Multi-Region Genomic Landscape Analysis for the Preoperative Prediction of Lymph Node Metastasis in Esophageal Carcinoma

Objective: Esophageal cancer is an aggressive malignant tumor, with 90 percent of the patients prone to recurrence and metastasis. Although recent studies have identified some potential biomarkers, these biomarkers' clinical or pathological significance is still unclear. Therefore, it is urgent to further identify and study novel molecular changes occurring in esophageal cancer. It has positive clinical significance to identify a tumor-specific mutation in patients after surgery for an effective intervention to improve the prognosis of patients.Methods: In this study, we performed whole-exome sequencing (WES) on 33 tissue samples from six esophageal cancer patients with lymph node metastasis, compared the differences in the genomic and evolutionary maps in different tissues, and then performed pathway enrichment analysis on non-synonymous mutation genes. Finally, we sorted out the somatic mutation data of all patients to analyze the subclonality of each tumor.Results: There were significant differences in somatic mutations between the metastatic lymph nodes and primary lesions in the six patients. Clustering results of pathway enrichment analysis indicated that the metastatic lymph nodes had certain commonalities. Tumors of the cloned exploration results illustrated that five patients showed substantial heterogeneity.Conclusion: WES technology can be used to explore the differences in regional evolutionary maps, heterogeneity, and detect patients' tumor-specific mutations. In addition, an in-depth understanding of the ontogeny and phylogeny of tumor heterogeneity can help to further find new molecular changes in esophageal cancer, which can improve the prognosis of EC patients and provide a valuable reference for their diagnosis.

Automated summary

In this study, whole-exome sequencing was performed on tissue samples from six esophageal cancer patients with lymph node metastasis. Significant differences in somatic mutations between metastatic lymph nodes and primary lesions were identified, and pathway enrichment analysis and subclonality analysis revealed commonalities and heterogeneity among the patients, highlighting the potential of identifying tumor-specific mutations for effective intervention and improving prognosis.