Comprehensive analysis of GSEC/miR-101-3p/SNX16/PAPOLG axis in hepatocellular carcinoma

MiR-101-3p Promotes Tumor Cell Proliferation and Migration via the Wnt Signal Pathway in MNNG-Induced Esophageal Squamous Cell Carcinoma

N-methyl-n'-nitroso-n'-nitroso guanidine (MNNG) can induce esophageal squamous cell carcinoma (ESCC), and microRNAs are associated with the development of ESCC and may serve as potential tumor prognostic markers. Thus, the aim of this study was to evaluate the potential function of miR-101-3p in MNNG-induced ESCC. An investigation of risk factors in patients with ESCC was carried out and the concentration of nine nitrosamines in urine samples was detected by the SPE-GC-MS technique. Then, we performed cancer tissue gene sequencing analysis, and RT-qPCR verified the expression level of miR-101-3p. Subsequently, the relationship between miR-101-3p potential target genes and the ESCC patients' prognosis was predicted. Finally, we investigated the function of miR-101-3p in MNNG-induced ESCC pathogenesis and the regulatory mechanism of the signaling pathway by in vivo and in vitro experiments. The results revealed that high dietary nitrosamine levels are high-risk factors for ESCC. MiR-101-3p is down-regulated in ESCC tissues and cells, and its potential target genes are enriched in cell migration and cancer-related pathways. MiR-101-3p target genes include AXIN1, CK1, and GSK3, which are involved in the regulation of the Wnt signaling pathway. MiR-101-3p overexpression promotes apoptosis and inhibits the proliferation and migration of Eca109 cells. The Wnt pathway is activated after subchronic exposure to MNNG, and the Wnt pathway is inhibited by the overexpression of miR-101-3p in Eca109 cells. Down-regulated miR-101-3p may exert tumor suppressive effects by regulating the Wnt pathway and may be a useful biomarker for predicting ESCC progression.

Data augmentation based on the WGAN-GP with data block to enhance the prediction of genes associated with RNA methylation pathways

RNA methylation modification influences various processes in the human body and has gained increasing attention from scholars. Predicting genes associated with RNA methylation pathways can significantly aid biologists in studying RNA methylation processes. Several prediction methods have been investigated, but their performance is still limited by the scarcity of positive samples. To address the challenge of data imbalance in RNA methylation-associated gene prediction tasks, this study employed a generative adversarial network to learn the feature distribution of the original dataset. The quality of synthetic samples was controlled using the Classifier Two-Sample Test (CTST). These synthetic samples were then added to the data blocks to mitigate class distribution imbalance. Experimental results demonstrated that integrating the synthetic samples generated by our proposed model with the original data enhances the prediction performance of various classifiers, outperforming other oversampling methods. Moreover, gene ontology (GO) enrichment analyses further demonstrate the effectiveness of the predicted genes associated with RNA methylation pathways. The model generating gene samples with PyTorch is available at https://github.com/heyheyheyheyhey1/WGAN-GP_RNA_methylation.

SNX16 is required for hepatocellular carcinoma survival via modulating the EGFR-AKT signaling pathway

Sorting nexin 16 (SNX16), a pivotal sorting nexin, emerges in tumor progression complexity, fueling research interest. However, SNX16's biological impact and molecular underpinnings in hepatocellular carcinoma (HCC) remain elusive. This study probes SNX16's function, clinical relevance via mRNA, and protein expression in HCC. Overexpression/knockdown assays of SNX16 were employed to elucidate impacts on HCC cell invasion, proliferation, and EMT. Additionally, the study delved into SNX16's regulation of the EGFR-AKT signaling cascade mechanism. SNX16 overexpression in HCC correlates with poor patient survival; enhancing proliferation, migration, invasion, and tumorigenicity, while SNX16 knockdown suppresses these processes. SNX16 downregulation curbs phospho-EGFR, dampening AKT signaling. EGFR suppression counters SNX16-overexpression-induced HCC proliferation, motility, and invasiveness. Our findings delineate SNX16's regulatory role in HCC, implicating it as a prospective therapeutic target.

