Characterization of AKT Somatic Mutations in Chinese Breast Cancer Patients.
Ontology highlight
ABSTRACT: Purpose
This study aimed to investigate AKT gene mutation status in Chinese breast cancer patients.Methods
The study included 411 breast cancer patients hospitalized in Guangdong Provincial People's Hospital (GDPH) from June 1, 2017 to September 27, 2018. Mastectomy or breast conserving surgery was performed, and tissue samples were subjected to next-generation sequencing (NGS) to determine AKT gene mutation status. Meanwhile, the expression of human epidermal growth factor receptor 2 (Her2), progesterone receptor (PR), and estrogen receptor (ER) was analyzed by immunohistochemistry staining. The Cancer Genome Atlas (TCGA) database was used for comparative studies.Results
Patients in the GDPH cohort had an older age (P < 0.001), higher postmenopausal rate (P < 0.001), larger tumor size (P < 0.001), higher histologic type of infiltrating duct cancer (P < 0.001), higher metastatic rate (P < 0.001), higher expression of ER (P = 0.015) and HER2 (P < 0.001), and higher percentage of the HR/HER2 subtype (P < 0.001) than those in the TCGA cohort. The GDPH cohort displayed lower rates of overall AKT and AKT3 mutation (P < 0.001), but a higher AKT1 mutation rate (P < 0.0001) compared with the TCGA cohort. Notably, the NGS studies identified missense mutation and copy number amplification as the most common AKT variation type in the GDPH and TCGA cohorts, respectively. Specifically, E17K mutation in AKT1 was predominantly detected in GDPH cohort, while being absent in TCGA cohort. Moreover, in the GDPH cohort, AKT variation was correlated with a number of clinicopathological variables, including age over 50, HER2-, HR+/HER2-, and PR+.Conclusion
Patients in the GDPH cohort had lower rates of AKT and AKT3 mutation and higher AKT1 mutation rate than those in the TCGA cohort, while harboring missense mutations detected predominantly as E17K mutation in AKT1. In GDPH cohort, there were correlations between AKT mutation and the clinicopathological characteristics of patients.
SUBMITTER: Wen L
PROVIDER: S-EPMC8039050 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Phosphosite abundances are normalized (see Supplementary Methods, "Normalization").</li><li>Phosphoproteome raw files and datasets for PIK3CA- and TP53-mutant isogenic cell lines (TMT10-plex quantification; see Supplementary Methods)</li><li>Proteome Peptide Spectrum Match reports exported from Spectrum Mill for each of the 37 iTRAQ4 experiments, including the RefSeq FASTA file used for searches, and a Spectrum Mill quality metrics report</li></ul></p><p>Information on the complete TCGA Breast invasive carcinoma cohort (BRCA) can be found <a href="https://portal.gdc.cancer.gov/projects/TCGA-BRCA" target="_blank">here</a>.<br/>Genomic data for the 105 TCGA samples used in the CPTAC Proteome study can be downloaded from <a href="https://portal.gdc.cancer.gov/legacy-archive/search/f?filters=%7B%22op%22:%22and%22,%22content%22:%5B%7B%22op%22:%22in%22,%22content%22:%7B%22field%22:%22cases.project.program.name%22,%22value%22:%5B%22TCGA%22%5D%7D%7D,%7B%22op%22:%22in%22,%22content%22:%7B%22field%22:%22cases.project.project_id%22,%22value%22:%5B%22TCGA-BRCA%22%5D%7D%7D%5D%7D"target="_blank">here</a>.</p><ul><li>Dataset imported into MassIVE from <a href="https://cptac-data-portal.georgetown.edu/cptac/s/S029">https://cptac-data-portal.georgetown.edu/cptac/s/S029</a> on 08/28/19</li><li>Dataset source: <a href="https://pdc.esacinc.com/pdc/browse/filters/study_name:TCGA_Breast_Cancer_Proteome|TCGA_Breast_Cancer_Phosphoproteome" target="_blank">https://pdc.esacinc.com/pdc/browse/filters/study_name:...</a></li></ul>
2019-08-28 | MSV000084248 | MassIVE