Primary liver cancer is the second leading cause of cancer-related death worldwide. At present, liver cancer is often in an advanced stage once diagnosed, and treatment effects are generally poor. Therefore, there is an urgent need for other powerful treatments. Macrophages are an important component of the tumor microenvironment, and macrophage polarization is crucial to tumor proliferation and differentiation. Regulatory interactions between macrophage subtypes, such as M1 and M2, lead to a number of clinical outcomes, including tumor progression and metastasis. So, it is important to study the drivers of this process. Long non-coding RNA has been widely proven to be of great value in the early diagnosis and treatment of tumors. Many studies have shown that long non-coding RNA participates in macrophage polarization through its ability to drive M1 or M2 polarization, thereby participating in the occurrence and development of liver cancer. In this article, we systematically elaborated on the long non-coding RNAs involved in the polarization of liver cancer macrophages, hoping to provide a new idea for the early diagnosis and treatment of liver cancer. Liver cancer- related studies were retrieved from PubMed. Based on our identification of LncRNA and macrophage polarization as powerful therapies for liver cancer, we analyzed research articles in the PubMed system in the last ten years on the crosstalk between LncRNA and macrophage polarization. By targeting M1/M2 macrophage polarization, LncRNA may promote or suppress liver cancer, and the references are determined primarily by the article\'s impact factor. Consequently, the specific mechanism of action between LncRNA and M1/M2 macrophage polarization was explored, along with the role of their crosstalk in the occurrence, proliferation, and metastasis of liver cancer. lncRNA is bidirectionally expressed in liver cancer and can target macrophage polarization to regulate tumor behavior. lncRNA mainly functions as ceRNA and can participate in the crosstalk between liver cancer cells and macrophages through extracellular vesicles. lncRNA can potentially participate in the immunotherapy of liver cancer by targeting macrophages and becoming a new biomolecular marker of liver cancer.

This commentary explores the burgeoning field of disulfidptosis-related long noncoding RNAs (lncRNAs) in the prognosis and therapeutic targeting of colorectal cancer (CRC). By evaluating recent research, including the pivotal study \"Predicting colorectal cancer prognosis based on long noncoding RNAs of disulfidptosis genes\" by Wang et al, this analysis underscores the critical role of lncRNAs in deciphering the molecular complexities of CRC. Highlighting the innovative methodologies and significant findings, I discuss the implications for patient survival, therapeutic response, and the potential of lncRNAs as biomarkers for precision medicine. The integration of bioinformatics, clinical databases, and molecular biology in these studies offers a promising avenue for advancing CRC treatment strategies and improving patient outcomes.

This study aims to elucidate the key regulatory molecules, specifically messenger RNAs (mRNAs), long noncoding RNAs (lncRNAs), and microRNAs (miRNAs) and their roles in the development and progression of spinal cord injury (SCI). Expression profiles (GSE45006, GSE19890, and GSE125630) for SCI were sourced from the Gene Expression Omnibus (GEO) database. By comparing rats with SCI at various time points against those without SCI, we identified differentially expressed mRNAs (DEmRNAs), lncRNAs (DElncRNAs), and miRNAs (DEmiRNAs). The GSE45006 dataset facilitated the production of DEmRNAs, which were then clustered using Mfuzz. Subsequently, we constructed a protein-protein interaction (PPI) network and anticipated interaction pairs between miRNA-mRNA and lncRNA-mRNA. These pairs were instrumental in forming a regulatory network involving lncRNA-miRNA-mRNA interactions. Additionally, we conducted functional enrichment studies on the DEmRNAs within these gene networks. A total of 2313 DEmRNAs were identified using the GSE45006 dataset, alongside 111 DEmiRNAs from GSE19890. From GSE125630, we extracted 154 DElncRNAs and 2322 DEmRNAs. Our analysis revealed 294 up-regulated DEmRNAs, grouped into the up-cluster, and 407 down-regulated DEmRNAs, forming the down-cluster. Key hub genes in the PPI network, such as Rhof, Vav1, Lyz2, Rab3a, Lyn, Cyfip1, Gns, and Nckap1l, were identified. Additionally, the study successfully constructed a competing endogenous RNA (ceRNA) network, revealing 55 unique lncRNA-miRNA-mRNA link pairs. Our research established a ceRNA network associated with SCI, identifying several critical lncRNA-miRNA-mRNA connection pairs integral to the disease\'s onset and progression. Notably, significant associations, including the AABR07041411.1-miR-125a-5p-Slc4a7 and the Smg1-rno-miR-331-3p-Tlr4 pairs, were observed to exert a significant influence within this biological context.

