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Objective: Increasing evidence highlights the roles of N6-methyladenosine (m6A) and its regulators in oncogenesis. Herein, this study observed the associations of m6A regulators with breast cancer.Methods: RNA-seq profiles of breast cancer were retrieved from the Cancer Genome Atlas (TCGA) database. The expression of m6A regulators was analyzed in tumor and normal tissues. Their expression correlations were analyzed by Spearson test. Overall survival (OS) analysis of these regulators was then presented. Gene set enrichment analysis (GSEA) was performed in high and low YTHDF1 expression groups. The correlations of YTHDF1 expression with immune cells and tumor mutation burden (TMB) were calculated in breast cancer samples. Somatic variation was assessed in high and low YTHDF1 expression groups.Results: Most of m6A regulators were abnormally expressed in breast cancer compared to normal tissues. At the mRNA levels, there were closely relationships between them. Among them, YTHDF1 up-regulation was significantly related to undesirable prognosis (p = 0.025). GSEA results showed that high YTHDF1 expression was associated with cancer-related pathways. Furthermore, YTHDF1 expression was significantly correlated with T cells CD4 memory activated, NK cells activated, monocytes, and macrophages. There were higher TMB scores in YTHDF1 up-regulation group than its down-regulation group. Missense mutation and non-sense mutation were the most frequent mutation types.Conclusion: Our findings suggested that dysregulated m6A regulator YTHDF1 was predictive of survival outcomes as well as response to immunotherapy of breast cancer, and were closely related to immune microenvironment.

Background Triple-negative breast cancer (TNBC) is the most aggressive subtype of breast cancer, and the targeted therapies are lacking for this type of cancer. We previously demonstrated that Huaier effectively improve 5-year OS and DFS in stage III TNBC patients, and the polysaccharides of Huaier (PS-T) have been identified as the major components of Huaier. However, the mechanisms of anti-tumor action of PS-T is unclear. This study aimed to investigate the effect of PS-T on TNBC cell invasion and migration. Results This study showed that PS-T inhibited cell invasion and migration both in vitro and in vivo by inducing autophagy to suppress epithelial-mesenchymal transition (EMT). Autophagy inhibitor LY294002 or knockdown of ATG5 suppressed the inhibitory effects of PS-T. In addition, as a key transcription factor controlling EMT initiation, Snail was found to be degraded by PS-T induced autophagy. In addition, overexpression of Snail reversed the inhibitory effects of PS-T. Furthermore, it was confirmed that the expression of Snail was inversely correlated with LC3 and associated with poor prognosis using immunohistochemistry and TCGA database analysis, respectively. Conclusions This study demonstrated that PS-T could inhibit EMT in breast cancer cells by inducing autophagy to degrade Snail protein, thus improving the prognosis of TNBC, offering potential treatment alternatives for TNBC patients.

BackgroundAccurate evaluation of the response to neoadjuvant chemotherapy (NAC) provides important information about systemic therapies for breast cancer, which implies pharmacological response, prognosis, and guide further therapy. Gene profiles overcome the shortcomings of the relatively limited detection indicators of the classical pathological evaluation criteria and the subjectivity of observation, but are complicated and expensive. Therefore, it is essential to develop a more accurate, repeatable, and economical evaluation approach for neoadjuvant chemotherapy responses.MethodsWe analyzed the transcriptional profiles of chemo-resistant breast cancer cell lines and tumors of chemo-resistant breast cancer patients in the GSE25066 dataset. We preliminarily screened out common significantly differentially expressed genes and constructed a NAC response risk model using LASSO regression and univariate and multivariate analyses. The differences in bioinformatic features of tumor cells, immune characteristics, and prognosis were compared between high and low-risk group. The potential drugs that could reverse chemotherapy resistance in breast cancer were screened by the CMap database.ResultsThirty-six genes were commonly up/down-regulated in both NAC chemo-resistant tumors and cells compared to the sensitive tumors and wild-type cells. Through LASSO regression, we obtained a risk model composed of 12 genes. The risk model divided patients into high and low-risk groups. Univariate and multivariate Cox regression analyses suggested that the risk score is an independent prognostic factor for evaluating NAC response in breast cancer. Tumors in risk groups exhibited significant differences in molecular biological characteristics, tumor-infiltrating lymphocytes, and immunosuppressive molecule expression. Our results suggested that the risk score was also a good prognostic factor for breast cancer. Finally, we screened potential drugs that could reverse chemotherapy resistance in breast cancer.ConclusionA novel 12 gene-signature could be used to predict NAC response and predict prognosis in breast cancer.