Epigallocatechin gallate modulates ferroptosis through downregulation of tsRNA-13502 in non-small cell lung cancer.

Ferroptosis, an iron-dependent regulated cell death mechanism, holds significant promise as a therapeutic strategy in oncology. In the current study, we explored the regulatory effects of epigallocatechin gallate (EGCG), a prominent polyphenol in green tea, on ferroptosis and its potential therapeutic implications for non-small cell lung cancer (NSCLC). Treatment of NSCLC cell lines with varying concentrations of EGCG resulted in a notable suppression of cell proliferation, as evidenced by a reduction in Ki67 immunofluorescence staining. Western blot analyses demonstrated that EGCG treatment led to a decrease in the expression of glutathione peroxidase 4 (GPX4) and solute carrier family 7 member 11 (SLC7A11) while increasing the levels of acyl-CoA synthetase long-chain family member 4 (ACSL4). These molecular changes were accompanied by an increase in intracellular iron, malondialdehyde (MDA), and reactive oxygen species (ROS), alongside ultrastructural alterations characteristic of ferroptosis. Through small RNA sequencing and RT-qPCR, transfer RNA-derived small RNA 13502 (tsRNA-13502) was identified as a significant target of EGCG action, with its expression being upregulated in NSCLC tissues compared to adjacent non-tumorous tissues. EGCG was found to modulate the ferroptosis pathway by downregulating tsRNA-13502 and altering the expression of key ferroptosis regulators (GPX4/SLC7A11 and ACSL4), thereby promoting the accumulation of iron, MDA, and ROS, and ultimately inducing ferroptosis in NSCLC cells. This study elucidates EGCG's multifaceted mechanisms of action, underscoring the modulation of ferroptosis as a viable therapeutic approach for enhancing NSCLC treatment outcomes.

The global burden and trends of four major types of heart disease, 1990-2019: a systematic analysis for the Global Burden of Disease Study 2019.

OBJECTIVES: The global burden of heart disease is severe and increasing in the coming years. This study aims to analyze the global burden of heart disease. STUDY DESIGN: Rheumatic heart disease (RHD), ischemic heart disease (IHD), hypertensive heart disease (HHD), and non-rheumatic valvular heart disease (NRVHD) were selected and analyzed from the Global Burden of Disease Study 2019. METHODS: The prevalence, deaths, disability-adjusted life years and their corresponding age-standardized rates were obtained from the Global Burden of Disease Study 2019. In addition, estimated annual percentage change was calculated to better assess epidemiological trends. In addition, we performed an age-period-cohort analysis using the Nordpred package in R program to predict death trends over the next 20 years. RESULTS: Globally, the prevalence of four heart diseases (RHD, IHD, HHD, and NRVHD) increased by 70.5%, 103.5%, 137.9%, and 110.0% compared with 1990, respectively. The deaths cases of RHD decreased by 15.6%, whereas IHD, HHD, and NRVHD increased by 60.4%, 76.6%, and 110.6%. Compared with absolute values, their corresponding age-standardized rates only showed a slight increase trend or even decreased in some areas with high sociodemographic index. In the next 20 years, the absolute values of deaths will continue to increase, whereas their age-standardized rates of deaths will flatten out. CONCLUSIONS: Globally, the absolute values of heart disease have increased over the past 30 years and will continue to increase over the next 20 years. Targeted prevention and control strategies and measures need to be developed and improved to reduce this burden.

Polycystic ovary syndrome and the risk of endometrial, ovarian and breast cancer: An updated meta-analysis.

BACKGROUND AND AIMS: This updated meta-analysis aimed to further quantify the risk of endometrial, ovarian, and breast cancer in patients with polycystic ovary syndrome (PCOS), thus providing updated and more reliable estimates. METHODS AND RESULTS: We identified relevant articles by searching electronic databases of PubMed, Embase, Web of Science, and Chinese Biological Medical Literature (CBM) published up to March 20, 2021. The pooled effect estimates and their 95% confidence intervals (CIs) were calculated using the random-effect model or the fixed-effect model. A total of 26 eligible studies were included. We found that PCOS was significantly associated with endometrial cancer (odds ratios [OR]: 3.66, 95%CI: 2.05-6.54, P < 0.001), but not with ovarian or breast cancer (OR: 1.23, 95%CI: 0.99-1.53, P = 0.059; OR: 0.94, 95%CI: 0.78-1.14, P = 0.551, respectively). However, in subgroups of high-quality studies, cohort studies, younger women (54 years or less or premenopausal), and studies with unadjusted body mass index (BMI), PCOS patients had a significantly higher risk of ovarian cancer. CONCLUSION: These results indicated that PCOS is a significant risk factor for endometrial cancer independent of BMI, but not for breast cancer. PCOS may increase the risk of ovarian cancer in younger women.

