Comprehensive Analysis of lncRNA and miRNA Regulatory Network Reveals Potential Prognostic Non-coding RNA Involved in Breast Cancer Progression

Regulatory and therapeutic implications of competing endogenous RNA network in breast cancer progression and metastasis: A review

Breast cancer (BC) is a global health concern, and development of diagnostic tools and targeted treatments for BC remains challenging. Therapeutic approaches for BC often involve a combination of surgery, radiation therapy, chemotherapy, targeted therapy, and hormone therapy. In recent years, there has been a growing interest in the role of noncoding RNAs (ncRNAs), including long ncRNAs (lncRNAs) and microRNAs (miRNAs), in BC and their therapeutic implications. Various biological processes such as cell proliferation, migration, and apoptosis rely on the activities of these ncRNAs, and their dysregulation has been implicated in BC progression. The regulatory function of the competitive endogenous RNA (ceRNA) network, which comprises lncRNAs, miRNAs, and mRNAs, has been the subject of extensive pathophysiological research. Most lncRNAs serve as molecular sponges for miRNAs and sequester their activities, thereby regulating the expression of target mRNAs and contributing to the promotion or inhibition of BC progression. This review summarizes recent findings on the role of ceRNA networks in BC progression, metastasis, and therapeutic resistance, and highlights the association of ceRNA networks with transcription factors and signaling pathways. Understanding the ceRNA network can lead to the discovery of biomarkers and targeted treatment methods to prevent the spread and metastasis of BC.

Transcriptional Profiling of SARS-CoV-2-Infected Calu-3 Cells Reveals Immune-Related Signaling Pathways

The COVID-19 disease, caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), emerged in late 2019 and rapidly spread worldwide, becoming a pandemic that infected millions of people and caused significant deaths. COVID-19 continues to be a major threat, and there is a need to deepen our understanding of the virus and its mechanisms of infection. To study the cellular responses to SARS-CoV-2 infection, we performed an RNA sequencing of infected vs. uninfected Calu-3 cells. Total RNA was extracted from infected (0.5 MOI) and control Calu-3 cells and converted to cDNA. Sequencing was performed, and the obtained reads were quality-analyzed and pre-processed. Differential expression was assessed with the EdgeR package, and functional enrichment was performed in EnrichR for Gene Ontology, KEGG pathways, and WikiPathways. A total of 1040 differentially expressed genes were found in infected vs. uninfected Calu-3 cells, of which 695 were up-regulated and 345 were down-regulated. Functional enrichment analyses revealed the predominant up-regulation of genes related to innate immune response, response to virus, inflammation, cell proliferation, and apoptosis. These transcriptional changes following SARS-CoV-2 infection may reflect a cellular response to the infection and help to elucidate COVID-19 pathogenesis, in addition to revealing potential biomarkers and drug targets.

Integrative analysis of multi-omics data reveals a pseudouridine-related lncRNA signature for prediction of glioma prognosis and chemoradiotherapy sensitivity

BACKGROUND

Glioblastoma is the most common type of glioma with a high incidence and poor prognosis, and effective medical treatment remains challenging. Pseudouridine (Ψ) is the first post-transcriptional modification discovered and one of the most abundant modifications to RNA. However, the prognostic value of Ψ-related lncRNAs (ΨrLs) for glioma patients has never been systematically evaluated. This study aims to construct a risk model based on ΨrLs signature and to validate the predictive efficiency of the model.

METHOD

Transcriptomic data, genomic data, and relevant clinical data of glioma patients were extracted from the Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA). ΨrLs with significant correlation with Ψ-related genes were identified, and univariate Cox regression, least absolute shrinkage and selection operator (LASSO) regression, and multivariate Cox regression were used to further select biomarkers and construct a ΨrLs signature risk model. Then, the expression of lncRNAs of ΨrLs signature in multiple glioma cell lines was detected by qPCR. Further, ROC analysis, stratification analysis, correlation analysis, survival analysis, nomogram, enrichment analysis, immune infiltration analysis, chemoradiotherapy sensitivity analysis, somatic mutation, and recurrent copy number variation (CNV) analysis were used to validate the predictive efficiency of ΨrLs signature in TCGA and CGGA datasets.

RESULTS

A four-lncRNA ΨrLs signature (DNAJC27-AS1, GDNF-AS1, ZBTB20-AS4, and DNMBP-AS1) risk model was constructed. By ROC analysis, stratified analysis, correlation analysis, survival analysis, and nomogram, the signature showed satisfactory predictive efficiency. Functional enrichment analysis revealed the differences in immune-related biological processes between high- and low-risk groups. Immune infiltration analysis showed that the high-risk group had lower tumor purity and higher stromal, immune and ESTIMATE scores. Mitoxantrone was identified as effective drug for low-risk group of glioma patients. Key genes in glioma development, including IDH1, EGFR, PTEN, etc., were differentially mutated between risk groups. The main recurrent CNVs in low-risk groups were 19q13.42 deletion and 7q34 amplification; 10q23.31 deletion and 12q14.1 in the high-risk group.

