503P Self-supervised AI reveals novel determinants of lethality in lung adenocarcinoma

outcome cluster in every dataset is defined by signatures of high immune population, high PD-L1, and low B-cells, all of which were confirmed at the protein level by mIF.It also shows an exclusion of epithelial T-cells visible in routine H&E.Spatially resolved transcriptomics reveals overexpression of stromal extracellular matrix programs, supporting this physical exclusion of T-cells from the tumour regions.Our findings suggest a key role for B-cells in tumour virulence and checkpoint inhibitor sensitivity, and we are now studying their broader influence on the immune microenvironment. Conclusions:We propose a robust new transcriptomic based classification of LUAD which defines 6 LUAD variants, each with key clinicopathological features, and which highlights the defining role of B-cells in tumour virulence.

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Publication Details

Journal
ESMO Open
Published
2026-03-17
DOI
https://doi.org/10.1016/j.esmoop.2026.106818
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
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article

503P Self-supervised AI reveals novel determinants of lethality in lung adenocarcinoma

Lucas Farndale, Kai Rakovic, Alexandrina Pancheva, John Le Quesne et al.
ESMO Open
Radiomics and Machine Learning in Medical Imaging
article

503P Self-supervised AI reveals novel determinants of lethality in lung adenocarcinoma

Lucas Farndale, Kai Rakovic, Alexandrina Pancheva, John Le Quesne, Dennis T. Chang, Adalberto Claudio Quiros, C. Miller, K. Yuan
article en

Abstract

outcome cluster in every dataset is defined by signatures of high immune population, high PD-L1, and low B-cells, all of which were confirmed at the protein level by mIF.It also shows an exclusion of epithelial T-cells visible in routine H&E.Spatially resolved transcriptomics reveals overexpression of stromal extracellular matrix programs, supporting this physical exclusion of T-cells from the tumour regions.Our findings suggest a key role for B-cells in tumour virulence and checkpoint inhibitor sensitivity, and we are now studying their broader influence on the immune microenvironment. Conclusions:We propose a robust new transcriptomic based classification of LUAD which defines 6 LUAD variants, each with key clinicopathological features, and which highlights the defining role of B-cells in tumour virulence.

ESMO OpenVol. 11
Cancer Research UK (GB), Cancer Research UK Scotland Institute (GB), CRUK Lung Cancer Centre of Excellence (GB), University of Glasgow (GB)
Good health and well-being
Openalex Percentile: Top 19%
Radiomics and Machine Learning in Medical Imaging
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503P Self-supervised AI reveals novel determinants of lethality in lung adenocarcinoma — Lucas Farndale, Kai Rakovic, et al. · ESMO Open (2026) | TGRS Research Map | TGRS