Peripheral Blood-Based DNA Methylation of Long Non-Coding RNA H19 and Metastasis-Associated Lung Adenocarcinoma Transcript 1 Promoters are Potential Non-Invasive Biomarkers for Gastric Cancer Detection.

INTRODUCTION: The early diagnosis and detection could greatly improve the clinical outcome of gastric cancer (GC) patients. However, the non-invasive biomarkers for GC detection remain to be identified. METHOD: We used online databases (GEPIA, UALCAN, Kaplan-Meier plotter, TIMER, and MEXPRESS) to explore the association between H19 or metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) expression in tissues and the occurrence, development, prognosis, the levels of immune cell infiltration, and methylation of GC; the correlation between mRNA expression and DNA methylation levels of genes were also examined. Methylation levels of H19 or MALAT1 in peripheral blood were compared between 150 GC patients and 100 healthy controls (HCs). Predictive nomograms were constructed among female and male groups for GC diagnosis. The calibration curves, Hosmer-Lemeshow test, and decision curve analysis were also used to examine the nomograms' predictive ability and clinical values. RESULTS: Using multiple online databases, we found that the mRNA expressions of H19 and MALAT1 in tissues were related to the occurrence of GC, and such expressions were associated with immune cell infiltration of GC and negatively correlated with DNA methylation levels of H19 and MALAT1. H19 gene, H19C island, and MALAT1B island, as well as 20 CpG sites were hypermethylated in peripheral blood of GC patients compared with HCs; similar results were also found in female and male groups (P < .05 for all). The combination of H19c3, H19c4, MALAT1b12, and age, as well as the combination of H19b7, H19c1, H19c5, and age in the nomograms could distinguish GC patients from HCs in the female group and male group, respectively. CONCLUSION: We found statistically significant hypermethylation of H19 and MALAT1 promoters in GC patients, and meaningful sensitivity and specificity of MALAT1 and H19 methylation in discriminating GC and HCs were observed in both female and male groups, which indicates that the peripheral blood-based DNA methylation of H19 and MALAT1 could act as potential non-invasive biomarkers for the diagnosis of GC.

Machine learning-based biomarker screening for acute myeloid leukemia prognosis and therapy from diverse cell-death patterns.

Acute myeloid leukemia (AML) exhibits pronounced heterogeneity and chemotherapy resistance. Aberrant programmed cell death (PCD) implicated in AML pathogenesis suggests PCD-related signatures could serve as biomarkers to predict clinical outcomes and drug response. We utilized 13 PCD pathways, including apoptosis, pyroptosis, ferroptosis, autophagy, necroptosis, cuproptosis, parthanatos, entotic cell death, netotic cell death, lysosome-dependent cell death, alkaliptosis, oxeiptosis, and disulfidptosis to develop predictive models based on 73 machine learning combinations from 10 algorithms. Bulk RNA-sequencing, single-cell RNA-sequencing transcriptomic data, and matched clinicopathological information were obtained from the TCGA-AML, Tyner, and GSE37642-GPL96 cohorts. These datasets were leveraged to construct and validate the models. Additionally, in vitro experiments were conducted to substantiate the bioinformatics findings. The machine learning approach established a 6-gene pan-programmed cell death-related genes index (PPCDI) signature. Validation in two external cohorts showed high PPCDI associated with worse prognosis in AML patients. Incorporating PPCDI with clinical variables, we constructed several robust prognostic nomograms that accurately predicted prognosis of AML patients. Multi-omics analysis integrating bulk and single-cell transcriptomics revealed correlations between PPCDI and immunological features, delineating the immune microenvironment landscape in AML. Patients with high PPCDI exhibited resistance to conventional chemotherapy like doxorubicin but retained sensitivity to dasatinib and methotrexate (FDA-approved drugs for other leukemias), suggesting the potential of PPCDI to guide personalized therapy selection in AML. In summary, we developed a novel PPCDI model through comprehensive analysis of diverse programmed cell death pathways. This PPCDI signature demonstrates great potential in predicting clinical prognosis and drug sensitivity phenotypes in AML patients.

