ArticleOncotarget2017
Genes with mutation significance were highly associated with the clinical pattern of patients with breast cancer.
Article in Oncotarget, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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
2 citing papers in PubMed, 3 citations in OpenAlex.
- PIK3CA Gene Mutations in Solid Malignancies: Association with Clinicopathological Parameters and Prognosis.Cancers · 2019Review
- TP53 Polymorphism Contributes to the Susceptibility to Bipolar Disorder but Not to Schizophrenia in the Chinese Han Population.Journal of molecular neuroscience : MN · 2019Article
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In the United States, breast cancer is the second leading cause of cancer death in women. Over the past 20 years, breast cancer incidence and mortality rates increased rapidly in developing regions. We aimed to identify the gene mutation patterns that associated with the clinical patterns, including survival status, histo-pathological classes and so forth, of breast cancer. We retrieved 1098 cases of the clinical information, and level-3 legacy data of mRNA expression level, protein expression data and mutation files from GDC data portal. The genes with mutation significance were obtained. We studied the impacts of mutation types on the expression levels of mRNA and protein. Different statistics methods were used to calculate the correlation between the mutation types and the expression data or histo-clinical measures. There were 24 genes with mutation significance identified. The most mutated genes were selected to study the role of specific mutations played on the patients with breast cancer. One interesting finding was the missense mutations on TP53 were related with high expression levels of mRNA and protein. The missense mutations on TP53 were highly related with the morphology, race, ER status, PR status and HER2 Status, while the truncated mutations were only related with the morphology, ER status and PR status. The missense mutation on PIK3CA was highly associated with the morphology, race, ER status and PR status. The mutants with different mutants and the wild type of the most mutated genes had different impacts on the histo-clinical measures that might help personalized therapy.
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Registered trials
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