BACKGROUND: Necroptosis-related long noncoding RNAs (lncRNAs) play crucial roles in cancer initiation and progression. Nevertheless, the role and mechanism of necroptosis-related lncRNAs in soft tissue sarcomas (STS) is so far unknown and needs to be explored further.
METHODS: Clinical and genomic data were obtained from the UCSC Xena database. All STS patients\' subclusters were performed by unsupervised consensus clustering method based on the prognosis-specific lncRNAs, and then assessed their survival advantage and immune infiltrates. In addition, we explored the pathways and biological processes in subclusters through gene set enrichment analysis. At last, we established the necroptosis-related lncRNA-based risk signature (NRLncSig) using the least absolute shrinkage and selection operator (LASSO) method, and explored the prediction performance and immune microenvironment of this signature in STS.
RESULTS: A total of 911 normal soft tissue samples and 259 STS patients were included in current study. 39 prognosis-specific necroptosis-related lncRNAs were selected. Cluster 2 had a worse survival than the cluster 1 and characterized by different immune landscape in STS. A worse outcome in the high-risk group was observed by survival analysis and indicated an immunosuppressive microenvironment. The ROC curve analyses illustrated that the NRLncSig performing competitively in prediction of prognosis for STS patients. In addition, the nomogram presents excellent performance in predicting prognosis, which may be more beneficial towards STS patients\' treatment.
CONCLUSIONS: Our result indicated that the NRLncSig could be a good independent predictor of prognosis, and significantly connected with immune microenvironment, thereby providing new insights into the roles of necroptosis-related lncRNAs in STS.

Long noncoding RNAs (lncRNAs) have been discovered to be extensively involved in eukaryotic epigenetic, transcriptional, and post-transcriptional regulatory processes with the advancements in sequencing technology and genomics research. Therefore, they play crucial roles in the body\'s normal physiology and various disease outcomes. Presently, numerous unknown lncRNA sequencing data require exploration. Establishing deep learning-based prediction models for lncRNAs provides valuable insights for researchers, substantially reducing time and costs associated with trial and error and facilitating the disease-relevant lncRNA identification for prognosis analysis and targeted drug development as the era of artificial intelligence progresses. However, most lncRNA-related researchers lack awareness of the latest advancements in deep learning models and model selection and application in functional research on lncRNAs. Thus, we elucidate the concept of deep learning models, explore several prevalent deep learning algorithms and their data preferences, conduct a comprehensive review of recent literature studies with exemplary predictive performance over the past 5 years in conjunction with diverse prediction functions, critically analyze and discuss the merits and limitations of current deep learning models and solutions, while also proposing prospects based on cutting-edge advancements in lncRNA research.

Thousands of lncRNAs have been found in zebrafish embryogenesis and adult tissues, but their identification and organogenesis-related functions have not yet been elucidated. In this study, high-throughput sequencing was performed at three different organogenesis stages of zebrafish embryos that are important for zebrafish muscle development. The three stages were 10 hpf (hours post fertilization) (T1), 24 hpf (T2), and 36 hpf (T3). LncRNA gas5, associated with muscle development, was screened out as the next research target by high-throughput sequencing and qPCR validation. The spatiotemporal expression of lncRNA gas5 in zebrafish embryonic muscle development was studied through qPCR and in situ hybridization, and functional analysis was conducted using CRISPR/Cas9 (clustered regularly interspaced short palindromic repeats/Cas9, CRISPR/Cas9). The results were as follows: (1) A total of 1486 differentially expressed lncRNAs were identified between T2 and T1, among which 843 lncRNAs were upregulated and 643 were downregulated. The comparison with T3 and T2 resulted in 844 differentially expressed lncRNAs, among which 482 lncRNAs were upregulated and 362 lncRNAs were downregulated. A total of 2137 differentially expressed lncRNAs were found between T3 and T1, among which 1148 lncRNAs were upregulated and 989 lncRNAs were downregulated, including lncRNA gas5, which was selected as the target gene. (2) The results of spatiotemporal expression analysis showed that lncRNA gas5 was expressed in almost all detected embryos of different developmental stages (0, 2, 6, 10, 16, 24, 36, 48, 72, 96 hpf) and detected tissues of adult zebrafish. (3) After lncRNA gas5 knockout using CRISPR/Cas9 technology, the expression levels of detected genes related to muscle development and adjacent to lncRNA gas5 were more highly affected in the knockout group compared with the control group, suggesting that lncRNA gas5 may play a role in embryonic muscle development in zebrafish. (4) The results of the expression of the skeletal myogenesis marker myod showed that the expression of myod in myotomes was abnormal, suggesting that skeletal myogenesis was affected after lncRNA gas5 knockout. The results of this study provide an experimental basis for further studies on the role of lncRNA gas5 in the embryonic skeletal muscle development of zebrafish.

