ArticlePloS one2017
Identification of genes and critical control proteins associated with inflammatory breast cancer using network controllability.
Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 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
11 citing papers in PubMed, 17 citations in OpenAlex.
- Controllability Analysis of Intercellular Protein-Protein Interaction Networks.Computational and structural biotechnology journal · 2026Article
- A practically efficient algorithm for identifying critical control proteins in directed probabilistic biological networks.NPJ systems biology and applications · 2024Article
- Measuring criticality in control of complex biological networks.NPJ systems biology and applications · 2024Article
- Domination based classification algorithms for the controllability analysis of biological interaction networks.Scientific reports · 2022Article
- CASP9 As a Prognostic Biomarker and Promising Drug Target Plays a Pivotal Role in Inflammatory Breast Cancer.International journal of analytical chemistry · 2022Article
- Pharmacologically controlling protein-protein interactions through epichaperomes for therapeutic vulnerability in cancer.Communications biology · 2021Article
- Constraint-based models for dominating protein interaction networks.IET systems biology · 2021Article
- Highly connected, non-redundant microRNA functional control in breast cancer molecular subtypes.Interface focus · 2021Article
- Control Analysis of Protein-Protein Interaction Network Reveals Potential Regulatory Targets for MYCN.Frontiers in oncology · 2021Article
- Integration of metabolomic and transcriptomic data reveals metabolic pathway alteration in breast cancer and impact of related signature on survival.Journal of cellular physiology · 2019Article
- The Hidden Control Architecture of Complex Brain Networks.iScience · 2019Article
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
One of the most aggressive forms of breast cancer is inflammatory breast cancer (IBC), whose lack of tumour mass also makes a prompt diagnosis difficult. Moreover, genomic differences between common breast cancers and IBC have not been completely assessed, thus substantially limiting the identification of biomarkers unique to IBC. Here, we developed a novel statistical analysis of gene expression profiles corresponding to microdissected IBC, non-IBC (nIBC) and normal samples that enabled us to identify a set of genes significantly associated with a specific disease state. Second, by using advanced methods based on controllability network theory, we identified a set of critical control proteins that uniquely and structurally control the entire proteome. By mapping high change variance genes in protein interaction networks, we found that a large statistically significant fraction of genes whose variance changed significantly between normal and IBC and nIBC disease states were among the set of critical control proteins. Moreover, this analysis identified the overlapping genes with the highest statistical significance; these genes may assist in developing future biomarkers and determining drug targets to disrupt the molecular pathways driving carcinogenesis in IBC.
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.