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Additional file 1. Fig. S1A. Expression of MPK17 in rice TP309 leaves at different time points following inoculation with Xoo. Fig. S1B. Expression of XA21 in MPK1-RNAi and MPK17-OX transgenic rice plants. Fig. S2. Construction and verification of MPK17-RNAi transformation vector. Fig. S3. Identification of MPK17-RNAi transgenic lines by PCR and WB. Fig. S4. Identification of MPK17-OX in transgenic rice. Fig. S5. RT-PCR analysis of MPK17-RNAi and MPK17-OX transgenic rice plants. Fig. S6. Xa21-mediated resistance in rice at 31℃following overexpression of MPK17. Fig. S7. Effects of MPK17 abundance on the propagation of Xoo in rice leaves. Fig. S8. Expression of WRKY protein in rice leaves infected with Xoo. Fig. S9. Expression of pathogenesis-related protein PR1A in MPK17-regulated rice plants.

Lifei Ma,1,2 Guiqin Song,1 Meiyu Li,3 Xiuqing Hao,4 Yong Huang,1 Jinping Lan,1 Siqian Yang,5 Zetian Zhang,6 Guohui Zhang,3 Jiao Mu3,7 1College of Laboratory Medicine, Hebei North University, Zhangjiakou, Hebei 075000, People’s Republic of China; 2State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences, School of Basic Medicine, Peking Union Medical College, Beijing 100005, People’s Republic of China; 3Department of Forensic Medicine, Hebei North University, Zhangjiakou, Hebei 075000, People’s Republic of China; 4Department of Pathology, The First Affiliated Hospital of Hebei North University, Zhangjiakou, Hebei 075000, People’s Republic of China; 5College of Life Sciences and Medicine, Zhejiang Sci-Tech University, Hangzhou, Zhejiang 310018, People’s Republic of China; 6Department of Gastroenterology, The First Affiliated Hospital of Hebei North University, Zhangjiakou, Hebei 075000, People’s Republic of China; 7Department of Biomedical Engineering, School of Biological Science and Medical Engineering, Beihang University, Beijing 100191, People’s Republic of ChinaCorrespondence: Jiao Mu; Guohui Zhang Department of Forensic Medicine, Zhangjiakou, Hebei 075000, People’s Republic of ChinaTel +86-18931315882; +86-18931316008 Email jiaomu@hebeinu.edu.cn; 18931316008@163.comBackground: Triple-negative breast cancer (TNBC) is the most common and aggressive type of breast cancer with an unfavourable outcome worldwide. Novel therapeutic targets are urgently required to explore this malignancy. This study explored the ceRNA network and the important genes for predicting the therapeutic targets.Methods: It identified the differentially expressed genes of mRNAs, lncRNAs and miRNAs between TNBC and non-TNBC samples in four cohorts (TCGA, GSE38959, GSE45827 and GSE65194) to explore the novel therapeutic targets for TNBC. Downstream analyses, including functional enrichment analysis, ceRNA network, protein–protein interaction and survival analysis, were then conducted by bioinformatics analysis. Finally, the potential core protein of the ceRNA network in TNBC was validated by immunohistochemistry.Results: A total of 1,045 lncRNAs and 28 miRNAs were differentially expressed in the TCGA TNBC samples, and the intersections of 282 mRNAs (176 upregulations and 106 downregulations) between the GEO and TCGA databases were identified. A ceRNA network composed of 7 lncRNAs, 62 mRNAs, 12 miRNAs and 244 edges specific to TNBC was established. The functional assay showed dysregulated genes, and GO, DO and KEGG enrichment analysis were performed. Survival analysis showed that mRNA LIFR and lncRNA AC124312.3 were significantly correlated with the overall survival of patients with TNBC in the TCGA databases (P < 0.05). Finally, the LIFR protein was validated, and immunohistochemical results showed the upregulated expression of LIFR in TNBC tissues.Conclusion: Thus, our study presents an enhanced understanding of the ceRNA network in TNBC, where the key gene LIFR may be a new promising potential therapeutic target for patients with TNBC.Keywords: triple-negative breast cancer, ceRNA network, overall survival, novel biomarkers, leukemia inhibitory factor receptor