Hypoxia increases mutational load of breast cancer cells through frameshift mutations

Oncoimmunology. 2020 Apr 16;9(1):1750750. doi: 10.1080/2162402X.2020.1750750. eCollection 2020.

Abstract

Tumor hypoxia-induced downregulation of DNA repair pathways and enhanced replication stress are potential sources of genomic instability. A plethora of genetic changes such as point mutations, large deletions and duplications, microsatellite and chromosomal instability have been discovered in cells under hypoxic stress. However, the influence of hypoxia on the mutational burden of the genome is not fully understood. Here, we attempted to elucidate the DNA damage response and repair patterns under different types of hypoxic stress. In addition, we examined the pattern of mutations exclusively induced under chronic and intermittent hypoxic conditions in two breast cancer cell lines using exome sequencing. Our data indicated that hypoxic stress resulted in transcriptional downregulation of DNA repair genes which can impact the DNA repair induced during anoxic as well as reoxygenated conditions. In addition, our findings demonstrate that hypoxic conditions increased the mutational burden, characterized by an increase in frameshift insertions and deletions. The somatic mutations were random and non-recurring, as huge variations within the technical duplicates were recognized. Hypoxia also resulted in an increase in the formation of potential neoantigens in both cell lines. More importantly, these data indicate that hypoxic stress mitigates DNA damage repair pathways and causes an increase in the mutational burden of tumor cells, thereby interfering with hypoxic cancer cell immunogenicity.

Keywords: DNA repair; Hypoxia; mutational burden.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Breast Neoplasms* / genetics
  • Cell Hypoxia*
  • DNA Repair
  • Frameshift Mutation*
  • Humans

Grants and funding

This work was supported by the Sheikh Hamdan Medical Award [MRG-230/2017–2018]; TIFAC-CORE in Pharmacogenomics, DST-FIST, K-FIST, MAHE [TIFAC-CORE]; TIFAC-CORE in Pharmacogenomics, DST-FIST, K-FIST [TIFAC-CORE].