Abstract 5028: Integration of molecular data into cancer patient database

Abstract

Abstract Background: Precision medicine holds promise of being a more effective method for treating complex diseases such as cancer. Nuanced care is needed, as the development and clinical course of cancer is multifactorial with influences from the general health status of the patient, germline and neoplastic mutations, co-morbidities, and environment including "lifestyle". To tailor an individualized treatment to the patient, such multifactorial data must be presented in an easy-to-use, easy-to-analyze fashion for providers to use effectively. Purpose: To address the need, we have built a searchable database integrating cancer-critical gene mutation status, serum galectin protein markers, serum and tumor glycomic profiles, with clinical, demographic, and lifestyle data points of individual patients. Methods: The initial data was acquired from breast, colon, and lung cancer patients’ serum and biopsy samples from the Prisma Health Cancer Institute Biorepository. The acquired data contains the status of 2,800 COSMIC cancer-critical gene mutations, individual patient profiles of five serum galectins, and serum and biopsy glycan structures from each patient’s glycomic profile. DNA from tumor cells was used to screen the regions frequently mutated in human cancer genes. Multiplex PCR using Ion AmpliSeq࣪ Cancer Hotspot panel v2 was performed by Precision Genetics. Enzyme-linked immunosorbent assay was employed to perform galectin profiling of cancer patient serum samples. Glycomic profiling of serum and biopsy samples was performed by the Emory Comprehensive Glycomic Core. In addition, healthy control values for galectin and glycomic profiles were obtained and added to the patient database for reference. The data is being stored using Microsoft SQL servers and is fed into an interactive web application using RStudio. Results: Our interactive database allows care providers to amalgamate cohorts from these groups to find correlations between different data types with the possibility of finding a "stage signature" based upon a combination of genetic mutations, galectin serum levels, glycan signatures, and patient clinical data and lifestyle choices. Conclusion: Our project provides a framework for an integrated interactive database to analyze molecular and clinical patterns across cancer stages and provides opportunities for increased diagnostic and prognostic power. Citation Format: Basil H. Chaballout, Avery T. Funkhouser, Bailey B. Blair, Jane L. Goodwin, Alexander M. Strigenz, Connie M. Arthur, Julie C. Martin, W. Jeffery Edenfield, Anna V. Blenda. Integration of molecular data into cancer patient database [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5028.