Additional file 1 of Robust machine−learning based prognostic index using cytotoxic T lymphocyte evasion genes highlights potential therapeutic targets in colorectal cancer

Name: Additional file 1 of Robust machine−learning based prognostic index using cytotoxic T lymphocyte evasion genes highlights potential therapeutic targets in colorectal cancer
Creator: Zhang, Huabing; Wang, Chen; Xu, Yuanmin; Zuo, Xiaomin; Zhao, Hu; Li, Zichen; Chan, Shixin; Wang, Xu; Han, Qijun; Wang, Ming; Wang, Zhenglin; Dai, Longfei; Chen, Wei; Chen, Jiajie; Yang, Yang
Published: 2024-02-29 00:00:00
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Figshare2024-02-29 更新2026-04-08 收录

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Additional file 1: Figure S1. (A) Expression and (B) prognostic significance of 31 core CERGs in TCGA-CRC dataset. Figure S2. IHC score of HOXC6 (A), G0S2 (B), and MX2 (C) in normal tissues and CRC. **p < 0.01; ***p < 0.001. Table S1. Published signatures applied for model comparison. Table S2. Sequences for qRT-PCR primers. Table S3. Detailed si-RNA sequences used in the study. Table S4. 182 CERGs from published research and 1793 IRGs from Immport database. Table S5. Published signatures applied for model comparison. C-index of each combination of machine learning method for developing the prognostic signature. Table S6. AUC value of each combination of machine learning method for constructing the immunotherapy-related signature.

提供机构：

Zhang, Huabing; Wang, Chen; Xu, Yuanmin; Zuo, Xiaomin; Zhao, Hu; Li, Zichen; Chan, Shixin; Wang, Xu; Han, Qijun; Wang, Ming; Wang, Zhenglin; Dai, Longfei; Chen, Wei; Chen, Jiajie; Yang, Yang

创建时间：

2024-02-01