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Objective <p>The objective of this study is to explore the expression patterns of angiogenesis-related genes in papillary thyroid cancer (PTC) to enhance understanding of the molecular mechanisms underlying angiogenesis in this malignancy. The findings provide valuable insights into the development of therapeutic strategies.</p> Methods <p>Angiogenesis related genes in tumor and adjacent tissues of PCT were analyzed in public database. Immune and cluster analysis were performed on differentially expressed genes, machine learning to obtain key markers, and diagnostic model has been established; Comparative analysis was conducted in tumor and adjacent tissues in PCT public database, combined with angiogenesis related pathways, to identify key cell subgroups and perform transcription factor analysis in tumor and adjacent tissues; The key markers were validated by qPCR.</p> Results <p>41 genes related to angiogenesis in tumors and adjacent tissues were obtained, including 8 differentially expressed genes (EMCN, PML, CANX, CDH13, SPHK1, IL18, VEGFA, and RHOB). Machine learning modeling was performed on the 41 angiogenesis related genes to obtain 6 key markers (EGF, CDH13, SPHK1, CANX, PML, and EMCN). Five genes with significant meaning (CDH13, SPHK1, CANX, PML, and EMCN) were identified and validated using qPCR on the tissues of our cohort, resulting in three genes with consistent expression (CDH13, SPHK1, EMCN).</p> Conclusion <p>The biological process of angiogenesis plays an important role in the occurrence and development of PCT. CDH13, SPHK1, and EMCN may play an important roles.</p>

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Comprehensive evaluation of angiogenesis-associated genes in papillary thyroid cancer using bulk RNA and single-cell sequencing data

  • 期刊论文

  • 发表日期：

    2026年7月19日

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  • Jun Zhao,
  • Ya-Xin Qin,
  • Min Zhao,
  • Hui Niu,
  • Xiao-Qi Liu

摘要

Objective

The objective of this study is to explore the expression patterns of angiogenesis-related genes in papillary thyroid cancer (PTC) to enhance understanding of the molecular mechanisms underlying angiogenesis in this malignancy. The findings provide valuable insights into the development of therapeutic strategies.

Methods

Angiogenesis related genes in tumor and adjacent tissues of PCT were analyzed in public database. Immune and cluster analysis were performed on differentially expressed genes, machine learning to obtain key markers, and diagnostic model has been established; Comparative analysis was conducted in tumor and adjacent tissues in PCT public database, combined with angiogenesis related pathways, to identify key cell subgroups and perform transcription factor analysis in tumor and adjacent tissues; The key markers were validated by qPCR.

Results

41 genes related to angiogenesis in tumors and adjacent tissues were obtained, including 8 differentially expressed genes (EMCN, PML, CANX, CDH13, SPHK1, IL18, VEGFA, and RHOB). Machine learning modeling was performed on the 41 angiogenesis related genes to obtain 6 key markers (EGF, CDH13, SPHK1, CANX, PML, and EMCN). Five genes with significant meaning (CDH13, SPHK1, CANX, PML, and EMCN) were identified and validated using qPCR on the tissues of our cohort, resulting in three genes with consistent expression (CDH13, SPHK1, EMCN).

Conclusion

The biological process of angiogenesis plays an important role in the occurrence and development of PCT. CDH13, SPHK1, and EMCN may play an important roles.