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Detection of Novel Gene Biomarkers in non-small cell lung cancer using integrated approaches in DNA methylation expression

  • Vaibhav Kumar Sunkaria
  • , Jhen Li Huang
  • , Lucy Yi Hsuan Lai
  • , Shu Jen Chen
  • , Tun Wen Pai*
  • *Corresponding author for this work
  • National Taipei University of Technology
  • National Taiwan Ocean University
  • ACT Genomics, Co. Ltd.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Lung cancer is one of primal and ubiquitous cause of cancer related fatalities in the world. Leading cause of these fatalities is non-small cell lung cancer (NSCLC) with a percentage of 85. The major subtypes of NSCLC are Lung Adenocarcinoma (LUAD), Lung Squamous cell carcinoma (LUSC), and Large cell carcinoma. Early-stage surgical detection and removal of tumor offers a favorable prognosis and better survival rates. However, more than 75% patients have stage III/IV at the time of diagnosis and despite advanced major developments in oncology survival rates remain poor. Carcinogens produce widespread DNA methylation changes within cells. These changes are characterized by globally hyper or hypo methylated regions around CpG islands. Many of these changes occur early in tumorigenesis and are highly prevalent across a tumor type. In this study, DNA methylation profiles were extracted from TCGA for 418 LUAD and 370 LUSC tissue samples from patients compared with 32 and 42 non-malignant ones respectively. A standard pipeline was performed to consider significant differentially methylated sites as primary biomarkers, while secondary biomarkers were obtained from associated comorbidities and associated disease genes from meta-Analysis study. Concordant candidates were utilized for NSCLC relevant biomarker candidates. Gene ontology annotations were used to calculate gene-pair distance matrix for all candidate biomarkers. Clustering algorithms were utilized to categorize candidate genes into different functional groups using gene distance matrix. There were 35 CpG loci identified as key biomarkers by comparing TCGA training cohort with GEO testing cohort from these functional groups.

Original languageEnglish
Title of host publicationICBBS 2022 - 2022 11th International Conference on Bioinformatics and Biomedical Science
PublisherAssociation for Computing Machinery
Pages8-15
Number of pages8
ISBN (Electronic)9781450396929
DOIs
StatePublished - 28 10 2022
Event11th International Conference on Bioinformatics and Biomedical Science, ICBBS 2022 - Nanning, China
Duration: 28 10 2022 → 30 10 2022

Publication series

NameACM International Conference Proceeding Series

Conference

Conference11th International Conference on Bioinformatics and Biomedical Science, ICBBS 2022
Country/TerritoryChina
CityNanning
Period28/10/22 → 30/10/22

Bibliographical note

Publisher Copyright:
© 2022 ACM.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Comorbidities
  • DNA Methylation
  • Functional Clustering
  • LUAD
  • LUSC
  • Lung Cancer

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