LncmiRHG-MIR100HG: A new budding star in cancer

LncRNA MIR100HG Promotes Cell Proliferation in Nasopharyngeal Carcinoma by Targeting miR-136-5p/IL-6 Axis

Nasopharyngeal carcinoma (NPC) features high mortality and poor prognosis. Additionally, long non-coding RNAs (lncRNAs) play a significant role in developing NPC and other types of cancer. But the functional mechanism of MIR100HG in NPC remains unclear. The long non-coding RNA MIR100HG messenger RNA (mRNA) expression was thoroughly evaluated in NPC tumors and adjacent tissues using quantitative polymerase chain reaction (qPCR). Furthermore, we employed Kaplan-Meier analysis to compare the expression of MIR100HG with survival outcomes. The CCK8 test was utilized to investigate the impact of the lncRNA MIR100HG/miR-136-5p/IL-6 axis on cell proliferation in NPC. The study's findings indicated overexpression of the lncRNA MIR100HG in both NPC tumors and cell lines. This upregulation was associated with a poorer outcome in individuals with NPC. When lncRNA MIR100HG was knocked down in vitro, NPC cell proliferation was inhibited, resulting in tumor suppression. In certain oncogenic capacities, the lncRNA MIR100HG functions as a competitive endogenous RNA for miR-136-5p, hence impeding the inhibitory effect of miR-136-5p on its target gene, IL-6. In summary, the findings of the present investigation suggested that lncRNA MIR100HG exhibits promising characteristics as a potential indicator for the prognosis and diagnosis of NPC.

LncRNA MIR100HG affects the proliferation and metastasis of lung cancer cells through mediating the microRNA-5590-3p/DCBLD2 axis

OBJECTIVE

The aim of this paper is to investigate the effect of long noncoding RNA (lncRNA) MIR100HG on the proliferation and metastasis of lung cancer cells by mediating the microRNA (miR)-5590-3p/DCBLD2 axis.

METHODS

RNA levels of MIR100HG, miR-5590-3p, and DCBLD2 in lung cancer tissues and cells were detected by quantitative reverse-transcription polymerase chain reaction, and protein level was assessed by Western blot. Effects of MIR100HG or miR-5590-3p on proliferation, migration, and invasion of lung cancer cells were detected by Cell Counting Kit-8, colony formation, and Transwell assays. Luciferase reporter assay and RNA-immunoprecipitation assay confirmed the target relationship between miR-5590-3p and MIR100HG or DCBLD2.

RESULTS

MIR100HG and DCBLD2 were highly expressed, while miR-5590-3p was lowly expressed in lung cancer tissues and cells. Silencing MIR100HG or upregulating miR-5590-3p impeded lung cancer cell proliferation, migration, and invasion. MIR100HG could up-regulate DCBLD2 by sponging miR-5590-3p. Downregulation of miR-5590-3p partly overturned the suppressive effect of silencing MIR100HG on lung cancer cell proliferation and metastasis, and overexpression of DCBLD2 also reversed the effect of overexpression of miR-5590-3p on lung cancer cell proliferation and metastasis.

CONCLUSION

LncRNA MIR100HG promotes lung cancer progression by targeting and negatively regulating DCBLD2 through binding with miR-5590-3p.

Co-Expression Network Analysis Unveiled lncRNA-mRNA Links Correlated to Epidermal Growth Factor Receptor-Tyrosine Kinase Inhibitor Resistance and/or Intermediate Epithelial-to-Mesenchymal Transition Phenotypes in a Human Non-Small Cell Lung Cancer Cellular Model System

We investigated mRNA-lncRNA co-expression patterns in a cellular model system of non-small cell lung cancer (NSCLC) sensitive and resistant to the epithelial growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) erlotinib/gefitinib. The aim of this study was to unveil insights into the complex mechanisms of NSCLC targeted therapy resistance and epithelial-to-mesenchymal transition (EMT). Genome-wide RNA expression was quantified for weighted gene co-expression network analysis (WGCNA) to correlate the expression levels of mRNAs and lncRNAs. Functional enrichment analysis and identification of lncRNAs were conducted on modules associated with the EGFR-TKI response and/or intermediate EMT phenotypes. We constructed lncRNA-mRNA co-expression networks and identified key modules and their enriched biological functions. Processes enriched in the selected modules included RHO (A, B, C) GTPase and regulatory signaling pathways, apoptosis, inflammatory and interleukin signaling pathways, cell adhesion, cell migration, cell and extracellular matrix organization, metabolism, and lipid metabolism. Interestingly, several lncRNAs, already shown to be dysregulated in cancer, are connected to a small number of mRNAs, and several lncRNAs are interlinked with each other in the co-expression network.

The Role of the Dysregulation of Long Non-Coding and Circular RNA Expression in Medulloblastoma: A Systematic Review

Medulloblastoma (MB) is the most common malignant brain tumor in childhood. Although recent multi-omic studies have led to advances in MB classification, there is still room for improvement with regard to treatment response and survival. Therefore, identification of new and less invasive biomarkers is needed to refine the diagnostic process and to develop more personalized treatment strategies. In this context, non-coding RNAs (ncRNAs) could be useful biomarkers for MB. In this article, we reviewed the role of two types of ncRNAs, long non-coding (lncRNAs) and circular RNAs (circRNAs), as biomarkers for the diagnosis, subgroup classification, and prognosis of MB. We also reviewed potential candidates with specific functions and mechanisms of action in the disease. We performed a search in PubMed and Scopus using the terms ("long non coding RNAs" OR "lncRNAs") and ("circular RNAs" OR "circRNAs") AND "medulloblastoma" to identify biomarker discovery or functional studies evaluating the effects of these ncRNAs in MB. A total of 26 articles met the inclusion criteria. Among the lncRNAs, the tumorigenic effects of the upregulated lnc-IRX3-80 and lnc-LRRC47-78 were the most studied in MB. Among the circRNAs, the upregulation of circSKA3 and its functional impact in MB cell lines were the most consistent results, so this circRNA could be considered a potential biomarker in MB. Additional validation is required for many deregulated lncRNAs and circRNAs; therefore, further studies are warranted.

Exploiting Long Non-Coding RNAs and Circular RNAs as Pharmacological Targets in Triple-Negative Breast Cancer Treatment

Breast cancer is one of the most frequent causes of cancer death among women worldwide. In particular, triple-negative breast cancer (TNBC) represents the most aggressive breast cancer subtype because it is characterized by the absence of molecular targets, thus making it an orphan type of malignancy. The discovery of new molecular druggable targets is mandatory to improve treatment success. In that context, non-coding RNAs represent an opportunity for modulation of cancer. They are RNA molecules with apparently no protein coding potential, which have been already demonstrated to play pivotal roles within cells, being involved in different processes, such as proliferation, cell cycle regulation, apoptosis, migration, and diseases, including cancer. Accordingly, they could be used as targets for future TNBC personalized therapy. Moreover, the peculiar characteristics of non-coding RNAs make them reliable biomarkers to monitor cancer treatment, thus, to monitor recurrence or chemoresistance, which are the most challenging aspects in TNBC. In the present review, we focused on the oncogenic or oncosuppressor role of long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs) mostly involved in TNBC, highlighting their mode of action and depicting their potential role as a biomarker and/or as targets of new non-coding RNA-based therapeutics.

Anoikis-related long non-coding RNA signatures to predict prognosis and small molecular drug response in cervical cancer

Background: Cervical cancer (CC) is a major health threat to females, and distal metastasis is common in patients with advanced CC. Anoikis is necessary for the development of distal metastases. Understanding the mechanisms associated with anoikis in CC is essential to improve its survival rate. Methods: The expression matrix of long non-coding RNAs (lncRNAs) from cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) patients was extracted from The Cancer Genome Atlas (TCGA), and highly relevant anoikis-related lncRNAs (ARLs) were identified by the single sample gene set enrichment analysis (ssGSEA) method. ARLs-related molecular subtypes were discerned based on prognosis-related ARLs. ARLs-related prognostic risk score (APR_Score) was calculated and risk model was constructed using LASSO COX and COX models. In addition, we also assessed immune cell activity in the immune microenvironment (TME) for both subtypes and APR_Score groups. A nomogram was utilized for predicting improved clinical outcome. Finally, this study also discussed the potential of ARLs-related signatures in predicting response to immunotherapy and small molecular drugs. Results: Three ARLs-related subtypes were identified from TCGA-CESC (AC1, AC2, and AC3), with AC3 patients having the highest ARG scores, higher angiogenesis scores, and the worst prognosis. AC3 had lower immune cell scores in TME but higher immune checkpoint gene expression and higher potential for immune escape. Next, we constructed a prognostic risk model consisting of 7-ARLs. The APR_Score exhibited a greater robustness as an independent prognostic indicator in predicting prognosis, and the nomogram was a valuable tool for survival prediction. ARLs-related signatures emerged as a potential novel indicator for immunotherapy and small molecular drug selection. Conclusion: We firstly constructed novel ARLs-related signatures capable of predicting prognosis and offered novel ideas for therapy response in CC patients.

