Enhanced CT-based radiomics model to predict natural killer cell infiltration and clinical prognosis in non-small cell lung cancer DOI Creative Commons
Xiangzhi Meng, Haijun Xu, Yicheng Liang

et al.

Frontiers in Immunology, Journal Year: 2024, Volume and Issue: 14

Published: Jan. 12, 2024

Natural killer (NK) cells are crucial for tumor prognosis; however, their role in non-small-cell lung cancer (NSCLC) remains unclear. The current detection methods NSCLC inefficient and costly. Therefore, radiomics represent a promising alternative. We analyzed the radiogenomics datasets to extract clinical, radiological, transcriptome data. effect of NK on prognosis was assessed. Tumors were delineated using 3D Slicer, features extracted pyradiomics. A model developed validated five-fold cross-validation. nomogram constructed selected clinical variables radiomic score (RS). CIBERSORTx database gene set enrichment analysis used explore correlations cell infiltration molecular mechanisms. Higher correlated with better overall survival (OS) (P = 0.002). showed an area under curve 0.731, 0.726 post-validation. RS differed significantly between high low < 0.01). nomogram, variables, effectively predicted 3-year OS. ICOS BTLA genes 0.001) macrophage M0/M2 levels. key pathways included TNF-α signaling via NF-κB Wnt/β-catenin signaling. Our accurately NSCLC. Combined characteristics, it can predict patients Bioinformatic revealed expression underlying

Language: Английский

Enhanced CT-based radiomics model to predict natural killer cell infiltration and clinical prognosis in non-small cell lung cancer DOI Creative Commons
Xiangzhi Meng, Haijun Xu, Yicheng Liang

et al.

Frontiers in Immunology, Journal Year: 2024, Volume and Issue: 14

Published: Jan. 12, 2024

Natural killer (NK) cells are crucial for tumor prognosis; however, their role in non-small-cell lung cancer (NSCLC) remains unclear. The current detection methods NSCLC inefficient and costly. Therefore, radiomics represent a promising alternative. We analyzed the radiogenomics datasets to extract clinical, radiological, transcriptome data. effect of NK on prognosis was assessed. Tumors were delineated using 3D Slicer, features extracted pyradiomics. A model developed validated five-fold cross-validation. nomogram constructed selected clinical variables radiomic score (RS). CIBERSORTx database gene set enrichment analysis used explore correlations cell infiltration molecular mechanisms. Higher correlated with better overall survival (OS) (P = 0.002). showed an area under curve 0.731, 0.726 post-validation. RS differed significantly between high low < 0.01). nomogram, variables, effectively predicted 3-year OS. ICOS BTLA genes 0.001) macrophage M0/M2 levels. key pathways included TNF-α signaling via NF-κB Wnt/β-catenin signaling. Our accurately NSCLC. Combined characteristics, it can predict patients Bioinformatic revealed expression underlying

Language: Английский

Citations

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