Large-scale Pan-cancer Cell Line Screening Identifies Actionable and Effective Drug Combinations.

Oncology drug combinations can improve therapeutic responses and increase treatment options for patients. The number of possible combinations is vast and responses can be context-specific. Systematic screens can identify clinically relevant, actionable combinations in defined patient subtypes. We present data for 109 anticancer drug combinations from AstraZeneca's oncology small molecule portfolio screened in 755 pan-cancer cell lines. Combinations were screened in a 7 × 7 concentration matrix, with more than 4 million measurements of sensitivity, producing an exceptionally data-rich resource. We implement a new approach using combination Emax (viability effect) and highest single agent (HSA) to assess combination benefit. We designed a clinical translatability workflow to identify combinations with clearly defined patient populations, rationale for tolerability based on tumor type and combination-specific "emergent" biomarkers, and exposures relevant to clinical doses. We describe three actionable combinations in defined cancer types, confirmed in vitro and in vivo, with a focus on hematologic cancers and apoptotic targets. SIGNIFICANCE: We present the largest cancer drug combination screen published to date with 7 × 7 concentration response matrices for 109 combinations in more than 750 cell lines, complemented by multi-omics predictors of response and identification of "emergent" combination biomarkers. We prioritize hits to optimize clinical translatability, and experimentally validate novel combination hypotheses. This article is featured in Selected Articles from This Issue, p. 695.

Association of sugar sweetened beverage consumption with insomnia and depressive symptoms among first grade middle school students from Yunnan Province / 中国学校卫生

Objective@#To investigate the association of sugar sweetened beverage (SSB) consumption with insomnia and depressive symptoms among first grade middle school students from Yunnan Province, so as to provide evidence to guide interventions for the treatment of these symptoms in this population.@*Methods@#From October to December 2022, 8 500 firstgrade middle school students from 11 counties in Yunnan Province were selected by cluster random sampling. Depressive symptoms, SSB consumption, and insomnia symptoms among students were evaluated by the Child Depression Scale (CDI), dietary frequency questionnaire, and Insomnia Severity Index (ISI). A Logistic regression model was employed to analyze the relationship between SSB consumption, insomnia, depressive symptoms, and their interaction effects among students.@*Results@#The detection rate of depressive symptoms was 28.3%, and having insomnia symptoms ( OR=6.07, 95%CI =5.46-6.75), consuming carbonated beverages ( OR=1.20, 95%CI =1.08-1.34), tea ( OR=1.13, 95%CI =1.02-1.25), energy drinks ( OR=1.36, 95%CI =1.23-1.50), and other beverages ( OR=1.32, 95%CI =1.19-1.45) were positively correlated with depressive symptoms among first grade middle school students ( P < 0.05). Carbonated beverages (additive effect: OR=2.96, 95%CI =2.72-3.22, multiplicative effect: OR=4.75, 95%CI =4.25- 5.32 ), fruit drinks (additive effect: OR=2.61, 95%CI =2.40-2.82; multiplicative effect: OR=4.43, 95%CI =3.94-4.97), tea (additive effect: OR=2.70, 95%CI =2.47-2.89; multiplicative effect: OR=4.34, 95%CI =3.86-4.89), energy drinks (additive effect: OR=2.82, 95%CI =2.61-3.05; multiplicative effect: OR=4.48, 95%CI =3.92-5.12), sweetened milk (additive effect: OR= 2.73, 95%CI =2.06-2.96; multiplicative effect: OR=4.61, 95%CI =4.12-5.17) and other beverages (additive effect: OR= 2.73 , 95%CI =2.53-2.95; multiplicative effect: OR=4.56, 95%CI =4.00-5.20) had both additive and multiplicative effects with insomnia, and increased the risk of depressive symptoms in first grade middle school students ( P <0.01).@*Conclusions@#The interaction between the consumption of SSB and insomnia symptoms may increase the risk of depressive symptoms among first grade middle school students in Yunnan Province. It is necessary to advocate middle school students to reduce SSB intake, in order to decrease the occurrence of depressive symptoms among this population.

