RANKL/RANK promotes the migration of gastric cancer cells by interacting with EGFR

BACKGROUND: The incidence and mortality rates of gastric cancer (GC) rank in top five among all malignant tumors. Chemokines and their receptor-signaling pathways reportedly play key roles in the metastasis of malignant tumor cells. Receptor activator of nuclear factor κB ligand (RANKL) is a member of the tumor necrosis factor family, with strong chemokine-like effects. Some studies have pointed out that the RANKL/RANK pathway is vital for the metastasis of cancer cells, but the specific mechanisms in GC remain poorly understood. RESULTS: This study reports original findings in cell culture models and in patients with GC. Flow cytometry and western blotting analyses showed that RANK was expressed in BGC-823 and SGC-7901 cells in particular. Chemotaxis experiments and wound healing assay suggested that RANKL spurred the migration of GC cells. This effect was offset by osteoprotegerin (OPG), a decoy receptor for RANKL. RANKL contributed to the activation of human epidermal growth factor receptor (HER) family pathways. The lipid raft core protein, caveolin 1 (Cav-1), interacted with both RANK and human epidermal growth factor receptor-1(EGFR). Knockdown of Cav-1 blocked the activation of EGFR and cell migration induced by RANKL. Moreover, RANK-positive GC patients who displayed higher levels of EGFR expression had poor overall survival. CONCLUSIONS: In summary, we confirmed that with the promotion of RANKL, RANK and EGFR can form complexes with the lipid raft core protein Cav-1, which together promote GC cell migration. The formation of the RANK-Cav-1-EGFR complex provides a novel mechanism for the metastasis of GC. These observations warrant confirmation in independent studies, in vitro and in vivo. They also inform future drug target discovery research and innovation in the treatment of GC progression

A multiscale analysis of the relationship between urbanization and CO2 emissions using geo-weighted regression model

Abstract It is of great practical significance to explore the relationship between urbanization and CO2 emissions for the low-carbon development of cities. However, the multiscale assessment of spatial relationship between population, land and economic urbanization and CO2 emissions is lacked. In this study, we first adopted the spatial statistical methods to evaluate the spatial pattern of China’s CO2 emissions in 2019. Then, we spatially quantified China’s urbanization of land, population and economy based on statistical data. Finally, we used the geo-weighted regression model to explore the spatial relationship between urbanization and CO2 emissions at the national-economic zone-province scale. The results displayed that there is obvious spatial heterogeneity in the relationship between China’s urbanization and CO2 emissions. The significant positive correlation between urbanization and CO2 emissions were mainly located in the northeastern, eastern and southwestern regions, consistent with the characteristics of the Heihe–Tengchong Line. The uneven development of land, population and economic urbanization would lead to more CO2 emissions. We suggest that China should attend the balanced development of urban land, population and economy, and avoid the additional carbon emissions caused by incongruence, to further the development of low-carbon cities

Impacts of Energy Price on Agricultural Production, Energy Consumption, and Carbon Emission in China: A Price Endogenous Partial Equilibrium Model Analysis

Energy market volatility will have systemic effects on agricultural production, energy consumption and carbon emissions. This paper aims to evaluate the impacts of energy price on agricultural production, energy consumption, and carbon emission in China. To achieve the objective, this paper, firstly, constructed a price endogenous partial equilibrium model, and then designed four scenarios of energy price fluctuations, finally evaluating the impacts of energy price fluctuations on agricultural production and its energy consumption and carbon emission. The results revealed that: (1) The impacts on agricultural production are very limited, but higher energy price will result in producers’ welfare loss by 0.6% to 1.4%, under different scenarios. (2) Energy price drives negative impacts on agricultural energy consumption and carbon emission, 1.6%/3.2% and 1.3%/2.6%, respectively, in low/high amplitude scenarios. (3) Heterogeneous impacts are confirmed in the regional analysis; South China is simulated to be the most sensitive area. To mitigate the impacts from energy price and reduce carbon emission in agriculture, several policy implications have recently been proposed, including strengthening supervision of the energy market, constructing an energy saving price-setting mechanism, launching policy instruments to improve energy efficiencies and facilitate cleaner farming techniques, and formulating specific measurements of energy saving and emission reduction for different regions

The Impact of the Expression Level of Intratumoral Dihydropyrimidine Dehydrogenase on Chemotherapy Sensitivity and Survival of Patients in Gastric Cancer: A Meta-Analysis