Recent Clinical Advances on Long Non-Coding RNAs in Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) is a more aggressive type of breast cancer due to its heterogeneity and complex molecular mechanisms. TNBC has a high risk for metastasis, and it is difficult to manage clinical conditions of the patients. Various investigations are being conducted to overcome these challenges using RNA, DNA, and proteins for early diagnosis and treatment. Recently, long non-coding RNAs (lncRNAs) have emerged as a novel target to treat the multistep process of TNBC. LncRNAs regulate epigenetic expression levels, cell proliferation and apoptosis, and tumour invasiveness and metastasis. Thus, lncRNA-based early diagnosis and treatment options could be helpful, especially for patients with severe TNBC. lncRNAs are expressed in a highly specific manner in cells and tissues and are involved in TNBC progression and development. lncRNAs could be used as sensitive and specific targets for diagnosis, treatment, and monitoring of patients with TNBC. Therefore, the exploration of novel diagnostic and prognostic biomarkers is of extreme importance. Here, we discuss the molecular advances on lncRNA regulation of TNBC and lncRNA-based early diagnosis, treatment, and drug resistance.

A cuproptosis-related LncRNA signature: Integrated analysis associated with biochemical recurrence and immune landscape in prostate cancer

Background: As a new form of regulated cell death, cuproptosis differs profoundly from apoptosis, ferroptosis, pyroptosis, and necroptosis. The correlation between cuproptosis and long non-coding RNAs (lncRNAs) has been increasingly studied recently. In this study, a novel cuproptosis-related lncRNA prognostic signature was developed to investigate biochemical recurrence (BCR) and tumor immune landscape in prostate cancer (PCa). Methods and Materials: The transcriptome data and clinicopathologic information of PCa patients were downloaded from The Cancer Genome Atlas (TCGA). Pearson's correlation analysis was applied to identify lncRNAs associated with cuproptosis. Based on Cox regression analysis and the least absolute shrinkage and selection operator (LASSO) regression analysis, we developed a cuproptosis-related lncRNA prognostic model (risk score) to predict the BCR of PCa patients. Additionally, we also constructed a nomogram with the risk score and clinicopathologic features. The biological function, tumor mutation burden (TMB), immune cell infiltration, expression levels of immune checkpoint genes, and anti-cancer drug sensitivity were investigated. Results: We constructed and validated the cuproptosis-related lncRNA signature prognostic model (risk score) by six crlncRNAs. All patients were divided into the low- and high-risk groups based on the median risk score. The Kaplan-Meier (KM) survival analysis revealed that the high-risk group had shorter BCR-free survival (BCRFS). The risk score has been proven to be an independent prognostic factor of BCR in PCa patients. In addition, a nomogram of risk scores and clinicopathologic features was established and demonstrated an excellent predictive capability of BCR. The ROC curves further validated that this nomogram had higher accuracy of predicting the BCR compared to other clinicopathologic features. We also found that the high-risk group had higher TMB levels and more infiltrated immune cells. Furthermore, patients with high TMB in the high-risk group were inclined to have the shortest BCRFS. Finally, patients in the high-risk group were more susceptible to docetaxel, gefitinib, methotrexate, paclitaxel, and vinblastine. Conclusion: The novel crlncRNA signature prognostic model shows a greatly prognostic prediction value of BCR for PCa patients, extends our thought on the association of cuproptosis and PCa, and provides novel insights into individual-based treatment strategies for PCa.