ASS1 inhibits triple-negative breast cancer by regulating PHGDH stability and de novo serine synthesis.

Argininosuccinate synthase (ASS1), a critical enzyme in the urea cycle, acts as a tumor suppressor in many cancers. To date, the anticancer mechanism of ASS1 has not been fully elucidated. Here, we found that phosphoglycerate dehydrogenase (PHGDH), a key rate-limiting enzyme in serine synthesis, is a pivotal protein that interacts with ASS1. Our results showed that ASS1 directly binds to PHGDH and promotes its ubiquitination-mediated degradation to inhibit serine synthesis, consequently suppressing tumorigenesis. Importantly, the tumor suppressive effects of ASS1 were strongly abrogated by PHGDH knockout. In addition, ASS1 knockout and knockdown partially rescued cell proliferation when serine and glycine were depleted, while the inhibitory effect of ASS1 overexpression on cell proliferation was restored by the addition of serine and glycine. These findings unveil a novel role of ASS1 and suggest that the ASS1/PHGDH serine synthesis pathway is a promising target for cancer therapy.

Spinosyn A and Its Derivative Inhibit Colorectal Cancer Cell Growth via the EGFR Pathway.

Spinosyn A (SPA), derived from a soil microorganism, Saccharopolyspora spinosa, and its derivative, LM2I, has potential inhibitory effects on a variety of cancer cells. However, the effects of SPA and LM2I in inhibiting the growth of human colorectal cancer cells and the molecular mechanisms underlying these effects are not fully understood. Cell viability was tested by using a 3-(4,5-dimethylthiazol-2-yl-)-2,5-diphenyltetrazolium bromide (MTT) assay and a colony formation assay. On the basis of the IC50 values of SPA and LM2I in seven colorectal cancer (CRC) cell lines, sensitive (HT29 and SW480) and insensitive (SW620 and RKO) cell lines were screened. The GSE2509 and GSE10843 data sets were used to identify 69 differentially expressed genes (DEGs) between sensitive and insensitive cell lines. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, and protein-protein interactions (PPI) were performed to elucidate the molecular mechanisms of the DEGs. The hub gene of the DEGs was detected by Western blot analysis and verified using the CRISPR/Cas9 system. Our data indicate that SPA and its derivative LM2I have significant antiproliferative activity in seven colorectal cancer cell lines and colorectal xenograft tumors. On the basis of bioinformatics analysis, it was demonstrated that epidermal growth factor receptor (EGFR) was the hub gene of the DEGs and was associated with the inhibitory effects of SPA and LM2I in CRC cell lines. The study also revealed that SPA and LM2I inhibited the EGFR pathway in vitro and in vivo.

Clustering analysis and prognostic model based on PI3K/AKT-related genes in pancreatic cancer.

Background: Pancreatic cancer is one of most aggressive malignancies with a dismal prognosis. Activation of PI3K/AKT signaling is instrumental in pancreatic cancer tumorigenesis. The aims of this study were to identify the molecular clustering, prognostic value, relationship with tumor immunity and targeting of PI3K/AKT-related genes (PARGs) in pancreatic cancer using bioinformatics. Methods: The GSEA website was searched for PARGs, and pancreatic cancer-related mRNA data and clinical profiles were obtained through TCGA downloads. Prognosis-related genes were identified by univariate Cox regression analysis, and samples were further clustered by unsupervised methods to identify significant differences in survival, clinical information and immune infiltration between categories. Next, a prognostic model was constructed using Lasso regression analysis. The model was well validated by univariate and multivariate Cox regression analyses, Kaplan-Meier survival analysis and ROC curves, and correlations between risk scores and patient pathological characteristics were identified. Finally, GSEA, drug prediction and immune checkpoint protein analyses were performed. Results: Pancreatic cancers were divided into Cluster 1 (C1) and Cluster 2 (C1) according to PARG mRNA expression. C1 exhibited longer overall survival (OS) and higher immune scores and CTLA4 expression, whereas C2 exhibited more abundant PD-L1. A 6-PARG-based prognostic model was constructed to divide pancreatic cancer patients into a high-risk score (HRS) group and a low-risk score (LRS) group, where the HRS group exhibited worse OS. The risk score was defined as an independent predictor of OS. The HRS group was significantly associated with pancreatic cancer metastasis, aggregation and immune score. Furthermore, the HRS group exhibited immunosuppression and was sensitive to radiotherapy and guitarbine chemotherapy. Multidrug sensitivity prediction analysis indicated that the HRS group may be sensitive to PI3K/AKT signaling inhibitors (PIK-93, GSK2126458, CAL-101 and rapamycin) and ATP concentration regulators (Thapsigargin). In addition, we confirmed the oncogenic effect of protein phosphatase 2 regulatory subunit B'' subunit alpha (PPP2R3A) in pancreatic cancer in vitro and in vivo. Conclusions: PARGs predict prognosis, tumor immune profile, radiotherapy and chemotherapy drug sensitivity and are potential predictive markers for pancreatic cancer treatment that can help clinicians make decisions and personalize treatment.

