investigative imaging and biopsies. There is an unmet need for biomarkers that can distinguish between malignant and benign breast lesions. We performed miRNA profiling on 638 patients with abnormal mammograms and 100 healthy controls. A six-miRNA panel was identified and validated in an independent cohort that had an AUC of 0.881 when differentiating between cases versus those with benign lesions or healthy individuals with normal mammograms. In addition, biomarker panel scores increased with tumor size, stage and number of lymph nodes involved. This study demonstrates that circulating miRNAs can potentially be used in conjunction with mammography to differentiate between patients with malignant and benign breast lesions.

Abstract

Mammography is extensively used for breast cancer screening but has high false-positive rates. Here, prospectively collected blood samples were used to identify circulating microRNA (miRNA) biomarkers to discriminate between malignant and benign breast lesions among women with abnormal mammograms. The Discovery cohort comprised 72 patients with breast cancer and 197 patients with benign breast lesions, while the Validation cohort had 73 and 196 cancer and benign cases, respectively. Absolute expression levels of 324 miRNAs were determined using RT-qPCR. miRNA biomarker panels were identified by: (1) determining differential expression between malignant and benign breast lesions, (2) focusing on top differentially expressed miRNAs, and (3) building panels from an unbiased search among all expressed miRNAs. Two-fold cross-validation incorporating a feature selection algorithm and logistic regression was performed. A six-miRNA biomarker panel identified by the third strategy, had an area under the curve (AUC) of 0.785 and 0.774 in the Discovery and Validation cohorts, respectively, and an AUC of 0.881 when differentiating between cases versus those with benign lesions or healthy individuals with normal mammograms. Biomarker panel scores increased with tumor size, stage and number of lymph nodes involved. Our work demonstrates that circulating miRNA signatures can potentially be used with mammography to differentiate between patients with malignant and benign breast lesions.

Machine Learning Models to Improve the Differentiation Between Benign and Malignant Breast Lesions on Ultrasound: A Multicenter External Validation Study

Purpose

This study aimed to establish and evaluate the usefulness of a simple, practical, and easy-to-promote machine learning model based on ultrasound imaging features for diagnosing breast cancer (BC).

Materials and Methods

Logistic regression, random forest, extra trees, support vector, multilayer perceptron, and XG Boost models were developed. The modeling data set of 1345 cases was from a tertiary class A hospital in China. The external validation data set of 1965 cases were from 3 tertiary class A hospitals and 2 primary hospitals. The area under the receiver operating characteristic curve (AUC) was used as the main evaluation index, and pathological biopsy was used as the gold standard for evaluating each model. Diagnostic capability was also compared with that of clinicians.

Results

Among the six models, the logistic model showed superior diagnostic efficiency, with an AUC of 0.771 and 0.906 and Brier scores of 0.181 and 0.165 in the test and validation sets, respectively. The AUCs of the clinician diagnosis and the logistic model were 0.913 and 0.906. Their AUCs in the tertiary class A hospitals were 0.915 and 0.915, respectively, and were 0.894 and 0.873 in primary hospitals, respectively.

Conclusion

The externally validated logical model can be used to distinguish between malignant and benign breast lesions in ultrasound images. Compared with clinician diagnosis, the logistic model has better diagnostic efficiency, making it potentially useful to assist in screening, particularly in lower level medical institutions.

Trial Registration

http://www.clinicaltrials.gov. ClinicalTrials.gov ID: NCT03080623.

Clinical Identification of Dysregulated Circulating microRNAs and Their Implication in Drug Response in Triple Negative Breast Cancer (TNBC) by Target Gene Network and Meta-Analysis

Resistance to therapy is a persistent problem that leads to mortality in breast cancer, particularly triple-negative breast cancer (TNBC). MiRNAs have become a focus of investigation as tissue-specific regulators of gene networks related to drug resistance. Circulating miRNAs are readily accessible non-invasive potential biomarkers for TNBC diagnosis, prognosis, and drug-response. Our aim was to use systems biology, meta-analysis, and network approaches to delineate the drug resistance pathways and clinical outcomes associated with circulating miRNAs in TNBC patients. MiRNA expression analysis was used to investigate differentially regulated circulating miRNAs in TNBC patients, and integrated pathway regulation, gene ontology, and pharmacogenomic network analyses were used to identify target genes, miRNAs, and drug interaction networks. Herein, we identified significant differentially expressed circulating miRNAs in TNBC patients (miR-19a/b-3p, miR-25-3p, miR-22-3p, miR-210-3p, miR-93-5p, and miR-199a-3p) that regulate several molecular pathways (PAM (PI3K/Akt/mTOR), HIF-1, TNF, FoxO, Wnt, and JAK/STAT, PD-1/PD-L1 pathways and EGFR tyrosine kinase inhibitor resistance (TKIs)) involved in drug resistance. Through meta-analysis, we demonstrated an association of upregulated miR-93, miR-210, miR-19a, and miR-19b with poor overall survival outcomes in TNBC patients. These results identify miRNA-regulated mechanisms of drug resistance and potential targets for combination with chemotherapy to overcome drug resistance in TNBC. We demonstrate that integrated analysis of multi-dimensional data can unravel mechanisms of drug-resistance related to circulating miRNAs, particularly in TNBC. These circulating miRNAs may be useful as markers of drug response and resistance in the guidance of personalized medicine for TNBC.

