Details

Autor(en) / Beteiligte

• Ko, Kyung-Pil
• Zhang, Shengzhe
• Huang, Yuanjian
• Kim, Bongjun
• Zou, Gengyi
• Jun, Sohee
• Zhang, Jie
• Zhao, Yahui
• Martin, Cecilia
• Dunbar, Karen J.
• Efe, Gizem
• Rustgi, Anil K.
• Nakagawa, Hiroshi
• Zhang, Haiyang
• Liu, Zhihua
• Park, Jae-Il

Titel

Tumor niche network-defined subtypes predict immunotherapy response of esophageal squamous cell cancer

Ist Teil von

• iScience, 2024-05, Vol.27 (5), p.109795, Article 109795

Ort / Verlag

United States: Elsevier Inc

Erscheinungsjahr

2024

Link zum Volltext

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• Despite the promising outcomes of immune checkpoint inhibitors (ICIs), resistance to ICI presents a new challenge. Therefore, selecting patients for specific ICI 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 and transcriptional signatures of T cells and myeloid cells define distinct ESCC subtypes characterized by T cell exhaustion, and interleukin (IL) and interferon (IFN) signaling. Furthermore, this approach classifies ESCC patients into ICI responders and non-responders, as validated by whole tumor transcriptomes and liquid biopsy-based single-cell transcriptomes of anti-PD-1 ICI responders and non-responders. Our study stratifies ESCC patients based on TME transcriptional network, providing novel insights into tumor niche remodeling and potentially predicting ICI responses in ESCC patients. [Display omitted] •Immunotherapy-sensitive ESCC patients prediction by scRNA-seq-based TME profiling•Integrative analyses of T cells and myeloid cells predict immunotherapy response•IL and IFN signaling pathways in T cells characterize the immunotherapy responders Immune response; Cancer systems biology; Cancer; Transcriptomics