SynthesisBMC medical genetics2014
Meta-analysis of differentially expressed genes in osteosarcoma based on gene expression data.
Synthesis in BMC medical genetics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers, 11 of them syntheses that pooled 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.
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.
Who cites it
41 citing papers in PubMed, 11 syntheses or guidelines pooled it.
- In vitro model of predicting metastatic ability using tumor derived extracellular vesicles; beyond seed soil hypothesis.Scientific reports · 2022Pooled it
- Revealing the link between macrophage in microenvironment of osteosarcoma and poor prognosis by utilizing the Integrated analysis.Journal of musculoskeletal & neuronal interactions · 2021Pooled it
- Identification of drought stress-responsive genes in rice (Journal of genetics · 2020Pooled it
- Identification of key genes in osteosarcoma by meta‑analysis of gene expression microarray.Molecular medicine reports · 2019Pooled it
- Expression of the ZIP/SLC39A transporters in β-cells: a systematic review and integration of multiple datasets.BMC genomics · 2017Pooled it
- Integrated Analysis of Expression Profile Based on Differentially Expressed Genes in Middle Cerebral Artery Occlusion Animal Models.International journal of molecular sciences · 2016Pooled it
- Identification of Polycystic Ovary Syndrome (PCOS) Specific Genes in Cumulus and Mural Granulosa Cells.PloS one · 2016Pooled it
- Network-Based Meta-Analyses of Associations of Multiple Gene Expression Profiles with Bone Mineral Density Variations in Women.PloS one · 2016Pooled it
- Meta-Analyses of Microarray Datasets Identifies ANO1 and FADD as Prognostic Markers of Head and Neck Cancer.PloS one · 2016Pooled it
- Pooled it
- Pooled it
- Comparison of Differentially Expressed Genes in Human and Canine Osteosarcoma.Life (Basel, Switzerland) · 2025Article
- PTBP2 promotes cell survival and autophagy in chronic myeloid leukemia by stabilizing BNIP3.Cell death & disease · 2025Article
- A Pan-Cancer Analysis of Natriuretic Peptide Receptor 3 (NPR3) with Clinical Cohort and in vitro Validation.Journal of inflammation research · 2025Article
- Targeting the mitochondrial protein YME1L to inhibit osteosarcoma cell growth in vitro and in vivo.Cell death & disease · 2024Article
- The whole transcriptome analysis using FFPE and fresh tissue samples identifies the molecular fingerprint of osteosarcoma.Experimental biology and medicine (Maywood, N.J.) · 2024Article
- Identification of FXYD6 as the novel biomarker for glioma based on differential expression and DNA methylation.Cancer medicine · 2023Article
- Carboxypeptidase E is a prognostic biomarker co-expressed with osteoblastic genes in osteosarcoma.PeerJ · 2023Article
- ADCK1 is a potential therapeutic target of osteosarcoma.Cell death & disease · 2022Article
- Identity of MMP1 and its effects on tumor progression in head and neck squamous cell carcinoma.Cancer medicine · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundTo uncover the genes involved in the development of osteosarcoma (OS), we performed a meta-analysis of OS microarray data to identify differentially expressed genes (DEGs) and biological functions associated with gene expression changes between OS and normal control (NC) tissues.
methodsWe used publicly available GEO datasets of OS to perform a meta-analysis. We performed Gene Ontology (GO) enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and Protein-Protein interaction (PPI) networks analysis.
resultsEight GEO datasets, including 240 samples of OS and 35 samples of controls, were available for the meta-analysis. We identified 979 DEGs across the studies between OS and NC tissues (472 up-regulated and 507 down-regulated). We found GO terms for molecular functions significantly enriched in protein binding (GO: 0005515, P = 3.83E-60) and calcium ion binding (GO: 0005509, P = 3.79E-13), while for biological processes, the enriched GO terms were cell adhesion (GO:0007155, P = 2.26E-19) and negative regulation of apoptotic process (GO: 0043066, P = 3.24E-15), and for cellular component, the enriched GO terms were cytoplasm (GO: 0005737, P = 9.18E-63) and extracellular region (GO: 0005576, P = 2.28E-47). The most significant pathway in our KEGG analysis was Focal adhesion (P = 5.70E-15). Furthermore, ECM-receptor interaction (P = 1.27E-13) and Cell cycle (P = 4.53E-11) are found to be highly enriched. PPI network analysis indicated that the significant hub proteins containing PTBP2 (Degree = 33), RGS4 (Degree = 15) and FXYD6 (Degree = 13).
conclusionsOur meta-analysis detected DEGs and biological functions associated with gene expression changes between OS and NC tissues, guiding further identification and treatment for OS.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.