Systems Medicine Design for Triple-Negative Breast Cancer and Non-Triple-Negative Breast Cancer Based on Systems Identification and Carcinogenic Mechanisms

Triple-negative breast cancer (TNBC) is a heterogeneous subtype of breast cancers with poor prognosis. The etiology of triple-negative breast cancer (TNBC) is involved in various biological signal cascades and multifactorial aberrations of genetic, epigenetic and microenvironment. New therapeutic for TNBC is urgently needed because surgery and chemotherapy are the only available modalities nowadays. A better understanding of the molecular mechanisms would be a great challenge because they are triggered by cascade signaling pathways, genetic and epigenetic regulations, and drug–target interactions. This would allow the design of multi-molecule drugs for the TNBC and non-TNBC. In this study, in terms of systems biology approaches, we proposed a systematic procedure for systems medicine design toward TNBC and non-TNBC. For systems biology approaches, we constructed a candidate genome-wide genetic and epigenetic network (GWGEN) by big databases mining and identified real GWGENs of TNBC and non-TNBC assisting with corresponding microarray data by system identification and model order selection methods. After that, we applied the principal network projection (PNP) approach to obtain the core signaling pathways denoted by KEGG pathway of TNBC and non-TNBC. Comparing core signaling pathways of TNBC and non-TNBC, essential carcinogenic biomarkers resulting in multiple cellular dysfunctions including cell proliferation, autophagy, immune response, apoptosis, metastasis, angiogenesis, epithelial-mesenchymal transition (EMT), and cell differentiation could be found. In order to propose potential candidate drugs for the selected biomarkers, we designed filters considering toxicity and regulation ability. With the proposed systematic procedure, we not only shed a light on the differences between carcinogenetic molecular mechanisms of TNBC and non-TNBC but also efficiently proposed candidate multi-molecule drugs including resveratrol, sirolimus, and prednisolone for TNBC and resveratrol, sirolimus, carbamazepine, and verapamil for non-TNBC.

Triple-negative breast cancer: promising prognostic biomarkers currently in development

Introduction: Triple-negative breast cancer (TNBC) is an aggressive type of breast cancer associated with poor prognosis and limited treatment options. Validated prognostic and predictive biomarkers are needed to guide treatment decisions and prognostication.Areas covered: In this review, we discuss established and developing prognostic and predictive biomarkers in TNBC and associated emerging and approved therapies. Biomarkers reviewed include epidermal growth factor receptor (EGFR), vascular endothelial growth factors (VEGF), fibroblast growth factor receptor (FGFR), human epidermal growth factor receptor 2 (HER2), androgen receptor, NOTCH signaling, oxidative stress/redox signaling, microRNAs, TP53 mutation, breast cancer susceptibility gene 1 or 2 (BRCA1/2) mutation/homologous recombination deficiency (HRD), NTRK gene fusion, PI3K/AKT/mTOR, immune biomarkers (programmed death-ligand 1 (PDL1), tumor-infiltrating lymphocytes (TILs), tumor mutational burden (TMB), neoantigens, defects in DNA mismatch repair proteins (dMMR)/microsatellite instability-high (MSI-H)), circulating tumor cells/cell-free DNA, novel targets of antibody-drug conjugates, and residual disease.Expert opinion: Biomarker-driven care in the management of TNBC is increasing and has helped expand options for patients diagnosed with this subtype of breast cancer. Research efforts are ongoing to identify additional biomarkers and targeted treatment options with the ultimate goal of improving clinical outcomes and survivorship.

Advances in multiplexed techniques for the detection and quantification of microRNAs

MicroRNA detection is currently a crucial analytical chemistry challenge: almost 2000 papers were referenced in PubMed in 2018 and 2019 for the keywords "miRNA detection method". MicroRNAs are potential biomarkers for multiple diseases including cancers, neurodegenerative and cardiovascular diseases. Since miRNAs are stably released in bodily fluids, they are of prime interest for the development of non-invasive diagnosis methods, such as liquid biopsies. Their detection is however challenging, as high levels of sensitivity, specificity and robustness are required. The analysis also needs to be quantitative, since the aim is to detect miRNA concentration changes. Moreover, a high multiplexing capability is also of crucial importance, since the clinical potential of miRNAs probably lays in our ability to perform parallel mapping of multiple miRNA concentrations and recognize typical disease signature from this profile. A plethora of biochemical innovative detection methods have been reported recently and some of them provide new solutions to the problem of sensitive multiplex detection. In this review, we propose to analyze in particular the new developments in multiplexed approaches to miRNA detection. The main aspects of these methods (including sensitivity and specificity) will be analyzed, with a particular focus on the demonstrated multiplexing capability and potential of each of these methods.