An Isoxazoloquinone Derivative Inhibits Tumor Growth by Targeting STAT3 and Triggering Its Ubiquitin-Dependent Degradation.

BACKGROUND: Triple-negative breast cancer (TNBC) is the most aggressive breast cancer subtype, with shorter five-year survival than other breast cancer subtypes, and lacks targeted and hormonal treatment strategies. The signal transducer and activator of transcription 3 (STAT3) signaling is up-regulated in various tumors, including TNBC, and plays a vital role in regulating the expression of multiple proliferation- and apoptosis-related genes. RESULTS: By combining the unique structures of the natural compounds STA-21 and Aulosirazole with antitumor activities, we synthesized a class of novel isoxazoloquinone derivatives and showed that one of these compounds, ZSW, binds to the SH2 domain of STAT3, leading to decreased STAT3 expression and activation in TNBC cells. Furthermore, ZSW promotes STAT3 ubiquitination, inhibits the proliferation of TNBC cells in vitro, and attenuates tumor growth with manageable toxicities in vivo. ZSW also decreases the mammosphere formation of breast cancer stem cells (BCSCs) by inhibiting STAT3. CONCLUSIONS: We conclude that the novel isoxazoloquinone ZSW may be developed as a cancer therapeutic because it targets STAT3, thereby inhibiting the stemness of cancer cells.

Synchronizing Detection and Removal of Smoke in Endoscopic Images With Cyclic Consistency Adversarial Nets.

Smoke removal is an important and meaningful issue for endoscopic surgery, which can enhance the visual quality of endoscopic images. Because it is practically impossible to construct a large training dataset of pair-matched endoscopic images with/without smoke, the Generative Adversarial Nets (GANs) based models are usually used for endoscopic image desmoke. But they have difficulties in either locating the accurate smoke area, or recovering realistic internal organ or tissue details. In this paper, we propose a new approach, called Desmoke-CycleGAN, which combined detection, estimation, and removal of smoke together, to improve the CycleGAN model for endoscopic image smoke removal. In addition, both pixel-level and perceptual-level consistency loss have been incorporated in the proposed model, which helps the model to be more stable and efficient for recovering realistic details in endoscopic images. The experimental results have demonstrated that this method outperforms other state-of-the-art smoke removal approaches with unpaired real endoscopic images.

Cycle-Consistent Adversarial Networks for Smoke Detection and Removal in Endoscopic Images.

During endoscopic surgery, smoke removal is important and meaningful for increasing the visual quality of endoscopic images. However, unlike natural image dehaze, it is practical impossible to build a large paired endoscopic image training dataset with/without smoke. Therefore, in this paper, we propose a new approach, called Desmoke-CycleGAN, which combined detection and removal of smoke together, to improve the CycleGAN model for endoscopic image smoke removal. The detector can provide information about smoke locations and densities, which helps the GAN model to be more stable and efficient for smoke removal. Although some imperfections still exist, the experimental results have demonstrated that this method outperforms other state-of-the-art smoke removal approaches with unpaired real endoscopic images.Clinical Relevance- This can help improve the visibility in endoscopic surgery and to get smoke-free endoscopic images with better quality.

Naturally-occurring spinosyn A and its derivatives function as argininosuccinate synthase activator and tumor inhibitor.

