ArticleFrontiers in genetics2022
Integrative Analysis of Biomarkers and Mechanisms in Adamantinomatous Craniopharyngioma.
Article in Frontiers in genetics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis 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
13 citing papers in PubMed, 1 synthesis or guideline pooled it, 19 citations in OpenAlex.
- The spectrum of radiation therapy options for craniopharyngioma: a systematic review.Journal of neuro-oncology · 2025Pooled it
- E2F7 targets S100A2 to suppress CD8Journal of molecular medicine (Berlin, Germany) · 2026Article
- Causal inference of inflammatory proteins in infertility: a Mendelian randomization study.Frontiers in endocrinology · 2025Article
- Article
- The clinical significance of inflammatory mediators in predicting obesity and progression-free survival in patients with adult-onset Craniopharyngioma.BMC cancer · 2024Article
- Proteomics study of primary and recurrent adamantinomatous craniopharyngiomas.Clinical proteomics · 2024Article
- Ferroptosis-related biomarkers for adamantinomatous craniopharyngioma treatment: conclusions from machine learning techniques.Frontiers in endocrinology · 2024Article
- Protein expression of S100A2 reveals it association with patient prognosis and immune infiltration profile in colorectal cancer.Journal of Cancer · 2023Article
- Identification of PANoptosis-relevant subgroups to evaluate the prognosis and immune landscape of patients with liver hepatocellular carcinoma.Frontiers in cell and developmental biology · 2023Article
- Pathological Diagnosis of Adult Craniopharyngioma on MR Images: An Automated End-to-End Approach Based on Deep Neural Networks Requiring No Manual Segmentation.Journal of clinical medicine · 2022Article
- Review
- Influence of S100A2 in Human Diseases.Diagnostics (Basel, Switzerland) · 2022Review
- Applications of machine learning in tumor-associated macrophages.Frontiers in immunology · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Craniopharyngioma is a benign tumor, and the predominant treatment methods are surgical resection and radiotherapy. However, both treatments may lead to complex complications, seriously affecting patients' survival rate and quality of life. Adamantinomatous craniopharyngioma (ACP), as one of the histological subtypes of craniopharyngioma, is associated with a high incidence and poor prognosis, and there is a gap in the targeted therapy of immune-related genes for ACP. In this study, two gene expression profiles of ACP, namely GSE68015 and GSE94349, were downloaded from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were identified by the Limma package, and 271 differentially expressed immune-related genes (DEIRGs) were obtained from the Immport database. The gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA) were performed for annotation, visualization, and integrated discovery. Five hub genes, including CXCL6, CXCL10, CXCL11, CXCL13, and SAA1, were screened out through protein-protein interaction (PPI) network interaction construction. Two diagnostic markers, namely S100A2 and SDC1 (both of which have the Area Under Curve value of 1), were screened by the machine learning algorithm. CIBERSORT analysis showed that M2 macrophages, activated NK cells, and gamma delta T cells had higher abundance in ACP infiltration, while CD8+ T cells, regulatory T cells, and Neutrophils had less abundance in ACP infiltration. The expression of gamma delta T cells was positively correlated with CXCL6, S100A2, SDC1, and SAA1, while CD8+ T cells expression was negatively correlated with CXCL6, S100A2, SDC1, and CXCL10. ACP with high CXCL6 showed remarkable drug sensitivity to Pentostatin and Wortmannin via CellMiner database analysis. Our results deepened the understanding of the molecular immune mechanism in ACP and provided potential biomarkers for the precisely targeted therapy for ACP.
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.