In silico assessment of DNA damage response gene variants associated with head and neck cancer

Abstract

Head and neck cancer (HNC), the sixth most common cancer globally, stands first in India, especially Northeast India, where tobacco usage is predominant, which introduces various carcinogens leading to malignancies by accumulating DNA damages. Consequently, the present work aimed to predict the impact of significant germline variants in DNA repair and Tumour Suppressor genes on HNC development. WES in Ion Proton^TM platform on ‘discovery set’ (n = 15), followed by recurrence assessment of the observed variants on ‘confirmation set’ (n = 40) using Sanger Sequencing was performed on the HNC-prevalent NE Indian populations. Initially, 53 variants were identified, of which seven HNC-linked DNA damage response gene variants were frequent in the studied populations. Different tools ascertained the biological consequences of these variants, of which the non-coding variants viz. EXO1_rs4150018, RAD52_rs6413436, CHD5_rs2746066, HACE1_rs6918700 showed risk, while FLT3_rs2491227 and BMPR1A_rs7074064 conferred protection against HNC by affecting transcriptional regulation and splicing mechanism. Molecular Dynamics Simulation of the full-length p53 model predicted that the observed coding TP53_rs1042522 variant conferred HNC-risk by altering the structural dynamics of the protein, which displayed difficulty in the transition between active and inactive conformations due to high-energy barrier. Subsequent pathway and gene ontology analysis revealed that EXO1, RAD52 and TP53 variants affected the Double-Strand Break Repair pathway, whereas CHD5 and HACE1 variants inactivated DNA repair cascade, facilitating uncontrolled cell proliferation, impaired apoptosis and malignant transformation. Conversely, FLT3 and BMPR1A variants protected against HNC by controlling tumorigenesis, which requires experimental validation. These findings may serve as prognostic markers for developing preventive measures against HNC.

Keywords:

• HNC
• cancer-causing genes
• in silico assessment
• germline variants
• DNA damage response
• transcriptional regulation
• full-length p53 model
• molecular dynamics simulation

Acknowledgements

Our acknowledgement goes to the Department of Science & Technology (DST), Govt. of India for providing fellowship to R.D. under DST-INSPIRE scheme, and University Grant Commission (UGC), Govt. of India for providing fellowship to S.L. under UGC-MANF scheme. We are also thankful to Bioinformatics division of Invitrogen Bioservices India Pvt. Ltd. (Thermo Fisher Scientific) for their support in the WES data analysis.

Disclosure statement

The authors declare that there are no conflicts of interest.

Additional information

Funding

The author(s) reported there is no funding associated with the work featured in this article.