Prediction of esophageal cancer risk based on genetic variants and environmental risk factors in Chinese population.

BACKGROUND: Results regarding whether it is essential to incorporate genetic variants into risk prediction models for esophageal cancer (EC) are inconsistent due to the different genetic backgrounds of the populations studied. We aimed to identify single-nucleotide polymorphisms (SNPs) associated with EC among the Chinese population and to evaluate the performance of genetic and non-genetic factors in a risk model for developing EC. METHODS: A meta-analysis was performed to systematically identify potential SNPs, which were further verified by a case-control study. Three risk models were developed: a genetic model with weighted genetic risk score (wGRS) based on promising SNPs, a non-genetic model with environmental risk factors, and a combined model including both genetic and non-genetic factors. The discrimination ability of the models was compared using the area under the receiver operating characteristic curve (AUC) and the net reclassification index (NRI). The Akaike information criterion (AIC) and Bayesian information criterion (BIC) were used to assess the goodness-of-fit of the models. RESULTS: Five promising SNPs were ultimately utilized to calculate the wGRS. Individuals in the highest quartile of the wGRS had a 4.93-fold (95% confidence interval [CI]: 2.59 to 9.38) increased risk of EC compared with those in the lowest quartile. The genetic or non-genetic model identified EC patients with AUCs ranging from 0.618 to 0.650. The combined model had an AUC of 0.707 (95% CI: 0.669 to 0.743) and was the best-fitting model (AIC = 750.55, BIC = 759.34). The NRI improved when the wGRS was added to the risk model with non-genetic factors only (NRI = 0.082, P = 0.037). CONCLUSIONS: Among the three risk models for EC, the combined model showed optimal predictive performance and can help to identify individuals at risk of EC for tailored preventive measures.

A polygenetic risk score combined with environmental factors better predict susceptibility to hepatocellular carcinoma in Chinese population.

AIMS: This study aimed to investigate environmental factors and genetic variant loci associated with hepatocellular carcinoma (HCC) in Chinese population and construct a weighted genetic risk score (wGRS) and polygenic risk score (PRS). METHODS: A case-control study was applied to confirm the single nucleotide polymorphisms (SNPs) and environmental variables linked to HCC in the Chinese population, which had been screened by meta-analyses. wGRS and PRS were built in training sets and validation sets. Area under the curve (AUC), net reclassification improvement (NRI), integrated discrimination improvement (IDI), Akaike information criterion (AIC), and Bayesian information criterion (BIC) were applied to evaluate the performance of the models. RESULTS: A total of 13 SNPs were included in both risk prediction models. Compared with wGRS, PRS had better accuracy and discrimination ability in predicting HCC risk. The AUC for PRS in combination with drinking history, cirrhosis, HBV infection, and family history of HCC in training sets and validation sets (AUC: 0.86, 95% CI: 0.84-0.89; AUC: 0.85, 95% CI: 0.81-0.89) increased at least 20% than the AUC for PRS alone (AUC: 0.63, 95% CI: 0.60-0.67; AUC: 0.65, 95% CI: 0.60-0.71). CONCLUSIONS: A novel model combining PRS with alcohol history, HBV infection, cirrhosis, and family history of HCC could be applied as an effective tool for risk prediction of HCC, which could discriminate at-risk individuals for precise prevention.

ncRNADrug: a database for validated and predicted ncRNAs associated with drug resistance and targeted by drugs.

Drug resistance is a major barrier in cancer treatment and anticancer drug development. Growing evidence indicates that non-coding RNAs (ncRNAs), especially microRNAs (miRNAs), long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs), play pivotal roles in cancer progression, therapy, and drug resistance. Furthermore, ncRNAs have been proven to be promising novel therapeutic targets for cancer treatment. Reversing dysregulated ncRNAs by drugs holds significant potential as an effective therapeutic strategy for overcoming drug resistance. Therefore, we developed ncRNADrug, an integrated and comprehensive resource that records manually curated and computationally predicted ncRNAs associated with drug resistance, ncRNAs targeted by drugs, as well as potential drug combinations for the treatment of resistant cancer. Currently, ncRNADrug collects 29 551 experimentally validated entries involving 9195 ncRNAs (2248 miRNAs, 4145 lncRNAs and 2802 circRNAs) associated with the drug resistance of 266 drugs, and 32 969 entries involving 10 480 ncRNAs (4338 miRNAs, 6087 lncRNAs and 55 circRNAs) targeted by 965 drugs. In addition, ncRNADrug also contains associations between ncRNAs and drugs predicted from ncRNA expression profiles by differential expression analysis. Altogether, ncRNADrug surpasses the existing related databases in both data volume and functionality. It will be a useful resource for drug development and cancer treatment. ncRNADrug is available at http://www.jianglab.cn/ncRNADrug.

