Identification of circRNA/lncRNA-miRNA-Transcription Factor-mRNA Networks to Identify Potential Biomarkers in Response to Neoadjuvant Therapy for Breast Cancer

Donghai Li,* Zhiying Zhang,* Yibo Chen, Xueyu Zhao, Kunyuan He, Rui Zhang Department of Thyroid and Breast Surgery, Affiliated Hospital of Inner Mongolia Medical University, Hohhot, Inner Mongolia Autonomous Region, People′s Republic of China*These authors contributed equally to this workCorrespondence: Rui Zhang, Department of Thyroid and Breast Surgery, Affiliated Hospital of Inner Mongolia Medical University, No. 1 Tongdao North Street, Huiming District, Hohhot, Inner Mongolia Autonomous Region, 010050, People′s Republic of China, Email zhangrui999999@163.comBackground: Neoadjuvant therapy (NAT) is the standard treatment option for locally advanced breast cancer (BC). Noncoding RNAs are known to play a significant role in cancer development. However, the involvement of the circular RNA (circRNA)/long non-coding RNA (lncRNA)–(miRNA)–mRNA competitive endogenous RNA (ceRNA) network in the antitumor effects of NAT in BC remains unclear.Methods: Ribosomal RNA (rRNA)-depleted RNA sequencing (RNA-seq) was performed to identify differentially expressed lncRNAs (DElncRNAs), circRNAs (DEcircRNAs), mRNAs (DEmRNAs) and transcription factors (DE-TFs) between pre-therapy tumor tissues and adjacent normal tissues, as well as between post-NAT tumor tissues and pre-therapy tumor tissues. The changes in gene expression in the ceRNA network were confirmed by RT-qPCR.Results: We identified dysregulated RNAs associated with NAT, including 2693 DEcircRNAs, 25 DElncRNAs, 58 DE-TFs, and 878 DEmRNAs. Three core ceRNA networks were constructed bioinformatically, centered on the key DE-TFs, including HOXC11, NKX2-2, and PRAME. RT-qPCR results confirmed a significant increase in the levels of circRNA_31003, circRNA_42276, MIAT, HOXC11, NKX2-2, PRAME, CCL5, NEK2, and RAD54L in tumor tissues before therapy when compared to normal tissues, but these levels decreased in post-NAT tumor group compared to pre-therapy tumor group. In contrast, the expression of miR-1225-3p, miR-661, and miR-143-5p showed a notable decline in pre-therapy tumors in comparison to normal tissues; however, these expressions elevated significantly in post-NAT tumor group compared to pre-therapy tumor group.Conclusion: Associated regulatory networks were constructed to explore candidate biomarkers that may respond to NAT treatment in BC.Keywords: breast cancer, neoadjuvant therapy, rRNA-depleted RNA-seq, transcription factors, network