Downregulation of lncRNA EPB41L4A-AS1 promotes gastric cancer cell proliferation, migration and invasion

BMC Gastroenterology, Journal Year: 2024, Volume and Issue: 24(1)

Published: April 16, 2024

Abstract Background The incidence of gastric cancer ranks the first among digestive tract tumors in China. However, there are no specific symptoms early stage tumor and diagnosis process is complex, so more effective detection methods very needed. In this study, a novel long noncoding RNA (lncRNA) was introduced as diagnostic biomarker for cancer, which brought new thinking to exploration its pathological mechanism clinical prediction. Methods level lncRNA EPB41L4A-AS1 (EPB41L4A-AS1) serum cells verified via real-time quantitative polymerase chain reaction (RT-qPCR). Receiver operating characteristic (ROC) curve performed based on level, possibility EPB41L4A-AS analyzed. chi-square test evaluated correlation between expression information. were cultured transfected vitro, mediations abnormal viability motility through cell counting kit-8 (CCK-8) Transwell assay. Furthermore, luciferase activity assay confirm sponge molecule microRNA-17-5p (miR-17-5p) EPB41L4A-AS1. Results decreased low indicated resultful value. Overexpression inhibited cells, while knockdown promoted deterioration. directly targeted regulated ofmiR-17-5p. Conclusion This study elaborated that lowly expressed cancer. Silencing beneficial proliferation, migration, invasion. provides patients by targeting miR-17-5p.

Language: Английский

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Identification of a fatty acid metabolism-related gene signature to predict prognosis in stomach adenocarcinoma

Aging, Journal Year: 2024, Volume and Issue: 16(10), P. 8552 - 8571

Published: May 13, 2024

Background: Fatty acid metabolism (FAM) contributes to tumorigenesis and tumor development, but the role of FAM in progression stomach adenocarcinoma (STAD) has not been comprehensively clarified. Methods: The expression data clinical follow-up information were obtained from Cancer Genome Atlas (TCGA). pathway was analyzed by gene set enrichment analysis (GSEA) single-sample GSEA (ssGSEA) methods. Univariate Cox regression conducted select prognosis genes. Molecular subtypes classified consensus clustering analysis. Furthermore, least absolute shrinkage selection operator (Lasso) employed develop a risk model. ESTIMATE tumour immune dysfunction exclusion (TIDE) algorithm used assess immunity. pRRophetic package predict drug sensitivity. Results: Based on 14 related genes (FAMRG), 2 clusters determined. Patients C2 showed worse overall survival (OS). 7-FAMRG model established as an independent predictor for STAD, with higher riskscore indicating unfavorable OS. High patients had TIDE score these more sensitive anticancer drugs such Bortezomib, Dasatinib Pazopanib. A nomogram based effective prediction tool applicable settings. results pan-cancer supported prominent application value other cancer types. Conclusion: FAMRGs this study could help STAD offer new directions future studies dysfunctional FAM-induced damage anti-tumor disease.

Language: Английский

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Integration of single-cell RNA-seq and bulk RNA-seq to construct liver hepatocellular carcinoma stem cell signatures to explore their impact on patient prognosis and treatment

PLoS ONE, Journal Year: 2024, Volume and Issue: 19(4), P. e0298004 - e0298004

Published: April 18, 2024

Liver hepatocellular carcinoma (LIHC) is a prevalent form of primary liver cancer. Research has demonstrated the contribution tumor stem cells in facilitating recurrence, metastasis, and treatment resistance. Despite this, there remains lack established cancer (CSCs)-associated genes signatures for effectively predicting prognosis guiding strategies patients diagnosed with LIHC.

Language: Английский

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Transforming growth factor-β (TGF-β) signaling pathway-related genes in predicting the prognosis of colon cancer and guiding immunotherapy

Cancer Pathogenesis and Therapy, Journal Year: 2023, Volume and Issue: 2(4), P. 299 - 313

Published: Dec. 12, 2023

Colon cancer is a malignant tumor with high malignancy and low survival rate whose heterogeneity limits systemic immunotherapy. Transforming growth factor-β (TGF-β) signaling pathway-related genes are associated multiple tumors, but their role in prognosis prediction microenvironment (TME) regulation colon poorly understood. Using bioinformatics, this study aimed to construct risk signature for cancer, which may provide means developing new effective treatment strategies. consensus clustering, patients The Cancer Genome Atlas (TCGA) adenocarcinoma were classified into several subtypes based on the expression of TGF-β genes, differences survival, molecular, immunological TME characteristics drug sensitivity examined each subtype. Ten that make up TGF-β-related predictive found by least absolute shrinkage selector operation (LASSO) regression using data from TCGA database confirmed Gene Expression Omnibus (GEO) dataset. A nomogram incorporating scores clinicopathologic factors was developed stratify accurate clinical diagnosis therapy. Two identified, TGF-β-high subtype being poorer superior Mutation analyses showed incidence gene mutations After completing construction, categorized high- low-risk subgroups median score signature. exhibited performance relative age, gender, stage, as evidenced its AUC 0.686. Patients high-risk subgroup had higher levels immunosuppressive cell infiltration immune checkpoints TME, suggesting these better responses divided two different clustering analysis genes. constructed show promise biomarker evaluating potential utility screening individuals

Language: Английский

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