Evidence map›Paper›PMID 41664158›Full record

SynthesisJournal of orthopaedic surgery and research2026

Proteomic trajectories in human rotator cuff degeneration: a systematic review of immunohistochemical studies.

Dave Osinachukwu Duru, Andrew Kailin Zhou, Patrick J Carroll, Amr Elmaraghy

Abstract readSystematic Review
In one paragraph

Synthesis in Journal of orthopaedic surgery and research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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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

4 authors.

Dave Osinachukwu DuruSchool of Clinical Medicine, University of Cambridge, Cambridge, UK. dd614@cam.ac.uk.
Andrew Kailin ZhouUniversity of Warwick, Coventry, UK.
Patrick J CarrollDivision of Orthopaedic Surgery, Department of Surgery, University of Toronto, Toronto, ON, Canada.
Amr ElmaraghyDivision of Orthopaedic Surgery, Department of Surgery, University of Toronto, Toronto, ON, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRotator cuff (RC) repairs heal unreliably, particularly in chronic disease. The molecular mechanisms underlying failed repair remain poorly understood. While individual studies have examined protein expression in diseased RC tissue, no synthesis has investigated these findings across various disease stages. This systematic review explores the stage-specific protein expression of human RC degeneration using immunohistochemistry.

methodsFollowing PRISMA guidelines, MEDLINE, Embase, and Cochrane Library were systematically searched to September 2025 for human studies that use immunohistochemistry to evaluate protein expression in intraoperative RC tendon or muscle biopsies. Study quality was appraised with Joanna Briggs Institute (JBI) tools. No meta-analysis was performed due to heterogeneity.

resultsForty-seven studies were included. Despite methodological heterogeneity, convergent molecular patterns emerged within disease stages. Partial and small tears demonstrated hypoxic-inflammatory-apoptotic signatures (HIF-1α, BNip3, IL-6, IL-1β, MMP-1/3/9) with preserved regenerative markers (Ki67, CD34), suggesting reparative potential. Medium tears exhibited sustained angiogenic activity (VEGF) and emerging adipogenic drift (PPARγ, C/EBPα). Large and massive tears showed depletion of anabolic factors (TGF-β1, BMP-5), M2-macrophage predominance (CD206, CD163), and fibrofatty infiltration. Patient comorbidities (diabetes, vitamin D deficiency, smoking) amplified inflammatory and adipogenic signatures.

conclusionsCross-sectional human immunohistochemical evidence infers a stage-associated molecular trajectory: inflammatory-hypoxic stress with retained reparative capacity at earlier disease stages to fibrotic-adipogenic failure at later stages. This molecular framework may support future approaches to surgical decision-making and precision therapies.

Indexed as

ImmunohistochemistryProteomicsRotator CuffRotator Cuff InjuriesBiomarkersHumansBiomarkersBiomarkersFibrosisHypoxiaImmunohistochemistryInflammationProteinsRegenerative medicineRotator cuff tear

Identifiers

PMID41664158
PMCPMC12983771

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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.