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Background <p>The APOBEC (apolipoprotein B mRNA editing enzyme, catalytic polypeptide-like) family plays a vital mutagenic role in diverse human malignancies. Nevertheless, the biological characteristics of APOBEC family members and their clinical significance in cancer have not been comprehensively explored. Our primary objective was to characterize the distribution and clinical relevance of APOBEC family members and their mutations across multiple cancer types, with a particular focus on thyroid carcinoma (THCA).</p> Methods <p>In this study, we employed an integrated, multi-faceted approach combining diverse statistical and bioinformatics methods. Data sources included whole-exome sequencing (WES), targeted next-generation sequencing (NGS), bulk RNA sequencing (RNA-seq), single-cell RNA sequencing (scRNA-seq), Western blot assays, drug sensitivity analyses, and in vivo animal models.</p> Results <p>APOBEC mutations occupy a significant position in the mutation landscape of THCA. High APOBEC mutation enrichment scores were strongly associated with poor prognosis, immune evasion, and increased risk of malignant progression in THCA patients. These mutations contribute to tumor advancement and influence cellular differentiation within the tumor microenvironment. Additionally, we developed a prognostic APOBEC mutagenesis model using machine learning, which was validated across multiple THCA cohorts. In vitro and in vivo experiments demonstrated that APOBEC2 inhibition effectively suppressed tumor proliferation, metastasis, and glycolytic activity, while simultaneously enhancing immune activation and boosting the efficacy of immune checkpoint inhibitors.</p> Conclusion <p>Our study systematically characterizes APOBEC mutations across various cancer types and underscores their promise as biomarkers for aggressive tumor phenotypes, prognostic assessment, and immunotherapy response to THCA. These findings were accomplished through multi-omics sequencing and validated through comprehensive in vitro and in vivo experiments.</p>

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Comprehensive Insights into APOBEC Mutations in Thyroid Cancer: Prognostic and Therapeutic Discoveries

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年7月26日

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  • Wei Luo,
  • Feng Liu,
  • Mengyu Li,
  • Jialong Yu,
  • Ziyun Liu,
  • Xuan Cheng,
  • Yue Huang,
  • Yu Liu,
  • Mei Tao,
  • Yuqi Wang,
  • Yiping Zou,
  • Xiaobin Shang,
  • Chao Yang,
  • Xianhui Ruan,
  • Yanchao Qin,
  • Xiangqian Zheng

摘要

Background

The APOBEC (apolipoprotein B mRNA editing enzyme, catalytic polypeptide-like) family plays a vital mutagenic role in diverse human malignancies. Nevertheless, the biological characteristics of APOBEC family members and their clinical significance in cancer have not been comprehensively explored. Our primary objective was to characterize the distribution and clinical relevance of APOBEC family members and their mutations across multiple cancer types, with a particular focus on thyroid carcinoma (THCA).

Methods

In this study, we employed an integrated, multi-faceted approach combining diverse statistical and bioinformatics methods. Data sources included whole-exome sequencing (WES), targeted next-generation sequencing (NGS), bulk RNA sequencing (RNA-seq), single-cell RNA sequencing (scRNA-seq), Western blot assays, drug sensitivity analyses, and in vivo animal models.

Results

APOBEC mutations occupy a significant position in the mutation landscape of THCA. High APOBEC mutation enrichment scores were strongly associated with poor prognosis, immune evasion, and increased risk of malignant progression in THCA patients. These mutations contribute to tumor advancement and influence cellular differentiation within the tumor microenvironment. Additionally, we developed a prognostic APOBEC mutagenesis model using machine learning, which was validated across multiple THCA cohorts. In vitro and in vivo experiments demonstrated that APOBEC2 inhibition effectively suppressed tumor proliferation, metastasis, and glycolytic activity, while simultaneously enhancing immune activation and boosting the efficacy of immune checkpoint inhibitors.

Conclusion

Our study systematically characterizes APOBEC mutations across various cancer types and underscores their promise as biomarkers for aggressive tumor phenotypes, prognostic assessment, and immunotherapy response to THCA. These findings were accomplished through multi-omics sequencing and validated through comprehensive in vitro and in vivo experiments.