Regulatory Interplay between miR-181a-5p and Estrogen Receptor Signaling Cascade in Breast Cancer

Simple Summary

Despite huge efforts in breast cancer care programs, patient’s survival rates greatly vary. Differences in response to therapy still represent the major challenge for clinicians and biologists. Define new anticancer mechanisms and innovative predictors for resistance could be a valid strategy to permanently defeat breast cancer. Here we propose the epigenetic based reprogramming of breast cancer, which leverages on the crosstalk between miR-181a-5p and Estrogen Receptor α. This simultaneously approach allows to induce miR-181a-5p and reduce the receptor expression, blocking the estrogen-dependent proliferative pathway underlying breast cancer progression. Since the epigenetic approach insists on transcriptional regulation, it is mostly independent of the acquired resistance mechanisms typically induced by prolonged endocrine therapy and therefore can be used as a sensitizer, neoadjuvant, or in combination with the standard in care treatments against breast cancer.

Abstract

The efficacy and side effects of endocrine therapy in breast cancer (BC) depend largely on estrogen receptor alpha (ERα) expression, the specific drug administered, and treatment scheduling. Although the benefits of endocrine therapy outweigh any adverse effects in the initial stages of BC, later- or advanced-stage tumors acquire resistance to treatments. The mechanisms underlying tumor resistance to therapy are still not well understood, posing a major challenge for BC patient care. Epigenetic regulation and miRNA expression may be involved in the switch from a treatment-sensitive to a treatment-resistant state and could provide a valid therapeutic strategy for ERα negative BC. Here, a hybrid lysine-specific histone demethylase inhibitor, MC3324, displaying selective estrogen receptor down-regulator-like activities in BC, was used to highlight the interplay between epigenetic and ERα signaling. MC3324 anticancer action is mediated by microRNA (miRNA) expression regulation, indicating an innovative function for this molecule. Integrated analysis suggests a crosstalk between estrogen signaling, ERα interactors, miRNAs, and their putative targets. Specifically, miR-181a-5p expression is regulated by MC3324 and has an impact on cellular levels of ERα. A comparison of breast tumor versus healthy mammary tissues confirmed the important role of miR-181a-5p in ERα regulation and points to its putative predictive function in BC therapy.

Current Achievements and Applications of Transcriptomics in Personalized Cancer Medicine

Over the last decades, transcriptome profiling emerged as one of the most powerful approaches in oncology, providing prognostic and predictive utility for cancer management. The development of novel technologies, such as revolutionary next-generation sequencing, enables the identification of cancer biomarkers, gene signatures, and their aberrant expression affecting oncogenesis, as well as the discovery of molecular targets for anticancer therapies. Transcriptomics contribute to a change in the holistic understanding of cancer, from histopathological and organic to molecular classifications, opening a more personalized perspective for tumor diagnostics and therapy. The further advancement on transcriptome profiling may allow standardization and cost reduction of its analysis, which will be the next step for transcriptomics to become a canon of contemporary cancer medicine.

miR-335-5p suppresses gastric cancer progression by targeting MAPK10

Background

Recent studies have established the roles of microRNAs (miRNAs) in cancer progression. The aberrant expression of miR-335-5p has been reported in many cancers, including gastric cancer (GC). In this study, the precise roles of miR-335-5p in GC as well as the molecular mechanisms underlying its effects, including the role of its target MAPK10, were evaluated.

Methods

Quantitative real-time PCR was used to evaluate miR-335-5p levels in GC cell lines and tissues. MTT and colony formation assays were used to detect cell proliferation, and Transwell and wound-healing assays were used to evaluate the invasion and migration of GC cells. The correlation between levels of miR-335-5p and the cell cycle-related target gene mitogen-activated protein kinase 10 (MAPK10) in GC was analyzed. In addition, the candidate target was evaluated by a luciferase reporter assay, qRT-PCR, and western blotting.

Results

The levels of miR-335-5p were downregulated in GC tissues and cell lines. Furthermore, miR-335-5p inhibited the proliferation and migration of GC cells and induced apoptosis. Additionally, miR-335-5p arrested the cell cycle at the G1/S phase in GC cells in vitro. Levels of miR-335-5p and the cell cycle-related target gene MAPK10 in GC were correlated, and MAPK10 was directly targeted by miR-335-5p.

Conclusions

These data suggest that miR-335-5p is a tumor suppressor and acts via MAPK10 to inhibit GC progression.

Evaluating the Use of Circulating MicroRNA Profiles for Lung Cancer Detection in Symptomatic Patients

Importance

The overall low survival rate of patients with lung cancer calls for improved detection tools to enable better treatment options and improved patient outcomes. Multivariable molecular signatures, such as blood-borne microRNA (miRNA) signatures, may have high rates of sensitivity and specificity but require additional studies with large cohorts and standardized measurements to confirm the generalizability of miRNA signatures.

Objective

To investigate the use of blood-borne miRNAs as potential circulating markers for detecting lung cancer in an extended cohort of symptomatic patients and control participants.

