Development of the expression and prognostic significance of m 5 C ‐related LncRNAs in breast cancer

Identifying SLC2A6 as the novel protective factor in breast cancer by TP53-related genes affecting M1 macrophage infiltration

The high heterogeneity of breast cancer (BC) caused by pathogenic gene mutations poses a challenge to immunotherapy, but the underlying mechanism remains unknown. The difference in the infiltration of M1 macrophages induced by TP53 mutations has a significant impact on BC immunotherapy. The aim of this study was to develop a TP53-related M1 macrophage infiltration molecular typing risk signature in BC and evaluate the biological functions of the key gene to find new immunotherapy biomarkers. Weighted correlation network analysis (WGCNA) and negative matrix factorization (NMF) were used for distinguishing BC subtypes. The signature and the nomogram were both constructed and evaluated. Biological functions of the novel signature gene SLC2A6 were confirmed through in vitro and in vivo experiments. RNA-Sequencing and protein profiling were used for detecting the possible mechanism of SLC2A6. The results suggested that four BC subtypes were distinguished by TP53-related genes that affect M1 macrophage infiltration. The signature constructed by molecular typing characteristics could evaluate BC's clinical features and tumor microenvironment. The nomogram could accurately predict the prognosis. The signature gene SLC2A6 was found to have an abnormally low expression in tumor tissues. Overexpression of SLC2A6 could inhibit proliferation, promote mitochondrial damage, and result in apoptosis of tumor cells. The HSP70 family member protein HSPA6 could bind with SLC2A6 and increase with the increased expression of SLC2A6. In summary, the risk signature provides a reference for BC risk assessment, and the signature gene SLC2A6 could act as a tumor suppressor in BC.

Epitranscriptomic orchestrations: Unveiling the regulatory paradigm of m6A, A-to-I editing, and m5C in breast cancer via long noncoding RNAs and microRNAs

Breast cancer (BC) poses a persistent global health challenge, particularly in countries with elevated human development indices linked to factors such as increased life expectancy, education, and wealth. Despite therapeutic progress, challenges persist, and the role of epitranscriptomic RNA modifications in BC remains inadequately understood. The epitranscriptome, comprising diverse posttranscriptional modifications on RNA molecules, holds the potential to intricately modulate RNA function and regulation, implicating dysregulation in various diseases, including BC. Noncoding RNAs (ncRNAs), acting as posttranscriptional regulators, influence physiological and pathological processes, including cancer. RNA modifications in long noncoding RNAs (lncRNAs) and microRNAs (miRNAs) add an extra layer to gene expression control. This review delves into recent insights into epitranscriptomic RNA modifications, such as N-6-methyladenosine (m6A), adenine-to-inosine (A-to-I) editing, and 5-methylcytosine (m5C), specifically in the context of lncRNA and miRNAs in BC, highlighting their potential implications in BC development and progression. Understanding this intricate regulatory landscape is vital for deciphering the molecular mechanisms underlying BC and identifying potential therapeutic targets.

Disulfidptosis-related lncRNA signatures assess immune microenvironment and drug sensitivity in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is associated with a high mortality rate, where resistance to immunotherapy and chemotherapy plays a crucial role. A newly identified form of cell death called disulfidptosis shows promise, but its biological mechanism in HCC remains uncertain. In this study, a prognostic model was developed for Disulfidptosis-related long non-coding RNAs (DRLs) from 370 HCC patients sourced from TCGA-LIHC, utilizing five key features: AC026356.1, AC073254.1, PXN-AS1 expression, AC026412.3, and AC099066.2. High-risk HCC patients had lower survival, CD4+ T cell infiltration, and elevated immune checkpoint gene expression. Furthermore, based on the features of DRLs, HCC was classified into three subtypes. Notably, patients belonging to different subtypes demonstrated varying overall survival rates, immune cell infiltration patterns, and sensitivity to immune therapy. Moreover, the novel DRL AC026412.3 (HR = 40.207) emerged as the most significant prognostic factor, exhibiting high expression across all HCC cells. Elevated expression of AC026412.3 promoted HCC cell proliferation and induced resistance to gefitinib. In conclusion, we have discovered five DRLs and constructed a prognostic risk model. Our findings validate the correlation between DRL-related prognostic models, tumor subtypes, and the HCC immune microenvironment along with its implications for immunotherapy. Moreover, further investigation into the molecular mechanisms of key biomarkers like AC026412.3 in the future will contribute significantly to advancing our comprehension of HCC's pathogenesis and drug resistance mechanisms.

