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Cell State Heterogeneity at Single Cell Level in Gastric Organoids

Authors
Takeshi Hagihara1, Kie Kyon Huang1, Raghav Sundar1,2,3,4, Tomoyuki Uchihara1, Clara Shi Ya Ng1, Su Ting Tay1, Angie Lay Keng Tan1, Jimmy Bok Yan So3,4,5, and Patrick Tan1,4,6,7

Affiliations

  1. Cancer and Stem Cell Biology Program, Duke-NUS Medical School, Singapore.
  2. Department of Haematology-Oncology, National University Cancer Institute, National University Health System, Singapore.
  3. Yong Loo Lin School of Medicine, National University of Singapore, Singapore.
  4. Singapore Gastric Cancer Consortium, Singapore.
  5. Department of Surgery, University Surgical Cluster, National University Health System, Singapore.
  6. Cancer Science Institute of Singapore, National University of Singapore, Singapore.
  7. Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore

Introduction
Gastric cancer exhibits significant heterogeneity. Patient-derived organoids (PDOs) serve as valuable tools for studying its biology, as they maintain both intra-tumoral heterogeneity and inter-patient heterogeneity. Recent years have seen a surge in single-cell analyses of PDOs. For example, single-cell RNA sequencing (scRNA-seq) studies of pancreatic cancer PDOs revealed cell state heterogeneity and plasticity of cancer cells. However, our understanding of single-cell level heterogeneity in gastric PDOs remains limited. Here, we aim to address this gap by performing scRNA-seq on gastric PDOs from our biobank.

Methods
Since October 2021, we have been establishing our own gastric PDO biobank, which comprises 38 gastric cancer PDOs from 26 patients, along with 3 intestinal metaplasia and 25 normal gastric PDOs. All PDOs underwent whole-exome-sequencing and whole-transcriptome sequencing analyses. To assess cell states within PDOs, scRNA-seq was performed on 5 PDOs.

Results
Our biobank covers all four TGCA types. Cancer organoids are categorized into two subtypes: C1, enriched in intestinal lineage and MYC signature, and C3, enriched in neuro-related lineage and Epithelial Mesenchymal Transition (EMT) signature based on GSEA. Consistent with GSEA findings, C3 organoids exhibit higher z-scores for various EMT signatures. Analyses with scHCL dataset reveal higher intestine lineage scores in C1 organoids and lower gastro-intestinal lineage scores in C3. Additionally, scRNA-seq analyses reveal heterogeneity in EMT and lineage cell states within each organoid.

Conclusion
Our gastric PDO biobank encompasses a broad spectrum of gastric cancers. Cancer PDOs are classified into the two subtypes with distinct cell states of EMT and lineage by transcriptome profiling. Moreover, even within each organoid, heterogeneity in EMT and lineage cell states is observed.