Gastric Cancer Registry: A comprehensive patient-reported resource for multidisciplinary and translational genomic approaches to gastric cancer
| Autor: | James M. Ford, Alison Almeda, Meredith A. Mills, Paul Van Hummelen, Hojoon Lee, Anna C Hooker, Hanlee P. Ji |
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| Rok vydání: | 2020 |
| Předmět: | |
| Zdroj: | Journal of Clinical Oncology. 38:432-432 |
| ISSN: | 1527-7755 0732-183X |
| DOI: | 10.1200/jco.2020.38.4_suppl.432 |
| Popis: | 432 Background: Gastric cancer (GC) is the fifth leading cancer diagnosis and third frequent cause of cancer death globally. GC results from a cascade of molecular and genetic changes owing to environmental and genetic factors. While there are known risks to GC, more is to be learned about its development so to establish effective screens for early stages of cancer. Methods: The Gastric Cancer Registry (GCR) was built to investigate GC and discover informative genomic biomarkers. The GCR comprises medical, family, and social history and genomics data from patients with GC, a family history of GC, and/or a known mutation in the gene CDH1. Samples of saliva and gastric tumors are collected when available. The GCR allows us to leverage several genome sequencing datasets to construct a complete molecular landscape of GC. Early analysis of GC tissue includes whole exome sequencing (WES) to identify mutations, whole genome sequencing (WGS) for copy number variation, and RNA sequencing (RNAseq) for expression profiling. Results are used to inform of clonal neoantigens, microbiome, and immune cell populations. Saliva will be analyzed with linked reads sequencing to unearth germline mutations not picked up in standard clinical gene panels. Results: Datasets from 455 patients and samples from 159 patients have been collected. In a pilot study, we pinpointed specific mutations using WES and revealed extensive changes in genome copy number involving clinically actionable genes through WGS. Most tumors had a high degree of genomic instability and exhibited candidate markers for treatment decisions and response. Additionally, we found that RNAseq revealed tumor subgroups through gene expression signatures. Conclusions: The GCR is an informative resource enabling the identification of biomarkers for GC. With the GCR we are integrating expertise in translational cancer genomics with molecular biology, statistics, and bioinformatics to build a platform for discovery and the development of tools that will ultimately improve the detection, treatment, and prevention of GC. |
| Databáze: | OpenAIRE |
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