Pan-cancer Multi-omics Analysis Reveals HMGN1 as a Potential Prognostic and Immune Infiltration-associated Biomarker.

BACKGROUND: The High Mobility Group Nucleosomal Binding Domain 1 Gene (HMGN1) is crucial for epigenetic regulation. However, the specific function of HMGN1 in cancer development is unclear. METHODS: Raw data on HMGN1 expression were procured from Genotype-Tissue Expression (GTEx), the University of Alabama- Birmingham CANcer data analysis Portal (UALCAN), and The Cancer Genome Atlas (TCGA). Thereafter, the pan-cancer analysis was implemented to understand the HMGN1 expression patterns, prognostic value, and immunological features. Furthermore, the Gene Set Enrichment Analysis (GSEA) was executed via R language. In addition, the relationship between HMGN1 and the sensitivity of antitumor drugs was also determined. Finally, real-time PCR (RT-PCR) experiments were carried out. RESULTS: Pan-cancer analysis revealed that HMGN1 was upregulated in several solid tumors and was associated with pathological staging and poor prognosis. In addition, HMGN1 was found to be involved in regulating the tumor microenvironment. The GSEA enrichment analysis indicated that HMGN1 assisted in the regulation of oncogenic processes, especially metabolic and immune pathways. Furthermore, HMGN1 expression was linked to microsatellite instability (MSI) and tumor mutational burden (TMB) across diverse tumor types. RT-PCR assays indicated that HMGN1 was overexpressed in the gastric and breast cancer cell lines and tissues. CONCLUSION: This study highlighted the potential of HMGN1 as a biomarker for pan- - cancer analysis.

Construction and validation of a signature for T cell-positive regulators related to tumor microenvironment and heterogeneity of gastric cancer.

Background: Positive regulators of T cell function play a vital role in the proliferation and differentiation of T cells. However, their functions in gastric cancer have not been explored so far. Methods: The TCGA-STAD dataset was utilized to perform consensus clustering in order to identify subtypes related to T cell-positive regulators. The prognostic differentially expressed genes of these subtypes were identified using the least absolute shrinkage and selection operator (LASSO) regression analysis. To validate the robustness of the identified signature, verification analyses were conducted across the TCGA-train, TCGA-test, and GEO datasets. Additionally, a nomogram was constructed to enhance the clinical efficacy of this predictive tool. Transwell migration, colony formation, and T cell co-culture assays were used to confirm the function of the signature gene in gastric cancer and its influence on T cell activation. Results: Two distinct clusters of gastric cancer, related to T cell-positive regulation, were discovered through the analysis of gene expression. These clusters exhibited notable disparities in terms of survival rates (P = 0.028), immune cell infiltration (P< 0.05), and response to immunotherapy (P< 0.05). Furthermore, a 14-gene signature was developed to classify gastric cancer into low- and high-risk groups, revealing significant differences in survival rates, tumor microenvironment, tumor mutation burden, and drug sensitivity (P< 0.05). Lastly, a comprehensive nomogram model was constructed, incorporating risk factors and various clinical characteristics, to provide an optimal predictive tool. Additionally, an assessment was conducted on the purported molecular functionalities of low- and high-risk gastric cancers. Suppression of DNAAF3 has been observed to diminish the migratory and proliferative capabilities of gastric cancer, as well as attenuate the activation of T cells induced by gastric cancer within the tumor microenvironment. Conclusion: We identified an ideal prognostic signature based on the positive regulators of T cell function in this study.

