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. 2022 Jul 6;20:302. doi: 10.1186/s12967-022-03510-8

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© The Author(s) 2022

Open AccessThis 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

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Fig. 4 — Chemotherapy alters the tumor microenvironment. A, B UMAP plots show patient-specific spatial transcriptomics (ST) expression patterns between colon1 and colon2, A UMAP plot of ST data after CCA, B UMAP plot of ST data without CCA. C Cell compositions predicted in different patients by ssGSEA, predicted cell compositions in all clusters (left), predicted cell composition in fibroblast cluster (middle), predicted cell composition in tumor cluster (right). D Boxplots show the cell compositions of iCAFs, NK cells and monocytes in all clusters. E, F Box plots show the patient-specific metabolism patterns scored by ssGSEA. p value < 0.05 was considered as cut-off criteria