A Tumor Suppressor Gene-Based Prognostic Classifier Predicts Prognosis, Tumor Immune Infiltration, and Small Molecule Compounds in Breast Cancer.

Journal: Frontiers in genetics
Published Date: Feb 3, 2022

Abstract

Tumor suppressor genes (TSGs) play critical roles in the cell cycle checkpoints and in modulating genomic stability. Here, we aimed to develop a TSG-based prognostic classifier for breast cancer. Gene expression profiles and clinical information of breast cancer were curated from TCGA (discovery set) and Gene Expression Omnibus (GEO) repository (GSE12093 and GSE17705 datasets as testing sets). Univariate cox regression analysis and random forest machine learning method were presented for screening characteristic TSGs. After multivariate cox regression analyses, a TSG-based prognostic classifier was constructed. The predictive efficacy was verified by C-index and receiver operating characteristic (ROC) curves. Meanwhile, the predictive independency was assessed through uni- and multivariate cox regression analyses and stratified analyses. Tumor immune infiltration was estimated ESTIMATE and CIBERSORT algorithms. Small molecule agents were predicted through CMap method. Molecular subtypes were clustered based on the top 100 TSGs with the most variance. A prognostic classifier including nine TSGs was established. High-risk patients were predictive of undesirable prognosis. C-index and ROC curves demonstrated its excellent predictive performance in prognosis. Also, this prognostic classifier was independent of conventional clinicopathological parameters. Low-risk patients exhibited increased infiltration levels of immune cells like T cells CD8. Totally, 48 small molecule compounds were predicted to potentially treat breast cancer. Five TSG-based molecular subtypes were finally constructed, with distinct prognosis and clinicopathological features. Collectively, this study provided a TSG-based prognostic classifier with the potential to predict clinical outcomes and immune infiltration in breast cancer and identified potential small molecule agents against breast cancer.

Authors

  • Suxiao Jiang
    Department of Surgery, Yinchuan Maternal and Child Health Hospital, Yinchuan, China.
  • Xiangjing Bu
    Department of Surgery, Yinchuan Maternal and Child Health Hospital, Yinchuan, China.
  • Desheng Tang
    Department of Surgery, The First Affiliated Hospital of Harbin Medical University, Heilongjiang, China.
  • Changsheng Yan
    Department of Surgery, The First Affiliated Hospital of Harbin Medical University, Heilongjiang, China.
  • Yan Huang
    Department of Neurology, University of Texas Health Science Center at Houston, Houston, TX.
  • Kun Fang
    Department of Surgery, Yinchuan Maternal and Child Health Hospital, Yinchuan, China.

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