A disulfidptosis-related lncRNA signature for predicting prognosis and evaluating the tumor immune microenvironment of lung adenocarcinoma

As a novel form of regulated cell death (RCD), disulfidptosis offering a significant opportunity in better understanding of tumor pathogenesis and therapeutic strategies. Long non-coding RNAs (lncRNAs) regulate the biology functions of tumor cells by engaging with a range of targets. However, the prognostic value of disulfidptosis-related lncRNAs (DRlncRNAs) in lung adenocarcinoma (LUAD) remains unclear. Therefore, our study aimed at establishing a prognostic model for LUAD patients based on DRlncRNAs. RNA-seq data and clinical information were obtained from The Cancer Genome Atlas (TCGA) database. Subsequently, a prognostic model based on DRlncRNAs was constructed using LASSO and COX regression analysis. Patients were stratified into high- and low-risk groups based on their risk scores. Differences between the high-risk and low-risk groups were investigated in terms of overall survival (OS), functional enrichment, tumor immune microenvironment (TIME), somatic mutations, and drug sensitivity. Finally, the role of lncRNA GSEC in LUAD was validated through in vitro experiments. Using the prognostic model consists of 5 DRlncRNAs (AL365181.2, GSEC, AC093673.1, AC012615.1, AL606834.1), the low-risk group exhibited a markedly superior survival in comparison to the high-risk group. The significant differences were observed among patients from different risk groups in OS, immune cell infiltration, immune checkpoint expression, immunotherapy response, and mutation landscape. Experimental results from cellular studies demonstrate the knockdown of lncRNA GSEC leading to a significant reduction in the proliferation and migration abilities of LUAD cells. Our prognostic model, constructed using 5 DRlncRNAs, exhibited the capacity to independently predict the survival of LUAD patients, providing the potentially significant assistance in prognosis prediction, and treatment effects optimization. Moreover, our study established a foundation for further research on disulfidptosis in LUAD and proposed new perspectives for the treatment of LUAD.

Decoding the regulatory landscape of lncRNAs as potential diagnostic and prognostic biomarkers for gastric and colorectal cancers

Colorectal cancer (CRC) and gastric cancer (GC) are major contributors to cancer-related mortality worldwide. Despite advancements in understanding molecular mechanisms and improved drug treatments, the overall survival rate for patients remains unsatisfactory. Metastasis and drug resistance are major challenges contributing to the high mortality rate in both CRC and GC. Recent research has shed light on the role of long noncoding RNAs (lncRNAs) in the development and progression of these cancers. LncRNAs regulate gene expression through various mechanisms, including epigenetic modifications and interactions with microRNAs (miRNAs) and proteins. They can serve as miRNA precursors or pseudogenes, modulating gene expression at transcriptional and post-transcriptional levels. Additionally, circulating lncRNAs have emerged as non-invasive biomarkers for the diagnosis, prognosis, and prediction of drug therapy response in CRC and GC. This review explores the intricate relationship between lncRNAs and CRC/GC, encompassing their roles in cancer development, progression, and chemoresistance. Furthermore, it discusses the potential of lncRNAs as therapeutic targets in these malignancies. The interplay between lncRNAs, miRNAs, and tumor microenvironment is also highlighted, emphasizing their impact on the complexity of cancer biology. Understanding the regulatory landscape and molecular mechanisms governed by lncRNAs in CRC and GC is crucial for the development of effective diagnostic and prognostic biomarkers, as well as novel therapeutic strategies. This review provides a comprehensive overview of the current knowledge and paves the way for further exploration of lncRNAs as key players in the management of CRC and GC.

