The integrated molecular and histological analysis defines subtypes of esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC) is highly heterogeneous. Our understanding of full molecular and immune landscape of ESCC remains limited, hindering the development of personalised therapeutic strategies. To address this, we perform genomic-transcriptomic characterizations and AI-aided histopathological image analysis of 120 Chinese ESCC patients. Here we show that ESCC can be categorized into differentiated, metabolic, immunogenic and stemness subtypes based on bulk and single-cell RNA-seq, each exhibiting specific molecular and histopathological features based on an amalgamated deep-learning model. The stemness subgroup with signature genes, such as WFDC2, SFRP1, LGR6 and VWA2, has the poorest prognosis and is associated with downregulated immune activities, a high frequency of EP300 mutation/activation, functional mutation enrichment in Wnt signalling and the highest level of intratumoural heterogeneity. The immune profiling by transcriptomics and immunohistochemistry reveals ESCC cells overexpress natural killer cell markers XCL1 and CD160 as immune evasion. Strikingly, XCL1 expression also affects the sensitivity of ESCC cells to common chemotherapy drugs. This study opens avenues for ESCC treatment and provides a valuable public resource to better understand ESCC.

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Publication Details

Journal
Nature Communications
Published
2024-10-17
DOI
https://doi.org/10.1038/s41467-024-53164-x
Citations
24
Primary Topic
Esophageal Cancer Research and Treatment
Type
article
Field-Weighted Citation Impact
13.75

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article

The integrated molecular and histological analysis defines subtypes of esophageal squamous cell carcinoma

Weiwei Wang, Junkuo Li, Jinxin Miao, Emma Bailey et al.
24 citations
Nature Communications
Esophageal Cancer Research and Treatment
13.75
article

The integrated molecular and histological analysis defines subtypes of esophageal squamous cell carcinoma

Weiwei Wang, Junkuo Li, Jinxin Miao, Emma Bailey, Peinan Chen, Nicholas R. Lemoine, Zhongxian Zhang, Faraz Khan, Huisha Xu, Yongjun Guo, Chinedu A. Anene, Louisa S. Chard, Zhimin Wang, Xia Xue, Shuangshuang Lu, Jianzeng Dong, Zifang Zhang, Yaohe Wang, Guozhong Jiang, Peng Liu, Yue Chen, Pengju Wang, Jun Wang, Zhizhong Wang, Wencai Li, Lirong Zhang, Zhenguo Cheng, Yunshu Dong, Dongling Gao, Rathi Gangeswaran
article en
24 citations

Abstract

Esophageal squamous cell carcinoma (ESCC) is highly heterogeneous. Our understanding of full molecular and immune landscape of ESCC remains limited, hindering the development of personalised therapeutic strategies. To address this, we perform genomic-transcriptomic characterizations and AI-aided histopathological image analysis of 120 Chinese ESCC patients. Here we show that ESCC can be categorized into differentiated, metabolic, immunogenic and stemness subtypes based on bulk and single-cell RNA-seq, each exhibiting specific molecular and histopathological features based on an amalgamated deep-learning model. The stemness subgroup with signature genes, such as WFDC2, SFRP1, LGR6 and VWA2, has the poorest prognosis and is associated with downregulated immune activities, a high frequency of EP300 mutation/activation, functional mutation enrichment in Wnt signalling and the highest level of intratumoural heterogeneity. The immune profiling by transcriptomics and immunohistochemistry reveals ESCC cells overexpress natural killer cell markers XCL1 and CD160 as immune evasion. Strikingly, XCL1 expression also affects the sensitivity of ESCC cells to common chemotherapy drugs. This study opens avenues for ESCC treatment and provides a valuable public resource to better understand ESCC.

Nature CommunicationsVol. 15(1)
Queen Mary University of London (GB), Chinese Academy of Sciences (CN), Zhengzhou University (CN), The Fifth People's Hospital of Anyang (CN), Institute of Biophysics (CN), Beijing Anzhen Hospital (CN), Henan Cancer Hospital (CN), First Affiliated Hospital of Zhengzhou University (CN), Anyang Tumor Hospital (CN), Leeds Beckett University (GB)
Cancer Research UK, Zhengzhou University, Associazione Italiana per la Ricerca sul Cancro, Medical Research Council
No poverty
Openalex Percentile: Top 1%
Esophageal Cancer Research and Treatment
13.75
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