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Background <p>Endometrial cancer (EC) is a prevalent gynecological malignancy with prognoses varying significantly across molecular subtypes. PANoptosis, a recently identified mode of cell death, has been implicated in tumor progression, yet its role in EC remains understudied. This study aims to explore the prognostic and immunomodulatory functions of PANoptosis-related genes (PANRGs) in EC and their associations with molecular subtypes, thereby facilitating targeted and precision therapy.</p> Methods <p>EC expression profiles and clinical data were acquired from uterine corpus endometrial carcinoma (UCEC) project of TCGA database. PANRGs were identified via Gene Set Variation Analysis (GSVA) and Weighted Gene Co-expression Network Analysis (WGCNA). Prognostic feature genes were screened using LASSO, Random Forest, GBM, and XGBOOST algorithms to construct a risk signature. Mutation profiles, immune characteristics, and molecular subtype associations across risk groups were analyzed, with functional emphasis on key signature genes. CCK-8 and Transwell assays were used to confirm the biological effects of key markers on EC cells, while Western blotting assays were employed to illustrate the underlying mechanisms.</p> Results <p>GSVA and WGCNA identified 40 differentially expressed PANRGs. Machine learning algorithms further filtered out four prognostic genes (FOXP3, SIGLEC1, RASSF4, BATF). The low-risk group exhibited significantly better overall survival than the high-risk group, with distinct mutation and immune regulation profiles. Consensus clustering analysis revealed associations between these differences and EC molecular subtypes. SIGLEC1, with its poor prognostic correlation, promoted the growth of EC cells as well as the invasion and migration ability, and knocking down SIGLEC1 led to apoptosis, pyroptosis and necroptosis.</p> Conclusion <p>PANRGs-based prognostic signatures distinguished EC clinical outcomes and correlated with immune regulation and mutation profiles. SIGLEC1 exerted an oncogenic effect by resisting panoptosis and served as a prognostic and immune marker.</p>

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Establishiment of PANoptosis-related prognostic signature and experimental identification of SIGLEC1 as an oncogenic biomarker in endometrial cancer

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年4月17日

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  • Zhenying Zhu,
  • Jie Yuan,
  • Ning Liu,
  • Yanyan Gao,
  • Xiaochao Fu,
  • Lihui Yan

摘要

Background

Endometrial cancer (EC) is a prevalent gynecological malignancy with prognoses varying significantly across molecular subtypes. PANoptosis, a recently identified mode of cell death, has been implicated in tumor progression, yet its role in EC remains understudied. This study aims to explore the prognostic and immunomodulatory functions of PANoptosis-related genes (PANRGs) in EC and their associations with molecular subtypes, thereby facilitating targeted and precision therapy.

Methods

EC expression profiles and clinical data were acquired from uterine corpus endometrial carcinoma (UCEC) project of TCGA database. PANRGs were identified via Gene Set Variation Analysis (GSVA) and Weighted Gene Co-expression Network Analysis (WGCNA). Prognostic feature genes were screened using LASSO, Random Forest, GBM, and XGBOOST algorithms to construct a risk signature. Mutation profiles, immune characteristics, and molecular subtype associations across risk groups were analyzed, with functional emphasis on key signature genes. CCK-8 and Transwell assays were used to confirm the biological effects of key markers on EC cells, while Western blotting assays were employed to illustrate the underlying mechanisms.

Results

GSVA and WGCNA identified 40 differentially expressed PANRGs. Machine learning algorithms further filtered out four prognostic genes (FOXP3, SIGLEC1, RASSF4, BATF). The low-risk group exhibited significantly better overall survival than the high-risk group, with distinct mutation and immune regulation profiles. Consensus clustering analysis revealed associations between these differences and EC molecular subtypes. SIGLEC1, with its poor prognostic correlation, promoted the growth of EC cells as well as the invasion and migration ability, and knocking down SIGLEC1 led to apoptosis, pyroptosis and necroptosis.

Conclusion

PANRGs-based prognostic signatures distinguished EC clinical outcomes and correlated with immune regulation and mutation profiles. SIGLEC1 exerted an oncogenic effect by resisting panoptosis and served as a prognostic and immune marker.