Machine learning reveals diverse cell death patterns in lung adenocarcinoma prognosis and therapy.

Cancer cell growth, metastasis, and drug resistance pose significant challenges in the management of lung adenocarcinoma (LUAD). However, there is a deficiency in optimal predictive models capable of accurately forecasting patient prognoses and guiding the selection of targeted treatments. Programmed cell death (PCD) pathways play a pivotal role in the development and progression of various cancers, offering potential as prognostic indicators and drug sensitivity markers for LUAD patients. The development and validation of predictive models were conducted by integrating 13 PCD patterns with comprehensive analysis of bulk RNA, single-cell RNA transcriptomics, and pertinent clinicopathological details derived from TCGA-LUAD and six GEO datasets. Utilizing the machine learning algorithms, we identified ten critical differentially expressed genes associated with PCD in LUAD, namely CHEK2, KRT18, RRM2, GAPDH, MMP1, CHRNA5, TMPRSS4, ITGB4, CD79A, and CTLA4. Subsequently, we conducted a programmed cell death index (PCDI) based on these genes across the aforementioned cohorts and integrated this index with relevant clinical features to develop several prognostic nomograms. Furthermore, we observed a significant correlation between the PCDI and immune features in LUAD, including immune cell infiltration and the expression of immune checkpoint molecules. Additionally, we found that patients with a high PCDI score may exhibit resistance to immunotherapy and standard adjuvant chemotherapy regimens; however, they may benefit from other FDA-supported drugs such as docetaxel and dasatinib. In conclusion, the PCDI holds potential as a prognostic signature and can facilitate personalized treatment for LUAD patients.

Multi-omic profiling reveals potential biomarkers of hepatocellular carcinoma prognosis and therapy response among mitochondria-associated cell death genes in the context of 3P medicine.

Background: Cancer cell growth, metastasis, and drug resistance are major challenges in treating liver hepatocellular carcinoma (LIHC). However, the lack of comprehensive and reliable models hamper the effectiveness of the predictive, preventive, and personalized medicine (PPPM/3PM) strategy in managing LIHC. Methods: Leveraging seven distinct patterns of mitochondrial cell death (MCD), we conducted a multi-omic screening of MCD-related genes. A novel machine learning framework was developed, integrating 10 machine learning algorithms with 67 different combinations to establish a consensus mitochondrial cell death index (MCDI). This index underwent rigorous evaluation across training, validation, and in-house clinical cohorts. A comprehensive multi-omics analysis encompassing bulk, single-cell, and spatial transcriptomics was employed to achieve a deeper insight into the constructed signature. The response of risk subgroups to immunotherapy and targeted therapy was evaluated and validated. RT-qPCR, western blotting, and immunohistochemical staining were utilized for findings validation. Results: Nine critical differentially expressed MCD-related genes were identified in LIHC. A consensus MCDI was constructed based on a 67-combination machine learning computational framework, demonstrating outstanding performance in predicting prognosis and clinical translation. MCDI correlated with immune infiltration, Tumor Immune Dysfunction and Exclusion (TIDE) score and sorafenib sensitivity. Findings were validated experimentally. Moreover, we identified PAK1IP1 as the most important gene for predicting LIHC prognosis and validated its potential as an indicator of prognosis and sorafenib response in our in-house clinical cohorts. Conclusion: This study developed a novel predictive model for LIHC, namely MCDI. Incorporating MCDI into the PPPM framework will enhance clinical decision-making processes and optimize individualized treatment strategies for LIHC patients. Supplementary Information: The online version contains supplementary material available at 10.1007/s13167-024-00362-8.

BNIP3 and DAPK1 methylation in peripheral blood leucocytes are noninvasive biomarkers for gastric cancer.

