Integrated cohort of esophageal squamous cell cancer reveals genomic features underlying clinical characteristics

Abstract

Esophageal squamous cell cancer (ESCC) is the major pathologic type of esophageal cancer in Asian population. To systematically evaluate the mutational features underlying clinical characteristics, we establish the integrated dataset of ESCC-META that consists of 1930 ESCC genomes from 33 datasets. The data process pipelines lead to well homogeneity of this integrated cohort for further analysis. We identified 11 mutational signatures in ESCC, some of which are related to clinical features, and firstly detect the significant mutated hotspots in TGFBR2 and IRF2BPL. We screen the survival related mutational features and found some genes had different prognostic impacts between early and late stage, such as PIK3CA and NFE2L2. Based on the results, an applicable approach of mutational score is proposed and validated to predict prognosis in ESCC. As an open-sourced, quality-controlled and updating mutational landscape, the ESCC-META dataset could facilitate further genomic and translational study in this field.

The Molecular Characterization of Genetic Abnormalities in Esophageal Squamous Cell Carcinoma May Foster the Development of Targeted Therapies

“…Two recent studies reported an integrative genomic analysis of a large cohort of published ESCC patients [31,32]. Zou et al reported the integrated reanalysis of the mutation data of WGS or WES from a total of 1145 tumor samples present in 7 large ESCC cohorts [31]. In 1145 ESCC patients, an average of 4.3 mutations/megabase was observed.…”

“…Using a cutoff of eight mutations/megabase to distinguish low tumor mutation burden (TMB) from high, it was shown that patients with high TMB have a lower OS compared with those with low TMB [31]. In the 7 cohorts of ESCC patients included in this analysis, 47 mutated genes were considered driver genes, but only 7 genes (TP53, NOTCH1, CDKN2A, ZNF50, NFE2L2, PIK3CA and RB1) were considered driver genes in the majority of studies; some genes, such as FAT1, FAT2, PTEN, EP300, FBXW7, APS31, MUC16 and RP&15, were considered driver genes only in a minority of studies [31]. Only the mutations of a few genes were correlated to clinical parameters, such as ZNF50 mutations related to lymph node metastasis [31].…”

Large-scale genomic analyses reveal alterations and mechanisms underlying clonal evolution and immune evasion in esophageal cancer

“…This requires not only sequencing a large number of patients to overcome its strong inter-tumoral heterogeneity, but also characterizing in detail the clonal makeup and evolution to decipher ESCC intra-tumoral heterogeneity. New research 4 , 5 published recently in Nature Communications have specifically taken on these two challenges, by performing genomic and epigenomic analyses with significant breadth and depth, and shed novel insights into ESCC tumor heterogeneity with translational implications.…”

“…To address the inter-tumoral heterogeneity, Li et al 5 curated and integrated ESCC sequencing data from 1930 patients across 33 studies, representing one of the largest compendia of paired tumor-normal sequences. To ensure data quality and minimize batch effects, the authors paid extra attention and made efforts during quality control, data processing, homogenization and verification.…”

“…In summary, by performing large-scale genomic investigation, combined with in-depth computational and statistical analyses, these new studies 4 , 5 have uncovered novel mutational features exhibiting robust associations with key clinical parameters, revealed molecular mechanisms driving clonal diversification, and characterized the interplay between immune selection pressure and tumor evolution. Moving forward, new single-cell genomic and epigenomic technologies are revolutionizing the research on tumor heterogeneity, and recent single-cell RNA-seq studies 11 – 13 have begun to highlight the extensive diversity of gene expression programs among ESCC cancer cells.…”