Abstract
Abstract Metastasis is the most frequent cause of morbidity and mortality in cancer. Metastatic disease lethality is often the result of cancer progression despite treatment. Therapeutic resistance is seen nearly in all cases of metastatic cancer. Genetic studies relying on deep sequencing have shown that many cancers are genetically heterogeneous as a result of diverse clonal populations with delineating and unique set of mutations. Several studies suggest that resistance mutations are present in tumors before the start of treatment and via evolution, clonal populations expand under therapeutic selection. However, these minor allelic mutations that define clonal populations are not typically detectable with typical sequencing coverage (20-50X) employed in whole genome approaches. Relying on an innovative programmable targeting method that enables us to rapidly configure nearly any region of the human genome and efficiently sequence cancer genomes, we are determining the extent of intratumoral genetic heterogeneity and clonal diversity in colorectal cancer. Our study involves over 120 patients with available clinical data and a subset of matched tumors indicative of tumor progression (e.g. tumor-normal, premalignant-malignant, malignant-metastasis). Via an integrative analysis of TCGA, COSMIC and other genomic data sets of colorectal cancer, we identified the top ranking 53 cancer genes prone to mutation and associated with advanced colorectal cancer by. These top genes are found in known cancer pathways such as the WNT and RAS/RAF pathway and we are analyzing the exons of these genes for mutations, insertions and deletions with a sequencing depth of at least 1000x. Preliminary results have shown that we can readily reach sequencing depths of 7000x with our automated targeting approach and that a minimal sequencing depth of 1000x will enable detection of aberrations present in the sample below 1%. Samples are being analyzed for the overall level of heterogeneity and correlation of clonal mutations to clinical outcome. For optimal personalized treatment of cancer patients, the analysis of intratumoral genetic heterogeneity may be useful in predicting treatment response and metastatic potential of any given primary colorectal cancer. Citation Format: Erik S. Hopmans, Hojoon Lee, Laura Miotke, Rowza Tur Rumma, Sue Grimes, John M. Bell, Hanlee P. Ji. Analysis of colorectal intratumoral genetic heterogeneity by high efficiency and rapid deep targeted sequencing. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 3584. doi:10.1158/1538-7445.AM2014-3584
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
