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. 2023 Dec 18;13:22598. doi: 10.1038/s41598-023-48798-8

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© The Author(s) 2023, corrected publication 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/.

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The DEGs and pathway enrichment analysis acquired unsupervised hierarchical clustering of LAMA3 stratified CCA sample of microarray dataset. (a) Heatmap image and (b) PCA plot indicating the separation low and high LAMA3 expression. (c) DEGs in high vs low LAMA3 expression group. Statistically significant DEGs cut-off are with the adjusted P < 0.05 and the Log2 FC of 3.32. (d) Pathway enrichment analysis of DEGs using EnrichR consolidated databases: BioPlanet, KEGG and Wikipathways. DEGs were considered at FC > 2 and P < 0.05. Enriched pathway were considered when combined score > 50.