Identification and Validation of a Novel 2-LncRNAs Signature Associated with m6A Regulation in Colorectal Cancer.
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ABSTRACT:
SUBMITTER: Wang K
PROVIDER: S-EPMC8692696 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundLong non-coding RNAs (lncRNAs) play an important role in angiogenesis, immune response, inflammatory response and tumor development and metastasis. m6 A (N6-methyladenosine) is one of the most common RNA modifications in eukaryotes. The aim of our research was to investigate the potential prognostic value of m6A-related lncRNAs in ovarian cancer (OC).MethodsThe data we need for our research was downloaded from the Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) database. Pearson correlation analysis between 21 m6A regulators and lncRNAs was performed to identify m6A-related lncRNAs. Univariate Cox regression analysis was implemented to screen for lncRNAs with prognostic value. A least absolute shrinkage and selection operator (LASSO) Cox regression and multivariate Cox regression analyses was used to further reduct the lncRNAs with prognostic value and construct a m6A-related lncRNAs signature for predicting the prognosis of OC patients.ResultsTwo hundred seventy-five m6A-related lncRNAs were obtained using pearson correlation analysis. 29 m6A-related lncRNAs with prognostic value was selected through univariate Cox regression analysis. Then, a seven m6A-related lncRNAs signature was identified by LASSO Cox regression. Each patient obtained a riskscore through multivariate Cox regression analyses and the patients were classified into high-and low-risk group using the median riskscore as a cutoff. Kaplan-Meier curve revealed that the patients in high-risk group have poor outcome. The receiver operating characteristic curve revealed that the predictive potential of the m6A-related lncRNAs signature for OC was powerful. The predictive potential of the m6A-related lncRNAs signature was successfully validated in the GSE9891, GSE26193 datasets and our clinical specimens. Multivariate analyses suggested that the m6A-related lncRNAs signature was an independent prognostic factor for OC patients. Moreover, a nomogram based on the expression level of the seven m6A-related lncRNAs was established to predict survival rate of patients with OC. Finally, a competing endogenous RNA (ceRNA) network associated with the seven m6A-related lncRNAs was constructed to understand the possible mechanisms of the m6A-related lncRNAs involed in the progression of OC.ConclusionsIn conclusion, our research revealed that the m6A-related lncRNAs may affect the prognosis of OC patients and identified a seven m6A-related lncRNAs signature to predict the prognosis of OC patients.
| S-EPMC9178823 | biostudies-literature
Project description:BackgroundBoth N6-methyladenosine (m6A) modification and lncRNAs play an important role in the carcinogenesis and cancer inhibition of ovarian cancer (OC). However, lncRNAs involved in m6A regulation (LI-m6As) have never been reported in OC. Herein, we aimed to identify and validate a signature based on LI-m6A for OC.MethodsRNA sequencing profiles with corresponding clinical information associated with OC and 23 m6A regulators were extracted from TCGA. The Pearson correlation coefficient (PCC) between lncRNAs and 23 m6A regulators (|PCC|> 0.4 and p < 0.01) was calculated to identify LI-m6As. The LI-m6As with significant prognostic value were screened based on univariate Cox regression analysis to construct a risk model by LASSO Cox regression. Gene Set Enrichment Analysis (GSEA) was implemented to survey the biological functions of the risk groups. Several clinicopathological characteristics were utilized to evaluate their ability to predict prognosis, and a nomogram was constructed to evaluate the accuracy of survival prediction. Besides, immune microenvironment, checkpoint, and drug sensitivity in the two risk groups were compared using comprehensive algorithms. Finally, real-time qPCR analysis and cell counting kit-8 assays were performed on an alternative lncRNA, CACNA1G-AS1.ResultsThe training cohort involving 258 OC patients and the validation cohort involving 111 OC patients were downloaded from TCGA. According to the PCC between the m6A regulators and lncRNAs, 129 LI-m6As were obtained to perform univariate Cox regression analysis and then 10 significant prognostic LI-m6As were identified. A prognostic signature containing four LI-m6As (AC010894.3, ACAP2-IT1, CACNA1G-AS1, and UBA6-AS1) was constructed according to the LASSO Cox regression analysis of the 10 LI-m6As. The prognostic signature was validated to show completely opposite prognostic value in the two risk groups and adverse overall survival (OS) in several clinicopathological characteristics. GSEA indicated that differentially expressed genes in disparate risk groups were enriched in several tumor-related pathways. At the same time, we found significant differences in some immune cells and chemotherapeutic agents between the two groups. An alternative lncRNA, CACNA1G-AS1, was proven to be upregulated in 30 OC specimens and 3 OC cell lines relative to control. Furthermore, knockdown of CACNA1G-AS1 was proven to restrain the multiplication capacity of OC cells.ConclusionsBased on the four LI-m6As (AC010894.3, ACAP2-IT1, CACNA1G-AS1, and UBA6-AS1), the risk model we identified can independently predict the OS and therapeutic value of OC. CACNA1G-AS1 was preliminarily proved to be a malignant lncRNA.
