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. 2023 Jun 4;23(2):196. doi: 10.1007/s10142-023-01122-z

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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 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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Fig. 6 — Prognosis-related purity-independent three-gene network visualization. A Purity-independent regulatory network constructed using 3 prognosis-related mRNAs, 15 miRNAs, and 3 lncRNAs. B Time-dependent receiver operating characteristic (ROC) curves of the construction group (n = 540) for overall survival prediction using the three-gene model. C One-year time-dependent ROC curves for overall survival, showing higher area under the curve (AUC) values for the three-gene model compared to other clinic al factors in the validation groups (n = 288). D Time-dependent ROC curves of the validation group (n = 288) for overall survival prediction using the three-gene model. E One-year time-dependent ROC curves for overall survival, demonstrating higher AUC values for the three-gene model compared to other clinical factors in the validation groups (n = 288). F Decision curve analysis of the three-gene model, clinical models, and the combined model at 12 months post-pancreatectomy in the construction group (n = 540). G Frequency count of variables selected using the LASSO algorithm, repeated 1000 times in The Cancer Genome Atlas (TCGA) using BLASSO (n = 160). H Violin plot of ITGA3 expression constructed using the single-cell pancreatic cancer dataset of Peng et al. Cell types are arranged from left to right based on decreasing ITGA3 expression (n = 35)