Evidence map›Paper›PMID 40075571›Full record

ReviewCancers2025

Bacterial-Mediated In Situ Engineering of Tumour-Associated Macrophages for Cancer Immunotherapy.

Gabriela Christina Kuhl, Mark Tangney

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 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Review
  3. 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

2 authors.

Gabriela Christina KuhlCancer Research @UCC, College of Medicine and Health, University College Cork, T12 K8AF Cork, Ireland.
Mark TangneyCancer Research @UCC, College of Medicine and Health, University College Cork, T12 K8AF Cork, Ireland.

Funding

Science Foundation Ireland 628 18/SPP/3522
6 · The paper itself

Abstract

BACKGROUND/

objectivesTumour-associated macrophages (TAMs) are critical components of the tumour microenvironment (TME), significantly influencing cancer progression and treatment resistance. This review aims to explore the innovative use of engineered bacteria to reprogram TAMs, enhancing their anti-tumour functions and improving therapeutic outcomes.

methodsWe conducted a systematic review following a predefined protocol. Multiple databases were searched to identify relevant studies on TAMs, their phenotypic plasticity, and the use of engineered bacteria for reprogramming. Inclusion and exclusion criteria were applied to select studies, and data were extracted using standardised forms. Data synthesis was performed to summarise the findings, focusing on the mechanisms and therapeutic benefits of using non-pathogenic bacteria to modify TAMs.

resultsThe review summarises the findings that engineered bacteria can selectively target TAMs, promoting a shift from the tumour-promoting M2 phenotype to the tumour-fighting M1 phenotype. This reprogramming enhances pro-inflammatory responses and anti-tumour activity within the TME. Evidence from various studies indicates significant tumour regression and improved immune responses following bacterial therapy.

conclusionsReprogramming TAMs using engineered bacteria presents a promising strategy for cancer therapy. This approach leverages the natural targeting abilities of bacteria to modify TAMs directly within the tumour, potentially improving patient outcomes and offering new insights into immune-based cancer treatments. Further research is needed to optimise these methods and assess their clinical applicability.

Indexed as

drug delivery systemsgene and cell therapyrecombinant microbes

Identifiers

PMID40075571
PMCPMC11899205

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.