ArticleBMC medical genomics2016
SFRP1 is a possible candidate for epigenetic therapy in non-small cell lung cancer.
Article in BMC medical genomics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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19 citing papers in PubMed, 41 citations in OpenAlex.
- Promoter hypermethylation of SFRP1 is an allele fraction-dependent prognostic biomarker in metastatic pancreatic ductal adenocarcinoma.Frontiers in oncology · 2025Article
- Integrated analysis of DNA methylome and transcriptome reveals SFRP1 and LIPG as potential drivers of ovarian cancer metastasis.Journal of gynecologic oncology · 2023Article
- Promoter hypermethylation of SFRP1 as a prognostic and potentially predictive blood-based biomarker in patients with localized pancreatic ductal adenocarcinoma.Frontiers in oncology · 2023Article
- Xprediction: Explainable EGFR-TKIs response prediction based on drug sensitivity specific gene networks.PloS one · 2022Article
- PCA-based unsupervised feature extraction for gene expression analysis of COVID-19 patients.Scientific reports · 2021Article
- Artificial Intelligence in Bulk and Single-Cell RNA-Sequencing Data to Foster Precision Oncology.International journal of molecular sciences · 2021Review
- Epigenetics ofCancers · 2020Review
- Prediction and Analysis of Skin Cancer Progression using Genomics Profiles of Patients.Scientific reports · 2019Article
- Association between SFRP promoter hypermethylation and different types of cancer: A systematic review and meta-analysis.Oncology letters · 2019Article
- Alteration in gene expression profiles of thymoma: Genetic differences and potential novel targets.Thoracic cancer · 2019Article
- Prognostic value of epigenomic profiling in lung cancer.Translational cancer research · 2019Article
- Drug candidate identification based on gene expression of treated cells using tensor decomposition-based unsupervised feature extraction for large-scale data.BMC bioinformatics · 2019Article
- Tensor Decomposition-Based Unsupervised Feature Extraction Applied to Single-Cell Gene Expression Analysis.Frontiers in genetics · 2019Article
- Article
- Tensor decomposition-based and principal-component-analysis-based unsupervised feature extraction applied to the gene expression and methylation profiles in the brains of social insects with multiple castes.BMC bioinformatics · 2018Article
- Tensor decomposition-based unsupervised feature extraction identifies candidate genes that induce post-traumatic stress disorder-mediated heart diseases.BMC medical genomics · 2017Article
- Identification of candidate drugs using tensor-decomposition-based unsupervised feature extraction in integrated analysis of gene expression between diseases and DrugMatrix datasets.Scientific reports · 2017Article
- Principal Components Analysis Based Unsupervised Feature Extraction Applied to Gene Expression Analysis of Blood from Dengue Haemorrhagic Fever Patients.Scientific reports · 2017Article
- Tensor decomposition-based unsupervised feature extraction applied to matrix products for multi-view data processing.PloS one · 2017Article
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundNon-small cell lung cancer (NSCLC) remains a lethal disease despite many proposed treatments. Recent studies have indicated that epigenetic therapy, which targets epigenetic effects, might be a new therapeutic methodology for NSCLC. However, it is not clear which objects (e.g., genes) this treatment specifically targets. Secreted frizzled-related proteins (SFRPs) are promising candidates for epigenetic therapy in many cancers, but there have been no reports of SFRPs targeted by epigenetic therapy for NSCLC.
methodsThis study performed a meta-analysis of reprogrammed NSCLC cell lines instead of the direct examination of epigenetic therapy treatment to identify epigenetic therapy targets. In addition, mRNA expression/promoter methylation profiles were processed by recently proposed principal component analysis based unsupervised feature extraction and categorical regression analysis based feature extraction.
resultsThe Wnt/β-catenin signalling pathway was extensively enriched among 32 genes identified by feature extraction. Among the genes identified, SFRP1 was specifically indicated to target β-catenin, and thus might be targeted by epigenetic therapy in NSCLC cell lines. A histone deacetylase inhibitor might reactivate SFRP1 based upon the re-analysis of a public domain data set. Numerical computation validated the binding of SFRP1 to WNT1 to suppress Wnt signalling pathway activation in NSCLC.
conclusionsThe meta-analysis of reprogrammed NSCLC cell lines identified SFRP1 as a promising target of epigenetic therapy for NSCLC.
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