ArticleOncotarget2016
A network-based method for identifying prognostic gene modules in lung squamous carcinoma.
Article in Oncotarget, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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
9 citing papers in PubMed.
- The bioinformatics analysis of RIOX2 gene in lung adenocarcinoma and squamous cell carcinoma.PloS one · 2021Article
- Identification of Novel Biomarkers Related to Lung Squamous Cell Carcinoma Using Integrated Bioinformatics Analysis.Computational and mathematical methods in medicine · 2021Article
- Integrative analyses of noncoding RNAs reveal the potential mechanisms augmenting tumor malignancy in lung adenocarcinoma.Nucleic acids research · 2020Article
- Villi development core-related gene expression associated with lung squamous cancer prognosis.Medicine · 2019Article
- Expression Differentiation Is Not Helpful in Identifying Prognostic Genes Based on TCGA Datasets.Molecular therapy. Nucleic acids · 2018Article
- The Hierarchical Modular Structure of HER2+ Breast Cancer Network.Frontiers in physiology · 2018Article
- Network-Wide Screen Identifies Variation of Novel Precise On-Module Targets Using Conformational Modudaoism.CPT: pharmacometrics & systems pharmacology · 2018Article
- A Computational Method of Defining Potential Biomarkers based on Differential Sub-Networks.Scientific reports · 2017Article
- Identification of prognostic genes through expression differentiation during metastatic process in lung adenocarcinoma.Scientific reports · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Similarities in gene expression between both developing embryonic and precancerous tissues and cancer tissues may help identify much-needed biomarkers and therapeutic targets in lung squamous carcinoma. In this study, human lung samples representing ten successive time points, from embryonic development to carcinogenesis, were used to construct global gene expression profiles. Differentially expressed genes with similar expression in precancerous and cancer samples were identified. Using a network-based greedy searching algorithm to analyze the training cohort (n = 69) and three independent testing cohorts, we successfully identified a significant 22-gene module in which expression levels were correlated with overall survival in lung squamous carcinoma patients.
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.