Systematic analysis of the cuprotosis in tumor microenvironment and prognosis of gastric cancer.

Cuprotosis is a new programmed cell death related to cancer. However, the characteristics of cuprotosis in gastric cancer (GC) remain unknown. Ten cuprotosis molecules from 1544 GC patients were used to identify three GC molecular genotypes. Cluster A was characterized by the best clinical outcome and was significantly enriched in metabolic signaling pathways. Cluster B exhibited elevated immune activation, high immune stroma scores and was significantly enriched in tumor immune signaling pathways. Cluster C was characterized by severe immunosuppression and poor response to immunotherapy. Notably, the citrate cycle, cell cycle, and p53 signaling pathways were enriched in the differentially expressed genes among the three subtypes, which were critical signaling pathways for cell death. We also developed a cuprotosis signature risk score that could accurately predict the survival, immunity, and subtype of GC. This study presents a systematic analysis of cuprotosis molecules and provides new immunotherapeutic targets for GC patients.

An antigen processing and presentation signature for prognostic evaluation and immunotherapy selection in advanced gastric cancer.

Objective: The aim of the study was to propose a signature based on genes associated with antigen processing and presentation (APscore) to predict prognosis and response to immune checkpoint inhibitors (ICIs) in advanced gastric cancer (aGC). Background: How antigen presentation-related genes affected the immunotherapy response and whether they could predict the clinical outcomes of the immune checkpoint inhibitor (ICI) in aGC remain largely unknown. Methods: In this study, an aGC cohort (Kim cohort, RNAseq, N=45) treated by ICIs, and 467 aGC patients from seven cohorts were conducted to investigate the value of the APscore predicting the prognosis and response to ICIs. Subsequently, the associations of the APscore with the tumor microenvironment (TME), molecular characteristics, clinical features, and somatic mutation variants in aGC were assessed. The area under the receiver operating characteristic curve (AUROC) of the APscore was analyzed to estimate response to ICIs. Cox regression or Log-rank test was used to estimate the prognosis of aGC patients. Results: The APscore constructed by principal component analysis algorithms was an effective predictive biomarker of the response to ICIs in the Kim cohort and 467 aGC patients (Kim: AUC =0.85, 95% CI: 0.69-1.00; 467 aGC: AUC =0.69, 95% CI: 0.63-0.74). The APscore also was a prognostic biomarker in 467 aGC patients (HR=1.73, 95% CI: 1.21-2.46). Inhibitory immunity, decreased TMB and low stromal scores were observed in the high APscore group, while activation of immunity, increased TMB, and high stromal scores were observed in the low APscore group. Next, we evaluated the value of several central genes in predicting the prognosis and response to ICIs in aGC patients, and verified them using immunogenic, transcriptomic, genomic, and multi-omics methods. Lastly, a predictive model built successfully discriminated patients with vs. without immunotherapy response and predicted the survival of aGC patients. Conclusions: The APscore was a new biomarker for identifying high-risk aGC patients and patients with responses to ICIs. Exploration of the APscore and hub genes in multi-omics GC data may guide treatment decisions.

Impacts of psychological resilience on self-efficacy and quality of life in patients with diabetic foot ulcers: a prospective cross-sectional study.

BACKGROUND: Patients with diabetic foot ulcer (DFU) usually have a poor quality of life (QoL) and self-efficacy, which is affected by many risk factors. However, the role of psychological resilience in QoL and self-efficacy in DFU patients has remained unclear. METHODS: This prospective cross-sectional study was performed in a single center from January 2018 to February 2020. A total of 98 DFU patients were enrolled in this study. Some demographic and clinical data were prospectively collected from participants. The psychological resilience of participants was assessed by Connor-Davidson resilience scale (CD-RISC). Self-efficacy was also assessed using the diabetes management self-efficacy scale (DMSES) and QoL was assessed by the 36-item short-form (SF-36) health survey. Univariable and multivariable linear regression were used to analyze the risk factors of self-efficacy and QoL. Then, logistic regression was used to analyze the predictors of psychological resilience among the participants. RESULTS: A CD-RISC score of more than 85 points was defined as high psychological resilience in this study; there were 28 participants diagnosed with high psychological resilience and 70 patients with low psychological resilience. Those with high psychological resilience had significantly higher self-efficacy, general health, vitality, social functioning, role emotional, and mental health than those with low psychological resilience. According to multivariable linear regression, low psychological resilience and older age were identified as risk factors of self-efficacy. On the contrary, low psychological resilience, older age, lower perceived social support and higher level of glycated hemoglobin were identified as risk factors of QoL. Finally, males had lower psychological resilience than females and those receiving more social support had higher psychological resilience than participants receiving less social support. CONCLUSIONS: Some risk factors of QoL and self-efficacy were identified in this study and these results may provide some evidence for the improvement of QoL and self-efficacy in DFU patients. Being female and receiving higher social support were shown to have potential for improving psychological resilience in DFU patients.

