Evidence map›Paper›PMID 39858016›Full record

ReviewCancers2025

Next-Generation Immunotherapy for Hepatocellular Carcinoma: Mechanisms of Resistance and Novel Treatment Approaches.

Shabnam Eghbali, Thatcher Ross Heumann

Abstract readReview
In one paragraph

Review in Cancers, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

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

14 citing papers in PubMed.

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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

2 authors.

Shabnam EghbaliDivision of Internal Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37232, USA.ORCID 0000-0002-1326-0050
Thatcher Ross HeumannDivision of Hematology and Oncology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37232, USA.

Funding

Vanderbilt Clinical Oncology Research Career Development ProgramK12CA090625 · NCI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI Debra L. Friedman, Paula Jill Hurley · 2001 to 2026
$16.9M
National Institute of Health (USA) NIH K12 CA090625-17NCI NIH HHS K12 CA090625
6 · The paper itself

Abstract

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality worldwide, and, with only 15-20% of HCC patients being suitable for potentially curative treatments, the vast majority of patients with HCC ultimately require systemic therapy. For decades, the choice of effective systemic therapy for HCC remained sparse. In recent years, after the combination of atezolizumab and bevacizumab demonstrated superior overall survival over the first-line standard, sorafenib, there has been a major therapeutic paradigm shift to immunotherapy-based regimens for HCC. While representing a great leap forward for the treatment of this cancer, the reality is that less than one-third of patients achieve an objective response to immune checkpoint inhibitor-based therapy, so there remains a significant clinical need for further therapeutic optimization. In this review, we provide an overview of the current landscape of immunotherapy for unresectable HCC and delve into the tumor intrinsic and extrinsic mechanisms of resistance to established immunotherapies with a focus on novel therapeutic targets with strong translational potential. Following this, we spotlight emerging immunotherapy approaches and notable clinical trials aiming to optimize immunotherapy efficacy in HCC that include novel immune checkpoint inhibitors, tumor microenvironment modulators, targeted delivery systems, and locoregional interventions.

Indexed as

angiogenesisbispecific antibodiescancer vaccineCAR-T cell therapyglypican-3hepatocellular carcinomaimmunotherapylocoregional therapyneoadjuvantWnt/β-catenin

Identifiers

PMID39858016
PMCPMC11764197

What Socratic 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 Socratic graph.