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Long non-coding RNAs (lncRNAs) play important roles in various biological progresses of carcinogenesis. However, the function of lncRNAs in human sinonasal squamous cell carcinoma (SNSCC) remains greatly unclear. In the current study, lncRNA AC091729.7 expression was examined in SNSCC samples by using microarray, RNA in situ hybridization (ISH) and real-time fluorescence quantitative PCR (qRT-PCR). Cell viability, colony-formation, wound-healing, and transwell assays were applied to SNSCC cells. Xenograft mouse models were employed to evaluate the role of AC091729.7 in growth of SNSCC in vivo. Human protein microarray (HuprotTM Protoarray) and RNA immunoprecipitation (RIP) were used for identifying AC091729.7 binding proteins in SNSCC. Results showed AC091729.7 was upregulated and closely connected with the survival of the SNSCC patients. Knockdown of AC091729.7 suppressed SNSCC cell migration, proliferation, invasion in vitro. Furthermore, downregulation of AC091729.7 could inhibit the growth of SNSCC in vivo. Moreover, Human protein microarray and RIP suggested that AC091729.7 directly combine with the serine/arginine rich splicing factor 2 (SRSF2). Our results suggest that in the cell progression of SNSCC, lncRNA AC091729.7 plays a carcinogenic role and serves as a novel biomarker and latent curative target in SNSCC patients. [ABSTRACT FROM AUTHOR]

Breast cancer (BC) is one of the frequent tumors that seriously endanger the physical and mental well-being in women with strong heterogeneity, and its pathogenesis involves multiple risk factors. Depending on the type of BC, hormonal therapy, targeted therapy, and immunotherapy are the current systemic treatment options along with conventional chemotherapy. Despite significant progress in understanding BC pathogenesis and therapeutic options, there is still a need to identify new therapeutic targets and develop more effective treatments. According to recent sequencing and profiling studies, non-coding (nc) RNAs genes are deregulated in human cancers via deletion, amplification, abnormal epigenetic, or transcriptional regulation, and similarly, the expression of many ncRNAs is altered in breast cancer cell lines and tissues. The ability of single ncRNAs to regulate the expression of multiple downstream gene targets and related pathways provides a theoretical basis for studying them for cancer therapeutic drug development and targeted delivery. Therefore, it is far-reaching to explore the role of ncRNAs in tumor development and their potential as therapeutic targets. Here, our review outlines the potential of two major ncRNAs, long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) as diagnostic and prognostic biomarkers as well as targets for new therapeutic strategies in breast cancer. [ABSTRACT FROM AUTHOR]

Cancer chimeric, or fusion, transcripts are thought to most frequently appear due to chromosomal aberrations that combine moieties of unrelated normal genes. When being expressed, this results in chimeric RNAs having upstream and downstream parts relatively to the breakpoint position for the 5'- and 3'-fusion components, respectively. As many other types of cancer mutations, fusion genes can be of either driver or passenger type. The driver fusions may have pivotal roles in malignisation by regulating survival, growth, and proliferation of tumor cells, whereas the passenger fusions most likely have no specific function in cancer. The majority of research on fusion gene formation events is concentrated on identifying fusion proteins through chimeric transcripts. However, contemporary studies evidence that fusion events involving noncoding RNA (ncRNA) genes may also have strong oncogenic potential. In this review we highlight most frequent classes of ncRNAs fusions and summarize current understanding of their functional roles. In many cases, cancer ncRNA fusion can result in altered concentration of the non-coding RNA itself, or it can promote protein expression from the protein-coding fusion moiety. Differential splicing, in turn, can enrich the repertoire of cancer chimeric transcripts, e.g. as observed for the fusions of circular RNAs and long non-coding RNAs. These and other ncRNA fusions are being increasingly recognized as cancer biomarkers and even potential therapeutic targets. Finally, we discuss the use of ncRNA fusion genes in the context of cancer detection and therapy. [ABSTRACT FROM AUTHOR]

Introduction: Urothelial Bladder Cancer (BC) is the ninth most common cancer worldwide. It is classified into Non Muscle Invasive (NMIBC) and Muscle Invasive Bladder Cancer (MIBC), which are characterized by frequent recurrences and progression rate, respectively. The diagnosis and monitoring are obtained through invasive methods as cystoscopy and post-surgery biopsies. Thus, a panel of biomarkers able to discriminate BC based on grading or staging represents a significant step forward in the patients' workup. In this perspective, long non-coding RNAs (lncRNAs) are emerged as reliable candidates as potential biomarker given their specific and regulated expression. In the present work we propose two lncRNAs, the Small Ubiquitin Modifier 1 pseudogene 3 (SUMO1P3), a poorly characterized pseudogene, and the Urothelial Carcinoma Associated 1 (UCA1) as candidates to monitor the BC progression. Methods: This study was a retrospective trial enrolling NMIBC and MIBC patients undergoing surgical intervention: the expression of the lncRNA SUMO1P3 and UCA1 was evaluated in urine from 113 subjects (cases and controls). The receiver operating characteristic curve analysis was used to evaluate the performance of single or combined biomarkers in discriminating cases from controls. Results: SUMO1P3 and UCA1 expression in urine was able to significantly discriminate low grade NMIBC, healthy control and benign prostatic hyperplasia subjects versus high grade NMIBC and MIBC patients. We also demonstrated that miR-320a, which binds SUMO1P3, was reduced in high grade NMIBC and MIBC patients and the SUMO1P3/miR-320a ratio was used to differentiate cases versus controls, showing a statistically significant power. Finally, we provided an automated method of RNA extraction coupled to ddPCR analysis in a perspective of clinical application. Discussion: We have shown that the lncRNA SUMO1P3 is increased in urine from patients with high grade NMIBC and MIBC and that it is likely to be good candidate to predict bladder cancer progression if used alone or in combination with UCA1 or with miRNA320a. [ABSTRACT FROM AUTHOR]

Osteosarcoma (OS) is a malignancy characterized by the proliferation of osteoblasts that predominantly affects pediatric and adolescent populations. At present, early detection of OS is significantly lacking, coupled with treatment challenges such as high recurrence rates, increased side effects, and the development of drug resistance. Therefore, developing new diagnostic and therapeutic modalities is clinically significant. Exosomes are naturally occurring nanoparticles found in the body that contain various materials, including DNA, RNA, and proteins. Owing to their numerous beneficial properties, including histocompatibility and in vivo stability, they can be useful as drug carriers. With the development of competitive endogenous non-coding RNA (ncRNA) networks, the role of ncRNA in OS cell control has been increasingly studied. This review provides a thorough summary of multiple potential biogenetic pathways of different ncRNAs in exosomes, including microRNAs, long ncRNAs, and circular RNAs. Moreover, the review highlights their effects on OS cells and their potential applications in the diagnosis, treatment, and control of OS drug resistance. The interplay between different types of ncRNAs, which collectively affect OS through the networks of competing endogenous ncRNAs, is the primary focus of this research.

Breast cancer (BC) is one of the frequent tumors that seriously endanger the physical and mental well-being in women with strong heterogeneity, and its pathogenesis involves multiple risk factors. Depending on the type of BC, hormonal therapy, targeted therapy, and immunotherapy are the current systemic treatment options along with conventional chemotherapy. Despite significant progress in understanding BC pathogenesis and therapeutic options, there is still a need to identify new therapeutic targets and develop more effective treatments. According to recent sequencing and profiling studies, non-coding (nc) RNAs genes are deregulated in human cancers via deletion, amplification, abnormal epigenetic, or transcriptional regulation, and similarly, the expression of many ncRNAs is altered in breast cancer cell lines and tissues. The ability of single ncRNAs to regulate the expression of multiple downstream gene targets and related pathways provides a theoretical basis for studying them for cancer therapeutic drug development and targeted delivery. Therefore, it is far-reaching to explore the role of ncRNAs in tumor development and their potential as therapeutic targets. Here, our review outlines the potential of two major ncRNAs, long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) as diagnostic and prognostic biomarkers as well as targets for new therapeutic strategies in breast cancer.