| S-EPMC8268297 | biostudies-literature
Project description:Pyroptosis is an inflammatory form of cell death triggered by certain inflammasomes. However, research concerning pyroptosis-related lncRNAs in hepatocellular carcinoma (HCC) remains scarce. This study aims to explore the prognostic pyroptosis-related long non-coding RNAs (lncRNAs) of HCC patients. Data of 373 HCC patients were obtained from the TCGA database. The entire cohort was randomly divided into a training cohort and a validation cohort in a 2:1 ratio. Pyroptosis-related lncRNAs were identified by the Pearson correlation analysis with reported pyroptosis-related genes. LASSO Cox regression was used to construct the signature. A prognostic signature consisting of nine pyroptosis-related lncRNAs was identified, and patients with lower risk scores had a better prognosis than those with higher risk scores. Multivariate Cox regression analysis showed that the signature was an independent risk factor for prognosis in both the training and validation cohorts. In the training cohort, the area under the signature curve reached 0.8043 at 1-year, 0.7878 at 2-year, and 0.8118 at 3-year; in the validation cohort, it reached 0.7315 at 1-year, 0.7372 at 2-year, and 0.7222 at 3-year. Gene set enrichment analysis (GSEA) suggested associations between the signature and several immune-related pathways. The expression of multiple immune checkpoints was also increased in the high-risk group, including PD-1, PD-L1, CTLA4, B7-H3, VSIR, LAG3, and TIGIT. A novel pyroptosis-related lncRNA signature, which may be associated with tumor immunity and potentially serve as an indicator for immunotherapy, has been identified to precisely predict the prognosis of HCC patients.
| S-EPMC9133103 | biostudies-literature
Project description:The RNA methylation of N6 adenosine (m6A) plays a crucial role in various biological processes. Strong evidence reveals that the dysregulation of long non-coding RNAs (lncRNA) brings about the abnormality of downstream signaling in multiple ways, thus influencing tumor initiation and progression. Currently, it is essential to discover effective and succinct molecular biomarkers for predicting colorectal cancer (CRC) prognosis. However, the prognostic value of m6A-related lncRNAs for CRC remains unclear, especially for progression-free survival (PFS). Here, we screened 24 m6A-related lncRNAs in 622 CRC patients and identified five lncRNAs (SLCO4A1-AS1, MELTF-AS1, SH3PXD2A-AS1, H19 and PCAT6) associated with patient PFS. Compared to normal samples, their expression was up-regulated in CRC tumors from TCGA dataset, which was validated in 55 CRC patients from our in-house cohort. We established an m6A-Lnc signature for predicting patient PFS, which was an independent prognostic factor by classification analysis of clinicopathologic features. Moreover, the signature was validated in 1,077 patients from six independent datasets (GSE17538, GSE39582, GSE33113, GSE31595, GSE29621, and GSE17536), and it showed better performance than three known lncRNA signatures for predicting PFS. In summary, our study demonstrates that the m6A-Lnc signature is a promising biomarker for forecasting patient PFS in CRC.
