ArticleGenes & cancer2010
Identification of the YES1 Kinase as a Therapeutic Target in Basal-Like Breast Cancers.
Article in Genes & cancer, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
What it found
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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.
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Who cites it
17 citing papers in PubMed, 33 citations in OpenAlex.
- Computational Phosphosite-Specific Network Analysis of YES1 Y426 Reveals Cancer-Associated Phosphorylation Patterns.Proteomes · 2026Article
- Exploiting YES1-Driven EGFR Expression Improves the Efficacy of EGFR Inhibitors.Molecular cancer research : MCR · 2025Article
- Targeting YES1 Disrupts Mitotic Fidelity and Potentiates the Response to Taxanes in Triple-Negative Breast Cancer.Cancer research · 2024Article
- ACSL3 regulates breast cancer progressionCancer biology & medicine · 2024Article
- Emerging Roles of YES1 in Cancer: The Putative Target in Drug Resistance.International journal of molecular sciences · 2024Review
- A renaissance for YES in cancer.Oncogene · 2023Review
- CRISPR-Cas9-mediated gene therapy in lung cancer.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2023Review
- CRISPR/Cas9 application in cancer therapy: a pioneering genome editing tool.Cellular & molecular biology letters · 2022Review
- Effect of miR-140-5p on the regulation of proliferation and apoptosis in NSCLC and its underlying mechanism.Experimental and therapeutic medicine · 2019Article
- Article
- A statistical method for detecting differentially expressed SNVs based on next-generation RNA-seq data.Biometrics · 2017Article
- PIK3CA mutations are common in lobular carcinoma in situ, but are not a biomarker of progression.Breast cancer research : BCR · 2017Article
- Current Evidence and Future Perspectives on HuR and Breast Cancer Development, Prognosis, and Treatment.Neoplasia (New York, N.Y.) · 2016Review
- Transcriptome Profiling Reveals Disruption of Innate Immunity in Chronic Heavy Ethanol Consuming Female Rhesus Macaques.PloS one · 2016Article
- Article
- Lipid biology of breast cancer.Biochimica et biophysica acta · 2013Review
- Identification of potent Yes1 kinase inhibitors using a library screening approach.Bioorganic & medicinal chemistry letters · 2013Article
Corrections and comments
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Authors and funding
9 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Normal cellular behavior can be described as a complex, regulated network of interaction between genes and proteins. Targeted cancer therapies aim to neutralize specific proteins that are necessary for the cancer cell to remain viable in vivo. Ideally, the proteins targeted should be such that their downregulation has a major impact on the survival/fitness of the tumor cells and, at the same time, has a smaller effect on normal cells. It is difficult to use standard analysis methods on gene or protein expression levels to identify these targets because the level thresholds for tumorigenic behavior are different for different genes/proteins. We have developed a novel methodology to identify therapeutic targets by using a new paradigm called "gene centrality." The main idea is that, in addition to being overexpressed, good therapeutic targets should have a high degree of connectivity in the tumor network because one expects that suppression of its expression would affect many other genes. We propose a mathematical quantity called "centrality," which measures the degree of connectivity of genes in a network in which each edge is weighted by the expression level of the target gene. Using our method, we found that several SRC proto-oncogenes LYN, YES1, HCK, FYN, and LCK have high centrality in identifiable subsets of basal-like and HER2+ breast cancers. To experimentally validate the clinical value of this finding, we evaluated the effect of YES1 knockdown in basal-like breast cancer cell lines that overexpress this gene. We found that YES1 downregulation has a significant effect on the survival of these cell lines. Our results identify YES1 as a target for therapeutics in a subset of basal-like breast cancers.
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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.