Hepatocellular carcinoma (HCC) is the most common type of liver cancer, characterized by a high morbidity rate. Long non-coding RNAs (lncRNAs) play an important role in regulating various cellular processes and diseases, including cancer. However, their specific roles and mechanisms in HCC are not fully understood. This study used a multi-cohort design to investigate necroptosis-related lncRNAs (NRLs) in patients with HCC. We curated a list of 1095 NRLs and 838 genes showing differential expression between tumor and normal tissues. Among them, we found 105 NRLs closely associated with the prognosis of HCC patients. The 10 lncRNAs (AC100803.3, AC027237.2, AL158166.1, LINC02870, AC026412.3, LINC02159, AC027097.1, AC139887.4, AC007405.1, AL023583.1) generated by LASSO-Cox regression analysis were used to create a prognostic risk model for HCC and group patients into groups based on risk. The KEGG analysis revealed distinct pathway enrichments in high-risk (H-R) and low-risk (L-R) subgroups. According to GO analysis, this study identified 230 differentially expressed genes (DEGs) that were significantly enriched in specific biological processes. Comparison of immune checkpoint-related genes (MCPGs) between H-R and L-R patients revealed significant differences. Moreover, we established a correlation between the risk scores of patients with liver cancer and their sensitivity to 16 chemotherapeutic agents. Employing protein-protein interaction (PPI) analysis, we identified 10 hub genes that potentially regulate the molecular networks involved in HCC development. This study is a pioneering effort to investigate the roles of NRLs in HCC. It opens a new avenue for potential targeted therapies and provides insights into the molecular mechanisms of HCC.

The confrontation between humans and bacteria is ongoing, with strategies for combating bacterial infections continually evolving. With the advancement of RNA sequencing technology, non-coding RNAs (ncRNAs) associated with bacterial infections have garnered significant attention. Recently, long ncRNAs (lncRNAs) have been identified as regulators of sterile inflammatory responses and cellular defense against live bacterial pathogens. They are involved in regulating host antimicrobial immunity in both the nucleus and cytoplasm. Increasing evidence indicates that lncRNAs are critical for the intricate interactions between host and pathogen during bacterial infections. This paper emphatically elaborates on the potential applications of lncRNAs in clinical hallmarks, cellular damage, immunity, virulence, and drug resistance in bacterial infections in greater detail. Additionally, we discuss the challenges and limitations of studying lncRNAs in the context of bacterial infections and highlight clear directions for this promising field.

Ischemic stroke is a significant cause of morbidity and mortality worldwide. Autophagy, a process of intracellular degradation, has been shown to play a crucial role in the pathogenesis of ischemic stroke. Long non-coding RNAs (lncRNAs) have emerged as essential regulators of autophagy in various diseases, including ischemic stroke. Recent studies have identified several lncRNAs that modulate autophagy in ischemic stroke, including MALAT1, MIAT, SNHG12, H19, AC136007. 2, C2dat2, MEG3, KCNQ1OT1, SNHG3, and RMRP. These lncRNAs regulate autophagy by interacting with key proteins involved in the autophagic process, such as Beclin-1, ATG7, and LC3. Understanding the role of lncRNAs in regulating autophagy in ischemic stroke may provide new insights into the pathogenesis of this disease and identify potential therapeutic targets for its treatment.

UNASSIGNED: Oral squamous cell carcinoma (OSCC) stands as the predominant form of oral cancer, marked by a poor prognosis. Ferroptosis, a type of programmed cell death, plays a critical role in the initiation and progression of various cancers. Long non-coding RNAs (lncRNAs) are prominent in modulating cancer development. Nevertheless, the prognostic significance of ferroptosis-related lncRNAs (FRLs) in OSCC remains inadequately explored. This study aims to develop a predictive signature based on FRLs to forecast the prognosis of OSCC patients.
UNASSIGNED: We gathered expression profiles of FRLs along with clinical data from The Cancer Genome Atlas (TCGA) and FerrDb databases. A prognostic model based on 10 FRLs were constructed using Cox regression analyses with LASSO algorithms, and their predictive power was evaluated. Then, the model was used to investigate functional enrichment, immune landscape, m6A genes, somatic variations, and drug response in different risk cohorts of patients. Finally, the expression and function of STARD4-AS1 (steroidogenic acute regulator protein-related lipid transfer domain containing 4-antisense RNA 1), a potential prognostic marker for OSCC screening based on our bioinformatics analysis, were investigated in vitro.
UNASSIGNED: We developed a signature comprising 10 FRLs to stratify patients into two risk cohorts according to their calculated risk scores. Patients classified as high-risk exhibited significantly poorer prognoses compared to those in the low-risk cohort. Furthermore, survival analysis, patient risk heat plot, and risk curve verified the accuracy of the signature. The role of this signature in OSCC was well investigated using immune microenvironment, mutational, and gene set enrichment analysis (GSEA). Moreover, seven drugs, including cisplatin and docetaxel, were identified as potential treatments for patients with high-risk cancers. In addition, the knockdown of STARD4-AS1 in OSCC cell lines markedly inhibited cell proliferation and migration and induced ferroptosis.
UNASSIGNED: Using this signature may improve overall survival predictions in OSCC, throwing new light on immunotherapies and targeted therapies. Moreover, STARD4-AS1 might regulate the process of ferroptosis and could be used as a novel biomarker of OSCC.