The role of competing endogenous RNA network in the development of hepatocellular carcinoma: potential therapeutic targets

The current situation of hepatocellular carcinoma (HCC) management is challenging due to its high incidence, mortality, recurrence and metastasis. Recent advances in gene genetic and expression regulation have unveiled the significant role of non-coding RNA (ncRNA) in various cancers. This led to the formulation of the competing endogenous RNA (ceRNA) hypothesis, which posits that both coding RNA and ncRNA, containing miRNA response elements (MRE), can share the same miRNA sequence. This results in a competitive network between ncRNAs, such as lncRNA and mRNA, allowing them to regulate each other. Extensive research has highlighted the crucial role of the ceRNA network in HCC development, impacting various cellular processes including proliferation, metastasis, cell death, angiogenesis, tumor microenvironment, organismal immunity, and chemotherapy resistance. Additionally, the ceRNA network, mediated by lncRNA or circRNA, offers potential in early diagnosis and prevention of HCC. Consequently, ceRNAs are emerging as therapeutic targets for HCC. The complexity of these gene networks aligns with the multi-target approach of traditional Chinese medicine (TCM), presenting a novel perspective for TCM in combating HCC. Research is beginning to show that TCM compounds and prescriptions can affect HCC progression through the ceRNA network, inhibiting proliferation and metastasis, and inducing apoptosis. Currently, the lncRNAs TUG1, NEAT1, and CCAT1, along with their associated ceRNA networks, are among the most promising ncRNAs for HCC research. However, this field is still in its infancy, necessitating advanced technology and extensive basic research to fully understand the ceRNA network mechanisms of TCM in HCC treatment.

Identification of a novel intermittent hypoxia-related prognostic lncRNA signature and the ceRNA of lncRNA GSEC/miR-873-3p/EGLN3 regulatory axis in lung adenocarcinoma

Background

Lung adenocarcinoma (LUAD) is still the most prevalent type of respiratory cancer. Intermittent hypoxia can increase the mortality and morbidity associated with lung cancer. Long non-coding RNAs (lncRNAs) are crucial in lung adenocarcinoma. However, the effects of intermittent hypoxia-related long non-coding RNAs (IHRLs) on lung adenocarcinoma are still unknown.

Method

In the current research, eight IHRLs were selected to create a prognostic model. The risk score of the prognostic model was evaluated using multivariate and univariate analyses, and its accuracy and reliability were validated using a nomogram and ROC. Additionally, we investigated the relationships between IHRLs and the immune microenvironment.

Result

Our analysis identified GSEC, AC099850.3, and AL391001.1 as risk lncRNAs, while AC010615.2, AC010654.1, AL513550.1, LINC00996, and LINC01150 were categorized as protective lncRNAs. We observed variances in the expression of seven immune cells and 15 immune-correlated pathways between the two risk groups. Furthermore, our results confirmed the ceRNA network associated with the intermittent hypoxia-related lncRNA GSEC/miR-873-3p/EGLN3 regulatory pathway. GSEC showed pronounced expression in lung adenocarcinoma tissues and specific cell lines, and its inhibition resulted in reduced proliferation and migration in A549 and PC9 cells. Intriguingly, GSEC manifested oncogenic properties by sponging miR-873-3p and demonstrated a tendency to modulate EGLN3 expression favorably.

Conclusion

GSEC acts as an oncogenic lncRNA by interacting with miR-873-3p, modulating EGLN3 expression. This observation underscores the potential of GSEC as a diagnostic and therapeutic target for LUAD.

Novel methylation-related long non-coding RNA clinical outcome prediction method: the clinical phenotype and immune infiltration research in low-grade gliomas

Background

Recent studies have suggested that long non-coding RNAs (lncRNAs) may play crucial role in low-grade glioma; however, the underlying mechanisms linking them to epigenetic methylation remain unclear.

Methods

We downloaded expression level data for regulators associated with N1 methyladenosine (m1A), 5-methyladenine (m5C), and N6 methyladenosine (m6A) (M1A/M5C/M6A) methylation from the Cancer Genome Atlas-low-grade glioma (TCGA-LGG) database. We identified the expression patterns of lncRNAs, and selected methylation-related lncRNAs using Pearson correlation coefficient>0.4. Non-negative matrix dimensionality reduction was then used to determine the expression patterns of the methylation-associated lncRNAs. We constructed a weighted gene co-expression network analysis (WGCNA) network to explore the co-expression networks between the two expression patterns. Functional enrichment of the co-expression network was performed to identify biological differences between the expression patterns of different lncRNAs. We also constructed prognostic networks based on the methylation presence in lncRNAs in low-grade gliomas.

