A necroptosis‐related gene signature for predicting prognosis, immune landscape, and drug sensitivity in hepatocellular carcinoma
Abstract Background Hepatocellular carcinoma (HCC) remains a growing threat to global health. Necroptosis is a newly discovered form of cell necrosis that plays a vital role in cancer development. Thus, we conducted this study to identify a predictive signature of HCC based on necroptosis‐related ge...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2022-12-01
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| Series: | Cancer Medicine |
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| Online Access: | https://doi.org/10.1002/cam4.4812 |
| _version_ | 1798004873213509632 |
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| author | Junliang Chen Huaitao Wang Lei Zhou Zhihao Liu Hui Chen Xiaodong Tan |
| author_facet | Junliang Chen Huaitao Wang Lei Zhou Zhihao Liu Hui Chen Xiaodong Tan |
| author_sort | Junliang Chen |
| collection | DOAJ |
| description | Abstract Background Hepatocellular carcinoma (HCC) remains a growing threat to global health. Necroptosis is a newly discovered form of cell necrosis that plays a vital role in cancer development. Thus, we conducted this study to identify a predictive signature of HCC based on necroptosis‐related genes. Methods The tumor samples in the liver hepatocellular carcinoma (LIHC) cohort from The Cancer Genome Atlas (TCGA) database were subtyped using the consensus clustering algorithm. Univariate Cox regression and LASSO‐Cox analysis were performed to identify a gene signature from genes differentially expressed between tumor clusters. Then, we integrated the TNM stage and the prognostic model to build a nomogram. The gene signature and the nomogram were externally validated in the GSE14520 cohort from the Gene Expression Omnibus (GEO) and the LIRP‐JP cohort from the International Cancer Genome Consortium (ICGC). Evaluations of predictive performance evaluations were conducted using Kaplan–Meier plots, time‐dependent receiver operating characteristic curves, principal component analyses, concordance indices, and decision curve analyses. The tumor microenvironment was estimated using eight published methods. Finally, we forecasted the sensitivity of HCC patients to immunotherapy and chemotherapy based on this gene signature. Results We identified two necroptosis‐related clusters and a 10‐gene signature (MTMR2, CDCA8, S100A9, ANXA10, G6PD, SLC1A5, SLC2A1, SPP1, PLOD2, and MMP1). The gene signature and the nomogram had good predictive ability in the TCGA, ICGC, and GEO cohorts. The risk score was positively associated with the levels of necroptosis and immune cell infiltrations (especially of immunosuppressive cells). The high‐risk group could benefit more from immunotherapy and some chemotherapeutics than the low‐risk group. Conclusion The necroptosis‐related gene signature provides a new method for the risk stratification and treatment optimization of HCC. The nomogram can further improve predictive accuracy. |
| first_indexed | 2024-04-11T12:30:24Z |
| format | Article |
| id | doaj.art-9f08174e7a2846fc96c98252e9313597 |
| institution | Directory Open Access Journal |
| issn | 2045-7634 |
| language | English |
| last_indexed | 2024-04-11T12:30:24Z |
| publishDate | 2022-12-01 |
| publisher | Wiley |
| record_format | Article |
| series | Cancer Medicine |
| spelling | doaj.art-9f08174e7a2846fc96c98252e93135972022-12-22T04:23:47ZengWileyCancer Medicine2045-76342022-12-0111245079509610.1002/cam4.4812A necroptosis‐related gene signature for predicting prognosis, immune landscape, and drug sensitivity in hepatocellular carcinomaJunliang Chen0Huaitao Wang1Lei Zhou2Zhihao Liu3Hui Chen4Xiaodong Tan5Department of General Surgery Shengjing Hospital of China Medical University Shenyang Liaoning P. R. ChinaDepartment of General Surgery Shengjing Hospital of China Medical University Shenyang Liaoning P. R. ChinaDepartment of General Surgery Shengjing Hospital of China Medical University Shenyang Liaoning P. R. ChinaDepartment of General Surgery Shengjing Hospital of China Medical University Shenyang Liaoning P. R. ChinaDepartment of General Surgery Shengjing Hospital of China Medical University Shenyang Liaoning P. R. ChinaDepartment of General Surgery Shengjing Hospital of China Medical University Shenyang Liaoning P. R. ChinaAbstract Background Hepatocellular carcinoma (HCC) remains a growing threat to global health. Necroptosis is a newly discovered form of cell necrosis that plays a vital role in cancer development. Thus, we conducted this study to identify a predictive signature of HCC based on necroptosis‐related genes. Methods The tumor samples in the liver hepatocellular carcinoma (LIHC) cohort from The Cancer Genome Atlas (TCGA) database were subtyped using the consensus clustering algorithm. Univariate Cox regression and LASSO‐Cox analysis were performed to identify a gene signature from genes differentially expressed between tumor clusters. Then, we integrated the TNM stage and the prognostic model to build a nomogram. The gene signature and the nomogram were externally validated in the GSE14520 cohort from the Gene Expression Omnibus (GEO) and the LIRP‐JP cohort from the International Cancer Genome Consortium (ICGC). Evaluations of predictive performance evaluations were conducted using Kaplan–Meier plots, time‐dependent receiver operating characteristic curves, principal component analyses, concordance indices, and decision curve analyses. The tumor microenvironment was estimated using eight published methods. Finally, we forecasted the sensitivity of HCC patients to immunotherapy and chemotherapy based on this gene signature. Results We identified two necroptosis‐related clusters and a 10‐gene signature (MTMR2, CDCA8, S100A9, ANXA10, G6PD, SLC1A5, SLC2A1, SPP1, PLOD2, and MMP1). The gene signature and the nomogram had good predictive ability in the TCGA, ICGC, and GEO cohorts. The risk score was positively associated with the levels of necroptosis and immune cell infiltrations (especially of immunosuppressive cells). The high‐risk group could benefit more from immunotherapy and some chemotherapeutics than the low‐risk group. Conclusion The necroptosis‐related gene signature provides a new method for the risk stratification and treatment optimization of HCC. The nomogram can further improve predictive accuracy.https://doi.org/10.1002/cam4.4812gene signaturehepatocellular carcinomanecroptosisnomogramprognosistherapy |
| spellingShingle | Junliang Chen Huaitao Wang Lei Zhou Zhihao Liu Hui Chen Xiaodong Tan A necroptosis‐related gene signature for predicting prognosis, immune landscape, and drug sensitivity in hepatocellular carcinoma Cancer Medicine gene signature hepatocellular carcinoma necroptosis nomogram prognosis therapy |
| title | A necroptosis‐related gene signature for predicting prognosis, immune landscape, and drug sensitivity in hepatocellular carcinoma |
| title_full | A necroptosis‐related gene signature for predicting prognosis, immune landscape, and drug sensitivity in hepatocellular carcinoma |
| title_fullStr | A necroptosis‐related gene signature for predicting prognosis, immune landscape, and drug sensitivity in hepatocellular carcinoma |
| title_full_unstemmed | A necroptosis‐related gene signature for predicting prognosis, immune landscape, and drug sensitivity in hepatocellular carcinoma |
| title_short | A necroptosis‐related gene signature for predicting prognosis, immune landscape, and drug sensitivity in hepatocellular carcinoma |
| title_sort | necroptosis related gene signature for predicting prognosis immune landscape and drug sensitivity in hepatocellular carcinoma |
| topic | gene signature hepatocellular carcinoma necroptosis nomogram prognosis therapy |
| url | https://doi.org/10.1002/cam4.4812 |
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