Evidence map›Paper›PMID 41631009›Full record

ArticleJournal of bone oncology2026

Efferocytosis-associated transcriptomic patterns characterize prognosis and immune landscape in osteosarcoma.

Xueliang Song, Xiaofan Tou, Li Li, Fengxian Wang, Chengqun Qian, Ru Wang, Jiahong Shen

Abstract read
In one paragraph

Article in Journal of bone oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. Article
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

7 authors.

Xueliang SongCancer Center, Department of Orthopedics, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, Hangzhou 310014, Zhejiang, China.
Xiaofan TouCancer Center, Department of Orthopedics, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, Hangzhou 310014, Zhejiang, China.
Li LiCancer Center, Department of Orthopedics, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, Hangzhou 310014, Zhejiang, China.
Fengxian WangCancer Center, Department of Orthopedics, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, Hangzhou 310014, Zhejiang, China.
Chengqun QianCancer Center, Department of Orthopedics, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, Hangzhou 310014, Zhejiang, China.
Ru WangCancer Center, Department of Orthopedics, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, Hangzhou 310014, Zhejiang, China.
Jiahong ShenCancer Center, Department of Orthopedics, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, Hangzhou 310014, Zhejiang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Osteosarcoma (OS) is the most common primary malignant bone tumor in adolescents, characterized by high heterogeneity and poor prognosis. Efferocytosis, the clearance of apoptotic cells, has been implicated in tumor progression and immune evasion, but its role in OS remains unclear. Methods: We integrated TARGET-OS as a training cohort with three GEO datasets for validation. Efferocytosis pathways were quantified by ssGSEA, and WGCNA was applied to identify associated gene modules. Candidate genes were screened using univariate Cox regression, and a prognostic signature was developed with machine learning models and validated across cohorts. Functional enrichment, immune infiltration, and immunotherapy prediction analyses were performed. scRNA-seq from six OS patients and spatial transcriptomic profiling were further used to characterize the cellular distribution and communication of efferocytosis-related genes. The functions of MAGEA11 in OS were explored both in vivo and in vitro. Results: The Brown module showed the strongest association with efferocytosis pathways. The StepCox + Ridge model achieved robust prognostic performance and stratified patients into risk groups with significantly different survival. Enrichment analysis revealed upregulated genes related to endothelial and nitric oxide pathways, while downregulated genes were linked to immune signaling and extracellular matrix remodeling. High-risk patients exhibited elevated M2 macrophages, altered checkpoint expression, and greater predicted sensitivity to immunotherapy. At the single-cell level, efferocytosis activity was enriched in OS cells, with MAGEA11 showing the highest expression. High-risk tumors displayed stronger intercellular signaling, particularly from OS cells and CAFs to macrophages and endothelial cells. Spatial transcriptomics confirmed enrichment of efferocytosis at tumor and interface regions, correlating positively with stromal and myeloid cells and negatively with T cells. Mechanistically, MAGEA11 promoted OS tumor growth, and drove a pro-efferocytic microenvironment by enhancing Gas6 secretion, which polarized macrophages toward an M2 phenotype and upregulated their efferocytosis receptors (MERTK/AXL). Conclusions: We established an efferocytosis-related prognostic signature and elucidated its underlying mechanism wherein MAGEA11 promoted immunosuppression via a Gas6-MERTK/AXL-dependent efferocytosis circuit. This integrated study positions efferocytosis as a key driver of the OS microenvironment and a promising target for clinical intervention.

Indexed as

EfferocytosisImmune landscapeMachine learningMAGEA11Osteosarcoma

Identifiers

PMID41631009
PMCPMC12860682

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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 OpenQuestion graph.