背景:成人T细胞白血病/淋巴瘤(ATLL)是一种癌症疾病,是由于1型人类T细胞白血病病毒感染而发展起来的。它可以分为四个主要亚型,包括,急性,慢性,阴燃,和淋巴瘤。尽管有临床表现,对于这些亚型的分类,没有可靠的诊断性生物标志物.
方法:这里,我们采用了机器学习方法,即,支持向量机-具有交叉验证的递归特征消除(SVM-RFECV)来分类来自无症状载体(AC)的不同ATLL亚型。多个mRNA和miRNA的表达值被用作特征。之后,通过探索经过实验验证的miRNA的靶基因,鉴定了每种亚型的可靠miRNA-mRNA相互作用.
结果:结果显示miR-21及其与DAAM1和E2F2的相互作用在急性,SMAD7在慢性,阴燃亚型中的MYEF2和PARP1可以显着分类不同的亚型。
结论:考虑到所构建模型的高精度,已鉴定的mRNA和miRNA被认为是各种ATLL亚型的潜在治疗靶标和预后生物标志物。
BACKGROUND: Adult T-cell Leukemia/Lymphoma (ATLL) is a cancer disease that is developed due to the infection by human T-cell leukemia virus type 1. It can be classified into four main subtypes including, acute, chronic, smoldering, and lymphoma. Despite the clinical manifestations, there are no reliable diagnostic biomarkers for the classification of these subtypes.
METHODS: Herein, we employed a machine learning approach, namely, Support Vector Machine-Recursive Feature Elimination with Cross-Validation (SVM-RFECV) to classify the different ATLL subtypes from Asymptomatic Carriers (ACs). The expression values of multiple mRNAs and miRNAs were used as the features. Afterward, the reliable miRNA-mRNA interactions for each subtype were identified through exploring the experimentally validated-target genes of miRNAs.
RESULTS: The results revealed that miR-21 and its interactions with DAAM1 and E2F2 in acute, SMAD7 in chronic, MYEF2 and PARP1 in smoldering subtypes could significantly classify the diverse subtypes.
CONCLUSIONS: Considering the high accuracy of the constructed model, the identified mRNAs and miRNA are proposed as the potential therapeutic targets and the prognostic biomarkers for various ATLL subtypes.