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ZENODO
Dataset . 2025
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2025
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2025
License: CC BY
Data sources: Datacite
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Multi-omics analysis reveals the link between Treg distribution and therapy efficacy in Hepatocellular Carcinoma patients treated with tremelimumab plus durvalumab

Authors: Myojin, Yuta; Kedei, Noemi; Greten, Tim;

Multi-omics analysis reveals the link between Treg distribution and therapy efficacy in Hepatocellular Carcinoma patients treated with tremelimumab plus durvalumab

Abstract

Introduction Hepatocellular carcinoma (HCC) remains a significant contributor to cancer-related deaths. Immunotherapy, either alone or in combination, has emerged as the standard treatment for advanced HCC. Notably, the combination of durvalumab (dur) and tremelimumab (trem) has received FDA approval based on findings from the HIMALAYA trial. However, comprehensive studies elucidating immune responses are lacking. We conducted a thorough analysis utilizing clinical samples from tumor biopsies to understand the mechanism of response. Methods Multiplexed immunofluorescence microscopy was used to analyze immune cell infiltration in primary human liver cancer samples. We developed and validated a comprehensive 37-plex antibody panel for immunofluorescence imaging of human FFPE samples. We applied highly multiplexed co-detection by indexing (CODEX) technology to simultaneously profile in situ expression of 37 proteins at sub-cellular resolution in 20 HCC patient samples using whole slide scanning. We established an image analysis pipeline to quantify all major cell populations in the human liver using supervised manual gating and unsupervised clustering algorithms using the exported matrix of the marker expression and spatial information. Clinical metadata including sex, gender, ethnicity, pretreatment, and histopathological reports are available for all patient samples. Results Using high-dimensional spatially resolved quantitative analysis of multiplexed immunofluorescence microscopy images, we generated a unique dataset and profiled the single-cell pathology landscape for human HCC treated with immunotherapy. In situ phenotyping of 400,000 single cells (including 130,000 CD45+ immune cells) allowed for the quantification of cell phenotype clusters, differential analysis of activation markers, and spatial features of each individual cell. This analysis revealed the comprehensive profile of the cell composition and spatial interactions of different cells in the TiME of patients treated with immunotherapy. Further details on the study can be obtained in our paper once it’s published. Conclusion We developed the CODEX panel for FFPE biopsy samples of HCC patients.

Each image contains 1: HALO exported interactive markup image file :Tif 2: HALO exported image :Tif 3: HALO_AI Exported matrix file :csv.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
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