Abstract 1153: Using spatial transcriptomics to dissect cell to cell cooperation in lung adenocarcinoma

Abstract

Abstract Lung cancer is the second most common cancer in the United States and the leading cause of cancer related deaths in this country. Unfortunately, efficacious treatments for lung cancer remain suboptimal. Lung cancer is characterized by several distinct subtypes of which lung adenocarcinoma is the most common, comprising about 40% of this malignancy. The hallmark gene mutations of lung adenocarcinoma include TP53, RAS, and STK11. LKB1 is a serine-threonine kinase (coded by the gene STK11) that largely functions as a tumor suppressor, and is mutated in 20-30% of non-small cell lung cancers (NSCLCs). The diversity between and within lung cancer subtypes, as well as within a patient (i.e. metastases vs primary tumor), makes treating this cancer very challenging. Lung adenocarcinoma, in particular, has collective invasion packs of cells adjacent to the primary tumor that correlate with metastatic disease in mouse models. We hypothesize that the transcriptomic profile of the collective invasion packs in lung adenocarcinoma patients varies significantly from the adjacent primary tumor and represents a targetable metastatic sub-population. This work will help to identify specific cell signaling pathways that have the translational potential to develop novel therapeutics for metastatic disease, ultimately improving patient outcomes through precision medicine. Utilizing patient lung adenocarcinoma samples with KRAS and KRAS+LKB1 mutations, we identified regions of interest including bulk tumor and surrounding invasion packs. Then, using GeoMx digital spatial profiling technology (by Nanostring) and next-gen sequencing, we generated transcriptomic profiles from bulk tumor and invasion packs. Preliminary results indicate region specific transcriptomic differences, highlighting the heterogeneity of these cell populations. More specifically, collective invasion packs exhibit upregulation of gene networks involving immune cell differentiation, function, oxidative phosphorylation, tumor invasiveness, and mitochondrial structure. To discern the metastatic potential, transcriptomic profiles and biological functions will be compared between invasion packs, tumor bulk vs invasion packs, and finally, inter-patient differences. Successful completion of this project will characterize transcriptomes of metastatic lung cancer and has the potential to ultimately identify biomarkers of aggressive disease. Lastly, this foundational study will pave the way for future studies on the transcriptomic landscape of metastatic pediatric cancers and cancer predisposition syndromes. Citation Format: Raehannah Jamshidi, Lyra Griffiths, Rich Johnston, Vaunita Parihar, Frank Schneider, Adam Marcus. Using spatial transcriptomics to dissect cell to cell cooperation in lung adenocarcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1153.