Design, Setting, and Participants

This multicenter, cohort study included patients from case-control and cohort studies (TREND and COSYCONET) with 3102 patients being enrolled by convenience sampling between March 3, 2009, and March 19, 2018. For the cohort study TREND, population sampling was performed. Clinical diagnoses were obtained for 3046 patients (606 patients with non-small cell and small cell lung cancer, 593 patients with nontumor lung diseases, 883 patients with diseases not affecting the lung, and 964 unaffected control participants). No samples were removed because of experimental issues. The collected data were analyzed between April 2018 and November 2019.

Main Outcomes and Measures

Sensitivity and specificity of liquid biopsy using miRNA signatures for detection of lung cancer.

Results

A total of 3102 patients with a mean (SD) age of 61.1 (16.2) years were enrolled. Data on the sex of the participants were available for 2856 participants; 1727 (60.5%) were men. Genome-wide miRNA profiles of blood samples from 3046 individuals were evaluated by machine-learning methods. Three classification scenarios were investigated by splitting the samples equally into training and validation sets. First, a 15-miRNA signature from the training set was used to distinguish patients diagnosed with lung cancer from all other individuals in the validation set with an accuracy of 91.4% (95% CI, 91.0%-91.9%), a sensitivity of 82.8% (95% CI, 81.5%-84.1%), and a specificity of 93.5% (95% CI, 93.2%-93.8%). Second, a 14-miRNA signature from the training set was used to distinguish patients with lung cancer from patients with nontumor lung diseases in the validation set with an accuracy of 92.5% (95% CI, 92.1%-92.9%), sensitivity of 96.4% (95% CI, 95.9%-96.9%), and specificity of 88.6% (95% CI, 88.1%-89.2%). Third, a 14-miRNA signature from the training set was used to distinguish patients with early-stage lung cancer from all individuals without lung cancer in the validation set with an accuracy of 95.9% (95% CI, 95.7%-96.2%), sensitivity of 76.3% (95% CI, 74.5%-78.0%), and specificity of 97.5% (95% CI, 97.2%-97.7%).

Conclusions and Relevance

The findings of the study suggest that the identified patterns of miRNAs may be used as a component of a minimally invasive lung cancer test, complementing imaging, sputum cytology, and biopsy tests.

Association of mammographic density measures and breast cancer "intrinsic" molecular subtypes

PURPOSE

We evaluated the association of percent mammographic density (PMD), absolute dense area (DA), and non-dense area (NDA) with risk of "intrinsic" molecular breast cancer (BC) subtypes.

METHODS

We pooled 3492 invasive BC and 10,148 controls across six studies with density measures from prediagnostic, digitized film-screen mammograms. We classified BC tumors into subtypes [63% Luminal A, 21% Luminal B, 5% HER2 expressing, and 11% as triple negative (TN)] using information on estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2), and tumor grade. We used polytomous logistic regression to calculate odds ratio (OR) and 95% confidence intervals (CI) for density measures (per SD) across the subtypes compared to controls, adjusting for age, body mass index and study, and examined differences by age group.

RESULTS

All density measures were similarly associated with BC risk across subtypes. Significant interaction of PMD by age (P = 0.001) was observed for Luminal A tumors, with stronger effect sizes seen for younger women < 45 years (OR = 1.69 per SD PMD) relative to women of older ages (OR = 1.53, ages 65-74, OR = 1.44 ages 75 +). Similar but opposite trends were seen for NDA by age for risk of Luminal A: risk for women: < 45 years (OR = 0.71 per SD NDA) was lower than older women (OR = 0.83 and OR = 0.84 for ages 65-74 and 75 + , respectively) (P < 0.001). Although not significant, similar patterns of associations were seen by age for TN cancers.

CONCLUSIONS

Mammographic density measures were associated with risk of all "intrinsic" molecular subtypes. However, findings of significant interactions between age and density measures may have implications for subtype-specific risk models.

Triple negative breast cancer in the era of miRNA

The objective of this review is to elucidate the role of miRNAs in triple negative breast cancer (TNBC). To achieve our goal, we searched databases such as PubMed, ScienceDirect, Springer, Web of Science and Scopus. We retrieved up to 1233 articles, based a rigorous selection criterion, only 197 articles were extensively reviewed. We selected articles only addressing TNBC, but not other types of breast cancer, with the employed approach being miRNA analysis and/or profiling. Our extensive review resulted in grouping of miRNAs into categories in which specific members of miRNAs have roles in specific mechanism in TNBC i.e., carcinogenesis, invasion, metastasis, apoptosis, diagnosis, prognosis, and treatment. TNBC is an aggressive subtype of breast cancer; therefore, different approaches for accurate diagnosis, prognosis and treatment are needed. In this review we summarize the up-to-date miRNA profiling, prognostic, and therapeutic findings that add to the route of controlling TNBC.

