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<p>Emerging evidence suggests the importance of basement membrane components in cancer metastasis; however, their specific roles in esophageal carcinoma remain underexplored. To investigate this, we analyzed 152 esophageal cancer and 11 normal esophageal tissue samples, identifying basement membrane-related prognostic signatures through differential gene expression profiling and Least Absolute Shrinkage and Selection Operator regression. A six-gene panel (LAMC2, GPC2, AGRN, ITGA3, LAMA3, and LOXL4) demonstrated robust predictive capacity, which we subsequently integrated with clinical features via nomogram modeling to predict overall survival. Our computational analyses revealed distinct tumor microenvironment immune cell profiles and chemotherapeutic drug sensitivities across risk strata. We performed an immunohistochemical assay to confirm increased tumor tissue expression, thereby reinforcing the clinical relevance of these biomarkers. Experimental validation using KYSE-150 esophageal squamous carcinoma cells demonstrated that while LAMC2 knockdown attenuated cellular migration, AGRN, GPC2, ITGA3, LAMA3, and LOXL4 suppression enhanced migratory capacity. Proliferation assays further revealed increased growth rates upon GPC2, ITGA3, and LAMA3 expression inhibition. Our results established a basement membrane-derived risk model for esophageal carcinoma and revealed the roles of the model genes in tumor progression regulation. This model advances prognostic stratification and provides insights into therapeutic targets.</p>

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A model of basement membrane-related regulators for prediction of prognoses in esophageal cancer and verification in vitro

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年4月15日

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  • Lang Xu,
  • Bingna Wang,
  • Chen Wang,
  • Nan Mao,
  • Yating Huang,
  • Xihua Fu,
  • Tao Feng,
  • Qiming He,
  • Yang Zhang,
  • Guoxing You,
  • Xiaojun Ma,
  • Xinsheng Peng,
  • Jianfen Su

摘要

Emerging evidence suggests the importance of basement membrane components in cancer metastasis; however, their specific roles in esophageal carcinoma remain underexplored. To investigate this, we analyzed 152 esophageal cancer and 11 normal esophageal tissue samples, identifying basement membrane-related prognostic signatures through differential gene expression profiling and Least Absolute Shrinkage and Selection Operator regression. A six-gene panel (LAMC2, GPC2, AGRN, ITGA3, LAMA3, and LOXL4) demonstrated robust predictive capacity, which we subsequently integrated with clinical features via nomogram modeling to predict overall survival. Our computational analyses revealed distinct tumor microenvironment immune cell profiles and chemotherapeutic drug sensitivities across risk strata. We performed an immunohistochemical assay to confirm increased tumor tissue expression, thereby reinforcing the clinical relevance of these biomarkers. Experimental validation using KYSE-150 esophageal squamous carcinoma cells demonstrated that while LAMC2 knockdown attenuated cellular migration, AGRN, GPC2, ITGA3, LAMA3, and LOXL4 suppression enhanced migratory capacity. Proliferation assays further revealed increased growth rates upon GPC2, ITGA3, and LAMA3 expression inhibition. Our results established a basement membrane-derived risk model for esophageal carcinoma and revealed the roles of the model genes in tumor progression regulation. This model advances prognostic stratification and provides insights into therapeutic targets.