Tumor heterogeneity in Esophageal Adenocarcinoma: a genomic approach

INTRODUCTION: Esophageal adenocarcinoma (EAC) is a severe malignancy in terms of prognosis and mortality rate. Because its great genetic heterogeneity, disputes regarding classification, prevention and treatments are still unsolved. AIM: We investigated intra- and inter-EAC heterogeneity by defining EAC’s somatic mutational profile and the role of candidate microRNAs, to correlate the molecular profile of tumors to clinical outcomes and to identify biomarkers for classification. METHODS: 38 EAC cases were analyzed via high-throughput cell sorting technology combined with targeted sequencing and whole genome low-pass sequencing. Targeted sequencing of further 169 cases was performed to widen the study. miR221 and miR483-3p expression was profiled via qPCR in 112 EACs and correlation with clinical outcomes was investigated. RESULTS: 35/38 EACs carried at least one somatic mutation absent in stromal cells. TP53 was found mutated in 73.7% of cases. Selective sorting revealed tumor subclones with different mutational loads and copy number alterations, confirming the high intra-tumor heterogeneity of EAC. Mutations were in most cases at homozygous state, and we identified alterations that were missed with the whole-tumor analysis. Mutations in HNF1A gene, not previously associated with EAC, were identified in both cohorts. Higher expression of miR483-3p and miR221 was associated with poorer cancer specific survival (P=0.0293 and P=0.0059), and recurrence in the Lauren intestinal subtype (P=0.0459 and P=0.0002). Median expression levels of miRNAs were higher in patients with advanced tumor stages. The loss of SMAD4 immunoreactivity was significantly associated with poorer cancer specific survival and recurrence (P=0.0452; P=0.022 respectively). CONCLUSION: Combining selective sorting technology and next generation sequencing allowed to better define EAC inter- and intra-tumor heterogeneity. We identified HNF1A as a new mutated gene associated to EAC that could be involved in tumor progression and promising biomarkers such as SMAD4, miR221 and miR483-3p to identify patients at higher risk for more aggressive tumors.