Prostate cancer is a major contributor to male cancer-related mortality globally. It has a particular affinity for the skeletal system with metastasis to bones seriously impacting prognosis. The identification of prostate cancer biomarkers can significantly enhance diagnosis and patient monitoring. Research has found that cancer and metastases exhibit abnormal expression of numerous non-coding RNA. Some of these RNA facilitate prostate cancer bone metastasis by activating downstream signaling pathways, while others inhibit this process. Elucidating the functional processes of non-coding RNA in prostate cancer bone metastasis will likely lead to innovative treatment strategies for this malignant condition. In this review, the mechanistic role of the various RNA in prostate cancer is examined. Our goal is to provide a new avenue of approach to the diagnosis and treatment of bone metastasis in this cancer. [ABSTRACT FROM AUTHOR]

Cancer chimeric, or fusion, transcripts are thought to most frequently appear due to chromosomal aberrations that combine moieties of unrelated normal genes. When being expressed, this results in chimeric RNAs having upstream and downstream parts relatively to the breakpoint position for the 5’- and 3’-fusion components, respectively. As many other types of cancer mutations, fusion genes can be of either driver or passenger type. The driver fusions may have pivotal roles in malignisation by regulating survival, growth, and proliferation of tumor cells, whereas the passenger fusions most likely have no specific function in cancer. The majority of research on fusion gene formation events is concentrated on identifying fusion proteins through chimeric transcripts. However, contemporary studies evidence that fusion events involving non-coding RNA (ncRNA) genes may also have strong oncogenic potential. In this review we highlight most frequent classes of ncRNAs fusions and summarize current understanding of their functional roles. In many cases, cancer ncRNA fusion can result in altered concentration of the non-coding RNA itself, or it can promote protein expression from the protein-coding fusion moiety. Differential splicing, in turn, can enrich the repertoire of cancer chimeric transcripts, e.g. as observed for the fusions of circular RNAs and long non-coding RNAs. These and other ncRNA fusions are being increasingly recognized as cancer biomarkers and even potential therapeutic targets. Finally, we discuss the use of ncRNA fusion genes in the context of cancer detection and therapy.

IntroductionUrothelial Bladder Cancer (BC) is the ninth most common cancer worldwide. It is classified into Non Muscle Invasive (NMIBC) and Muscle Invasive Bladder Cancer (MIBC), which are characterized by frequent recurrences and progression rate, respectively. The diagnosis and monitoring are obtained through invasive methods as cystoscopy and post-surgery biopsies. Thus, a panel of biomarkers able to discriminate BC based on grading or staging represents a significant step forward in the patients’ workup. In this perspective, long non-coding RNAs (lncRNAs) are emerged as reliable candidates as potential biomarker given their specific and regulated expression. In the present work we propose two lncRNAs, the Small Ubiquitin Modifier 1 pseudogene 3 (SUMO1P3), a poorly characterized pseudogene, and the Urothelial Carcinoma Associated 1 (UCA1) as candidates to monitor the BC progression.MethodsThis study was a retrospective trial enrolling NMIBC and MIBC patients undergoing surgical intervention: the expression of the lncRNA SUMO1P3 and UCA1 was evaluated in urine from 113 subjects (cases and controls). The receiver operating characteristic curve analysis was used to evaluate the performance of single or combined biomarkers in discriminating cases from controls.ResultsSUMO1P3 and UCA1 expression in urine was able to significantly discriminate low grade NMIBC, healthy control and benign prostatic hyperplasia subjects versus high grade NMIBC and MIBC patients. We also demonstrated that miR-320a, which binds SUMO1P3, was reduced in high grade NMIBC and MIBC patients and the SUMO1P3/miR-320a ratio was used to differentiate cases versus controls, showing a statistically significant power. Finally, we provided an automated method of RNA extraction coupled to ddPCR analysis in a perspective of clinical application.DiscussionWe have shown that the lncRNA SUMO1P3 is increased in urine from patients with high grade NMIBC and MIBC and that it is likely to be good candidate to predict bladder cancer progression if used alone or in combination with UCA1 or with miRNA320a.

The article published in Frontiers in Oncology on October 14, 2024, titled "Corrigendum: A novel LncRNA, AC091729.7 promotes sinonasal squamous cell carcinomas proliferation and invasion through binding SRSF2," addresses an error in the legend for Figure 3F Transwell invasion assay. The authors acknowledge the mistake and clarify that it does not impact the scientific conclusions of the original article. The study focuses on the role of the long non-coding RNA AC091729.7 in promoting the proliferation and invasion of sinonasal squamous cell carcinomas by binding to SRSF2, providing insights into potential therapeutic targets for this type of cancer. [Extracted from the article]

Background: Laryngeal squamous cell carcinoma (LSCC) is one of the most frequent head and neck cancers worldwide. Long non-coding RNAs (lncRNAs) play a critical role in tumorigenesis. However, the clinical significance of lncRNAs in LSCC remains largely unknown. Methods: In this study, transcriptome sequencing was performed on 107 LSCC and paired adjacent normal mucosa (ANM) tissues. Furthermore, RNA expression and clinical data of 111 LSCC samples were obtained from The Cancer Genome Atlas (TCGA) database. Bioinformatics analysis were performed to construct a model for predicting the overall survival (OS) of LSCC patients. Moreover, we investigated the roles of lncRNAs in LSCC cells through loss-of-function experiments. Results: A seven-lncRNAs panel including ENSG00000233397, BARX1-DT, LSAMP-AS1, HOXB-AS4, MNX1-AS1, LINC01385, and LINC02893 was identified. The Kaplan–Meier analysis demonstrated that the seven-lncRNAs panel was significantly associated with OS (HR:6.21 [3.27-11.81], p-value<0.0001), disease-specific survival (DSS) (HR:4.34 [1.83-10.26], pvalue= 0.0008), and progression-free interval (PFI) (HR:3.78 [1.92-7.43], pvalue= 0.0001). ROC curves showed the seven-lncRNAs panel predicts OS with good specificity and sensitivity. Separately silencing the seven lncRNAs inhibited the proliferation, migration, and invasion capacity of LSCC cells. Conclusion: Collectively, this seven-lncRNAs panel is a promising signature for predicting the prognosis of LSCC patients, and these lncRNAs could serve as potential targets for LSCC treatment. [ABSTRACT FROM AUTHOR]

Thyroid cancer is a commonly diagnosed endocrine malignancy with increasing incidence worldwide. Long noncoding RNAs (lncRNAs) are known to function in the invasion and metastasis of thyroid cancer. According to the GSE66783 microarray dataset, long intergenic nonprotein coding RNA 284 (LINC00284) is aberrantly upregulated in thyroid cancer tissues. However, information regarding the specific role of LINC00284 in thyroid cancer remains elusive. Therefore, the current study set out to determine the role of LINC00284 in the development of thyroid cancer, along with an investigation of the underlying molecular mechanism. In parallel with the microarray data from GSE66783, LINC00284 was observed to be expressed at high levels in thyroid cancer cell lines. Moreover, loss-of-function experiments revealed that the downregulation of LINC00284 reduced aldehyde dehydrogenase (ALDH) activity and thyroid cancer cell proliferation, colony formation, and invasiveness, which promoted cell apoptosis. Mechanistically, using dual-luciferase reporter, RNA pull-down, and RNA immunoprecipitation (RIP) assays, LINC00284 was identified to competitively bind to microRNA-30d-5p (miR-30d-5p), which was observed to be expressed at low levels in thyroid cancer tissues and cells and directly targets the oncogene a disintegrin and metalloproteinase 12 (ADAM12). Overexpression of miR-30d-5p exerted tumor-suppressive effects on the malignant activity of thyroid cancer cells, changes that were reversed by LINC00284 overexpression or ADAM12 overexpression. Furthermore, LINC00284 activated the Notch signaling pathway by competitively binding to miR-30d-5p and increasing the expression of ADAM12. Finally, by performing in vivo experiments, we found that LINC00284 silencing or miR-30d-5p overexpression suppressed the tumorigenic ability of thyroid cancer cells and that overexpression of miR-30d-5p inhibited the LINC00284-induced tumorigenesis of thyroid cancer cells. Collectively, our findings indicate that LINC00284 competitively binds to miR-30d-5p and activates the ADAM12-dependent Notch signaling pathway, thereby promoting the development of thyroid cancer. [ABSTRACT FROM AUTHOR]

