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Despite recent progress in identifying aberrant genetic and epigenetic alterations in esophageal squamous cell carcinoma (ESCC), the mechanism of ESCC initiation remain unknown. Using genetically engineered esophageal organoids (EOs), we identified the key genetic determinants that drive ESCC tumorigenesis. A single-cell transcriptomic analysis uncovered that Trp53, Cdkn2a, and Notch1 (PCN) triple knockout (KO) induces neoplastic features of ESCC by generating distinct cell lineage trajectories with multiple root cells and high cell plasticity. Although Trp53 and Notch1 (PN) double KO was sufficient to induce esophageal neoplasia and cellular heterogeneity, additional inactivation of Cdkn2a was indispensable for immune landscape remodeling for in vivo tumorigenesis. PCN KO generated immunosuppressive niche enriched with exhausted T cells and M2 macrophages via the CCL2-CCR2 axis in an autochthonous ESCC mouse model. Moreover, genetic or pharmacological blockade of the CCL2-CCR2 axis suppressed ESCC tumorigenesis. Comparative single-cell transcriptomic analyses classified ESCC patient tumors into three subgroups and identified a specific subset recapitulating PCN-type ESCC signatures, including the high expression of CCL2 and CD274/PD-L1. Our study unveils that loss of TP53, CDKN2A, and NOTCH1 induces esophageal neoplasia and immune evasion for ESCC initiation and proposes the CCL2 blockade as a viable approach to target a subset of ESCC.

Despite the promising outcomes of immune checkpoint blockade (ICB), resistance to ICB presents a new challenge. Therefore, selecting patients for specific ICB applications is crucial for maximizing therapeutic efficacy. Herein we curated 69 human esophageal squamous cell cancer (ESCC) patients' tumor microenvironment (TME) single-cell transcriptomic datasets to subtype ESCC. Integrative analyses of the cellular network transcriptional signatures of T cells, myeloid cells, and fibroblasts define distinct ESCC subtypes characterized by T cell exhaustion, Interferon (IFN) a/b signaling, TIGIT enrichment, and specific marker genes. Furthermore, this approach classifies ESCC patients into ICB responders and non-responders, as validated by liquid biopsy single-cell transcriptomics. Our study stratifies ESCC patients based on TME transcriptional network, providing novel insights into tumor niche remodeling and predicting ICB responses in ESCC patients.