Modulatory Role of microRNAs in Triple Negative Breast Cancer with Basal-Like Phenotype

Development of new research, classification, and therapeutic options are urgently required due to the fact that TNBC is a heterogeneous malignancy. The expression of high molecular weight cytokeratins identifies a biologically and clinically distinct subgroup of TNBCs with a basal-like phenotype, representing about 75% of TNBCs, while the remaining 25% includes all other intrinsic subtypes. The triple negative phenotype in basal-like breast cancer (BLBC) makes it unresponsive to endocrine therapy, i.e., tamoxifen, aromatase inhibitors, and/or anti-HER2-targeted therapies; for this reason, only chemotherapy can be considered an approach available for systemic treatment even if it shows poor prognosis. Therefore, treatment for these subgroups of patients is a strong challenge for oncologists due to disease heterogeneity and the absence of unambiguous molecular targets. Dysregulation of the cellular miRNAome has been related to huge cellular process deregulations underlying human malignancy. Consequently, epigenetics is a field of great promise in cancer research. Increasing evidence suggests that specific miRNA clusters/signatures might be of clinical utility in TNBCs with basal-like phenotype. The epigenetic mechanisms behind tumorigenesis enable progress in the treatment, diagnosis, and prevention of cancer. This review intends to summarize the epigenetic findings related to miRNAome in TNBCs with basal-like phenotype.

Non-Invasive Biomarkers for Early Detection of Breast Cancer

Breast cancer is the most common cancer in women worldwide. Accurate early diagnosis of breast cancer is critical in the management of the disease. Although mammogram screening has been widely used for breast cancer screening, high false-positive and false-negative rates and radiation from mammography have always been a concern. Over the last 20 years, the emergence of "omics" strategies has resulted in significant advances in the search for non-invasive biomarkers for breast cancer diagnosis at an early stage. Circulating carcinoma antigens, circulating tumor cells, circulating cell-free tumor nucleic acids (DNA or RNA), circulating microRNAs, and circulating extracellular vesicles in the peripheral blood, nipple aspirate fluid, sweat, urine, and tears, as well as volatile organic compounds in the breath, have emerged as potential non-invasive diagnostic biomarkers to supplement current clinical approaches to earlier detection of breast cancer. In this review, we summarize the current progress of research in these areas.

Circulating microRNAs and their role in the immune response in triple-negative breast cancer

Breast cancer (BC) is the most common type of cancer in women worldwide, and despite advances in treatments, its incidence and mortality are increasing. Therefore, it is necessary to develop new, non-invasive tests that provide more accurate diagnosis and prognosis in a timely manner. A promising approach is measuring the presence of biomarkers to detect tumors at various stages and determine their specific characteristics, thus allowing for more personalized treatment. MicroRNAs (miRNAs) serve a role in gene expression, primarily by interacting with messenger RNAs, and may be potential biomarkers for detecting cancer. They are detectable in tissues and blood, including plasma and/or serum, are stable and often tumor specific. Also, different miRNAs are associated with specific BC molecular subtypes. Triple-negative BC (TNBC) is a type of BC in which the primary targets for hormonal therapy are absent. It is an aggressive phenotype, which frequently metastasizes and is associated with an unfavorable prognosis. The present review focuses on circulating miRNAs in patients with TNBC, with an emphasis on their interaction with the immune response checkpoint genes PD-1, PD-L1 and CTLA4. Modulation and response of the immune system are of interest in cancer treatment due to the success of immunotherapy in the treatment of various neoplasms. Based on the findings of this literature review and the in silico analysis performed as part of this review, it is concluded that circulating hsa-miR-195 and hsa-miR-155 in TNBC interact with checkpoint genes involved in the immune response. Further analysis of the expression of these circulating miRNAs and their association with prognosis in patients with TNBC treated with immunotherapy should be assessed to evaluate their possible use as non-invasive predictive biomarkers. In addition, functional studies to analyze biologically relevant targets in the development and prognosis of TNBC, which could be therapeutic targets, are also recommended.

Novel miRNA signature for predicting the stage of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer deaths worldwide. Recently, microRNAs (miRNAs) are reported to be altered and act as potential biomarkers in various cancers. However, miRNA biomarkers for predicting the stage of HCC are limitedly discovered. Hence, we sought to identify a novel miRNA signature associated with cancer stage in HCC. We proposed a support vector machine (SVM)-based cancer stage prediction method, SVM-HCC, which uses an inheritable bi-objective combinatorial genetic algorithm for selecting a minimal set of miRNA biomarkers while maximizing the accuracy of predicting the early and advanced stages of HCC. SVM-HCC identified a 23-miRNA signature that is associated with cancer stages in patients with HCC and achieved a 10-fold cross-validation accuracy, sensitivity, specificity, Matthews correlation coefficient, and area under the receiver operating characteristic curve (AUC) of 92.59%, 0.98, 0.74, 0.80, and 0.86, respectively; and test accuracy and test AUC of 74.28% and 0.73, respectively. We prioritized the miRNAs in the signature based on their contributions to predictive performance, and validated the prognostic power of the prioritized miRNAs using Kaplan–Meier survival curves. The results showed that seven miRNAs were significantly associated with prognosis in HCC patients. Correlation analysis of the miRNA signature and its co-expressed miRNAs revealed that hsa-let-7i and its 13 co-expressed miRNAs are significantly involved in the hepatitis B pathway. In clinical practice, a prediction model using the identified 23-miRNA signature could be valuable for early-stage detection, and could also help to develop miRNA-based therapeutic strategies for HCC.

