Data from Integrated multi-omics analysis of early lung adenocarcinoma links tumor biological features with predicted indolence or aggressiveness

• DOI: 10.1158/2767-9764.c.6729506.v1
• Publication Date: 2023-07-06T13:40:14Z
• Authors: Maria-Fernanda Se...; Yong Zou; Khushbu Patel; Shilin Zhao; Alexis Coullomb; Dianna J Rowe; Jonathan M Lehman; Jonathan Michael ...; Fabien Maldonado; Michael N Kammer; Vera Pancaldi; Carlos F Lopez

<div>Abstract<p>Lung adenocarcinoma (LUAD) is a heterogeneous group of tumors associated with different survival rates, even when detected at an early stage. Here, we aim to investigate the biological determinants LUAD indolence or aggressiveness using radiomics as surrogate behavior. We present set 92 patients data collected across methodologies. Patients were risk-stratified Computed Tomography–based Score Indicative Lung cancer Aggression (SILA) tool (0=least aggressive, 1= most aggressive). grouped indolent (x <= 0.4, n=14), intermediate (0.4 > x 0.6, n=27) and aggressive (0.6 1, n=52). Using CyTOF, identified subpopulations high HLA-DR expression that In RNA-Seq dataset, pathways related immune response behavior, while cell cycle proliferation extracted quantitative features from CT scans patients. Integrating these datasets four feature signatures patient clusters survival. single-cell RNA-Seq, found had significantly more T cells less B than tumors, latter higher abundance regulatory helpers. conclusion, able uncover correspondence between tumor biology, which could improve discrimination enhance our knowledge in biology offer novel personalized avenues for intervention.</p></div>