Integrative analysis of multiple genomic data from intrahepatic cholangiocarcinoma organoids enables tumor subtyping

Hee Seung Lee; Dai Hoon Han; Kyungjoo Cho; Soo Been Park; Chanyang Kim; Galam Leem; Dawoon E. Jung; Soon Sung Kwon; Chul Hoon Kim; Jung Hyun Jo; Hye Won Lee; Si Young Song; Jun Yong Park

doi:10.1038/s41467-023-35896-4

Integrative analysis of multiple genomic data from intrahepatic cholangiocarcinoma organoids enables tumor subtyping

Hee Seung Lee, Dai Hoon Han, Kyungjoo Cho, Soo Been Park, Chanyang Kim, Galam Leem, Dawoon E. Jung, Soon Sung Kwon, Chul Hoon Kim, Jung Hyun Jo, Hye Won Lee, Si Young Song, Jun Yong Park

Department of Internal Medicine

Research output: Contribution to journal › Article › peer-review

Abstract

As genomic analysis technology has advanced, it has become possible to sub-classify intrahepatic cholangiocarcinoma (ICC) at the histological or molecular level. Here, we verify the recently suggested two subgroups of ICC in the organoids model, compare the characteristics between types. ICC patients are subclassified into small-duct (SD) and large-duct (LD) subtype according to histological characteristics. ICC organoids are established, and unsupervised principal component analysis clustering separates each type of ICC. Differential gene expression reveals enrichment on KRAS, TGFβ and ERBB2 signaling pathways in LD-type compared with SD-type (P < 0.05). Gene set enrichment analysis demonstrates that the cholangiocarcinoma class 2 signature, defined by Andersen et al., is enriched in the LD-type (enrichment Score = 2.19, P < 0.001). A protein-protein interaction network analysis identifies ZNF217 as a significant hub protein (odds ratio = 4.96, P = 0.0105). We perform prospective modeling of histological subtype using patient-derived organoids. Moreover, gene expression profiling of ICC organoids enables identification of type-specific targetable pathways.

Original language	English
Article number	237
Journal	Nature communications
Volume	14
Issue number	1
DOIs	https://doi.org/10.1038/s41467-023-35896-4
Publication status	Published - 2023 Dec

Bibliographical note

Funding Information:
We thank Meritxell Huch (Max Planck Institute of Molecular Cell Biology and Genetics) for her kind share the organoid culture protocol, review and comments for this study results. We thank Dong-Su Jang (Medical Research Support Section, Yonsei University College of Medicine) for help with the illustrations, and Hyun-Yi Kim (NGenes Inc., Asan-si, Republic of Korea) for help with bioinformatical analysis. We also thank the Bioinformatics Collaboration Unit (BICU) in the Department of Biomedical System Informatics, Yonsei University College of Medicine. This study was supported by a Faculty Research Grant of Yonsei University College of Medicine grant no. 6-2016-0122 to H.D.H., and a Severance Surgeon’s Alumni Research Grant grant no. 2016-02 to H.D.H. This study was supported by a faculty research grant of Yonsei University College of Medicine (6-2020-0079 to H.S.L.). This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korean government (NRF-2021R1A2C1008898 to H.S.L.). This research was supported by a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (grant number: HI14C1324 to S.Y.S.).

Funding Information:
We thank Meritxell Huch (Max Planck Institute of Molecular Cell Biology and Genetics) for her kind share the organoid culture protocol, review and comments for this study results. We thank Dong-Su Jang (Medical Research Support Section, Yonsei University College of Medicine) for help with the illustrations, and Hyun-Yi Kim (NGenes Inc., Asan-si, Republic of Korea) for help with bioinformatical analysis. We also thank the Bioinformatics Collaboration Unit (BICU) in the Department of Biomedical System Informatics, Yonsei University College of Medicine. This study was supported by a Faculty Research Grant of Yonsei University College of Medicine grant no. 6-2016-0122 to H.D.H., and a Severance Surgeon’s Alumni Research Grant grant no. 2016-02 to H.D.H. This study was supported by a faculty research grant of Yonsei University College of Medicine (6-2020-0079 to H.S.L.). This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korean government (NRF-2021R1A2C1008898 to H.S.L.). This research was supported by a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (grant number: HI14C1324 to S.Y.S.).

Publisher Copyright:
© 2023, The Author(s).

