Application of next generation sequencing to CEPH cell lines to discover variants associated with FDA approved
Gunjan D Hariani, Ernest T Lam, Ernest J Lam
1Bioinformatics Research Center, North Carolina State University, 307 Ricks Hall, 1 Lampe Dr, Raleigh, NC 27695 CB7566, USA. motsinger@stat.ncsu.edu.
Background:
The goal of this study was to perform candidate gene association with cytotoxicity of chemotherapeutics in cell line models through resequencing and discovery of rare and low frequency variants along with common variations. Here, an association study of cytotoxicity response to 30 FDA approved drugs was conducted and we applied next generation targeted sequencing technology to discover variants from 103 candidate genes in 95 lymphoblastoid cell lines from 14 CEPH pedigrees. In this article, we called variants across 95 cell lines and performed association analysis for cytotoxic response using the Family Based Association Testing method and software.
Results:
We called 2281 variable SNP genotypes across the 103 genes for these cell lines and identified three genes of significant association within this marker set. Specifically, ATP-binding cassette, sub-family C, member 5 (ABCC5), metallothionein 1A (MT1A) and NAD(P)H dehydrogenase quinone1 (NQO1) were significantly associated with oxaliplatin drug response. The significant SNP on NQO1 (rs1800566) has been linked with poor survival rates in patients with non-small cell lung cancer treated with cisplatin (which belongs to the same class of drugs as oxaliplatin). A SNP (rs1846692) near the 5' region of MT1A was associated with arsenic trioxide.
Conclusions:
The results from this study are promising and this serves as a proof-of-principle demonstration of the use of sequencing data in the cytotoxicity models of human cell lines. With increased sample sizes, such studies will be a fast and powerful way to associate common and rare variants with drug response; while overcoming the cost and time limitations to recruit cohorts for association study.
Insights
This study identified three genes (ABCC5, MT1A, NQO1) associated with chemotherapy drug response in cell lines using next-generation sequencing. These findings demonstrate sequencing
Area of Science:
- Genomics
- Pharmacogenomics
- Cancer Research
Background:
- Investigating genetic variations influencing chemotherapy drug response is crucial for personalized medicine.
- Previous studies have focused on common variants, but rare and low-frequency variants also impact drug efficacy and toxicity.
- Lymphoblastoid cell lines provide a valuable model for genetic association studies.
Purpose of the Study:
- To perform candidate gene association analysis for chemotherapeutic drug cytotoxicity in human cell line models.
- To discover common, rare, and low-frequency variants in 103 candidate genes associated with drug response.
- To identify specific genes and single nucleotide polymorphisms (SNPs) linked to cytotoxicity of 30 FDA-approved drugs.
Main Methods:
- Applied next-generation targeted sequencing to resequence 103 candidate genes in 95 lymphoblastoid cell lines.
- Called 2281 variable SNP genotypes across the selected genes.
- Utilized Family Based Association Testing (FBAT) to analyze the association between genetic variants and cytotoxic response.
Main Results:
- Identified significant associations between three genes—ATP-binding cassette, sub-family C, member 5 (ABCC5), metallothionein 1A (MT1A), and NAD(P)H dehydrogenase quinone1 (NQO1)—and oxaliplatin response.
- A significant SNP (rs1800566) in NQO1 was previously linked to poor survival in non-small cell lung cancer patients treated with cisplatin.
- A SNP (rs1846692) near MT1A was associated with arsenic trioxide response.
Conclusions:
- This study serves as a proof-of-principle for using sequencing data to model drug cytotoxicity in human cell lines.
- The findings highlight the potential of associating common and rare variants with drug response.
- Increased sample sizes in future studies can accelerate the discovery of genetic markers for drug response, overcoming cohort recruitment challenges.
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