Genes, Vol. 15, Pages 312: Gene Expression Analysis for Uterine Cervix and Corpus Cancer Characterization

Genes, Vol. 15, Pages 312: Gene Expression Analysis for Uterine Cervix and Corpus Cancer Characterization Genes doi: 10.3390/genes15030312 Authors: Lucía Almorox Laura Antequera Ignacio Rojas Luis Javier Herrera Francisco M. Ortuño The analysis of gene expression quantification data is a powerful and widely used approach in cancer research. This work provides new insights into the transcriptomic changes that occur in healthy uterine tissue compared to those in cancerous tissues and explores the differences associated with uterine cancer localizations and histological subtypes. To achieve this, RNA-Seq data from the TCGA database were preprocessed and analyzed using the KnowSeq package. Firstly, a kNN model was applied to classify uterine cervix cancer, uterine corpus cancer, and healthy uterine samples. Through variable selection, a three-gene signature was identified (VWCE, CLDN15, ADCYAP1R1), achieving consistent 100% test accuracy across 20 repetitions of a 5-fold cross-validation. A supplementary similar analysis using miRNA-Seq data from the same samples identified an optimal two-gene miRNA-coding signature potentially regulating the three-gene signature previously mentioned, which attained optimal classification performance with an 82% F1-macro score. Subsequently, a kNN model was implemented for the classification of cervical cancer samples into their two main histological subtypes (adenocarcinoma and squamous cell carcinoma). A uni-gene signature (IC...
Source: Genes - Category: Genetics & Stem Cells Authors: Tags: Article Source Type: research