PTPRH promotes the progression of non-small cell lung cancer via glycolysis mediated by the PI3K/AKT/mTOR signaling pathway.

BACKGROUND: The protein tyrosine phosphatase H receptor (PTPRH) is known to regulate the occurrence and development of pancreatic and colorectal cancer. However, its association with glycolysis in non-small cell lung cancer (NSCLC) is still unclear. In this study, we aimed to investigate the relationship between PTPRH expression and glucose metabolism and the underlying mechanism of action. METHODS: The expression of PTPRH in NSCLC cells was evaluated by IHC staining, qRT‒PCR and Western blotting. The effect of PTPRH on cell biological behavior was evaluated by colony assays, EdU experiments, Transwell assays, wound healing assays and flow cytometry. Changes in F-18-fluorodeoxyglucose (18F-FDG) uptake and glucose metabolite levels after altering PTPRH expression were detected via a gamma counter and lactic acid tests. The expression of glycolysis-related proteins in NSCLC cells was detected by Western blotting after altering PTPRH expression. RESULTS: The results showed that PTPRH was highly expressed in clinical patient tissue samples and closely related to tumor diameter and clinical stage. In addition, PTPRH expression was associated with glycometabolism indexes on 18F-FDG positron emission tomography/computed tomography (PET/CT) imaging, the expression level of Ki67 and the expression levels of glycolysis-related proteins. PTPRH altered cell behavior, inhibited apoptosis, and promoted 18F-FDG uptake, lactate production, and the expression of glycolysis-related proteins. In addition, PTPRH modulated the glycometabolism of NSCLC cells via the phosphatidylinositol-3-kinase (PI3K)/protein kinase B (AKT)/mammalian target of rapamycin (mTOR) signaling pathway, as assessed using LY294002 and 740Y-P (an inhibitor and agonist of PI3K, respectively). The same results were validated in vivo using a xenograft tumor model in nude mice. Protein expression levels of PTPRH, glycolysis-related proteins, p-PI3K/PI3K and p-AKT/AKT were measured by IHC staining using a subcutaneous xenograft model in nude mice. CONCLUSIONS: In summary, we report that PTPRH promotes glycolysis, proliferation, migration, and invasion via the PI3K/AKT/mTOR signaling pathway in NSCLC and ultimately promotes tumor progression, which can be regulated by LY294002 and 740Y-P. These results suggest that PTPRH is a potential therapeutic target for NSCLC.

NOX4-derived ROS Regulates Aerobic Glycolysis of Breast Cancer through YAP Pathway.

Background: NOX4 is highly expressed in breast cancer and is closely associated with cell invasion and metastasis. The involvement of NOX4 in glycolysis in breast cancer remains unclear. The aim of this study was to investigate the role and mechanism of NOX4 in glycolysis in breast cancer. Methods: NOX4 expression in breast cancer cells was detected by qRT-PCR and western blotting. siRNAs and plasmids were used to silence or enhance the expression of NOX4. The mRNA and protein expression of HK2, GLUT1, PKM2, LDHA, and YAP was detected by qRT-PCR and western blotting, and the 18F-FDG uptake rate was detected by γ-radiometer. Detection of reactive oxygen species (ROS) in cells was performed using a commercial ROS kit. After transfection, CCK8, EDU and Transwell experiments were conducted to detect cell proliferation and migration ability. MicroPET imaging was used to detect the effects of NOX4 on tumor metabolism. Immunohistochemistry was used to detect the expression of NOX4, glycolytic enzymes HK2, GLUT1, PKM2, LDHA, the proliferation index KI67, and the activation of YAP pathway molecule. Results: In this study, the expression of NOX4 in MDA-MB-231 and MDA-MB-453 was higher than in MCF10A. qRT-PCR and western blotting experiments showed that NOX4 downregulation decreased the expression of glycolytic enzymes HK2, GLUT1, PKM2, LDHA, and 18F-FDG uptake. Conversely, the overexpression of NOX4 enhanced the expression of HK2, GLUT1, PKM2, LDHA, and 18F-FDG uptake. Proliferation and migration experiments showed that after down-regulation of NOX4, cell proliferation and migration ability decreased, while NOX4 overexpression promoted cell proliferation and migration ability. Additionally, ROS content and YAP expression decreased after NOX4 down-regulation, while ROS content and YAP expression increased following NOX4 overexpression, which was reversed by N-acetyl cysteine (NAC), a ROS inhibitor. Furthermore, exposure to NAC and Peptide17, a YAP inhibitor, blocked the increase in glycolytic enzyme expression, and the enhancement of proliferation and migration caused by NOX4 overexpression. In addition, in animal experiments, the results of the MicroPET imaging showed that the glucose metabolism rate of the NOX4 inhibitor group was significantly lower than that of the control group. ROS levels in the NOX4 inhibitor group was lower than that in the control group. Immunohistochemistry showed that the expression of HK2, GLUT1, PKM2, LDHA, KI67, and YAP in the NOX4 knock-down group were decreased. Conclusions: NOX4 affects breast cancer glycolysis through ROS-induced activation of the YAP pathway, further promoting the proliferation and migration of breast cancer cells.

