Peiyuan Huang

ORCID: 0000-0003-1954-756X
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About
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Research Areas
  • Ferroptosis and cancer prognosis
  • RNA modifications and cancer
  • Cancer-related molecular mechanisms research
  • Renal Diseases and Glomerulopathies
  • Cancer-related gene regulation
  • Renal cell carcinoma treatment
  • Multiple and Secondary Primary Cancers
  • Peptidase Inhibition and Analysis
  • Epigenetics and DNA Methylation
  • Global Cancer Incidence and Screening
  • Breast Cancer Treatment Studies
  • Cancer Immunotherapy and Biomarkers

Gaozhou People's Hospital
2021-2025

Jiaying University
2020

Abnormal m6A methylation plays a significant role in cancer progression. Increasingly, researchers have focused on developing lncRNA signatures to evaluate the prognosis of patients. The specific function m6A-related lncRNAs bladder patients and immune microenvironment remains elusive. Herein, we performed comprehensive analysis prognostic values their association with using TCGA dataset. A total 9 were dramatically correlated overall survival outcomes cancer. Two molecular subtypes (cluster...

10.1155/2021/7488188 article EN Journal of Oncology 2021-07-24

Background: There is increasing evidence of the epigenetic regulation immune response in cancer. However, specific functions and mechanisms RNA N6-methyladenosine (m6A) modification cell infiltration hepatocellular carcinoma (HCC) tumor microenvironment (TME) unknown. Methods: We systematically analyzed m6A-modification patterns 371 HCC samples based on 23 m6A regulators, determined their correlation with TME cell-infiltrating characteristics. Principal-component analysis algorithms was used...

10.18632/aging.203456 article EN cc-by Aging 2021-08-30

Background A second primary malignant tumor is one of the most important factors affecting long-term survival young women with breast cancer (YWBC). As main treatments for YWBC patients, postoperative radiotherapy (PORT) may increase risk malignancy (SPM). Methods Machine learning components, including ridge regression, XGBoost, k-nearest neighbor, light gradient boosting machine, logistic support vector neural network, and random forest, were used to construct a predictive model identify...

10.1371/journal.pone.0316722 article EN cc-by PLoS ONE 2025-02-06
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