Quantitative model for genome-wide cyclic AMP receptor protein binding site identification and characteristic analysis.

Cyclic AMP receptor proteins (CRPs) are important transcription regulators in many species. The prediction of CRP-binding sites was mainly based on position-weighted matrixes (PWMs). Traditional prediction methods only considered known binding motifs, and their ability to discover inflexible binding patterns was limited. Thus, a novel CRP-binding site prediction model called CRPBSFinder was developed in this research, which combined the hidden Markov model, knowledge-based PWMs and structure-based binding affinity matrixes. We trained this model using validated CRP-binding data from Escherichia coli and evaluated it with computational and experimental methods. The result shows that the model not only can provide higher prediction performance than a classic method but also quantitatively indicates the binding affinity of transcription factor binding sites by prediction scores. The prediction result included not only the most knowns regulated genes but also 1089 novel CRP-regulated genes. The major regulatory roles of CRPs were divided into four classes: carbohydrate metabolism, organic acid metabolism, nitrogen compound metabolism and cellular transport. Several novel functions were also discovered, including heterocycle metabolic and response to stimulus. Based on the functional similarity of homologous CRPs, we applied the model to 35 other species. The prediction tool and the prediction results are online and are available at: https://awi.cuhk.edu.cn/∼CRPBSFinder.

miRTarBase update 2022: an informative resource for experimentally validated miRNA-target interactions.

MicroRNAs (miRNAs) are noncoding RNAs with 18-26 nucleotides; they pair with target mRNAs to regulate gene expression and produce significant changes in various physiological and pathological processes. In recent years, the interaction between miRNAs and their target genes has become one of the mainstream directions for drug development. As a large-scale biological database that mainly provides miRNA-target interactions (MTIs) verified by biological experiments, miRTarBase has undergone five revisions and enhancements. The database has accumulated >2 200 449 verified MTIs from 13 389 manually curated articles and CLIP-seq data. An optimized scoring system is adopted to enhance this update's critical recognition of MTI-related articles and corresponding disease information. In addition, single-nucleotide polymorphisms and disease-related variants related to the binding efficiency of miRNA and target were characterized in miRNAs and gene 3' untranslated regions. miRNA expression profiles across extracellular vesicles, blood and different tissues, including exosomal miRNAs and tissue-specific miRNAs, were integrated to explore miRNA functions and biomarkers. For the user interface, we have classified attributes, including RNA expression, specific interaction, protein expression and biological function, for various validation experiments related to the role of miRNA. We also used seed sequence information to evaluate the binding sites of miRNA. In summary, these enhancements render miRTarBase as one of the most research-amicable MTI databases that contain comprehensive and experimentally verified annotations. The newly updated version of miRTarBase is now available at https://miRTarBase.cuhk.edu.cn/.

MethHC 2.0: information repository of DNA methylation and gene expression in human cancer.

DNA methylation is an important epigenetic regulator in gene expression and has several roles in cancer and disease progression. MethHC version 2.0 (MethHC 2.0) is an integrated and web-based resource focusing on the aberrant methylomes of human diseases, specifically cancer. This paper presents an updated implementation of MethHC 2.0 by incorporating additional DNA methylomes and transcriptomes from several public repositories, including 33 human cancers, over 50 118 microarray and RNA sequencing data from TCGA and GEO, and accumulating up to 3586 manually curated data from >7000 collected published literature with experimental evidence. MethHC 2.0 has also been equipped with enhanced data annotation functionality and a user-friendly web interface for data presentation, search, and visualization. Provided features include clinical-pathological data, mutation and copy number variation, multiplicity of information (gene regions, enhancer regions, and CGI regions), and circulating tumor DNA methylation profiles, available for research such as biomarker panel design, cancer comparison, diagnosis, prognosis, therapy study and identifying potential epigenetic biomarkers. MethHC 2.0 is now available at http://awi.cuhk.edu.cn/∼MethHC.

A Robust Drug-Target Interaction Prediction Framework with Capsule Network and Transfer Learning.