Interleukin-41 diminishes cigarette smoke-induced lung inflammation in mice.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) and other inflammatory lung illnesses are markedly exacerbated by cigarette smoke (CS). The novel cytokine interleukin (IL)-41 has immunoregulatory effects, but data on its function in lung inflammation caused by CS are limited and inconclusive. Our study aimed to investigate the ability of IL-41 to protect against CS-induced lung inflammation in vivo. METHODS: In this model, mice were exposed to six cigarettes three times daily for 1 h, with 4-hour intervals between exposures, for 5 consecutive days. Mice received an intraperitoneal dose of IL-41 or a negative control 1 day prior to their initial exposure to CS. On day 6, mice were sacrificed to assess the impact of IL-41 on CS-induced lung inflammation. RESULTS: We found that IL-41 pre-treatment alleviated pulmonary inflammatory infiltration and lung tissue lesions. IL-41 pre-treatment also limited CS-induced weight loss, and resulted in lower numbers of macrophages in the bronchoalveolar lavage fluid and lower percentages of neutrophils and monocytes in the blood. Furthermore, it promoted the polarization of M2 macrophages rather than M1 macrophages, as determined by immunohistochemistry. Consistent with its effects on M2 polarization, pre-treatment with IL-41 was associated with higher levels of IL-10 in the bronchoalveolar lavage fluid and lung tissues of CS-exposed animals and lower production of tumor necrosis factor-α, IL-6 and IL-1ß in the serum and lung tissues. CONCLUSIONS: These findings suggest that IL-41 could be used therapeutically to treat CS-induced lung inflammatory disorders as it inhibits CS-induced pulmonary inflammation when administered in vivo in mice.

Development and validation of an inflammatory response-related signature in triple negative breast cancer for predicting prognosis and immunotherapy.

Background: Inflammation is one of the most important characteristics of tumor tissue. Signatures based on inflammatory response-related genes (IRGs) can predict prognosis and treatment response in a variety of tumors. However, the clear function of IRGs in the triple negative breast cancer (TNBC) still needs to be explored. Methods: IRGs clusters were discovered via consensus clustering, and the prognostic differentially expressed genes (DEGs) across clusters were utilized to develop a signature using a least absolute shrinkage and selection operator (LASSO). Verification analyses were conducted to show the robustness of the signature. The expression of risk genes was identified by RT-qPCR. Lastly, we formulated a nomogram to improve the clinical efficacy of our predictive tool. Results: The IRGs signature, comprised of four genes, was developed and was shown to be highly correlated with the prognoses of TNBC patients. In contrast with the performance of the other individual predictors, we discovered that the IRGs signature was remarkably superior. Also, the ImmuneScores were elevated in the low-risk group. The immune cell infiltration showed significant difference between the two groups, as did the expression of immune checkpoints. Conclusion: The IRGs signature could act as a biomarker and provide a momentous reference for individual therapy of TNBC.

Corrigendum: Identification and validation of a novel senescence-related biomarker for thyroid cancer to predict the prognosis and immunotherapy.

[This corrects the article DOI: 10.3389/fimmu.2023.1128390.].

Diagnostic model constructed by five EMT-related genes for renal fibrosis and reflecting the condition of immune-related cells.

Background: Renal fibrosis is a physiological and pathological characteristic of chronic kidney disease (CKD) to end-stage renal disease. Since renal biopsy is the gold standard for evaluating renal fibrosis, there is an urgent need for additional non-invasive diagnostic biomarkers. Methods: We used R package "limma" to screen out differently expressed genes (DEGs) based on Epithelial-mesenchymal transformation (EMT), and carried out the protein interaction network and GO, KEGG enrichment analysis of DEGs. Secondly, the least absolute shrinkage and selection operator (LASSO), random forest tree (RF), and support vector machine-recursive feature elimination (SVM-RFE) algorithms were used to identify candidate diagnostic genes. ROC curves were plotted to evaluate the clinical diagnostic value of these genes. In addition, mRNA expression levels of candidate diagnostic genes were analyzed in control samples and renal fibrosis samples. CIBERSORT algorithm was used to evaluate immune cells level. Additionally, gene set enrichment analysis (GSEA) and drug sensitivity were conducted. Results: After obtaining a total of 24 DEGs, we discovered that they were mostly involved in several immunological and inflammatory pathways, including NF-KappaB signaling, AGE-RAGE signaling, and TNF signaling. Five genes (COL4A2, CXCL1, TIMP1, VCAM1, and VEGFA) were subsequently identified as biomarkers for renal fibrosis through machine learning, and their expression levels were confirmed by validation cohort data sets and in vitro RT-qPCR experiment. The AUC values of these five genes demonstrated significant clinical diagnostic value in both the training and validation sets. After that, CIBERSORT analysis showed that these biomarkers were strongly associated with immune cell content in renal fibrosis patients. GSEA also identifies the potential roles of these diagnostic genes. Additionally, diagnostic candidate genes were found to be closely related to drug sensitivity. Finally, a nomogram for diagnosing renal fibrosis was developed. Conclusion: COL4A2, CXCL1, TIMP1, VCAM1, and VEGFA are promising diagnostic biomarkers of tissue and serum for renal fibrosis.

