The abnormal m6A modification caused by m6A modulators is a common feature of various tumors; however, little is known about which m6A modulator plays the most important role in triple-negative breast cancer (TNBC). In this study, when analyzing the influence of m6A modulators (METTL3, METTL14, WTAP, FTO, and ALKBH5) on the prognosis of breast cancer, especially in TNBC using several on-line databases, methyltransferase-like 3 (METTL3) was found to have low expression in breast cancer, and was closely associated with short-distance-metastasis-free survival in TNBC. Further investigation showed that knockdown of METTL3 could enhance the ability of migration, invasion, and adhesion by decreasing m6A level in TNBC cell lines. Collagen type III alpha 1 chain (COL3A1) was identified and verified as a target gene of METTL3. METTL3 could down-regulate the expression of COL3A1 by increasing its m6A methylation, ultimately inhibiting the metastasis of TNBC cells. Finally, with immunohistochemistry staining in breast cancer tissues, it was proved that METTL3 expression was negatively correlated with COL3A1 in TNBC, but not in non-TNBC. This study demonstrated the potential mechanism of m6A modification in metastasis and provided potential targets for treatment in TNBC.

Objective: To investigate the value of delta-radiomics after the first cycle of neoadjuvant chemotherapy (NAC) using dynamic contrast-enhanced (DCE) MRI for early prediction of pathological complete response (pCR) in patients with breast cancer. Methods: From September 2018 to May 2021, a total of 140 consecutive patients (training, n = 98: validation, n = 42), newly diagnosed with breast cancer who received NAC before surgery, were prospectively enrolled. All patients underwent DCE-MRI at pre-NAC (pre-) and after the first cycle (1st-) of NAC. Radiomic features were extracted from the postcontrast early, peak, and delay phases. Delta-radiomics features were computed in each contrast phases. Least absolute shrinkage and selection operator (LASSO) and a logistic regression model were used to select features and build models. The model performance was assessed by receiver operating characteristic (ROC) analysis and compared by DeLong test. Results: The delta-radiomics model based on the early phases of DCE-MRI showed a highest AUC (0.917/0.842 for training/validation cohort) compared with that using the peak and delay phases images. The delta-radiomics model outperformed the pre-radiomics model (AUC = 0.759/0.617, p = 0.011/0.047 for training/validation cohort) in early phase. Based on the optimal model, longitudinal fusion radiomic models achieved an AUC of 0.871/0.869 in training/validation cohort. Clinical-radiomics model generated good calibration and discrimination capacity with AUC 0.934 (95%CI: 0.882, 0.986)/0.864 (95%CI: 0.746, 0.982) for training and validation cohort. Delta-radiomics based on early contrast phases of DCE-MRI combined clinicopathology information could predict pCR after one cycle of NAC in patients with breast cancer.

Drug resistance is a major challenge in cancer therapeutics. Abundant evidence indicates that DNA repair systems are enhanced after repetitive chemotherapeutic treatments, rendering cancers cells drug-resistant. Flap endonuclease 1 (FEN1) plays critical roles in DNA replication and repair and in counteracting replication stress, which is a key mechanism for many chemotherapeutic drugs to kill cancer cells. FEN1 was previously shown to be upregulated in response to DNA damaging agents. However, it is unclear about the transcription factors that regulate FEN1 expression in human cancer. More importantly, it is unknown whether up-regulation of FEN1 has an adverse impact on the prognosis of chemotherapeutic treatments of human cancers. To reveal regulation mechanism of FEN1 expression, we search and identify FEN1 transcription factors or repressors and investigate their function on FEN1 expression by using a combination of biochemical, molecular, and cellular approaches. Furthermore, to gain insights into the impact of FEN1 levels on the response of human cancer to therapeutic treatments, we determine FEN1 levels in human breast cancer specimens and correlate them to the response to treatments and the survivorship of corresponding breast cancer patients. We observe that FEN1 is significantly up-regulated upon treatment of chemotherapeutic drugs such as mitomycin C (MMC) and Taxol in breast cancer cells. We identify that the transcription factor/repressor YY1 binds to the FEN1 promoter and suppresses the expression of FEN1 gene. In response to the drug treatments, YY1 is dissociated from the FEN1 promoter region leading over-expression of FEN1. Overexpression of YY1 in the cells results in down-regulation of FEN1 and sensitization of the cancer cells to MMC or taxol. Furthermore, we observe that the level of FEN1 is inversely correlated with cancer drug and radiation resistance and with survivorship in breast cancer patients. Altogether, our current data indicate that YY1 is a transcription repressor of FEN1 regulating FEN1 levels in response to DNA damaging agents. FEN1 is up-regulated in human breast cancer and its levels inversely correlated with cancer drug and radiation resistance and with survivorship in breast cancer patients.