Drug-target interactions (DTIs) are considered a crucial component of drug design and drug discovery. To date, many computational methods were developed for drug-target interactions, but they are insufficiently informative for accurately predicting DTIs due to the lack of experimentally verified negative datasets, inaccurate molecular feature representation, and ineffective DTI classifiers. Therefore, we address the limitations of randomly selecting negative DTI data from unknown drug-target pairs by establishing two experimentally validated datasets and propose a capsule network-based framework called CapBM-DTI to capture hierarchical relationships of drugs and targets, which adopts pre-trained bidirectional encoder representations from transformers (BERT) for contextual sequence feature extraction from target proteins through transfer learning and the message-passing neural network (MPNN) for the 2-D graph feature extraction of compounds to accurately and robustly identify drug-target interactions. We compared the performance of CapBM-DTI with state-of-the-art methods using four experimentally validated DTI datasets of different sizes, including human (Homo sapiens) and worm (Caenorhabditis elegans) species datasets, as well as three subsets (new compounds, new proteins, and new pairs). Our results demonstrate that the proposed model achieved robust performance and powerful generalization ability in all experiments. The case study on treating COVID-19 demonstrates the applicability of the model in virtual screening.

Effects of Natural Products on Enzymes Involved in Ferroptosis: Regulation and Implications.

Ferroptosis is a form of regulated cell death that is characterized by the accumulation of iron-dependent lipid peroxides. The regulation of ferroptosis involves both non-enzymatic reactions and enzymatic mechanisms. Natural products have demonstrated potential effects on various enzymes, including GPX4, HO-1, NQO1, NOX4, GCLC, and GCLM, which are mainly involved in glutathione metabolic pathway or oxidative stress regulation, and ACSL3 and ACSL4, which mainly participate in lipid metabolism, thereby influencing the regulation of ferroptosis. In this review, we have provided a comprehensive overview of the existing literature pertaining to the effects of natural products on enzymes involved in ferroptosis and discussed their potential implications for the prevention and treatment of ferroptosis-related diseases. We also highlight the potential challenge that the majority of research has concentrated on investigating the impact of natural products on the expression of enzymes involving ferroptosis while limited attention is given to the regulation of enzyme activity. This observation underscores the considerable potential and scope for exploring the influence of natural products on enzyme activity.

miRTarBase 2020: updates to the experimentally validated microRNA-target interaction database.

MicroRNAs (miRNAs) are small non-coding RNAs (typically consisting of 18-25 nucleotides) that negatively control expression of target genes at the post-transcriptional level. Owing to the biological significance of miRNAs, miRTarBase was developed to provide comprehensive information on experimentally validated miRNA-target interactions (MTIs). To date, the database has accumulated >13,404 validated MTIs from 11,021 articles from manual curations. In this update, a text-mining system was incorporated to enhance the recognition of MTI-related articles by adopting a scoring system. In addition, a variety of biological databases were integrated to provide information on the regulatory network of miRNAs and its expression in blood. Not only targets of miRNAs but also regulators of miRNAs are provided to users for investigating the up- and downstream regulations of miRNAs. Moreover, the number of MTIs with high-throughput experimental evidence increased remarkably (validated by CLIP-seq technology). In conclusion, these improvements promote the miRTarBase as one of the most comprehensively annotated and experimentally validated miRNA-target interaction databases. The updated version of miRTarBase is now available at http://miRTarBase.cuhk.edu.cn/.

Enzyme Activity of Natural Products on Cytochrome P450.

Drug-metabolizing enzymes, particularly the cytochrome P450 (CYP450) monooxygenases, play a pivotal role in pharmacokinetics. CYP450 enzymes can be affected by various xenobiotic substrates, which will eventually be responsible for most metabolism-based herb-herb or herb-drug interactions, usually involving competition with another drug for the same enzyme binding site. Compounds from herbal or natural products are involved in many scenarios in the context of such interactions. These interactions are decisive both in drug discovery regarding the synergistic effects, and drug application regarding unwanted side effects. Herein, this review was conducted as a comprehensive compilation of the effects of herbal ingredients on CYP450 enzymes. Nearly 500 publications reporting botanicals' effects on CYP450s were collected and analyzed. The countries focusing on this topic were summarized, the identified herbal ingredients affecting enzyme activity of CYP450s, as well as methods identifying the inhibitory/inducing effects were reviewed. Inhibitory effects of botanicals on CYP450 enzymes may contribute to synergistic effects, such as herbal formulae/prescriptions, or lead to therapeutic failure, or even increase concentrations of conventional medicines causing serious adverse events. Conducting this review may help in metabolism-based drug combination discovery, and in the evaluation of the safety profile of natural products used therapeutically.

Multi-omics profiling reveals microRNA-mediated insulin signaling networks.

