Significance of Gastrokine-1 Polymorphism Rs4254535 as a Prognostic Marker and its Association with Clinical Characteristics in Chinese Lung Cancer Patients

Background: The single nucleotide polymorphism (SNP) of Gastrokine-1 (GKN1) is associated with lung cancer but its association with prognosis is not clear. Methods: Genomic DNA was extracted from the blood samples of 888 patients with lung cancer. The association between GKN1 polymorphism rs4254535 and prognostic was analyzed by the Kaplan-Meier (KM) method, Log-rank test, and Cox proportional hazards model. Results: In females and patients diagnosed with late-stage lung cancer, the CC genotype (CC vs TT, adjusted odds ratio [HR] = 0.57, 95% Confidence Interval [CI]: 0.33-0.99, P = 0.045; HR = 0.66, 95% CI: 0.48-0.92, P = 0.014) and recessive CC genotype (CC vs TT + TC, HR = 0.55, 95% CI: 0.32-0.94, P = 0.028; HR = 0.64, 95% CI: 0.47-0.89, P = 0.006) of rs4254535 conferred a better prognosis, compared with the TT and TT + TC genotype. Rs4254535 dominate TC + CC genotype, recessive CC genotype, and C allele who were adenocarcinoma patients had a significantly better prognosis. The recessive CC genotype of non-smoking patients has a better prognosis, compared to the TT + TC genotype. Additionally, in the dominant TT + TC genotype and C allele, no family history patients had a significantly better prognosis, compared to the TT genotype. Conclusion: For lung cancer patients, GKN1 polymorphism rs4254535 may be a protective genetic marker and predicts the prognosis of lung cancer patients.

Andrographolide restored production performances and serum biochemical indexes and attenuated organs damage in Mycoplasma gallisepticum-infected broilers

1. This study aimed to study the preventive and therapeutic effects of andrographolide (Andro) during Mycoplasma gallisepticum HS strain (MG) infection in ArborAcres (AA) broilers.2. The minimum inhibitory concentration (MIC) of Andro against MG was measured. Broiler body weight, feed efficiency, morbidity, cure rate and mortality were recorded during the experiment. Air sac lesion scores and immune organ index were calculated. Expression of pMGA1.2 in lung tissue and serum biochemical indices were examined. Histopathological examinations of immune organs, liver, trachea and lung tissue were conducted by Haematoxylin and Eosin stain.3. MIC was 3.75 μg/mL and Andro significantly inhibited the expression of pMGA1.2 (P ≤ 0.05). Compared with control MG-infected group, Andro low-dose and high-dose prevention reduced the morbidity of chronic respiratory disease in 40.00% and 50.00%, respectively. Mortality of C, D and E group was 16.67%, 10.00% and 6.67%, respectively. Cure rate of E, F, G and H group was 92.00%, 92.86%, 93.33% and 100.0%, respectively. Compared with control MG-infected group, Andro treatment significantly increased average weight gain (AWG), relative weight gain rate (RWG) and feed conversion rate (FCR) at 18 to 24 days (P ≤ 0.05). Compared with control group, Andro alone treatment significantly increased AWG in broilers (P ≤ 0.05).4. Compared with control MG-infected group, Andro significantly attenuated MG-induced air sac lesion, immune organs, liver, trachea and lung damage in broilers. Andro alone treatment did not induce abnormal morphological changes in these organs in healthy broilers. Serum biochemical analysis results showed, comparing with control MG-infected group, Andro significantly decreased the content of total protein, albumin, globulin, alanine aminotransferase, aspartate aminotransferase, total bilirubin, urea, creatinine, uric acid, total cholesterol, and increased the albumin/globulin ratio and content of alkaline phosphatase, apolipoprotein B and apolipoprotein A-I in a dose-dependent manner (P ≤ 0.05).5. Andro could act as a potential agent against MG infection in broilers.

Effects of wearing personal protective equipment during COVID-19 pandemic on composition and diversity of skin bacteria and fungi of medical workers

BACKGROUND

During the COVID-19 pandemic, wearing PPE can induce skin damage such as erythema, pruritus, erosion, and ulceration among others. Although the skin microbiome is considered important for skin health, the change of the skin microbiome after wearing PPE remain unknown.

OBJECTIVE

The present study aimed to characterize the diversity and structure of bacterial and fungal flora on skin surfaces of healthcare workers wearing personal protective equipment (PPE) during the COVID-19 pandemic using metagenomic next-generation sequencing (mNGS).