Establishment and validation of a ubiquitination-related gene signature associated with prognosis in pancreatic duct adenocarcinoma.

Background: Patients with pancreatic duct adenocarcinoma (PDAC) have varied prognoses that depend on numerous variables. However, additional research is required to uncover the latent impact of ubiquitination-related genes (URGs) on determining PDAC patients' prognoses. Methods: The URGs clusters were discovered via consensus clustering, and the prognostic differentially expressed genes (DEGs) across clusters were utilized to develop a signature using a least absolute shrinkage and selection operator (LASSO) regression analysis of data from TCGA-PAAD. Verification analyses were conducted across TCGA-PAAD, GSE57495 and ICGC-PACA-AU to show the robustness of the signature. RT-qPCR was used to verify the expression of risk genes. Lastly, we formulated a nomogram to improve the clinical efficacy of our predictive tool. Results: The URGs signature, comprised of three genes, was developed and was shown to be highly correlated with the prognoses of PAAD patients. The nomogram was established by combining the URGs signature with clinicopathological characteristics. We discovered that the URGs signature was remarkably superior than other individual predictors (age, grade, T stage, et al). Also, the immune microenvironment analysis indicated that ESTIMATEscore, ImmuneScores, and StromalScores were elevated in the low-risk group. The immune cells that infiltrated the tissues were different between the two groups, as did the expression of immune-related genes. Conclusion: The URGs signature could act as the biomarker of prognosis and selecting appropriate therapeutic drugs for PDAC patients.

Corrigendum: Prognostic implication and immunotherapy response prediction of a ubiquitination-related gene signature in breast cancer.

[This corrects the article DOI: 10.3389/fgene.2022.1038207.].

Identification of a novel reactive oxygen species (ROS)-related genes model combined with RT-qPCR experiments for prognosis and immunotherapy in gastric cancer.

Reactive oxygen species play a crucial role in the prognosis and tumor microenvironment (TME) of malignant tumors. An ROS-related signature was constructed in gastric cancer (GC) samples from TCGA database. ROS-related genes were obtained from the Molecular Signatures Database. Consensus clustering was used to establish distinct ROS-related subtypes related to different survival and immune cell infiltration patterns. Sequentially, prognostic genes were identified in the ROS-related subtypes, which were used to identify a stable ROS-related signature that predicted the prognosis of GC. Correlation analysis revealed the significance of immune cell iniltration, immunotherapy, and drug sensitivity in gastric cancers with different risks. The putative molecular mechanisms of the different gastric cancer risks were revealed by functional enrichment analysis. A robust nomogram was established to predict the outcome of each gastric cancer. Finally, we verified the expression of the genes involved in the model using RT-qPCR. In conclusion, the ROS-related signature in this study is a novel and stable biomarker associated with TME and immunotherapy responses.

Predictive Value of Noninvasive Peripheral Atherosclerosis Measurement for Coronary Artery Disease in Patients with Long T2DM Duration.