OBJECTIVE: The objective of this study is to comprehensively investigate the potential value of BNIP3 and DAPK1 methylation in peripheral blood leukocytes as a non-invasive biomarker for the detection of gastric cancer (GC), prediction of chemotherapy efficacy, and prognosis assessment. PATIENTS AND METHODS: Initially, multiple bioinformatic analyses were employed to explore the genetic landscape and biological effects of BNIP3 and DAPK1 in GC tissues. Subsequently, case-control and prospective follow-up studies were conducted to compare the differences in BNIP3 and DAPK1 methylation levels in peripheral blood leukocytes among GC patients and healthy controls, as well as between patients exhibiting sensitivity and resistance to platinum plus fluorouracil treatment, and between patients with varying survival outcomes of GC. Additionally, several predictive nomograms were constructed based on the identified CpG sites and relevant clinical parameters to forecast the occurrence of GC, chemotherapy efficacy, and prognosis. RESULTS: The upregulation of BNIP3 and DAPK1 was found to be associated with the development and poorer survival outcomes of GC. Furthermore, the expression of BNIP3/DAPK1 exhibited an inverse relationship with their DNA methylation levels and demonstrated a positive correlation with immune cell infiltration, as well as the IC50 values of 5-Fluorouracil and Cisplatin in GC tissues. Increased infiltration of macrophages in the high-expression groups was observed to be linked to unfavorable GC survival. In the case-control and follow-up studies, lower methylation levels of BNIP3 and DAPK1 were identified in the peripheral leukocytes of GC patients compared to healthy controls. Hypomethylation was also associated with more aggressive subtypes, diminished chemotherapy efficacy, and poorer survival outcomes in GC. CONCLUSION: The DNA methylation of BNIP3 and DAPK1 in peripheral blood leukocytes holds promise as a novel non-invasive biomarker for predicting the occurrence of GC, chemotherapy efficacy, and prognosis assessment.

Predictive value of peripheral blood leukocytes-based methylation of Long non-coding RNA MALAT1 and H19 in the chemotherapy effect and prognosis of gastric cancer.

BACKGROUND: The predictive value of the methylation of Long non-coding RNA (lncRNA) metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) and H19 promoters in peripheral blood leukocytes as a non-invasive biomarker for the chemotherapy effect and prognosis gastric cancer (GC) is unclear. METHODS: The DNA methylation of H19 and MALAT1 between chemotherapy-sensitive and non-sensitive groups and between groups with better and worse survival of GC was compared using regression analyses. Several predictive nomograms were constructed. The genetic alteration of MALAT1 and H19 and the association between gene expression and immune status in GC were also investigated using bioinformatics analysis. RESULTS: Higher genetic methylations in peripheral blood were noticed in GC groups with poorer survival. The constructed nomograms presented strong predictive values for the chemotherapy effect and 3-year survival of disease-free survival, progression-free survival, and overall survival, with the area under the curve as 0.838, 0.838, 0.912, and 0.925, respectively. Significant correlations between MALAT1 or H19 expression and marker genes of immune checkpoints and immune pathways were noticed. The high infiltration of macrophages in H19-high and low infiltration of CD8+ T cells in MALAT1-high groups were associated with worse survival of GC. CONCLUSIONS: MALAT1 and H19 have the potential to predict the chemotherapy response and clinical outcomes of GC.

Identification and validation of a cellular senescence-related lncRNA signature for prognostic prediction in patients with multiple myeloma.