BACKGROUND: MicroRNAs (miRNAs) play a key role in mediating the action of insulin on cell growth and the development of diabetes. However, few studies have been conducted to provide a comprehensive overview of the miRNA-mediated signaling network in response to glucose in pancreatic beta cells. In our study, we established a computational framework integrating multi-omics profiles analyses, including RNA sequencing (RNA-seq) and small RNA sequencing (sRNA-seq) data analysis, inverse expression pattern analysis, public data integration, and miRNA targets prediction to illustrate the miRNA-mediated regulatory network at different glucose concentrations in INS-1 pancreatic beta cells (INS-1), which display important characteristics of the pancreatic beta cells. RESULTS: We applied our computational framework to the expression profiles of miRNA/mRNA of INS-1, at different glucose concentrations. A total of 1437 differentially expressed genes (DEGs) and 153 differentially expressed miRNAs (DEmiRs) were identified from multi-omics profiles. In particular, 121 DEmiRs putatively regulated a total of 237 DEGs involved in glucose metabolism, fatty acid oxidation, ion channels, exocytosis, homeostasis, and insulin gene regulation. Moreover, Argonaute 2 immunoprecipitation sequencing, qRT-PCR, and luciferase assay identified Crem, Fn1, and Stc1 are direct targets of miR-146b and elucidated that miR-146b acted as a potential regulator and promising target to understand the insulin signaling network. CONCLUSIONS: In this study, the integration of experimentally verified data with system biology framework extracts the miRNA network for exploring potential insulin-associated miRNA and their target genes. The findings offer a potentially significant effect on the understanding of miRNA-mediated insulin signaling network in the development and progression of pancreatic diabetes.

miRTarBase update 2018: a resource for experimentally validated microRNA-target interactions.

MicroRNAs (miRNAs) are small non-coding RNAs of ∼ 22 nucleotides that are involved in negative regulation of mRNA at the post-transcriptional level. Previously, we developed miRTarBase which provides information about experimentally validated miRNA-target interactions (MTIs). Here, we describe an updated database containing 422 517 curated MTIs from 4076 miRNAs and 23 054 target genes collected from over 8500 articles. The number of MTIs curated by strong evidence has increased ∼1.4-fold since the last update in 2016. In this updated version, target sites validated by reporter assay that are available in the literature can be downloaded. The target site sequence can extract new features for analysis via a machine learning approach which can help to evaluate the performance of miRNA-target prediction tools. Furthermore, different ways of browsing enhance user browsing specific MTIs. With these improvements, miRTarBase serves as more comprehensively annotated, experimentally validated miRNA-target interactions databases in the field of miRNA related research. miRTarBase is available at http://miRTarBase.mbc.nctu.edu.tw/.

Ouroboros resembling competitive endogenous loop (ORCEL) in circular RNAs revealed through transcriptome sequencing dataset analysis.

BACKGROUND: Emerging evidence indicates that Circular RNAs (circRNAs) exert post-transcriptional regulation of gene expression. A subclass of circRNA was found enriched with miRNA target sites. This evidence suggests that this kind of circRNA functions as natural miRNA sponge. Noticing the potential impacts of circular RNA research, we were motivated to identify novel circRNAs as well as putative circRNA-miRNA interactions through retroactive sourced transcriptome sequencing samples. RESULTS: Through the analysis in 465 RNA-seq runs and 22 reports published in recent years, putatively circRNA sponged miRNA that had been experimentally verified targeting circRNA host gene were found. From this observation, supporting evidence of the competitive endogenous relationship of circRNAs and miRNAs targeting circRNA host genes can be observed. Given the self-regulation and self-induction nature of these circRNAs, this kind of hypothetical phenomenon was hereby called Ouroboros Resembling Competitive Endogenous Loop (ORCEL) in circular RNAs. CONCLUSIONS: The fact that miRNA sponge circRNA originated from region miRNA target sites enriched regions, while genes encoded from these regions are conserved to be miRNA targets rationalize the existence of ORCEL.

miRTarBase 2016: updates to the experimentally validated miRNA-target interactions database.