Leaf mustard (Brassica juncea L. Czern & Coss), an important vegetable crop, experiences pronounced adversity due to seasonal drought stress, particularly at the seed germination stage. Although there is partial comprehension of drought-responsive genes, the role of long non-coding RNAs (lncRNAs) in adjusting mustard\'s drought stress response is largely unexplored. In this study, we showed that the drought-tolerant cultivar \'Weiliang\' manifested a markedly lower base water potential (-1.073 MPa vs -0.437 MPa) and higher germination percentage (41.2% vs 0%) than the drought-susceptible cultivar \'Shuidong\' under drought conditions. High throughput RNA sequencing techniques revealed a significant repertoire of lncRNAs from both cultivars during germination under drought stress, resulting in the identification of 2,087 differentially expressed lncRNAs (DELs) and their correspondingly linked 12,433 target genes. It was noted that 84 genes targeted by DEL exhibited enrichment in the photosynthesis pathway. Gene network construction showed that MSTRG.150397, a regulatory lncRNA, was inferred to potentially modulate key photosynthetic genes (Psb27, PetC, PetH, and PsbW), whilst MSTRG.107159 was indicated as an inhibitory regulator of six drought-responsive PIP genes. Further, weighted gene co-expression network analysis (WGCNA) corroborated the involvement of light intensity and stress response genes targeted by the identified DELs. The precision and regulatory impact of lncRNA were verified through qPCR. This study extends our knowledge of the regulatory mechanisms governing drought stress responses in mustard, which will help strategies to augment drought tolerance in this crop.

Osteoarthritis (OA) is a chronic degenerative joint disease with multiple causative factors such as aging, mechanical injury, and obesity. Autophagy is a complex dynamic process that is involved in the degradation and modification of intracellular proteins and organelles under different pathophysiological conditions. Autophagy, as a cell survival mechanism under various stress conditions, plays a key role in regulating chondrocyte life cycle metabolism and cellular homeostasis. Non-coding RNAs (ncRNAs) are heterogeneous transcripts that do not possess protein-coding functions, but they can act as effective post-transcriptional and epigenetic regulators of gene and protein expression, thus participating in numerous fundamental biological processes. Increasing evidence suggests that ncRNAs, autophagy, and their crosstalk play crucial roles in OA pathogenesis. Therefore, we summarized the complex role of autophagy in OA chondrocytes and focused on the regulatory role of ncRNAs in OA-associated autophagy to elucidate the complex pathological mechanisms of the ncRNA-autophagy network in the development of OA, thus providing new research targets for the clinical diagnosis and treatment of OA.

In recent years, burgeoning research has underscored the pivotal role of non-coding RNA in orchestrating the growth, development, and pathogenesis of various diseases across organisms. However, despite these advances, our understanding of the specific contributions of long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs) to lens development remains notably limited. Clarifying the intricate gene regulatory networks is imperative for unraveling the molecular underpinnings of lens-related disorders. In this study, we aimed to address this gap by conducting a comprehensive analysis of the expression profiles of messenger RNAs (mRNAs), lncRNAs, and circRNAs at critical developmental time points of the mouse lens, encompassing both embryonic (E10.5, E12.5, and E16.5) and postnatal stages (P0.5, P10.5, and P60). Leveraging RNA-sequencing technology, we identified key transcripts pivotal to lens development. Our analysis revealed differentially expressed (DE) mRNAs, lncRNAs, and circRNAs across various developmental stages. Particularly noteworthy, there were 1831 co-differentially expressed (CO-DE) mRNAs, 150 CO-DE lncRNAs, and 13 CO-DE circRNAs identified during embryonic stages. Gene Ontology (GO) enrichment analysis unveiled associations primarily related to lens development, DNA conformational changes, and angiogenesis among DE mRNAs and lncRNAs. Furthermore, employing protein-protein interaction networks, mRNA-lncRNA co-expression networks, and circRNA-microRNA-mRNA networks, we predicted candidate key molecules implicated in lens development. Our findings underscore the pivotal roles of lncRNAs and circRNAs in this process, offering fresh insights into the pathogenesis of lens-related disorders and paving the way for future exploration in this field.