Diagnosis of triple negative breast cancer based on radiomics signatures extracted from preoperative contrast-enhanced chest computed tomography

Background

To explore the diagnostic value of radiomics features of preoperative computed tomography (CT) for triple negative breast cancer (TNBC) for better treatment of patients with breast cancer.

Methods

A total of 890 patients with breast cancer admitted to our hospital from June 2016 to January 2018 were analyzed. They were diagnosed by surgery and pathology to have mass and invasive breast cancer and had contrast-enhanced chest CT examination before operation. 300 patients were randomly selected for the study, including 100 TNBC and 200 non-TNBC (NTNBC) patients. Among them 180 were used in discovery group and 120 were used in validation group. The molecular subtypes of breast cancer in the patients were determined immunohistochemistrially. Radiomics features were extracted from three dimensional CT-images. The LASSO logistic method was used to select image features and calculate radiomics scores. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic value of radiomics scores for TNBC.

Results

Five image features were found to be related to TNBC subtype (P < 0.001). These image features based-radiomic signatures had good predictive values for TNBC with the areas under ROC curve (AUC) of 0.881 (95% CI: 0.781–0.921) in the discovery group and 0.851 (95% CI: 0.761–0.961) in the validation group, respectively. The sensitivities and specificities were 0.767, and 0.873 in the discovery group and 0.785 and 0.915 in the validation group.

Conclusions

Radiomic signature based on preoperative CT is capable of distinguishing patients with TNBC and NTNBC. It adds additional value for conventional chest contrast-enhanced CT and helps plan the strategy for clinical treatment of the patients.

Label-free characterization of different kinds of cells using optoelectrokinetic-based microfluidics

We report a novel, to the best of our knowledge, method to rapidly characterize different kinds of cells and drug-treated cancer cells using a label-free biomarker of self-rotation in an optoelectrokinetics (OEK)-based microfluidic platform. OEK incorporates optics and electrokinetics into microfluidics, thereby offering a contact-free, label-free, and rapid approach to the cellular manipulation community. Self-rotational behaviors of four different kinds of cells were experimentally investigated by the frequency-sweeping of an AC bias potential in an optically induced nonuniform and irrotational electric field. The results revealed that these kinds of cells displayed a Gaussian distribution versus the AC frequency as well as different self-rotational speeds under the same conditions. Furthermore, the peak self-rotational speed varied from one kind of cell to another, with that of cancer cells higher than that of normal cells. In addition, MCF-7 cells treated by various concentrations of drug showed remarkably different self-rotational speeds. This finding suggests a high potential of developing a new label-free biomarker to rapidly distinguish different kinds of cancer cells and quantitatively monitor the response of cancer patients to various treatments.

MiR-144: A New Possible Therapeutic Target and Diagnostic/Prognostic Tool in Cancers

MicroRNAs (miRNAs) are small and non-coding RNAs that display aberrant expression in the tissue and plasma of cancer patients when tested in comparison to healthy individuals. In past decades, research data proposed that miRNAs could be diagnostic and prognostic biomarkers in cancer patients. It has been confirmed that miRNAs can act either as oncogenes by silencing tumor inhibitors or as tumor suppressors by targeting oncoproteins. MiR-144s are located in the chromosomal region 17q11.2, which is subject to significant damage in many types of cancers. In this review, we assess the involvement of miR-144s in several cancer types by illustrating the possible target genes that are related to each cancer, and we also briefly describe the clinical applications of miR-144s as a diagnostic and prognostic tool in cancers.

Triple negative breast cancer: A thorough review of biomarkers

Triple-negative breast cancer (TNBC) is defined as a type of breast cancer with lack of expression of estrogen receptor (ER), progesterone receptor (PR) and HER2 protein. The tumorigenesis is not likely to be driven by hormonal or HER2 pathway. In comparison to other types of breast cancer, TNBC stands out for its aggressive behavior, more prone to early recurrence. Historically, TNBC has been considered a disease with poor response to molecular target therapy, requiring better validation of biomarkers. Recent issues related to tumor heterogeneity have been widely discussed suggesting the subdivision of TNBC into different molecular subtypes. Through a complete research on the main published trials databases and platforms of ongoing clinical studies, the current manuscript was carried out in order to present a critical view of the role of immunohistochemical and molecular biomarkers for the prognosis and response prediction of TNBC to traditional therapy and new molecular target agents.

Nanotechnological based miRNA intervention in the therapeutic management of neuroblastoma

Neuroblastoma (NB) is a widely diagnosed cancer in children, characterized by amplification of the gene encoding the MYCN transcription factor, which is highly predictive of poor clinical outcome and metastatic disease. microRNAs (a class of small non-coding RNAs) are regulated by MYCN transcription factor in neuroblastoma cells. The current research is focussed on identifying differential role of miRNAs and their interactions with signalling proteins, which are intricately linked with cellular processes like apoptosis, proliferation or metastasis. However, the therapeutic success of miRNAs is limited by pharmaco-technical issues which are well counteracted by nanotechnological advancements. The nanoformulated miRNAs unload anti-cancer drugs in a controlled and prespecified manner at target sites, to influence the activity of target protein in amelioration of NB. Recent advances and developments in the field of miRNAs-based systems for clinical management of NBs and the role of nanotechnology to overcome challenges with drug delivery of miRNAs have been reviewed in this paper.