| S-EPMC9407446 | biostudies-literature
Project description:Background: Colorectal cancer is the fourth most deadly cancer worldwide. Although current treatment regimens have prolonged the survival of patients, the prognosis is still unsatisfactory. Inflammation and lncRNAs are closely related to tumor occurrence and development in CRC. Therefore, it is necessary to establish a new prognostic signature based on inflammation-related lncRNAs to improve the prognosis of patients with CRC. Methods: LASSO-penalized Cox analysis was performed to construct a prognostic signature. Kaplan-Meier curves were used for survival analysis and ROC curves were used to measure the performance of the signature. Functional enrichment analysis was conducted to reveal the biological significance of the signature. The R package "maftool" and GISTIC2.0 algorithm were performed for analysis and visualization of genomic variations. The R package "pRRophetic", CMap analysis and submap analysis were performed to predict response to chemotherapy and immunotherapy. Results: An effective and independent prognostic signature, IRLncSig, was constructed based on sixteen inflammation-related lncRNAs. The IRLncSig was proved to be an independent prognostic indicator in CRC and was superior to clinical variables and the other four published signatures. The nomograms were constructed based on inflammation-related lncRNAs and detected by calibration curves. All samples were classified into two groups according to the median value, and we found frequent mutations of the TP53 gene in the high-risk group. We also found some significantly amplificated regions in the high-risk group, 8q24.3, 20q12, 8q22.3, and 20q13.2, which may regulate the inflammatory activity of cancer cells in CRC. Finally, we identified chemotherapeutic agents for high-risk patients and found that these patients were more likely to respond to immunotherapy, especially anti-CTLA4 therapy. Conclusion: In short, we constructed a new signature based on sixteen inflammation-related lncRNAs to improve the outcomes of patients in CRC. Our findings have proved that the IRLncSig can be used as an effective and independent marker for predicting the survival of patients with CRC.
| S-EPMC9561096 | biostudies-literature
Project description:Pyroptosis is a newly discovered programmed cell death mechanism involved in tumorigenesis. Long non-coding RNAs (lncRNAs) have been implicated in colorectal cancer (CRC). However, the potential role of pyroptosis-related lncRNAs (PRLs) in CRC remains unelucidated. Therefore, we retrieved transcriptomic data of CRC patients from The Cancer Genome Atlas (TCGA). With the use of univariate and multivariate Cox proportional hazards regression models and the random forest algorithm, a new risk model was constructed based on eight PRLs: Z99289.2, FENDRR, CCDC144NL-ASL, TEX41, MNX1-AS1, NKILA, LINC02798, and LINC02381. Then, according to the Kaplan-Meier plots, the relationship of PRLs with the survival of CRC patients was explored and validated with our risk model in external datasets (Gene Expression Omnibus (GEO) databases; GEO17536, n = 177, and GSE161158, n = 250). To improve its clinical utility, a nomogram combining PRLs that could predict the clinical outcome of CRC patients was established. A full-spectrum immune landscape of CRC patients mediated by PRLs could be described. The PRLs were stratified into two molecular subtypes involved in immune modulators, immune infiltration of tumor immune microenvironment, and inflammatory pathways. Afterward, Tumor Immune Dysfunction and Exclusion (TIDE) and microsatellite instability (MSI) scores were analyzed. Three independent methods were applied to predict PRL-related sensitivity to chemotherapeutic drugs. Our comprehensive analysis of PRLs in CRC patients demonstrates a potential role of PRLs in predicting response to treatment and prognosis of CRC patients, which may provide a better understanding of molecular mechanisms underlying CRC pathogenesis and facilitate the development of effective immunotherapy.
| S-EPMC9748486 | biostudies-literature
Project description:The colorectal cancer (CRC) is one of the leading causes of cancer-related death worldwide, but the pathogenesis of CRC remains not well-known. Increasing studies have highlighted the critical roles of long noncoding RNAs (lncRNAs) in tumorigenesis and cancer cells metastasis, however, the expression pattern, biological roles of lncRNAs, and the mechanisms responsible for their function in CRC remain elusive. In this study, we performed a genome-wide comprehensive analysis of lncRNAs profiling and clinical relevance to identify novel lncRNAs for the further study in CRC. RNA sequencing and microarray data obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) were annotated and analyzed to find differentially expressed lncRNAs in CRC. Analysis of these datasets revealed that hundreds of lncRNAs expression are dysregulated in CRC tissues when compared with normal tissues. By genomic variation analyses, we identified that some of these lncRNAs dysregulation is associated with the copy number amplification or deletion. Moreover, many lncRNAs expression levels are significantly associated with CRC patients overall and recurrence-free survivals, such as H19, LEF1-AS1, and RP11-296E3.2. Furthermore, we identified one liver metastasis-associated lncRNA termed LUCAT1 in CRC by analyzing lncRNAs expression profiles in the CRC tissues from patients with liver metastasis compared with the CRC tissues without metastasis. Finally, loss-of-function assays determined that knockdown of LUCAT1 could impair CRC cells invasion. Taken together, aberrantly expressed lncRNAs may play critical roles in the development and liver metastasis of CRC, and our findings may provide useful resource for identification of novel biomarkers of CRC.