Association between latent classes of dietary patterns and depressive symptoms among firstgrade students from multi ethnic middle schools in Yunnan Province / 中国学校卫生

Objective@#To determine the latent class of dietary patterns and their association with depressive symptoms among first grade students from multi ethnic middle schools in Yunnan Province, so as to provide a reference basis for promoting mental health among border middle school students.@*Methods@#A cluster random sampling involving 8 500 first grade middle school students from 11 counties in Yunnan Province was conducted by a questionnaire survey between October to December 2022. The Children s Depression Inventory (CDI) was used to assess the depressive symptoms and the Food Frequency Questionnaire was used to collect eating behavior data. The latent profile analysis model was used to fit the latent class of dietary patterns among students. The association between the dietary pattern latent class and depressive symptoms was analyzed by Logistic regression.@*Results@#The depressive symptom detection rate among firstgrade middle school students was 28.3%. Prevalence of depressive symptom in girls (30.9%) was higher than boys (25.5%) with a statistically significant difference ( χ 2=29.83, P <0.01). The dietary patterns among first grade middle school students were classified into four latent classes, as follows:class 1 (low consumption of all dietary components), class 2 (high consumption of fruit, milk and dairy products), class 3 (high consumption of vegetables and meat, and low consumption of processed foods) and class 4 (low consumption of milk, dairy products and eggs, and high consumption of processed foods). After adjusting for confounding variables, the class 3 dietary pattern was negatively correlated with depressive symptoms ( OR=0.62, 95%CI =0.52-0.74) and the class 4 dietary pattern was positively correlated with depressive symptoms ( OR= 1.28 , 95%CI =1.05-1.57) ( P <0.05), compared with the class 1 dietary pattern.@*Conclusions@#Multi ethnic first grade middle school students in Yunnan Province follow various dietary patterns. Unhealthy dietary patterns increase the risk of depressive symptoms. The dietary patterns of multi ethnic middle school students in Yunnan Province should be adjusted to promote the establishment of healthy dietary patterns and reduce the risk of depression symptoms in middle school students.

Decision tree model of depressive symptoms among first grade students from multi ethnic middle schools in Yunnan Province / 中国学校卫生

Objective@#To understand the occurrence and predictive factors of depressive symptoms among multi ethnic middle school students in Yunnan Province, so as to provide a referential framework for schools to carry out targeted mental health education.@*Methods@#From October to December 2022, 8 500 first grade students from 23 middle schools were selected from 11 minority areas in Yunnan Province by cluster random sampling method. Demographic information and data relating to the students lifestyles were collected by questionnaire, and the Children s Depression Inventory (CDI) was used to evaluate depressive symptoms. Chi square test was performed to compare differences in the detection rate of depressive symptoms among first grade middle school students for univariate analysis. A decision tree model of depressive symptoms in middle school students was established by using the Chi squared automatic interaction detector (CHAID).@*Results@#The detection rate of depressive symptoms among first grade students from multi ethnic middle schools in Yunnan Province was 28.26%. The decision tree model of depressive symptoms was academic stress ( χ 2=469.08) at the first level, breakfast behaviors (low/moderate academic stress: χ 2=155.49; severe academic stress: χ 2=105.24) at the second level, and the number of close friends (low/moderate academic stress and consuming breakfast 0- 2 days weekly: χ 2=23.15; low/moderate academic stress and consuming breakfast 3-4 days weekly: χ 2=14.99; severe academic stress and consuming breakfast 0-2 days weekly: χ 2=29.26; severe academic stress and consuming breakfast 3-4 days weekly: χ 2=20.15), ethnicity ( χ 2=78.22) and drinking ( χ 2=50.36) at the third level ( P <0.01).@*Conclusions@#The study identifies academic stress, breakfast behaviors, number of close friends, drinking and ethnicity as predictive factors of depressive symptoms among multi ethnic middle school students in Yunnan Province. Schools should develop targeted strategies for preventing and managing depressive symptoms in middle school students, so as to reduce their occurrence.

[Industrial development and biomedical application prospect of recombinant collagen].

