一种针对按性别和 KRAS 分层的结直肠癌铁死亡的机器学习和药物再利用方法。
A machine learning and drug repurposing approach to target ferroptosis in colorectal cancer stratified by sex and KRAS.
发表日期:2024 Jun 28
作者:
Hong Yan, Xinyi Shen, Yisha Yao, Sajid A Khan, Shuangge Ma, Caroline H Johnson
来源:
Cell Death & Disease
摘要:
关于 KRAS 等癌基因的作用机制,结直肠癌 (CRC) 中性别差异的情况尚未得到很好的描述。然而,我们最近的研究表明,来自携带 KRAS 突变的男性患者的肿瘤减少了称为铁死亡的铁依赖性细胞死亡。基于这些发现,我们利用公共数据库和我们内部的 CRC 肿瘤队列,进一步检查了 CRC 中的铁死亡,考虑到患者的性别和 KRAS 突变。通过二次采样推断和变量重要性分析(VIMP),我们发现男性患者的 KRAS 突变型和野生型肿瘤之间基因表达存在显着差异。这些基因抑制(例如 SLC7A11 )或驱动(例如 SLC1A5 )铁死亡,并且这些发现通过高斯混合模型得到了进一步验证。此外,我们探索了铁死亡调节基因的预后价值,并通过后向消除算法的随机生存森林(RSF-BE)发现了转录和代谢水平上的性别和 KRAS 特异性差异。值得注意的是,参与精氨酸合成和谷胱甘肽代谢的基因和代谢物与具有 KRAS 突变的男性肿瘤的预后具有独特的相关性。此外,由于成本高、损耗率高且新药开发速度缓慢,药物再利用变得越来越流行,这为更有效地治疗常见和罕见疾病提供了一种方法。此外,越来越多的证据表明,抑制或诱导铁死亡可以提高药物敏感性或克服化疗耐药性。因此,我们利用癌症药物敏感性基因组学 (GDSC) 资源的数据研究了所有 CRC 原发肿瘤细胞系的基因表达、代谢物水平和药物敏感性之间的相关性。我们观察到 KRAS 突变 CRC 细胞系中的铁死亡抑制基因(如 DHODH 、 GCH1 和 AIFM2 )对顺铂和紫杉醇具有耐药性,这强调了为什么这些药物对这些患者无效。这里生成的综合图谱为未来的研究提供了有价值的生物学见解,并且这些发现得到了对大规模公开数据和我们内部队列的严格分析的支持。该研究还强调了 VIMP、高斯混合模型和 RSF-BE 模型在多组学研究界的潜在应用。总之,这种综合方法为在 KRAS 突变 CRC 中利用精确分子特征分析和药物再利用可能性打开了大门。
The landscape of sex differences in Colorectal Cancer (CRC) has not been well characterized with respect to the mechanisms of action for oncogenes such as KRAS. However, our recent study showed that tumors from male patients with KRAS mutations have decreased iron-dependent cell death called ferroptosis. Building on these findings, we further examined ferroptosis in CRC, considering both sex of the patient and KRAS mutations, using public databases and our in-house CRC tumor cohort. Through subsampling inference and variable importance analysis (VIMP), we identified significant differences in gene expression between KRAS mutant and wild type tumors from male patients. These genes suppress (e.g., SLC7A11 ) or drive (e.g., SLC1A5 ) ferroptosis, and these findings were further validated with Gaussian mixed models. Furthermore, we explored the prognostic value of ferroptosis regulating genes and discovered sex- and KRAS-specific differences at both the transcriptional and metabolic levels by random survival forest with backward elimination algorithm (RSF-BE). Of note, genes and metabolites involved in arginine synthesis and glutathione metabolism were uniquely associated with prognosis in tumors from males with KRAS mutations. Additionally, drug repurposing is becoming popular due to the high costs, attrition rates, and slow pace of new drug development, offering a way to treat common and rare diseases more efficiently. Furthermore, increasing evidence has shown that ferroptosis inhibition or induction can improve drug sensitivity or overcome chemotherapy drug resistance. Therefore, we investigated the correlation between gene expression, metabolite levels, and drug sensitivity across all CRC primary tumor cell lines using data from the Genomics of Drug Sensitivity in Cancer (GDSC) resource. We observed that ferroptosis suppressor genes such as DHODH , GCH1 , and AIFM2 in KRAS mutant CRC cell lines were resistant to cisplatin and paclitaxel, underscoring why these drugs are not effective for these patients. The comprehensive map generated here provides valuable biological insights for future investigations, and the findings are supported by rigorous analysis of large-scale publicly available data and our in-house cohort. The study also emphasizes the potential application of VIMP, Gaussian mixed models, and RSF-BE models in the multi-omics research community. In conclusion, this comprehensive approach opens doors for leveraging precision molecular feature analysis and drug repurposing possibilities in KRAS mutant CRC.