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Aerial View of the Association Between m6A-Related LncRNAs and Clinicopathological Characteristics of Pancreatic Cancer.

ABSTRACT: Pancreatic cancer is a highly malignant tumor with a poor survival prognosis. We attempted to establish a robust prognostic model to elucidate the clinicopathological association between lncRNA, which may lead to poor prognosis by influencing m6A modification, and pancreatic cancer. We investigated the lncRNAs expression level and the prognostic value in 440 PDAC patients and 171 normal tissues from GTEx, TCGA, and ICGC databases. The bioinformatic analysis and statistical analysis were used to illustrate the relationship. We implemented Pearson correlation analysis to explore the m6A-related lncRNAs, univariate Cox regression and Kaplan-Meier methods were performed to identify the seven prognostic lncRNAs signatures. We inputted them in the LASSO Cox regression to establish a prognostic model in the TCGA database, verified in the ICGC database. The AUC of the ROC curve of the training set is 0.887, while the validation set is 0.711. Each patient has calculated a risk score and divided it into low-risk and high-risk subgroups by the median value. Moreover, the model showed a robust prognostic ability in the stratification analysis of different risk subgroups, pathological grades, and recurrence events. We established a ceRNA network between lncRNAs and m6A regulators. Enrichment analysis indicated that malignancy-associated biological function and signaling pathways were enriched in the high-risk subgroup and m6A-related lncRNAs target mRNA. We have even identified small molecule drugs, such as Thapsigargin, Mepacrine, and Ellipticine, that may affect pancreatic cancer progression. We found that seven lncRNAs were highly expressed in tumor patients in the GTEx-TCGA database, and LncRNA CASC19/UCA1/LINC01094/LINC02323 were confirmed in both pancreatic cell lines and FISH relative quantity. We provided a comprehensive aerial view between m6A-related lncRNAs and pancreatic cancer's clinicopathological characteristics, and performed experiments to verify the robustness of the prognostic model.

SUBMITTER: Huang B

PROVIDER: S-EPMC8762256 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Background:N6-methyladenosine (m6A) modification holds an important position in tumorigenesis and metastasis because it can change gene expression and even function in multiple levels including RNA splicing, stability, translocation and translation. In present study, we aim to conducted comprehensive investigation on m6A RNA methylation regulators and m6A-related genes in pancreatic cancer and their association with survival time. Methods:Based on Univariate Cox regression analysis, protein-protein interaction analysis, LASSO Cox regression, a risk prognostic model, STRING, Spearman and consensus clustering analysis, data from The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) database was used to analyze 15 m6A RNA methylation regulators that were widely reported and 1,393 m6A-related genes in m6Avar. Results:We found that 283 candidate m6A RNA methylation-related genes and 4 m6A RNA methylation regulatory factors, including RNA binding motif protein 15 (RBM15), methyltransferase like 14 (METTL14), fat mass and obesity-associated protein (FTO), and ?-ketoglutarate-dependent dioxygenase AlkB homolog 5 (ALKBH5), differed significantly among different stages of the American Joint Committee on Cancer (AJCC) staging system. Protein-protein interaction analysis indicated epidermal growth factor receptor (EGFR), plectin-1 (PLEC), BLM RecQ like helicase (BLM), and polo like kinase 1 (PLK1) were closely related to other genes and could be considered as hub genes in the network. The results of LASSO Cox regression and the risk prognostic model indicated that AJCC stage, stage T and N, KRAS mutation status and x8q23.3 CNV fragment mutation differed significantly between the high-risk and the low-risk subgroups. The AUCs of 1 to 5 years after surgery were all more than 0.7 and increased year by year. Finally, we found KRAS mutation status and AJCC stage differed significantly among these groups after TCGA samples divided into subgroups with k=7. Moreover, we identified four m6A RNA methylation related genes expressed significantly differently among these seven subgroups, including collagen type VII alpha 1 chain (COL7A1), branched chain amino acid transaminase 1 (BCAT1), zinc finger protein 596 (ZNF596), and PLK1. Conclusions:Our study systematically analyzed the m6A RNA methylation related genes, including expression, protein-protein interaction, potential function, and prognostic value and provides important clues to further research on the function of RNA m6A methylation and its related genes in pancreatic cancer.