Recombinant collagen, as an alternative to natural collagen, has the potential to be widely used in biomaterials, biomedicine, etc. Diverse recombinant collagens and their variants can be industrially produced in a variety of expression systems, which lays a foundation for exploring and expanding the clinical application of recombinant collagens. We reviewed different expression systems for recombinant collagens, such as prokaryotic expression systems, yeast expression systems, as well as plant, insect, mammal, and human cell expression systems, and introduced the advantages, potential applications, and limitations of recombinant collagen. In particularly, we focused on the current progress in the recombinant collagen production, including recombinant expression system construction and hydroxylation strategies of recombinant collagen, and summarized the current biomedical applications of recombinant collagen.

Effective drug combinations in breast, colon and pancreatic cancer cells.

Combinations of anti-cancer drugs can overcome resistance and provide new treatments1,2. The number of possible drug combinations vastly exceeds what could be tested clinically. Efforts to systematically identify active combinations and the tissues and molecular contexts in which they are most effective could accelerate the development of combination treatments. Here we evaluate the potency and efficacy of 2,025 clinically relevant two-drug combinations, generating a dataset encompassing 125 molecularly characterized breast, colorectal and pancreatic cancer cell lines. We show that synergy between drugs is rare and highly context-dependent, and that combinations of targeted agents are most likely to be synergistic. We incorporate multi-omic molecular features to identify combination biomarkers and specify synergistic drug combinations and their active contexts, including in basal-like breast cancer, and microsatellite-stable or KRAS-mutant colon cancer. Our results show that irinotecan and CHEK1 inhibition have synergistic effects in microsatellite-stable or KRAS-TP53 double-mutant colon cancer cells, leading to apoptosis and suppression of tumour xenograft growth. This study identifies clinically relevant effective drug combinations in distinct molecular subpopulations and is a resource to guide rational efforts to develop combinatorial drug treatments.

Project Score database: a resource for investigating cancer cell dependencies and prioritizing therapeutic targets.

CRISPR genetic screens in cancer cell models are a powerful tool to elucidate oncogenic mechanisms and to identify promising therapeutic targets. The Project Score database (https://score.depmap.sanger.ac.uk/) uses genome-wide CRISPR-Cas9 dropout screening data in hundreds of highly annotated cancer cell models to identify genes required for cell fitness and prioritize novel oncology targets. The Project Score database currently allows users to investigate the fitness effect of 18 009 genes tested across 323 cancer cell models. Through interactive interfaces, users can investigate data by selecting a specific gene, cancer cell model or tissue type, as well as browsing all gene fitness scores. Additionally, users can identify and rank candidate drug targets based on an established oncology target prioritization pipeline, incorporating genetic biomarkers and clinical datasets for each target, and including suitability for drug development based on pharmaceutical tractability. Data are freely available and downloadable. To enhance analyses, links to other key resources including Open Targets, COSMIC, the Cell Model Passports, UniProt and the Genomics of Drug Sensitivity in Cancer are provided. The Project Score database is a valuable new tool for investigating genetic dependencies in cancer cells and the identification of candidate oncology targets.

High-throughput sequencing analysis of the microbiota of subgingival plaque in patients with periodontitis / 口腔疾病防治

