GABRP is a Promising Prognostic Biomarker and Associated with Immune Cell Infiltration in Lung Squamous Cell Carcinoma

Fu, Jiding; Lin, Jie; Zeng, Xiaohui; Li, Guanger; Wei, Yier; Xian, Lewu

doi:10.2147/pgpm.s403868

Cited by 2 publications

(2 citation statements)

References 29 publications

(34 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The advancement of gene sequencing technology and the accessibility of public databases have facilitated the gathering of gene expression data, thereby accelerating the discovery of prognostic biomarkers. 21 , 22 In this study, our team aimed to utilize bioinformatics methods to pinpoint diagnostic biomarkers for gastric cancer. Firstly, GSVA algorithm and Kaplan-Meier were used to assess the prognosis value of GABA-related pathways.…”

Section: Introductionmentioning

confidence: 99%

Identification of Novel Prognostic Biomarkers That are Associated with Immune Microenvironment Based on GABA-Related Molecular Subtypes in Gastric Cancer

Wang¹,

Huang²,

Ye³

et al. 2023

PGPM

View full text Add to dashboard Cite

Background Gamma-aminobutyric acid (GABA) plays an important role in tumorigenesis and progression. Despite this, the role of Reactome GABA receptor activation (RGRA) on gastric cancer (GC) remains unclear. This study was intended to screen RGRA-related genes in GC and investigate their prognostic value. Methods GSVA algorithm was used to assess the score of RGRA. GC patients were divided into two subtypes based on the median score of RGRA. GSEA, functional enrichment analysis, and immune infiltration analysis were performed between the two subgroups. Then, differentially expressed analysis, and weighted gene co-expression network analysis (WGCNA) were used to identify RGRA-related genes. The prognosis and expression of core genes were analyzed and validated in the TCGA database, GEO database, and clinical samples. ssGSEA and ESTIMATE algorithms were used to assess the immune cell infiltration in the low- and high-core genes subgroups. Results High-RGRA subtype had a poor prognosis and activated immune-related pathways, as well as an activated immune microenvironment. ATP1A2 was identified to be the core gene. The expression of ATP1A2 was associated with the overall survival rate and tumor stage, and its expression was down-regulated in GC patients. Furthermore, ATP1A2 expression was positively correlated with the level of immune cells, including B cells, CD8 T cells, cytotoxic cells, DC, eosinophils, macrophages, mast cells, NK cells, and T cells. Conclusion Two RGRA-related molecular subtypes were identified that could predict the outcome in GC patients. ATP1A2 was a core immunoregulatory gene and was associated with prognosis and immune cell infiltration in GC.

show abstract

Section: Introductionmentioning

confidence: 99%

Identification of Novel Prognostic Biomarkers That are Associated with Immune Microenvironment Based on GABA-Related Molecular Subtypes in Gastric Cancer

Wang¹,

Huang²,

Ye³

et al. 2023

PGPM

View full text Add to dashboard Cite

show abstract

“…The progress in gene sequencing technology and the availability of public databases have made it easier to collect gene expression data, thereby speeding up the identification of prognostic biomarkers. 23 , 24 In this study, we utilized the GSVA algorithm to evaluate heme metabolism. Differentially expressed HRGs were identified from the TCGA dataset.…”

Section: Introductionmentioning

confidence: 99%

Heme Metabolism-Related Gene TENT5C is a Prognostic Marker and Investigating Its Immunological Role in Colon Cancer

Han,

Li,

Wang

et al. 2023

PGPM

View full text Add to dashboard Cite

Background There is a strong correlation between consuming high amounts of heme and an elevated risk of developing various types of cancer, including colorectal cancer. However, the role of heme metabolism-related genes (HRGs) in colorectal cancer remains unclear. Our study aimed to identify prognostic markers for colorectal cancer patients based on these genes. Methods The heme metabolism score was assessed using gene set variation analysis (GSVA). Potential prognostic HRGs were identified from the TCGA-COAD dataset using LASSO and COX regression analyses. The expression level of TENT5C was validated in the GEO database and clinical samples. To explore the association between TENT5C expression and immune cell infiltrations, we performed ESTIMATE and single-sample gene set enrichment analysis (ssGSEA). Results The low level of heme metabolism score was associated with a poor prognosis in colorectal cancer patients. TENT5C is a prognostic gene and an independent prognostic biomarker for overall survival. Its expression was confirmed in multiple datasets and clinical samples, showing a positive correlation with immune cells and immune score. GSEA results suggested TENT5C’s significant role in regulating immune and inflammatory responses in colorectal cancer. Conclusion TENT5C can be used as a biomarker in colorectal cancer. Additionally, TENT5C is associated with both prognosis and immune infiltration. These findings lay a strong groundwork for future research to delve into the specific role of TENT5C in the development and advancement of colorectal cancer.

show abstract

GABRP is a Promising Prognostic Biomarker and Associated with Immune Cell Infiltration in Lung Squamous Cell Carcinoma

Cited by 2 publications

References 29 publications

Identification of Novel Prognostic Biomarkers That are Associated with Immune Microenvironment Based on GABA-Related Molecular Subtypes in Gastric Cancer

Identification of Novel Prognostic Biomarkers That are Associated with Immune Microenvironment Based on GABA-Related Molecular Subtypes in Gastric Cancer

Heme Metabolism-Related Gene TENT5C is a Prognostic Marker and Investigating Its Immunological Role in Colon Cancer

Contact Info

Product

Resources

About