Evidence mapPaperPMID 41381712Full record

ArticleNPJ precision oncology2025

Differential implications of tumor endothelial cell and lymphocyte densities in advanced hepatocellular carcinoma patients treated with immunotherapy.

Gwangil Kim, Beodeul Kang, Jung Yong Hong, Haeyoun Kang, Jung Sun Kim, Sohyun Hwang, Sung Hwan Lee, Sang Hoon Jung, Chansik An, Won Suk Lee and 10 more

Abstract read
In one paragraph

Article in NPJ precision oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
field-weighted citation impact
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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

20 authors.

Gwangil Kim *Department of Pathology, CHA Bundang Medical Center, Seongnam, Korea.
Beodeul Kang *Medical Oncology, Department of Internal Medicine, CHA Bundang Medical Center, CHA University School of Medicine, Seongnam, Korea.
Jung Yong Hong *Division of Hematology-Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.
Haeyoun KangDepartment of Pathology, CHA Bundang Medical Center, Seongnam, Korea.
Jung Sun KimMedical Oncology, Department of Internal Medicine, CHA Bundang Medical Center, CHA University School of Medicine, Seongnam, Korea.
Sohyun HwangDepartment of Pathology, CHA Bundang Medical Center, Seongnam, Korea.
Sung Hwan LeeDepartment of Surgery, CHA Bundang Medical Center, CHA University, Seongnam, Korea.
Sang Hoon JungDepartment of Radiology, CHA Bundang Medical Center, CHA University, Seongnam, Korea.
Chansik AnDepartment of Radiology, CHA Bundang Medical Center, CHA University, Seongnam, Korea.
Won Suk LeeMedical Oncology, Department of Internal Medicine, CHA Bundang Medical Center, CHA University School of Medicine, Seongnam, Korea.
Chiyoon OumLunit Inc., Seoul, Korea.
Gahee ParkLunit Inc., Seoul, Korea.
Mingu KangLunit Inc., Seoul, Korea.
Yoojoo LimLunit Inc., Seoul, Korea.
Jin Woo OhLunit Inc., Seoul, Korea.
Siraj M AliLunit Inc., Seoul, Korea.
Chan-Young OckLunit Inc., Seoul, Korea.
Chan KimMedical Oncology, Department of Internal Medicine, CHA Bundang Medical Center, CHA University School of Medicine, Seongnam, Korea. chan@cha.ac.kr.
Ho Yeong LimDivision of Hematology-Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea. hoylim@skku.edu.
Hong Jae ChonMedical Oncology, Department of Internal Medicine, CHA Bundang Medical Center, CHA University School of Medicine, Seongnam, Korea. minidoctor@cha.ac.kr.

Funding

National Research Foundation of Korea NRF-2023R1A2C2004339National Research Foundation of Korea NRF-2023R1A2C2006375
6 · The paper itself

Abstract

We investigated whether artificial intelligence (AI)-based tumor microenvironment profiling correlates with treatment efficacy in unresectable hepatocellular carcinoma (HCC) patients treated with immune checkpoint inhibitor (ICI) therapies. Spatial distribution of immune/non-immune cells from pretreatment H&E images of 163 patients was retrospectively analyzed using an AI/deep-learning model. High tumor endothelial cell (TEC) density was associated with significantly longer progression-free survival (PFS) in the atezolizumab plus bevacizumab (atezo-bev) cohort (HR 0.51 [0.27-0.97]; p = 0.037) but not in the anti-PD-1 monotherapy cohort (HR 1.02 [0.59-1.77]; p = 0.935). Conversely, inflamed immune phenotype, characterized by high intratumoral TIL densities, predicted longer PFS after anti-PD-1 monotherapy (HR 0.50 [0.25-0.99]; p = 0.042) but not after atezo-bev (HR 0.92 [0.50-1.69]; p = 0.762). Our exploratory analysis using AI/deep-learning model demonstrated high TEC density predicted superior outcomes with atezo-bev, while TIL presence correlated with improved anti-PD-1 monotherapy efficacy in HCC patients, suggesting potential clinical applicability in treatment selection.

Identifiers

PMID41381712
PMCPMC12775446

What Socratic holds

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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 Socratic graph.