Objective: To investigate the clinicopathological features of perivascular epithelioid cell tumor (PEComa) of the lung. Methods: Eight PEComa cases of the lung diagnosed at the First Affiliated Hospital of Soochow University, Suzhou, China from July 2008 to December 2021 were collected and subject to immunohistochemical staining, fluorescence in situ hybridization and next generation sequencing. The relevant literature was reviewed and the clinicopathological features were analyzed. Results: There were 5 males and 3 females, aged from 18 to 70 years (mean 39 years). There were 3 cases of the right upper lung, 3 cases of the left lower lung, 1 case of the left upper lung and 1 case of the right middle lung. Seven cases were solitary and 1 case was multifocal (4 lesions). Seven cases were benign while one was malignant. The tumors were all located in the peripheral part of the lung, with a maximum diameter of 0.2-4.0 cm. Grossly, they were oval and well circumscribed. Microscopically, the tumor cells were oval, short spindle-shaped, arranged in solid nests, acinar or hemangiopericytoma-like patterns, with clear or eosinophilic cytoplasm. The stroma was rich in blood vessels with hyalinization. Coagulated necrosis and high-grade nuclei were seen in the malignant case, and calcification was seen in 2 cases. Immunohistochemically, the tumor cells were positive for Melan A (8/8), HMB45 (7/8), CD34 (6/8), TFE3 (4/7), and SMA (3/8). All cases were negative for CKpan and S-100. TFE3 (Xp11.2) gene fusion was examined using the TFE3 break-apart fluorescence in situ hybridization in 5 cases, in which only the malignant case was positive. The next generation sequencing revealed the SFPQ-TFE3 [t(X;1)(p11.2;p34)] fusion. Follow-up of the patients ranged from 12 to 173 months while one patient was lost to the follow-up. The malignant case had tumor metastasis to the brain 4 years after the operation and then received radiotherapy. Other 6 cases had no recurrence and metastasis, and all the 7 patients survived. Conclusions: Most of the PEComas of the lung are benign. When there are malignant morphological features such as necrosis, high-grade nuclei or SFPQ-TFE3 gene fusion, close follow-up seems necessary.
Male ; Female ; Humans ; In Situ Hybridization, Fluorescence ; Perivascular Epithelioid Cell Neoplasms/pathology* ; Lung/pathology* ; Basic Helix-Loop-Helix Leucine Zipper Transcription Factors/genetics* ; Necrosis ; Biomarkers, Tumor/analysis*

Male ; Humans ; Prostate/pathology* ; Adenocarcinoma/pathology* ; Giant Cells/pathology*

Alanine Transaminase ; Animals ; Carbon Tetrachloride ; Gastrointestinal Microbiome ; Liver/pathology* ; Liver Cirrhosis/pathology* ; Male ; Mice ; Mice, Inbred C57BL ; Quinazolines

Adult ; Brain ; Brain Diseases ; Heat Stroke ; Humans ; Magnetic Resonance Imaging ; Male ; Retrospective Studies

Adult ; Air Pollutants, Occupational ; Humans ; Lung ; Male ; Occupational Diseases ; Occupational Exposure ; Vital Capacity ; Welding

Cross-Sectional Studies ; Depression/epidemiology* ; Humans ; Job Satisfaction ; Occupational Stress/epidemiology* ; Oil and Gas Fields ; Stress, Psychological ; Surveys and Questionnaires

To address the increasing need for detecting and validating protein biomarkers in clinical specimens, mass spectrometry (MS)-based targeted proteomic techniques, including the selected reaction monitoring (SRM), parallel reaction monitoring (PRM), and massively parallel data-independent acquisition (DIA), have been developed. For optimal performance, they require the fragment ion spectra of targeted peptides as prior knowledge. In this report, we describe a MS pipe-line and spectral resource to support targeted proteomics studies for human tissue samples. To build the spectral resource, we integrated common open-source MS computational tools to assemble a freely accessible computational workflow based on Docker. We then applied the workflow to gen-erate DPHL, a comprehensive DIA pan-human library, from 1096 data-dependent acquisition (DDA) MS raw files for 16 types of cancer samples. This extensive spectral resource was then applied to a proteomic study of 17 prostate cancer (PCa) patients. Thereafter, PRM validation was applied to a larger study of 57 PCa patients and the differential expression of three proteins in prostate tumor was validated. As a second application, the DPHL spectral resource was applied to a study consisting of plasma samples from 19 diffuse large B cell lymphoma (DLBCL) patients and 18 healthy control subjects. Differentially expressed proteins between DLBCL patients and healthy control subjects were detected by DIA-MS and confirmed by PRM. These data demonstrate that the DPHL supports DIA and PRM MS pipelines for robust protein biomarker discovery. DPHL is freely accessible at https://www.iprox.org/page/project.html?id=IPX0001400000.

