Dissecting Intra-Tumoral Changes Following Immune Checkpoint Blockades in Intrahepatic Cholangiocarcinoma via Single-Cell Analysis

Sun, Bao-Ye; Zhou, Cheng; Guan, Ruijuan; Liu, Gao; Yang, Zhixu; Wang, Zhu-Tao; Gan, Wei; Zhou, Jian; Fan, Jia; Yi, Yong; Qiu, Shuang–Jian

doi:10.3389/fimmu.2022.871769

Cited by 17 publications

(16 citation statements)

References 56 publications

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“…8a ). The strong enrichment of monocytes in PBMC samples and Kupffer cells in Normal phenotype was consistent with physiological distributions of myeloid cells whereas the pro-fibrogenic macrophage Mp_02_SPP1 in ICC and conventional DC featuring LAMP3 expression (DC_CCL19) exhibited significant concentration in ICC and HCC respectively as frequently discussed in literature 26 , 40 , 41 (Fig. 8a ).…”

Section: Technical Validationsupporting

confidence: 83%

GepLiver: an integrative liver expression atlas spanning developmental stages and liver disease phases

Zhang

Qin

et al. 2023

Sci Data

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Chronic liver diseases usually developed through stepwise pathological transitions under the persistent risk factors. The molecular changes during liver transitions are pivotal to improve liver diagnostics and therapeutics yet still remain elusive. Cumulative large-scale liver transcriptomic studies have been revealing molecular landscape of various liver conditions at bulk and single-cell resolution, however, neither single experiment nor databases enabled thorough investigations of transcriptomic dynamics along the progression of liver diseases. Here we establish GepLiver, a longitudinal and multidimensional liver expression atlas integrating expression profiles of 2469 human bulk tissues, 492 mouse samples, 409,775 single cells from 347 human samples and 27 liver cell lines spanning 16 liver phenotypes with uniformed processing and annotating methods. Using GepLiver, we have demonstrated dynamic changes of gene expression, cell abundance and crosstalk harboring meaningful biological associations. GepLiver can be applied to explore the evolving expression patterns and transcriptomic features for genes and cell types respectively among liver phenotypes, assisting the investigation of liver transcriptomic dynamics and informing biomarkers and targets for liver diseases.

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Section: Technical Validationsupporting

confidence: 83%

GepLiver: an integrative liver expression atlas spanning developmental stages and liver disease phases

Zhang

Qin

et al. 2023

Sci Data

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“… 46 The immune fluorescence staining of 264 patients with ICC revealed that high infiltration of SPP1+TAMs was associated with inferior outcomes, consistent with our result. 47 SPP+1 TAMs were reported to interact with FAP+fibroblast cells, remodeling the extracellular matrix and inhibiting the infiltration of immune cells, leading to immunotherapy resistance. 48 Another study in colorectal liver metastasis revealed that patients who respond to neoadjuvant chemotherapy showed a decrease of SPP1+macrophages, while the opposite results were observed in the nonresponders.…”

Section: Discussionmentioning

confidence: 99%

Single-cell transcriptome analysis revealed the immune profile of PD-1 blockade in gallbladder carcinoma liver metastasis

Xie

Ning

Hua

et al. 2023

Hepatology Communications

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Background: Gallbladder carcinoma is the most common cancer of the biliary tract, and the immune checkpoint blockade showed promising efficacy in the treatment of advanced gallbladder carcinoma. However, the underlying mechanisms remain unknown. Methods: Single-cell RNA sequencing was used to reveal immune cell dynamics in an anti-PD-1 responder with gallbladder carcinoma liver metastases. Gene set variation analysis, pseudotime analysis, single-cell regulatory network inference and clustering analysis, and CellChat analysis were used to identify the functions of each cell cluster. Immunohistochemistry and multicolored immunohistochemistry analysis were applied to confirm the intratumoral cell types, and the prognostic value of CXCL13+CD8+T cells in patients with gallbladder carcinoma liver metastases with immunotherapy was evaluated. Four biliary tract carcinoma and 3 immunotherapy bulk RNA-seq datasets were analyzed to investigate the prognostic value of CXCL13+CD8+T cells and SPP1+TAMs. Result: A total of 19,648 high-quality single-cell transcriptome data were obtained from liver metastasis before and after aPD-1 therapy. We discovered improved cytotoxic activity in CD8+T cells and enhanced proinflammatory phenotypes in myeloid cells. The identified SPP1+TAMs were related to poor prognosis. The increased effector/memory T cells represented characteristics similar to exhausted T cells in transitory status after aPD-1therapy, which may play a crucial role in the antitumor immune response. We further revealed that CXCL13+T cells in a high subtype of biliary tract carcinoma were characterized as a ‘hot tumor’ profile with high immune scores, correlated to the immunostimulatory context with favorable survival, and can predict effective responses to immunotherapy. Conclusions: Our study provided an overview of immune cell dynamics in gallbladder carcinoma liver metastases after aPD-1 treatment and highlighted the importance of CXCL13+T cells in biliary tract carcinoma and effective responses to immunotherapy, which would advance the understanding and treatment of the disease.

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“…The single-cell RNA data included in this study were obtained based on a previous HCC study (GSE125449). 25 …”

Section: Methodsmentioning

confidence: 99%

Identification and Validation in a Novel Classification of Helicase Patterns for the Prediction of Tumor Proliferation and Prognosis

Yin¹,

Xu²,

Liu³

et al. 2022

JHC

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Background Helicases have been classified as a class of enzymes that determine the stability of the cellular genome. There is growing evidence that helicases can help tumor cells resist drug killing by repairing Deoxyribose Nucleic Acid (DNA) or stabilizing transcription, which may contribute to the understanding of drug resistance. Currently, identifying cancer biomarkers among helicases and stratifying patients according to helicase activity will be able to guide treatment well. Methods We clustered 371 hepatocellular carcinoma (HCC) patients from The Cancer Genome Atlas (TCGA) by consensus clustering based on helicase expression profiles to identify potential molecular subtypes. The Multiscale Embedded Gene Co-Expression Network Analysis (MEGENA) algorithm was used to find core differential gene modules between different molecular subtypes, and single-cell analysis was utlized to explore the potential function of hub gene. Immunohistochemical (IHC) staining was used to verify the diagnostic value of DDX56 and its ability to reflect the proliferation efficiency of cancer cells. Results We identified two subtypes associated with helicase. High helicase subtype was associated with poor clinical outcome, massive M0 macrophage infiltration, and highly active cell proliferation features. In addition, we identified a new biomarker, DDX56 , which has not been reported in HCC, was highly expressed in HCC tissues, associated with poor prognosis, and was also shown to be associated with high cell proliferative activity. Conclusion In conclusion, based on helicase expression profiles, we have developed a new classification system for HCC, which is a proliferation-related system, and has clinical significance in evaluating prognosis and treating HCC patients, including immunotherapy and chemotherapy. In addition, we identified a new biomarker, DDX 56 , which is overexpressed in HCC tissues, predicts a poor prognosis and is a validated index of tumor cell proliferation.

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Dissecting Intra-Tumoral Changes Following Immune Checkpoint Blockades in Intrahepatic Cholangiocarcinoma via Single-Cell Analysis

Cited by 17 publications

References 56 publications

GepLiver: an integrative liver expression atlas spanning developmental stages and liver disease phases

GepLiver: an integrative liver expression atlas spanning developmental stages and liver disease phases

Single-cell transcriptome analysis revealed the immune profile of PD-1 blockade in gallbladder carcinoma liver metastasis

Identification and Validation in a Novel Classification of Helicase Patterns for the Prediction of Tumor Proliferation and Prognosis

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