Nasopharyngeal carcinoma (NPC) is a malignant tumor originating from the nasopharyngeal epithelial cells. Common treatment methods for NPC include radiotherapy, chemotherapy, and surgical intervention. Despite these approaches, the prognosis for NPC remains poor due to treatment resistance and recurrence. Hence, there is a crucial need for more comprehensive research into the mechanisms underlying treatment resistance in NPC. Long non coding RNAs (LncRNAs) are elongated RNA molecules that do not encode proteins. They paly significant roles in various biological processes within tumors, such as chemotherapy resistance, radiation resistance, and tumor recurrence. Recent studies have increasingly unveiled the mechanisms through which LncRNAs contribute to treatment resistance in NPC. Consequently, LncRNAs hold promise as potential biomarkers and therapeutic targets for diagnosing NPC. This review provides an overview of the role of LncRNAs in NPC treatment resistance and explores their potential as therapeutic targets for managing NPC.

BACKGROUND: Podocyte apoptosis plays a vital role in proteinuria pathogenesis in diabetic nephropathy (DN). The regulatory relationship between long noncoding RNAs (lncRNAs) and podocyte apoptosis has recently become another research hot spot in the DN field.
OBJECTIVE: To investigate whether lncRNA protein-disulfide isomerase-associated 3 (Pdia3) could regulate podocyte apoptosis through miR-139-3p and revealed the underlying mechanism.
METHODS: Using normal glucose or high glucose (HG)-cultured podocytes, the cellular functions and exact mechanisms underlying the regulatory effects of lncRNA Pdia3 on podocyte apoptosis and endoplasmic reticulum stress (ERS) were explored. LncRNA Pdia3 and miR-139-3p expression were measured through quantitative real-time polymerase chain reaction. Relative cell viability was detected through the cell counting kit-8 colorimetric assay. The podocyte apoptosis rate in each group was measured through flow cytometry. The interaction between lncRNA Pdia3 and miR-139-3p was examined through the dual luciferase reporter assay. Finally, western blotting was performed to detect the effect of lncRNA Pdia3 on podocyte apoptosis and ERS via miR-139-3p.
RESULTS: The expression of lncRNA Pdia3 was significantly downregulated in HG-cultured podocytes. Next, lncRNA Pdia3 was involved in HG-induced podocyte apoptosis. Furthermore, the dual luciferase reporter assay confirmed the direct interaction between lncRNA Pdia3 and miR-139-3p. LncRNA Pdia3 overexpression attenuated podocyte apoptosis and ERS through miR-139-3p in HG-cultured podocytes.
CONCLUSIONS: Taken together, this study demonstrated that lncRNA Pdia3 overexpression could attenuate HG-induced podocyte apoptosis and ERS by acting as a competing endogenous RNA of miR-139-3p, which might provide a potential therapeutic target for DN.

OBJECTIVE: Hypertrophy ligamentum flavum (LFH) is a common cause of lumbar spinal stenosis, resulting in significant disability and morbidity. Although long noncoding RNAs (lncRNAs) have been associated with various biological processes and disorders, their involvement in LFH remains not fully understood.
METHODS: Human ligamentum flavum samples were analyzed using lncRNA sequencing followed by validation through quantitative real-time polymerase chain reaction. To explore the potential biological functions of differentially expressed lncRNA-associated genes, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed. We also studied the impact of lncRNA PARD3-AS1 on the progression of LFH in vitro.
RESULTS: In the LFH tissues when compared to that in the nonhypertrophic ligamentum flavum (LFN) tissues, a total of 1,091 lncRNAs exhibited differential expression, with 645 upregulated and 446 downregulated. Based on GO analysis, the differentially expressed transcripts primarily participated in metabolic processes, organelles, nuclear lumen, cytoplasm, protein binding, nucleic acid binding, and transcription factor activity. Moreover, KEGG pathway analysis indicated that the differentially expressed lncRNAs were associated with the hippo signaling pathway, nucleotide excision repair, and nuclear factor-kappa B signaling pathway. The expression of PARD3-AS1, RP11-430G17.3, RP1-193H18.3, and H19 was confirmed to be consistent with the sequencing analysis. Inhibition of PARD3-AS1 resulted in the suppression of fibrosis in LFH cells, whereas the overexpression of PARD3-AS1 promoted fibrosis in LFH cells in vitro.
CONCLUSIONS: This study identified distinct expression patterns of lncRNAs that are linked to LFH, providing insights into its underlying mechanisms and potential prognostic and therapeutic interventions. Notably, PARD3-AS1 appears to play a significant role in the pathophysiology of LFH.

Infertility has become a global disease burden. Although assisted reproductive technologies are widely used, the assisted reproduction birth rate is no more than 30% worldwide. Therefore, understanding the mechanisms of reproduction can provide new strategies to improve live birth rates and clinical outcomes of enhanced implantation. Long noncoding RNAs (lncRNAs) have been reported to exert regulatory roles in various biological processes and diseases in many species. In this review, we especially focus on the role of lncRNAs in human reproduction. We summarize the function and mechanisms of lncRNAs in processes vital to reproduction, such as spermatogenesis and maturation, sperm motility and morphology, follicle development and maturation, embryo development and implantation. Then, we highlight the importance and diverse potential of lncRNAs as good diagnostic molecular biomarkers and therapeutic targets for infertility treatment.