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. 2023 Apr 12;21:255. doi: 10.1186/s12967-023-04080-z

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© The Author(s) 2023

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. 1 — Bioinformatics analysis of FAP biological and tumor microenvironment characteristics in pancreatic cancer. a Pan-cancer analysis of FAP expression. b Identification of optimal FAP expression cutoff dividing PDAC cohort. The upper scatter plot shows each cutoff point’s standardized log-rank statistic value. The lower Kaplan-Meier plot shows overall survival for patients divided by the optimal cutoff. c–f Biology and TME characteristics in high-FAP vs. low-FAP groups of PDAC cohort. c Density distribution of tumor purity. d Enrichment score of HALLMARK gene-sets related to high FAP expression. e Volcano map of the chemokines. f Immune suppressive characteristics estimated by IOBR. g IHC staining of FAP protein expression in 9 pancreatic cancer samples