Results

We identified 44 regulators by literature review. Using a correlation coefficient greater than 0.4, we identified 2330 lncRNAs, among which 108 lncRNAs with independent prognostic values were further screened using univariate Cox regression at P< 0.05. Functional enrichment of the co-expression networks revealed that regulation of trans-synaptic signaling, modulation of chemical synaptic transmission, calmodulin binding, and SNARE binding were mostly enriched in the blue module. The calcium and CA2 signaling pathways were associated with different methylation-related long non-coding chains. Using the Least Absolute Shrinkage Selector Operator (LASSO) regression analysis, we analyzed a prognostic model containing four lncRNAs. The model's risk score was 1.12 *AC012063 + 0.74 * AC022382 + 0.32 * AL049712 + 0.16 * GSEC. Gene set variation analysis (GSVA) revealed significant differences in mismatch repair, cell cycle, WNT signaling pathway, NOTCH signaling pathway, Complement and Cascades, and cancer pathways at different GSEC expression levels. Thus, these results suggest that GSEC may be involved in the proliferation and invasion of low-grade glioma, making it a prognostic risk factor for low-grade glioma.

Conclusion

Our analysis identified methylation-related lncRNAs in low-grade gliomas, providing a foundation for further research on lncRNA methylation. We found that GSEC could serve as a candidate methylation marker and a prognostic risk factor for overall survival in low-grade glioma patients. These findings shed light on the underlying mechanisms of low-grade glioma development and may facilitate the development of new treatment strategies.

Comprehensive analysis of cuproptosis-related prognostic gene signature and tumor immune microenvironment in HCC

Background: Copper is an indispensable mineral element involved in many physiological metabolic processes. Cuproptosis is associated with a variety of cancer such as hepatocellular carcinoma (HCC). The objective of this study was to examine the relationships between the expression of cuproptosis-related genes (CRGs) and tumor characteristics, including prognosis and microenvironment of HCC. Methods: The differentially expressed genes (DEGs) between high and low CRGs expression groups in HCC samples were identified, and further were analyzed for functional enrichment analysis. Then, CRGs signature of HCC was constructed and analyzed utilizing LASSO and univariate and multivariate Cox regression analysis. Prognostic values of CRGs signature were evaluated by Kaplan-Meier analysis, independent prognostic analysis and nomograph. The expression of prognostic CRGs was verified by Real-time quantitative PCR (RT-qPCR) in HCC cell lines. In addition, the relationships between prognostic CRGs expression and the immune infiltration, tumor microenvironment, antitumor drugs response and m6A modifications were further explored using a series of algorithms in HCC. Finally, ceRNA regulatory network based on prognostic CRGs was constructed. Results: The DEGs between high and low CRG expression groups in HCC were mainly enriched in focal adhesion and extracellular matrix organization. Besides, we constructed a prognostic model that consists of CDKN2A, DLAT, DLST, GLS, and PDHA1 CRGs for predicting the survival likelihood of HCC patients. And the elevated expression of these five prognostic CRGs was substantially in HCC cell lines and associated with poor prognosis. Moreover, immune score and m6A gene expression were higher in the high CRG expression group of HCC patients. Furthermore, prognostic CRGs have higher mutation rates in HCC, and are significantly correlated with immune cell infiltration, tumor mutational burden, microsatellite instability, and anti-tumor drug sensitivity. Then, eight lncRNA-miRNA-mRNA regulatory axes that affected the progression of HCC were predicted. Conclusion: This study demonstrated that the CRGs signature could effectively evaluate prognosis, tumor immune microenvironment, immunotherapy response and predict lncRNA-miRNA-mRNA regulatory axes in HCC. These findings extend our knowledge of cuproptosis in HCC and may inform novel therapeutic strategies for HCC.

