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Original research
Organoid cultures of early-onset colorectal cancers reveal distinct and rare genetic profiles
  1. Helen H N Yan1,
  2. Hoi Cheong Siu1,
  3. Siu Lun Ho1,
  4. Sarah S K Yue1,
  5. Yang Gao1,
  6. Wai Yin Tsui1,
  7. Dessy Chan1,
  8. April S Chan1,
  9. Jason W H Wong2,3,
  10. Alice H Y Man1,
  11. Bernard C H Lee1,
  12. Annie S Y Chan1,
  13. Anthony K W Chan1,
  14. Ho Sang Hui1,
  15. Arthur K L Cheung3,4,
  16. Wai Lun Law5,
  17. Oswens S H Lo5,
  18. Siu Tsan Yuen1,6,
  19. Hans Clevers7,8,
  20. Suet Yi Leung1,3,4
  1. 1Department of Pathology, The University of Hong Kong, Queen Mary Hospital, Pokfulam, Hong Kong
  2. 2School of Biomedical Sciences, The University of Hong Kong, Pokfulam, Hong Kong
  3. 3Centre for PanorOmic Sciences, The University of Hong Kong, Pokfulam, Hong Kong
  4. 4The Jockey Club Centre for Clinical Innovation and Discovery, LKS Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong
  5. 5Department of Surgery, The University of Hong Kong, Queen Mary Hospital, Pokfulam, Hong Kong
  6. 6Department of Pathology, St. Paul's Hospital, No.2, Eastern Hospital Road, Causeway Bay, Hong Kong
  7. 7Hubrecht Institute for Developmental Biology and Stem Cell Research, University Medical Centre Utrecht, Utrecht, The Netherlands
  8. 8Princess Maxima Center for Pediatric Oncology, 3584 CT, Utrecht, The Netherlands
  1. Correspondence to Dr Suet Yi Leung, Department of Pathology, The University of Hong Kong, Pokfulam, Hong Kong; suetyi{at}hku.hk; Dr Helen H N Yan; yanhelen{at}hku.hk

Abstract

Objective Sporadic early-onset colorectal cancer (EOCRC) has bad prognosis, yet is poorly represented by cell line models. We examine the key mutational and transcriptomic alterations in an organoid biobank enriched in EOCRCs.

Design We established paired cancer (n=32) and normal organoids (n=18) from 20 patients enriched in microsatellite-stable EOCRC. Exome and transcriptome analysis was performed.

Results We observed a striking diversity of molecular phenotypes, including PTPRK-RSPO3 fusions. Transcriptionally, RSPO fusion organoids resembled normal colon organoids and were distinct from APC mutant organoids, with high BMP2 and low PTK7 expression. Single cell transcriptome analysis confirmed the similarity between RSPO fusion organoids and normal organoids, with a propensity for maturation on Wnt withdrawal, whereas the APC mutant organoids were locked in progenitor stages. CRISPR/Cas9 engineered mutation of APC in normal human colon organoids led to upregulation of PTK7 protein and suppression of BMP2, but less so with an engineered RNF43 mutation. The frequent co-occurrence of RSPO fusions with SMAD4 or BMPR1A mutation was confirmed in TCGA database searches. RNF43 mutation was found in organoid from a leukaemia survivor with a novel mutational signature; and organoids with POLE proofreading mutation displayed ultramutation. The cancer organoid genomes were stable over long culture periods, while normal human colon organoids tended to be subject to clonal dominance over time.

Conclusions These organoid models enriched in EOCRCs with linked genomic data fill a gap in existing CRC models and reveal distinct genetic profiles and novel pathway cooperativity.

  • colorectal cancer
  • colorectal cancer genes
  • colon carcinogenesis
  • gene expression
  • Early-onset colon cancer
  • organoid models
  • R-spondin fusion
  • RNF43
  • serrated neoplasia
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Footnotes

  • Contributors HHNY, SYL and HC conceived the study. HHNY and SYL directed the study. HHNY, SYL, HC and STY contributed to the project design. HCS, YG and JWHW performed the bioinformatics data analysis. HHNY, SLH, SSKY, WYT, DC, ASC, AHYM, BCHL, ASYC, AKWC, HSH, AKLC, STY and SYL collected data, performed experiments and/or analysed data. OSHL and WLL contributed clinical data, samples and critical comments on the manuscript. HC contributed protocols and/or reagents and critical comments on the manuscript. SYL and HHNY analysed and interpreted data, wrote the manuscript with assistance, comments and final approval from all authors.

  • Funding This work was majorly supported by a Health and Medical Research Fund from the Food and Health Bureau, The Government of Hong Kong Special Administrative Region (Project No. 02132886) (on organoid establishment and exome sequencing analysis) and partly by a theme-based research grant from the Research Grants Council of the Hong Kong Special Administrative Region, China (Project No. T12-710/16 R); a donation from the Hong Kong Jockey Club Charities Trust (on single cell transcriptome analysis); a Croucher Foundation Endowed Professorship to SYL and the Kadoorie Charitable Foundation.

  • Competing interests SYL and STY have received research sponsorship from Pfizer, Merck, Servier and Curegenix. HC is an inventor on several patents relating to Wnt activity in cancers and a pending patent on growing organoids from patients with colorectal cancer. He is a cofounder and SAB member of Surrozen, a start-up in Silicon Valley; a SAB member of Kallyope (New York), Merus (Utrecht) and Decibel (Boston); a non-executive board member of Roche (Basel) and SAB member of the Roche subsidiary Genentech (San Francisco) since 2019; a scientific advisor for and investor in Life Sciences Partners, a biotech venture capital firm located in Amsterdam.

  • Patient consent for publication Not required.

  • Ethics approval Institutional Review Board of The University of Hong Kong/Hospital Authority Hong Kong West Cluster.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Data availability statement Data are available in a public, open access repository. The whole genome, exome and RNA sequencing data have been deposited into the European Genome-Phenome Archive with accession number EGAS00001004063 (https://www.ebi.ac.uk/ega/studies/EGAS00001004063). Application to a data access committee as a standard procedure in the EGA for data access containing human genetic data is needed, for the use of data for medical research by bona fide researchers. Normalised single-cell RNA sequencing data were deposited to GEO with accession number GEO142116 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE142116).

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