S100P as a potential biomarker for immunosuppressive microenvironment in pancreatic cancer: a bioinformatics analysis and in vitro study.

BACKGROUND: Immunosuppression is a significant factor contributing to the poor prognosis of cancer. S100P, a member of the S100 protein family, has been implicated in various cancers. However, its role in the tumor microenvironment (TME) of pancreatic cancer remains unclear. This study aimed to investigate the potential impact of S100P on TME characteristics in patients with pancreatic cancer. METHODS: Multiple data (including microarray, RNA-Seq, and scRNA-Seq) were obtained from public databases. The expression pattern of S100P was comprehensively evaluated in RNA-Seq data and validated in four different microarray datasets. Prognostic value was assessed through Kaplan-Meier plotter and Cox regression analyses. Immune infiltration levels were determined using the ESTIMATE and ssGSEA algorithms and validated at the single-cell level. Spearman correlation test was used to examine the correlation between S100P expression and immune checkpoint genes, and tumor mutation burden (TMB). DNA methylation analysis was performed to investigate the change in mRNA expression. Reverse transcription PCR (RT-PCR) and immunohistochemical (IHC) were utilized to validate the expression using five cell lines and 60 pancreatic cancer tissues. RESULTS: This study found that S100P was differentially expressed in pancreatic cancer and was associated with poor prognosis (P < 0.05). Notably, S100P exhibited a significant negative-correlation with immune cell infiltration, particularly CD8 + T cells. Furthermore, a close association between S100P and immunotherapy was observed, as it strongly correlated with TMB and the expression levels of TIGIT, HAVCR2, CTLA4, and BTLA (P < 0.05). Intriguingly, higher S100P expression demonstrated a negative correlation with methylation levels (cg14323984, cg27027375, cg14900031, cg14140379, cg25083732, cg07210669, cg26233331, and cg22266967), which were associated with CD8 + T cells. In vitro RT-PCR validated upregulated S100P expression across all five pancreatic cancer cell lines, and IHC confirmed high S100P levels in pancreatic cancer tissues (P < 0.05). CONCLUSION: These findings suggest that S100P could serve as a promising biomarker for immunosuppressive microenvironment, which may provide a novel therapeutic way for pancreatic cancer.

Human Proteome Microarray identifies autoantibodies to tumor-associated antigens as serological biomarkers for the diagnosis of hepatocellular carcinoma.

The identification of the high-efficiency and non-invasive biomarkers for hepatocellular carcinoma (HCC) detection is urgently needed. This study aims to screen out potential autoantibodies to tumor-associated antigens (TAAbs) and to assess their diagnostic value for HCC. Fifteen potential TAAbs were screened out from the Human Proteome Microarray by 30 HCC sera and 22 normal control sera, of which eight passed multiple-stage validations by ELISA with a total of 1625 human serum samples from normal controls (NCs) and patients with HCC, liver cirrhosis, chronic hepatitis B, gastric cancer, esophageal cancer, and colorectal cancer. Finally, an immunodiagnostic model including six TAAbs (RAD23A, CAST, RUNX1T1, PAIP1, SARS, PRKCZ) was constructed by logistic regression, and yielded the area under curve (AUC) of 0.835 and 0.788 in training and validation sets, respectively. The serial serum samples from HCC model mice were tested to explore the change in TAAbs during HCC formation, and an increasing level of autoantibodies was observed. In conclusion, the panel of six TAAbs can provide potential value for HCC detection, and the strategy to identify novel serological biomarkers can also provide new clues in understanding immunodiagnostic biomarkers.

Analysis of the disease burden trend of malignant tumors of the female reproductive system in China from 2006 to 2020.