MicroRNAs (miRNAs) are small non-coding RNAs of approximately 22 nucleotides, which negatively regulate the gene expression at the post-transcriptional level. This study describes an update of the miRTarBase (http://miRTarBase.mbc.nctu.edu.tw/) that provides information about experimentally validated miRNA-target interactions (MTIs). The latest update of the miRTarBase expanded it to identify systematically Argonaute-miRNA-RNA interactions from 138 crosslinking and immunoprecipitation sequencing (CLIP-seq) data sets that were generated by 21 independent studies. The database contains 4966 articles, 7439 strongly validated MTIs (using reporter assays or western blots) and 348 007 MTIs from CLIP-seq. The number of MTIs in the miRTarBase has increased around 7-fold since the 2014 miRTarBase update. The miRNA and gene expression profiles from The Cancer Genome Atlas (TCGA) are integrated to provide an effective overview of this exponential growth in the miRNA experimental data. These improvements make the miRTarBase one of the more comprehensively annotated, experimentally validated miRNA-target interactions databases and motivate additional miRNA research efforts.

Large-Scale Functional Analysis of CRP-Mediated Feed-Forward Loops.

Feed-forward loops (FFLs) represent an important and basic network motif to understand specific biological functions. Cyclic-AMP (cAMP) receptor protein (CRP), a transcription factor (TF), mediates catabolite repression and regulates more than 400 genes in response to changes in intracellular concentrations of cAMP in Escherichia coli. CRP participates in some FFLs, such as araBAD and araFGH operons and adapts to fluctuating environmental nutrients, thereby enhancing the survivability of E. coli. Although computational simulations have been conducted to explore the potential functionality of FFLs, a comprehensive study on the functions of all structural types on the basis of in vivo data is lacking. Moreover, the regulatory role of CRP-mediated FFLs (CRP-FFLs) remains obscure. We identified 393 CRP-FFLs in E. coli using EcoCyc and RegulonDB. Dose⁻response genomic microarray of E. coli revealed dynamic gene expression of each target gene of CRP-FFLs in response to a range of cAMP dosages. All eight types of FFLs were present in CRP regulon with various expression patterns of each CRP-FFL, which were further divided into five functional groups. The microarray and reported regulatory relationships identified 202 CRP-FFLs that were directly regulated by CRP in these eight types of FFLs. Interestingly, 34% (147/432) of genes were directly regulated by CRP and CRP-regulated TFs, which indicates that these CRP-regulated genes were also regulated by other CRP-regulated TFs responding to environmental signals through CRP-FFLs. Furthermore, we applied gene ontology annotation to reveal the biological functions of CRP-FFLs.

Integrated MicroRNA-mRNA Analysis Reveals miR-204 Inhibits Cell Proliferation in Gastric Cancer by Targeting CKS1B, CXCL1 and GPRC5A.

Gastric cancer (GC) is the second most frequent cause of cancer-related deaths worldwide. MicroRNAs are single-stranded RNA molecules of 21-23 nucleotides that regulate target gene expression through specific base-pairing interactions between miRNA and untranslated regions of targeted mRNAs. In this study, we generated a multistep approach for the integrated analysis of miRNA and mRNA expression. First, both miRNA and mRNA expression profiling datasets in gastric cancer from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) identified 79 and 1042 differentially expressed miRNAs and mRNAs, respectively, in gastric cancer. Second, inverse correlations between miRNA and mRNA expression levels identified 3206 miRNA-mRNA pairs combined with 79 dysregulated miRNAs and their 774 target mRNAs predicted by three prediction tools, miRanda, PITA, and RNAhybrid. Additionally, miR-204, which was found to be down-regulated in gastric cancer, was ectopically over-expressed in the AGS gastric cancer cell line and all down-regulated targets were identified by RNA sequencing (RNA-seq) analysis. Over-expression of miR-204 reduced the gastric cancer cell proliferation and suppressed the expression of three targets which were validated by qRT-PCR and luciferase assays. For the first time, we identified that CKS1B, CXCL1, and GPRC5A are putative targets of miR-204 and elucidated that miR-204 acted as potential tumor suppressor and, therefore, are useful as a promising therapeutic target for gastric cancer.

GeNOSA: inferring and experimentally supporting quantitative gene regulatory networks in prokaryotes.

