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Poster viewing and lunch

34P - Investigating morphological heterogeneity in luminal breast cancer integrating artificial intelligence and spatial transcriptomics

Date

12 May 2023

Session

Poster viewing and lunch

Presenters

Nicola Occelli

Citation

Annals of Oncology (2023) 8 (1suppl_4): 101218-101218. 10.1016/esmoop/esmoop101218

Authors

N. Occelli1, M. Serra1, M. Rediti1, L. Collet1, F. Lifrange2, X. Wang1, D. Vincent1, G. Rouas1, L. Craciun1, D. Larsimont1, D. Venet1, M. Vikkula3, F.P. Duhoux4, L. Buisseret1, F. Rothé1, C. Sotiriou1

Author affiliations

  • 1 Institute Jules Bordet, Brussels/BE
  • 2 CHU de Liège - Sart Tilman Site, Liège/BE
  • 3 De Duve Institute UCLouvain, Woluwe-Saint-Lambert/BE
  • 4 Cliniques Universitaires Saint-Luc (UCLouvain Saint-Luc), Brussels/BE

Resources

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Abstract 34P

Background

Hormone receptor-positive (HR+), HER2-negative (HER2-) breast cancer (BC) accounts for around 65% of all BCs. Invasive lobular and ductal carcinoma (ILC, IDC) show distinct histology and clinical presentation. In this study, our goal is to exploit morphological differences between IDC and ILC by combining artificial intelligence and spatial transcriptomics (ST) to characterize intra-tumor heterogeneity.

Methods

We analyzed 131 H&E whole slide images (WSIs) from frozen HR+, HER2- BC samples, of which 43 were ILC and 88 were IDC. Images were morphologically annotated using QuPath. We performed ST (Visium 10X Genomics®) on the ILC samples. A neural network (NN) was trained to perform histology classification from WSIs and detect the most relevant tissue regions for such classification. Gene expression data from ST were used to characterize these regions.

Results

The NN achieved 0.95 ROC AUC in predicting histology (ILC vs IDC). Interestingly, in 36/43 ILC samples, adipose tissue had the highest relative importance in assessing the histological subtype, suggesting crucial morphological differences in adipocytes between ILC and IDC. Of note, we observed intra-sample heterogeneity in the importance levels of tumor areas, with just 13% of the overall tumor cells showing high importance in the classification. We mapped the most relevant tissue regions for histology classification to the ST spots (for ILC). Pathway enrichment analysis on differentially expressed genes (DEG) relative to these spots revealed enrichment in metabolic and adipogenesis-related pathways (padj < 0.05). When limiting the analysis on spots composed by more than 30% of tumor cells, DEG revealed enrichment in metabolic-related pathways (padj < 0.05).

Conclusions

Adipose tissue morphology was revealed to be a key feature in distinguishing histological subtypes in HR+, HER2- BC. Importantly, tumor cells with increased metabolism showed to be crucial in the histological classification, suggesting differences in metabolism between IDC and ILC. Further validation is needed.

Legal entity responsible for the study

The authors.

Funding

FNRS, Fondation Jules Bordet, Breast Cancer Research Foundation, Fondation contre le Cancer.

Disclosure

F.P. Duhoux: Financial Interests, Institutional, Advisory Board: Roche, Pfizer, AstraZeneca, Lilly, Novartis, Amgen, Daiichi Sankyo, Pierre Fabre, Gilead, Seagen, MSD; Financial Interests, Institutional, Invited Speaker: Novartis, Pfizer, MSD, Roche, MSD, Boehringer Ingelheim, Pfizer, Novartis, Lilly, AbbVie, Seagen, Gilead, AstraZeneca, Menarini, Immutep; Financial Interests, Institutional, Expert Testimony: Seagen, Novartis, MSD. C. Sotiriou: Financial Interests, Institutional, Advisory Board: Astellas, Vertex, Seattle Genetics, Amgen, INC, Merck & Co; Financial Interests, Personal, Advisory Board: Cepheid, Puma; Financial Interests, Personal, Invited Speaker: Eisai, Prime oncology, Teva; Financial Interests, Institutional, Other, Travel: Roche; Financial Interests, Institutional, Other, Internal speaker: Genentech; Financial Interests, Personal, Other, Regional speaker: Pfizer; Financial Interests, Institutional, Invited Speaker: Exact Sciences. All other authors have declared no conflicts of interest.

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