Fangcang shelter hospitals are a One Health approach for responding to the COVID-19 outbreak in Wuhan, China.

In February 2020, the exponential growth of COVID-19 cases in Wuhan city posed a huge economic burden to local medical systems. Consequently, Wuhan established Fangcang Shelter hospitals as a One Health approach for responding to and containing the COVID-19 outbreak by isolating and caring for mild-to-moderate cases. However, it is unclear to what degree the hospitals contained COVID-19. This study performed an interrupted time series analysis to compare the number of new confirmed cases of COVID-19 before and after the operation of Fangcang Shelter hospitals. The initial number of confirmed cases in Wuhan increased significantly by 68.54 cases per day prior to February 4, 2020. Compared with the number of cases noted 20 days before the use of Fangcang Shelter hospitals, a sustained reduction in the number of confirmed cases (trend change, -125.57; P < 0.0001) was noted 41 days after the use of the hospitals. Immediate-level changes were observed for confirmed cases (level change, 725.97; P = 0.025). These changes led to an estimated 5148 fewer confirmed cases (P < 0.0001). According to the mean confirmed cases of 395.71 per day before the intervention, we estimated that Wuhan had advanced the terminal phase of COVID-19 by 13 days. Furthermore, immediately after introduction of Fangcang Shelter Hospitals on February 5, the reproduction number dropped rapidly, from a pre-introduction rate of 4.0 to 2.0. The Fangcang Shelter hospitals most likely to reversed the epidemic trend of COVID-19 while a containment strategy was implemented in Wuhan. In a One Health perspective, Fangcang Shelter hospitals, with their functions of isolation and treatment of confirmed COVID-19 patients, engaging professionals from many disciplines, such as medicine, engineering, architecture, psychology, environmental health, and social sciences. The results of this study provide a valuable reference for health policy makers in other countries.

Epidemiology of 2019 novel coronavirus in Jiangsu Province, China after wartime control measures: A population-level retrospective study.

BACKGROUND: A novel coronavirus emerged in China in December 2019, and human-to-human transmission was previously identified. This study aimed to compare the epidemiological characteristics in Jiangsu Province and assess whether so-called wartime control measures changed the trend of coronavirus disease 2019 (COVID-19) in the province. METHODS: Epidemiological data were obtained from the websites of China's Bureau of Health and the People's Government of Jiangsu Province and informal online sources from January 22 to February 20, 2020. RESULTS: The cumulative number of patients in Jiangsu Province (over 79 million people) was 613. The number of daily confirmed new cases reached the inflection point on January 31 with the maximum of 39 cases. The temporal number of patients peaked from January 29 to February 9. The proportion of confirmed cases who were residents or travelers to Hubei Province was 100.0%-58.8% before January 31 and then gradually declined. The proportion of close contacts increased gradually from January 27 to February 17. The geographical distribution of COVID-2019 cases showed that all 13 cites reported confirmed new cases after only five days of the first confirmed new case in Suzhou. The cases were concentrated in Nanjing, Suzhou, and Xuzhou with a high population density (over eight million people). The epidemiological features of COVID-2019 cases in Wuxi, Jiangsu showed that seven confirmed cases were tourists from others areas beyond Hubei Province. The longest incubation period of COVID-2019 was 19 days based on the onset of laboratory-confirmed cases. CONCLUSION: The number of daily confirmed new cases in Jiangsu Province peaked around January 31 and then declined. This result emphasized that wartime control measures, such as putting cities on lockdown to limit population mobility in Jiangsu Province, resulted in dramatic reductions in COVID-19 cases.