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A seven-nuclear receptor-based prognostic signature in breast cancer

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Abstract

Background

Breast cancer (BRCA) is a malignant cancer that threatened the life of female with unsatisfactory prognosis. The aim of this study was to identify prognostic nuclear receptors (NRs) signature of BRCA.

Methods

BRCA patient samples were collected from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. Consensus clustering analysis, univariate Cox regression analysis and the least absolute shrinkage and selection operator (LASSO) Cox regression analysis were performed to evaluate, select NRs as prognostic factors and build Risk Score model. GSEA analysis was explored to check signaling differences between High- and Low-Risk group. Nomogram model basing on age and Risk Score was established to predict the 1-, 3- and 5-year survival. Model performance was assessed by a time-dependent receiver operating characteristic (ROC) curve and calibration plot. CIBERSORT, ESTIMATE and TIMER algorithm were introduced to evaluate the immune landscape.

Results

NR3C1, NR4A3, THRA, RXRG, NR2F6, NR1D2 and RORB were optimized as a prognostic signature for BRCA. This seven-NR-based Risk Score could effectively predict overall survival status. The area under the curve (AUC) of 1-, 3- and 5-year overall survival are 0.702, 0.734 and 0.722 in TCGA training cohort, and 0.630, 0.721 and 0.823 in GEO validation cohort, respectively. Calibration plot demonstrated satisfactory agreement between predictive and observed outcomes. Nomogram model worked well on predicting survival probabilities. Multiple cancer-related pathways were highly enriched in High-Risk group. High- and Low-Risk groups showed significant differed immune cell infiltration. There exists an obvious connection between Risk Score and immune checkpoints LAG3, PD1 and TIM3.

Conclusion

The seven-NR-based Risk Score represents a promising signature for estimating overall survival in patients with BRCA, and is correlated with the immune microenvironment.

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Authors and Affiliations

  1. Ambuiatory Surgery Treatment Department, Cangzhou Central Hospital, Cangzhou, 061001, Hebei Province, China

    F. Wu

  2. Department of Diagnostic Imaging, Affiliated Hospital of North China University of Science and Technology, Tangshan, 063000, Hebei, China

    W. Chen

  3. Ultrasound Department II, Cangzhou Central Hospital, Cangzhou, 061001, Hebei Province, China

    X. Kang

  4. Department of Thyroid and Mammary Gland III, Cangzhou Central Hospital, No. 16 Xinhua West Road, Yunhe District, Cangzhou, 061001, Hebei Province, China

    L. Jin, J. Bai, H. Zhang & X. Zhang

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12094_2020_2517_MOESM1_ESM.tif

Figure S1 GSEA analysis identified KEGG signaling pathways enriched between High- and Low- Risk group. The ECM-reporter interaction (A), glycolysis gluconeogenesis (B), pathways in cancer (C), regulation of actin cytoskeleton (D) and Wnt signaling pathway (E) were upregulated in High-Risk group compared with the Low-Risk group. The Oxidative phosphorylation (F) and proteasome pathway (G) were suppressed (TIF 11851 KB)

12094_2020_2517_MOESM2_ESM.tif

Figure S2 TIMER analysis determined infiltration of immune cells. The infiltration levels of Macrophage (A), CD4 T cells (B) and CD8 cells (C) in TCGA patient samples (TIF 12628 KB)

12094_2020_2517_MOESM3_ESM.tif

Figure S3 ESTIMATE analysis evaluated the immune score. ESTIMATE algorithm was conducted using “estimate” R package to evaluate the ESTIMATE score (A), immune score (B), stromal score (C) and tumor purity (D) of High- and Low-Risk group (TIF 13026 KB)

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Wu, F., Chen, W., Kang, X. et al. A seven-nuclear receptor-based prognostic signature in breast cancer. Clin Transl Oncol 23, 1292–1303 (2021). https://doi.org/10.1007/s12094-020-02517-1

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  • DOI: https://doi.org/10.1007/s12094-020-02517-1

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