Evidence map›Paper›PMID 41013723›Full record

ReviewJournal of hematology & oncology2025

Combination immunotherapy in hepatocellular carcinoma: synergies among immune checkpoints, TKIs, and chemotherapy.

Suoyi Dai, Yuhang Chen, Wenxun Cai, Shu Dong, Jiangang Zhao, Lianyu Chen, Chien-Shan Cheng

Abstract readReview
In one paragraph

Review in Journal of hematology & oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed, 4 pooled it
–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

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

35 citing papers in PubMed, 4 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Review
  6. Review
  7. Review
  8. Defect-Engineered BiOAdvanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Article
  9. Review
  10. Article
  11. Article
  12. Article
  13. Review
  14. Article
  15. Review
  16. Article
  17. Article
  18. Leveraging Artificial Intelligence and Large Language Models for Cancer Immunotherapy.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Review
  19. Review
  20. Review
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

7 authors.

Suoyi Dai *Department of Integrative Oncology, Fudan University Shanghai Cancer Center, Shanghai, 200032, China.
Yuhang Chen *Department of Integrative Oncology, Fudan University Shanghai Cancer Center, Shanghai, 200032, China.
Wenxun CaiDepartment of Integrative Oncology, Fudan University Shanghai Cancer Center, Shanghai, 200032, China.
Shu DongDepartment of Integrative Oncology, Fudan University Shanghai Cancer Center, Shanghai, 200032, China.
Jiangang ZhaoDepartment of Integrative Oncology, Fudan University Shanghai Cancer Center, Shanghai, 200032, China.
Lianyu ChenDepartment of Integrative Oncology, Fudan University Shanghai Cancer Center, Shanghai, 200032, China. lianyu-chen@alu.fudan.edu.cn.
Chien-Shan ChengDepartment of Integrative Oncology, Fudan University Shanghai Cancer Center, Shanghai, 200032, China. natcheng@connect.hku.hk.

Funding

National Natural Science Foundation of China,China 82174169
6 · The paper itself

Abstract

Combination therapy is rapidly becoming the cornerstone of hepatocellular carcinoma (HCC) treatment. Immune checkpoint inhibitors (ICIs) have emerged as a central strategy in systemic therapy, yet their efficacy as monotherapies remains limited. Consequently, combinatorial approaches, such as ICIs-Tyrosine kinase inhibitors (TKIs), ICIs-chemotherapy, and dual ICI regimens, are gaining momentum. While clinical trials have established efficacy benchmarks, mechanistic insights remain scarce, partly due to the limitations of current preclinical models in mimicking the complex tumor microenvironment (TME). Given the substantial heterogeneity of HCC, spanning genetic, transcriptomic, and immunologic dimensions, treatment outcomes vary widely. Additional factors such as gut microbiota and epigenetic modifications further influence therapeutic response and resistance. Although PD-1, PD-L1, and CTLA-4 inhibitors are widely used, unresponsiveness is common. Novel targets such as LAG-3, TIM-3, TIGIT, and VISTA, as well as strategies to reprogram fibrotic and immunosuppressive TME, are under active investigation. Ultimately, translating basic insights into personalized therapy will depend on predictive biomarkers and integrated analyses that account for the complex interactions among tumor cells, the immune system, and the TME. This review synthesizes current knowledge and cellular mechanisms underpinning combination therapies, highlights therapeutic synergies, and discusses emerging directions for stratified treatment in HCC.

Indexed as

Antineoplastic Combined Chemotherapy ProtocolsCarcinoma, HepatocellularImmune Checkpoint InhibitorsImmunotherapyLiver NeoplasmsProtein Kinase InhibitorsAnimalsHumansTumor MicroenvironmentImmune Checkpoint InhibitorsProtein Kinase InhibitorsChemotherapyCombination immunotherapyHepatocellular carcinoma (HCC)Immune checkpoint inhibitors (ICIs)Tyrosine kinase inhibitors (TKIs)

Identifiers

PMID41013723
PMCPMC12465164

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.