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. 2023 Apr 6;55(5):807–819. doi: 10.1038/s41588-023-01355-5

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© The Author(s) 2023

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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Extended Data Fig. 10 — Cell type identification and feature analysis from previously published single cell RNA-Seq data in NSCLC. (a) Analysis of top immunohistochemistry (IHC) markers for Tumor Intrinsic (TI) subtypes in single cell non-small cell lung cancer (NSCLC) data⁵¹. Leiden cluster 12 demonstrated moderate expression of all 3 IHC markers for the De-Differentiated TI-1 subtype identified from bulk RNA-Seq. Other cluster demonstrated Adeno, Squamous, or mixed Adeno/Squamous markers, with no predominantly Large Cell clusters. (b) Dotplots of the top 10 favorable (left) and unfavorable (right) single genes identified in limma voom analysis of the SU2C-MARK cohort, as expressed in single cell NSCLC data. As observed for features in the larger correlation blocks earlier (Fig. 7b), individual predictors with uncorrelated single cell profiles could be found within each category (for example, CXCL9 vs. CXCL11 among favorable predictors, and SIPA1L2 and PDLIM3 within unfavorable predictors).