POLD4 Gene Expression as a Prognostic Indicator for Synthetic Lethality with PARP Inhibitors in Lung Cancer Cells

Abstract

The major goals of this project were to generate p12 knockout cell lines and use these, as well as the wild-type cell lines, to demonstrate that loss of p12 leads to heightened sensitivity to chemotherapeutic agents and PARP inhibitors. In parallel, the sensitivities of small cell lung cancer cell (SCLC) lines that lack p12 would be studied. The goals of the study were to generate p12 knockout cells, and to analyze their sensitivities to the PARP inhibitors, The results showed that depletion of p12 in cultured cells leads to a defect in homologous recombination, and also increased sensitivity to the PARP inhibitors Olaparib, Niraparib, Rucaparib and Talazoparib. SCLC cells exhibit high sensitivity to PARP inhibitors, equal or greater than that of the p12 knockout cells. The significance of these findings is that they identify p12 expression as being required for homologous recombination. The findings also provide a basis for the prediction that cancers low in p12 expression should exhibit enhanced sensitivity to PARP inhibitors. The findings also provide a greater understanding of the specific roles of the two forms of DNA polymerase delta in human cells. The p12 is a subunit of the heteroetrameric Pol delta4 form, but is absent in the trimeric Pol delta3 form. Our studies support the concept that Pol delta3 is required for cellular DNA replication, while Pol delta4 is dispensible but is required for homologous recombination.

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Document Details

Document Type
Technical Report
Publication Date
Nov 01, 2019
Accession Number
AD1094491

Entities

People

  • Sufang Zhang

Organizations

  • New York Medical College

Tags

DTIC Thesaurus Topics

  • Biomedical Research
  • Cancer
  • Cell Line
  • Cells
  • Chemotherapeutic Agents
  • Chemotherapy
  • Cultured Cells
  • Gene Expression
  • Genes
  • Genetic Phenomena
  • Indicators
  • Inhibitors
  • Lethality
  • Lung Cancer
  • Neoplasms
  • New York
  • Statistical Analysis

Fields of Study

  • Biology

Readers

  • Molecular Biology and Genetics
  • Molecular Genetics
  • Oncology