Multiple myeloma (MM) is the second most common hematologic malignancy, which primarily occurs in the elderly. Cellular senescence is considered to be closely associated with the occurrence and progression of malignant tumors including MM, and lncRNA can mediate the process of cellular senescence by regulating key signaling pathways such as p53/p21 and p16/RB. However, the role of cellular senescence related lncRNAs (CSRLs) in MM development has never been reported. Herein, we identified 11 CSRLs (AC004918.5, AC103858.1, AC245100.4, ACBD3-AS1, AL441992.2, ATP2A1-AS1, CCDC18-AS1, LINC00996, TMEM161B-AS1, RP11-706O15.1, and SMURF2P1) to build the CSRLs risk model, which was confirmed to be highly associated with overall survival (OS) of MM patients. We further demonstrated the strong prognostic value of the risk model in MM patients receiving different regimens, especially for those with three-drug combination of bortezomib, lenalidomide, and dexamethasone (VRd) as first-line therapy. Not only that, our risk model also excels in predicting the OS of MM patients at 1, 2, and 3 years. In order to verify the function of these CSRLs in MM, we selected the lncRNA ATP2A1-AS1 which presented the largest expression difference between high-risk groups and low-risk groups for subsequent analysis and validation. Finally, we found that down-regulation of ATP2A1-AS1 can promote cellular senescence in MM cell lines. In conclusion, the CSRLs risk model established in present study provides a novel and more accurate method for predicting MM patients' prognosis and identifies a new target for MM therapeutic intervention.

Global, regional, and national deaths, disability-adjusted life years, years lived with disability, and years of life lost for the global disease burden attributable to second-hand smoke, 1990-2019: A systematic analysis for the Global Burden of Disease Study.

BACKGROUND: Smoke-free policies have led to a decline in smoking prevalence. Nevertheless, as the global population grows, more non-smokers are exposed to second-hand smoke (SHS) hazards. Mitigating SHS hazards requires a systematic analysis of the global disease burden attributable to SHS. METHODS: Data on SHS was extracted from the Global Burden of Disease Study 2019. First, we measured the disease burden of SHS by the number of cases and age-standardized rates of deaths, disability-adjusted life years (DALYs), years lived with disability (YLDs), and years of life lost (YLLs) from 1990 to 2019. Second, trends in the disease burden of SHS in different periods were estimated based on the annual percentage change (APC) by joinpoint regression analysis. Finally, using histogram plots, world maps, Pearson correlation analysis, and population attributable fraction (PAF), we conducted a stratified analysis of SHS exposure by sex, age, geographic location, sociodemographic index (SDI) level, and disease. RESULTS: The number of deaths caused by SHS remained stable between 1990 and 2019, and the number of YLDs more than doubled in three decades. In contrast, the number of DALYs and YLLs caused by SHS decreased. The declining trend in deaths (APC = -1.42 % [95 % UI -1.79 %, -1.05 %]), DALYs (APC = -1.91 % [95 % UI -2.15 %, -1.67 %]), and YLLs (APC = -1.28 % [95 % UI -1.93 %, -0.64 %]) had slowed down in recent years, while SHS-related YLDs were still increasing (APC = 1.84 % [95 % UI 0.74 %, 2.96 %]). From 2010 to 2019, we found that SHS exposure increased the risk of tracheal, bronchus, and lung cancer (PAF increased by 11.75 %), breast cancer (PAF increased by 5.36 %), diabetes mellitus (PAF increased by 8.24 %), and ischemic heart disease (PAF increased by 4.46 %). In addition, the disease burden caused by SHS was highest in middle SDI and low-middle SDI countries. CONCLUSION: The global disease burden attributable to SHS is still severe, and policymakers need to implement more effective measures to reduce the harm of SHS.

Global, regional, and national burden of digestive diseases: findings from the global burden of disease study 2019.

Background: The global burden of digestive diseases has been rising in the last 30 years. The rates and trends of incidence, deaths, and disability-adjusted life-years (DALYs) for digestive diseases need to be investigated. Methods: We extracted the data on overall digestive diseases and by cause between 1990-2019 from the Global Burden of Diseases 2019 website, including the absolute number and the corresponding age-standardized rates of incidence (ASIR), deaths (ASDR), and DALYs (ASDALYs). Results: Globally, the incident cases, deaths, and DALYs of digestive diseases in 2019 increased by 74.44, 37.85, and 23.46%, respectively, compared with that in 1990, with an increasing ASIR of 0.09%, as well as decreasing ASDR and ASDALYs of 1.38 and 1.32% annually. The sociodemographic index (SDI) of overall digestive diseases showed a slight increase in ASIR from low to middle-low regions. The downtrend in ASDR and ASDALYs was found in all SDI regions. The burden of incidence was higher in females, while the burden of deaths and DALYs was higher in males for the overall digestive diseases and most causes. The estimated annual percentage changes were significantly associated with the baseline ASIR, ASDR, and ASDALYs for the overall digestive diseases, and the negative correlations between ASDR, ASDALYs, and human development index both in 1990 (R = -0.68, R = -0.69) and 2019 (R = -0.71, R = -0.73) were noticed. Conclusion: The findings indicate that digestive diseases remain a significant public health burden, with substantial variation across countries, sexes, and age groups. Therefore, implementing age, gender, and country-specific policies for early screening and targeted interventions could significantly reduce the global burden of digestive diseases.

