Personalized cancer medicine involves identifying clinically actionable cancer mutations and genomic aberrations in any given tumor. As we recently published in the November 2011 issue of Nature Biotechnology, Oligonucleotide-Selective Sequencing (OS-Seq) is a novel targeted resequencing approach that fundamentally improves the detection of cancer mutations from clinical samples. This technology has the potential for enabling the rapid, accurate detection of cancer mutations for both translational research studies and potentially, """"""""personalized"""""""" cancer diagnostics. OS-Seq provides a number of advantages to make personalized cancer analysis accessible, rapid, robust and accurate. The overall workflow is simplified such that the majority of preparative steps take place on a standard fluidics device and the actual experimental manipulation is limited. The performance is improved compared to the current commercially available methods for targeted, gene-specific cancer sequencing analysis. Based on our empirical analysis and subsequent refinements in designing capture probes, we demonstrate very specific capture of genomic targets with less variance than other methods. We achieve a high level of sequencing coverage on our targets that permit sensitive and specific detection of cancer mutations. With recent improvements in sequencing technology speed, OS-Seq can potentially be adapted to analyze large number of cancer genes in a matter of days which includes the time that genomic DNA is extracted from a biopsy to the completion of the targeted sequencing run. This holds the possibility of rapidly identifying cancer mutations from clinical samples. Our proposal is focused on development of the OS-Seq technology for identifying cancer mutations, rearrangements, copy number alterations and potential cancer-related infectious agents from clinical tumor samples. To achieve this goal, we will develop key aspects of OS-Seq technology for integrated detection of cancer mutations and genomic aberrations with simple protocols that are reliable, rapid and with high accuracy.
Personalized cancer medicine involves assessing an individual patient's tumor for mutation and genomic aberrations and subsequently using this invaluable genetic data to determine appropriate therapy. There have been isolated successes as of late in the endeavor of personalized medicine based on cancer genetics. To insure that all cancer patients have access and benefit from this new clinical paradigm we propose developing an innovative and potentially disruptive technology that enables personalized genetic analysis of their tumors in a rapid, robust and accurate fashion with potential for diagnostic application.
|Shin, GiWon; Grimes, Susan M; Lee, HoJoon et al. (2017) CRISPR-Cas9-targeted fragmentation and selective sequencing enable massively parallel microsatellite analysis. Nat Commun 8:14291|
|Xia, Li C; Sakshuwong, Sukolsak; Hopmans, Erik S et al. (2016) A genome-wide approach for detecting novel insertion-deletion variants of mid-range size. Nucleic Acids Res 44:e126|
|Zheng, Grace X Y; Lau, Billy T; Schnall-Levin, Michael et al. (2016) Haplotyping germline and cancer genomes with high-throughput linked-read sequencing. Nat Biotechnol 34:303-11|
|Nadauld, Lincoln D; Garcia, Sarah; Natsoulis, Georges et al. (2014) Metastatic tumor evolution and organoid modeling implicate TGFBR2 as a cancer driver in diffuse gastric cancer. Genome Biol 15:428|
|Hopmans, Erik S; Natsoulis, Georges; Bell, John M et al. (2014) A programmable method for massively parallel targeted sequencing. Nucleic Acids Res 42:e88|
|Natsoulis, Georges; Zhang, Nancy; Welch, Katrina et al. (2013) Identification of Insertion Deletion Mutations from Deep Targeted Resequencing. J Data Mining Genomics Proteomics 4:|
|Myllykangas, Samuel; Ji, Hanlee P (2010) Targeted deep resequencing of the human cancer genome using next-generation technologies. Biotechnol Genet Eng Rev 27:135-58|