Evidence map›Paper›PMID 39764598›Full record

ReviewInternational journal of surgery (London, England)2025

Focus on mechano-immunology: new direction in cancer treatment.

Lin Zhao, Yajun Gui, Xiangying Deng

Abstract readReview
In one paragraph

Review in International journal of surgery (London, England), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. Review
  5. 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

3 authors.

Lin ZhaoDepartment of Pathology, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China.
Yajun GuiDepartment of Pathology, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China.
Xiangying DengDepartment of Pathology, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The immune response is modulated by a diverse array of signals within the tissue microenvironment, encompassing biochemical factors, mechanical forces, and pressures from adjacent tissues. Furthermore, the extracellular matrix and its constituents significantly influence the function of immune cells. In the case of carcinogenesis, changes in the biophysical properties of tissues can impact the mechanical signals received by immune cells, and these signals c1an be translated into biochemical signals through mechano-transduction pathways. These mechano-transduction pathways have a profound impact on cellular functions, influencing processes such as cell activation, metabolism, proliferation, and migration, etc. Tissue mechanics may undergo temporal changes during the process of carcinogenesis, offering the potential for novel dynamic levels of immune regulation. Here, we review advances in mechanoimmunology in malignancy studies, focusing on how mechanosignals modulate the behaviors of immune cells at the tissue level, thereby triggering an immune response that ultimately influences the development and progression of malignant tumors. Additionally, we have also focused on the development of mechano-immunoengineering systems, with the help of which could help to further understand the response of tumor cells or immune cells to alterations in the microenvironment and may provide new research directions for overcoming immunotherapeutic resistance of malignant tumors.

Indexed as

Mechanotransduction, CellularNeoplasmsTumor MicroenvironmentExtracellular MatrixHumansImmunotherapy

Identifiers

PMID39764598
PMCPMC12372750

What OpenQuestion holds

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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 OpenQuestion graph.