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Background <p>Hepatocellular carcinoma (HCC) is the most common primary liver cancer, characterized by high heterogeneity and poor prognosis. Chromatin remodeling regulates chromatin structure and function, and its dysregulation promotes tumor progression. Histone deacetylase 2 (HDAC2) is a key regulator involved in this process. This study links clinicopathological features with molecular mechanisms to elucidate the role of the chromatin-remodeling factor HDAC2 in hepatocellular carcinoma.</p> Method <p>Based on whole-slide images (WSIs) from TCGA-LIHC, pathological features were extracted by combining ResNet-50 and CellProfiler to build a prognostic model. SHAP was subsequently applied to interpret the most influential predictive features. Through integrative multi-omics analysis, HDAC2 was identified as a core gene, and its association with malignant phenotypes was validated using the Human Protein Atlas (HPA), bulk transcriptomic data, and single-cell datasets. Malignant cells were further identified with inferCNVpy, while CellChat and Vector were used to characterize intercellular communication and developmental trajectories. Finally, spatial transcriptomics integrated with the Spotlight and MISTy algorithms revealed the spatial distribution of HDAC2 and its interactions within the tumor microenvironment. The pro-tumor capability of HDAC2 was verified by both cell-based assays and nude mouse tumorigenicity experiments.</p> Results <p>From WSIs, 630 features were extracted with CellProfiler and 2,048 with ResNet-50. the top nine prognostic features were used to build a Lasso + GBM model selected from 101 machine learning algorithm combinations. SHAP analysis revealed the contribution of each feature. Correlation analysis with a curated chromatin remodeling gene set identified 49 genes significantly associated with these 9 features. For HDAC2, integrative analyses across bulk, single-cell, and spatial transcriptomics revealed its biological roles and underlying mechanisms. ROC curve analysis confirmed strong predictive performance, with average AUCs of 0.84 and 0.77 in the training and validation sets, respectively. HDAC2 knockdown reduced IL-1β/IL-6/TNF-α transcripts, lowered colony formation by ~ 55%, curbed invasion/migration by ~ 30–50% (<i>P</i> &lt; 0.001), and trimmed xenograft weight by ~ 35% (<i>P</i> &lt; 0.01), confirming that HDAC2 drives proliferation, motility and in-vivo tumorigenicity.</p> Conclusion <p>HDAC2 drives hepatocellular carcinoma (HCC) progression by strengthening intercellular communication and forming a spatially organized oncogenic axis. Further analyses indicate that HDAC2-high cells can be regarded as differentiation origin points of the tumor and are significantly associated with poor prognosis.</p>

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HDAC2-mediated chromatin remodeling drives hepatocellular carcinoma progression: an integrative analysis of computational pathology and multi-transcriptomics

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年12月9日

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  • Shiyang Yin,
  • Xuancheng Zhou,
  • Lai Jiang,
  • Yuheng Gu,
  • Jingxuan Dai,
  • Haiqing Chen,
  • Shengke Zhang,
  • Jiaan Lu,
  • Gang Huang,
  • Yuxuan Jiang,
  • Xun Sang,
  • Kun Yuan,
  • Hua Yang,
  • Guanhu Yang,
  • Shangke Huang,
  • Hao Chi,
  • Ke Xu

摘要

Background

Hepatocellular carcinoma (HCC) is the most common primary liver cancer, characterized by high heterogeneity and poor prognosis. Chromatin remodeling regulates chromatin structure and function, and its dysregulation promotes tumor progression. Histone deacetylase 2 (HDAC2) is a key regulator involved in this process. This study links clinicopathological features with molecular mechanisms to elucidate the role of the chromatin-remodeling factor HDAC2 in hepatocellular carcinoma.

Method

Based on whole-slide images (WSIs) from TCGA-LIHC, pathological features were extracted by combining ResNet-50 and CellProfiler to build a prognostic model. SHAP was subsequently applied to interpret the most influential predictive features. Through integrative multi-omics analysis, HDAC2 was identified as a core gene, and its association with malignant phenotypes was validated using the Human Protein Atlas (HPA), bulk transcriptomic data, and single-cell datasets. Malignant cells were further identified with inferCNVpy, while CellChat and Vector were used to characterize intercellular communication and developmental trajectories. Finally, spatial transcriptomics integrated with the Spotlight and MISTy algorithms revealed the spatial distribution of HDAC2 and its interactions within the tumor microenvironment. The pro-tumor capability of HDAC2 was verified by both cell-based assays and nude mouse tumorigenicity experiments.

Results

From WSIs, 630 features were extracted with CellProfiler and 2,048 with ResNet-50. the top nine prognostic features were used to build a Lasso + GBM model selected from 101 machine learning algorithm combinations. SHAP analysis revealed the contribution of each feature. Correlation analysis with a curated chromatin remodeling gene set identified 49 genes significantly associated with these 9 features. For HDAC2, integrative analyses across bulk, single-cell, and spatial transcriptomics revealed its biological roles and underlying mechanisms. ROC curve analysis confirmed strong predictive performance, with average AUCs of 0.84 and 0.77 in the training and validation sets, respectively. HDAC2 knockdown reduced IL-1β/IL-6/TNF-α transcripts, lowered colony formation by ~ 55%, curbed invasion/migration by ~ 30–50% (P < 0.001), and trimmed xenograft weight by ~ 35% (P < 0.01), confirming that HDAC2 drives proliferation, motility and in-vivo tumorigenicity.

Conclusion

HDAC2 drives hepatocellular carcinoma (HCC) progression by strengthening intercellular communication and forming a spatially organized oncogenic axis. Further analyses indicate that HDAC2-high cells can be regarded as differentiation origin points of the tumor and are significantly associated with poor prognosis.