Evidence map›Paper›PMID 42298489›Full record

ArticleBMC cancer2026

Identification and validation of programmed cell death-related genes in osteosarcoma: inhibiting CIB1 as a promising therapeutic strategy.

Bin Hu, Li Du, Changchun Lu, Dingding Huang, Mingmang Pan, Feng Xue, Yuchun Shen, Liang Ding, Nuo Yin

Abstract read
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Article in BMC cancer, 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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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

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Bin Hu *Department of Orthopedics, Jinzhou Medical University Postgraduate Education Base, The Third People's Hospital of Sichuan Province, Chengdu, 610100, China.
Li Du *Department of Orthopaedics, Shanghai Jiao Tong University Affiliated Sixth People's Hospital South Campus, Shanghai, 201400, China.
Changchun Lu *Department of Orthopaedics, Shanghai Jiao Tong University Affiliated Sixth People's Hospital South Campus, Shanghai, 201400, China.
Dingding Huang *Department of Anesthesiology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital South Campus, Shanghai, 201400, China.
Mingmang PanDepartment of Orthopaedics, Shanghai Jiao Tong University Affiliated Sixth People's Hospital South Campus, Shanghai, 201400, China.
Feng XueDepartment of Orthopaedics, Shanghai Jiao Tong University Affiliated Sixth People's Hospital South Campus, Shanghai, 201400, China.
Yuchun ShenDepartment of Orthopaedics, Shanghai Jiao Tong University Affiliated Sixth People's Hospital South Campus, Shanghai, 201400, China.
Liang DingDepartment of Orthopedics, Ningbo Branch of Renji Hospital, Shanghai Jiao Tong University School of Medicine, Ningbo, 315336, China. dl1900@sina.com.
Nuo YinDepartment of Orthopaedics, Shanghai Jiao Tong University Affiliated Sixth People's Hospital South Campus, Shanghai, 201400, China. yn0102067@126.com.

Funding

Shanghai Fengxian District Science and Technology Commission Project 20221102
6 · The paper itself

Abstract

backgroundThis study explores programmed cell death (PCD)-related genes in osteosarcoma through bioinformatics and experimental validation.

methodsAnalysis of datasets from the GEO and TCGA databases identified 5,327 differentially expressed genes (DEGs), among which 294 overlapped with PCD-related genes.

resultsLASSO regression analysis identified six hub genes, and five of these (CIB1, CREB3L1, IL6R, TGFβ2, and TNFRSF10C) were further validated in osteosarcoma tissues. Notably, CIB1 exhibited significantly elevated expression and was selected for in-depth analysis. CIB1 downregulation inhibited osteosarcoma cell proliferation and invasion by inducing apoptosis and causing G2/M phase cell cycle arrest, and was associated with increased p53 expression, decreased phosphorylation of Akt and STAT3, and altered BCL2/BAX ratios, suggesting involvement of these pathways in the observed effects.

conclusionsIn vitro experiments confirmed the tumor-suppressive role of CIB1 inhibition. These findings highlight CIB1 as a promising therapeutic target for osteosarcoma treatment.

Indexed as

Bone NeoplasmsCalcium-Binding ProteinsOsteosarcomaApoptosisBiomarkers, TumorCell Line, TumorCell ProliferationCyclic AMP Response Element-Binding ProteinGene Expression ProfilingGene Expression Regulation, NeoplasticHumansNerve Tissue ProteinsBiomarkers, TumorCalcium-Binding ProteinsCIB1 protein, humanCREB3L1 protein, humanCyclic AMP Response Element-Binding ProteinNerve Tissue ProteinsCIB1OsteosarcomaPredictive biomarkerPrognosisProgrammed cell death

Identifiers

PMID42298489
PMCPMC13495217

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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.