Low-Coverage Whole Genome Sequencing Using Laser Capture Microscopy with Combined Digital Droplet PCR: An Effective Tool to Study Copy Number and Kras Mutations in Early Lung Adenocarcinoma Development.
Low-Coverage Whole Genome Sequencing Using Laser Capture Microscopy with Combined Digital Droplet PCR: An Effective Tool to Study Copy Number and Kras Mutations in Early Lung Adenocarcinoma Development.
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DOI:
10.3390/ijms222112034
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发表时间:
2021-11-06
影响因子:
5.6
通讯作者:
Sears CR
中科院分区:
文献类型:
--
作者:
Mickler EA;Zhou H;Phang TL;Geraci MW;Stearman RS;Sears CR
Defining detailed genomic characterization of early tumor progression is critical to identifying key regulators and pathways in carcinogenesis as potentially druggable targets. In human lung cancer, work to characterize early cancer development has mainly focused on squamous cancer, as the earliest lesions are more proximal in the airways and often accessible by repeated bronchoscopy. Adenocarcinomas are typically located distally in the lung, limiting accessibility for biopsy of pre-malignant and early stages. Mouse lung cancer models recapitulate many human genomic features and provide a model for tumorigenesis with pre-malignant atypical adenomatous hyperplasia and in situ adenocarcinomas often developing contemporaneously within the same animal. Here, we combined tissue characterization and collection by laser capture microscopy (LCM) with digital droplet PCR (ddPCR) and low-coverage whole genome sequencing (LC-WGS). ddPCR can be used to identify specific missense mutations in Kras (Kirsten rat sarcoma viral oncogene homolog, here focused on Kras Q61) and estimate the percentage of mutation predominance. LC-WGS is a cost-effective method to infer localized copy number alterations (CNAs) across the genome using low-input DNA. Combining these methods, the histological stage of lung cancer can be correlated with appearance of Kras mutations and CNAs. The utility of this approach is adaptable to other mouse models of human cancer.
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DOI:
10.1093/bioinformatics/btq033
发表时间:
2010-03-15
期刊:
Bioinformatics (Oxford, England)
影响因子:
--
作者:
Quinlan AR;Hall IM
通讯作者:
Hall IM
影响因子:
--
作者:
Kellar A;Egan C;Morris D
通讯作者:
Morris D
影响因子:
11.2
作者:
Jakubek, Yasminka;Lang, Wenhua;Kadara, Humam
通讯作者:
Kadara, Humam
DOI:
10.1164/rccm.201806-1178oc
发表时间:
2019-09-15
影响因子:
24.7
作者:
Kadara, Humam;Sivakumar, Smruthy;Scheet, Paul
通讯作者:
Scheet, Paul
影响因子:
4.7
作者:
Zhou, Huaxin;Saliba, Jacob;Sears, Catherine R.
通讯作者:
Sears, Catherine R.