BackgroundCuproptosis is considered a novel copper-induced cell death model regulated by targeting lipoylated TCA cycle proteins. In this study, we established a novel signature based on cuproptosis-related lncRNAs (crlncRNAs) to predict the prognosis and immune landscape of head and neck squamous cell carcinoma.MethodsRNA-seq matrix, somatic mutation files, and clinical data were obtained from The Cancer Genome Atlas database. After dividing patients into two sets, a crlncRNA signature was established based on survival related crlncRNAs, which were selected by the univariate Cox analysis and least absolute shrinkage and selection operator Cox regression. To evaluate the model, Kaplan-Meier survival analysis and time-dependent receiver operating characteristic (ROC) were utilized, and a nomogram was established for survival prediction. Immune landscape analysis, drug sensitivity, cluster analysis, tumor mutation burden (TMB) and ceRNA network analysis were conducted subsequently.ResultsA crlncRNA related prognosis signature was finally constructed with 12 crlncRNAs. The areas under the ROC curves (AUCs) were 0.719, 0.705 and 0.693 respectively for 1, 3, and 5-year’s overall survival (OS). Patients in the low-risk group behaved a better prognosis, lower TMB, higher immune function activity and scores. In addition, patients from cluster 2 were more sensitive to chemotherapy and immunotherapy.ConclusionIn this study, we constructed a novel crlncRNA risk model to predict the survival of HNSCC patients. This reliable and acceptable prognostic signature may guide and promote the progress of novel treatment strategies for HNSCC patients.

BackgroundThis study aimed to identify autophagy-related long non-coding RNAs (lncRNAs) associated with progression of neuroblastoma (NB), and to build an autophagy-related lncRNA signature that helps to predict progression-free survival (PFS) of NB.MethodsThree independent gene expression datasets were utilized in this study. Autophagy-related genes (ARG) associated with PFS of NB patients were firstly identified by univariate Cox survival analysis. lncRNAs correlated with those PFS-related ARGs were then identified. The least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox regression analyses were performed to select out those lncRNAs with the best prognostic value for PFS. The Receiver Operating Characteristic (ROC) and Area Under Curve (AUC) analyses were performed to assess the prediction accuracy.ResultsFour autophagy-related lncRNAs (AL356599.1, AC022075.1, AC020928.1 and LINC02076) were found to be with the best prognostic value and integrated into a four-lncRNA risk signature for predicting PFS of NB patients. The four-lncRNA signature significantly stratify NB patients into two risk groups, with high-risk group has significantly poorer PFS than the low-risk group. The prognostic role of the lncRNA signature was independent with other clinical risk factors. The ROC curves revealed that the lncRNA signature has a good performance in predicting PFS (AUC > 0.70). A nomogram based on COG (Children’s Oncology Group) risk and the lncRNA risk score was constructed, showing good prediction accuracy (C-index = 0.700). The prognostic ability of the nomogram was better than that of COG risk alone (AUC = 0.790 versus AUC = 0.748). GSEA analyses revealed that multiple autophagy-related gene sets are significantly enriched in the low-risk group.ConclusionsWe identified an autophagy-related four-lncRNA signature that could help to predict the PFS of NB patients. Autophagy-related gene sets are significantly enriched in low-risk group, suggesting tumor suppressive roles of autophagy in NB.

Purpose: Renal clear cell carcinoma (ccRCC) is the most lethal of all pathological subtypes of renal cell carcinoma (RCC). Genomic instability was recently reported to be related to the occurrence and development of kidney cancer. The biological roles of long non-coding RNAs (lncRNAs) in tumorigenesis have been increasingly valued, and various lncRNAs were found to be oncogenes or cancer suppressors. Herein, we identified a novel genomic instability-associated lncRNA (GILncs) model for ccRCC patients to predict the overall survival (OS). Methods: The Cancer Genome Atlas (TCGA) database was utilized to obtain full transcriptome data, somatic mutation profiles, and clinical characteristics. The differentially expressed lncRNAs between the genome-unstable-like group (GU) and the genome-stable-like group (GS) were defined as GILncs, with | logFC| > 1 and an adjusted p-value< 0.05 for a false discovery rate. All samples were allocated into GU-like or GS-like types based on the expression of GILncs observed using hierarchical cluster analyses. A genomic instability-associated lncRNA signature (GILncSig) was constructed using parameters of the included lncRNAs. Quantitative real-time PCR analysis was used to detect the in vitro expression of the included lncRNAs. Validation of the risk model was performed by the log-rank test, time-dependent receiver operating characteristic (ROC) curves analysis, and multivariate Cox regression analysis. Results: Forty-six lncRNAs were identified as GILncs. LINC00460, AL139351.1, and AC156455.1 were employed for GILncSig calculation based on the results of Cox analysis. GILncSig was confirmed as an independent predictor for OS of ccRCC patients. Additionally, it presented a higher efficiency and accuracy than other RCC prognostic models reported before. Conclusion: GILncSig score was qualified as a critical indicator, independent of other clinical factors, for prognostic prediction of ccRCC patients. [ABSTRACT FROM AUTHOR]

Necroptosis, which is recently recognized as a form of programmed cell death, plays a critical role in cancer biology, including tumorigenesis and cancer immunology. It was recognized not only to defend against tumor progression by suppressing adaptive immune responses but also to promote tumorigenesis and cancer metastasis after recruiting inflammatory responses. Thus the crucial role of necrosis in tumorigenesis has attracted increasing attention. Due to the heterogeneity of the tumor immune microenvironment (TIME) in lung adenocarcinoma (LUAD), the prognosis and the response to immunotherapy vary distinctly across patients, underscoring the need for a stratification algorithm for clinical practice. Although previous studies have formulated the crucial role of lncRNAs in tumorigenicity, the relationship between necroptosis-related lncRNAs, TIME, and the prognosis of patients with LUAD was still elusive. In the current study, a robust and novel prognostic stratification model based on Necroptosis-related LncRNA Risk Scoring (NecroLRS) and clinicopathological parameters was constructed and systemically validated in both internal and external validation cohorts. The expression profile of four key lncRNAs was further validated by qRT-PCR in 4 human LUAD cell lines. And a novel immune landscape alteration was observed between NecroLRS-High and -Low patients. To further elucidate the mechanism of necroptosis in the prognosis of LUAD from a single-cell perspective, a novel stratification algorithm based on K-means clustering was introduced to extract both malignant and NecroLRS-High subsets from epithelial cells. And the necroptosis-related immune infiltration landscape and developmental trajectory were investigated respectively. Critically, NecroLRS was found to be positively correlated with neutrophil enrichment, inflammatory immune response, and malignant phenotypes of LUAD. In addition, novel ligand-receptor pairs between NecroLRS-High cells and other immunocytes were investigated and optimal therapeutic compounds were screened to provide potential targets for future studies. Taken together, our findings reveal emerging mechanisms of necroptosis-induced immune microenvironment alteration on the deteriorative prognosis and may contribute to improved prognosis and individualized precision therapy for patients with LUAD. [ABSTRACT FROM AUTHOR]

Exosomal long non-coding RNAs (lncRNAs) have emerged as a cell-free biomarker for clinical evaluation of cancers. However, the potential clinical applications of exosomal lncRNAs in acute myeloid leukemia (AML) remain unclear. Herein, we attempted to identify plasma exosomal lncRNAs as prospective biomarkers for AML. In this study, plasma exosomes were first successfully extracted from AML patients and healthy donors (HD). Subsequently, the downregulated plasma exosomal lncRNAs (LINC00265, LINC00467, and UCA1) and the upregulated plasma exosomal lncRNA (SNHG1) were identified in AML patients (n=65) compared to HD (n=20). Notably, individual exosomal LINC00265, LINC00467, UCA1, or SNHG1 had a capability for discriminating AML patients from HD, and their combination displayed better efficiency. Furthermore, exosomal LINC00265 and LINC00467 were increased expressed in patients achieving complete remission after chemotherapy. Importantly, there was upregulation of exosomal LINC00265 and downregulation of exosomal SNHG1 upon allogeneic hematopoietic stem cell transplantation. Additionally, these lncRNAs were high stability in plasma exosomes. Exosomal LINC00265, LINC00467, UCA1, and SNHG1 may act as promising cell-free biomarkers for AML diagnosis and treatment monitoring and provide a new frontier of liquid biopsy for this type of cancer. [ABSTRACT FROM AUTHOR]

Objective: Hepatocellular carcinoma (HCC) is amalignant tumor. The occurrence of HCC is involved in the alteration of a variety of oncogenes or tumor suppressor genes, but the specific molecular mechanism remains unknown. This research proved the effects of long non-coding RNA NEAT1 (lncRNA NEAT1) on the viability, proliferation, migration, and invasion of hepatocellular carcinoma cells and explored the mechanism behind these effects. Methods: NEAT1 in 97H and Huh7 cell lines was overexpressed or knocked down, respectively. The expression of FOXP3 and its target gene PKM2 was hinged on qRT-PCR and Western blot, respectively. RNA pulldown and RNA immunoprecipitation experiments were carried out to detect the interaction between NEAT1 and proteins. Finally, the effect of NEAT1 on the tumor volume of HCC was verified by animal experiments. Results: A series of experiments have shown that NEAT1 knockdown can inhibit the viability, proliferation, migration, and invasion of HCC cells; NEAT1 can bind FOXP3 to promote PKM2 transcription; PKM2 knockdown can inhibit the viability, proliferation, migration, and invasion of HCC cells; and PKM2 knockdown reversed the function of NEAT1. Conclusion: lncRNA NEAT1 can promote the malignant behavior of HCC cells, while silencing of NEAT1 can inhibit that behavior of HCC cells. Mechanically, NEAT1 promotes the transcriptional activation of PKM2 by binding FOXP3, and PKM2 knockout reverses the function of NEAT1. [ABSTRACT FROM AUTHOR]

The role of long non-coding RNA (lncRNA) in human tumors has gradually received increasing attention in recent years. Particularly, the different functions of lncRNAs in different subcellular localizations have been widely investigated. The upregulation of lncRNA small nucleolar RNA host gene 17 (SNHG17) has been observed in various human tumors. Growing evidence has proved that SNHG17 plays a tumor-promoting role in tumorigenesis and development. This paper describes the molecular mechanisms by which SNHG17 contributes to tumor formation and development. The different functions of SNHG17 in various subcellular localizations are also emphasized: its function in the cytoplasm as a competing endogenous RNA (ceRNA), its action in the nucleus as a transcriptional coactivator, and its function through the polycomb repressive complex 2 (PRC2)-dependent epigenetic modifications that regulate transcriptional processes. Finally, the correlation between SNHG17 and human tumors is summarized. Its potential as a novel prognostic and diagnostic biomarker for cancer is explored especially. [ABSTRACT FROM AUTHOR]

Objective: Improved molecular testing for common somatic mutations and the identification of mRNA and microRNA expression classifiers are promising approaches for the diagnosis of thyroid nodules. However, there is a need to improve the diagnostic accuracy of such tests for identifying thyroid cancer. Recent findings have revealed a crucial role of long non-coding RNAs (lncRNAs) in gene modulation. Thus, we aimed to evaluate the diagnostic value of selected lncRNAs from The Atlas of Noncoding RNAs in Cancer (TANRIC) thyroid cancer dataset. Methods: LncRNAs in TANRIC thyroid cancer dataset that have significantly increased or decreased expression in papillary thyroid cancer (PTC) tissues were selected as candidates for PTC diagnosis. Surgical specimens from patients who underwent thyroidectomy were used to determine the separation capability of candidate lncRNAs between malignant and benign nodules. Fine needle aspiration samples were obtained and screened for candidate lncRNAs to verify their diagnostic value. Results: LRRC52-AS1, LINC02471, LINC02082, UNC5B-AS1, LINC02408, MPPED2-AS1, LNCNEF, LOC642484, ATP6V0E2-AS1, and LOC100129129 were selected as the candidate lncRNAs. LRRC52-AS1, LINC02082, UNC5B-AS1, MPPED2-AS1, LNCNEF, and LOC100129129 expression levels were significantly increased or decreased in malignant nodules compared to those in benign nodules and paired normal thyroid tissues. The combination of LRRC52-AS1, LINC02082, and UNC5B-AS1 showed favorable results for the diagnosis of PTC from fine needle aspirates, with 88.9% sensitivity and 100.0% specificity. Conclusions: LncRNA expression analysis is a promising approach for advancing the molecular diagnosis of PTC. Further studies are needed to identify lncRNAs of additional diagnostic value. [ABSTRACT FROM AUTHOR]

Background: Early diagnosis of colorectal cancer could significantly improve the prognosis and reduce mortality. However, indeterminate diagnosis is often met in pathology diagnosis in biopsy samples. Abnormal expression of long non-coding RNA (lncRNA) is associated with the initiation and progression of colorectal cancer. It is of great value and clinical significance to explore lncRNAs as candidate diagnostic biomarkers in colorectal cancer. Methods: Based on the within-sample relative expression levels of lncRNA pairs, we identified a group of candidate diagnostic biomarkers for colorectal cancer. In addition, we validated it in independent datasets produced by different laboratories and different platforms. We also tested it in colorectal cancer tissue samples using quantitative real-time polymerase chain reaction (RT-qPCR). Results: A biomarker consisting of six lncRNA pairs including nine lncRNAs was identified for the diagnosis of colorectal cancer. For a total of 950 cancer samples and 247 non-cancer samples, both of the sensitivity and specificity could achieve approximately 90%. For adenoma samples, the accuracy could achieve 73%. For normal tissues from inflammatory bowel disease patients, 93% (14/15) were correctly classified as non-cancer. Furthermore, the lncRNA pair biomarker showed excellent performance in all clinical stages; even in the early stage, the accuracy could achieve 87% and 82% in stage I and II. Meanwhile, the biomarker was also robust to the microsatellite instability status. More importantly, we measured the biomarker in 35 colorectal cancer and 30 cancer-adjacent tissue samples using quantitative real-time polymerase chain reaction (RT-qPCR). The accuracy could achieve 93.3% (70/75). Specially, even in early-stage tumors (I and II), the accuracy could also achieve 90.9% (30/33). The enrichment analysis revealed that these lncRNAs were involved in highly associated cancer pathways and immune-related pathways. Immune analysis showed that these marker lncRNAs were associated with multiple immune cells, implying that they might be involved in the regulation of immune cell functions in colorectal cancer. Most of the biomarker lncRNAs were also differentially expressed between the mutant group and wild-type group of colorectal cancer driver genes. Conclusion: We identified and validated six lncRNA pairs including nine lncRNAs as a biomarker for assisting in the diagnosis of colorectal cancer. [ABSTRACT FROM AUTHOR]

Long non-coding RNA LINC00152 (cytoskeleton regulator, or LINC00152) is an 828-bp lncRNA located on chromosome 2p11.2. LINC00152 was originally discovered during research on hepatocarcinogenesis and has since been regarded as a crucial oncogene that regulates gene expression in many cancer types. LINC00152 is aberrantly expressed in various cancers, including gastric, breast, ovarian, colorectal, hepatocellular, and lung cancer, and glioma. Several studies have indicated that LINC00152 is correlated with cell proliferation, apoptosis, migration, invasion, cell cycle, epithelialmesenchymal transition (EMT), chemotherapy and radiotherapy resistance, and tumor growth and metastasis. High LINC00152 expression in most tumors is significantly associated with poor patient prognosis. Mechanistic analysis has demonstrated that LINC00152 can serve as a competing endogenous RNA (ceRNA) by sponging miRNA, regulating the abundance of the protein encoded by a particular gene, or modulating gene expression at the epigenetic level. LINC00152 can serve as a diagnostic or prognostic biomarker, as well as a therapeutic target for most cancer types. In the present review, we discuss the roles and mechanisms of LINC00152 in human cancer, focusing on its functions in chemotherapy and radiotherapy resistance. [ABSTRACT FROM AUTHOR]

