Evidence map›Paper›PMID 41120252›Full record

ReviewHuman vaccines & immunotherapeutics2025

Chimeric antigen receptor cells as a tool for localized delivery of TNFα in solid cancer treatment.

Zhenqiang Yao, Chutamath Sittplangkoon

Abstract readReview
In one paragraph

Review in Human vaccines & immunotherapeutics, 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

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

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

2 authors.

Zhenqiang YaoDepartment of Pathology and Laboratory Medicine, University of Rochester Medical Center, Rocheter, NY, USA.ORCID 0000-0002-4664-3648
Chutamath SittplangkoonDepartment of Pathology and Laboratory Medicine, University of Rochester Medical Center, Rocheter, NY, USA.

Funding

Role of Macrophage in Osteoimmunology with AgingR01AG076731 · NIA · UNIVERSITY OF ROCHESTER · PI Zhenqiang Yao · 2022 to 2026
$2.1M
NIA NIH HHS R01 AG076731
6 · The paper itself

Abstract

Chimeric antigen receptor (CAR)-T cells are effective in treating blood cancers but not solid cancers and can cause severe side effects, including cytokine release syndrome (CRS). One strategy to enhance the efficacy of CAR-T cells while avoiding CRS in cancer treatment is to deliver a single tumoricidal factor. TNFα is well known for triggering apoptosis signaling; however, it alone is not effective in treating cancers because it significantly increases the levels of inhibitor of apoptosis proteins (IAPs), a family of E3 ubiquitin ligases that block caspase-induced apoptosis. Thus, localized delivery of TNFα by targeting the tumors using the adoptive cells combined with an IAP antagonist, which degrades IAP proteins, could lead to improved outcomes in cancer treatment. This article reviews TNFα-induced apoptosis signaling pathway, outlines the principles for designing CAR-T cells, CAR-macrophages and CAR-dendritic cells expressing TNFα, used alone or in combination with IAP antagonists, and discusses the potential contraindications of IAP antagonists with several clinical used drugs for cancer treatment.

Indexed as

Immunotherapy, AdoptiveNeoplasmsReceptors, Chimeric AntigenTumor Necrosis Factor-alphaAnimalsApoptosisDendritic CellsHumansInhibitor of Apoptosis ProteinsMacrophagesSignal TransductionT-LymphocytesInhibitor of Apoptosis ProteinsReceptors, Chimeric AntigenTumor Necrosis Factor-alphaCancerchimeric antigen receptor (CAR) cell therapydendritic cell (DC)inhibitor of apoptosis proteins (IAPs)macrophageSMAC memetic (IAP antagonist)T celltumor necrosis factor-α (TNFα)

Identifiers

PMID41120252
PMCPMC12542605

What OpenQuestion holds

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Registered trials

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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 OpenQuestion graph.