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. 2024;20(37):2993-3008.
doi: 10.1080/14796694.2024.2405459. Epub 2024 Sep 30.

Comprehensive analysis of RNA-5-methylcytosine modification in breast cancer brain metastasis

Affiliations

Comprehensive analysis of RNA-5-methylcytosine modification in breast cancer brain metastasis

Peiying Cai et al. Future Oncol. 2024.

Abstract

Aim: To delineate the RNA-5-methylcytosine (m5C) modification of breast cancer brain metastasis (BCBM).Methods: Methylated RNA immunoprecipitation next-generation sequencing (MeRIP-seq) was performed to obtain RNA-m5C patterns of BCBM.Results: 1048 hypermethylation and 1866 hypomethylation m5C peaks were identified in BCBM compared with those in breast cancer. The most significant m5C hypermethylated genes included ENG, SHANK1, IGFN1, EVL and MMP9, whereas the most significant m5C hypomethylated genes included AREG, SAA2, TP53I11, KRT7 and LCN2. MeRIP-qPCR data were concordant with the corresponding MeRIP-seq results in terms of the observed m5C levels. Conjoint analysis identified 190 hyper-up genes characterized by concurrent m5C hypermethylation and up-regulation, alongside 284 hypo-down genes exhibiting both m5C hypomethylation and down-regulation.Conclusion: This study presents the first comprehensive analysis of RNA-m5C modification in BCBM.

Keywords: 5-methylcytosine (m5C); breast cancer brain metastasis; methylated RNA immunoprecipitation sequencing (MeRIP-seq); molecular mechanism.

Plain language summary

[Box: see text].

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Conflict of interest statement

The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

Figures

Figure 1.
Figure 1.
The characteristics and distributions of m5C RNA methylation peaks in the BC and BCBM groups. (A-B) Venn diagram of m5C methylation peaks (A) and annotated gene read counts (B) in the BC and BCBM groups. (C-D) Distributions of m5C methylation peaks in the BC (C) and BCBM (D) groups. (E-F) Proportion of m5C occurred at different regions in the BC (E) and BCBM (F) groups. The m5C methylation of mRNAs in both the BC and BCBM groups occurred mainly in CDS.
Figure 2.
Figure 2.
Validation of m5C RNA methylation level of the candidate genes. (A–D) Relative m5C RNA methylation level of IGFN1, EVL, AREG and KRT7 in the BCBM group versus the BC group by MeRIP-qPCR. n = 3. (E) Comparison of the mean fold changes (log10 transformed) between MeRIP-qPCR and MeRIP-seq. (F) Correlation analysis of the mean fold changes (log10 transformed) between MeRIP-qPCR results and MeRIP-seq data regarding the relative m5C RNA methylation levels.
Figure 3.
Figure 3.
Functional enrichment analysis of the m5C hypermethylated mRNAs in the BCBM group versus the BC group. (A–C) GO analysis of the m5C hypermethylated mRNAs. (D) KEGG pathway analysis of the m5C hypermethylated mRNAs. BP: Biological process; CC: Cellular component; MF: Molecular function.
Figure 4.
Figure 4.
Differentially expressed transcript variants of the input samples in the BCBM group versus the BC group by RNA-seq. (A) Volcano plot of the differentially expressed transcript variants in the BCBM group versus the BC group. A total of 1,085 up-regulated and 1,288 down-regulated transcript variants were found in the BCBM group versus the BC group. Horizontal dotted line, padj = 0.05 (-log10 scaled). (B) Hierarchical cluster analysis showing the different expression patterns of transcript variants between the BCBM group and the BC group. (C) Principal component analysis (PCA) using the differentially expressed transcript variants (DEGs). PCA shows that the variants in the BCBM group are distinct from those in the BC group. PC1: Principal component 1; PC2: Principal component 2.
Figure 5.
Figure 5.
Correlation analyzes between m5C RNA methylation and transcript variant differential expression. (A) Scatter plot graph for m5C RNA methylation and transcript variant expression. (B) Up-set graph for m5C RNA methylation and transcript variant expression. (C) Top two PPI networks in MCODE analysis based on the genes with coefficient changes. (D) Enrichment analysis of the top two MCODE genes.
Figure 6.
Figure 6.
Validation of the differential expression levels of the candidate mRNAs in the BCBM group versus the group. (A-D) Relative mRNA levels of IGFN1, EVL, AREG, and KRT7 in the BCBM group versus the BC group by RT-qPCR. n = 3. (E) Correlation analysis of the mean fold changes (log10 transformed) between qPCR results and RNA-seq data regarding the relative expression levels. (F) Quadrantal diagram of m5C RNA methylation and mRNA expression based on the MeRIP-qPCR and RT-qPCR data.
Figure 7.
Figure 7.
Analysis of m5C RNA methylation regulators involved in BCBM. (A) Differential expression level of the m5C RNA methylation regulators. Methyltransferases: NOP2, NSUN1, NSUN2, NSUN3, NSUN4, NSUN5, NSUN6, NSUN7, DNMT1, DNMT3A and DNMT3B. Demethylases: TET2 and TET3. Binding protein: ALYREF and YBX1. (B-G) Validation of the differential expression level of the candidate regulators based on TCGA samples. (H) Correlation analysis between the methyltransferase NSUN5 and demethylase TET2.

References

    1. Corti C, Antonarelli G, Criscitiello C, et al. Targeting brain metastases in breast cancer. Cancer Treat Rev. 2022;103:102324. doi: 10.1016/j.ctrv.2021.102324 - DOI - PubMed
    1. Morgan AJ, Giannoudis A, Palmieri C. The genomic landscape of breast cancer brain metastases: a systematic review. Lancet Oncol. 2021;22(1):e7–e17. doi: 10.1016/S1470-2045(20)30556-8 - DOI - PubMed
    1. Kennecke H, Yerushalmi R, Woods R, et al. Metastatic behavior of breast cancer subtypes. J Clin Oncol. 2010;28(20):3271–3277. doi: 10.1200/JCO.2009.25.9820 - DOI - PubMed
    1. Lowery FJ, Yu D. Brain metastasis: unique challenges and open opportunities. Biochim Biophys Acta Rev Cancer. 2017;1867(1):49–57. doi: 10.1016/j.bbcan.2016.12.001 - DOI - PMC - PubMed
    1. Wu S, Lu J, Zhu H, et al. A novel axis of circKIF4A-miR-637-STAT3 promotes brain metastasis in triple-negative breast cancer. Cancer Lett. 2024;581:216508. doi: 10.1016/j.canlet.2023.216508 - DOI - PubMed