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The hub ten gene-based risk score system using RNA m6A methylation regulator features and tumor immune microenvironment in breast cancer

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Abstract

Background

RNA N6-methyladenosine (m6A) modification is primarily regulated by m6A regulators, which play significant epigenetic regulatory roles in tumorigenesis, tumor development, and tumor immune microenvironment. However, the correlation between m6A regulators and immune cell infiltration in breast cancer remains unclear.

Methods

In this study, m6A modification patterns were evaluated based on 31 m6A modification regulators. m6A clusters were determined by consensus clustering. Immune landscape and immune cell infiltration subgroups were characterized by m6A clusters. Key module and hub genes related to m6A regulators and immune infiltration cells were identified by WGCNA. LASSO algorithm was applied to select prognostic signatures. Multivariate Cox regression analysis was applied to assess the prognostic value of gene signatures.

Results

Two distinct m6A clusters were determined based on the expression of 31 m6A modification regulators and characterized by two tumor immune microenvironment (TIME) immune cell infiltration subgroups. Further, a total of 1971 differentially expressed genes between breast cancer patients and healthy controls were screened, nine modules associated with clinical characteristics of breast cancer patients were identified. Later, one key module and 13 hub genes correlated with m6A regulators and immune infiltration cells were identified. LASSO Cox regression analysis selected and constructed a ten-gene prognostic model to build a risk score system for individual breast cancer patient prognosis. The performance of the ten-gene-based risk score system was further validated in an independent dataset with an AUC of 0.659.

Conclusions

This study revealed that m6A modification regulators played a significant role in the TIME regulation of breast cancer. The hub ten gene-based risk score system is valuable in predicting the prognosis of breast cancer patients, which may provide potential significance for breast cancer diagnosis, prognosis, and immunotherapy in the future.

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Availability of data and materials

The study utilized datasets from Gene Expression Omnibus (GEO) and are freely available to the public.

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Acknowledgements

We are grateful to Prof. Yan Wang for her useful suggestions in project design. This research was partially supported by the National Natural Science Foundation of China (41931291, 81672726, 81902960).

Funding

This work was supported by the National Natural Science Foundation of China (41931291, 81672726, 81902960), the Non-profit Central Research Institute Fund of Chinese Academy of Medical Sciences (2019PT310027), the State Key Laboratory of Molecular Oncology (SKLMO-2021–21, SKLMO-KF2021-21), and the Natural Science Foundation of Beijing (7204241).

Author information

Author notes

  1. Baowen Yuan and Wei Liu are co-first authors.

Authors and Affiliations

  1. Key Laboratory of Cancer and Microbiome, State Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China

    Baowen Yuan, Miaomiao Huo, Jingyao Zhang & Yunkai Yang

  2. Department of Biochemistry and Molecular Biology, Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), School of Basic Medical Sciences, Tianjin Medical University, Tianjin, 300070, China

    Wei Liu & Tianyang Gao

  3. Beijing Key Laboratory of Cancer Invasion and Metastasis Research, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Capital Medical University, Beijing, 100069, China

    Xin Yin, Tianshu Yang, Xu Teng, Wei Huang & Hefen Yu

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  1. Baowen Yuan
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Contributions

B.Y. and H.Y. conceived and designed this study. B.Y. performed the analysis and interpreted the data. B.Y. and W.L. wrote the manuscript. M.H., J.Z., Y.Y., T.G., X.Y., and T.Y. helped review the data and manuscript. H.Y., W.H., and X.T. supervised the study.

Corresponding authors

Correspondence to Xu Teng, Wei Huang or Hefen Yu.

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Yuan, B., Liu, W., Huo, M. et al. The hub ten gene-based risk score system using RNA m6A methylation regulator features and tumor immune microenvironment in breast cancer. Breast Cancer 29, 645–658 (2022). https://doi.org/10.1007/s12282-022-01341-5

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  • DOI: https://doi.org/10.1007/s12282-022-01341-5

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