Dataset Information

Development and validation of prognostic m6A-related lncRNA and mRNA model in thyroid cancer.

ABSTRACT: Although N6-methyladenosine (m6A) regulators and lncRNAs influence the carcinogenesis of thyroid cancer (THCA), the association between m6A-related lncRNAs and THCA remains unexplored. Therefore, we have developed and validated a prognostic model based on m6A-related lncRNAs and mRNAs in THCA. Data from the Cancer Genome Atlas were used to analyze the expression and prognostic characteristics of m6A-related lncRNAs and mRNAs in THCA. Univariate Cox regression analysis was used to screen out independent prognostic factors, while Lasso Cox regression was performed to construct m6A-related lncRNA and mRNA models. The correlation between the prognostic models and gene mutation, immune cell infiltration, tumor microenvironment score, tumor mutational burden, and microsatellite instability were assessed. The prognostic models showed excellent accuracy in predicting the prognosis of patients with THCA. Our study established an m6A-related nomogram capable of predicting the prognosis of patients with THCA. In addition, the hub lncRNAs and mRNAs provide insight into improving the prognosis of THCA. These findings can improve our understanding of m6A modifications in THCA and the prognosis and treatment strategies of THCA.

SUBMITTER: Zhu Y

PROVIDER: S-EPMC9360246 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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Development and validation of prognostic m6A-related lncRNA and mRNA model in thyroid cancer.

Zhu Yu Y Yu Tian T Huang Ju J Ma Xitao X Shen Tao T Li Annuo A Yue Rensong R

American journal of cancer research 20220715 7

Although N6-methyladenosine (m6A) regulators and lncRNAs influence the carcinogenesis of thyroid cancer (THCA), the association between m6A-related lncRNAs and THCA remains unexplored. Therefore, we have developed and validated a prognostic model based on m6A-related lncRNAs and mRNAs in THCA. Data from the Cancer Genome Atlas were used to analyze the expression and prognostic characteristics of m6A-related lncRNAs and mRNAs in THCA. Univariate Cox regression analysis was used to screen out inde ...[more]

PMID: 35968348

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Project description:BackgroundColonic adenocarcinoma (COAD) is a common gastrointestinal tract tumor, and its occurrence and progression are typically associated with genomic instability, tumor-suppressor gene and oncogene mutations, and tumor mutational load. N6-methyladenosine (m6A) modification of RNAs and long non-coding RNA (lncRNA) expression are important in tumorigenesis and progression. However, the regulatory roles of m6A-associated lncRNAs in the tumor microenvironment, stratification of prognosis, and immunotherapy are unclear.MethodsWe screened 43 prognostic lncRNAs linked to m6A and performed consistent molecular typing of COAD using consensus clustering. The single-sample Gene Set Enrichment Analysis and ESTIMATE algorithms were used to assess the immune characteristics of different subgroups. Covariation between methylation-related prognostic lncRNAs was eliminated by least absolute shrinkage and selection operator Cox regression. A nomogram was created and evaluated by combining the methylation-related prognostic lncRNA model with other clinical factors. The relationship between the prognostic model grouping and microsatellite instability, immunophenotype score, and tumor mutation burden was validated using R scripts. Finally, we used a linkage map to filter sensitive medicines to suppress the expression of high-risk genes. Three m6A-associated lncRNA modes were identified in 446 COAD specimens with different clinical endpoints and biological statuses. Risk scores were constructed based on the m6A-associated lncRNA signature genes. Patients with lower risk scores showed superior immunotherapy responses and clinical benefits compared to those with higher risk scores. Lower risk scores were also correlated with higher immunophenotype scores, tumor mutation burden, and mutation rates in significantly mutated genes (e.g., FAT4 and MUC16). Piperidolate, quinostatin, and mecamylamin were screened for their abilities to suppress the expression of high-risk genes in the model.ConclusionsQuantitative assessment of m6A-associated lncRNAs in single tumors can enhance the understanding of tumor microenvironment profiles. The prognostic model constructed using m6A-associated lncRNAs may facilitate prognosis and immunotherapy stratification of patients with COAD; finally, three drugs with potential therapeutic value were screened based on the model.

Project description:BackgroundLung cancer has been a prominent research focus in recent years due to its role in cancer-related fatalities globally, with lung adenocarcinoma (LUAD) being the most prevalent histological form. Nonetheless, no signature of lactate metabolism-related long non-coding RNAs (LMR-lncRNAs) has been developed for patients with LUAD. Accordingly, we aimed to develop a unique LMR-lncRNA signature to determine the prognosis of patients with LUAD.MethodThe Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases were utilized to derive the lncRNA expression patterns. Identification of LMR-lncRNAs was accomplished by analyzing the co-expression patterns between lncRNAs and LMR genes. Subsequently, the association between lncRNA levels and survival outcomes was determined to develop an effective signature. In the TCGA cohort, Cox regression was enlisted to build an innovative signature consisting of three LMR-lncRNAs, which was validated in the GEO validation cohort. GSEA and immune infiltration analysis were conducted to investigate the functional annotation of the signature and the function of each type of immune cell.ResultsFourteen differentially expressed LMR-lncRNAs were strongly correlated with the prognosis of patients with LUAD and collectively formed a new LMR-lncRNA signature. The patients could be categorized into two cohorts based on their LMR-lncRNA signatures: a low-risk and high-risk group. The overall survival of patients with LUAD in the high-risk group was considerably lower than those in the low-risk group. Using Cox regression, this signature was shown to have substantial potential as an independent prognostic factor, which was further confirmed in the GEO cohort. Moreover, the signature could anticipate survival across different groups based on stage, age, and gender, among other variables. This signature also correlated with immune cell infiltration (including B cells, neutrophils, CD4+ T cells, CD8+ T cells, etc.) as well as the immune checkpoint blockade target CTLA-4.ConclusionWe developed and verified a new LMR-lncRNA signature useful for anticipating the survival of patients with LUAD. This signature could give potentially critical insight for immunotherapy interventions in patients with LUAD.

Dataset Information

Development and validation of prognostic m6A-related lncRNA and mRNA model in thyroid cancer.

Publications

Development and validation of prognostic m6A-related lncRNA and mRNA model in thyroid cancer.

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