With the development of gene testing technology, we have found many different genes, and lncRNA is one of them. LncRNAs refer to a non-protein coding RNA molecule with a length of more than 200bp, which is one of the focuses of research on human malignant diseases such as LUAD. LncRNAs act as an oncogene or inhibitor to regulate the occurrence and progression of tumors. The differential expression of LncRNAs promotes or inhibits the progression of lung adenocarcinoma by affecting cell proliferation, metastasis, invasion, and apoptosis, thus affecting the prognosis and survival rate of patients. Therefore, LncRNAs can be used as a potential target for diagnosis and treatment of cancer. The early diagnosis of the disease was made through the detection of tumor markers. Because lung adenocarcinoma is not easy to diagnose in the early stage and tumor markers are easy to ignore, LncRNAs play an important role in the diagnosis and treatment of lung adenocarcinoma. The main purpose of this article is to summarize the known effects of LncRNAs on lung adenocarcinoma, the effect of differential expression of LncRNAs on the progression of lung adenocarcinoma, and related signal transduction pathways. And to provide a new idea for the future research of lung adenocarcinoma-related LncRNAs.

Disulfidptosis is a recently identified mode of regulated cell death. Regulating disulfidptosis in carcinoma is a promising therapeutic approach. Long non-coding RNAs (lncRNAs) have been reported to be related to the occurrence and development of many cancers. Disulfidptosis-related lncRNAs (DRLs) in HPV-negative oral squamous cell carcinoma (OSCC) have not been studied. Based on The Cancer Genome Atlas (TCGA) database, least absolute shrinkage selection operator (LASSO) analysis and Cox regression analysis were used to identify overall survival related DRLs and construct the signature. Kaplan-Meier, time-dependent receiver operating characteristics (ROC) and principal component analyses (PCA) were explored to demonstrate the prediction potential of the signature. Subgroup analysis stratified by different clinicopathological characteristics were conducted. Nomogram was established by DRLs signature and independent clinicopathological characteristics. The calibration plots were performed to reveal the accuracy of nomogram. Immune cell subset infiltration, immunotherapy response, drug sensitivity analysis, and tumor mutation burden (TMB) were conducted. Underlying functions and pathways were explored by Gene Set Enrichment Analysis (GSEA) analysis. Previous lncRNA signatures of OSCC were retrieved from PubMed for further validation. Gene expression omnibus (GEO) datasets (GSE41613 and GSE85446) were merged as an external validation for DRLs signature. Consensus clustering analysis of DRLs signature and experimental validation of DRLs were also explored. This research sheds light on the robust performance of DRLs signature in survival prediction, immune cell infiltration, immune escape, and immunotherapy of HPV-negative OSCC.

Lung adenocarcinoma (LUAD) is a prevalent malignant tumor worldwide, with high incidence and mortality rates. However, there is still a lack of specific and sensitive biomarkers for its early diagnosis and targeted treatment. Disulfidptosis is a newly identified mode of cell death that is characteristic of disulfide stress. Therefore, exploring the correlation between disulfidptosis-related long non-coding RNAs (DRGs-lncRNAs) and patient prognosis can provide new molecular targets for LUAD patients.
The study analysed the transcriptome data and clinical data of LUAD patients in The Cancer Genome Atlas (TCGA) database, gene co-expression, and univariate Cox regression methods were used to screen for DRGs-lncRNAs related to prognosis. The risk score model of lncRNA was established by univariate and multivariate Cox regression models. TIMER, CIBERSORT, CIBERSORT-ABS, and other methods were used to analyze immune infiltration and further evaluate immune function analysis, immune checkpoints, and drug sensitivity. Real-time polymerase chain reaction (RT-PCR) was performed to detect the expression of DRGs-lncRNAs in LUAD cell lines.
A total of 108 lncRNAs significantly associated with disulfidptosis were identified. A prognostic model was constructed by screening 10 lncRNAs with independent prognostic significance through single-factor Cox regression analysis, LASSO regression analysis, and multiple-factor Cox regression analysis. Survival analysis of patients through the prognostic model showed that there were obvious survival differences between the high- and low-risk groups. The risk score of the prognostic model can be used as an independent prognostic factor independent of other clinical traits, and the risk score increases with stage. Further analysis showed that the prognostic model was also different from tumor immune cell infiltration, immune function, and immune checkpoint genes in the high- and low-risk groups. Chemotherapy drug susceptibility analysis showed that high-risk patients were more sensitive to Paclitaxel, 5-Fluorouracil, Gefitinib, Docetaxel, Cytarabine, and Cisplatin. Additionally, RT-PCR analysis demonstrated differential expression of DRGs-lncRNAs between LUAD cell lines and the human bronchial epithelial cell line.
The prognostic model of DRGs-lncRNAs constructed in this study has certain accuracy and reliability in predicting the survival prognosis of LUAD patients, and provides clues for the interaction between disulfidptosis and LUAD immunotherapy.