Circular extrachromosomal DNA promotes tumor heterogeneity in high-risk medulloblastoma

Circular extrachromosomal DNA (ecDNA) in patient tumors is an important driver of oncogenic gene expression, evolution of drug resistance and poor patient outcomes. Applying computational methods for the detection and reconstruction of ecDNA across a retrospective cohort of 481 medulloblastoma tumors from 465 patients, we identify circular ecDNA in 82 patients (18%). Patients with ecDNA-positive medulloblastoma were more than twice as likely to relapse and three times as likely to die within 5 years of diagnosis. A subset of tumors harbored multiple ecDNA lineages, each containing distinct amplified oncogenes. Multimodal sequencing, imaging and CRISPR inhibition experiments in medulloblastoma models reveal intratumoral heterogeneity of ecDNA copy number per cell and frequent putative 'enhancer rewiring' events on ecDNA. This study reveals the frequency and diversity of ecDNA in medulloblastoma, stratified into molecular subgroups, and suggests copy number heterogeneity and enhancer rewiring as oncogenic features of ecDNA.

Coordinated inheritance of extrachromosomal DNA species in human cancer cells

The chromosomal theory of inheritance has dominated human genetics, including cancer genetics. Genes on the same chromosome segregate together while genes on different chromosomes assort independently, providing a fundamental tenet of Mendelian inheritance. Extrachromosomal DNA (ecDNA) is a frequent event in cancer that drives oncogene amplification, dysregulated gene expression and intratumoral heterogeneity, including through random segregation during cell division. Distinct ecDNA sequences, herein termed ecDNA species, can co-exist to facilitate intermolecular cooperation in cancer cells. However, how multiple ecDNA species within a tumor cell are assorted and maintained across somatic cell generations to drive cancer cell evolution is not known. Here we show that cooperative ecDNA species can be coordinately inherited through mitotic co-segregation. Imaging and single-cell analyses show that multiple ecDNAs encoding distinct oncogenes co-occur and are correlated in copy number in human cancer cells. EcDNA species are coordinately segregated asymmetrically during mitosis, resulting in daughter cells with simultaneous copy number gains in multiple ecDNA species prior to any selection. Computational modeling reveals the quantitative principles of ecDNA co-segregation and co-selection, predicting their observed distributions in cancer cells. Finally, we show that coordinated inheritance of ecDNAs enables co-amplification of specialized ecDNAs containing only enhancer elements and guides therapeutic strategies to jointly deplete cooperating ecDNA oncogenes. Coordinated inheritance of ecDNAs confers stability to oncogene cooperation and novel gene regulatory circuits, allowing winning combinations of epigenetic states to be transmitted across cell generations.

[Artificial intelligence-based literature data warehouse for vaccine safety]

Objective: To establish a sustainable updated literature data warehouse for global vaccine safety assessment, and provide data support for evidence-based vaccine safety assessment. Methods: Semi-automated construction and updating of a literature data warehouse were achieved through the continuous integration of standard operating steps of evidence-based reviews with artificial intelligence technologies. Following the standard procedure of a systematic literature review, the literatures about vaccine safety assessment published before November 29, 2020 were retrieved from 9 databases including OVID, Scopus, Web of Science, Cochrane Library, and ClinicalTrails.org in English and Wanfang, CNKI, VIP, and SinoMed in Chinese. Literatures were screened for two rounds in a semi-automatic manner (by artificial intelligence literature processing system and manual work) according to the inclusion/exclusion criteria. Furthermore, the literatures were classified according to the types of vaccines and adverse events. The updating strategy was established, and the literature data warehouse was updated regularly. Experts were organized to select specific vaccine safety topics and carry out special demonstration studies. Results: More than 0.41 million articles were retrieved. According to the inclusion/exclusion criteria, 23 304 articles were included after two rounds of screening. At present, we have selected and completed three prior topics as demonstration studies, including the systematic review of "DPT (diphtheria, pertussis and tetanus) vaccine and encephalopathy/encephalitis", and the classified management of literatures about allergic purpura and brachial plexus neuritis. Conclusions: The sustainable updated literature data warehouse of vaccine safety can provide high-quality research data for vaccine safety research, including evidence support for immunization related policy-making and adjustment and vaccine safety-related methodological research or clinical tool development; and further demonstration studies can provide references for building a new methodological framework system for timely and efficient completion of the evidence-based assessment of vaccine safety.

