LncRNA HABON promoted liver cancer cells survival under hypoxia by inhibiting mPTP opening

The fate and function of non-coding RNAs during necroptosis

Necroptosis is a novel form of cell death which is activated when apoptotic cell death signals are disrupted. Accumulating body of observations suggests that noncoding RNAs, which are the lately discovered mystery of the human genome, are significantly associated with necroptotic signaling circuitry. The fate and function of miRNAs have been well documented in human disease, especially cancer. Recently, lncRNAs have gained much attention due to their diverse regulatory functions. Although available studies are currently based on bioinformatic analysis, predicted interactions desires further attention, as these hold significant promise and should not be overlooked. In the light of these, here we comprehensively review and discuss noncoding RNA molecules that play significant roles during execution of necroptotic cell death.

Unraveling the intriguing interplay: Exploring the role of lncRNAs in caspase-independent cell death

Cell death plays a crucial role in various physiological and pathological processes. Until recently, programmed cell death was mainly attributed to caspase-dependent apoptosis. However, emerging evidence suggests that caspase-independent cell death (CICD) mechanisms also contribute significantly to cellular demise. We and others have reported and functionally characterized numerous long noncoding RNAs (lncRNAs) that modulate caspase-dependent apoptotic pathways potentially in a pathway-dependent manner. However, the interplay between lncRNAs and CICD pathways has not been comprehensively documented. One major reason for this is that most CICD pathways have been recently discovered with some being partially characterized at the molecular level. In this review, we discuss the emerging evidence that implicates specific lncRNAs in the regulation and execution of CICD. We summarize the diverse mechanisms through which lncRNAs modulate different forms of CICD, including ferroptosis, necroptosis, cuproptosis, and others. Furthermore, we highlight the intricate regulatory networks involving lncRNAs, protein-coding genes, and signaling pathways that orchestrate CICD in health and disease. Understanding the molecular mechanisms and functional implications of lncRNAs in CICD may unravel novel therapeutic targets and diagnostic tools for various diseases, paving the way for innovative strategies in disease management and personalized medicine. This article is categorized under: RNA in Disease and Development > RNA in Disease.

The role of mitochondria-related lncRNAs in characterizing the immune landscape and supervising the prognosis of osteosarcoma

Mitochondrial damage is related to the functional properties of immune cells as well as to tumorigenesis and progression. Nevertheless, there is an absence concerning the systematic evaluation of mitochondria-associated lncRNAs (MALs) in the immune profile and tumor microenvironment of osteosarcoma patients. Based on transcriptomic and clinicopathological data from the TARGET database, MAL-related patterns were ascertained by consistent clustering, and gene set variation analysis of the different patterns was completed. Next, a MAL-derived scoring system was created using Cox and LASSO regression analyses and validated by Kaplan-Meier and ROC curves. The GSEA, ESTIMATE, and CIBERSORT algorithms were utilized to characterize the immune status and underlying biological functions in the different MAL score groups. MAL-derived risk scores were well stabilized and outperformed traditional clinicopathological features to reliably predict 5-year survival in osteosarcoma cohorts. Moreover, patients with increased MAL scores were observed to suffer from poorer prognosis, higher tumor purity, and an immunosuppressive microenvironment. Based on estimated half-maximal inhibitory concentrations, the low-MAL score group benefited more from gemcitabine and docetaxel, and less from thapsigargin and sunitinib compared to the high-MAL score group. Pan-cancer analysis demonstrated that six hub MALs were strongly correlated with clinical outcomes, immune subtypes, and tumor stemness indices in various common cancers. Finally, we verified the expression patterns of hub MALs in osteosarcoma with qRT-PCR. In summary, we identified the crosstalk between prognostic MALs and tumor-infiltrating immune cells in osteosarcoma, providing a potential strategy to ameliorate clinical stratification management.

Ferroptosis-related lncRNA model based on CFAP58-DT for predicting prognosis and immunocytes infiltration in endometrial cancer

Background

Endometrial cancer (EC) is a kind of common gynecological tumor. Further study on the markers related to the prognosis of endometrial cancer is important for women worldwide.

Methods

The Cancer Genome Atlas (TCGA) database was used to obtain the transcriptome profiling and clinical data. A model was built using packages based on R software. Immune-related databases were employed to analyze the infiltration of immunocytes. Quantitative real-time PCR (qRT-PCR), cell counting kit-8 (CCK-8), and transwell assays were utilized to investigate the role of CFAP58-DT in EC.

Results

Following Cox regression analysis, 1,731 ferroptosis-related long non-coding RNA (lncRNA) were screened, and a 9-related lncRNA prognostic model was constructed. Patients were classified as high- and low-risk according to their expression spectrum. Kaplan-Meier (KM) analysis showed that the prognosis of low-risk patients was poor. Operating characteristic curves, decision curve analysis, and a nomogram suggested the model could independently guide prognostic evaluation, with higher sensitivity, specificity, and efficiency than other common clinical characteristics. Gene Set Enrichment Analysis (GSEA) was conducted to determine the enriched pathways among the two groups and evaluation of the immune-infiltrating conditions were performed to help improve immune therapy. Finally, we conducted cytological studies on the model's most important indicators.