Objective @# To detect the composition of the subgingival microbiota in generalized aggressive periodontitis (GAgP) and severe chronic periodontitis (SCP) patients tested by high-throughput sequencing (HTS) technologies, analyze its diversity and function by using bioinformatics, and observe changes in the subgingival microbiota before and after periodontal initial therapy.@* Methods@#Eleven patients with GAgP and 14 patients with SCP who visited the Department of Periodontics in Stomatological Hospital of Kunming Medical University from September 2018 to May 2019 were recruited, and subgingival plaque samples were collected at baseline and 6 weeks after initial therapy. Then, the genomic DNA was distracted and sequenced by the Illumina MiSeq high-throughput sequencing platform. QIIME (quantitative insights in microbial ecology), Mothur, SPSS and other software were used to analyze community information. LEfSe difference analysis (linear discriminant analysis effect size), network analysis, and the KEGG PATHWAY database (https://www.kegg.jp/kegg/pathway.html) were used to predict community function. @* Results @# At baseline, the dominant microbiota of GAgP and SCP patients were similar, including Bacteroidetes, Porphyromonas and Porphyromonas endodontalis. Six weeks after initial therapy, as the periodontal pocket became shallower, the variation trend of the microbiota of GAgP and SCP patients was similar. The relative abundance of gram-negative bacteria, such as Bacteroidetes, Porphyromonas and Porphyromonas endodontalis, decreased, while the relative abundance of gram-positive bacteria, such as Proteobacteria, Actinomyces and Rothia aeria, increased. Actinobacteria were significantly increased biomarkers of the subgingival microbiota in GAgP after treatment. Streptococcus is an important genus that connects the microbiota related to periodontitis and the microbiota related to periodontal health. Community function prediction result showed that initial treatment can reduce the functions of amino acid metabolism, methane metabolism, and peptidase in GAgP and SCP patients.@*Conclusion@#The subgingival microbiota of GAgP and SCP patients are similar. Streptococcus, as an early colonizer, may play an important role in promoting plaque biofilm formation and maturation in the process of subgingival flora from health to imbalance. Initial therapy can change the composition and structure of the subgingival microbiota, reduce community diversity, and reduce the functions of amino acid metabolism, methane metabolism, and peptidase in GAgP and SCP patients.

Drug mechanism-of-action discovery through the integration of pharmacological and CRISPR screens.

Low success rates during drug development are due, in part, to the difficulty of defining drug mechanism-of-action and molecular markers of therapeutic activity. Here, we integrated 199,219 drug sensitivity measurements for 397 unique anti-cancer drugs with genome-wide CRISPR loss-of-function screens in 484 cell lines to systematically investigate cellular drug mechanism-of-action. We observed an enrichment for positive associations between the profile of drug sensitivity and knockout of a drug's nominal target, and by leveraging protein-protein networks, we identified pathways underpinning drug sensitivity. This revealed an unappreciated positive association between mitochondrial E3 ubiquitin-protein ligase MARCH5 dependency and sensitivity to MCL1 inhibitors in breast cancer cell lines. We also estimated drug on-target and off-target activity, informing on specificity, potency and toxicity. Linking drug and gene dependency together with genomic data sets uncovered contexts in which molecular networks when perturbed mediate cancer cell loss-of-fitness and thereby provide independent and orthogonal evidence of biomarkers for drug development. This study illustrates how integrating cell line drug sensitivity with CRISPR loss-of-function screens can elucidate mechanism-of-action to advance drug development.

Cell Model Passports-a hub for clinical, genetic and functional datasets of preclinical cancer models.

In vitro cancer cell cultures are facile experimental models used widely for research and drug development. Many cancer cell lines are available and efforts are ongoing to derive new models representing the histopathological and molecular diversity of tumours. Cell models have been generated by multiple laboratories over decades and consequently their annotation is incomplete and inconsistent. Furthermore, the relationships between many patient-matched and derivative cell lines have been lost, and accessing information and datasets is time-consuming and difficult. Here, we describe the Cell Model Passports database; cellmodelpassports.sanger.ac.uk, which provides details of cell model relationships, patient and clinical information, as well as access to associated genetic and functional datasets. The Passports database currently contains curated details and standardized annotation for >1200 cell models, including cancer organoid cultures. The Passports will be updated with newly derived cell models and datasets as they are generated. Users can navigate the database via tissue, cancer-type, genetic feature and data availability to select a model most suitable for specific applications. A flexible REST-API provides programmatic data access and exploration. The Cell Model Passports are a valuable tool enabling access to high-dimensional genomic and phenotypic cancer cell model datasets empowering diverse research applications.

[Analysis of Changes in Medical Device Classification Concept of the New EU Regulations].

By comparing new medical device regulations with existing directives in the European Union, the revising ideas of new EU medical device regulations, especially the changes of the classification management concepts, were analyzed to provide clues for the industry to interpret the new EU regulations, and references for the classification management innovation in our country.

