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Abstract：
Hepatocellular carcinoma (HCC) is a highly prevalent and fatal cancer. The role of PANoptosis, a novel form of programmed cell death, in HCC is yet to be fully understood. This study focuses on identifying and analyzing PANoptosis-associated differentially expressed genes in HCC (HPAN_DEGs), aiming to enhance our understanding of HCC pathogenesis and potential treatment strategies.
We analyzed HCC differentially expressed genes from TCGA and IGCG databases and mapped them to the PANoptosis gene set, identifying 69 HPAN_DEGs. These genes underwent enrichment analyses, and consensus clustering analysis was used to determine three distinct HCC subgroups based on their expression profiles. The immune characteristics and mutation landscape of these subgroups were evaluated, and drug sensitivity was predicted using the HPAN-index and relevant databases.
The HPAN_DEGs were mainly enriched in pathways associated with the cell cycle, DNA damage, Drug metabolism, Cytokines, and Immune receptors. We identified three HCC subtypes (Cluster_1, SFN+PDK4-; Cluster_2, SFN-PDK4+; Cluster_3, SFN/PDK4 intermediate expression) based on the expression profiles of the 69 HPAN_DEGs. These subtypes exhibited distinct clinical outcomes, immune characteristics, and mutation landscapes. The HPAN-index, generated by machine learning using the expression levels of 69 HPAN_DEGs, was identified as an independent prognostic factor for HCC. Moreover, the high HPAN-index group exhibited a high response to immunotherapy, while the low HPAN-index group showed sensitivity to small molecule targeted drugs. Notably, we observed that the YWHAB gene plays a significant role in Sorafenib resistance.
This study identified 69 HPAN_DEGs crucial to tumor growth, immune infiltration, and drug resistance in HCC. Additionally, we discovered three distinct HCC subtypes and constructed an HPAN-index to predict immunotherapeutic response and drug sensitivity. Our findings underscore the role of YWHAB in Sorafenib resistance, presenting valuable insights for personalized therapeutic strategy development in HCC.
We analyzed HCC differentially expressed genes from TCGA and IGCG databases and mapped them to the PANoptosis gene set, identifying 69 HPAN_DEGs. These genes underwent enrichment analyses, and consensus clustering analysis was used to determine three distinct HCC subgroups based on their expression profiles. The immune characteristics and mutation landscape of these subgroups were evaluated, and drug sensitivity was predicted using the HPAN-index and relevant databases.
The HPAN_DEGs were mainly enriched in pathways associated with the cell cycle, DNA damage, Drug metabolism, Cytokines, and Immune receptors. We identified three HCC subtypes (Cluster_1, SFN+PDK4-; Cluster_2, SFN-PDK4+; Cluster_3, SFN/PDK4 intermediate expression) based on the expression profiles of the 69 HPAN_DEGs. These subtypes exhibited distinct clinical outcomes, immune characteristics, and mutation landscapes. The HPAN-index, generated by machine learning using the expression levels of 69 HPAN_DEGs, was identified as an independent prognostic factor for HCC. Moreover, the high HPAN-index group exhibited a high response to immunotherapy, while the low HPAN-index group showed sensitivity to small molecule targeted drugs. Notably, we observed that the YWHAB gene plays a significant role in Sorafenib resistance.
This study identified 69 HPAN_DEGs crucial to tumor growth, immune infiltration, and drug resistance in HCC. Additionally, we discovered three distinct HCC subtypes and constructed an HPAN-index to predict immunotherapeutic response and drug sensitivity. Our findings underscore the role of YWHAB in Sorafenib resistance, presenting valuable insights for personalized therapeutic strategy development in HCC.
摘要：
■肝细胞癌（HCC）是一种非常普遍和致命的癌症。PANoptosis的作用，一种新形式的程序性细胞死亡，在HCC中尚未完全了解。本研究的重点是识别和分析肝癌中PANoptosis相关的差异表达基因（HPAN_DEGs），旨在增强我们对HCC发病机制和潜在治疗策略的理解。
■我们分析了来自TCGA和IGCG数据库的HCC差异表达基因，并将它们映射到PANoptosis基因集，识别69个HPAN_DEG。这些基因进行了富集分析，和共识聚类分析用于根据其表达谱确定三个不同的HCC亚组。评估了这些亚组的免疫特征和突变景观，使用HPAN指数和相关数据库预测药物敏感性。
■HPAN_DEGs主要富集在与细胞周期相关的通路中，DNA损伤,药物代谢，细胞因子,和免疫受体。我们根据69个HPAN_DEG的表达谱确定了三种HCC亚型（Cluster_1，SFNPDK4-;Cluster_2，SFN-PDK4;Cluster_3，SFN/PDK4中间表达）。这些亚型表现出不同的临床结果，免疫特性，和突变景观。HPAN指数，由机器学习使用69个HPAN_DEG的表达水平生成，被确定为HCC的独立预后因素。此外，高HPAN指数组表现出对免疫疗法的高反应，而低HPAN指数组显示出对小分子靶向药物的敏感性。值得注意的是,我们观察到YWHAB基因在索拉非尼抗性中起重要作用。
■这项研究确定了69个对肿瘤生长至关重要的HPAN_DEGs，免疫浸润，和肝癌的耐药性。此外,我们发现了三种不同的HCC亚型,并构建了HPAN指数来预测免疫治疗应答和药物敏感性.我们的发现强调了YWHAB在索拉非尼耐药性中的作用，为肝癌个性化治疗策略的制定提供有价值的见解。
■我们分析了来自TCGA和IGCG数据库的HCC差异表达基因，并将它们映射到PANoptosis基因集，识别69个HPAN_DEG。这些基因进行了富集分析，和共识聚类分析用于根据其表达谱确定三个不同的HCC亚组。评估了这些亚组的免疫特征和突变景观，使用HPAN指数和相关数据库预测药物敏感性。
■HPAN_DEGs主要富集在与细胞周期相关的通路中，DNA损伤,药物代谢，细胞因子,和免疫受体。我们根据69个HPAN_DEG的表达谱确定了三种HCC亚型（Cluster_1，SFNPDK4-;Cluster_2，SFN-PDK4;Cluster_3，SFN/PDK4中间表达）。这些亚型表现出不同的临床结果，免疫特性，和突变景观。HPAN指数，由机器学习使用69个HPAN_DEG的表达水平生成，被确定为HCC的独立预后因素。此外，高HPAN指数组表现出对免疫疗法的高反应，而低HPAN指数组显示出对小分子靶向药物的敏感性。值得注意的是,我们观察到YWHAB基因在索拉非尼抗性中起重要作用。
■这项研究确定了69个对肿瘤生长至关重要的HPAN_DEGs，免疫浸润，和肝癌的耐药性。此外,我们发现了三种不同的HCC亚型,并构建了HPAN指数来预测免疫治疗应答和药物敏感性.我们的发现强调了YWHAB在索拉非尼耐药性中的作用，为肝癌个性化治疗策略的制定提供有价值的见解。