Conclusions

Overall, we identified a prognostic ferroptosis-related lncRNA model based on CFAP58-DT for predicting the prognosis and immune-infiltrating conditions in EC. We concluded that the potential oncogenic role of CFAP58-DT can further guide immunotherapy and chemotherapy.

Identification and Validation a Necroptosis-Related Prognostic Signature in Cervical Cancer

Necroptosis is a promising novel target for cervical cancer therapy. Nevertheless, differentially expressed necroptosis-related genes (NRGs) in cervical cancer and their associations with prognosis are far from fully clarified. In this study, differentially expressed NRGs (DE-NRGs) were screened out and their bio-function was elucidated. Subsequently, a prognostic scoring model based on the regression coefficients of the screened out NRGs and their corresponding mRNA expressions were constructed and validated. Finally, the survival probability of cervical cancer patients based on the constructed prognostic scoring model in 3 and 5 years was predicted and assessed. We found 17 DE-NRGs in cervical cancer tissues which were closely related to cancer progression, and most of them were significantly highly expressed. Furthermore, 3 NRG were confirmed as the prognostic signature genes from 17 DE-NRGs by regression analysis. Overall survival predicted through our prognostic scoring model was lower in the high-risk group than in the low-risk group (p < 0.05) in both the TCGA cohort and the external GEO44001 validation cohort. What's more, the prediction performance of our prognostic scoring models well verified by the ROC curve, and the risk score calculated could act as an independent prognostic factor for cervical cancer patients. The calibration curve and C-index (0.776) of the nomogram analysis suggested that the predictive performance of the nomogram was satisfactory. Our study identified and validated a necroptosis-related prognostic signature in cervical cancer, which could well predict the prognosis for cervical cancer patients.

A necroptosis-related lncRNA signature was identified to predict the prognosis and immune microenvironment of IDH-wild-type GBM

Introduction

Necroptosis-related genes are essential for the advancement of IDH-wild-type GBM. However, the putative effects of necroptosis-related lncRNAs (nrlncRNAs) in IDH-wild-type GBM remain unknown.

Methods

By using the TCGA and GTEx databases, a nrlncRNA prognostic signature was created using LASSO Cox regression. The median risk score was used to categorize the patients into low and high-risk groups. To confirm the validity, univariate, multivariate Cox regression and ROC curves were used. Furthermore, by enrichment analysis, immune correlation analysis, and drug sensitivity analysis, the targeted lncRNAs were selected for further verification. As the highest upregulated expression in tumor than peritumor specimens, RP11-131L12.4 was selected for phenotype and functional experiments in primary GBM cells.

Results

Six lncRNAs were proved to be closely related to necroptosis in IDH-1-wild-type GBM, which were used to create a new signature. For 1-, 2-, and 3-year OS, the AUCs were 0.709, 0.645 and 0.694, respectively. Patients in the low-risk group had a better prognosis, stronger immune function activity, and more immune cell infiltration. In contrast, enrichment analysis revealed that the malignant phenotype was more prevalent in the high-risk group. In vitro experiments indicated that RP11-131L12.4 increased the tumor proliferation, migration and invasion, but decreased the necroptosis. Moreover, this nrlncRNA was also proved to be negatively associated with patient prognosis.

Conclusion

The signature of nrlncRNAs may aid in the formulation of tailored and precise treatment for individuals with IDH-wild-type GBM. RP11-131L12.4 may play indispensable role in necroptosis suppression.

COVID-19 metabolism: Mechanisms and therapeutic targets

Severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) dysregulates antiviral signaling, immune response, and cell metabolism in human body. Viral genome and proteins hijack host metabolic network to support viral biogenesis and propagation. However, the regulatory mechanism of SARS‐CoV‐2‐induced metabolic dysfunction has not been elucidated until recently. Multiomic studies of coronavirus disease 2019 (COVID‐19) revealed an intensive interaction between host metabolic regulators and viral proteins. SARS‐CoV‐2 deregulated cellular metabolism in blood, intestine, liver, pancreas, fat, and immune cells. Host metabolism supported almost every stage of viral lifecycle. Strikingly, viral proteins were found to interact with metabolic enzymes in different cellular compartments. Biochemical and genetic assays also identified key regulatory nodes and metabolic dependencies of viral replication. Of note, cholesterol metabolism, lipid metabolism, and glucose metabolism are broadly involved in viral lifecycle. Here, we summarized the current understanding of the hallmarks of COVID‐19 metabolism. SARS‐CoV‐2 infection remodels host cell metabolism, which in turn modulates viral biogenesis and replication. Remodeling of host metabolism creates metabolic vulnerability of SARS‐CoV‐2 replication, which could be explored to uncover new therapeutic targets. The efficacy of metabolic inhibitors against COVID‐19 is under investigation in several clinical trials. Ultimately, the knowledge of SARS‐CoV‐2‐induced metabolic reprogramming would accelerate drug repurposing or screening to combat the COVID‐19 pandemic.