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

Area of Science:

• Oncology
• Molecular Biology
• Genomics

Background:

• Esophageal squamous cell carcinoma (ESCC) is a deadly cancer requiring better therapeutic strategies.
• Understanding ESCC molecular landscape and heterogeneity is crucial for developing effective treatments.

Purpose of the Study:

• To perform multi-dimensional molecular characterization of ESCC.
• To develop a prognostic subtype classifier (PrSC) for ESCC patients.
• To explore the tumor microenvironment (TME) heterogeneity and identify potential therapeutic targets.

Main Methods:

• Integrated multiple ESCC expression datasets and combined ATAC-seq and RNA-seq for chromatin accessibility analysis.
• Constructed a prognosis-related subtype classifier (PrSC) and assessed its association with TME and immunotherapy.
• Validated key gene signatures in clinical samples and screened for subtype-specific therapeutic agents.

Main Results:

• Identified common differentially expressed genes (cDEGs) and key genes (HEATR1, TIMELESS, DTL, GINS1, RUVBL1, ECT2) crucial for ESCC cell survival.
• Demonstrated that PrSC is a robust tool for prognosis assessment and reflects TME heterogeneity.
• Discovered TNS1^high fibroblasts linked to immune exclusion and identified TG-101348 and Vinorelbine as potential subtype-specific agents.

Conclusions:

• Established a multi-dimensional characterization of ESCC and a robust prognostic scoring tool.
• Highlighted the role of TNS1^high fibroblasts in the ESCC tumor microenvironment.
• Identified potential therapeutic agents and demonstrated PrSC's value in predicting immunotherapy response.