Endosulfan triggers epithelial-mesenchymal transition via PTP4A3-mediated TGF-β signaling pathway in prostate cancer cells

Wang, Yue; Guo, Yubing; Hu, Yumeng; Sun, Yuhan; Xu, Dan

doi:10.1016/j.scitotenv.2020.139234

Cited by 15 publications

(1 citation statement)

References 48 publications

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“…Bioinformatics, which conducts in-depth research on diseases based on public databases, has also become an important means of analyzing data [6,7]. In prostate cancer, the focus of screening high-throughput data is mainly limited to screening individual biomarkers [8,9]. With the deepening of research, diagnosis based on a single biomarker can no longer meet actual needs.…”

Section: Introductionmentioning

confidence: 99%

Improved T staging diagnosis and outcome prediction of prostate cancer using genomic LASSO model

Lei

zhang

Chen

et al. 2023

Preprint

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As one of the most diagnosed malignancies in men, prostate cancer has exhibited a high incidence rate in recent years. According to the NCCN guidelines, TNM staging of prostate cancer is an important basis for the best treatment modality. Here in this study, we established two model systems for PCa's T staging diagnosis and disease-free prediction for the first time, based on the combined analysis of WGCNA, univariate COX, and LASSO regression. Models for T staging and disease-free exhibited a high accuracy of 81.3% and 77.5% in the validation cohort, respectively. In addition, a significant negative correlation between gene expression and DNA methylation was observed in these models, which may provide new insight for further studies. Overall, our research can assist clinical diagnosis, predict the disease-free survival of patients, guide the choice of treatment options, and provide new ideas for the studies of prostate cancer.

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Section: Introductionmentioning

confidence: 99%