Dataset Information

M1 macrophage-related gene model for NSCLC immunotherapy response prediction.

ABSTRACT: Patients diagnosed with non-small cell lung cancer (NSCLC) have a limited lifespan and exhibit poor immunotherapy outcomes. M1 macrophages have been found to be essential for antitumor immunity. This study aims to develop an immunotherapy response evaluation model for NSCLC patients based on transcription. RNA sequencing profiles of 254 advanced-stage NSCLC patients treated with immunotherapy are downloaded from the POPLAR and OAK projects. Immune cell infiltration in NSCLC patients is examined, and thereafter, different coexpressed genes are identified. Next, the impact of M1 macrophage-related genes on the prognosis of NSCLC patients is investigated. Six M1 macrophage coexpressed genes, namely, NKX2-1, CD8A , SFTA3, IL2RB, IDO1, and CXCL9, exhibit a strong association with the prognosis of NSCLC and serve as effective predictors for immunotherapy response. A response model is constructed using a Cox regression model and Lasso Cox regression analysis. The M1 genes are validated in our TD-FOREKNOW NSCLC clinical trial by RT-qPCR. The response model shows excellent immunotherapy response prediction and prognosis evaluation value in advanced-stage NSCLC. This model can effectively predict advanced NSCLC prognosis and aid in identifying patients who could benefit from customized immunotherapy as well as sensitive drugs.

SUBMITTER: Wu S

PROVIDER: S-EPMC10984861 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

M1 macrophage-related gene model for NSCLC immunotherapy response prediction.

Wu Sifan S Sheng Qiqi Q Liu Pengjun P Jiao Zhe Z Lv Jinru J Qiao Rong R Xie Dongkun D Wang Zanhan Z Ge Jiamei J Li Penghui P Wei Tiaoxia T Lei Jie J Fan Jieyi J Wang Liang L

Acta biochimica et biophysica Sinica 20240301 3

Patients diagnosed with non-small cell lung cancer (NSCLC) have a limited lifespan and exhibit poor immunotherapy outcomes. M1 macrophages have been found to be essential for antitumor immunity. This study aims to develop an immunotherapy response evaluation model for NSCLC patients based on transcription. RNA sequencing profiles of 254 advanced-stage NSCLC patients treated with immunotherapy are downloaded from the POPLAR and OAK projects. Immune cell infiltration in NSCLC patients is examined, ...[more]

PMID: 38379417

Similar Datasets

Project description:Background and Objectives: Triple-negative breast cancer (TNBC), a highly aggressive and heterogeneous subtype of breast cancer, accounts for ap-proximately 10-15% of all breast cancer cases. Currently, there is no effective therapeutic target for TNBC. Tu-mor-associated macrophages (TAMs), which can be phenotypically classified into M1 and M2 subtypes, have been shown to influence the prognosis of various cancers, including ovarian cancer. This study aimed to investigate the role of M1/M2 macrophages in the TNBC tumor microenvironment (TME), with a focus on identifying prognostic genes and predicting immunotherapy response. Materials and Methods: The study employed the CIBERSORT algorithm to analyze immune cell expression in the TME. Genes associated with the M1/M2 macrophage ratio were identified using Pearson correlation analysis and used to classify patients into dis-tinct clusters. Dimensionality reduction techniques, including univariate Cox regression and Lasso, were applied to these genes. The expression of prognostic genes was validated through immunohistochemistry. Results: The study found a high prevalence of TAMs in the TME. Among the patient clusters, 109 differentially expressed genes (DEGs) were identified. Three significant DEGs (LAMP3, GZMB, and CXCL13) were used to construct the riskScores. The riskScore model effectively stratified patients based on mortality risk. Gene Set Enrichment Analysis (GSEA) associated the riskScore with several significant pathways, including mismatch repair, JAK/STAT3 signaling, VEGF signaling, antigen processing presentation, ERBB signaling, and P53 signaling. The study also predicted patient sensitivity to im-munotherapy using the riskScores. The expression of the three significant DEGs was validated through immunohisto-chemistry. Conclusions: The study concluded that the riskScore model, based on the M1/M2 macrophage ratio, is a valid prognostic tool for TNBC. The findings underscore the importance of the TME in TNBC progression and prognosis and highlight the po-tential of the riskScore model in predicting immunotherapy response in TNBC patients.

Dataset Information

M1 macrophage-related gene model for NSCLC immunotherapy response prediction.

Publications

M1 macrophage-related gene model for NSCLC immunotherapy response prediction.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets