Integration of single-cell and bulk RNA-sequencing data to construct and validate a signature based on NK cell marker genes to predict immunotherapy response and prognosis in colorectal cancer

We aimed to create a NK cell marker genes-based signature to predict immunotherapy response and prognosis in colorectal cancer. We integrated scRNA-seq data from four Gene Expression Omnibus (GEO) samples and performed Weighted gene correlation network analysis (WGCNA) based on 587 the Cancer Genome Atlas (TCGA) colorectal cancer samples to uncover NK cell-related genes. We identified 1080 NK cell-related core genes and 276 NK cell-related feature genes based on WGCNA and clustering and annotation of scRNA-seq data, respectively. Six key NK cell-related prognostic signature genes were obtained by univariate and LASSO regression analyses, including ADAM8, CTSD, CCL4, IL2RB, TTC38, and PLEK. Two validation cohorts from the GEO dataset, comprising 124 and 201 samples respectively, were used. The signature was significantly associated with overall survival and correlated with immune cell infiltration, immune and stromal scores, and immune checkpoint genes. Furthermore, the signature was associated with the homologous recombination deficiency (HRD) and T-cell receptor (TCR) scores. In conclusion, our study proposes a new prognostic signature based on NK cell marker genes, which may serve as a potential tool to predict overall survival and immunotherapy response for CRC patients.

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Publication Details

Journal
Discover Oncology
Published
2025-02-07
DOI
https://doi.org/10.1007/s12672-025-01842-7
Primary Topic
Immune Cell Function and Interaction
Type
article
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article

Integration of single-cell and bulk RNA-sequencing data to construct and validate a signature based on NK cell marker genes to predict immunotherapy response and prognosis in colorectal cancer

Ming Li, Jinxiu Wu, Xiaoyu Qin, Wenjuan Xu
Discover Oncology
Immune Cell Function and Interaction
article

Integration of single-cell and bulk RNA-sequencing data to construct and validate a signature based on NK cell marker genes to predict immunotherapy response and prognosis in colorectal cancer

Ming Li, Jinxiu Wu, Xiaoyu Qin, Wenjuan Xu
article en

Abstract

We aimed to create a NK cell marker genes-based signature to predict immunotherapy response and prognosis in colorectal cancer. We integrated scRNA-seq data from four Gene Expression Omnibus (GEO) samples and performed Weighted gene correlation network analysis (WGCNA) based on 587 the Cancer Genome Atlas (TCGA) colorectal cancer samples to uncover NK cell-related genes. We identified 1080 NK cell-related core genes and 276 NK cell-related feature genes based on WGCNA and clustering and annotation of scRNA-seq data, respectively. Six key NK cell-related prognostic signature genes were obtained by univariate and LASSO regression analyses, including ADAM8, CTSD, CCL4, IL2RB, TTC38, and PLEK. Two validation cohorts from the GEO dataset, comprising 124 and 201 samples respectively, were used. The signature was significantly associated with overall survival and correlated with immune cell infiltration, immune and stromal scores, and immune checkpoint genes. Furthermore, the signature was associated with the homologous recombination deficiency (HRD) and T-cell receptor (TCR) scores. In conclusion, our study proposes a new prognostic signature based on NK cell marker genes, which may serve as a potential tool to predict overall survival and immunotherapy response for CRC patients.

Discover OncologyVol. 16(1)
Second Military Medical University (CN), Punan Hospital (CN), Shanghai Pudong New Area Gongli Hospital (CN)
Good health and well-being
Openalex Percentile: Top 97%
Immune Cell Function and Interaction
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Integration of single-cell and bulk RNA-sequencing data to construct and validate a signature based on NK cell marker genes to predict immunotherapy response and prognosis in colorectal cancer — Ming Li, Jinxiu Wu, et al. · Discover Oncology (2025) | TGRS Research Map | TGRS