Telomeres arecomplexprotective structures located at theendsof linear eukaryotic chromosomes. Their purpose is to prevent genomic instability. Research progress in telomere biology during the past decades has identified a network of telomeric transcripts of which the best-studied is TElomeric Repeat-containing RNA (TERRA). TERRA was shown to be important not only for the preservation of telomere homeostasis and genomic stability but also for the expression of hundreds of genes across the human genome. These findings added a new level of complexity to telomere biology. Herein we provide insights on the telomere transcriptome, its relevance for proper telomere function, and its implications in human pathology. We also discuss possible clinical opportunities of exosomal telomere transcripts detection as a biomarker in cancer precisionmedicine. [ABSTRACT FROM AUTHOR]

Breast cancer (BC) is one of the frequent tumors that seriously endanger the physical and mental well-being in women with strong heterogeneity, and its pathogenesis involves multiple risk factors. Depending on the type of BC, hormonal therapy, targeted therapy, and immunotherapy are the current systemic treatment options along with conventional chemotherapy. Despite significant progress in understanding BC pathogenesis and therapeutic options, there is still a need to identify new therapeutic targets and develop more effective treatments. According to recent sequencing and profiling studies, non-coding (nc) RNAs genes are deregulated in human cancers via deletion, amplification, abnormal epigenetic, or transcriptional regulation, and similarly, the expression of many ncRNAs is altered in breast cancer cell lines and tissues. The ability of single ncRNAs to regulate the expression of multiple downstream gene targets and related pathways provides a theoretical basis for studying them for cancer therapeutic drug development and targeted delivery. Therefore, it is far-reaching to explore the role of ncRNAs in tumor development and their potential as therapeutic targets. Here, our review outlines the potential of two major ncRNAs, long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) as diagnostic and prognostic biomarkers as well as targets for new therapeutic strategies in breast cancer., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Li, Ji, Ye, Tang, Wang, Chen and Yang.)

Telomeres are complex protective structures located at the ends of linear eukaryotic chromosomes. Their purpose is to prevent genomic instability. Research progress in telomere biology during the past decades has identified a network of telomeric transcripts of which the best-studied is TElomeric Repeat-containing RNA (TERRA). TERRA was shown to be important not only for the preservation of telomere homeostasis and genomic stability but also for the expression of hundreds of genes across the human genome. These findings added a new level of complexity to telomere biology. Herein we provide insights on the telomere transcriptome, its relevance for proper telomere function, and its implications in human pathology. We also discuss possible clinical opportunities of exosomal telomere transcripts detection as a biomarker in cancer precision medicine.

Background and objectivesProstate specific antigen (PSA) is currently the most commonly used biomarker for prostate cancer diagnosis. However, when PSA is in the gray area of 4-10 ng/ml, the diagnostic specificity of prostate cancer is extremely low, leading to overdiagnosis in many clinically false-positive patients. This study was trying to discover and evaluate a novel urine biomarker long non-coding RNA (lncRNA546) to improve the diagnostic accuracy of prostate cancer in PSA gray-zone.MethodsA cohort study including consecutive 440 participants with suspected prostate cancer was retrospectively conducted in multi-urology centers. LncRNA546 scores were calculated with quantitative real-time polymerase chain reaction. The area under the receiver operating characteristic curve (AUROC), decision curve analysis (DCA) and a biopsy-specific nomogram were utilized to evaluate the potential for clinical application. Logistic regression model was constructed to confirm the predictive power of lncRNA546.ResultsLncRNA546 scores were sufficient to discriminate positive and negative biopsies. ROC analysis showed a higher AUC for lncRNA546 scores than prostate cancer antigen 3 (PCA3) scores (0.78 vs. 0.66, p

N7-Methylguanosine (m7G) and long non-coding RNAs (lncRNAs) have been widely reported to play an important role in cancer. However, there is little known about the relationship between m7G-related lncRNAs and esophageal squamous cell carcinoma (ESCC). In this study, we aimed to find new potential biomarkers and construct an m7Grelated lncRNA prognostic signature for ESCC. Three molecular clusters were identified by consensus clustering of 963 m7G-related lncRNAs, of which cluster B is preferentially related to poorer prognosis, higher immune and stromal scores, higher mRNA levels of immune checkpoints, and higher immune infiltrate level. We constructed a robust and effective m7G-related lncRNA prognostic signature (m7G-LPS, including 7 m7G-related prognostic lncRNAs) and demonstrated its prognostic value and predictive ability in the GEO and TCGA cohorts. The risk score was able to serve as an independent risk factor for patients with ESCC and showed better prediction than the traditional clinical risk factors. The immune score, stromal score, the infiltration level of immune cells and expression of immune checkpoints were significantly higher in the high-risk subgroup compared to the low-risk subgroup. The establishment of nomogram further improved the performance of m7G-LPS and facilitated its clinical application. Finally, we used GTEx RNA-seq data and qRT-PCR experiments to verify the expression levels of 7 m7G-related lncRNAs. To a certain degree, m7G-lncRNAs can be used as prognostic markers and therapeutic targets for ESCC patients. [ABSTRACT FROM AUTHOR]

Long non-coding RNAs (IncRNAs) widely regulate gene expression and play Important roles in the pathogenesis of human diseases, including malignant tumors. However, the functions of most IncRNAs remain to be elucidated. In order to study and screen novel IncRNAs with important functions in the carcinogenesis of nasopharyngeal carcinoma (NPC), we constructed a IncRNA expression profile of 10 NPC tissues and 6 controls through a gene microarray. We identified 1,276 IncRNAs, of which most are unknown, with different expression levels in the healthy and NPC tissues. In order to shed light on the functions of these unknown IncRNAs, we first constructed a co-expression network of IncRNAs and mRNAs using bioinformatics and systematic biological approach. Moreover, mRNAs were clustered and enriched by their biological functions, and those IncRNAs have similar expression trends with mRNAs were defined as functional molecules with potential biological significance. The module may help identify key IncRNAs in the carcinogenesis of NPC and provide clues for in-depth study of their functions and associated signaling pathways. We suggest the newly identified IncRNAs may have clinic value as biomarkers and therapeutic targets for NPC diagnosis and treatment. [ABSTRACT FROM AUTHOR]

With completing the whole genome sequencing project, awareness of lncRNA further deepened. The growth arrest-specific transcript 5 (GAS5) was initially identified in growth-inhibiting cells. GAS5 is a lncRNA (long non-coding RNA), and it plays a crucial role in various human cancers. There are small ORFs (open reading frames) in the exons of the GAS5 gene sequence, but they do not encode functional proteins. In addition, GAS5 is also the host gene of several small nucleolar RNAs (snoRNA). These snoRNAs are believed to play a suppressive role during tumor progression by methylating ribosomal RNA (rRNA). As a result, GAS5 expression levels in tumor tissues are significantly reduced, leading to increased malignancy, poor prognosis, and drug resistance. Recent studies have demonstrated that GAS5 can interact with miRNAs by base-pairing and other functional proteins to inhibit their biological functions, impacting signaling pathways and changing the level of intracellular autophagy, oxidative stress, and immune cell function in vivo. In addition, GAS5 participates in regulating proliferation, invasion, and apoptosis through the above molecular mechanisms. This article reviews the recent discoveries on GAS5, including its expression levels in different tumors, its biological behavior, and its molecular regulation mechanism in human cancers. The value of GAS5 as a molecular marker in the prevention and treatment of cancers is also discussed. [ABSTRACT FROM AUTHOR]