METHODS

A total of 10 Chinese volunteers were recruited and the microbiome of their face, hand, and back were analyzed before and after wearing PPE. Moreover, VISIA was used to analyze skin features.

RESULTS

Results of alpha bacterial diversity showed that there was statistically significant decrease in alpha diversity indice in the skin samples from face, hand, and three sites after wearing PPE as compared with the indice in the skin samples before wearing PPE. Further, the results of evaluated alpha fungal diversity show that there was a statistically significant decrease in alpha diversity indices in the skin samples from hand after wearing PPE as compared with the indices in the skin samples before wearing PPE (P<0.05). Results of the current study found that the main bacteria on the face, hand, and back skin samples before wearing the PPE were Propionibacterium spp. (34.04%), Corynebacterium spp. (13.12%), and Staphylococcus spp. (38.07%). The main bacteria found on the skin samples after wearing the PPE were Staphylococcus spp. (31.23%), Xanthomonas spp. (26.21%), and Cutibacterium spp. (42.59%). The fungal community composition was similar in three skin sites before and after wearing PPE.

CONCLUSION

It was evident that wearing PPE may affect the skin microbiota, especially bacteria. Therefore, it was evident that the symbiotic microbiota may reflect the skin health of medical workers during the COVID-19 pandemic.

Prediction of lung cancer risk in Chinese population with genetic-environment factor using extreme gradient boosting

BACKGROUND

Detecting early-stage lung cancer is critical to reduce the lung cancer mortality rate; however, existing models based on germline variants perform poorly, and new models are needed. This study aimed to use extreme gradient boosting to develop a predictive model for the early diagnosis of lung cancer in a multicenter case-control study.

MATERIALS AND METHODS

A total of 974 cases and 1005 controls in Shanghai and Taizhou were recruited, and 61 single nucleotide polymorphisms (SNPs) were genotyped. Multivariate logistic regression was used to calculate the association between signal SNPs and lung cancer risk. Logistic regression (LR) and extreme gradient boosting (XGBoost) algorithms, a large-scale machine learning algorithm, were adopted to build the lung cancer risk model. In both models, 10-fold cross-validation was performed, and model predictive performance was evaluated by the area under the curve (AUC).

RESULTS

After FDR adjustment, TYMS rs3819102 and BAG6 rs1077393 were significantly associated with lung cancer risk (p < 0.05). For lung cancer risk prediction, the model predicted only with epidemiology attained an AUC of 0.703 for LR and 0.744 for XGBoost. Compared with the LR model predicted only with epidemiology, further adding SNPs and applying XGBoost increased the AUC to 0.759 (p < 0.001) in the XGBoost model. BAG6 rs1077393 was the most important predictor among all SNPs in the lung cancer prediction XGBoost model, followed by TERT rs2735845 and CAMKK1 rs7214723. Further stratification in lung adenocarcinoma (ADC) showed a significantly elevated performance from 0.639 to 0.699 (p = 0.009) when applying XGBoost and adding SNPs to the model, while the best model for lung squamous cell carcinoma (SCC) prediction was the LR model predicted with epidemiology and SNPs (AUC = 0.833), compared with the XGBoost model (AUC = 0.816).

CONCLUSION

Our lung cancer risk prediction models in the Chinese population have a strong predictive ability, especially for SCC. Adding SNPs and applying the XGBoost algorithm to the epidemiologic-based logistic regression risk prediction model significantly improves model performance.

Prognosis of lung cancer with simple brain metastasis patients and establishment of survival prediction models: a study based on real events

Objectives

The aim of this study was to explore risk factors for the prognosis of lung cancer with simple brain metastasis (LCSBM) patients and to establish a prognostic predictive nomogram for LCSBM patients.

Materials and methods

Three thousand eight hundred and six cases of LCSBM were extracted from the Surveillance, Epidemiology, and End Results (SEER) database from 2010 to 2015 using SEER Stat 8.3.5. Lung cancer patients only had brain metastasis with no other organ metastasis were defined as LCSBM patients. Prognostic factors of LCSBM were analyzed with log-rank method and Cox proportional hazards model. Independent risk and protective prognostic factors were used to construct nomogram with accelerated failure time model. C-index was used to evaluate the prediction effect of nomogram.

