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The metabolic genomic atlas reveals potential drivers and clinically relevant insights into the etiology of esophageal squamous cell carcinoma
Background: Esophageal squamous cell carcinoma (ESCC) is one of the most common cancers globally, with a poor prognosis and ambiguous therapy target. As a hallmark of cancer, metabolism reprogramming plays a critical role in the development of ESCC; however, the genomic alterations underlying this r...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Ivyspring International Publisher
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9475459/ https://www.ncbi.nlm.nih.gov/pubmed/36168622 http://dx.doi.org/10.7150/thno.70814 |
Sumario: | Background: Esophageal squamous cell carcinoma (ESCC) is one of the most common cancers globally, with a poor prognosis and ambiguous therapy target. As a hallmark of cancer, metabolism reprogramming plays a critical role in the development of ESCC; however, the genomic alterations underlying this reconfiguration are still largely unknown. Methods: We have comprehensively studied the metabolic genomic variations in an integrated ESCC cohort of 490 patients and characterized the somatic alterations associated with various metabolic pathways. Results: The somatic mutations and copy number alterations (CNAs) occurred heterogeneously in all patients. Using CNA-based clustering, we stratified patients into three clusters and Cluster3 with more deletions marked for worse prognosis. Our findings revealed detailed genetic alterations in components of metabolic pathways and highlighted the role of metal ion channel transporters and non-neuronal/neuronal synapse systems in the development of ESCC. We found a subset of potential metabolic drivers and functionally validated RYR2, MGST3, and CYP8B1 involved in the ESCC-associated malignancy. Another key finding was that we identified 27 metabolic genes with genomic alterations that could serve as independent prognostic factors and figured out two genetic panels that could stratify patients into distinct prognostic groups. Conclusion: Collectively, our study provided a deep insight into the metabolic landscape in ESCC, extending our understanding of the metabolic reconfiguration underlying the genomic basis of ESCC. Furthermore, our findings revealed potential prognostic factors of ESCC, which are expected to contribute to the accurate determination of the prognosis in the clinic. |
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