All Science Journal Classification (ASJC) codes

Chemistry(all)
Biochemistry, Genetics and Molecular Biology(all)
General
Physics and Astronomy(all)

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10.1038/s41467-023-35896-4

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title = "Integrative analysis of multiple genomic data from intrahepatic cholangiocarcinoma organoids enables tumor subtyping",

abstract = "As genomic analysis technology has advanced, it has become possible to sub-classify intrahepatic cholangiocarcinoma (ICC) at the histological or molecular level. Here, we verify the recently suggested two subgroups of ICC in the organoids model, compare the characteristics between types. ICC patients are subclassified into small-duct (SD) and large-duct (LD) subtype according to histological characteristics. ICC organoids are established, and unsupervised principal component analysis clustering separates each type of ICC. Differential gene expression reveals enrichment on KRAS, TGFβ and ERBB2 signaling pathways in LD-type compared with SD-type (P < 0.05). Gene set enrichment analysis demonstrates that the cholangiocarcinoma class 2 signature, defined by Andersen et al., is enriched in the LD-type (enrichment Score = 2.19, P < 0.001). A protein-protein interaction network analysis identifies ZNF217 as a significant hub protein (odds ratio = 4.96, P = 0.0105). We perform prospective modeling of histological subtype using patient-derived organoids. Moreover, gene expression profiling of ICC organoids enables identification of type-specific targetable pathways.",

author = "Lee, {Hee Seung} and Han, {Dai Hoon} and Kyungjoo Cho and Park, {Soo Been} and Chanyang Kim and Galam Leem and Jung, {Dawoon E.} and Kwon, {Soon Sung} and Kim, {Chul Hoon} and Jo, {Jung Hyun} and Lee, {Hye Won} and Song, {Si Young} and Park, {Jun Yong}",

note = "Funding Information: We thank Meritxell Huch (Max Planck Institute of Molecular Cell Biology and Genetics) for her kind share the organoid culture protocol, review and comments for this study results. We thank Dong-Su Jang (Medical Research Support Section, Yonsei University College of Medicine) for help with the illustrations, and Hyun-Yi Kim (NGenes Inc., Asan-si, Republic of Korea) for help with bioinformatical analysis. We also thank the Bioinformatics Collaboration Unit (BICU) in the Department of Biomedical System Informatics, Yonsei University College of Medicine. This study was supported by a Faculty Research Grant of Yonsei University College of Medicine grant no. 6-2016-0122 to H.D.H., and a Severance Surgeon{\textquoteright}s Alumni Research Grant grant no. 2016-02 to H.D.H. This study was supported by a faculty research grant of Yonsei University College of Medicine (6-2020-0079 to H.S.L.). This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korean government (NRF-2021R1A2C1008898 to H.S.L.). This research was supported by a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (grant number: HI14C1324 to S.Y.S.). Funding Information: We thank Meritxell Huch (Max Planck Institute of Molecular Cell Biology and Genetics) for her kind share the organoid culture protocol, review and comments for this study results. We thank Dong-Su Jang (Medical Research Support Section, Yonsei University College of Medicine) for help with the illustrations, and Hyun-Yi Kim (NGenes Inc., Asan-si, Republic of Korea) for help with bioinformatical analysis. We also thank the Bioinformatics Collaboration Unit (BICU) in the Department of Biomedical System Informatics, Yonsei University College of Medicine. This study was supported by a Faculty Research Grant of Yonsei University College of Medicine grant no. 6-2016-0122 to H.D.H., and a Severance Surgeon{\textquoteright}s Alumni Research Grant grant no. 2016-02 to H.D.H. This study was supported by a faculty research grant of Yonsei University College of Medicine (6-2020-0079 to H.S.L.). This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korean government (NRF-2021R1A2C1008898 to H.S.L.). This research was supported by a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (grant number: HI14C1324 to S.Y.S.). Publisher Copyright: {\textcopyright} 2023, The Author(s).",

year = "2023",

month = dec,

doi = "10.1038/s41467-023-35896-4",

language = "English",

volume = "14",

journal = "Nature Communications",

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T1 - Integrative analysis of multiple genomic data from intrahepatic cholangiocarcinoma organoids enables tumor subtyping

AU - Lee, Hee Seung

AU - Han, Dai Hoon

AU - Cho, Kyungjoo

AU - Park, Soo Been

AU - Kim, Chanyang

AU - Leem, Galam

AU - Jung, Dawoon E.

