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机器学习在肥厚型心肌病和癌症新型生物标志物中的应用及实验验证。

Machine learning and experimental validation of novel biomarkers for hypertrophic cardiomyopathy and cancers.

机构信息

Cardiovascular Center, The Affiliated Hospital of Yunnan University, Yunnan University, Kunming, Yunnan, China.

School of Medicine, Yunnan University, Kunming, Yunnan, China.

出版信息

J Cell Mol Med. 2024 Aug;28(16):e70034. doi: 10.1111/jcmm.70034.

Abstract

Hypertrophic cardiomyopathy (HCM) is a hereditary cardiac disorder marked by anomalous thickening of the myocardium, representing a significant contributor to mortality. While the involvement of immune inflammation in the development of cardiac ailments is well-documented, its specific impact on HCM pathogenesis remains uncertain. Five distinct machine learning algorithms, namely LASSO, SVM, RF, Boruta and XGBoost, were utilized to discover new biomarkers associated with HCM. A unique nomogram was developed using two newly identified biomarkers and subsequently validated. Furthermore, samples of HCM and normal heart tissues were gathered from our institution to confirm the variance in expression levels and prognostic significance of GATM and MGST1. Five novel biomarkers (DARS2, GATM, MGST1, SDSL and ARG2) associated with HCM were identified. Subsequent validation revealed that GATM and MGST1 exhibited significant diagnostic utility for HCM in both the training and test cohorts, with all AUC values exceeding 0.8. Furthermore, a novel risk assessment model for HCM patients based on the expression levels of GATM and MGST1 demonstrated favourable performance in both the training (AUC = 0.88) and test cohorts (AUC = 0.9). Furthermore, our study revealed that GATM and MGST1 exhibited elevated expression levels in HCM tissues, demonstrating strong discriminatory ability between HCM and normal cardiac tissues (AUC of GATM = 0.79; MGST1 = 0.86). Our findings suggest that two specific cell types, monocytes and multipotent progenitors (MPP), may play crucial roles in the pathogenesis of HCM. Notably, GATM and MGST1 were found to be highly expressed in various tumours and showed significant prognostic implications. Functionally, GATM and MGST1 are likely involved in xenobiotic metabolism and epithelial mesenchymal transition in a wide range of cancer types. GATM and MGST1 have been identified as novel biomarkers implicated in the progression of both HCM and cancer. Additionally, monocytes and MPP may also play a role in facilitating the progression of HCM.

摘要

肥厚型心肌病(HCM)是一种遗传性心脏病,其特征为心肌异常增厚,是导致死亡率升高的重要原因。尽管免疫炎症在心脏疾病的发展中起着重要作用,但它对 HCM 发病机制的具体影响仍不确定。我们使用五种不同的机器学习算法(LASSO、SVM、RF、Boruta 和 XGBoost)来发现与 HCM 相关的新生物标志物。使用两个新确定的生物标志物开发了一个独特的列线图,并随后进行了验证。此外,我们从机构中收集了 HCM 和正常心脏组织的样本,以证实 GATM 和 MGST1 的表达水平变化及其对 HCM 的预后意义。我们确定了五个与 HCM 相关的新型生物标志物(DARS2、GATM、MGST1、SDSL 和 ARG2)。随后的验证表明,在训练和测试队列中,GATM 和 MGST1 对 HCM 均具有显著的诊断效用,所有 AUC 值均超过 0.8。此外,基于 GATM 和 MGST1 表达水平的 HCM 患者新型风险评估模型在训练队列(AUC=0.88)和测试队列(AUC=0.9)中均表现出良好的性能。此外,我们的研究表明,GATM 和 MGST1 在 HCM 组织中表达水平升高,在 HCM 和正常心脏组织之间具有很强的区分能力(GATM 的 AUC=0.79;MGST1 的 AUC=0.86)。我们的研究结果表明,两种特定的细胞类型,单核细胞和多能祖细胞(MPP),可能在 HCM 的发病机制中起关键作用。值得注意的是,GATM 和 MGST1 在各种肿瘤中表达水平升高,并具有显著的预后意义。功能上,GATM 和 MGST1 可能参与了广泛的癌症类型中的异生物质代谢和上皮间质转化。GATM 和 MGST1 已被确定为与 HCM 和癌症进展相关的新型生物标志物。此外,单核细胞和 MPP 也可能在促进 HCM 进展中发挥作用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/aa3c/11333198/881f5cbba1a6/JCMM-28-e70034-g001.jpg

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