Scholarlink

<p>Lung adenocarcinoma (LUAD) shows marked heterogeneity, limiting the effectiveness of traditional classifications. We integrated bulk transcriptomic data from TCGA and multicenter cohorts with spatial transcriptomics for in situ validation. Analysis of glucocorticoid (GC) and mitophagy pathways identified 127 core genes, enabling a novel molecular subtyping and survival risk model that predicted prognosis and correlated with immune infiltration. High mobility group AT-hook 1 (HMGA1) emerged as a key regulator of tumor metabolism, immune evasion, and therapy resistance. Spatial transcriptomics with RCTD-based deconvolution showed a tumor-enriched and heterogeneous HMGA1 expression pattern and a positive spatial association with epithelial cell proportion in tumor sections. Single-cell RNA-seq analysis further resolved HMGA1 enrichment to tumor epithelial cells, and CIBERSORTx projection linked the HMGA1-high tumor epithelial cell state to poor prognosis and increased proliferation. Functional assays showed that high HMGA1 expression conferred sensitivity to metabolic inhibitors but resistance to proteasome inhibitors, while HMGA1 knockout suppressed tumor growth and enhanced anti–PD-1 efficacy. By integrating bulk modeling with spatial validation, this study establishes a GC–mitophagy–based classification and highlights HMGA1 as a promising biomarker for prognostic stratification and personalized immunotherapy in LUAD.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Glucocorticoid and mitophagy signaling–based molecular subtyping reveals HMGA1 as a prognostic and immunotherapy biomarker in lung adenocarcinoma

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年6月20日

查看全文
  • Junjie Yu,
  • Yantao Jiang,
  • Qingqing Xiong,
  • Yongmeng Wu,
  • Wei Luo,
  • Luyao Tong,
  • Yi Lu,
  • Lianmin Zhang,
  • Peng Chen,
  • Tingting Qin

摘要

Lung adenocarcinoma (LUAD) shows marked heterogeneity, limiting the effectiveness of traditional classifications. We integrated bulk transcriptomic data from TCGA and multicenter cohorts with spatial transcriptomics for in situ validation. Analysis of glucocorticoid (GC) and mitophagy pathways identified 127 core genes, enabling a novel molecular subtyping and survival risk model that predicted prognosis and correlated with immune infiltration. High mobility group AT-hook 1 (HMGA1) emerged as a key regulator of tumor metabolism, immune evasion, and therapy resistance. Spatial transcriptomics with RCTD-based deconvolution showed a tumor-enriched and heterogeneous HMGA1 expression pattern and a positive spatial association with epithelial cell proportion in tumor sections. Single-cell RNA-seq analysis further resolved HMGA1 enrichment to tumor epithelial cells, and CIBERSORTx projection linked the HMGA1-high tumor epithelial cell state to poor prognosis and increased proliferation. Functional assays showed that high HMGA1 expression conferred sensitivity to metabolic inhibitors but resistance to proteasome inhibitors, while HMGA1 knockout suppressed tumor growth and enhanced anti–PD-1 efficacy. By integrating bulk modeling with spatial validation, this study establishes a GC–mitophagy–based classification and highlights HMGA1 as a promising biomarker for prognostic stratification and personalized immunotherapy in LUAD.