Significantly correlation between tourism and COVID-19: evidence from 178 countries and territories.

INTRODUCTION: The high development of tourism is considered a factor that facilitates the global spread of infectious diseases. The association between tourism and the epidemic of coronavirus diseases 2019 (COVID-19) remains unclear. METHODOLOGY: We retrieved the data of COVID-19 in 178 countries/territories from the Center for Systems Science and Engineering at Johns Hopkins University. Data on tourism indicators were collected from the World Tourism Organization. We used Spearman's correlation analysis to explore the association between tourism and the epidemic of COVID-19. RESULTS: We find that international tourism expenditure, international tourism receipts, international tourist arrivals, and international tourism exports were significantly correlated with the total number of cases (rs=0.86, rs=0.79, rs=0.80, rs=0.81, respectively), the daily growth of cases of COVID-19 (rs=0.84, rs=0.76, rs=0.78, rs=0.78, respectively), and the number of cases (per million persons) (rs=0.52, rs=0.53, rs=0.36, rs=0.53, respectively) (p < 0.0001 for all), especially in places with high-income. Tourism as percentage of exports was slightly associated with the total number of cases and the daily growth of cases (rs=-0.33, rs=-0.33) (p < 0.0001 for both). CONCLUSIONS: The clinical and public health care providers must realize the potential for the transmission of infections across regions and put more effort to prevent and respond to future infections.

Multimolecular characteristics of cell-death related hub genes in human cancers: a comprehensive pan-cancer analysis.

Failure of the normal process of cell death pathways contributes to the defection of immune systems and the occurrence of cancers. The key genes, the multimolecular mechanisms, and the immune functions of these genes in pan-cancers remain unclear. Using online databases of The Cancer Genome Atlas, GEPIA2, TISIDB, HPA, Kaplan-Meier Plotter, PrognoScan, cBioPortal, GSCALite, TIMER, and Sangerbox, we identified the key genes from the six primary cell death-related pathways and performed a comprehensive analysis to investigate the multimolecular characteristics and immunological functions of the hub genes in 33 human cancers. We identified five hub genes in the six primary cell death-related pathways (JUN, NFKB1, CASP3, PARP1, and TP53). We found that CASP3, PARP1, and TP53 were overexpressed in 28, 23, and 27 cancers. The expression of the five genes was associated with the development and prognosis of many cancers. Particularly, JUN, NFKB1, CASP3, and TP53 have prognostic values in Brain Lower Grade Glioma (LGG), while PARP1 and CASP3 could predict the survival outcomes in Adrenocortical carcinoma (ACC). In addition, an extensive association between five genes' expression, DNA methylation, and tumor-immune system interactions was noticed. The five cell death-related hub genes could function as potential biomarkers for various cancers, particularly LGG and ACC. The immunological function analysis of the five genes also proposes new targets for developing immunosuppressants and improving the immunotherapy efficacy of cancers. However, further extensive clinical and experimental research are required to validate their clinical values.

Influence of age and gender on the epidemic of COVID-19 : Evidence from 177 countries and territories-an exploratory, ecological study.

