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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.

SUBMITTER: Lee HS

PROVIDER: S-EPMC9842736 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature

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

Lee Hee Seung HS Han Dai Hoon DH Cho Kyungjoo K Park Soo Been SB Kim Chanyang C Leem Galam G Jung Dawoon E DE Kwon Soon Sung SS Kim Chul Hoon CH Jo Jung Hyun JH Lee Hye Won HW Song Si Young SY Park Jun Yong JY

Nature communications 20230116 1

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 ...[more]

PMID: 36646721

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Project description:As genomic analysis technology has advanced, it has become possible to sub-classify intrahepatic cholangiocarcinoma (ICC) at the histological or molecular level. However, there are no truly representative models of ICC subtypes for use in studying developmental differences, carcinogenesis, and personalized drug response. Here, we sought to verify recent suggested two subgroup of ICC in organoids model, compare the characteristics between LD and SD type of ICC, and find the type-specific gene expression profile and targetable pathway as a therapeutic target. ICC organoids from 16 patients pathologically diagnosed with cholangiocarcinoma were prepared according to a previously established organoid culture protocol. ICC patients were subclassified into small-duct (SD) type and large-duct (LD) type according to histological characteristics and S100P, N-cadherin, and CD56 expression. ICC organoids were successfully established within one month and exhibited a morphology similar to that of their matching primary cancer. LD- and SD-type organoids exhibited histologic phenotypes and staining patterns characteristic of the corresponding ICC subtypes. ICC organoids showed high concordance of somatic mutations with primary tumors. Unsupervised principal component analysis clustering effectively separated each type of ICC. Differential gene expression revealed significant enrichment on KRAS, TGFβ and ERBB2 signaling pathways in LD-type compared with SD-type ICC (P<0.05). Gene set enrichment analysis further demonstrated that the cholangiocarcinoma class 2 signature, defined by Andersen et al., was significantly enriched in the LD-type (enrichment score=2.19, P<0.001). A protein-protein interaction network analysis identified ZNF217 as a significant hub protein (odds ratio=4.96, P=0.0105). We successfully performed prospective modeling of histological subtype specification using patient-derived ICC organoids. Moreover, gene expression profiling of ICC organoids enabled identification of type-specific targetable pathways.

Project description:Intrahepatic cholangiocarcinoma (iCCA) is the second most common primary liver cancer. It is defined by cholangiocytic differentiation and has poor prognosis. Recently, epigenetic processes have been shown to play an important role in cholangiocarcinogenesis. We performed an integrative analysis on 52 iCCAs using both genetic and epigenetic data with a specific focus on DNA methylation components. We found recurrent isocitrate dehydrogenase 1 (IDH1) and IDH2 (28%) gene mutations, recurrent arm-length copy number alterations (CNAs), and focal alterations such as deletion of 3p21 or amplification of 12q15, which affect BRCA1 Associated Protein 1, polybromo 1, and mouse double minute 2 homolog. DNA methylome analysis revealed excessive hypermethylation of iCCA, affecting primarily the bivalent genomic regions marked with both active and repressive histone modifications. Integrative clustering of genetic and epigenetic data identified four iCCA subgroups with prognostic relevance further designated as IDH, high (H), medium (M), and low (L) alteration groups. The IDH group consisted of all samples with IDH1 or IDH2 mutations and showed, together with the H group, a highly disrupted genome, characterized by frequent deletions of chromosome arms 3p and 6q. Both groups showed excessive hypermethylation with distinct patterns. The M group showed intermediate characteristics regarding both genetic and epigenetic marks, whereas the L group exhibited few methylation changes and mutations and a lack of CNAs. Methylation-based latent component analysis of cell-type composition identified differences among these four groups. Prognosis of the H and M groups was significantly worse than that of the L group. Conclusion: Using an integrative genomic and epigenomic analysis approach, we identified four major iCCA subgroups with widespread genomic and epigenomic differences and prognostic implications. Furthermore, our data suggest differences in the cell-of-origin of the iCCA subtypes.

Project description:BackgroundIntrahepatic cholangiocarcinoma (iCCA) is a highly lethal malignancy of the biliary tract. Analysis of somatic mutational profiling can reveal new prognostic markers and actionable treatment targets. In this study, we explored the utility of genomic mutation signature and tumor mutation burden (TMB) in predicting prognosis in iCCA patients.MethodsWhole-exome sequencing and corresponding clinical data were collected from the ICGC portal and cBioPortal database to detect the prognostic mutated genes and determine TMB values. To identify the hub prognostic mutant signature, we used Cox regression and Lasso feature selection. Mutation-related signature (MRS) was constructed using multivariate Cox regression. The predictive performances of MRS and TMB were assessed using Kaplan-Meier (KM) analysis and receiver operating characteristic (ROC). We performed a functional enrichment pathway analysis using gene set enrichment analysis (GSEA) for mutated genes. Based on the MRS, TMB, and the TNM stage, a nomogram was constructed to visualize prognosis in iCCA patients.ResultsThe mutation landscape illustrated distributions of mutation frequencies and types in iCCA, and generated a list of most frequently mutated genes (such as Tp53, KRAS, ARID1A, and IDH1). Thirty-two mutated genes associated with overall survival (OS) were identified in iCCA patients. We obtained a six-gene signature using the Lasso and Cox method. AUCs for the MRS in the prediction of 1-, 3-, and 5-year OS were 0.759, 0.732, and 0.728, respectively. Kaplan-Meier analysis showed a significant difference in prognosis for patients with iCCA having a high and low MRS score (P < 0.001). GSEA was used to show that several signaling pathways, including MAPK, PI3K-AKT, and proteoglycan, were involved in cancer. Conversely, survival analysis indicated that TMB was significantly associated with prognosis. GSEA indicated that samples with high MRS or TMB also showed an upregulated expression of pathways involved in tumor signaling and the immune response. Finally, the predictive nomogram (that included MRS, TMB, and the TNM stage) demonstrated satisfactory performance in predicting survival in patients with iCCA.ConclusionsMutation-related signature and TMB were associated with prognosis in patients with iCCA. Our study provides a valuable prognostic predictor for determining outcomes in patients with iCCA.

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

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

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