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Construction of a prognostic risk assessment model for HER2 + breast cancer based on autophagy-related genes

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Abstract

Although breast cancer (BC) has a low mortality rate relative to other cancers, it prominently affects the survival of patients with human epidermal growth factor receptor-2 (HER2 +) BC due to its high recurrence rate. By far, it has been found that autophagy can affect various tumor occurrence and development, as well as patients’ prognosis. HER2 + BC patient samples and autophagy-related genes (ARGs) were acquired from a public database, least absolute shrinkage and selection operator (LASSO) and Cox analyses (including univariate and multivariate analyses) were utilized to construct a 9-ARGs model, which was verified by using HER2 + BC patient samples in The Cancer Genome Atlas (TCGA) dataset. Sample risk score was worked out based on characteristic genes, and prominent differences in overall survival were tracked down between high- and low-risk groups. Predictive ability of the model was validated by drawing receiver operating characteristic (ROC) curves and then calculating the area under the curves (AUC) value. Results showed good accuracy and prediction ability of the model in both validation set and training set. For the purpose of facilitating model application in clinical practice, we constructed a nomogram combing clinical factors and risk scores to evaluate 1-year, 3-year and 5-year survival of HER2 + BC patients. In addition, we assessed the correlation of risk score with tumor mutational burden and tumor immune infiltration. Results exhibited that in a high-risk group, tumor mutation was relatively high, while tumor immune infiltration was relatively poor. Overall, based on ARGs, the prognostic signature in this study can tellingly evaluate prognoses of HER2 + BC patients and provide a reference for clinicians.

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Data sharing is not applicable to this article as no datasets were generated or analysed during the current study.

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Funding

This study was funded by the Public welfare project of Jinhua Science and Technology Plan, (2021–4-045).

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Authors and Affiliations

  1. Department of Breast and Thyroid Surgery, Jinhua Municipal Central Hospital, 365 East Renmin Road, Jinhua City, 321000, Zhejiang Province, China

    Fan Wang, Linghui Fang & Bifei Fu

  2. Department of Breast and Thyroid Surgery, Jinhua Maternal and Child Health Care Hosptital, Jinhua City, 321000, Zhejiang Province, China

    Chen Fan

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  1. Fan Wang
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Contributions

Conceptualization: FW. Data curation: FW. Formal analysis: LF. Methodology: LF. Software: BF. Validation: BF. Investigation: CF. Writing—original draft: FW. Writing—review & editing: LF.

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Correspondence to Fan Wang.

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Author Fan Wang declares that he/she has no conflict of interest. Author Linghui Fang declares that he/she has no conflict of interest. Author Bifei Fu declares that he/she has no conflict of interest. Author Chen Fan declares that he/she has no conflict of interest.

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Wang, F., Fang, L., Fu, B. et al. Construction of a prognostic risk assessment model for HER2 + breast cancer based on autophagy-related genes. Breast Cancer 30, 478–488 (2023). https://doi.org/10.1007/s12282-023-01440-x

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  • DOI: https://doi.org/10.1007/s12282-023-01440-x

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