Flap endonuclease 1 (FEN1) is recognized as a pivotal factor in DNA replication, long‐patch excision repair, and telomere maintenance. Excessive FEN1 expression has been reported to be closely associated with cancer progression, but the specific mechanism has not yet been explored. In the present study, we demonstrated that FEN1 promoted breast cancer cell proliferation via an epigenetic mechanism of FEN1‐mediated up‐regulation of DNA methyltransferase (DNMT)1 and DNMT3a. FEN1 was proved to interact with DNMT3a through proliferating cell nuclear antigen (PCNA) to suppress microRNA (miR)‐200a‐5p expression mediated by methylation. Furthermore, miR‐200a‐5p was identified to repress breast cancer cell proliferation by inhibiting the expression of its target genes, hepatocyte growth factor (MET), and epidermal growth factor receptor (EGFR). Overall, our data surprisingly demonstrate that FEN1 promotes breast cancer cell growth via the formation of FENl/PCNA/DNMT3a complex to inhibit miR‐200a expression by DNMT‐mediated methylation and to recover the target genes expression of miR‐200a, MET, and EGFR. The novel epigenetic mechanism of FEN1 on proliferation promotion provides a significant clue that FEN1 might serve as a predictive biomarker and therapeutic target for breast cancer.—Zeng, X., Qu, X., Zhao, C., Xu, L., Hou, K., Liu, Y., Zhang, N., Feng, J., Shi, S., Zhang, L., Xiao, J., Guo, Z., Teng, Y., Che, X. FEN1 mediates miR‐200a methylation and promotes breast cancer cell growth via MET and EGFR signaling. FASEB J. 33, 10717–10730 (2019). www.fasebj.org

Hormone receptor-positive breast cancer accounts for around 75% of breast cancers. The estrogen receptor pathway promotes tumor progression and endocrine resistance. Recently, the cross-talk between the ER signaling pathway and cell cycle regulation has been identified. It is necessary to determine the underlying molecular mechanisms involved in the ER signaling pathway and find new target genes for prognosis and drug resistance in ER+ breast cancer. In this study, lncRNA MAFG-AS1 was shown to be up-regulated and associated with poor prognosis in ER+ breast cancer. Functionally, down-regulation of MAFG-AS1 could inhibit cell proliferation and promote apoptosis. In addition, MAFG-AS1 which contained an estrogen-responsive element could promote CDK2 expression by sponging miR-339-5p. Subsequently, MAFG-AS1 and CDK2 were found to be up-regulated in tamoxifen-resistant MCF-7 cells. Cross-talk between the ER signaling pathway and cell cycle conducted by MAFG-AS1 and CDK2 could promote tamoxifen resistance. In conclusion, our study indicated that estrogen-responsive lncRNA MAFG-AS1 up-regulated CDK2 by sponging miR-339-5p, which promoted ER+ breast cancer proliferation. Cross-talk between the ER signaling pathway and cell cycle suggested that lncRNA MAFG-AS1 is a potential biomarker and therapeutic target in ER+ breast cancer. CDK2 inhibitors may be applied to endocrine resistance therapy.