NCAPG Promotes Tumor Progression and Modulates Immune Cell Infiltration in Glioma.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35372056", "kind": "science-record", "revision": 5, "content_hash": "sha256:129adc536c13d0b0ebb3192f146a215619a672aeed77a2cb42a76cc964ed8489", "created_at": "2026-11-01T18:14:11Z", "updated_at": "2026-11-01T22:48:47Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "NCAPG Promotes Tumor Progression and Modulates Immune Cell Infiltration in Glioma.", "doi": "10.3389/fonc.2022.770628", "pmid": "35372056", "authors": ["Guangrong Zheng", "Tao Han", "Xiaomu Hu", "Zhou Yang", "Jin Wang", "Zhenyi Wen", "Hengyu Li", "Hongjin Wang"], "journal": "Frontiers in oncology", "year": 2022, "abstract": "Glioma is one of the most deadly types of brain cancer. As it is highly invasive, the prognosis for glioma patients remains dismal, with median survival rarely exceeding 16 months. Thus, developing a new prognostic biomarker for glioma and investigating its molecular mechanisms is necessary for the development of an efficient treatment strategy. In this study, we analyzed a cohort of 1,131 glioma patients using RNA-seq data from The Cancer Genome Atlas (TCGA project) and Gene Expression Omnibus (GSE4290 and GSE16011 datasets), and validated the results using the RNA-seq data of 1,018 gliomas from the Chinese Glioma Genome Atlas (CGGA project). We used the R language as the main tool for statistical analysis and data visualization. We found that NCAPG, a mitosis-associated chromosomal condensing protein, is highly expressed in glioma tissues. Furthermore, the expression of NCAPG increased significantly with the increase in tumor grade, and high NCAPG expression was found to be a predictor of poor overall survival in glioma patients (P < 0.001). This result shows that NCAPG expression could be an independent prognostic factor. Importantly, when the expression of NCAPG was knocked down, the CCK-8 assay revealed that the proliferation of glioma cells (LN-229 and T98G cell lines) decreased significantly compared with the control group. In addition, the healing rates of these cells were significantly lower in the si-NCAPG group than in the control group (P < 0.001). We then used the CIBERSORT algorithm to analyze the expression levels of 22 subpopulations of immune cells and found that NCAPG was significantly negatively correlated with natural killer cell activation. In addition, it was positively correlated with MHC-I molecules and ADAM17. Our study is first in comprehensively describing the high expression of NCAPG in glioma. It also shows that NCAPG can function as an independent prognostic predictor of glioma, and that targeting NCAPG can be a new strategy for the treatment of glioma patients.", "claims": [{"id": "claim-method", "statement": "The DEGs in GSE16011 and GSE4290 between glioma and normal specimens were identified using GEO2R online tools with the criteria |logFC| > 2 and adjusted P value < 0.05. For the TCGA glioma dataset, we used the limma package of R to analyze the differences between the tumor and normal tissues using the criteria |logFC| > 2 and adjusted P value < 0.05.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35372056", "locator": "sections[4] \"Data Processing of Differentially Expressed Genes (DEGs)\" paragraph 2", "quote": "The DEGs in GSE16011 and GSE4290 between glioma and normal specimens were identified using GEO2R online tools with the criteria |logFC| > 2 and adjusted P value < 0.05. For the TCGA glioma dataset, we used the limma package of R to analyze the differences between the tumor and normal tissues using the criteria |logFC| > 2 and adjusted P value < 0.05."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The original contributions presented in the study are included in the article/ Supplementary Material , further inquiries can be directed to the corresponding authors.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35372056", "locator": "sections[26] \"Data Availability Statement\" paragraph 2", "quote": "The original contributions presented in the study are included in the article/ Supplementary Material , further inquiries can be directed to the corresponding authors."}], "state": "complete"}, {"id": "claim-target-result", "statement": "A total of 297 DEGs were common to the three datasets, including 236 downregulated and 61 upregulated genes in glioma tissues compared with normal tissues.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:35372056", "locator": "sections[16] \"Identification of DEGs in Glioma\" paragraph 2", "quote": "We then used the Venn diagram software and identified a total of 297 DEGs that were common to the three datasets, including 236 downregulated (logFC < 2) and 61 upregulated genes (logFC > 2) in the glioma tissues compared with normal tissues ( Figure 1A )."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "A total of 297 DEGs were common to the three datasets, including 236 downregulated and 61 upregulated genes in glioma tissues compared with normal tissues.", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:35372056"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE16011"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "complete", "blocked_on": null, "description": "Apply the paper's statistical method to the resolved series and compare the result with the published target.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE16011"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:35372056", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fonc.2022.770628", "sha256": 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