P183. Multi-omics analyses reveal spatial heterogeneity in primary and metastatic oesophageal squamous cell carcinoma
Presented During: Thoracic Poster Session II
First affliated Hospital of Soochow University
Suzhou, Jiangsu
China - Contact Me
Yu Feng, M.D., Ph.D
Dr. Yu Feng is an Associate Chief Physician at the Department of Thoracic Surgery in the First Affiliated Hospital of Soochow University. Dr. Feng has published more than 20 publications in peer-reviewed journals.
Sunday, May 4, 2025: 9:00 AM - 4:00 PM
Seattle Convention Center | Summit
Room: Poster Area, Exhibit Hall
Description
Objective: 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 LNmetsubregions 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, PTdeepand 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. LNmetexhibited 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 PTdeepand/or LNmetshould be systematically performed to obtain a more comprehensive understanding of ESCC and better inform treatment decisions.
Authors
Yu Feng (1), haitao huang (2), Dong Jiang (3), Jun Zhao (3)
Institutions
(1) First affliated Hospital of Soochow University, Suzhou, Jiangsu, (2) N/A, nantong, China, (3) the First Affiliated Hospital of Soochow University, Suzhou, NA
Methods: Primary tumour superficial (PTsup), deep (PTdeep) and LNmetsubregions 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, PTdeepand 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. LNmetexhibited 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 PTdeepand/or LNmetshould be systematically performed to obtain a more comprehensive understanding of ESCC and better inform treatment decisions.
Authors
Yu Feng (1), haitao huang (2), Dong Jiang (3), Jun Zhao (3)
Institutions
(1) First affliated Hospital of Soochow University, Suzhou, Jiangsu, (2) N/A, nantong, China, (3) the First Affiliated Hospital of Soochow University, Suzhou, NA