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Published on: July 21, 2018
Targeting NLRC4 for potential therapeutic strategies in lung adenocarcinoma
Xue Xu1, Meng-Yu Zhang2, Jia-Qi Fan3
1Department of Gerontology, The Second Hospital of Shandong University, Jinan, China.
Background:
Autophagy, a vital cellular process, plays a significant role in the development of a spectrum of diseases, notably cancer. The objective of this study was to assess the prognostic significance and explore the possible roles of autophagy-related genes (ARGs) in lung adenocarcinoma (LUAD) and in 33 cancer types.
Methods:
In this study, ARGs were sourced from the Human Autophagy Database (HADb), with gene expression data retrieved from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. The LASSO Cox and multivariate Cox regression models were employed to identify ARGs with prognostic significance, leading to the development of the Autophagy-Related Gene Prognostic Signature (ARGPS), which was compared with previously established prognostic models. The associations between the ARGPS and clinical parameters were examined to identify independent prognostic factors. Additionally, a pan-cancer analysis underscored the role of the ARGPS in immune subtyping, the tumor immune context, survival outcomes, stemness scores, and sensitivity to antitumor drugs. Finally, a virtual drug screening was performed to predict potential target interactions.
Results:
In the GSE116959 dataset, we identified 14 DEARGs with statistical significance (p < 0.05 and |logFC|> 1). Using LASSO Cox and multivariate Cox regression, we developed an independent prognostic signature, identifying seven ARGs to form the ARGPS. LUAD patients were stratified into low-risk and high-risk groups. Pan-cancer analysis highlighted significant heterogeneity in ARGPS expression among various cancers. ARGPS members were significantly correlated with immune infiltration, drug resistance, and stemness in tumors. Virtual screening identified five potential NLRC4-targeting drugs for LUAD treatment.
Conclusions:
In this study, we developed a predictive risk model based on seven ARGs. We comprehensively examined ARGPS expression and its correlation with immune infiltration and the tumor microenvironment. These findings could inform targeted immunotherapy and chemotherapy for LUAD and other cancers. The low expression of NLRC4 in LUAD indicated its potential as a therapeutic target.
Insights
This study developed a prognostic signature using autophagy-related genes (ARGs) to predict outcomes in lung adenocarcinoma (LUAD) and other cancers. The signature correlates with immune response and drug sensitivity, identifying NLRC4 as a potential therapeutic target.
Area of Science:
- Oncology
- Molecular Biology
- Genetics
Background:
- Autophagy is a critical cellular process implicated in cancer development.
- Autophagy-related genes (ARGs) play a significant role in various cancers, including lung adenocarcinoma (LUAD).
Purpose of the Study:
- To assess the prognostic significance of ARGs in LUAD and 33 other cancer types.
- To develop a predictive model for patient outcomes based on ARGs.
Main Methods:
- ARGs were identified from the Human Autophagy Database (HADb).
- Gene expression data from TCGA and GEO databases were analyzed using LASSO Cox and multivariate Cox regression.
- A pan-cancer analysis explored correlations with immune infiltration, stemness, and drug sensitivity.
- Virtual drug screening was performed to identify potential therapeutic agents.
Main Results:
- A prognostic signature (ARGPS) comprising seven ARGs was developed.
- ARGPS effectively stratified LUAD patients into low-risk and high-risk groups.
- ARGPS expression showed significant correlations with immune infiltration, drug resistance, and stemness across various cancers.
- Five potential NLRC4-targeting drugs were identified for LUAD treatment.
Conclusions:
- A novel seven-ARG prognostic model (ARGPS) was established for LUAD and other cancers.
- The ARGPS is linked to immune infiltration and the tumor microenvironment, informing targeted therapies.
- Low NLRC4 expression in LUAD suggests its potential as a therapeutic target for novel treatments.
