Journal of Emerging Investigators

DyGS: a dynamic gene searching algorithm for detection Jenica Wang1*, Xue Gong2 1Henry M. Gunn High School, Palo Alto, CA *Current institution: Johns Hopkins University, Baltimore, MD 2Department of Urology, Stanford, CA

Summary Cancer is a lethal disease and ranks as the world’s the cellular and molecular levels. Different cancer second-most prevalent cause of death. So far, biopsy patients harbor unique mutations, which make cancer is the most common method conducted to determine detection and treatment more challenging (2, 3). Tissue the progression of tumors. However, this traditional biopsy is the conventional method used to determine the technique is invasive and cannot be used repeatedly. On progression of tumors, but this technique is invasive. On the other hand, liquid biopsies, also known as blood- the other hand, liquid biopsy is non-invasive and is a more sample tests, have become more and more promising. promising strategy for early cancer detection. Circulating One critical step in liquid biopsy is to create an effective tumor DNA (ctDNA) is released by dead tumor cells and gene panel that covers the maximum number of cancer cases possible. The hypotheses of this study are that flows into the bloodstream, which can be used for early both common genes and genes that are mutated in cancer detection and cancer monitoring (4). Some ctDNA specific cancer types will be present in the selected is released from circulating tumor cells (CTCs), which gene lists for the 12 cancer types, and some types are tumor cells that separate from the tumor and enter may have longer lists than others. In this study, we the bloodstream (5). Besides CTCs, ctDNA can also developed a novel dynamic gene-searching algorithm be derived from tumor-derived exosomes (6). Recent called Dynamic Gene Search (DyGS) to create a gene research conducted at Stanford University has developed panel for each of the 12 with the highest annual a method called CAPP-Seq that evaluates ctDNA to incidence and death rate. This algorithm generated lists profile and has the potential to reduce costs of genes for the 12 cancer types, ranging from 12 to 153 genes, with a median of 47 genes. Notably, many of the and increase detection sensitivity, which refers to how genes included in the panel can be targeted by various strong the stimulus must be for the technique to detect drugs. Therefore, the gene panels designed by the DyGS it (7). CAPP-Seq, also known as cancer personalized algorithm can be used as actionable drug targets for profiling by deep sequencing, is a sequencing method cancer treatment as well as biomarkers in liquid biopsy used to quantify cell-free DNA released from tumor cells to help identify the early stages of cancer. that entered the bloodstream (8). Currently, more than 40 commercial companies are racing to develop liquid Received: January 16, 2017; Accepted: June 5, 2017; biopsies; however, the gene panels generated have little Published: June 5, 2018 overlap. Gene panels contain genes associated with the disease under study, cancer in this case, and are Copyright: © 2018 Wang and Gong. All JEI articles utilized to analyze mutations in a given sample. This are distributed under the attribution non-commercial, function benefits cancer diagnosis due to the disease’s no derivative license (http://creativecommons.org/ known association with mutations. Companies such as licenses/by-nc-nd/3.0/). This means that anyone is free Guardant Health, Foundation Medicine, and Grail each to share, copy and distribute an unaltered article for non- have their own, specialized gene panels, which can lead commercial purposes provided the original author and to conflicting and even confusing results. To generate source is credited. consistent and comparable results as well as to reduce the cost of the test, an optimization algorithm based on Introduction public