MicroRNA expression studies: challenge of selecting reliable reference controls for data normalization

Accurate determination of microRNA expression levels is a prerequisite in using these small non-coding RNA molecules as novel biomarkers in disease diagnosis and prognosis. Quantitative PCR is the method of choice for measuring the expression levels of microRNAs. However, a major obstacle that affects the reliability of results is the lack of validated reference controls for data normalization. Various non-coding RNAs have previously been used as reference controls, but their use may lead to variations and lack of comparability of microRNA data among the studies. Despite the growing number of studies investigating microRNA profiles to discriminate between healthy and disease stages, robust reference controls for data normalization have so far not been established. In the present article, we provide an overview of different reference controls used in various diseases, and highlight the urgent need for the identification of suitable reference controls to produce reliable data. Our analysis shows, among others, that RNU6 is not an ideal normalizer in studies using patient material from different diseases. Finally, our article tries to disclose the challenges to find a reference control which is uniformly and stably expressed across all body tissues, fluids, and diseases.

How close are miRNAs from clinical practice? A perspective on the diagnostic and therapeutic market

The discovery of miRNAs in the mid-90s has changed the dogma of gene expression regulation. Currently, miRNAs are the main theme of thousands of publications each year and their involvement in human diseases is everyday more deeply understood. With that being known, what are the actual clinical applications of miRNAs and how far are they truly from the patients? To address this question, we reviewed the miRNA diagnostic and therapeutic market. With many companies developing miRNA panels, the activity is high in the diagnostic area. Some products, notably for thyroid cancer (Interpace Diagnostic), are already available to clinician and covered by major insurance companies. In comparison, the therapeutic market, mainly driven by miRNA mimics and antagomiR products, is less advanced. Miravirsen (produced by Roche/Santaris) and RG-101 (produced by Regulus Therapeutics), designed to treat hepatitis C, are considered the flagship products of this class of future drugs. All of the miRNA-based drugs are currently in clinical trials and none have yet reached the pharmaceutical breakthrough. However, acquisition of miRNA-based companies by major pharmas is sending a positive feedback on their potentials. With multiple initiatives on their way, the next years will definitely be determinant for the miRNA market that is still in his infancy.

Spring is in the air: seasonal profiles indicate vernal change of miRNA activity

The envisioned application of miRNAs as diagnostic or prognostic biomarkers calls for an in-depth understanding of their distribution and variability in different physiological states. While effects with respect to ethnic origin, age, or gender are known, the inter-individual variability of miRNAs across the four seasons remained largely hidden. We sequentially profiled the complete repertoire of blood-borne miRNAs for 25 physiologically normal individuals in spring, summer, fall, and winter (altogether 95 samples) and validated the results on 292 individuals (919 samples collected with the Mitra home sampling device) by RT-qPCR. Principal variance component analysis suggests that the largest variability observed in miRNA expression is due to individual variability and the individuals' gender. But the results also highlight a deviation of miRNA activity in samples collected during spring time. Following adjustment for multiple testing, remarkable differences are observed between spring and fall (77 miRNAs). The two most dys-regulated miRNAs were miR-181c-5p and miR-106b-5p (adjusted p-value of 0.007). Other significant miRNAs include miR-140-3p, miR-21-3p, and let-7c-5p. The dys-regulation was validated by RT-qPCR. Systems biology analysis further provides strong evidence for the immunological origin of the signals: dys-regulated miRNAs are enriched in CD56 cells and belong to various signalling and immune-system-related pathways. Our data suggest that besides known confounding factors such as age and sex, also the season in which a test is conducted might have a considerable influence on the expression of blood-borne miRNAs and subsequently might interfere with diagnosis based on such signatures.

Gene Expression and miRNAs Profiling: Function and Regulation in Human Epidermal Growth Factor Receptor 2 (HER2)-Positive Breast Cancer

Breast cancer is the second most common cause of cancer-related deaths among women worldwide. It is a heterogeneous disease with four major molecular subtypes. One of the subtypes, human epidermal growth factor receptor 2 (HER2)-enriched (HER2-positive) is characterized by the absence of estrogen and progesterone receptors and overexpression of HER2 receptor, and accounts for 15–20% of all breast cancers. Despite the anti-HER2 and cytotoxic chemotherapy, HER2 subtype is an aggressive disease with significant mortality. Recent advances in molecular biology techniques, including gene expression profiling, proteomics, and microRNA analysis, have been extensively used to explore the underlying mechanisms behind human breast carcinogenesis and metastasis including HER2-positive breast cancer, paving the way for developing new targeted therapies. This review focuses on recent advances on gene expression and miRNA status in HER2-positive breast cancer.