Results and conclusion

The younger patients (18–65 years old) accounted for 54.41%, while patients aged over 65 accounted for 45.59%.The ratio of male: female was 1:1. Lung cancer in the main bronchus, upper lobe, middle lobe and lower lobe were accounted for 4.91%, 62.80%, 4.47% and 27.82% respectively; and adenocarcinoma accounted for 57.83% of all lung cancer types. The overall median survival time was 12.2 months. Survival rates for 1-, 3- and 5-years were 28.2%, 8.7% and 4.7% respectively. We found female (HR = 0.81, 95% CI 0.75–0.87), the married (HR = 0.80; 95% CI 0.75–0.86), the White (HR = 0.90, 95% CI 0.84–0.95) and primary site (HR = 0.45, 95% CI 0.39–0.52) were independent protective factors while higher age (HR = 1.51, 95% CI 1.40–1.62), advanced grade (HR = 1.19, 95% CI 1.12–1.25) and advanced T stage (HR = 1.09, 95% CI 1.05–1.13) were independent risk prognostic factors affecting the survival of LCSBM patients. We constructed the nomogram with above independent factors, and the C-index value was 0.634 (95% CI 0.622–0.646). We developed a nomogram with seven significant LCSBM independent prognostic factors to provide prognosis prediction.

Astrocyte-Derived Exosomes in an iPSC Model of Bipolar Disorder

Bipolar I Disorder (BP) is a serious, recurrent mood disorder that is characterized by alternating episodes of mania and depression. To begin to identify novel approaches and pathways involved in BP, we have obtained skin samples from BP patients and undiagnosed control (C) individuals, reprogrammed them to form induced pluripotent stem cells (iPSC), and then differentiated the stem cells into astrocytes. RNAs from BP and C astrocytes were extracted and RNAseq analysis carried out. 501 differentially expressed genes were identified, including genes for cytoskeletal elements, extracellular matrix, signaling pathways, neurodegeneration, and notably transcripts that identify exosomes. When we compared highly expressed genes using hierarchial cluster analysis, "Exosome" was the first and most highly significant cluster identified, p < 5 × 10^-13, Benjamini correction. Exosomes are membrane-bound vesicles that package and remove toxic proteins from cells and also enable cell to cell communication. They carry genetic material, including DNA, mRNA and microRNAs, proteins, and lipids to target cells throughout the body. Exosomes are released by cortical neurons and astrocytes in culture and are present in BP vs C postmortem brain tissue. Little is known about what transcripts and proteins are targeted to neurons, how they regulate biological functions of the acceptor cell, or how that may be altered in mood disorders. Since astrocyte-derived exosomes have been suggested to promote neuronal plasticity, as well as to remove toxic proteins in the brain, alterations in their function or content may be involved in neurodevelopmental, neuropathological, and neuropsychiatric conditions. To examine exosome cargos and interactions with neural precursor cells, astrocytes were differentiated from four bipolar disorder (BP) and four control (C) iPSC lines. Culture supernatants from these astrocytes were collected, and exosomes isolated by ultra-centrifugation. Western blot analysis demonstrated the presence of the exosome markers CD9, CD81, and Hsp70. Nanosight technology was used to characterize exosomes from each astrocyte cell line, suggesting that exosomes were slightly more concentrated in culture supernatants derived from BP compared with C astrocytes but there was no difference in the mean sizes of the exosomes. Analysis of their function in neuronal differentiation is being carried out by labeling exosomes derived from bipolar patient and control astrocytes and adding them to control neural progenitor cells. Given the current interest in clearing toxic proteins from brains of patients with neurodegenerative disorders, exosomes may present similar opportunities in BP.

Effect of ERCC2 rs13181 and rs1799793 polymorphisms and environmental factors on the prognosis of patients with lung cancer

PURPOSE

The 5-year survival rate of patients with lung cancer in China is < 20%, and predicting their prognosis is difficult. Here, we investigated the association between two common non-synonymous single-nucleotide polymorphisms (SNPs) in the excision repair cross-complementing 2 (ERCC2) genes (rs13181 and rs1799793) and the prognosis of patients with lung cancer.

METHODS

Genomic DNA was extracted from the blood samples of 839 patients with lung cancer and genotyped using the SNPscan technique. The association between patient prognosis and the ERCC2 genotype was analyzed using a multivariate Cox proportional hazards model adjusted for multiple potential confounders.