Objective: This study aimed to compare the predictive value of carotid or femoral artery ultrasound for coronary artery disease (CAD) in type 2 Diabetes mellitus (T2DM) patients free from known CAD, and to assess the relationship with the severity of coronary artery stenosis. Methods: Cross-sectional study in adults with a T2DM duration of at least 5 years and without established CAD. Carotid plaque score (CPS) and Gensini score were used to measure the severity of carotid and coronary artery stenosis, respectively, and patients were divided into no or mild group, moderate group, and severe group according to the tertile of the score. Univariate and multivariate logistic regression analysis was used to explore the possible risk factors for CAD. Receiver operating characteristic (ROC) curves were created to determine the most accurate assessment for detecting significant CAD (≥50% stenosis). Results: 245 patients (137 male) aged 68.21±9.5 years (range: 36-95 years), with T2DM duration 12.04± 6.17 years (range: 5-34 years), and without CVD were included. CAD was diagnosed in 165 patients (67.3%). Multiple regression analysis showed that CPS, femoral plaque, and smoking were independently and positively correlated with CAD. CPS yielded the highest area under the curve for detecting significant coronary disease (AUC=0.7323). In contrast, the area under the curve of femoral artery plaque and carotid intima-media thickness was lower than 0.7, which was at a lower prediction level. Conclusion: In patients with long T2DM duration, CPS has a higher ability to predict the occurrence and severity of CAD. However, femoral artery plaque has special value in predicting moderate to severe coronary artery disease in patients with long-term T2DM.

Long non-coding RNA ATB expedites non-small cell lung cancer progression by the miR-200b/fibronectin 1 axis.

BACKGROUND: Long non-coding RNA (lncRNA) ATB belongs to an active modulator in multiple cancers, but its expression along with potential underlying non-small cell lung cancer (NSCLC) is obscure. Our study aimed to investigate the role and potential mechanism of LncRNA ATB in NSCLC. METHODS: LncRNA ATB expression in NSCLC tissues and cell lines was detected by qRT-PCR. Effects of LncRNA ATB on NSCLC cell proliferation, migration and invasion were assessed by MTS, colony formation and transwell assays. The connection among LncRNA ATB, miR-200b and fibronectin 1 (FN1) was determined by bioformatics prediction and luciferase reporter assay. RESULTS: In this research, upregulation of LncRNA ATB was discovered in NSCLC tissue samples and cell lines. LncRNA ATB was positively related to advanced tumor phase as well as lymph node metastasis. Cell function assays reflected LncRNA ATB expedited NSCLC cells proliferation, migration and invasion. LncRNA ATB promoted fibronectin 1 (FN1) expression via inhibiting miR-200b. Furthermore, LncRNA ATB depletion suppressed NSCLC cells proliferation, migration and invasion, while miR-200b inhibitor or pcDNA-FN1 rescued these effects. CONCLUSION: In summary, our outcomes elucidated that LncRNA ATB/miR-200b axis expedited NSCLC cells proliferation, migration and invasion by up-regulating FN1.

Identification and validation of a novel senescence-related biomarker for thyroid cancer to predict the prognosis and immunotherapy.