MRLA-Net: A tumor segmentation network embedded with a multiple receptive-field lesion attention module in PET-CT images.

The tumor image segmentation is an important basis for doctors to diagnose and formulate treatment planning. PET-CT is an extremely important technology for recognizing the systemic situation of diseases due to the complementary advantages of their respective modal information. However, current PET-CT tumor segmentation methods generally focus on the fusion of PET and CT features. The fusion of features will weaken the characteristics of the modality itself. Therefore, enhancing the modal features of the lesions can obtain optimized feature sets, which is extremely necessary to improve the segmentation results. This paper proposed an attention module that integrates the PET-CT diagnostic visual field and the modality characteristics of the lesion, that is, the multiple receptive-field lesion attention module. This paper made full use of the spatial domain, frequency domain, and channel attention, and proposed a large receptive-field lesion localization module and a small receptive-field lesion enhancement module, which together constitute the multiple receptive-field lesion attention module. In addition, a network embedded with a multiple receptive-field lesion attention module has been proposed for tumor segmentation. This paper conducted experiments on a private liver tumor dataset as well as two publicly available datasets, the soft tissue sarcoma dataset, and the head and neck tumor segmentation dataset. The experimental results showed that the proposed method achieves excellent performance on multiple datasets, and has a significant improvement compared with DenseUNet, and the tumor segmentation results on the above three PET/CT datasets were improved by 7.25%, 6.5%, 5.29% in Dice per case. Compared with the latest PET-CT liver tumor segmentation research, the proposed method improves by 8.32%.

18F-FDG PET/CT for assessing heterogeneous metabolic response between primary tumor and metastases and prognosis in non-small cell lung cancer.

INTRODUCTION: This study aimed to use 18F-fluorodeoxyglucose positron emission tomography and/or computed tomography (18FDG-PET/CT) imaging to evaluate the heterogeneous metabolic response between primary tumor and metastases in NSCLC after therapy and explored its correlation with prognosis. METHODS: The data of patients with NSCLC who underwent 18FDG-PET/CT before and after treatment were retrospectively analyzed. Heterogeneous metabolic response (HR), defined as the difference in metabolic response between any metastases and primary lesion, was evaluated using 18FDG-PET/CT. And the correlation between HR and clinical prognosis was also analyzed. RESULTS: A total of 56 patients with NSCLC including 56 primary lesions and 491 metastases were enrolled in the study. 46.4% (26/56) of patients had HR, especially in patients with stage IV disease and whose metastases with high metabolic burden. HR was significantly correlated with poorer overall survival (OS) and progression-free survival (PFS) (P < .001 and P = .045, respectively). The multivariate analysis suggested that HR was an unfavorable independent prognostic factor for OS (HR = 4.36; 95% CI, 2.00-9.49; P < .001) but not for PFS (P = .469). HR between lymph node metastases was correlated with shorter OS (P < .001) but not with PFS (P = .370). CONCLUSION: HR was observed between primary and metastatic lesions in NSCLC after treatment using PET/CT. HR is significantly associated with poor prognosis and is an independent prognostic factor for OS.

Experimental and modelling studies of collision avoidance strategy choices and behavioural characteristics in interweaving pedestrian flow.

The mechanisms of collision avoidance (CA) behaviours in interweaving pedestrian flow movements are important for pedestrian space planning and emergency management but not well understood yet. In this paper, a series of controlled interweaving pedestrian flow experiments with different densities are carried out to investigate the CA behaviours, especially CA strategy choices. Four types of CA strategies are manually identified in these experiments. Nine characteristic parameters based on the trajectory data are defined to explore the characteristics of CA behaviours. The experimental results reveal that (i) the CA behaviours change with density levels; (ii) heterogeneities can be found for individual pedestrians; (iii) the defined characteristic parameters show different statistical features for different types of CA strategies, and correlations exist between most of the parameter pairs; (iv) it usually takes 0.5-2.5 s to complete a CA process with a trajectory length of 0.5-3.5 m. A multi-nomial logit (MNL) model and a long-short-term-memory (LSTM) model are established respectively for predicting pedestrians' choices of CA strategies using the selected characteristic parameters as inputs. The modelling results prove the importance of using time-series data for pedestrian behaviour modelling, and the LSTM models show advantages over the MNL model at this point.