Post-Transcriptional Modifications to miRNAs Undergo Widespread Alterations, Creating a Unique Lung Adenocarcinoma...

Area of Science:

• Genomics
• Epigenetics
• Cancer Biology

Background:

• MicroRNAs (miRNAs) are key epigenetic regulators in cancer, influencing oncogene and tumor suppressor gene expression.
• IsomiRs, modified miRNA variants, can alter mRNA target binding and are implicated in cancer development.
• The isomiRomes of lung tissues remain largely uncharacterized.

Purpose of the Study:

• To characterize the isomiRomes of human lung adenocarcinoma (LUAD) and adult non-malignant lung (ANL) tissues.
• To investigate differences in isomiR expression profiles between LUAD and ANL samples.
• To evaluate the potential of isomiRs as biomarkers for early-stage LUAD detection.

Main Methods:

• Analysis of small RNA sequencing data from three cohorts of LUAD and ANL samples.
• Quantification of various isomiR types, including A-to-I edited, 5', 3' adenylated, and 3' uridylated isomiRs.
• Development and validation of machine learning models (SVM, Random Forest) to classify LUAD and ANL based on isomiR expression data.

Main Results:

• Identified 16 A-to-I edited isomiRs, 213 5' isomiRs, 128 3' adenylated isomiRs, and 100 3' uridylated isomiRs.
• Observed deregulation of ADAR and ADARB1 in LUAD, correlating with A-to-I editing rates.
• LUAD samples exhibited lower A-to-I editing and 3' adenylation rates compared to ANL samples.
• Machine learning models trained on A-to-I editing rates achieved high accuracy in distinguishing LUAD from ANL, outperforming models based on miRNA expression alone.

Conclusions:

• IsomiR expression profiles differ significantly between non-malignant and tumor lung tissues.
• Specific isomiR modifications, such as A-to-I editing, show potential as sensitive biomarkers for lung adenocarcinoma.
• Further research into isomiRs may lead to novel diagnostic and prognostic tools for LUAD.