The long non-coding RNA (lncRNA) ASAP1-IT1 has been recently shown to aberrantly increase in ovarian and bladder cancer, while its role in other malignancies remains unexplored. This study was to characterize the expression and assess the potential role of ASAP1-IT1 in hepatocellular carcinoma (HCC). Fifty-four paired HCC and histologically normal tissues were obtained from HCC patients. Human HCC cell lines (HepG2, Huh7, SMMC-7721, and BEL-7402) and a normal liver cell line (LO2) were used for in vitro studies. ASAP1-IT1-specific siRNAs were used to silence ASAP1-IT1 expression, while the pcDNA-ASAP1-IT1 vector was constructed to up-regulate its expression. In situ hybridization and qRT-PCR were performed to characterize subcellular localization and expression of ASAP1-IT1. Cell proliferation and migration assays were conducted to examine the role of ASAP1-IT1 in the progression of HCC. In silico analysis was conducted to predict putative miRNA binding sites, which were validated by luciferase reporter assays. ASAP1-IT1 levels were significantly increased in HCC tissues and cells compared with controls. Notably, higher ASAP1-IT1 levels were significantly associated with poorer prognosis of HCC patients. In situ hybridization analysis revealed that ASAP1-IT1 was mainly localized in the nucleus of hepatoma cells and differentially expressed in trabecular, compact, and pseudoglandular forms of liver cancer. Furthermore, knockdown of ASAP1-IT1 significantly suppressed cell proliferation and migration, while its overexpression significantly promoted cell proliferation and migration of HCC cells. Mechanistically, ASAP1-IT1 might exert its role in HCC progression, at least in part, by directly interacting with miR-221-3p. In conclusion, ASAP1-IT1 is abnormally elevated in HCC, and higher levels are correlated with poorer prognosis. An underlying mechanism has been proposed for ASAP1-IT1-associated promotion of proliferation and migration in HCC cells. These findings have provided evidence supporting the oncogenic role of ASAP1-IT1 in HCC. [ABSTRACT FROM AUTHOR]

Purpose: Studies reported that 5-methylcytosine (m5C) RNA transferase alters tumor progression; however, studies of m5C-related lncRNA remain lacking. This article intends to study the lncRNA modified by m5C RNA transferase in hepatocellular carcinoma using a combination of computational biology and basic experiments. Method: We identified 13 m5C RNA transferase-related genes and selected long non-coding RNAs with a Pearson correlation coefficient greater than 0.4. Univariate Cox regression analysis was used to screen m5C RNA transferase lncRNA related to survival phenotype. We divided TCGA-LIHC into two types of m5C RNA using non-negative matrix decomposition. According to WGCNA, the co-expression models of two lncRNA regulation modes were constructed to analyze the characteristic biological processes of the two m5C RNA transferase-related lncRNA gene models. Then, a predictive model of m5C RNA transferase lncRNA was using LASSO regression. Finally, we used cell experiments, transwell experiments, and clone formation experiments to test the relationship between SNHG4 and tumor cell proliferation in Hep-G2 and Hep-3b cells line. Results: We identified 436 m5C RNA transferase-related lncRNAs. Using univariate Cox regression analysis, 43 prognostic-related lncRNAs were determined according to P < 0.001. We divided TCGA-LIHC into two regulation modes of m5C RNA transferase using non-negative matrix factorization. The two regulation modes showed significant differences in overall and disease-free survival. We used LASSO to construct m5c-related lncRNA prognostic signature. Thus, a predictive m5C-lncRNA model was established using four lncRNAs: AC026412.3, AC010969.2, SNHG4, and AP003392.5. The score calculated by the m5C-lncRNA model significantly correlated with the overall survival of hepatocellular carcinoma. The receiver operating characteristic curve and decision curve analysis verified the accuracy of the predictive model. We observed a more robust immune response in the high-risk score group. The transwell experiments and clone formation experiments suggested that m5C RNA transferase-related lncRNA SNHG4 promotes the proliferation and migration of Hep-G2 and Hep-3b cells line. Conclusion: Two lncRNA expression patterns regulated by m5C RNA transferase were identified. The difference between the two expression patterns and the survival phenotype in the biological process was pointed out. A 5-methylcytosine RNA methyltransferases-related lncRNA overall survival signature was constructed. These results provide some understanding of the influence of m5C transferase on hepatocellular carcinoma. The prediction model of m5C transferase lncRNA has potential clinical value in managing hepatocellular carcinoma. [ABSTRACT FROM AUTHOR]

Long non-coding RNAs (lncRNAs) widely regulate gene expression and play important roles in the pathogenesis of human diseases, including malignant tumors. However, the functions of most lncRNAs remain to be elucidated. In order to study and screen novel lncRNAs with important functions in the carcinogenesis of nasopharyngeal carcinoma (NPC), we constructed a lncRNA expression profile of 10 NPC tissues and 6 controls through a gene microarray. We identified 1,276 lncRNAs, of which most are unknown, with different expression levels in the healthy and NPC tissues. In order to shed light on the functions of these unknown lncRNAs, we first constructed a co-expression network of lncRNAs and mRNAs using bioinformatics and systematic biological approach. Moreover, mRNAs were clustered and enriched by their biological functions, and those lncRNAs have similar expression trends with mRNAs were defined as functional molecules with potential biological significance. The module may help identify key lncRNAs in the carcinogenesis of NPC and provide clues for in-depth study of their functions and associated signaling pathways. We suggest the newly identified lncRNAs may have clinic value as biomarkers and therapeutic targets for NPC diagnosis and treatment.

With completing the whole genome sequencing project, awareness of lncRNA further deepened. The growth arrest-specific transcript 5 (GAS5) was initially identified in growth-inhibiting cells. GAS5 is a lncRNA (long non-coding RNA), and it plays a crucial role in various human cancers. There are small ORFs (open reading frames) in the exons of the GAS5 gene sequence, but they do not encode functional proteins. In addition, GAS5 is also the host gene of several small nucleolar RNAs (snoRNA). These snoRNAs are believed to play a suppressive role during tumor progression by methylating ribosomal RNA (rRNA). As a result, GAS5 expression levels in tumor tissues are significantly reduced, leading to increased malignancy, poor prognosis, and drug resistance. Recent studies have demonstrated that GAS5 can interact with miRNAs by base-pairing and other functional proteins to inhibit their biological functions, impacting signaling pathways and changing the level of intracellular autophagy, oxidative stress, and immune cell function in vivo. In addition, GAS5 participates in regulating proliferation, invasion, and apoptosis through the above molecular mechanisms. This article reviews the recent discoveries on GAS5, including its expression levels in different tumors, its biological behavior, and its molecular regulation mechanism in human cancers. The value of GAS5 as a molecular marker in the prevention and treatment of cancers is also discussed.

Increased glycolysis in tumor cells is frequently associated with drug resistance. Overexpression of glucose transporter-1 (GLUT1) promotes the Warburg effect and mediates chemoresistance in various cancers. Aberrant GLUT1 expression is considered as an essential early step in the development of endometrial cancer (EC). However, its role in EC glycolysis and chemoresistance and the upstream mechanisms underlying GLUT1 overexpression, remain undefined. Here, we demonstrated that GLUT1 was highly expressed in EC tissues and cell lines and that high GLUT1 expression was associated with poor prognosis in EC patients. Both gain-of-function and loss-of-function studies showed that GLUT1 increased EC cell proliferation, invasion, and glycolysis, while also making them resistant to paclitaxel. The long non-coding RNA TMPO-AS1 was found to be overexpressed in EC tissues and to be negatively associated with EC patient outcomes. RNA-immunoprecipitation and luciferase reporter assays confirmed that TMPO-AS1 elevated GLUT1 expression by directly binding to two critical tumor suppressor microRNAs (miR-140 and miR-143). Downregulation of TMPO-AS1 remarkably reduced EC cell proliferation, invasion, glycolysis, and paclitaxel resistance in EC cells. This study established that dysregulation of the TMPO-AS1-miR-140/miR-143 axis contributes to glycolysis and drug resistance in EC cells by up-regulating GLUT1 expression. Thus, inhibiting TMPO-AS1 and GLUT1 may prove beneficial in overcoming glycolysis-induced paclitaxel resistance in patients with EC.

