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<p>Recent studies have highlighted the critical role of SMARCAL1 in cancer immune evasion, suggesting its potential as a target for immunotherapy. However, its prognostic and predictive value across diverse cancers remains unclear. In this study, we investigated the significance of SMARCAL1 as a pan-cancer biomarker through a multi-database approach. Analysis of TCGA and GTEx data revealed that elevated SMARCAL1 expression in most cancer types correlates with poor clinical outcomes. Protein expression and interaction networks were assessed using the Human Protein Atlas, while genetic alterations were examined via cBioPortal. Immune infiltration analysis using TIMER2.0 demonstrated a strong positive association between SMARCAL1 and immunosuppressive cell populations, particularly Tregs and M2 macrophages. The TIDE database was employed to predict immunotherapy response, whereas drug sensitivity and chemotherapeutic efficacy were evaluated using ROC Plotter and CellMiner, respectively. We confirmed SMARCAL1 overexpression at both mRNA and protein levels in NSCLC. GEO database analysis further suggested that high SMARCAL1 expression may dysregulate key pathways, including DNA replication, mismatch repair, and proteasome function. Integrating bioinformatics, cellular experiments, and clinical samples, this study provides evidence supporting SMARCAL1 as a potential predictive biomarker and therapeutic target in cancer immunotherapy.</p>

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Identifying and validating SMARCAL1 as a prognostic and immunotherapy predictive biomarker for NSCLC

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年12月29日

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  • Zeyan Pan,
  • Zhenli Hu,
  • Yunshuo Zhang,
  • Yang Jiao,
  • Rong Chai,
  • Wei Zhang,
  • Jingxi Zhang,
  • Yuchao Dong

摘要

Recent studies have highlighted the critical role of SMARCAL1 in cancer immune evasion, suggesting its potential as a target for immunotherapy. However, its prognostic and predictive value across diverse cancers remains unclear. In this study, we investigated the significance of SMARCAL1 as a pan-cancer biomarker through a multi-database approach. Analysis of TCGA and GTEx data revealed that elevated SMARCAL1 expression in most cancer types correlates with poor clinical outcomes. Protein expression and interaction networks were assessed using the Human Protein Atlas, while genetic alterations were examined via cBioPortal. Immune infiltration analysis using TIMER2.0 demonstrated a strong positive association between SMARCAL1 and immunosuppressive cell populations, particularly Tregs and M2 macrophages. The TIDE database was employed to predict immunotherapy response, whereas drug sensitivity and chemotherapeutic efficacy were evaluated using ROC Plotter and CellMiner, respectively. We confirmed SMARCAL1 overexpression at both mRNA and protein levels in NSCLC. GEO database analysis further suggested that high SMARCAL1 expression may dysregulate key pathways, including DNA replication, mismatch repair, and proteasome function. Integrating bioinformatics, cellular experiments, and clinical samples, this study provides evidence supporting SMARCAL1 as a potential predictive biomarker and therapeutic target in cancer immunotherapy.