Usefulness of serum microRNA as a predictive marker of recurrence and prognosis in biliary tract cancer after radical surgery

Biliary tract cancer (BTC) is an aggressive type of malignant tumour. Even after radical resection, the risk of recurrence is still high, resulting in a poor prognosis. Here, we investigated the usefulness of serum miRNAs as predictive markers of recurrence and prognosis for patients with BTC after radical surgery using 66 serum samples that were collected at three time points from 22 patients with BTC who underwent radical surgery. Using microarray analysis, we successfully identified six specific miRNAs (miR-1225-3p, miR-1234-3p, miR1260b, miR-1470, miR-6834-3p, and miR-6875-5p) associated with recurrence and prognosis of BTC after radical surgery. In addition, using a combination of these miRNAs, we developed a recurrence predictive index to predict recurrence in patients with BTC after operation with high accuracy. Patients having higher index scores (≥ cut-off) had significantly worse recurrence-free survival (RFS) and overall survival (OS) than those with lower index scores (<cut-off). Furthermore, the index was an independent factor related to RFS and OS by univariate and multivariate analyses using a Cox hazard proportional model. Overall, our results provided compelling evidence for the potential usefulness of specific serum miRNAs as effective predictive tools for recurrence and prognosis in patients with BTC who underwent radical surgery.

Inferring microRNA-disease association by hybrid recommendation algorithm and unbalanced bi-random walk on heterogeneous network

More and more research works have indicated that microRNAs (miRNAs) play indispensable roles in exploring the pathogenesis of diseases. Detecting miRNA-disease associations by experimental techniques in biology is expensive and time-consuming. Hence, it is important to propose reliable and accurate computational methods to exploring potential miRNAs related diseases. In our work, we develop a novel method (BRWHNHA) to uncover potential miRNAs associated with diseases based on hybrid recommendation algorithm and unbalanced bi-random walk. We first integrate the Gaussian interaction profile kernel similarity into the miRNA functional similarity network and the disease semantic similarity network. Then we calculate the transition probability matrix of bipartite network by using hybrid recommendation algorithm. Finally, we adopt unbalanced bi-random walk on the heterogeneous network to infer undiscovered miRNA-disease relationships. We tested BRWHNHA on 22 diseases based on five-fold cross-validation and achieves reliable performance with average AUC of 0.857, which an area under the ROC curve ranging from 0.807 to 0.924. As a result, BRWHNHA significantly improves the performance of inferring potential miRNA-disease association compared with previous methods. Moreover, the case studies on lung neoplasms and prostate neoplasms also illustrate that BRWHNHA is superior to previous prediction methods and is more advantageous in exploring potential miRNAs related diseases. All source codes can be downloaded from https://github.com/myl446/BRWHNHA.

Roles of MicroRNA-34a in Epithelial to Mesenchymal Transition, Competing Endogenous RNA Sponging and Its Therapeutic Potential

MicroRNA-34a (miR-34a), a tumor suppressor, has been reported to be dysregulated in various human cancers. MiR-34a is involves in certain epithelial-mesenchymal transition (EMT)-associated signal pathways to repress tumorigenesis, cancer progression, and metastasis. Due to the particularity of miR-34 family in tumor-associated EMT, the significance of miR-34a is being increasingly recognized. Competing endogenous RNA (ceRNA) is a novel concept involving mRNA, circular RNA, pseudogene transcript, and long noncoding RNA regulating each other’s expressions using microRNA response elements to compete for the binding of microRNAs. Studies showed that miR-34a is efficient for cancer therapy. Here, we provide an overview of the function of miR-34a in tumor-associated EMT. ceRNA hypothesis plays an important role in miR-34a regulation in EMT, cancer progression, and metastasis. Its potential roles and challenges as a microRNA therapeutic candidate are discussed. As the negative effect on cancer progression, miR-34a should play crucial roles in clinical diagnosis and cancer therapy.

Identifying a miRNA signature for predicting the stage of breast cancer

Breast cancer is a heterogeneous disease and one of the most common cancers among women. Recently, microRNAs (miRNAs) have been used as biomarkers due to their effective role in cancer diagnosis. This study proposes a support vector machine (SVM)-based classifier SVM-BRC to categorize patients with breast cancer into early and advanced stages. SVM-BRC uses an optimal feature selection method, inheritable bi-objective combinatorial genetic algorithm, to identify a miRNA signature which is a small set of informative miRNAs while maximizing prediction accuracy. MiRNA expression profiles of a 386-patient cohort of breast cancer were retrieved from The Cancer Genome Atlas. SVM-BRC identified 34 of 503 miRNAs as a signature and achieved a 10-fold cross-validation mean accuracy, sensitivity, specificity, and Matthews correlation coefficient of 80.38%, 0.79, 0.81, and 0.60, respectively. Functional enrichment of the 10 highest ranked miRNAs was analysed in terms of Kyoto Encyclopedia of Genes and Genomes and Gene Ontology annotations. Kaplan-Meier survival analysis of the highest ranked miRNAs revealed that four miRNAs, hsa-miR-503, hsa-miR-1307, hsa-miR-212 and hsa-miR-592, were significantly associated with the prognosis of patients with breast cancer.