The potential impact that the intratumoral expression level of dihydropyrimidine dehydrogenase (DPD) has on chemotherapy sensitivity and long-term survival for gastric cancer (GC) patients remains controversial; therefore, this study seeks to clarify this issue. Our meta-analysis was performed using Review Manager (RevMan) 5.3 software. In vitro drug sensitivity tests, correlation coefficients between sensitivity to 5-fluorouracil (5-FU), and expression levels of intratumoral DPD were used as effective indexes to analyse. Overall survival (OS) and progression-free survival (PFS) were used as endpoints for patient outcome, and hazard ratios (HRs) and 95% confidence intervals (CIs) were noted as measures of effect. There were 15 eligible studies including 1805 patients for the final analysis. The analysis revealed a statistically significant difference between the expression level of intratumoral DPD activity, DPD mRNA levels, and sensitivity to 5-FU in GC patients, with high expression levels of intratumoral DPD resulting in low sensitivity to 5-FU. However, no matter what therapeutic regimens were used, there was no significant difference for patient outcomes between high and low DPD expression groups, either in OS or in PFS. In conclusion, high levels of intratumoral DPD expression have a negative impact on sensitivity to 5-FU in GC patients, but no prognostic value for long-term survival was uncovered

Prognostic value of pretreatment standardized uptake value of F-18-fluorodeoxyglucose PET in patients with gastric cancer: a meta-analysis

Abstract Background F-18- fluorodeoxyglucose Positron emission tomography (18FDG-PET) has been widely used in clinical practice. However, the prognostic value of the pretreatment standardized uptake value (SUV) for patients with gastric cancer remains controversial. Methods Major databases were systematically searched. The quality of the included studies was assessed using the Newcastle–Ottawa scale; the PET protocols were also evaluated. The pooled hazard ratio (HR) for overall survival (OS) and recurrence-free survival (RFS) were used to estimate the effect size. Data from the included studies were analyzed using Review Manager Software version 5.2. Results Eight studies with 1080 patients were included. The pooled HR for OS of six studies including 672 patients was 1.72 (95% CI [1.28–2.3], p = 0.0004, I2 = 0%), indicating that patients with high SUVs may have poor prognosis. The pooled HR for RFS was 1.70 (95% CI [1.20–2.39], p = 0.003, I2 = 0%). Subgroup analysis based on the cutoff values determining method indicated that the receiver operating characteristic (ROC) method could better define the cutoff value. Subgroup analysis based on the therapeutic strategies used subsequently indicated the significant prognostic value of SUV. Conclusion In conclusion, our meta-analysis indicated that pretreatment SUV in primary lesions can be an important prognostic factor for overall survival and recurrence-free survival in patients with gastric cancer. High SUVs may indicate poor prognosis

A nomogram for predicting bowel obstruction in preoperative colorectal cancer patients with clinical characteristics

Abstract Background Bowel obstruction (BO) is a complication that commonly affects patients with colorectal cancer (CRC). BO causes severe outcomes, and its treatment leads to a dilemma for many surgeons. Moreover, the factors correlated to BO in preoperative CRC patients remain unclear. The objectives of this study were to investigate the clinical characteristics of BO to identify risk predictors and to construct a BO prediction model with preoperative CRC patients. Methods A large-scale, retrospective cohort, population-based study analyzed the data of 11,814 patients obtained from the Surveillance, Epidemiology, and End Results and Medicare claims-linked databases (SEER-M database). Patients aged ≥ 66 years and primarily diagnosed with CRC from 1992 to 2009 were divided into BO and non-BO groups. Cox proportional hazards regression models were used to determine predictors, and then, a nomogram was constructed by those predictors. Results A total of 11,814 patients (5293 men and 6251 women) were identified. In multivariate analysis, 14 factors were found to be associated with BO including age, race, marital status, residence location, T category, M category, primary tumor site, histologic type, histologic grade, tumor size, history of alcoholism, chemotherapy, radiotherapy, abdominal pain, and anemia. A nomogram predicting the 90- and 180-day rates of BO was built for the preoperative CRC patients with a C-index of 0.795. Conclusions This study identified 14 BO-related factors, and a statistical model was constructed to predict the onset of BO in preoperative CRC patients. The obtained data may guide decision-making for the intervention of patients at risk for BO