[The Analysis on Application of Global Medical Device Nomenclature(GMDN)].

The article has reviewed the administration technical structure and global application of the global medical device nomenclature(GMDN), analyzed the coordination between GMDN and the industry status of medical device in our country, put forward some suggestions on the applicaition of GMDN, provided some reference on raising the management level of medical device in our country.

[The Feasibility Study on the Application of Global Medical Device Nomenclature(GMDN)].

The article has analyzed the policy co-ordination, Industry coverage and technical experience of the global medical device nomenclature (GMDN) to our country, argued the feasibility on the application of GMDN in our medical device administration system, provided some reference on building the naming system of medical device in our country.

[The Preliminary Study on the Construction of Medical Device Naming System in China].

The article has summarized the situation related to medical device naming, analyzed the problems of medical device naming in our country, put forward some new thinking in building the naming system of medical device in our country provided some reference on technical study of medical device naming.

[International progress of unique device identification for medical devices].

Unique Device Identification (UDI) is a hot spot research area in the medical device administration. It comes a breakthrough from International Medical Device Regulators Forum (IMDRF) and government implementation recently. The article reviewed the advancement of IMDRF UDI program, discussed the framework for UDI system, analyzed the implementation of UDI in other countries, put forward some suggestions on the development of medical device coding system in our country.

Genomics of Drug Sensitivity in Cancer (GDSC): a resource for therapeutic biomarker discovery in cancer cells.

Alterations in cancer genomes strongly influence clinical responses to treatment and in many instances are potent biomarkers for response to drugs. The Genomics of Drug Sensitivity in Cancer (GDSC) database (www.cancerRxgene.org) is the largest public resource for information on drug sensitivity in cancer cells and molecular markers of drug response. Data are freely available without restriction. GDSC currently contains drug sensitivity data for almost 75 000 experiments, describing response to 138 anticancer drugs across almost 700 cancer cell lines. To identify molecular markers of drug response, cell line drug sensitivity data are integrated with large genomic datasets obtained from the Catalogue of Somatic Mutations in Cancer database, including information on somatic mutations in cancer genes, gene amplification and deletion, tissue type and transcriptional data. Analysis of GDSC data is through a web portal focused on identifying molecular biomarkers of drug sensitivity based on queries of specific anticancer drugs or cancer genes. Graphical representations of the data are used throughout with links to related resources and all datasets are fully downloadable. GDSC provides a unique resource incorporating large drug sensitivity and genomic datasets to facilitate the discovery of new therapeutic biomarkers for cancer therapies.

Systematic identification of genomic markers of drug sensitivity in cancer cells.

Clinical responses to anticancer therapies are often restricted to a subset of patients. In some cases, mutated cancer genes are potent biomarkers for responses to targeted agents. Here, to uncover new biomarkers of sensitivity and resistance to cancer therapeutics, we screened a panel of several hundred cancer cell lines--which represent much of the tissue-type and genetic diversity of human cancers--with 130 drugs under clinical and preclinical investigation. In aggregate, we found that mutated cancer genes were associated with cellular response to most currently available cancer drugs. Classic oncogene addiction paradigms were modified by additional tissue-specific or expression biomarkers, and some frequently mutated genes were associated with sensitivity to a broad range of therapeutic agents. Unexpected relationships were revealed, including the marked sensitivity of Ewing's sarcoma cells harbouring the EWS (also known as EWSR1)-FLI1 gene translocation to poly(ADP-ribose) polymerase (PARP) inhibitors. By linking drug activity to the functional complexity of cancer genomes, systematic pharmacogenomic profiling in cancer cell lines provides a powerful biomarker discovery platform to guide rational cancer therapeutic strategies.

[Analysis and thinking on the post marketing quality of the disposable sterilized syringe].

By scattered-sampling testing the disposable sterilized syringe according to legal inspection and explorative research methods of vitro cytotoxicity and easy oxide etc. testing, this article comprehensively evaluated and analyzed the product quality and found the potential risk. The results will help to improve the work process and product quality.