Identification of Hepatocellular Carcinoma Subtypes Based on Global Gene Expression Profiling to Predict the Prognosis and Potential Therapeutic Drugs
<b>Background:</b> Hepatocellular carcinoma (HCC) is a highly heterogeneous tumor, and distinguishing its subtypes holds significant value for diagnosis, treatment, and the prognosis. <b>Methods:</b> Unsupervised clustering analysis was conducted to classify HCC subtypes. Sub...
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2025-01-01
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| author | Cunzhen Zhang Jiyao Wang Lin Jia Qiang Wen Na Gao Hailing Qiao |
| author_facet | Cunzhen Zhang Jiyao Wang Lin Jia Qiang Wen Na Gao Hailing Qiao |
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| description | <b>Background:</b> Hepatocellular carcinoma (HCC) is a highly heterogeneous tumor, and distinguishing its subtypes holds significant value for diagnosis, treatment, and the prognosis. <b>Methods:</b> Unsupervised clustering analysis was conducted to classify HCC subtypes. Subtype signature genes were identified using LASSO, SVM, and logistic regression. Survival-related genes were identified using Cox regression, and their expression and function were validated via qPCR and gene interference. GO, KEGG, GSVA, and GSEA were used to determine enriched signaling pathways. ESTIMATE and CIBERSORT were used to calculate the stromal score, tumor purity, and immune cell infiltration. TIDE was employed to predict the patient response to immunotherapy. Finally, drug sensitivity was analyzed using the oncoPredict algorithm. <b>Results:</b> Two HCC subtypes with different gene expression profiles were identified, where subtype S1 exhibited a significantly shorter survival time. A subtype scoring formula and a nomogram were constructed, both of which showed an excellent predictive performance. COL11A1 and ACTL8 were identified as survival-related genes among the signature genes, and the downregulation of COL11A1 could suppress the invasion and migration of HepG2 cells. Subtype S1 was characterized by the upregulation of pathways related to collagen and the extracellular matrix, as well as downregulation associated with the xenobiotic metabolic process and fatty acid degradation. Subtype S1 showed higher stromal scores, immune scores, and ESTIMATE scores and infiltration of macrophages M0 and plasma cells, as well as lower tumor purity and infiltration of NK cells (resting/activated) and resting mast cells. Subtype S2 was more likely to benefit from immunotherapy. Subtype S1 appeared to be more sensitive to BMS-754807, JQ1, and Axitinib, while subtype S2 was more sensitive to SB505124, Pevonedistat, and Tamoxifen. <b>Conclusions:</b> HCC patients can be classified into two subtypes based on their gene expression profiles, which exhibit distinctions in terms of signaling pathways, the immune microenvironment, and drug sensitivity. |
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| institution | Kabale University |
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| language | English |
| publishDate | 2025-01-01 |
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| spelling | doaj-art-15e9b588b65a41ddb9bec89ac04413f92025-01-24T13:24:30ZengMDPI AGBiomedicines2227-90592025-01-0113123610.3390/biomedicines13010236Identification of Hepatocellular Carcinoma Subtypes Based on Global Gene Expression Profiling to Predict the Prognosis and Potential Therapeutic DrugsCunzhen Zhang0Jiyao Wang1Lin Jia2Qiang Wen3Na Gao4Hailing Qiao5Institute of Clinical Pharmacology, School of Basic Medical Sciences, Zhengzhou University, Zhengzhou 450001, ChinaInstitute of Clinical Pharmacology, School of Basic Medical Sciences, Zhengzhou University, Zhengzhou 450001, ChinaInstitute of Clinical Pharmacology, School of Basic Medical Sciences, Zhengzhou University, Zhengzhou 450001, ChinaInstitute of Clinical Pharmacology, School of Basic Medical Sciences, Zhengzhou University, Zhengzhou 450001, ChinaInstitute of Clinical Pharmacology, School