Combined signature of N7-methylguanosine regulators with their related genes and the tumor microenvironment: a prognostic and therapeutic biomarker for breast cancer

N7-甲基鸟苷调节剂与其相关基因和肿瘤微环境的联合特征:乳腺癌的预后和治疗生物标志物

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作者:Tingjun Li, Zhishan Chen, Zhitang Wang, Jingyu Lu, Debo Chen

Background

Identifying predictive markers for breast cancer (BC) prognosis and immunotherapeutic responses remains challenging. Recent findings indicate that N7-methylguanosine (m7G) modification and the tumor microenvironment (TME) are critical for BC tumorigenesis and metastasis, suggesting that integrating m7G modifications and TME cell characteristics could improve the predictive accuracy for prognosis and immunotherapeutic responses.

Conclusions

The m7G-TME classifier offers a promising tool for predicting prognosis and immunotherapeutic responses in BC, which could support personalized therapeutic strategies.

Methods

We utilized bulk RNA-sequencing data from The Cancer Genome Atlas Breast Cancer Cohort and the GSE42568 and GSE146558 datasets to identify BC-specific m7G-modification regulators and associated genes. We used multiple m7G databases and RNA interference to validate the relationships between BC-specific m7G-modification regulators (METTL1 and WDR4) and related genes. Single-cell RNA-sequencing data from GSE176078 confirmed the association between m7G modifications and TME cells. We constructed an m7G-TME classifier, validated the

Results

Immunohistochemistry and RT-qPCR results indicated that METTL1 and WDR4 overexpression in BC correlated with poor patient prognosis. Moreover, single-cell analysis revealed relationships between m7G modification and TME cells, indicating their potential as indicators of BC prognosis and treatment responses. The m7G-TME classifier enabled patient subgrouping and revealed significantly better survival and treatment responses in the m7Glow+TMEhigh group. Significant differences in tumor biological functions and immunophenotypes occurred among the different subgroups. Conclusions: The m7G-TME classifier offers a promising tool for predicting prognosis and immunotherapeutic responses in BC, which could support personalized therapeutic strategies.

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