[The risk prediction models for occurrence of cervical cancer: a systematic review]

Objective: To systematically summarize and assess risk prediction models for occurrence of cervical cancer and to provide evidence for selecting the most reliable model for practice, and guide cervical cancer screening. Methods: Two groups of keywords related to cervical cancer and risk prediction model were searched on Chinese databases (CNKI, and Wanfang) and English databases (PubMed, Embase, and Cochrane Library). Original articles that developed or validated risk prediction models and published before November 21, 2019, were selected. Information form was created based on the CHARMS checklist. The PROBAST was used to assess the risk of bias. Results: 12 eligible articles were identified, describing 15 prediction models, of which five were established in China. The predicted outcomes included multiple stages from cervical precancerous lesions to cancer occurrence, i.e., abnormal Pap smear (1), occurrence or recurrence of CIN (9), and occurrence of cervical cancer (5), etc. The most frequently used predictors were HPV infection (12), age (7), smoking (5), and education (5). There were two models using machine learning to develop models. In terms of model performance, the discrimination ranged from 0.53 to 0.87, while only two models assessed the calibration correctly. Only two models were externally validated in Taiwan of China, using people in different periods. All of the models were at high risk of bias, especially in the analysis domain. The problems were concentrated in the improper handling of missing data (13), preliminary evaluation of model performance (13), improper use of internal validation (12), and insufficient sample size (11). In addition, the problems of inconsistency measurements of predictors and outcomes (8) and the flawed report of the use of blindness for outcome measures (8) were also severe. Compared with the other models, the Rothberg (2018) model had relatively high quality. Conclusions: There are a certain number of cervical cancer risk prediction models, but the quality is poor. It is urgent to improve the measurement of predictors and outcomes, the statistical analysis details such as handling missing data and evaluation of model performance and externally validate existing models to better guide screening.

[Prescription sequence symmetry analysis in pharmacoepidemiology: a systematic review]

Objective: To systematically evaluate and analyze the original research of prescription sequence symmetry analysis (PSSA), summarize its research progress and methodological details, and provide a reference for the future use of this method. Methods: The keywords related to PSSA were used for literature retrieval from Chinese databases (CNKI, Wanfang, and VIP) and English databases (PubMed, Embase, and Cochrane). Original articles that were related to PSSA and published before June 30, 2020 were selected. Information form was developed by Excel. Stata was used for the statistics analysis. Results: There were 45 eligible articles included in the research. Since 2013, the number of studies using PSSA has increased rapidly. These studies were mainly conducted in Japan (n=11, 24.44%), China (n=10, 22.22%), Denmark (n=9, 20.00%), and Australia (n=8, 17.78%). Medical claim database was used most commonly when PSSA was implemented. The included studies involved 16 types of drugs, of which the number of studies of psychotropic drugs and statins was highest (n=8, 17.78%), and adverse reactions of almost all human systems were involved. In terms of methodology, 35 (77.78%) and 43 (95.56%) studies clearly reported the run-in period and interval period, of which 14 (31.11%) and 9 (20.00%) respectively gave the method or reason for determining the duration. In addition, 16 articles (35.56%) and 18 articles (40.00%) reported sensitivity analysis and subgroup analysis results, respectively. Conclusions: PSSA, one of the effective methods for safety signal detection in healthcare databases, has developed rapidly, but the methodological details and result reporting need to be improved. In China, PSSA research is still in its infancy, and it is necessary to pay attention to the quality of research and promote methodological exploration.

[A cross-sectional study on current status of rare disease related health information based on WeChat official accounts in China]

Objective: To understand the current status of rare disease related health information release in WeChat official accounts in China. Methods: We used a series of key words containing "rare diseases" and the names of the top 30 rare diseases in hospitalizations in China to search WeChat official accounts. Eligible articles were selected by systematic sampling. All including WeChat official accounts and articles were evaluated to extract the basic information. Results: No relevant WeChat official accounts were found for 14 rare diseases (46.67%). Most of the WeChat official accounts (52.17%) were initiated by patients and patient groups. No significant difference was detected in the total number of articles between the official accounts related with Traditional Chinese Medicine (TCM) and non-TCM related ones, however, the frequency of the monthly information release was significantly higher in TCM related official accounts (P<0.001), while the average reading number of articles was significantly higher in non-TCM related official accounts (P<0.001). Nearly 80% of the WeChat official accounts had navigation menu, and the average reading number of official accounts with menus was larger than those without menus. The top three topics were rare disease diagnosis and treatment knowledge (46.00%), public welfare activity for rare diseases (12.81%) and uncorrelated things (8.65%), while the first three leading topics were cutting-edge information, public welfare activity and patient story, respectively. Conclusions: The scale for rare disease related health information release based on WeChat official accounts in China has been basically formed, but it is still in development stage. Many improvements should be made in their coverage of rare diseases, release frequency, topic and form. It is urgent to establish or recreate some high-quality WeChat official accounts in order to provide precise information and effectively facilitate the prevention and treatment of rare diseases.