Evidence map›Paper›PMID 35634309›Full record

ArticleFrontiers in immunology2022

Multi-Scale Spatial Analysis of the Tumor Microenvironment Reveals Features of Cabozantinib and Nivolumab Efficacy in Hepatocellular Carcinoma.

Haoyang Mi, Won Jin Ho, Mark Yarchoan, Aleksander S Popel

Open access · goldAbstract read
In one paragraph

Article in Frontiers in immunology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.

0numbers the graph read from it
0cells of the map it votes in
38citing papers in PubMed
7.9field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

38 citing papers in PubMed, 87 citations in OpenAlex.

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  12. Spatial Architecture of Single-Cell and Vasculature in Tumor Microenvironment Predicts Clinical Outcomes in Triple-Negative Breast Cancer.Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc · 2025
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  16. Identification of the CD8Translational cancer research · 2024
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  20. Omics-based molecular classifications empowering in precision oncology.Cellular oncology (Dordrecht, Netherlands) · 2024
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 3 institutions in 1 country.

Haoyang MiDepartment of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, United States.
Won Jin HoSidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, United States.
Mark YarchoanSidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, United States.
Aleksander S PopelDepartment of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, United States.
Johns Hopkins Medicine · USBloomberg (United States) · USJohns Hopkins University · US

Funding

Tumor Antigens for Individual Signatures and TherapyP50CA062924 · NCI · JOHNS HOPKINS UNIVERSITY · PI JAFFEE, ELIZABETH M. · 1993 to 2022
$54.6M
Predictive experiment-based multiscale models of the tumor immune microenvironment and immunotherapy in breast cancerR01CA138264 · NCI · JOHNS HOPKINS UNIVERSITY · PI POPEL, ALEKSANDER S. · 2009 to 2023
$8.1M
Integrating bioinformatics into multiscale models for hepatocellular carcinomaU01CA212007 · NCI · JOHNS HOPKINS UNIVERSITY · PI EWALD, ANDREW JOSEF, FERTIG, ELANA · 2018 to 2022
$3.2M
NCI NIH HHS P50 CA062924NCI NIH HHS R01 CA138264NCI NIH HHS U01 CA212007
6 · The paper itself

Abstract

Background: Concomitant inhibition of vascular endothelial growth factor (VEGF) and programmed cell death protein 1 (PD-1) or its ligand PD-L1 is a standard of care for patients with advanced hepatocellular carcinoma (HCC), but only a minority of patients respond, and responses are usually transient. Understanding the effects of therapies on the tumor microenvironment (TME) can provide insights into mechanisms of therapeutic resistance. Methods: 14 patients with HCC were treated with the combination of cabozantinib and nivolumab through the Johns Hopkins Sidney Kimmel Comprehensive Cancer Center. Among them, 12 patients (5 responders + 7 non-responders) underwent successful margin negative resection and are subjects to tissue microarray (TMA) construction containing 37 representative tumor region cores. Using the TMAs, we performed imaging mass cytometry (IMC) with a panel of 27-cell lineage and functional markers. All multiplexed images were then segmented to generate a single-cell dataset that enables (1) tumor-immune compartment analysis and (2) cell community analysis based on graph-embedding methodology. Results from these hierarchies are merged into response-associated biological process patterns. Results: Image processing on 37 multiplexed-images discriminated 59,453 cells and was then clustered into 17 cell types. Compartment analysis showed that at immune-tumor boundaries from NR, PD-L1 level on tumor cells is significantly higher than remote regions; however, Granzyme B expression shows the opposite pattern. We also identify that the close proximity of CD8 Conclusion: These results demonstrate the feasibility of a novel application of multiplexed image analysis that is broadly applicable to quantitative analysis of pathology specimens in immuno-oncology and provides further evidence that CD163

Indexed as

Carcinoma, HepatocellularLiver NeoplasmsAnilidesB7-H1 AntigenCD8-Positive T-LymphocytesHumansNivolumabPyridinesSpatial AnalysisTumor MicroenvironmentVascular Endothelial Growth Factor AAnilidesB7-H1 AntigencabozantinibNivolumabPyridinesVascular Endothelial Growth Factor Abiomarkercomputational biologyhepatocellular carcinomaimmunotherapysystems biologytumor-immune microenvironments (TIME)

Identifiers

PMID35634309
PMCPMC9136005
OpenAlexW4280650826

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.