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Introduction: Single-cell RNA sequencing of dissociated tumors enables the profiling of cellular states in fine detail, but erases the cellular organization of the analyzed tissue. Spatially resolved transcriptomics (SRT) using 10X Genomics’ Visium platform combines histological staining and RNA sequencing by capturing each transcript across spatially barcoded microarrays. SRT yields gene-expression matrices resolved within 55-micron array spots, and creates opportunities to explore how lung biology is affected by lung adenocarcinoma and how tumor cells and the proximal microenvironment are modulated by targeted therapy. Methods: SRT reactions (n=8) were performed on surgical specimens from human lung adenocarcinomas driven by kinase domain mutations of EGFR (exon 19 deletion, L858R point mutation, exon 20 insertion). SRT reactions analyzed primary lung cancer (n=5) or paired tumor-adjacent lung tissues (n=3). Results: 28458 array spots were recorded across all samples, and array spots captured a median of 5800 total transcripts and a median of 2416 unique transcripts. Single marker gene expression and unsupervised clustering across array spots corresponded with histological annotations of lung structures and adenocarcinoma. Integration of single-cell RNA sequencing data from lung adenocarcinoma specimens permitted mapping and quantification of 15 major cell types, including cancer cells, T- and B- lymphocytes, macrophages, dendritic cells, fibroblasts, and endothelial cells. Compared with paired tumor-adjacent lung tissues, adenocarcinoma tissues contained fibroblast-enriched desmoplasia and B-cell enriched tertiary lymphoid structures. In a clinical case with resistance to Osimertinib, the standard tyrosine kinase inhibitor, gene signature analysis of cancer-containing array spots revealed enrichment of gap-junction, fatty acid metabolism, and kynurenine pathway signatures compared to treatment naïve array spots. Conclusion: This pilot study demonstrates the feasibility of using SRT in lung adenocarcinoma. Paired with a single-cell atlas of lung adenocarcinoma during targeted therapy, this approach enables hypothesis-generation to investigate the alterations of tumor and tumor microenvironmental architecture in relation to targeted therapy. Citation Format: Daniel L. Kerr, Wei Wu, Whitney Tamaki, Anatoly Urisman, Yu-Ting Chou, Philippe Gui, David M. Jablons, Trever G. Bivona, Collin M. Blakely. Spatially resolved transcriptomics of cellular architecture in EGFR-mutated lung cancer [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 3808. |