| S-EPMC5633553 | biostudies-other
Project description:The aim of this study is to explore the differentially expressed lncRNAs, which may have potential biological function and diagnostic value in colorectal cancer (CRC). Through integrated data mining, we finally identified nine differentially expressed lncRNAs and their potential mRNA targets. After a series of bioinformatics analyses, we screened significant pathways and GO terms that are related to the up-regulated and down-regulated transcripts respectively. Meanwhile, the nine lncRNAs were validated in 30 paired tissues and cell lines by qRT-PCR and the results were basically consistent with the microarray data. We also tested the nine lncRNAs in the serum of 30 CRC patients matched with the CRC tissue, 30 non-cancer patients and 30 health controls. Finally, we found that BLACAT1 was significant for the diagnosis of CRC. The area under the curve (AUC), sensitivity and specificity were 0.858 (95% CI: 0.765-0.951), 83.3% and 76.7% respectively between CRC patients and health controls. Moreover, BLACAT1 also had distinct value to discriminate CRC from other non-cancer diseases. The results indicated that the differentially expressed lncRNAs and their potential target transcripts could be considered as potential therapeutic targets for CRC patients. Meanwhile, lncRNA BLACAT1 might represent a new supplementary biomarker for the diagnosis of CRC.
| S-EPMC5390272 | biostudies-literature
Project description:BackgroundColorectal cancer (CRC) is one of the deadliest tumours, but its pathogenesis remains unclear. The involvement of differentially expressed long non-coding RNAs (lncRNAs) in CRC tumorigenesis makes them suitable tumour biomarkers.Methods/findingsHere, we screened 150 cases of CRC and 85 cases of paracancerous tissues in the GEO database for differentially expressed lncRNAs. The levels of lncRNA candidates in 84 CRC and paracancerous tissue samples were validated by qRT-PCR and their clinical significance was analyzed. We identified 15 lncRNAs with differential expression in CRC tumours; among them, AK098081 was significantly up-regulated, whereas AK025209, BC040303, BC037331, AK026659, and CR749831 were down-regulated in CRC. In a receiver operating characteristic curve analysis, the area under the curve for the six lncRNAs was 0.914. High expression of AK098081 and low expression of BC040303, CR749831, and BC037331 indicated poor CRC differentiation. CRC patients with lymph node metastasis had lower expression of BC037331. In addition, the group with high AK098081 expression presented significantly lower overall survival and disease-free survival rates than the low-expression group, confirming AK098081 as an independent risk factor for CRC patients.Conclusion/significanceIn conclusion, we have identified multiple CRC-associated lncRNAs from microarray expression profiles that can serve as novel biomarkers for the diagnosis and prognosis of CRC.
| S-EPMC5082825 | biostudies-literature
Project description:Laryngeal cancer (LC), a highly fatal tumor in the head and neck region, has been the focus of research in recent years. The study of LC has primarily focused on the role of long non-coding RNAs (lncRNAs) in regulating gene expression, as they have emerged as pivotal factors in this biological process. Additionally, a reversible RNA modification called N6-methyladenosine (m6A) has been observed to have a significant impact on gene expression as well. The purpose of this research is to investigate the impact of m6A-related lncRNAs on the prognosis of laryngeal squamous cell carcinoma (LSCC). Specifically, this investigation analyzed the m6A-related regulators' patterns of expression and mutation, encompassing a total of 15 regulators. Drawing upon the expression levels of prognostic m6A-regulated lncRNAs, two distinct lncRNA clusters were identified. Further analysis revealed differentially expressed lncRNAs between these clusters. In addition to studying the expression of lncRNAs, the researchers also examined the distribution of clinical characteristics and the tumor microenvironment (TME) in relation to the identified lncRNA clusters. This provided valuable insights into potential associations between lncRNA expression patterns and the clinical features of LSCC. Through the establishment of a risk model associated with lncRNAs, we were able to further investigate their clinical features, prognosis, and immune status. Additionally, we conducted a separate analysis of LINC00528, a lncRNA associated with smoking, examining its expression, overall survival time, correlated mRNAs, and conducting enrichment of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG), as well as determining the sensitivity of related drugs. RT-qPCR results also indicated an increase in LINC00528 expression among smoking LSCC patients. The findings suggest that a high expression level of LINC00528 in LSCC patients may lead to a more favorable prognosis, providing new insights for the management and treatment of LSCC patients, particularly those with high expression of LINC00528. Overall, this research sheds light on the prognostic impact of m6A-regulated lncRNAs in LSCC. The implications of these findings for the advancement of innovative therapeutic approaches for LSCC patients are noteworthy.
| S-EPMC10666777 | biostudies-literature