Precision medicine became the key strategy in development priority of science and technology in China. The large population-based cohorts become valuable resources in preventing and treating major diseases in the population, which can contribute scientific evidence for personalized treatment and precise prevention. The fundamental question of the achievements above, therefore, is how to construct a large population-based cohort in a standardized way. The Chinese Preventive Medicine Association co-ordinated experienced researchers from Peking University and other well-known institutes to write up two group standards Technical specification of data processing for large population-based cohort study (T/CPMA 001-2018) and Technical specification of data security for large population-based cohort study (T/CPMA 002-2018), on data management. The standards are drafted with principles of emphasizing their scientific, normative, feasible, and generalizable nature. In these two standards, the key principles are proposed, and technical specifications are recommended in data standardization, cleansing, quality control, data integration, data privacy protection, and database security and stability management in large cohort studies. The standards aim to guide the large population-based cohorts that have been or intended to be established in China, including national cohorts, regional population cohorts, and special population cohorts, hence, to improve domestic scientific research level and the international influence, and to support decision-making and practice of disease prevention and control.
China ; Cohort Studies ; Delivery of Health Care ; Humans ; Population Surveillance ; Quality Control ; Reference Standards

Objective: To describe the genetic structure of populations in different areas of China, and explore the effects of different strategies to control the confounding factors of the genetic structure in cohort studies. Methods: By using the genome-wide association study (GWAS) on data of 4 500 samples from 10 areas of the China Kadoorie Biobank (CKB), we performed principal components analysis to extract the first and second principal components of the samples for the component two-dimensional diagram generation, and then compared them with the source of sample area to analyze the characteristics of genetic structure of the samples from different areas of China. Based on the CKB cohort data, a simulation data set with cluster sample characteristics such as genetic structure differences and extensive kinship was generated; and the effects of different analysis strategies including traditional analysis scheme and mixed linear model on the inflation factor (λ) were evaluated. Results: There were significant genetic structure differences in different areas of China. Distribution of the principal components of the population genetic structure was basically consistent with the geographical distribution of the project area. The first principal component corresponds to the latitude of different areas, and the second principal component corresponds to the longitude of different areas. The generated simulation data showed high false positive rate (λ=1.16), even if the principal components of the genetic structure was adjusted or the area specific subgroup analysis was performed, λ could not be effectively controlled (λ>1.05); while, by using a mixed linear model adjusting for the kinship matrix, λ was effectively controlled regardless of whether the genetic structure principal component was further adjusted (λ=0.99). Conclusions: There were large differences in genetic structure among populations in different areas of China. In molecular epidemiology studies, bias caused by population genetic structure needs to be carefully treated. For large cohort data with complex genetic structure and extensive kinship, it is necessary to use a mixed linear model for association analysis.
China ; Genetic Structures ; Genome-Wide Association Study ; Humans ; Linear Models ; Principal Component Analysis

Objective: To evaluate the association of educational level with anthropometric measurements at different adult stages and their long-term changes in adults who participated in the second re-survey of China Kadoorie Biobank (CKB). Methods: The present study excluded participants who were aged >65 years, with incomplete or extreme measurement values, or with major chronic diseases at baseline survey or re-survey. The weight at age 25 years was self-reported. Body height, body weight and waist circumference at baseline survey (2004-2008) and re-survey (2013-2014) were analyzed. Results: The present study included 3 427 men and 6 320 women. Both body weight and waist circumference (WC) increased with age. From age 25 years to baseline survey (mean age 45.2±6.5), the mean weight change per 5-year was (1.70±2.63) kg for men and (1.27±2.10) kg for women. From baseline survey to re-survey (53.2±6.5), the mean changes per 5-year for body weight were (1.12±2.61) kg for men and (0.90±2.54) kg for women; and that for WC was (3.20±3.79) cm for men and (3.83±3.85) cm for women. Among women, low educational level was consistently associated with higher body mass index (BMI) and WC at age 25 years, baseline survey and re-survey. Among men, low educational level was associated with higher BMI at age 25 years. At baseline survey and re-survey, the educational level in men was not statistically associated with BMI; but men who completed junior or senior high school showed slight higher WC and increase of WC from baseline survey to re-survey than other male participants. Conclusions: Body weight and WC increased with age for both men and women. The associations of educational level with BMI and WC were different between men and women.
Adult ; Asian People/statistics & numerical data* ; Body Height ; Body Mass Index ; Body Weight ; China/epidemiology* ; Educational Status ; Female ; Humans ; Male ; Middle Aged ; Obesity/ethnology* ; Risk Factors ; Sex Distribution ; Waist Circumference/ethnology*