AU - Kwon, Soon Sung

AU - Kim, Chul Hoon

AU - Jo, Jung Hyun

AU - Lee, Hye Won

AU - Song, Si Young

AU - Park, Jun Yong

N1 - Funding Information: We thank Meritxell Huch (Max Planck Institute of Molecular Cell Biology and Genetics) for her kind share the organoid culture protocol, review and comments for this study results. We thank Dong-Su Jang (Medical Research Support Section, Yonsei University College of Medicine) for help with the illustrations, and Hyun-Yi Kim (NGenes Inc., Asan-si, Republic of Korea) for help with bioinformatical analysis. We also thank the Bioinformatics Collaboration Unit (BICU) in the Department of Biomedical System Informatics, Yonsei University College of Medicine. This study was supported by a Faculty Research Grant of Yonsei University College of Medicine grant no. 6-2016-0122 to H.D.H., and a Severance Surgeon’s Alumni Research Grant grant no. 2016-02 to H.D.H. This study was supported by a faculty research grant of Yonsei University College of Medicine (6-2020-0079 to H.S.L.). This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korean government (NRF-2021R1A2C1008898 to H.S.L.). This research was supported by a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (grant number: HI14C1324 to S.Y.S.). Funding Information: We thank Meritxell Huch (Max Planck Institute of Molecular Cell Biology and Genetics) for her kind share the organoid culture protocol, review and comments for this study results. We thank Dong-Su Jang (Medical Research Support Section, Yonsei University College of Medicine) for help with the illustrations, and Hyun-Yi Kim (NGenes Inc., Asan-si, Republic of Korea) for help with bioinformatical analysis. We also thank the Bioinformatics Collaboration Unit (BICU) in the Department of Biomedical System Informatics, Yonsei University College of Medicine. This study was supported by a Faculty Research Grant of Yonsei University College of Medicine grant no. 6-2016-0122 to H.D.H., and a Severance Surgeon’s Alumni Research Grant grant no. 2016-02 to H.D.H. This study was supported by a faculty research grant of Yonsei University College of Medicine (6-2020-0079 to H.S.L.). This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korean government (NRF-2021R1A2C1008898 to H.S.L.). This research was supported by a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (grant number: HI14C1324 to S.Y.S.). Publisher Copyright: © 2023, The Author(s).

PY - 2023/12

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N2 - As genomic analysis technology has advanced, it has become possible to sub-classify intrahepatic cholangiocarcinoma (ICC) at the histological or molecular level. Here, we verify the recently suggested two subgroups of ICC in the organoids model, compare the characteristics between types. ICC patients are subclassified into small-duct (SD) and large-duct (LD) subtype according to histological characteristics. ICC organoids are established, and unsupervised principal component analysis clustering separates each type of ICC. Differential gene expression reveals enrichment on KRAS, TGFβ and ERBB2 signaling pathways in LD-type compared with SD-type (P < 0.05). Gene set enrichment analysis demonstrates that the cholangiocarcinoma class 2 signature, defined by Andersen et al., is enriched in the LD-type (enrichment Score = 2.19, P < 0.001). A protein-protein interaction network analysis identifies ZNF217 as a significant hub protein (odds ratio = 4.96, P = 0.0105). We perform prospective modeling of histological subtype using patient-derived organoids. Moreover, gene expression profiling of ICC organoids enables identification of type-specific targetable pathways.

AB - As genomic analysis technology has advanced, it has become possible to sub-classify intrahepatic cholangiocarcinoma (ICC) at the histological or molecular level. Here, we verify the recently suggested two subgroups of ICC in the organoids model, compare the characteristics between types. ICC patients are subclassified into small-duct (SD) and large-duct (LD) subtype according to histological characteristics. ICC organoids are established, and unsupervised principal component analysis clustering separates each type of ICC. Differential gene expression reveals enrichment on KRAS, TGFβ and ERBB2 signaling pathways in LD-type compared with SD-type (P < 0.05). Gene set enrichment analysis demonstrates that the cholangiocarcinoma class 2 signature, defined by Andersen et al., is enriched in the LD-type (enrichment Score = 2.19, P < 0.001). A protein-protein interaction network analysis identifies ZNF217 as a significant hub protein (odds ratio = 4.96, P = 0.0105). We perform prospective modeling of histological subtype using patient-derived organoids. Moreover, gene expression profiling of ICC organoids enables identification of type-specific targetable pathways.

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Integrative analysis of multiple genomic data from intrahepatic cholangiocarcinoma organoids enables tumor subtyping

Abstract

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