BACKGROUND: The pandemic of coronavirus disease 2019 (COVID-19) is spreading worldwide with an uncertain ultimate impact on every aspect of human society. Recognizing the groups with higher susceptibility and fatality are in urgent need. METHODS: We retrieved the total number of confirmed incident and death cases of COVID-19 in 177 countries/territories from the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University (JHU). Data of age and gender composition were collected from the United Nations Department of Economic and Social Affairs. Spearman's correlation analysis was used to explore the association between the composition of age and gender and the incidence rate (IRC), case fatality rate (CFRC), and mortality rate of COVID-19 (MRC). Multiple comparisons were adjusted by the Bonferroni method, and the threshold p-value was set as p < 0.01. Software SPSS 23.0, ArcGIS 10.6, and GraphPad Prism 8.0 were used to generate our results. RESULTS: Median age was positively correlated to IRC, CFRC and MRC (rs = 0.60; rs = 0.27; rs = 0.61, p < 0.0001 for all). The age-dependent correlation between people over 65 years of age with IRC was higher in females, while the correlation between age distribution and CFRC as well as MRC was higher in males (p < 0.0001 for all). Besides, we found the age-gender-dependent differences were correlated to IRC in places with high income and associated with CFRC in non-high income countries/territories. CONCLUSION: The correlation between the composition of age and gender and the epidemic characteristics of COVID-19 confirmed previous points that females are more susceptible to COVID-19. The results remind us that more attention should be paid to male patients, particularly those over 65 years old for enhanced clinical management.

Associations of BNIP3 and DAPK1 gene polymorphisms with disease susceptibility, clinicopathologic features, anxiety, and depression in gastric cancer patients.

The purpose of this study is to explore the associations of BNIP3 and DAPK1 polymorphisms with disease susceptibility, clinicopathologic characteristics, depression, and anxiety in gastric cancer (GC) patients. In this study, 150 GC patients and 100 healthy controls were recruited. 1000 Genomes database and Haploview 4.0 software were used to select tag SNPs. Improved multiplex ligase detection reaction was used for genotyping. Data were analyzed using Chi-square test (χ2 test) and univariate and multivariate logistic regression. The results demonstrated that the rs10781582 of BNIP3 in the dominant model was associated with a reduced risk of GC in the younger group (P BH = 0.015), and the minor allele G of rs1329600 at DAPK1 was associated with reduced risk of GC (P BH = 0.018). In the stratified analysis, the rs3793742 and rs10781582 of BNIP3 in the dominant model were associated with gender and age of GC patients, respectively (rs3793742: P BH = 0.033; rs10781582: P BH = 0.030). The rs10781582 of BNIP3 in the dominant model was correlated with depression in GC patients (P BH = 0.003). However, no association was found between BNIP3 and DAPK1 polymorphisms and differentiation degree, TNM stage, lymph node metastases, visceral metastasis, and anxiety. In summary, polymorphisms of BNIP3 and DAPK1 were associated with a protective effect against GC. So far, this is the first study to explore the association between BNIP3 and DAPK1 gene polymorphism and GC risk, which may provide new insight about biologic mechanisms of GC pathogenesis.

Prognostic Values of E2F1/2 Transcriptional Expressions in Chromophobe Renal Cell Carcinoma Patients: Evidence from Bioinformatics Analysis.

BACKGROUND: Numerous studies on the E2F transcription factors have led to increasing insights that E2Fs could be an important driver of the formation and progression of many human cancers. Little is known about the function of distinct E2Fs in chromophobe renal cell carcinoma (chRCC). METHODS: We utilized the UALCAN, GEPIA, Cancer Genome Atlas (TCGA) database, cBioPortal, Metascape, STRING, Cytoscape, GeneMANIA, TIMER, TISIDB, GSCALite, and MEXPRESS databases to investigate the transcription level, genetic alteration, methylation, and biological function of E2Fs in chRCC patients, and its association with the occurrence, progress, prognosis, and immune cell infiltration in patients with chRCC. RESULTS: We found that E2F1/2/4/7/8 were more expressed in chRCC tissues than in normal tissues, while the expression of E2F5/6 was lower in the former than in the latter, and the expression levels of E2F1/2/4/5/6//7/8 were also associated with the histological parameters of chRCC, including T-stage and N-stage. Higher expression of E2F1/2/7/8 was found to be significantly correlated with worse overall survival (OS) in chRCC patients. Cox regression and time-dependent ROC analysis further suggested that E2F1/2 could be the potential independent biomarkers for chRCC prognosis. Besides, a moderate mutation rate of E2Fs (34%) was noticed in chRCC, and the genetic mutations in E2Fs were associated with poor survival of chRCC patients. We noticed that the expression of E2Fs was statistically correlated with the immune cell infiltration in chRCC. Moreover, we also found that the expression of E2F1 was significantly correlated with tumor-infiltrating lymphocytes and immunomodulators, E2F7 expression was associated with MHC molecules, and the expression of E2F1/8 was correlated to their methylation levels. CONCLUSION: Our results provide novel insights for selecting the prognostic biomarkers for chRCC and suggest that E2F1/2 could act as potential prognostic biomarkers for the survival of chRCC patients. However, more in-depth experiments are required to identify the underlying mechanisms and verify the clinical value of E2F1/2 in the prognosis of chRCC.

