ORIGINAL RESEARCH article
Front. Immunol.
Sec. Cancer Immunity and Immunotherapy
Volume 16 - 2025 | doi: 10.3389/fimmu.2025.1671956
This article is part of the Research TopicImmune Predictive and Prognostic Biomarkers in Immuno-Oncology: Refining the Immunological Landscape of CancerView all 45 articles
Integration of bulk and single-cell transcriptomic data reveals a novel signature related to liver metastasis and basement membrane in pancreatic cancer
Provisionally accepted
- Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
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Background: Pancreatic cancer (PC) is characterized by an exceptionally poor prognosis. Liver metastasis is the predominant distant metastasis model of PC. This study aims to construct a prognostic model based on PCLM and BM-related genes, while also validating the association between this model and the immune microenvironment of PC, as well as its predictive value for the efficacy of chemotherapy and immunotherapy. Methods: Transcriptomic, mutation, and clinical data were retrieved from the TCGA, ICGC, and GEO databases. Core prognostic genes were identified through single-cell (sc) and bulk transcriptomic sequencing data combined with WGCNA analysis. The prognostic model was established using machine learning algorithms and multivariate Cox regression analyses. Specifically, the TCGA-PAAD cohort was utilized as the training set while the PACA-AU cohort served as the validation set. The performance of this model was assessed in both the training and validation sets. Additionally, the associations between the model and tumor mutation burden (TMB) as well as tumor immunity were evaluated using multiple immunity databases. Additionally, the predictive capacity of the model regarding the efficacy of chemotherapy, immunotherapy, and targeted therapy was also assessed. Finally, the expression of COL7A1 was knockdown in cancer-associated fibroblasts (CAFs) in PC to explore its role in PC metastasis. Results: 30 PCLM and BM-related prognostic genes were preliminarily identified integrating sc and bulk transcriptomic data. Six signatures, including COL7A1, ITGA6, ITGA7, ITGB5, ITGB7 and NTN4, were subsequently utilized to construct a prognostic model for PC patients. Tumor immunity analysis revealed different immune landscapes between high- and low-risk groups . Furthermore, the high-risk group displayed significantly higher IC50 values for common PC chemotherapeutics. Notably, scRNA-seq analysis indicated that COL7A1 predominantly expressed in fibroblasts. Specifically, CAFs exhibited significantly higher COL7A1 expression compared with normal pancreatic fibroblasts, while knockdown of COL7A1 in CAFs significantly decreased migration ability of PC cells. Conclusion: This study developed and validated an innovative prognostic model for PC. This model may also serve as potential tool for predicting the tumor immune microenvironment and therapeutic efficacy. Notably, COL7A1, which was demonstrated to be significant in this study, warrants further investigation in future research.
Keywords: Pancreatic Cancer, liver metastasis, Basement Membrane, Prognostic model, Immunotherapy response, ScRNA-seq
Received: 23 Jul 2025; Accepted: 14 Oct 2025.
Copyright: © 2025 Zhou, Zhong, Yang, Cui and Wang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Yizhi Wang, wyz_pumch@zju.edu.cn
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