Genomic instability, a hallmark of cancer, occurs preferentially at specific genomic regions known as common fragile sites (CFSs). CFSs are evolutionarily conserved and late replicating regions with AT-rich sequences, and CFS instability is correlated with cancer. In the last decade, much progress has been made toward understanding the mechanisms of chromosomal instability at CFSs. However, despite tremendous efforts, identifying a cancer-associated CFS gene (CACG) remains a challenge and little is known about the function of CACGs at most CFS loci. Recent studies of FATS (for Fragile-site Associated Tumor Suppressor), a new CACG at FRA10F, reveal an active role of this CACG in regulating DNA damage checkpoints and suppressing tumorigenesis. The identification of FATS may inspire more discoveries of other uncharacterized CACGs. Further elucidation of the biological functions and clinical significance of CACGs may be exploited for cancer biomarkers and therapeutic benefits.

Frequent mutations of p53 in human cancers exemplify its crucial role as a tumor suppressor transcription factor, and p21, a transcriptional target of p53, plays a central role in surveillance of cell-cycle checkpoints. Our previous study has shown that FATS stabilize p21 to preserve genome integrity. In this study we identified a novel transcript variant of FATS (GenBank: GQ499374) through screening a cDNA library from mouse testis, which uncovered the promoter region of mouse FATS. Mouse FATS was highly expressed in testis. The p53-responsive elements existed in proximal region of both mouse and human FATS promoters. Functional study indicated that the transcription of FATS gene was activated by p53, whereas such effect was abolished by site-directed mutagenesis in the p53-RE of FATS promoter. Furthermore, the expression of FATS increased upon DNA damage in a p53-dependent manner. FATS expression was silent or downregulated in human cancers, and overexpression of FATS suppressed tumorigenicity in vivo independently of p53. Our results reveal FATS as a p53-regulated gene to monitor genomic stability.

Breast cancer is one of the most prevalent and diverse malignancies, and, with global cases increasing, the need for biomarkers to inform individual sensitivity to chemotherapeutics has never been greater. Our retrospective clinical analysis predicted that the expression of the fragile site-associated tumor suppressor (FATS) gene was associated with the sensitivity of breast cancer to neoadjuvant chemotherapy with paclitaxel. In vitro experiments subsequently demonstrated that FATS significantly increased the inhibitory effects of paclitaxel on breast cancer cells’ migration, growth, and survival. An interaction screen revealed that FATS interacted with MYH9 and promoted its degradation via the ubiquitin-proteasome pathway, thereby downregulating Wnt signaling. By overexpressing FATS and MYH9, we demonstrated that FATS enhanced paclitaxel-induced apoptosis in breast cancer cells by degrading MYH9 to downregulate the Wnt pathway. We also demonstrated in a mouse xenograft model that FATS significantly increased the chemosensitivity of breast cancer cells to paclitaxel in vivo. This study presents a new mechanism by which FATS interacts with MYH9 to suppress the Wnt/β-catenin signaling pathway and induce apoptosis, thus enhancing the sensitivity of breast cancer cells to paclitaxel chemotherapy. The results also propose novel biomarkers for predicting breast cancer sensitivity to neoadjuvant chemotherapy with paclitaxel. Finally, we provide in vivo evidence that the combination of paclitaxel with IWR-1, a novel Wnt pathway inhibitor, synergistically suppresses breast cancer growth, laying the foundation for future trials with this drug combination. These results therefore provide a number of potential solutions for more precise treatment of patients with breast cancer in the future.

The fragile-site associated tumor suppressor (FATS, formerly known as C10orf90), a regulator of p53-p21 pathway has been involved in the onset of breast cancer. Recent data support the idea that the crosstalk between FATS and p53 may be of physiological importance for reproduction during evolution. The aim of the current study was to test the hypothesis that FATS genetic polymorphism can influence the risk of breast cancer. We conducted population-based studies in two independent cohorts comprising 1 532 cases and 1 573 controls in Tianjin of North China, and 804 cases and 835 controls in Guangzhou of South China, coupled with functional validation methods, to investigate the role of FATS genetic variant in breast cancer risk. We identified a functional variant rs11245007 (905C > T, 262D/N) in fragile-site gene FATS that modulates p53 activation. FATS-262 N exhibited stronger E3 activity to polyubiquitinate p53 than did FATS-262D, leading to the stronger transcriptional activity of p53 and more pronounced stabilization of p53 protein and its activation in response to DNA damage. Case–control studies found that CT or TT genotype was significantly associated with a protective effect on breast cancer risk in women with parity ≥ 3, which was not affected by family history. Our findings suggest the role of FATS-p53 signaling cascade in suppressing pregnancy-related carcinogenesis and potential application of FATS genotyping in breast cancer prevention.

Endoscopic ultrasonography (EUS) is commonly utilized in preoperative staging of esophageal cancer, however with additional pain and cost as well as adverse events. Meanwhile, the accuracy of EUS is highly depend on the training and practice of operators and not universally available. Different operators would lead to high inter-observer variability. Therefore, it is desirable to explore an alternative way to determine preoperative T stage in esophageal cancer. Whether conventional endoscopy possess the ability to predict EUS T stage has never been investigated yet. In current study, with the assistance of Artificial intelligence, we have developed a deep learning model to predict EUS T stage based on 9,714 images collected from 3,333 patients. ResNet-152 pre-trained on the ImageNet dataset was trained with the appropriate transfer learning and fine-tuning strategies on the conventional endoscopic images and their corresponding labels (e.g., T1, T2, T3, T4 and Normal). Meanwhile, augmentation strategies including rotation and flipping were performed to increase the number of images to improve the prediction accuracy. Finally, 4,382 T1, 243 T2, 3,985 T3, 1,102 T4, 14,302 controls images were obtained and split into training dataset, validation dataset and independent testing dataset with the ratio of 4:1:1. Our model could achieve a satisfied performance with an area under the receiver-operating curve (AUC) were 0.9767, 0.9637, 0.9597 and 0.9442 for T1, T2, T3 and T4, respectively in independent testing dataset. In conclusion, conventional gastroscopy combined with artificial intelligence have the great potential to predict EUS T stage.

Among women, tripple-negative breast cancer (TNBC) is highly prevalent, and controlling recurrence and metastatic disease remains difficult in clinical pra