BACKGROUND: Malignant tumors of reproductive system seriously threaten women's life and health. We analyzed the changes in mortality and disease burden of cervical cancer, uterine cancer and ovarian cancer in China from 2006 to 2020 to provide a basis for formulating scientific prevention and control measures. METHODS: Annual death data for cervical cancer, uterine cancer and ovarian cancer were collected from the Chinese Cause of Death Surveillance. The crude mortality rate (CMR), age-standardized mortality rate (ASMR), annual percentage change (APC), and average APC (AAPC) were applied to analyze the trend of mortality. Loss of life expectancy (LLE) and years of life lost (YLL) were used to assess disease burden. RESULTS: From 2006 to 2020, there was no significant change in the total ASMR and standardized YLL rates of malignant tumors of the reproductive system, leading to an average LLE of 0.18 years. The YLL rate was the highest in the 55-59 age group. The mortality rate and disease burden of the three types of cancer have changed from uterine cancer higher than cervical cancer and ovarian cancer in 2006 to cervical cancer higher than ovarian cancer and uterine cancer in 2020. The ASMR and standardized YLL rate of uterine cancer showed a downward trend, and AAPC was - 5.21% (- 9.31% ~ - 0.91%) and - 6.07% (- 9.45% ~ - 2.58%), respectively. The mortality rates of cervical cancer and ovarian cancer remain high. CONCLUSION: The mortality and disease burden of malignant tumors of the female reproductive system in China are still at a high level. It is necessary to improve screening and prevention strategies as soon as possible, improve the techniques of diagnosis and treatment, and take adequate measures to protect women's life and health.

Malignant tumors of the female reproductive system are the leading causes of women's mortality worldwide, mainly including cervical cancer, uterine cancer and ovarian cancer. Numerous studies have reported mortality changes in the three primary reproductive system cancers among different countries, with inconsistent temporal trends. In 2020, almost 17.51% of malignant tumors of the female reproductive system deaths occurred in China because of the large population base and severe aging. However, there are limited studies on the disease burden of malignant tumors of the female reproductive system in China. This study analyzed the mortality, YLL and LLE of cervical cancer, uterine cancer and ovarian cancer using the National Death Cause Surveillance Dataset from 2006 to 2020. The findings revealed that mortality and disease burden of malignant tumors of the reproductive system showed no significant change. The mortality and disease burden of uterine cancer decreased significantly, but that of cervical cancer and ovarian cancer remain high. Cervical cancer has a higher mortality and disease burden than uterine cancer and ovarian cancer, making it the most severe malignant tumor of the female reproductive system. Screening and HPV vaccination will reduce the mortality and disease burden of cervical cancer in China, but this effect will take many years to manifest. Screening and prevention strategies for high-risk groups of uterine cancer and ovarian cancer should be established as soon as possible. In summary, the management and monitoring of malignant tumors of the female reproductive system should be strengthened.

DNA methylation dynamics associated with long-term isolation of simulated space travel.

Long-term isolation is one of the risk factors that astronauts will encounter in spaceflight. At present, few researches have explored DNA methylation dynamics during long-term isolation. In this study, using time series DNA methylation data from "Mars-500" mission, we conducted a multi-step analysis to investigate the characteristics and dynamic patterns of DNA methylation as well as their functional insights during long-term isolation. The results showed that genome-wide methylation changes were minimal. In the six identified DNA methylation dynamic patterns, most of significantly fluctuating CpG sites could be returned to the baseline in post-isolation, and the remaining sites persistently decreased during isolation. Next, functional enrichment analysis of genes with each pattern revealed strong functional specificity. Some patterns were also significantly associated with nervous system diseases, digestive system diseases and cancers. In conclusion, the DNA methylation dynamics during long-term isolation have great functional significance, and might be helpful for protection of astronaut health.

Anti-POSTN and Anti-TIMP1 Autoantibodies as Diagnostic Markers in Esophageal Squamous Cell Carcinoma.

