Department of Cell and Molecular Biology and Microbiology, Faculty of Biological Science and Technology, University of Isfahan, Isfahan, Iran.
Independent Researcher, Tehran, Iran.
Med Microbiol Immunol. 2023 Aug;212(4):263-270. doi: 10.1007/s00430-023-00767-8. Epub 2023 May 24.
Adult T-cell leukemia/lymphoma (ATLL) is pathogen-caused cancer that is progressed after the infection by human T-cell leukemia virus type 1. Four significant subtypes comprising acute, lymphoma, chronic, and smoldering have been identified for this cancer. However, there are no trustworthy prognostic biomarkers for these subtypes. We utilized a combination of two powerful network-based and machine-learning algorithms including differential co-expressed genes (DiffCoEx) and support vector machine-recursive feature elimination with cross-validation (SVM-RFECV) methods to categorize disparate ATLL subtypes from asymptomatic carriers (ACs). The results disclosed the significant involvement of CBX6, CNKSR1, and MAX in chronic, MYH10 and P2RY1 in acute, C22orf46 and HNRNPA0 in smoldering subtypes. These genes also can classify each ATLL subtype from AC carriers. The integration of the results of two powerful algorithms led to the identification of reliable gene classifiers and biomarkers for diverse ATLL subtypes.
成人 T 细胞白血病/淋巴瘤 (ATLL) 是由人类 T 细胞白血病病毒 1 感染后引起的病原体相关性癌症。这种癌症已经确定了四个重要的亚型，包括急性、淋巴瘤、慢性和亚临床。然而，这些亚型没有可靠的预后生物标志物。我们利用了两种强大的基于网络和机器学习算法的组合，包括差异共表达基因 (DiffCoEx) 和支持向量机递归特征消除与交叉验证 (SVM-RFECV) 方法，从无症状携带者 (AC) 中对不同的 ATLL 亚型进行分类。结果表明，CBX6、CNKSR1 和 MAX 显著参与慢性，MYH10 和 P2RY1 参与急性，C22orf46 和 HNRNPA0 参与亚临床亚型。这些基因也可以从 AC 携带者中分类每个 ATLL 亚型。两种强大算法的结果的整合，确定了用于不同 ATLL 亚型的可靠基因分类器和生物标志物。