The long non-coding RNA (lncRNA) ASAP1-IT1 has been recently shown to aberrantly increase in ovarian and bladder cancer, while its role in other malignancies remains unexplored. This study was to characterize the expression and assess the potential role of ASAP1-IT1 in hepatocellular carcinoma (HCC). Fifty-four paired HCC and histologically normal tissues were obtained from HCC patients. Human HCC cell lines (HepG2, Huh7, SMMC-7721, and BEL-7402) and a normal liver cell line (LO2) were used for in vitro studies. ASAP1-IT1-specific siRNAs were used to silence ASAP1-IT1 expression, while the pcDNA-ASAP1-IT1 vector was constructed to up-regulate its expression. In situ hybridization and qRT-PCR were performed to characterize subcellular localization and expression of ASAP1-IT1. Cell proliferation and migration assays were conducted to examine the role of ASAP1-IT1 in the progression of HCC. In silico analysis was conducted to predict putative miRNA binding sites, which were validated by luciferase reporter assays. ASAP1-IT1 levels were significantly increased in HCC tissues and cells compared with controls. Notably, higher ASAP1-IT1 levels were significantly associated with poorer prognosis of HCC patients. In situ hybridization analysis revealed that ASAP1-IT1 was mainly localized in the nucleus of hepatoma cells and differentially expressed in trabecular, compact, and pseudoglandular forms of liver cancer. Furthermore, knockdown of ASAP1-IT1 significantly suppressed cell proliferation and migration, while its overexpression significantly promoted cell proliferation and migration of HCC cells. Mechanistically, ASAP1-IT1 might exert its role in HCC progression, at least in part, by directly interacting with miR-221-3p. In conclusion, ASAP1-IT1 is abnormally elevated in HCC, and higher levels are correlated with poorer prognosis. An underlying mechanism has been proposed for ASAP1-IT1-associated promotion of proliferation and migration in HCC cells. These findings have provided evidence supporting the oncogenic role of ASAP1-IT1 in HCC.

PurposeStudies reported that 5-methylcytosine (m5C) RNA transferase alters tumor progression; however, studies of m5C-related lncRNA remain lacking. This article intends to study the lncRNA modified by m5C RNA transferase in hepatocellular carcinoma using a combination of computational biology and basic experiments.MethodWe identified 13 m5C RNA transferase-related genes and selected long non-coding RNAs with a Pearson correlation coefficient greater than 0.4. Univariate Cox regression analysis was used to screen m5C RNA transferase lncRNA related to survival phenotype. We divided TCGA-LIHC into two types of m5C RNA using non-negative matrix decomposition. According to WGCNA, the co-expression models of two lncRNA regulation modes were constructed to analyze the characteristic biological processes of the two m5C RNA transferase-related lncRNA gene models. Then, a predictive model of m5C RNA transferase lncRNA was using LASSO regression. Finally, we used cell experiments, transwell experiments, and clone formation experiments to test the relationship between SNHG4 and tumor cell proliferation in Hep-G2 and Hep-3b cells line.ResultsWe identified 436 m5C RNA transferase-related lncRNAs. Using univariate Cox regression analysis, 43 prognostic-related lncRNAs were determined according to P < 0.001. We divided TCGA-LIHC into two regulation modes of m5C RNA transferase using non-negative matrix factorization. The two regulation modes showed significant differences in overall and disease-free survival. We used LASSO to construct m5c-related lncRNA prognostic signature. Thus, a predictive m5C-lncRNA model was established using four lncRNAs: AC026412.3, AC010969.2, SNHG4, and AP003392.5. The score calculated by the m5C-lncRNA model significantly correlated with the overall survival of hepatocellular carcinoma. The receiver operating characteristic curve and decision curve analysis verified the accuracy of the predictive model. We observed a more robust immune response in the high-risk score group. The transwell experiments and clone formation experiments suggested that m5C RNA transferase-related lncRNA SNHG4 promotes the proliferation and migration of Hep-G2 and Hep-3b cells line.ConclusionTwo lncRNA expression patterns regulated by m5C RNA transferase were identified. The difference between the two expression patterns and the survival phenotype in the biological process was pointed out. A 5-methylcytosine RNA methyltransferases-related lncRNA overall survival signature was constructed. These results provide some understanding of the influence of m5C transferase on hepatocellular carcinoma. The prediction model of m5C transferase lncRNA has potential clinical value in managing hepatocellular carcinoma.

Osteosarcoma is one of the most common bone tumors in teenagers. We hope to provide a reliable method to predict the prognosis of osteosarcoma and find potential targets for early diagnosis and precise treatment. To address this issue, we performed a detailed bioinformatics analysis based on the Cancer Genome Atlas (TCGA). A total of 85 osteosarcoma patients with gene expression data and clinicopathological features were included in this study, which was considered the entire set. They were randomly divided into a train set and a test set. We identified six lncRNAs (ELFN1-AS1, LINC00837, OLMALINC, AL669970.3, AC005332.4 and AC023157.3), and constructed a signature that exhibited good predictive ability of patient survival and metastasis. What's more, we found that risk score calculated by the signature was positively correlated to tumor purity, CD4+ naive T cells, and negatively correlated to CD8+ T cells. Furthermore, we investigated each lncRNA in the signature and found that these six lncRNAs were associated with tumorigenesis and immune cells in the tumor microenvironment. In conclusion, we constructed and validated a signature, which had good performance in the prediction of survival, metastasis and immune microenvironment. Our study indicated possible mechanisms of these lncRNAs in the development of osteosarcoma, which may provide new insights into the precise treatment of osteosarcoma. [ABSTRACT FROM AUTHOR]

Background: Genomic instability (GI) is a critical feature of cancer which plays a key role in the occurrence and development of pancreatic adenocarcinoma (PAAD). Long non-coding RNA (LncRNA) is an emerging prognostic biomarker because it is involved in regulating GI. Recently, researchers used such GI-related LncRNAs (GILncRNAs) to establish a prognostic signature for patients with cancer and helped in predicting the overall prognosis of the patients. However, it is evident that patients with PAAD still lack such prognostic signature constructed with GILncRNA. Methods: The present study screened GILncRNAs from 83 patients with PAAD. Prognosis-related GILncRNAs were identified by univariate Cox regression analysis. The correlation coefficients of these GILncRNAs were obtained by multivariate Cox regression analysis and used to construct signatures. The signature in the present study was then assessed through survival analysis, mutation correlation analysis, independent prognostic analysis, and clinical stratification analysis in the training set and validated in the testing as well as all TCGA set. The current study performed external clinical relevance validation of the signature and validated the effect of AC108134.2 in GILncSig on PAAD using in vitro experiments. Finally, the function of GILncRNA signature (GILncSig) dependent on Gene Ontology enrichment analysis was explored and chemotherapeutic drug sensitivity analysis was also performed. Results: Results of the present study found that a total of 409 GILncRNAs were identified, 5 of which constituted the prognostic risk signature in this study, namely, AC095057.3, AC108134.2, AC124798.1, AL606834.1, and AC104695.4. It was found that the signature of the present study was better than others in predicting the overall survival and applied to patients with PAAD of all ages, genders, and tumor grades. Further, it was noted that the signature of the current study in the GSE102238, was correlated with tumor length, and tumor stage of patients with PAAD. In vitro , functional experiments were used in the present study to validate that AC108134.2 is associated with PAAD genomic instability and progression. Notably, results of the pRRophetic analysis in the current study showed that the high-risk group possessed reverse characteristics and was sensitive to chemotherapy. Conclusions: In conclusion, it was evident that the GILncSig used in the present study has good prognostic performance. Therefore, the signature may become a potential sensitive biological indicator of PAAD chemotherapy, which may help in clinical decision-making and management of patients with cancer. [ABSTRACT FROM AUTHOR]