More effective strategies are required to strengthen public awareness of COVID-19: Evidence from Google Trends.

BACKGROUND: The outbreak of coronavirus disease 2019 (COVID-19) has posed stress on the health and well-being of both Chinese people and the public worldwide. Global public interest in this new issue largely reflects people's attention to COVID-19 and their willingness to take precautionary actions. This study aimed to examine global public awareness of COVID-19 using Google Trends. METHODS: Using Google Trends, we retrieved public query data for terms of "2019-nCoV + SARS-CoV-2 + novel coronavirus + new coronavirus + COVID-19 + Corona Virus Disease 2019" between the 31st December 2019 and the 24th February 2020 in six major English-speaking countries, including the USA, the UK, Canada, Ireland, Australia, and New Zealand. Dynamic series analysis demonstrates the overall change trend of relative search volume (RSV) for the topic on COVID-19. We compared the top-ranking related queries and sub-regions distribution of RSV about COVID-19 across different countries. The correlation between daily search volumes on the topic related to COVID-19 and the daily number of people infected with SARS-CoV-2 was analyzed. RESULTS: The overall search trend of RSV regarding COVID-19 increased during the early period of observing time and reached the first apex on 31st January 2020. A shorter response time and a longer duration of public attention to COVID-19 was observed in public from the USA, the UK, Australia, and Canada, than that in Ireland and New Zealand. A slightly positive correlation between daily RSV about COVID-19 and the daily number of confirmed cases was observed (P < 0.05). People across countries presented a various interest to the RSV on COVID-19, and public awareness of COVID-19 was different in various sub-regions within countries. CONCLUSIONS: The results suggest that public response time to COVID-19 was different across countries, and the overall duration of public attention was short. The current study reminds us that governments should strengthen the publicity of COVID-19 nationally, strengthen the public's vigilance and sensitivity to COVID-19, inform public the importance of protecting themselves with enough precautionary measures, and finally control the spread of COVID-19 globally.

Overexpression of Rictor protein and Rictor-H. pylori interaction has impact on tumor progression and prognosis in patients with gastric cancer.

INTRODUCTION: Growing evidence indicates that Rictor (Rapamycin-insensitive companion of mTOR) is overexpressed across several malignancies and associated with poor survival. However, only limited data indicate that Rictor plays a role in gastric cancer (GC). We sought to explore the prognostic value of Rictor in GC and present interaction analysis between Rictor expression and H. pylori status regarding their effects over the prognosis of GC patient. MATERIALS AND METHODS: 250 GC tissues and 124 lymph node metastases were collected for the detection of Rictor by immunohistochemistry. Cox regression model was used to assess the association between Rictor expression and patient prognosis. Functional experiments were examined in transfected cells using Rictor siRNA. Additive and multiplicative interactions of Rictor and H. pylori were evaluated. RESULTS: In this study, the positive rate of Rictor was 51.6% (129/150) in GC tissues. Multivariate analyses showed that Rictor was independent unfavorable predictor for OS (HR = 1.554, 95% CI = 1.076-2.244, P = 0.019) and DFS (HR = 1.556, 95% CI = 1.081-2.240, P = 0.017). Patients with upregulated Rictor in the primary tumor and lymph node metastases had the worst prognosis. We observed significant additive and multiplicative interactions between Rictor expression and H. pylori status for OS and DFS (P < 0.05). Our in vitro experiment showed that knockdown of Rictor could suppress cell proliferation, induce apoptosis and inhibit tumor migration and invasion. CONCLUSION: Our results demonstrate that Rictor, acting as an oncogene, might be a potential prognostic biomarker and therapeutic target in GC. We suggest that Rictor expression and H. pylori status may be a prognostic marker in gastric cancer.