Evidence map›Paper›PMID 42707968›Full record

ReviewFrontiers in oncology2026

Adenosine signaling in tumor immune escape: metabolic checkpoints, myeloid suppression, and combination immunotherapy.

Rui Li, Shengbiao Li, Tongtong Zhang

Abstract readReview
In one paragraph

Review in Frontiers in oncology, 2026. 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

3 authors.

Rui LiSchool of Basic Medical Sciences, Southwest Medical University, Luzhou, China.
Shengbiao LiSchool of Basic Medical Sciences, Southwest Medical University, Luzhou, China.
Tongtong ZhangSchool of Basic Medical Sciences, Southwest Medical University, Luzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Adenosine is a central metabolic regulator of tumor immune escape, shaping the tumor microenvironment (TME) through suppression of effector lymphocytes and reprogramming of myeloid populations. Extracellular adenosine is generated primarily via the ectonucleotidases CD39 and CD73 and signals through A2A (A2AR) and A2B (A2BR) receptors on T cells, NK cells, tumor-associated macrophages (TAMs), myeloid-derived suppressor cells (MDSCs), and dendritic cells. This pathway promotes T-cell exhaustion, inhibits cytotoxicity, and enhances myeloid-driven immunosuppression, creating metabolic and spatial barriers that limit the efficacy of immune checkpoint blockade, STING agonists, radiotherapy, and emerging photothermal or nanomaterial-based therapies. Preclinical studies demonstrate that targeting the adenosine axis-via CD39/CD73 inhibition, receptor blockade, or combination strategies-can restore immune effector function, reprogram suppressive myeloid niches, and potentiate antitumor immunity. Spatial and circulating biomarkers, including tumor and exosomal CD73, adenosine gradients, and TAM/MDSC infiltration, may guide patient stratification and optimize combinatorial immunotherapy. Integrating adenosine-targeted approaches with PD-1/PD-L1 blockade, STING agonists, or adoptive cell therapies offers a rational strategy to overcome resistance and improve therapeutic outcomes. This review summarizes recent experimental evidence on the mechanisms of adenosine-mediated immune suppression, highlights translational opportunities, and discusses strategies for personalized and combination therapies aimed at dismantling metabolic immune checkpoints in cancer.

Indexed as

adenosineCD73/CD39immunotherapy resistancemyeloid suppressiontumor microenvironment

Identifiers

PMID42707968
PMCPMC13548807

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.