Multi‐omics analyses reveal spatial heterogeneity in primary and metastatic oesophageal squamous cell carcinoma
Background: Biopsies obtained from primary oesophageal squamous cell carcinoma (ESCC) guide diagnosis and treatment. However, spatial intra‐tumoral heterogeneity (ITH) influences biopsy‐derived information and patient responsiveness to therapy. Here, we aimed to elucidate the spatial ITH of ESCC and matched lymph node metastasis (LNmet). Methods: Primary tumour superficial (PTsup), deep (PTdeep) and LNmet subregions of patients with locally advanced resectable ESCC were evaluated using whole‐exome sequencing (WES), whole‐transcriptome sequencing and spatially resolved digital spatial profiling (DSP). To validate the findings, immunohistochemistry was conducted and a single‐cell transcriptomic dataset was analysed. Results: WES revealed 15.72%, 5.02% and 32.00% unique mutations in PTsup, PTdeep and LNmet, respectively. Copy number alterations and phylogenetic trees showed spatial ITH among subregions both within and among patients. Driver mutations had a mixed intra‐tumoral clonal status among subregions. Transcriptome data showed distinct differentially expressed genes among subregions. LNmet exhibited elevated expression of immunomodulatory genes and enriched immune cells, particularly when compared with PTsup (all P < .05). DSP revealed orthogonal support of bulk transcriptome results, with differences in protein and immune cell abundance between subregions in a spatial context. The integrative analysis of multi‐omics data revealed complex heterogeneity in mRNA/protein levels and immune cell abundance within each subregion. Conclusions: This study comprehensively characterised spatial ITH in ESCC, and the findings highlight the clinical significance of unbiased molecular classification based on multi‐omics data and their potential to improve the understanding and management of ESCC. The current practices for tissue sampling are insufficient for guiding precision medicine for ESCC, and routine profiling of PTdeep and/or LNmet should be systematically performed to obtain a more comprehensive understanding of ESCC and better inform treatment decisions.
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基因水平:PCR Array、RT-PCR、PCR、单细胞测序
蛋白水平:MSD、Luminex、CBA、Elispot、Antibody Array、ELISA、Sengenics
细胞水平:细胞染色、细胞分选、细胞培养、细胞功能
组织水平:空间多组学、多重荧光免疫组化、免疫组化、免疫荧光
数据分析:流式数据分析、组化数据分析、多因子数据分析
基因水平:PCR Array、RT-PCR、PCR、单细胞测序
蛋白水平:MSD、Luminex、CBA、Elispot、Antibody Array、ELISA、Sengenics
细胞水平:细胞染色、细胞分选、细胞培养、细胞功能
组织水平:空间多组学、多重荧光免疫组化、免疫组化、免疫荧光
数据分析:流式数据分析、组化数据分析、多因子数据分析
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