MiR-101: An Important Regulator of Gene Expression and Tumor Ecosystem

MiRNAs are small single-stranded non-coding RNAs. MiRNA contributes to the transcriptional and post-transcriptional regulation of mRNA in different cell types, including mRNA transcription inhibition and mRNA decay and phenotypes via the effect of several essential oncogenic processes and tumor microenvironment. MiR-101 is a highly conserved miRNA that was found to alter the expression in various human cancers. MiR-101 has been reported to have tumor oncogenic and suppressive effects to regulate tumorigenesis and tumor progression. In this review, we summarize the new findings about the roles of miR-101 in cancers and the underlying mechanisms of targeting genes degradation and microenvironment regulation, which will improve biological understanding and design of novel therapeutics.

Involvement of plasma lncRNA GSEC in sepsis discrimination and prognosis, and its correlation with macrophage cell inflammation and proliferation

BACKGROUND

Despite the dysregulation and function of G-quadruplex-forming sequence containing lncRNA (GSEC) have been widely reported in human cancers, there are few available data revealing its role in sepsis.

OBJECTIVE

To assess the expression and function of GSEC in the development of sepsis and its potential molecular mechanism.

MATERIALS AND METHODS

A total of 78 sepsis patients, 55 non-sepsis intensive care unit patients, and 42 healthy individuals were enrolled in this study. The expression of GSEC was evaluated in plasma and macrophage cells with polymerase chain reaction. The inflammation response of sepsis patients and macrophage cells was analyzed with an enzyme-linked immunosorbent assay. The diagnostic and prognostic value of GSEC in sepsis patients were estimated by receiver operator curve (ROC) and Cox analysis. The molecular mechanism underlying the function of GSEC was investigated in RAW264.7 cell with luciferase reporter assay and cell transfection.

RESULTS

Significant upregulation of GSEC was observed in sepsis patients' plasma, which could discriminate sepsis patients from healthy and non-sepsis individuals. Upregulation of GSEC was positively correlated with inflammation cytokine levels and adverse prognosis of sepsis patients. In vitro, GSEC was found to modulate the expression level of miR-873-3p, which mediated the regulatory effect of GSEC on the inflammation and proliferation of RAW264.7.

CONCLUSION

Upregulated GSEC could serve as a biomarker of sepsis pathogenesis and development. GSEC regulates the inflammation and proliferation of macrophage cells through modulating miR-873-3p.

miR-200c-3p, miR-222-5p, and miR-512-3p Constitute a Biomarker Signature of Sorafenib Effectiveness in Advanced Hepatocellular Carcinoma

Background: Sorafenib constitutes a suitable treatment alternative for patients with advanced hepatocellular carcinoma (HCC) in whom atezolizumab + bevacizumab therapy is contraindicated. The aim of the study was the identification of a miRNA signature in liquid biopsy related to sorafenib response. Methods: miRNAs were profiled in hepatoblastoma HepG2 cells and tested in animal models, extracellular vesicles (EVs), and plasma from HCC patients. Results: Sorafenib altered the expression of 11 miRNAs in HepG2 cells. miR-200c-3p and miR-27a-3p exerted an anti-tumoral activity by decreasing cell migration and invasion, whereas miR-122-5p, miR-148b-3p, miR-194-5p, miR-222-5p, and miR-512-3p exerted pro-tumoral properties by increasing cell proliferation, migration, or invasion, or decreasing apoptosis. Sorafenib induced a change in EVs population with an increased number of larger EVs, and promoted an accumulation of miR-27a-3p, miR-122-5p, miR-148b-3p, miR-193b-3p, miR-194-5p, miR-200c-3p, and miR-375 into exosomes. In HCC patients, circulating miR-200c-3p baseline levels were associated with increased survival, whereas high levels of miR-222-5p and miR-512-3p after 1 month of sorafenib treatment were related to poor prognosis. The RNA sequencing revealed that miR-200c-3p was related to the regulation of cell growth and death, whereas miR-222-5p and miR-512-3p were related to metabolic control. Conclusions: The study showed that Sorafenib regulates a specific miRNA signature in which miR-200c-3p, miR-222-5p, and miR-512-3p bear prognostic value and contribute to treatment response.