Background
Type: Article

Exploration of mRNAs and miRNA classifiers for various ATLL cancer subtypes using machine learning

Journal: Bmc Cancer (14712407)Year: 2022Volume: 22Issue: 1
Emamzadeh R.aGhobadi M.Z. Afsaneh E.Ghobadi M.Z.Emamzadeh R.a Afsaneh E.
All Open Access; Gold Open Access; Green Open AccessDOI:10.1186/s12885-022-09540-1Language: English

Abstract

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. © 2022, The Author(s).


Author Keywords

Asymptomatic carriersATLLATLL subtypesHTLV-1Machine learning

Other Keywords

AdultBiomarkersHuman T-lymphotropic virus 1HumansLeukemia-Lymphoma, Adult T-CellMachine LearningMicroRNAsRNA, Messengermessenger RNAmicroRNAnicotinamide adenine dinucleotide adenosine diphosphate ribosyltransferase 1oncoproteinprotein DAAM1protein MYEF2Smad7 proteintranscription factor E2F2unclassified drugbiological markermessenger RNAmicroRNAadult T cell leukemiaArticlecancer growthcancer prognosiscarcinogenesisclassifiercontrolled studydifferential gene expressiongene expressiongene targetinggenetic identificationgenetic variabilityheredityHTLV-1 infectionhumanmachine learningprotein RNA bindingrecursive feature eliminationsupport vector machinevalidation studyadultgeneticsHuman T-lymphotropic virus 1machine learningT cell leukemia