Esophageal cancer is one of the most commonly diagnosed malignant gastrointestinal tumors. The aim of the study was to explore the diagnostic values of anti-POSTN and anti-TIMP1 autoantibodies in esophageal squamous cell carcinoma (ESCC). Differentially expressed genes (DEGs) associated with esophageal cancer were screened out by the LIMMA method in the Gene Expression Profiling Interactive Analysis (GEPIA) platform. Search Tool for the Retrieval of Interacting Genes (STRING) was used to construct the protein-protein interaction (PPI) based on highly DEGs. The candidate hub genes were the intersection genes calculated based on degree and Maximal Clique Centrality (MCC) algorithms via Cytoscape. A total of 370 participants including 185 ESCC patients and 185 matched normal controls were enrolled in enzyme-linked immunosorbent assay (ELISA) to detect the expression levels of autoantibodies corresponding to POSTN and TIMP1 proteins. A total of 375 DEGs with high expression were obtained in esophageal cancer. A total of 20 hub genes were acquired using the cytoHubba plugin by degree and MCC algorithms. The expression levels of anti-POSTN and anti-TIMP1 autoantibodies were higher in the sera of ESCC patients (p < 0.05). Anti-POSTN autoantibody can diagnose ESCC patients with an AUC of 0.638 at the specificity of 90.27% and sensitivity of 27.57%, and anti-TIMP1 autoantibody can diagnose ESCC patients with an AUC of 0.585 at the specificity of 90.27% and sensitivity of 20.54% (p < 0.05). In addition, anti-POSTN and anti-TIMP1 autoantibodies can distinguish ESCC patients from normal controls in most clinical subgroups (p < 0.05). In conclusion, anti-POSTN and anti-TIMP1 autoantibodies may be considered the potential biomarkers in the clinical diagnosis of ESCC.

Trend of the mortality of major liver diseases and its impact on life expectancy in China from 2006 to 2017.

BACKGROUND: Liver diseases are the serious cause of death in China. We aim to describe the trends and disparities of major liver disease mortality rates and the loss of life expectancy (LLE) in China. METHODS: Annual percentage change (APC) and average APC (AAPC) were calculated using the Joinpoint regression model. LLE was calculated using cause eliminated life table. RESULTS: From 2006 to 2017, the overall age-standardized mortality rate (ASMR) of liver cirrhosis lightly declined (AAPC: -2.97%), whereas the ASMR of viral hepatitis and liver cancer remained stable. Viral hepatitis (AAPC: -4.36%) and liver cirrhosis (AAPC: -4.35%) ASMRs both declined for females. The highest ASMRs of viral hepatitis and liver cirrhosis were in the west region, while that of liver cancer was in the middle region. The ASMRs of liver cirrhosis in the middle region and liver cancer in the east region significantly decreased. The means of LLE on viral hepatitis, liver cirrhosis and liver cancer were 0.05, 0.1 and 0.46 years, respectively. CONCLUSIONS: The burden of liver diseases is still severe and there are disparities between genders and different regions in China. Accurate early diagnostic approaches for high-risk populations should be established to eliminate the burden of liver diseases.

Discovery and Validation of Serum Autoantibodies Against Tumor-Associated Antigens as Biomarkers in Gastric Adenocarcinoma Based on the Focused Protein Arrays.

INTRODUCTION: Previous studies have demonstrated that autoantibodies against tumor-associated antigens (TAAs) in patients with cancer can be used as sensitive immunodiagnostic biomarkers for the detection of cancer. Most of these TAAs are involved in the tumorigenesis pathway. Cancer driver genes with intragenic mutations can promote tumorigenesis. This study aims to identify autoantibodies against TAAs encoded by cancer driver genes in sera as potential immunodiagnostic biomarkers for gastric adenocarcinoma (GAC). METHODS: Protein arrays based on cancer driver genes were customized for screening candidate TAAs in 100 GAC sera and 50 normal control (NC) sera. Autoantibodies against candidate TAAs were assessed by enzyme-linked immunosorbent assay in both training group (205 GAC sera and 205 NC sera) and independent validation group (126 GAC sera and 126 NC sera). Moreover, the immunodiagnostic models were respectively established and validated in the training group and validation group. RESULTS: A panel with 5 autoantibodies including anti-TP53, anti-COPB1, anti-GNAS, anti-serine/arginine-rich splicing factor 2, and anti-SMARCB1 was selected by the Fisher linear discriminant analysis model with an areas under receiver operating characteristic curve (AUC) of 0.928 (95% confidence interval [CI]: 0.888-0.967) in the training cohort and an AUC of 0.885 (95% CI: 0.852-0.918) in the validation cohort. Besides, the panel with 5 autoantibodies including anti-TP53, anti-COPB1, anti-GNAS, anti-PBRM1, and anti-ACVR1B which were selected by the binary logistic regression model showed an AUC of 0.885 (95% CI: 0.852-0.919) in the training cohort and 0.884 (95% CI: 0.842-0.925) in the validation cohort. DISCUSSION: Two panels which were selected in this study could boost the detection of anti-TAA autoantibodies in sera as biomarkers for the detection of GAC.