Introduction: Cellular senescence is a hallmark of tumors and has potential for cancer therapy. Cellular senescence of tumor cells plays a role in tumor progression, and patient prognosis is related to the tumor microenvironment (TME). This study aimed to explore the predictive value of senescence-related genes in thyroid cancer (THCA) and their relationship with the TME. Methods: Senescence-related genes were identified from the Molecular Signatures Database and used to conduct consensus clustering across TCGA-THCA. Differentially expressed genes (DEGs) were identified between the clusters used to perform multivariate Cox regression and least absolute shrinkage and selection operator regression (LASSO) analyses to construct a senescence-related signature. TCGA dataset was randomly divided into training and test datasets to verify the prognostic ability of the signature. Subsequently, the immune cell infiltration pattern, immunotherapy response, and drug sensitivity of the two subtypes were analyzed. Finally, the expression of signature genes was detected across TCGA-THCA and GSE33630 datasets, and further validated by RT-qPCR. Results: Three senescence clusters were identified based on the expression of 432 senescence-related genes. Then, 23 prognostic DEGs were identified in TCGA dataset. The signature, composed of six genes, showed a significant relationship with survival, immune cell infiltration, clinical characteristics, immune checkpoints, immunotherapy response, and drug sensitivity. Low-risk THCA shows a better prognosis and higher immunotherapy response than high-risk THCA. A nomogram with perfect stability constructed using signature and clinical characteristics can predict the survival of each patient. The validation part demonstrated that ADAMTSL4, DOCK6, FAM111B, and SEMA6B were expressed at higher levels in the tumor tissue, whereas lower expression of MRPS10 and PSMB7 was observed. Discussion: In conclusion, the senescence-related signature is a promising biomarker for predicting the outcome of THCA and has the potential to guide immunotherapy.

Clinical characteristics and cancer-specific survival analysis of double primary cancer patients with lung cancer as the first primary cancer.

The objective of this study is to explore the prognostic factors of double primary cancer patients with lung cancer as the first primary cancer (FPC). The Surveillance, Epidemiology, and End Results (SEER) database is a database established by the National Institutes of Research for cancer registration purposes, which collects relatively complete demographic characteristics and clinical data for assessing the epidemiological characteristics of cancer worldwide. Clinical data on patients with a clear histopathological diagnosis of double primary with lung cancer as the FPC were identified and collected from the SEER database from 2010 to 2015. Survival curves were plotted by Kaplan-Meier survival analysis. Independent prognostic factors of patients were analyzed by COX proportional risk model. Clinical data were collected from a total of 9306 patients, including 6516 patients in the modeling group and 2790 patients in the validation group. When we retrieved that the FPC was lung cancer, we found that the most common site of the second primary cancer was located in the respiratory system (54.0%). In addition, the most common site of first primary lung cancer in patients with double primary cancer was the right upper lobe (33.3%). A total of 14 independent prognostic factors were included, and the constructed survival nomogram had high accuracy and clinical applicability. The nomogram established in this study can help to raise awareness of clinical workers and the importance of such diseases, and guide the treatment and follow-up strategies.

Prognostic implication and immunotherapy response prediction of a ubiquitination-related gene signature in breast cancer.

Breast cancer (BC) is one of the most common tumor types and has poor outcomes. In this study, a ubiquitination-related prognostic signature was constructed, and its association with immunotherapy response in BC was explored. A list of ubiquitination-related genes was obtained from the molecular signatures database, and a ubiquitination-related gene signature was obtained by least absolute shrinkage and selection operator Cox regression. The genes, TCN1, DIRAS3, and IZUMO4, had significant influence on BC outcomes. Patients were categorized into two clusters-a high-risk group with poor survival and a low-risk group with greater chances of controlling BC progression. Univariate and multivariate Cox regression analyses revealed that the risk signature was an independent prognostic factor for BC. Gene set enrichment analysis suggested that the high-risk group was enriched in cell cycle and DNA replication pathways. The risk score was positively linked to the tumor microenvironment and negatively correlated with the immunotherapy response. The IC50 values for rapamycin were higher in the low-risk group, whereas those for axitinib, AZD6244, erlotinib, GDC0941, GSK650394, GSK269962A, lapatinib, and PD0325901 were higher in the high-risk group. Therefore, the ubiquitination-related signature is considered a promising tool for predicting a BC patient's immunotherapy response.

Development of anoikis-related genes signature to predict the prognosis in gastric cancer patients.

