Transcriptomics based multi-dimensional characterization and drug screen in esophageal squamous cell carcinoma

Abstract

Background Esophageal squamous cell carcinoma (ESCC) remains one of the deadly cancer types. Comprehensively dissecting the molecular characterization and the heterogeneity of ESCC paves the way for developing more promising therapeutics. Methods Expression profiles of multiple ESCC datasets were integrated. ATAC-seq and RNA-seq were combined to reveal the chromatin accessibility features. A prognosis-related subtype classifier (PrSC) was constructed, and its association with the tumor microenvironment (TME) and immunotherapy was assessed. The key gene signature was validated in clinical samples. Based on the TME heterogeneity of ESCC patients, potential subtype-specific therapeutic agents were screened. Findings The common differentially expressed genes (cDEGs) in ESCC were identified. Up-regulated genes (HEATR1, TIMELESS, DTL, GINS1, RUVBL1, and ECT2) were found highly important in ESCC cell survival. The expression alterations of PRIM2, HPGD, NELL2, and TFAP2B were associated with chromatin accessibility changes. PrSC was a robust scoring tool that was not only associated with the prognosis of ESCC patients, but also could reflect the TME heterogeneity. TNS1 high fibroblasts were associated with immune exclusion. TG-101348 and Vinorelbine were identified as potential subtype-specific therapeutic agents. Besides, the application of PrSC into two immunotherapy cohorts indicated its potential value in assessing treatment response to immunotherapy. Interpretation Our study depicted the multi-dimensional characterization of ESCC, established a robust scoring tool for the prognosis assessment, highlighted the role of TNS1 high fibroblasts in TME, and identified potential drugs for clinical use. Funding A full list of funding bodies that contributed to this study can be found in the Acknowledgements section.

Artificial Intelligence-Assisted Transcriptomic Analysis to Advance Cancer Immunotherapy

“…Specifically, lymphocyte activation gene-3 (LAG3) may be a potential target for immunotherapy [ 65 ]. Furthermore, by combining the Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq) data with RNA-seq data of EC patients, Li et al uncovered the potential transcriptional regulation characterization and constructed a LASSO-based prognosis-related subtype classifier, which is associated with TME heterogeneity and immunotherapy responses [ 66 ].…”

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

“…Several recent studies have explored the gene expression profile of ESCC in view of identifying some genes whose expression is prognostic. Thus, Li et al explored the expression profiles of multiple ESCC datasets and, through the integration of these profiles, identified six upregulated genes (HEATR1, TIMELESS, DTL, RUVBL1 and ECT2), which were found to be highly important in ESCC survival; the alterations in the expression of four genes (PRIM2, HGPD, NELL2 and RFAP28) were associated with changes in chromatin accessibility [50]. The authors next explored intertumor heterogeneity and, using a regression and prognosis-related classifier, identified two tumor subtypes, S1 and S2, distinguished according to their outcomes and gene expression profiles.…”

Computational exploration of cellular communication in skin from emerging single-cell and spatial transcriptomic data

“…Application of CellChat to scRNA-seq data of esophageal squamous cell carcinoma (ESCC) highlighted the role of TNS1high fibroblasts in TME, in particular the interaction with cytotoxic T cells. Of note, TNS1high fibroblasts was associated with immune exclusion phenotype and poor prognosis of ESCC patients [ 61 ]. CellPhoneDB was applied to systematically study interactions within the TME in murine melanoma and identified stromal-immune interactions, such as C3–C3AR1, CXCL12–CXCR4 and CSF1–CSFR1 with macrophages as primary target [ 62 ].…”