Evidence map›Paper›PMID 39105848›Full record

SynthesisCancer immunology, immunotherapy : CII2024

Targeting PI3K-gamma in myeloid driven tumour immune suppression: a systematic review and meta-analysis of the preclinical literature.

Haonan Xu, Shannon Nicole Russell, Katherine Steiner, Eric O'Neill, Keaton Ian Jones

Abstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in Cancer immunology, immunotherapy : CII, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing 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

20 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. Article
  5. Review
  6. Recent progress in understanding ferroptosis mechanisms in infectious diseases.Frontiers in cellular and infection microbiology · 2026
    Review
  7. Review
  8. Review
  9. Review
  10. Article
  11. Review
  12. Review
  13. Targeting PI3Kγ in cancer.Trends in cancer · 2025
    Review
  14. Article
  15. Article
  16. Review
  17. Article
  18. 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

5 authors.

Haonan XuDepartment of Oncology, University of Oxford, Oxford, UK.
Shannon Nicole RussellNuffield Department of Surgical Sciences, University of Oxford, Oxford, UK.
Katherine SteinerBodleian Health Care Libraries, University of Oxford, Oxford, UK.
Eric O'NeillDepartment of Oncology, University of Oxford, Oxford, UK.
Keaton Ian JonesNuffield Department of Surgical Sciences, University of Oxford, Oxford, UK. keaton.jones@nds.ox.ac.uk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The intricate interplay between immune and stromal cells within the tumour microenvironment (TME) significantly influences tumour progression. Myeloid cells, including tumour-associated macrophages (TAMs), neutrophils (TANs), and myeloid-derived suppressor cells (MDSCs), contribute to immune suppression in the TME (Nakamura and Smyth in Cell Mol Immunol 17(1):1-12 (2020). https://doi.org/10.1038/s41423-019-0306-1 ; DeNardo and Ruffell in Nat Rev Immunol 19(6):369-382 (2019). https://doi.org/10.1038/s41577-019-0127-6 ). This poses a significant challenge for novel immunotherapeutics that rely on host immunity to exert their effect. This systematic review explores the preclinical evidence surrounding the inhibition of phosphoinositide 3-kinase gamma (PI3Kγ) as a strategy to reverse myeloid-driven immune suppression in solid tumours. EMBASE, MEDLINE, and PubMed databases were searched on 6 October 2022 using keyword and subject heading terms to capture relevant studies. The studies, focusing on PI3Kγ inhibition in animal models, were subjected to predefined inclusion and exclusion criteria. Extracted data included tumour growth kinetics, survival endpoints, and immunological responses which were meta-analysed. PRISMA and MOOSE guidelines were followed. A total of 36 studies covering 73 animal models were included in the review and meta-analysis. Tumour models covered breast, colorectal, lung, skin, pancreas, brain, liver, prostate, head and neck, soft tissue, gastric, and oral cancer. The predominant PI3Kγ inhibitors were IPI-549 and TG100-115, demonstrating favourable specificity for the gamma isoform. Combination therapies, often involving chemotherapy, radiotherapy, immune checkpoint inhibitors, biological agents, or vaccines, were explored in 81% of studies. Analysis of tumour growth kinetics revealed a statistically significant though heterogeneous response to PI3Kγ monotherapy, whereas the tumour growth in combination treated groups were more consistently reduced. Survival analysis showed a pronounced increase in median overall survival with combination therapy. This systematic review provides a comprehensive analysis of preclinical studies investigating PI3Kγ inhibition in myeloid-driven tumour immune suppression. The identified studies underscore the potential of PI3Kγ inhibition in reshaping the TME by modulating myeloid cell functions. The combination of PI3Kγ inhibition with other therapeutic modalities demonstrated enhanced antitumour effects, suggesting a synergistic approach to overcome immune suppression. These findings support the potential of PI3Kγ-targeted therapies, particularly in combination regimens, as a promising avenue for future clinical exploration in diverse solid tumour types.

Indexed as

Class Ib Phosphatidylinositol 3-KinaseMyeloid CellsNeoplasmsPhosphoinositide-3 Kinase InhibitorsTumor MicroenvironmentAnimalsHumansImmunotherapyMyeloid-Derived Suppressor CellsClass Ib Phosphatidylinositol 3-KinasePhosphoinositide-3 Kinase InhibitorsPIK3CG protein, humanMacrophageMeta-analysisPI3K-gammaRepolarisationTumour

Identifiers

PMID39105848
PMCPMC11303654

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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.