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. 2024 Jan 31;21:3. doi: 10.1186/s12989-024-00565-x

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© The Author(s) 2024

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 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 — Transcriptome profiling of tumors induced by MWCNTs and amosite asbestos. A Principal component analysis (PCA) shows clear separation of tumors from the control peritoneal tissues. B Unsupervised hierarchical clustering analysis and heat map of 3062 filtered genes at fold change < − 2 or > 2, ANOVA P < 0.001, and FDR P < 0.001. C Hierarchical clustering and heat map on a few selected genes encoding for proteins such as mesothelin, osteopontin, caveolin, integrin, syndecan, chemokine, and interleukin. D Venn diagrams display the quantity of genes that are common and unique among the datasets of MWCNT B, MWCNT C, and amosite asbestos. The genes in the Venn diagrams were filtered using fold change < − 2 or > 2, ANOVA P < 0.05, and FDR P < 0.05. Quality control criteria and bioinformatics tools were according to Transcriptome Analysis Console (TAC 4.0.2, Thermo Fisher Scientific)