Background: It is well known that the prognosis of Gastric cancer (GC) patient is affected by many factors. However, the latent impact of anoikis on the prognosis of GC patients is insufficient understood. Methods: According to the Cancer Genome Atlas (TCGA) database, we elected discrepantly expressed anoikis-related genes (ARGs). Univariate cox and the least absolute shrinkage and selection operator (lasso) analysis were applied to build the ARGs signature. The prognostic effect of the ARGs signature was also evaluated. A series of algorithms were performed to evaluate the discrepancies in the immune microenvironment. Moreover, the correlation between drug sensitivity and ARGs signature was analyzed. We also performed Real-Time Polymerase Chain Reaction (RT-PCR) to probe the signature. Results: The ARGs signature of 9 genes was constructed, which was apparently interrelated with the prognosis. The nomogram was established by combining the ARGs signature with clinicopathological characteristics. We found that the predictive power was noteworthily superior to other individual predictors. The immune microenvironment analysis indicated that ESTIMATEscore, ImmuneScores, StromalScores, tumor immune dysfunction and exclusion (TIDE) score were lower in the low-risk group, while immunophenoscore (IPS) was on the contrary. The infiltrated immune cells and immune checkpoint (ICP) expression levels were significantly different between the two groups. Furthermore, nine drugs were positively associated with the ARGs signature score. The results of RT-PCR analysis were consistent with our previous differential expression analysis. Conclusion: The developed ARGs signature could act as the biomarker and provide a momentous reference for Individual therapy of GC patients.

IGF2BP2 rs11705701 polymorphisms are associated with prediabetes in a Chinese population: A population-based case-control study.

Associations between insulin-like growth factor 2 mRNA-binding protein 2 (IGF2BP2) rs11705701, insulin receptor substrate 1 rs7578326, gastric inhibitory polypeptide receptor rs10423928 and transcription factor 7-like 2 rs12255372 gene polymorphisms with prediabetes and type 2 diabetes (T2D) have not been evaluated in the Han Chinese population. These four genetic variants were investigated for their associations with prediabetes and T2D among 490 unrelated patients with T2D, 471 patients with prediabetes and 575 healthy controls. Sequenom MassARRAY software was used to genotype the patients for these variants. The Generalized Multifactor Dimensionality Reduction method was used to analyze the gene-gene and gene-environment interactions. A breakdown analysis by gender revealed a significant association of IGF2BP2 rs11705701 with prediabetes under the dominant genetic model in females following application of the Bonferroni correction (odds ratio = 0.26; 95% confidence interval = 0.10-0.67; P=0.005). However, no significant associations were reported between any of the other three polymorphisms and T2D under any genetic models. Furthermore, there were no statistically significant gene-gene or gene-environment interactions when evaluated with the above association tests. The present case-control study reveals a significant association between IGF2BP2 rs11705701 and prediabetes in female patients.

Peripheral blood IRF1 expression as a marker for glucocorticoid sensitivity.

OBJECTIVE: Despite of the common usage of glucocorticoids (GCs), a significant portion of asthma patients exhibit GC insensitivity. This could be mediated by diverse mechanisms, including genomics. Recent work has suggested that measuring changes in gene expression may provide more predictive information about GC insensitivity than baseline gene expression alone, and that expression changes in peripheral blood may be reflective of those in the airway. METHODS: We performed in silico discovery using gene expression omnibus (GEO) data that evaluated GC effect on gene expression in multiple tissue types. Subsequently, candidate genes whose expression levels are affected by GC were examined in cell lines and in primary cells derived from human airway and blood. RESULTS: Through gene expression omnibus analysis, we identified interferon regulator factor 1 (IRF1), whose expression is affected by GC treatment in airway smooth muscle cells, normal human bronchial epithelial (NHBE) cells, and lymphoblastoid cell lines (LCLs). Significant IRF1 downregulation post GC exposure was confirmed in two cultured airway epithelial cell lines and primary NHBE cells (P<0.05). We observed large interindividual variation in GC-induced IRF1 expression changes among primary NHBE cells tested. Significant downregulation of IRF1 was also observed in six randomly selected LCLs (P<0.05), with variable degrees of downregulation among different samples. In peripheral blood mononuclear cells obtained from healthy volunteers, variable downregulation of IRF1 by GC was also shown. NFKB1, a gene whose expression is known to be downregulated by GC and the degree of downregulation of which is reflective of GC response, was used as a control in our study. IRF1 shows more consistent downregulation across tissue types when compared with NFKB1. CONCLUSION: Our results suggest that GC-induced IRF1 gene expression changes in peripheral blood could be used as a marker to reflect GC response in the airway.

