ArticleOncoTargets and therapy2016
Biomarker discovery to improve prediction of breast cancer survival: using gene expression profiling, meta-analysis, and tissue validation.
Article in OncoTargets and therapy, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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
23 citing papers in PubMed, 37 citations in OpenAlex.
- Exploration of crucial stromal risk genes associated with prognostic significance and chemotherapeutic opportunities in invasive ductal breast carcinoma.Journal, genetic engineering & biotechnology · 2025Article
- The Expression of the Claudin Family of Proteins in Colorectal Cancer.Biomolecules · 2024Review
- Expression patterns of claudins in cancer.Heliyon · 2023Review
- Subtype-specific network organization of molecular complexes in breast cancer.Journal of biosciences · 2023Article
- Identification of a six-gene signature to predict survival and immunotherapy effectiveness of gastric cancer.Frontiers in oncology · 2023Article
- Identification by Bioinformatics Analysis of Potential Key Genes Related to the Progression and Prognosis of Gastric Cancer.Frontiers in oncology · 2022Article
- Long non-coding RNA H19 mediates N-acetyltransferase 1 gene methylation in the development of tamoxifen resistance in breast cancer.Experimental and therapeutic medicine · 2022Article
- Relationship of the Levels of microRNA Gene Methylation with the Level of Their Expression and Pathomorphological Characteristics of Breast Cancer.Bulletin of experimental biology and medicine · 2021Article
- Personalization in Modern Radiation Oncology: Methods, Results and Pitfalls. Personalized Interventions and Breast Cancer.Frontiers in oncology · 2021Review
- Identification of a nine-gene prognostic signature for gastric carcinoma using integrated bioinformatics analyses.World journal of gastrointestinal oncology · 2020Article
- MAM domain containing 2 is a potential breast cancer biomarker that exhibits tumour-suppressive activity.Cell proliferation · 2020Article
- Constructing cancer patient-specific and group-specific gene networks with multi-omics data.BMC medical genomics · 2020Article
- Pancreatic neuroendocrine tumors: Therapeutic challenges and research limitations.World journal of gastroenterology · 2020Review
- Improved survival analysis by learning shared genomic information from pan-cancer data.Bioinformatics (Oxford, England) · 2020Article
- Causal network perturbations for instance-specific analysis of single cell and disease samples.Bioinformatics (Oxford, England) · 2020Article
- Identifying Biomarkers to Predict the Progression and Prognosis of Breast Cancer by Weighted Gene Co-expression Network Analysis.Frontiers in genetics · 2020Article
- Identification of aberrant gene expression during breast ductal carcinomaThe Journal of international medical research · 2020Article
- Microarray analysis and functional characterization revealed NEDD4-mediated cardiomyocyte autophagy induced by angiotensin II.Cell stress & chaperones · 2019Article
- A novel and reliable computational intelligence system for breast cancer detection.Medical & biological engineering & computing · 2018Article
- Identification of the potential crucial genes in invasive ductal carcinoma using bioinformatics analysis.Oncotarget · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeBreast cancer is the leading cause of cancer death worldwide in women. The molecular mechanism for human breast cancer is unknown. Gene microarray has been widely used in breast cancer research to identify clinically relevant molecular subtypes as well as to predict prognosis survival. So far, the valuable multigene signatures in clinical practice are unclear, and the biological importance of individual genes is difficult to detect, as the described signatures virtually do not overlap. Early prognosis of this disease, breast invasive ductal carcinoma (IDC) and breast ductal carcinoma in situ (DCIS), is vital in breast surgery.
methodsThus, this study reports gene expression profiling in large breast cancer cohorts from Gene Expression Omnibus, including GSE29044 (N=138) and GSE10780 (N=185) test series and four independent validation series GSE21653 (N=266), GSE20685 (N=327), GSE26971 (N=276), and GSE12776 (N=204). Significantly differentially expressed genes in human breast IDC and breast DCIS were detected by transcriptome microarray analysis.
resultsWe created a set of three genes (
conclusionUsing novel gene expression profiling together with a meta-analysis validation approach, we have identified a three-gene signature with independent prognostic impact. Furthermore,
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.