N6-methyladenosine (m6A) modification is the most abundant modification in long noncoding RNAs (lncRNAs). Current studies have shown that the abnormal expression of m6A-related genes is closely associated with the tumorigenesis and progression of glioma. However, the role of m6A-related lncRNAs in glioma development is still unclear. Herein, we screened 566 m6A-related lncRNAs in glioma from The Cancer Genome Atlas (TCGA) database. The expression pattern of these lncRNAs could cluster samples into two groups, in which various classical tumor-related functions and the tumor immune microenvironment were significantly different. Subsequently, a nine-factor m6A-related lncRNA prognostic signature (MLPS) was constructed by using a LASSO regression analysis in the training set and was validated in the test set and independent datasets. The AUC values of the MLPS were 0.881, 0.918 and 0.887 for 1-, 3- and 5-year survival in the training set, respectively, and 0.856, 0.916 and 0.909 for 1-, 3-, and 5-year survival in the test set, respectively. Stratification analyses of the MLPS illustrated its prognostic performance in gliomas with different characteristics. Correlation analyses showed that the infiltrations of monocytes and tumor-associated macrophages (TAMs) were significantly relevant to the risk score in the MLPS. Moreover, we detected the expression of four MLPS factors with defined sequences in glioma and normal cells by using RT–PCR. Afterwards, we investigated the functions of LNCTAM34A (one of the MLPS factors) in glioma cells, which have rarely been reported. Via in vitro experiments , LNCTAM34A was demonstrated to promote the proliferation, migration and epithelial-mesenchymal transition (EMT) of glioma cells. Overall, our study revealed the critical role of m6A-related lncRNAs in glioma and elucidated that LNCTAM34A could promote glioma proliferation, migration and EMT. [ABSTRACT FROM AUTHOR]

Pyroptosis is an inflammatory form of programmed cell death that is involved in various cancers, including hepatocellular carcinoma (HCC). Long non-coding RNAs (lncRNAs) were recently verified as crucial mediators in the regulation of pyroptosis. However, the role of pyroptosis-related lncRNAs in HCC and their associations with prognosis have not been reported. In this study, we constructed a prognostic signature based on pyroptosis-related differentially expressed lncRNAs in HCC. A co-expression network of pyroptosis-related mRNAs–lncRNAs was constructed based on HCC data from The Cancer Genome Atlas. Cox regression analyses were performed to construct a pyroptosis-related lncRNA signature (PRlncSig) in a training cohort, which was subsequently validated in a testing cohort and a combination of the two cohorts. Kaplan–Meier analyses revealed that patients in the high-risk group had poorer survival times. Receiver operating characteristic curve and principal component analyses further verified the accuracy of the PRlncSig model. Besides, the external cohort validation confirmed the robustness of PRlncSig. Furthermore, a nomogram based on the PRlncSig score and clinical characteristics was established and shown to have robust prediction ability. In addition, gene set enrichment analysis revealed that the RNA degradation, the cell cycle, the WNT signaling pathway, and numerous immune processes were significantly enriched in the high-risk group compared to the low-risk group. Moreover, the immune cell subpopulations, the expression of immune checkpoint genes, and response to chemotherapy and immunotherapy differed significantly between the high- and low-risk groups. Finally, the expression levels of the five lncRNAs in the signature were validated by quantitative real-time PCR. In summary, our PRlncSig model shows significant predictive value with respect to prognosis of HCC patients and could provide clinical guidance for individualized immunotherapy. [ABSTRACT FROM AUTHOR]

Background: Despite the availability of advanced technology to detect and treat esophageal squamous cell carcinoma (ESCC), the 5-year survival rate of ESCC patients is still meager. Recently, long non-coding RNAs (lncRNAs) have emerged as essential players in the diagnosis and prognosis of various cancers. Objective: This pilot study focused on identifying circulating lncRNAs as liquid biopsy markers for the ESCC. Methodology: We performed next-generation sequencing (NGS) to profile circulating lncRNAs in ESCC and healthy individuals' blood samples. The expression of the top five upregulated and top five downregulated lncRNAs were validated through quantitative real-time PCR (qRT-PCR), including samples used for the NGS. Later, we explored the diagnostic/prognostic potential of lncRNAs and their impact on the clinicopathological parameters of patients. To unravel the molecular target and pathways of identified lncRNAs, we utilized various bioinformatics tools such as lncRnome, RAID v2.0, Starbase, miRDB, TargetScan, Gene Ontology, and KEGG pathways. Results: Through NGS profiling, we obtained 159 upregulated, 137 downregulated, and 188 neutral lncRNAs in ESCC blood samples compared to healthy individuals. Among dysregulated lncRNAs, we observed LINC00324 significantly upregulated (2.11-fold; p-value = 0.0032) and LOC100507053 significantly downregulated (2.22-fold; p-value = 0.0001) in ESCC patients. Furthermore, we found LINC00324 and LOC100507053 could discriminate ESCC cancer patients' from non-cancer individuals with higher accuracy of Area Under the ROC Curve (AUC) = 0.627 and 0.668, respectively. The Kaplan-Meier and log-rank analysis revealed higher expression levels of LINC00324 and lower expression levels of LOC100507053 well correlated with the poor prognosis of ESCC patients with a Hazard ratio of LINC00324 = 2.48 (95% CI: 1.055 to 5.835) and Hazard ratio of LOC100507053 = 4.75 (95% CI: 2.098 to 10.76)]. Moreover, we also observed lncRNAs expression well correlated with the age (>50 years), gender (Female), alcohol, tobacco, and hot beverages consumers. Using bioinformatics tools, we saw miR-493-5p as the direct molecular target of LINC00324 and interacted with the MAPK signaling pathway in ESCC pathogenesis. Conclusion: This pilot study suggests that circulating LINC00324 and LOC100507053 can be used as a liquid biopsy marker of ESCC; however, multicentric studies are still warranted. [ABSTRACT FROM AUTHOR]

Osteosarcoma is one of the most common bone tumors in teenagers. We hope to provide a reliable method to predict the prognosis of osteosarcoma and find potential targets for early diagnosis and precise treatment. To address this issue, we performed a detailed bioinformatics analysis based on the Cancer Genome Atlas (TCGA). A total of 85 osteosarcoma patients with gene expression data and clinicopathological features were included in this study, which was considered the entire set. They were randomly divided into a train set and a test set. We identified six lncRNAs (ELFN1-AS1, LINC00837, OLMALINC, AL669970.3, AC005332.4 and AC023157.3), and constructed a signature that exhibited good predictive ability of patient survival and metastasis. What’s more, we found that risk score calculated by the signature was positively correlated to tumor purity, CD4+ naive T cells, and negatively correlated to CD8+ T cells. Furthermore, we investigated each lncRNA in the signature and found that these six lncRNAs were associated with tumorigenesis and immune cells in the tumor microenvironment. In conclusion, we constructed and validated a signature, which had good performance in the prediction of survival, metastasis and immune microenvironment. Our study indicated possible mechanisms of these lncRNAs in the development of osteosarcoma, which may provide new insights into the precise treatment of osteosarcoma.

Pyroptosis is an inflammatory form of programmed cell death that is involved in various cancers, including hepatocellular carcinoma (HCC). Long non-coding RNAs (lncRNAs) were recently verified as crucial mediators in the regulation of pyroptosis. However, the role of pyroptosis-related lncRNAs in HCC and their associations with prognosis have not been reported. In this study, we constructed a prognostic signature based on pyroptosis-related differentially expressed lncRNAs in HCC. A co-expression network of pyroptosis-related mRNAs–lncRNAs was constructed based on HCC data from The Cancer Genome Atlas. Cox regression analyses were performed to construct a pyroptosis-related lncRNA signature (PRlncSig) in a training cohort, which was subsequently validated in a testing cohort and a combination of the two cohorts. Kaplan–Meier analyses revealed that patients in the high-risk group had poorer survival times. Receiver operating characteristic curve and principal component analyses further verified the accuracy of the PRlncSig model. Besides, the external cohort validation confirmed the robustness of PRlncSig. Furthermore, a nomogram based on the PRlncSig score and clinical characteristics was established and shown to have robust prediction ability. In addition, gene set enrichment analysis revealed that the RNA degradation, the cell cycle, the WNT signaling pathway, and numerous immune processes were significantly enriched in the high-risk group compared to the low-risk group. Moreover, the immune cell subpopulations, the expression of immune checkpoint genes, and response to chemotherapy and immunotherapy differed significantly between the high- and low-risk groups. Finally, the expression levels of the five lncRNAs in the signature were validated by quantitative real-time PCR. In summary, our PRlncSig model shows significant predictive value with respect to prognosis of HCC patients and could provide clinical guidance for individualized immunotherapy.