NSUN6 Regulates NM23-H1 Expression in an m5C Manner to Affect Epithelial-Mesenchymal Transition in Lung Cancer

PURPOSE

The expression and regulatory mechanism of NSUN6 in lung cancer are still unclear. Our study explored whether NSUN6 mediates progression of lung cancer by affecting NM23-H1 expression in an m5C-dependent manner.

METHODS

qRT-PCR, CCK-8, colony formation, transwell, and Western blot analysis were employed to probe the impact of NSUN6 on lung cancer cell proliferation, migration, and epithelial-mesenchymal transition (EMT). RMVar database was utilized to forecast the downstream genes of NSUN6. The mode of interaction between NSUN6 and NM23-H1 was determined by dot blot, luciferase assay, m5C RIP, and cell function assays. The effect of NSUN6 expression on tumor growth was verified in vivo.

RESULTS

Expression of NSUN6 was reduced in lung cancer cells, and over-expression of NSUN6 restricted the proliferation of lung cancer cells, migration, and EMT. NSUN6 regulated NM23-H1 expression by modifying the 3'-UTR of NM23-H1 mRNA through m5C and inhibited lung cancer cell proliferation, migration, and EMT. In vivo experiments also showed that over-expression of NSUN6 inhibited the occurrence of lung cancer.

CONCLUSION

NSUN6 regulates NM23-H1 expression in an m5C-dependent manner to affect EMT in lung cancer. Thus, NSUN6 may be considered as a potential therapeutic target for lung cancer.

Creation of a Prognostic Model Using Cuproptosis-Associated Long Noncoding RNAs in Hepatocellular Carcinoma

Cuproptosis is an unusual form of cell death caused by copper accumulation in mitochondria. Cuproptosis is associated with hepatocellular carcinoma (HCC). Long noncoding RNAs (LncRNAs) have been shown to be effective prognostic biomarkers, yet the link between lncRNAs and cuproptosis remains unclear. We aimed to build a prognostic model of lncRNA risk and explore potential biomarkers of cuproptosis in HCC. Pearson correlations were used to derive lncRNAs co-expressed in cuproptosis. The model was constructed using Cox, Lasso, and multivariate Cox regressions. Kaplan-Meier survival analysis, principal components analysis, receiver operating characteristic curve, and nomogram analyses were carried out for validation. Seven lncRNAs were identified as prognostic factors. A risk model was an independent prognostic predictor. Among these seven lncRNAs, prostate cancer associated transcript 6 (PCAT6) is highly expressed in different types of cancer, activating Wnt, PI3K/Akt/mTOR, and other pathways; therefore, we performed further functional validation of PCAT6 in HCC. Reverse transcription-polymerase chain reaction results showed that PCAT6 was aberrantly highly expressed in HCC cell lines (HepG2 and Hep3B) compared to LO2 (normal hepatocytes). When its expression was knocked down, cells proliferated and migrated less. PCAT6 might be a potential biomarker for predicting prognosis in HCC.

Underexplored reciprocity between genome-wide methylation status and long non-coding RNA expression reflected in breast cancer research: potential impacts for the disease management in the framework of 3P medicine

Breast cancer (BC) is the most common female malignancy reaching a pandemic scale worldwide. A comprehensive interplay between genetic alterations and shifted epigenetic regions synergistically leads to disease development and progression into metastatic BC. DNA and histones methylations, as the most studied epigenetic modifications, represent frequent and early events in the process of carcinogenesis. To this end, long non-coding RNAs (lncRNAs) are recognized as potent epigenetic modulators in pathomechanisms of BC by contributing to the regulation of DNA, RNA, and histones' methylation. In turn, the methylation status of DNA, RNA, and histones can affect the level of lncRNAs expression demonstrating the reciprocity of mechanisms involved. Furthermore, lncRNAs might undergo methylation in response to actual medical conditions such as tumor development and treated malignancies. The reciprocity between genome-wide methylation status and long non-coding RNA expression levels in BC remains largely unexplored. Since the bio/medical research in the area is, per evidence, strongly fragmented, the relevance of this reciprocity for BC development and progression has not yet been systematically analyzed. Contextually, the article aims at:consolidating the accumulated knowledge on both-the genome-wide methylation status and corresponding lncRNA expression patterns in BC andhighlighting the potential benefits of this consolidated multi-professional approach for advanced BC management. Based on a big data analysis and machine learning for individualized data interpretation, the proposed approach demonstrates a great potential to promote predictive diagnostics and targeted prevention in the cost-effective primary healthcare (sub-optimal health conditions and protection against the health-to-disease transition) as well as advanced treatment algorithms tailored to the individualized patient profiles in secondary BC care (effective protection against metastatic disease). Clinically relevant examples are provided, including mitochondrial health control and epigenetic regulatory mechanisms involved.