RESULTS

The presence of ERCC2 rs13181 T>G significantly increased the risk of death (adjust hazard ratio (HR) = 1.29, 95% CI: 1.06-1.56, P = 0.009). Patients with the rs13181 TG genotype (adjust HR = 1.34, 95% CI: 1.08-1.65, P = 0.007) and rs13181 dominant mode TG+GG (adjust HR = 1.33, 95% CI: 1.08-1.63, P = 0.007) had significantly worse overall survival. Moreover, stratified analyses showed that patients with the TG and TG+GG rs13181 genotypes who were male, elderly (≥60 years), had a history of smoking, or without family history of malignant tumors had a significantly increased risk of death. In patients with adenocarcinoma lung cancer (ADC), the rs1799793 genotype CT (adjust HR = 1.49, 95% CI: 1.06-2.09, P = 0.023) and dominant model CT+TT (adjust HR = 1.45, 95% CI = 1.04-2.02, P = 0.027) were associated with an increased risk of death.

CONCLUSION

ERCC2 rs13181 and rs1799793 SNPs may be significant prognostic factors for the risk of death among patients with lung cancer.

Do food and stress biomarkers work for wastewater-based epidemiology? A critical evaluation

Dietary characteristics and oxidative stress are closely linked to the wellbeing of individuals. In recent years, various urinary biomarkers of food and oxidative stress have been proposed for use in wastewater-based epidemiology (WBE), in efforts to objectively monitor the food consumed and the oxidative stress experienced by individuals in a wastewater catchment. However, it is not clear whether such biomarkers are suitable for wastewater-based epidemiology. This study presents a suite of 30 urinary food and oxidative stress biomarkers and evaluates their applicability for WBE studies. This includes 22 biomarkers which were not previously considered for WBE studies. Daily per capita loads of biomarkers were measured from 57 wastewater influent samples from nine Australian catchments. Stability of biomarkers were assessed using laboratory scale sewer reactors. Biomarkers of consumption of vitamin B2, vitamin B3 and fibre, as well as a component of citrus had per capita loads in line with reported literature values despite susceptibility of degradation in sewer reactors. Consumption biomarkers of red meat, fish, fruit, other vitamins and biomarkers of stress had per capita values inconsistent with literature findings, and/or degraded rapidly in sewer reactors, indicating that they are unsuitable for use as WBE biomarkers in the traditional quantitative sense. This study serves to communicate the suitability of food and oxidative stress biomarkers for future WBE research.

The Chinese National Twin Registry: a 'gold mine' for scientific research

The Chinese National Twin Registry (CNTR) currently includes data from 61 566 twin pair from 11 provinces or cities in China. Of these, 31 705, 15 060 and 13 531 pairs are monozygotic, same-sex dizygotic and opposite-sex dizygotic pairs, respectively, determined by opposite sex or intrapair similarity. Since its establishment in 2001, the CNTR has provided an important resource for analysing genetic and environmental influences on chronic diseases especially cardiovascular diseases. Recently, the CNTR has focused on collecting biologic specimens from disease-concordant or disease-discordant twin pairs or from twin pairs reared apart. More than 8000 pairs of these twins have been registered, and blood samples have been collected from more than 1500 pairs. In this review, we summarize the main findings from univariate and multivariate genetic effects analyses, gene-environment interaction studies, omics studies exploring DNA methylation and metabolomic markers associated with phenotypes. There remains further scope for CNTR research and data mining. The plan for future development of the CNTR is described. The CNTR welcomes worldwide collaboration.

A novel biophysical based marker with multilevel, multiparameter expression for early stage cancer detection

e20673

Background: Early stage cancer detection remains to be elusive despite of many years of efforts. In this work, a bio-physical based marker (named Cancer Differentiation Analysis (CDA)) with multi-level and multi-parameter expression features has been developed which has shown a number of clear advantages over the traditional approaches such as bio-chemistry based marker, circulating tumor cell (CTC) and circuiting DNA (ct-DNA). In stage I non-small cell lung cancer (NSCLC), sensitivity and specificity reached a record high of 85.2% and 93.0%, respectively. Methods: In this study, 832 NSCLC cancer samples with pathological information and 642 samples from healthy individuals were measured in a single blind test. Peripheral blood of each individual was drawn in EDTA tubes. One class of bio-physical property in blood samples was utilized for CDA tests. The CDA data were first processed using an algorithm built from data base and subsequently analyzed using SPSS. The results were shown in the table. Results: The results indicated that CDA technology has a very good sensitivity and specificity even at stage I (85% and 93%, respectively), which is much better than those previously reported results by other methods. Conclusions: Initial results showed that CDA technology could effectively screen NSCLC patients from healthy individuals. As a novel bio-physical based cancer detection approach with multi-level and multi-parameter expressions, CDA technology could be a potential candidate for early stage cancer screening. [Table: see text]