Tumor-associated macrophage-based predictive and prognostic model for hepatocellular carcinoma.
Hepatocellular carcinoma (HCC) is a prevalent malignancy influenced by the interplay between the immune system and tumor progression, but the detailed biological mechanism still elusive. To address this, we integrate single-cell RNA sequencing (scRNAseq) data with bulk sequencing data to investigate...
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2025-01-01
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| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0325120 |
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| author | Changquan Shang Tiancong He Yi Zhang |
| author_facet | Changquan Shang Tiancong He Yi Zhang |
| author_sort | Changquan Shang |
| collection | DOAJ |
| description | Hepatocellular carcinoma (HCC) is a prevalent malignancy influenced by the interplay between the immune system and tumor progression, but the detailed biological mechanism still elusive. To address this, we integrate single-cell RNA sequencing (scRNAseq) data with bulk sequencing data to investigate the prognostic significance of tumor-associated macrophages (TAMs) signatures in HCC. Utilizing bioinformatics approaches, including differential gene expression analysis, Cox regression, and logistic regression modeling, we constructed a robust prognostic model that effectively stratifies HCC patients into distinct risk groups with significant differences in survival outcomes. Applying our model to multiple HCC cohorts, robust predictive and prognostic performances were observed. Moreover, examination of the tumor microenvironment (TME) revealed distinct patterns of immune cell infiltration between high-risk and low-risk patient groups, which may contribute to the poorer outcomes observed in high-risk patients. Finally, drug sensitivity and AutoDock simulations suggest that the signature genes we identified could be potential targets for HCC therapy. In summary, this study provides novel insights into the HCC tumor microenvironment and its interaction with TAMs, offering a prognostic model with potential for improving patient stratification and guiding the development of novel therapeutic approaches. Future research ought to concentrate on confirming our findings in larger, prospective studies and examining the functional implications of TAMs in HCC progression. |
| format | Article |
| id | doaj-art-7c7d735ff3f14ea3b13b2e3e37b637d9 |
| institution | Matheson Library |
| issn | 1932-6203 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj-art-7c7d735ff3f14ea3b13b2e3e37b637d92025-07-10T05:31:21ZengPublic Library of Science (PLoS)PLoS ONE1932-62032025-01-01207e032512010.1371/journal.pone.0325120Tumor-associated macrophage-based predictive and prognostic model for hepatocellular carcinoma.Changquan ShangTiancong HeYi ZhangHepatocellular carcinoma (HCC) is a prevalent malignancy influenced by the interplay between the immune system and tumor progression, but the detailed biological mechanism still elusive. To address this, we integrate single-cell RNA sequencing (scRNAseq) data with bulk sequencing data to investigate the prognostic significance of tumor-associated macrophages (TAMs) signatures in HCC. Utilizing bioinformatics approaches, including differential gene expression analysis, Cox regression, and logistic regression modeling, we constructed a robust prognostic model that effectively stratifies HCC patients into distinct risk groups with significant differences in survival outcomes. Applying our model to multiple HCC cohorts, robust predictive and prognostic performances were observed. Moreover, examination of the tumor microenvironment (TME) revealed distinct patterns of immune cell infiltration between high-risk and low-risk patient groups, which may contribute to the poorer outcomes observed in high-risk patients. Finally, drug sensitivity and AutoDock simulations suggest that the signature genes we identified could be potential targets for HCC therapy. In summary, this study provides novel insights into the HCC tumor microenvironment and its interaction with TAMs, offering a prognostic model with potential for improving patient stratification and guiding the development of novel therapeutic approaches. Future research ought to concentrate on confirming our findings in larger, prospective studies and examining the functional implications of TAMs in HCC progression.https://doi.org/10.1371/journal.pone.0325120 |
| spellingShingle | Changquan Shang Tiancong He Yi Zhang Tumor-associated macrophage-based predictive and prognostic model for hepatocellular carcinoma. PLoS ONE |
| title | Tumor-associated macrophage-based predictive and prognostic model for hepatocellular carcinoma. |
| title_full | Tumor-associated macrophage-based predictive and prognostic model for hepatocellular carcinoma. |
| title_fullStr | Tumor-associated macrophage-based predictive and prognostic model for hepatocellular carcinoma. |
| title_full_unstemmed | Tumor-associated macrophage-based predictive and prognostic model for hepatocellular carcinoma. |
| title_short | Tumor-associated macrophage-based predictive and prognostic model for hepatocellular carcinoma. |
| title_sort | tumor associated macrophage based predictive and prognostic model for hepatocellular carcinoma |
| url | https://doi.org/10.1371/journal.pone.0325120 |
| work_keys_str_mv | AT changquanshang tumorassociatedmacrophagebasedpredictiveandprognosticmodelforhepatocellularcarcinoma AT tianconghe tumorassociatedmacrophagebasedpredictiveandprognosticmodelforhepatocellularcarcinoma AT yizhang tumorassociatedmacrophagebasedpredictiveandprognosticmodelforhepatocellularcarcinoma |