Landscape of the relationship between type 2 diabetes and coronary heart disease through an integrated gene network analysis.

Type 2 diabetes (T2D) and coronary artery disease (CAD) are closely related chronic diseases with high prevalence and morbidity. However, a comprehensive comparison of the two diseases is lacking. Recent genome-wide association studies (GWAS) have identified a handful of single nucleotide polymorphisms (SNPs) that are significantly associated with the risk of T2D and CAD. These most significant findings may help interpret the pathogenesis of T2D and CAD. However, tremendous results from these GWAS are ignored. Here we revisited the raw datasets of these GWAS and performed an integrated gene network analysis to unveil the relationship between T2D and CAD by combining multiple datasets including protein-protein interaction (PPI) database, publication libraries, and pathway datasets. Our results showed that majority of genes were involved in the first module (1122 genes in T2D and 895 in CAD). Four pathways were found to be common in both T2D and CAD, including regulation of actin cytoskeleton, calcium signaling pathway, MAPK signaling pathway and focal adhesion (all P<0.00001). MAX which was involved in small cell lung cancer pathway was a hub gene unique to T2D (OR=1.2, P=0.006) but not in CAD. In contrast, three hub genes including PLEKHG5 (T2D: OR=1, P=1; CAD: OR=1.12, P=0.006), TIAM1 (T2D: OR=1, P=1; CAD: OR=1.48, P=0.004) and AKAP13 (T2D: OR=1, P=1; CAD: OR=1.38, P=0.001) were hub genes unique to CAD. Moreover, for some hub genes (such as SMAD3) that were susceptible to both T2D and CAD, their associated polymorphisms were unique to each of the two diseases. Our findings might provide a landscape of the relationship between T2D and CAD.

Prevalence and risk factors of gallbladder polypoid lesions in Chinese petrochemical employees.

AIM: To investigate the prevalence and risk factors of polypoid lesions of the gallbladder (PLGs) in petrochemical employees in Ningbo, Zhejiang Province, China. METHODS: All active and retired employees aged 20-90 years (n = 11098) of a refinery and chemical plant in eastern China were requested to participate in a health survey. The participants were subjected to interview, physical examination, laboratory assessments and ultrasonography. All the participants were invited to have a physical examination after a face-to-face interview. Fasting blood samples were obtained from the antecubital vein, and the samples were used for the analysis of biochemical values. Abdominal ultrasonography was conducted. RESULTS: A total of 10461 (7331 men and 3130 women) current and former petrochemical employees attended for screening. The overall prevalence of post-cholecystectomy, gallstones and PLGs was 0.9%, 5.2% and 7.4%, respectively. Compared with the increased prevalence of either gallstones or post-cholecystectomy in older persons, PLGs were more common in the middle-aged, peaking in those aged 40-59 years. Excluding the patients with gallstones, gallstones mixed with PLGs, or those who had undergone cholecystectomy, in the remaining 9828 participants, the prevalence of PLGs in men (8.9%) was significantly higher than that in women (5.5%, P < 0.001). The analyzed risk factors with increased OR for the development of PLGs were male gender (OR = 1.799, P < 0.001), age ≥ 30 years (OR = 2.699, P < 0.001) and hepatitis B surface antigen (HBsAg) positivity (OR = 1.374, P = 0.006). CONCLUSION: PLGs are not rare among Chinese petrochemical employees. Male gender, HBsAg positivity, and middle age are risk factors for developing PLGs.