Project description:Simple Summary Hepatocellular carcinoma (HCC) is known for its poor prognosis, but the markers for prognosis still remain unclear to date. This study focused on the long non-coding RNAs (lncRNAs) that linked with cuproptosis and N6-methyladenosine (m6A) in HCC, using data from the The Cancer Genetic Atlas (TCGA) database. The identified lncRNAs were used to develop a risk assessment model through specific types of statistical analysis. This model helped explore how different risk profiles affect the tumor’s genetic mutation load and the surrounding immune environment. Five particular lncRNAs were found to be significant in survival rates, and certain genes (TP53 and CTNNB1) were frequently mutated in high-risk patients. Interestingly, high-risk patients with a low genetic mutation load had the poorest survival rates, while low-risk patients with a high mutation load had the best survival rates. Furthermore, high-risk cases showed increased activity in certain cellular pathways, such as the cell cycle and glucose production. This study resulted in a promising lncRNA model that could potentially help in assessing and managing HCC. However, further studies are needed to confirm these findings. Abstract Cuproptosis and N6-methyladenosine (m6A) have potential as prognostic predictors in cancer patients, but their roles in hepatocellular carcinoma (HCC) are unclear. This study aimed to screen a total of 375 HCC samples were retrieved from the TCGA database, and lncRNAs related to cuproptosis and m6A were obtained through correlation analysis. To construct a risk assessment model, univariate Cox regression analysis and LASSO Cox regression were employed. Analyze the regulatory effect of relevant risk assessment models on tumor mutation load (TMB) and immune microenvironment. A total of five lncRNAs (AC007405.3, AL031985.3, TMCC1-AS1, MIR210HG, TMEM220-AS1) with independent overall survival-related risk models were obtained by LASSO survival regression. TP53 and CTNNB1 were the three genes found to have the most mutations in high-risk group patients. The high-risk group with low TMB had the worst survival, whereas the low-risk group with high TMB had the best survival. KEGG pathway analysis revealed that the high-risk group was enriched with cell cycle, oocyte meiosis, cell senescence, and glycolysis/glucose production pathways. We constructed a reliable cuproptosis- and m6A-related lncRNA model for the prognosis of HCC. The model may provide new insights into managing HCC patients, but further research is needed to validate it.

Project description:ObjectiveThe purpose of the present study was to evaluate the associations between seven tagging single nucleotide polymorphisms (tSNPs) and risk of breast cancer assessed by tumor pathological characteristics and body mass index (BMI).MethodsSeven tSNPs of four breast cancer susceptibility genes were analyzed in 734 Chinese women with breast cancer and 672 age-matched healthy controls; then, the association with clinicopathological characteristics, BMI, molecular subtype, TNM (T, tumor; N, lymph node; M, metastasis) staging and lymph node status was determined by unconditional logistic regression.ResultsRs12951053 in TP53 and rs16945628 in BRIP1, displayed increased risk of breast cancer in the BMI ≧ 25 kg/m2 group (OR=1.50, 95% CI: 1.02-2.21, P=0.041 and OR=1.92, 95% CI: 1.13-3.26, P=0.015, respectively). The other five tSNPs (rs1805812, rs2735385 and rs6999227 in NBS1, rs7220719 in BRIP1 and rs2299941 in PTEN) displayed a decreased risk of breast cancer in the 18.5≤BMI<25 kg/m2 group. Rs12951053 in TP53 and rs7220719 in BRIP1 exhibited an increased risk of triple-negative breast cancer (OR=1.50, 95% CI: 1.05-2.15, P=0.026 and OR=2.13, 95% CI: 1.05-4.29, P=0.032, respectively), but three tSNPs in NBS1 (rs1805812, rs2735385 and rs6999227) all displayed a negative association with both luminal B and triple-negative breast cancer. The tSNP rs2299941 in PTEN also exhibited a negative association with each molecular subtype, except triple-negative breast cancer. The majority of tSNPs displayed a negative association with stage II or III breast cancer. Most tSNPs showed a negative association with breast cancer that was lymph node negative or with 1-3 positive nodes. Only rs12951053 in TP53 displayed a positive association with lymph node-negative breast cancer (OR=1.43, 95% CI: 1.08-1.91, P=0.013).ConclusionThe majority of tSNPs displayed a negative association with breast cancer and only a few tSNPs (rs12951053 in TP53, rs16945628 and rs7220719 in BRIP1) showed an increased risk of breast cancer as defined by clinicopathological characteristics.

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Aerial View of the Association Between m6A-Related LncRNAs and Clinicopathological Characteristics of Pancreatic Cancer.

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