of Basic Medical Sciences, Zhengzhou University, Zhengzhou 450001, ChinaInstitute of Clinical Pharmacology, School of Basic Medical Sciences, Zhengzhou University, Zhengzhou 450001, China<b>Background:</b> Hepatocellular carcinoma (HCC) is a highly heterogeneous tumor, and distinguishing its subtypes holds significant value for diagnosis, treatment, and the prognosis. <b>Methods:</b> Unsupervised clustering analysis was conducted to classify HCC subtypes. Subtype signature genes were identified using LASSO, SVM, and logistic regression. Survival-related genes were identified using Cox regression, and their expression and function were validated via qPCR and gene interference. GO, KEGG, GSVA, and GSEA were used to determine enriched signaling pathways. ESTIMATE and CIBERSORT were used to calculate the stromal score, tumor purity, and immune cell infiltration. TIDE was employed to predict the patient response to immunotherapy. Finally, drug sensitivity was analyzed using the oncoPredict algorithm. <b>Results:</b> Two HCC subtypes with different gene expression profiles were identified, where subtype S1 exhibited a significantly shorter survival time. A subtype scoring formula and a nomogram were constructed, both of which showed an excellent predictive performance. COL11A1 and ACTL8 were identified as survival-related genes among the signature genes, and the downregulation of COL11A1 could suppress the invasion and migration of HepG2 cells. Subtype S1 was characterized by the upregulation of pathways related to collagen and the extracellular matrix, as well as downregulation associated with the xenobiotic metabolic process and fatty acid degradation. Subtype S1 showed higher stromal scores, immune scores, and ESTIMATE scores and infiltration of macrophages M0 and plasma cells, as well as lower tumor purity and infiltration of NK cells (resting/activated) and resting mast cells. Subtype S2 was more likely to benefit from immunotherapy. Subtype S1 appeared to be more sensitive to BMS-754807, JQ1, and Axitinib, while subtype S2 was more sensitive to SB505124, Pevonedistat, and Tamoxifen. <b>Conclusions:</b> HCC patients can be classified into two subtypes based on their gene expression profiles, which exhibit distinctions in terms of signaling pathways, the immune microenvironment, and drug sensitivity.https://www.mdpi.com/2227-9059/13/1/236hepatocellular carcinomasubtypesdiagnostic modelimmune microenvironmentdrug sensitivity |
| spellingShingle | Cunzhen Zhang Jiyao Wang Lin Jia Qiang Wen Na Gao Hailing Qiao Identification of Hepatocellular Carcinoma Subtypes Based on Global Gene Expression Profiling to Predict the Prognosis and Potential Therapeutic Drugs Biomedicines hepatocellular carcinoma subtypes diagnostic model immune microenvironment drug sensitivity |
| title | Identification of Hepatocellular Carcinoma Subtypes Based on Global Gene Expression Profiling to Predict the Prognosis and Potential Therapeutic Drugs |
| title_full | Identification of Hepatocellular Carcinoma Subtypes Based on Global Gene Expression Profiling to Predict the Prognosis and Potential Therapeutic Drugs |
| title_fullStr | Identification of Hepatocellular Carcinoma Subtypes Based on Global Gene Expression Profiling to Predict the Prognosis and Potential Therapeutic Drugs |
| title_full_unstemmed | Identification of Hepatocellular Carcinoma Subtypes Based on Global Gene Expression Profiling to Predict the Prognosis and Potential Therapeutic Drugs |
| title_short | Identification of Hepatocellular Carcinoma Subtypes Based on Global Gene Expression Profiling to Predict the Prognosis and Potential Therapeutic Drugs |
| title_sort | identification of hepatocellular carcinoma subtypes based on global gene expression profiling to predict the prognosis and potential therapeutic drugs |
| topic | hepatocellular carcinoma subtypes diagnostic model immune microenvironment drug sensitivity |
| url | https://www.mdpi.com/2227-9059/13/1/236 |
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