Argininosuccinate synthase (ASS1) is a ubiquitous enzyme in mammals that catalyzes the formation of argininosuccinate from citrulline and aspartate. ASS1 genetic deficiency in patients leads to an autosomal recessive urea cycle disorder citrullinemia, while its somatic silence or down-regulation is very common in various human cancers. Here, we show that ASS1 functions as a tumor suppressor in breast cancer, and the pesticide spinosyn A (SPA) and its derivative LM-2I suppress breast tumor cell proliferation and growth by binding to and activating ASS1. The C13-C14 double bond in SPA and LM-2I while the Cys97 (C97) site in ASS1 are critical for the interaction between ASS1 and SPA or LM-2I. SPA and LM-2I treatment results in significant enhancement of ASS1 enzymatic activity in breast cancer cells, particularly in those cancer cells with low ASS1 expression, leading to reduced pyrimidine synthesis and consequently the inhibition of cancer cell proliferation. Thus, our results establish spinosyn A and its derivative LM-2I as potent ASS1 enzymatic activator and tumor inhibitor, which provides a therapeutic avenue for tumors with low ASS1 expression and for those non-tumor diseases caused by down-regulation of ASS1.

Bioinformatics and machine learning methodologies to identify the effects of central nervous system disorders on glioblastoma progression.

Glioblastoma (GBM) is a common malignant brain tumor which often presents as a comorbidity with central nervous system (CNS) disorders. Both CNS disorders and GBM cells release glutamate and show an abnormality, but differ in cellular behavior. So, their etiology is not well understood, nor is it clear how CNS disorders influence GBM behavior or growth. This led us to employ a quantitative analytical framework to unravel shared differentially expressed genes (DEGs) and cell signaling pathways that could link CNS disorders and GBM using datasets acquired from the Gene Expression Omnibus database (GEO) and The Cancer Genome Atlas (TCGA) datasets where normal tissue and disease-affected tissue were examined. After identifying DEGs, we identified disease-gene association networks and signaling pathways and performed gene ontology (GO) analyses as well as hub protein identifications to predict the roles of these DEGs. We expanded our study to determine the significant genes that may play a role in GBM progression and the survival of the GBM patients by exploiting clinical and genetic factors using the Cox Proportional Hazard Model and the Kaplan-Meier estimator. In this study, 177 DEGs with 129 upregulated and 48 downregulated genes were identified. Our findings indicate new ways that CNS disorders may influence the incidence of GBM progression, growth or establishment and may also function as biomarkers for GBM prognosis and potential targets for therapies. Our comparison with gold standard databases also provides further proof to support the connection of our identified biomarkers in the pathology underlying the GBM progression.

Gender differences in the clinical management of patients with angina pectoris: a cross-sectional survey in primary care.

BACKGROUND: Previous research suggests that women admitted to hospital with acute myocardial infarction (MI) are managed less intensively than men. Chronic stable angina is the commonest clinical manifestation of coronary heart disease in the community, but little information is available concerning its contemporary clinical management. The aim of this study is to assess the extent of gender differences in the clinical management of angina pectoris in primary care. METHODS: A cross-sectional survey undertaken in 8 sentinel centres serving 63,724 individuals in the city of Liverpool (15% of the city population). Aspects of clinical care assessed included: risk factor recording (smoking, cholesterol, blood pressure, body mass index); secondary prevention (aspirin, beta-blocker, statin); cardiac investigation (exercise ECG, perfusion scanning, angiography); and revascularisation (percutaneous coronary intervention, coronary artery bypass grafting). Male-to-female adjusted odds ratios (AOR) were calculated (adjusted for age, angina duration, age at diagnosis and previous MI) using logistic regression. RESULTS: 1,162 patients (610 men; 552 women) with angina were identified. Women were older than men (71 vs 67 years), with a shorter duration of angina (6 vs 7 years), and a lower prevalence of previous MI (25% vs 43%). Men were significantly more likely than women to undergo detailed risk factor assessment (AOR = 1.35, 95%CI 1.06 to 1.73); receive 'triple' secondary prevention with aspirin, beta-blockers and statins (AOR = 1.47, 95%CI 1.07 to 2.02); access exercise ECG testing (AOR = 1.31, 95%CI 1.02 to 1.68); angiography (AOR = 1.61, 95%CI 1.23 to 2.12); and undergo coronary revascularisation (AOR = 1.93, 95%CI 1.39 to 2.68). CONCLUSION: Systematic gender differences exist in the comprehensive clinical management of patients with angina in primary care.