Accurate genome-wide genotyping from archival tissue to explore the contribution of common genetic variants to pre-cancer outcomes

Journal of Translational Medicine

Research

Lauryn Keeler Bruce¹  Daniela Nachmanson¹  Meghana Pagadala²  Grace Y. Lin³  Farnaz Hasteh³  Gerald P. Morris³  Thomas J. O’Keefe⁴  Joseph Steward⁵  Nicole Q. Lee⁵  Callie Cheung⁵  Olivier Harismendy⁶  Hannah Carter⁷ 

[1] Bioinformatics and Systems Biology Graduate Program, University of California San Diego, 9500 Gilman Drive, 92093, San Diego, CA, USA;Biomedical Science Graduate Program, University of California San Diego, 9500 Gilman Drive, 92093, San Diego, CA, USA;Department of Pathology, University of California San Diego, 9500 Gilman Drive, 92093, San Diego, CA, USA;Department of Surgery, University of California San Diego, 9500 Gilman Drive, 92093, San Diego, CA, USA;Moores Cancer Center, University of California San Diego, 3855 Health Science Drive, 92093, San Diego, CA, USA;Moores Cancer Center, University of California San Diego, 3855 Health Science Drive, 92093, San Diego, CA, USA;Division of Biomedical Informatics, Department of Medicine, University of California San Diego, 9500 Gilman Drive, 92093, San Diego, CA, USA;Moores Cancer Center, University of California San Diego, 3855 Health Science Drive, 92093, San Diego, CA, USA;Division of Medical Genetics, Department of Medicine, University of California San Diego, 92093, La Jolla, CA, USA;

关键词: Low-coverage whole-genome sequencing;    Breast cancer;    Ductal carcinoma in situ;    Polygenic risk score;    Pre-cancer;    Genotyping;   

DOI  :  10.1186/s12967-022-03810-z

 received in 2022-09-03, accepted in 2022-12-05,  发布年份 2022

来源: Springer

【 摘 要 】

PurposeThe contribution of common genetic variants to pre-cancer progression is understudied due to long follow-up time, rarity of poor outcomes and lack of available germline DNA collection. Alternatively, DNA from diagnostic archival tissue is available, but its somatic nature, limited quantity and suboptimal quality would require an accurate cost-effective genome-wide germline genotyping methodology.Experimental designBlood and tissue DNA from 10 individuals were used to benchmark the accuracy of Single Nucleotide Polymorphisms (SNP) genotypes, Polygenic Risk Scores (PRS) or HLA haplotypes using low-coverage whole-genome sequencing (lc-WGS) and genotype imputation. Tissue-derived PRS were further evaluated for 36 breast cancer patients (11.7 years median follow-up time) diagnosed with DCIS and used to model the risk of Breast Cancer Subsequent Events (BCSE).ResultsTissue-derived germline DNA profiling resulted in accurate genotypes at common SNPs (blood correlation r2 > 0.94) and across 22 disease-related polygenic risk scores (PRS, mean correlation r = 0.93). Imputed Class I and II HLA haplotypes were 96.7% and 82.5% concordant with clinical-grade blood HLA haplotypes, respectively. In DCIS patients, tissue-derived PRS was significantly associated with BCSE (HR = 2, 95% CI 1.2–3.8). The top and bottom decile patients had an estimated 28% and 5% chance of BCSE at 10 years, respectively.ConclusionsArchival tissue DNA germline profiling using lc-WGS and imputation, represents a cost and resource-effective alternative in the retrospective design of long-term disease genetic studies. Initial results in breast cancer suggest that common risk variants contribute to pre-cancer progression.

【 授权许可】

CC BY   
© The Author(s) 2022

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