CONCLUSIONS

Our study identified a four-lncRNA ΨrLs signature that effectively predicts the prognosis of glioma patients and may serve as a diagnostic tool. Risk scores of glioma patients generated by the signature is associated with immune-related biological processes and chemoradiotherapy sensitivity. These findings may inform the development of more targeted and effective therapies for glioma patients.

A novel Cuproptosis-related LncRNA signature to predict prognosis in hepatocellular carcinoma

Increased intracellular toxicity due to an imbalance in copper homeostasis caused by copper ion accumulation could regulate the rate of cancer cell growth and proliferation. The goal of this study was to create a novel Cuproptosis-related lncRNA signature that may be utilized to predict survival and immunotherapy in HCC patients. Cuproptosis-associated lncRNAs and differentially expressed lncRNAs between HCC tumor tissue and normal tissue were discovered first. By LASSO-Cox analysis, the overlapping lncRNAs were then utilized to build a Cuproptosis-associated lncRNA signature, which might be used to predict patient prognosis and responsiveness to immune checkpoint blockade (ICB) therapy. Differences in the infiltration of immune cell subpopulations between high and low-risk score subgroups were also analyzed. Moreover, a nomogram based on the Cuproptosis-associated lncRNA signature and clinical features was developed and demonstrated to have good predictive potential. Finally, qRT-PCR was performed in HerpG2 and MHCC-97H cell lines to explore whether these lncRNAs were indeed involved in the process of Cuproptosis. In summary, we created a prognostic lncRNA profile linked to Cuproptosis to forecast response to immunotherapy, which may provide a new potential non-apoptotic therapeutic perspective for HCC patients.

An innovative systematic approach introduced the involved lncRNA-miR-mRNA network in cell cycle and proliferation after conventional treatments in breast cancer patients

INTRODUCTION

The present study aimed to explore the involved lncRNA-miRNA-mRNA network in the cell cycle and proliferation after conventional treatments in Luminal A breast cancer patients.

METHODS

The candidate miRNAs (miRs), lncRNAs, and mRNAs were first taken from the Gene Expression Omnibus and TCGA databases. The lncRNA-miR-mRNA network was then constructed using the high-throughput sequencing data. The expression levels of selected targets were measured in the breast cancer and healthy samples by the Real-Time PCR technique and compared with the clinical outcomes by the Kaplan-Meier method.

RESULTS

Our analysis revealed a group of differentially expressed 3 lncRNAs, 9 miRs, and 14 mRNAs in breast cancer patients. A significant expression decrease of the selected tumor suppressor lncRNAs, miRs, and genes and a substantial expression increase of the selected onco-lncRNAs, oncomiRs, and oncogenes were obtained in the patients compared to the healthy group. The plasma levels of the lncRNAs, miRs, and mRNAs were more significant after the operation, chemotherapy, and radiotherapy than the pre-treatment. The Kaplan-Meier analysis indicated that the patients with a high expression of miR-21, miR-20b, IGF1R, and E2F2 and a low expression of miR-125a, PDCD4, and PTEN had exhibited a shorter overall survival rate.

CONCLUSION

Our results suggested that the underlying mechanisms of the lncRNA, miRs, and mRNAs and relevant signaling pathways may be considered predictive and therapeutic targets for breast cancer.

The double agents in liquid biopsy: promoter and informant biomarkers of early metastases in breast cancer

Breast cancer continues to be a major global problem with significant mortality associated with advanced stage and metastases at clinical presentation. However, several findings suggest that metastasis is indeed an early occurrence. The standard diagnostic techniques such as invasive core needle biopsy, serological protein marker assays, and non-invasive radiological imaging do not provide information about the presence and molecular profile of small fractions of early metastatic tumor cells which are prematurely dispersed in the circulatory system. These circulating tumor cells (CTCs) diverge from the primary tumors as clusters with a defined secretome comprised of circulating cell-free nucleic acids and small microRNAs (miRNAs). These circulatory biomarkers provide a blueprint of the mutational profile of the tumor burden and tumor associated alterations in the molecular signaling pathways involved in oncogenesis. Amidst the multitude of circulatory biomarkers, miRNAs serve as relatively stable and precise biomarkers in the blood for the early detection of CTCs, and promote step-wise disease progression by executing paracrine signaling that transforms the microenvironment to guide the metastatic CTCs to anchor at a conducive new organ. Random sampling of easily accessible patient blood or its serum/plasma derivatives and other bodily fluids collectively known as liquid biopsy (LB), forms an efficient alternative to tissue biopsies. In this review, we discuss in detail the divergence of early metastases as CTCs and the involvement of miRNAs as detectable blood-based diagnostic biomarkers that warrant a timely screening of cancer, serial monitoring of therapeutic response, and the dynamic molecular adaptations induced by miRNAs on CTCs in guiding primary and second-line systemic therapy.