Using Serological Proteome Analysis to Identify and Evaluate Anti-GRP78 Autoantibody as Biomarker in the Detection of Gastric Cancer.

The serological biomarkers as noninvasive tests are the most promising way for diagnosing gastric cancer (GC). Serological proteome analysis (SERPA) has been used to identify tumor-associated antigens (TAAs) and the corresponding autoantibodies in many studies. To explore the relationship between gastric cancer development and serum autoantibody anti-GRP78 response found by the method of SERPA with the GC cell line AGS, we included two cohorts (133 GC and 133 normal individuals in test group; 300 GC and 300 normal individuals in validation group) of patients with newly diagnosed GC for verification. All GC and normal controls were matched by age and gender. The autoantibody levels of the sera in two cohorts were measured by immunoassay. Finally, the results showed that 78-kDa glucose-regulated protein (GRP78) was identified in GC by SERPA and the level of anti-GRP78 antibody in GC was higher than that in normal individuals in the two cohorts. Receiver operating characteristic (ROC) curve analysis showed similar diagnostic value of anti-GRP78 antibody in test group (AUC: 0.718) and validation group (AUC: 0.666) to identify GC patients from normal individuals. The AUCs of anti-GRP78 autoantibody in the diagnosis of GC patients with different clinical characteristic ranged from 0.676 to 0.773 in test group and ranged from 0.645 to 0.707 in validation group. In conclusion, autoantibody against GRP78 might be a potential diagnostic biomarker. Further large-scale studies will be needed to validate and improve its performance of the sensitivity, specificity, and AUC value in distinguishing GC from other diseases.

Development and validation of prediction models for hypertension risks in rural Chinese populations.

BACKGROUND: Various hypertension predictive models have been developed worldwide; however, there is no existing predictive model for hypertension among Chinese rural populations. METHODS: This is a 6-year population-based prospective cohort in rural areas of China. Data was collected in 2007-2008 (baseline survey) and 2013-2014 (follow-up survey) from 8319 participants ranging in age from 35 to 74 years old. Specified gender hypertension predictive models were established based on multivariate Cox regression, Artificial Neural Network (ANN), Naive Bayes Classifier (NBC), and Classification and Regression Tree (CART) in the training set. External validation was conducted in the testing set. The estimated models were assessed by discrimination and calibration, respectively. RESULTS: During the follow-up period, 432 men and 604 women developed hypertension in the training set. Assessment for established models in men suggested men office-based model (M1) was better than others. C-index of M1 model in the testing set was 0.771 (95% confidence Interval (CI) = 0.750, 0.791), and calibration χ2 = 6.3057 (P = 0.7090). In women, women office-based model (W1) and ANN were better than the other models assessed. The C-indexes for the W1 model and the ANN model in the testing set were 0.765 (95% CI = 0.746, 0.783) and 0.756 (95% CI = 0.737, 0.775) and the calibrations χ2 were 6.7832 (P = 0.1478) and 4.7447 (P = 0.3145), respectively. CONCLUSIONS: Not all machine-learning models performed better than the traditional Cox regression models. The W1 and ANN models for women and M1 model for men have better predictive performance which could potentially be recommended for predicting hypertension risk among rural populations.

Mortality pattern trends and disparities among Chinese from 2004 to 2016.

