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J Cancer 2023; 14(15):2919-2930. doi:10.7150/jca.87079 This issue Cite

Research Paper

Characteristics of m⁶A-related LncRNAs in breast cancer as prognostic biomarkers and immunotherapy

Xinwei Han^1,2#, Yu Chen^1#, Jiaogui Xie¹, Yichao Wang^1✉

1. Tai Zhou Central Hospital (Taizhou University Hospital), No.999 Donghai Road, Jiaojiang District, Taizhou, Zhejiang, 318000, China.
2. Cytotherapy Laboratory, Shenzhen People's Hospital, 1017, Dongmen North Road, Luohu, Shenzhen, 518020, China.
# The authors contributed equally to the present manuscript.

✉ Corresponding author: Yichao Wang, Taizhou Central Hospital (Taizhou Univesity Hospital), No. 999 Donghai Road, Jiaojiang District, Taizhou, Zhejiang, 318000, China. E-mail: wangyichaobeicom.

Abstract

N6-methyladenosine (m⁶A) is a common RNA modification in coding and non-coding RNAs and plays an important role in the occurrence and development of breast cancer (BC). However, the role of m⁶A-related lncRNAs in breast cancer prognosis is unclear. This study aimed to help verify the biological function of m⁶A-related lncRNAs in breast cancer prognosis through bio-informatics techniques. First, we screened 18 m⁶A-related lncRNAs from the TCGA database: AL137847.1, AC137932.2, OTUD6B-AS1, MORF4L2-AS1, AC078846.1, AC012442.1, AL118556.1, AL138955.1, AC009754.1, AC024257.4, AL391095.1, AC024270.3, AC087392.1, LINC02649, AC090948.2, AL158212.1, ITGA6-AS1, AL133243.2 and constructed a risk-prognosis model based on this. Based on the model's median risk score, BC patients were divided into high-risk and low-risk groups. Then, the predictive value of the model was verified by Cox regression, Lasso regression, Kaplan-Meier curve and ROC curve analysis, and biological differences between the two groups were verified by GO enrichment analysis, tumor mutation burden, immune indications and in vitro tests. Importantly, the risk score of this prognostic model is an excellent independent prognostic factor, and m⁶A regulators are differentially expressed in patients with different risks. In addition, based on patients' different sensitivities to drugs, some drug candidates for different risk populations are screened to provide targets for breast cancer treatment. The difference in immune function between high-risk and low-risk patients also affected the sensitivity to immunotherapy. In the validation of clinical samples, we analyzed the expression of relevant lncRNAs in different risk groups and speculated the possible impact on the prognosis of breast cancer patients. The risk assessment tool built based on the full analysis of these m⁶A-related genes and m⁶A-related lncRNA libraries, as well as the m⁶A-related lncRNAs, has a high prognostic prediction ability, which may provide a supplementary screening method for accurately judging the prognosis of BC and a new perspective for personalized treatment of breast cancer patients.

Keywords: M⁶A, Breast cancer, LncRNA, Prognostic signature, Immune characteristic

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