BACKGROUND: With the changes in environmental, medical technique, population structure and national health projects, human mortality rates have undergone great changes all over the world. According to "World Health Statistics 2016: Monitoring Health for the SDGs (Sustainable Development Goals)", we can draw a globally vision about life expectancy and cause of death; also, significant inequality still persists within and among countries. This study was designed to research into the trend of mortality pattern in China, evaluate the disparities of age-specific and disease-specific mortality rates between male and female, and provides a scientific basis for further prevention strategies and policies design. METHODS: Data from the Chinese Disease Surveillance Points system were used to calculate crude and age-adjusted death rates, annual percent changes (APC) for men and women during 2004 to 2016. Age-standardized mortality rates (ASMR) were performed through the direct method with the World Health Organization's World Standard Population. APC, according to log linear model, was adopted to describe the mortality rate trend. The χ2 test was used to compare differences between age-specific and cause-specific mortality rates of men and women. Data analysis and figures were completed by R software. RESULTS: The mortality rates of men and women have decreased significantly (P < 0.05) during 2004-2016, and the APC were1.98 and 2.45%, respectively. In 2016, the crude mortality rate (CMR) and ASMR in all causes of death were 658.50 and 490.28 per 100,000 per year, respectively. The 5 leading causes of death were malignant neoplasm, cerebrovascular disease, heart disease, COPD, and accidental injury. The mortality rates of men were higher than that of women in all age groups. CONCLUSIONS: There are severe health gaps and disparities between male and female, and the chronic non-communicable diseases continue to be a serious health threat to Chinese residents.

Long noncoding RNA CASC15 predicts unfavorable prognosis and exerts oncogenic functions in non-small cell lung cancer.

BACKGROUND: Aberrant expression of long non-coding RNA cancer susceptibility 15 (lncRNA CASC15) has been documented in various human tumors, and upregulation of CASC15 is closely correlated with cancer progression. However, the expression profile and potential biological functions of lncRNA CASC15 in non-small cell lung cancer (NSCLC) have not been fully characterized. METHODS: The expression levels of CASC15 were assessed by qRT-PCR in human NSCLC tissues and by in situ hybridization in NSCLC tissue microarray. The relationship between CASC15 expression and clinical parameters, as well as prognosis were analyzed and validated in TCGA NSCLC datasets. The biological functions of CASC15 were analyzed by CCK-8 assay, cell migration and invasion assay in NSCLC cell lines in vitro. In addition, a mouse xenograft model was established to evaluate the effect of CASC15 knockdown on NSCLC tumor growth in vivo. Epithelial-mesenchymal transition (EMT) related molecules were examined by western blot and immunohistochemistry staining. RESULTS: We found that CASC15 was upregulated in NSCLC tissues and cell lines. High expression levels of CASC15 were correlated with malignancies and poor survival rate in NSCLC patients. Multivariate analysis revealed that CASC15 was an independent risk factor of prognosis. In addition, we demonstrated that CASC15 knockdown inhibited NSCLC cell proliferation, migration and invasion in vitro. Xenograft model showed CASC15 knockdown significantly suppressed NSCLC tumor growth. Mechanistically, we revealed that CASC15 regulated EMT-related molecules and promoted the NSCLC progression and metastasis. CONCLUSION: In summary, our findings suggest CASC15 exhibits an oncogenic role in promoting NSCLC tumorigenesis via regulating EMT.

Coffee consumption and risk of hypertension: a systematic review and dose-response meta-analysis of cohort studies.

Some debates exist regarding the association of coffee consumption with hypertension risk. We performed a meta-analysis including dose-response analysis aimed to derive a more quantitatively precise estimation of this association. PubMed and Embase were searched for cohort studies published up to 18 July 2017. Fixed-effects generalized least-squares regression models were used to assess the quantitative association between coffee consumption and hypertension risk across studies. Restricted cubic spline was used to model the dose-response association. We identified eight articles (10 studies) investigating the risk of hypertension with the level of coffee consumption, including 243,869 individuals and 58,094 incident cases of hypertension. We found no evidence of a nonlinear dose-response association of coffee consumption and hypertension (P nonlinearity = 0.243). The risk of hypertension was reduced by 2% (relative risk (RR) = 0.98, 95% confidence interval (CI) 0.98-0.99) with each one cup/day increment of coffee consumption. With the linear cubic spline model, the RRs of hypertension risk were 0.97 (95% CI 0.95-0.99), 0.95 (95% CI 0.91-0.99), 0.92 (95% CI 0.87-0.98), and 0.90 (95% CI 0.83-0.97) for 2, 4, 6, and 8 cups/day, respectively, compared with individuals with no coffee intakes. This meta-analysis provides quantitative evidence that consumption of coffee was inversely associated with the risk of hypertension in a dose-response manner.