MOTIVATION: The establishment of quantitative gene regulatory networks (qGRNs) through existing network component analysis (NCA) approaches suffers from shortcomings such as usage limitations of problem constraints and the instability of inferred qGRNs. The proposed GeNOSA framework uses a global optimization algorithm (OptNCA) to cope with the stringent limitations of NCA approaches in large-scale qGRNs. RESULTS: OptNCA performs well against existing NCA-derived algorithms in terms of utilization of connectivity information and reconstruction accuracy of inferred GRNs using synthetic and real Escherichia coli datasets. For comparisons with other non-NCA-derived algorithms, OptNCA without using known qualitative regulations is also evaluated in terms of qualitative assessments using a synthetic Saccharomyces cerevisiae dataset of the DREAM3 challenges. We successfully demonstrate GeNOSA in several applications including deducing condition-dependent regulations, establishing high-consensus qGRNs and validating a sub-network experimentally for dose-response and time-course microarray data, and discovering and experimentally confirming a novel regulation of CRP on AscG. AVAILABILITY AND IMPLEMENTATION: All datasets and the GeNOSA framework are freely available from http://e045.life.nctu.edu.tw/GeNOSA. CONTACT: syho@mail.nctu.edu.tw SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

CRP represses the CRISPR/Cas system in Escherichia coli: evidence that endogenous CRISPR spacers impede phage P1 replication.

The CRISPR/Cas system is an important aspect in bacterial immunology. The anti-phage activity of the CRISPR system has been established using synthetic CRISPR spacers, but in vivo studies of endogenous CRISPR spacers are relatively scarce. Here, we showed that bacteriophage P1 titre in Escherichia coli decreased in the glucose-containing medium compared with that in the absence of glucose. This glucose effect of E. coli against phage P1 infection disappeared in cse3 deletion mutants. The effect on the susceptibility to phage P1 was associated with cAMP receptor protein (CRP)-mediated repression of cas genes transcription and crRNA maturation. Analysis of the regulatory element in the cse1 promoter region revealed a novel CRP binding site, which overlapped with a LeuO binding site. Furthermore, the limited sequence identity between endogenous spacers and the phage P1 genome was necessary and sufficient for CRISPR-mediated repression of phage P1 replication. Trans-expression of the third and seventh spacers in the CRISPR I region or third and sixth spacers in the CRISPR II region effectively reduced phage P1 titres in the CRISPR deletion mutants. These results demonstrate a novel regulatory mechanism for cas repression by CRP and provide evidence that endogenous spacers can repress phage P1 replication in E. coli.

Recent insights into breast milk microRNA: their role as functional regulators.

Breast milk (BM) is a primary biofluid that plays a crucial role in infant development and the regulation of the immune system. As a class of rich biomolecules in BM, microRNAs (miRNAs) are regarded as active factors contributing to infant growth and development. Surprisingly, these molecules exhibit resilience in harsh conditions, providing an opportunity for infants to absorb them. In addition, many studies have shown that miRNAs in breast milk, when absorbed into the gastrointestinal system, can act as a class of functional regulators to effectively regulate gene expression. Understanding the absorption pattern of BM miRNA may facilitate the creation of formula with a more optimal miRNA balance and pave the way for novel drug delivery techniques. In this review, we initially present evidence of BM miRNA absorption. Subsequently, we compile studies that integrate both in vivo and in vitro findings to illustrate the bioavailability and biodistribution of BM miRNAs post-absorption. In addition, we evaluate the strengths and weaknesses of previous studies and discuss potential variables contributing to discrepancies in their outcomes. This literature review indicates that miRNAs can be absorbed and act as regulatory agents.

DrugRepoBank: a comprehensive database and discovery platform for accelerating drug repositioning.

In recent years, drug repositioning has emerged as a promising alternative to the time-consuming, expensive and risky process of developing new drugs for diseases. However, the current database for drug repositioning faces several issues, including insufficient data volume, restricted data types, algorithm inaccuracies resulting from the neglect of multidimensional or heterogeneous data, a lack of systematic organization of literature data associated with drug repositioning, limited analytical capabilities and user-unfriendly webpage interfaces. Hence, we have established the first all-encompassing database called DrugRepoBank, consisting of two main modules: the 'Literature' module and the 'Prediction' module. The 'Literature' module serves as the largest repository of literature-supported drug repositioning data with experimental evidence, encompassing 169 repositioned drugs from 134 articles from 1 January 2000 to 1 July 2023. The 'Prediction' module employs 18 efficient algorithms, including similarity-based, artificial-intelligence-based, signature-based and network-based methods to predict repositioned drug candidates. The DrugRepoBank features an interactive and user-friendly web interface and offers comprehensive functionalities such as bioinformatics analysis of disease signatures. When users provide information about a drug, target or disease of interest, DrugRepoBank offers new indications and targets for the drug, proposes new drugs that bind to the target or suggests potential drugs for the queried disease. Additionally, it provides basic information about drugs, targets or diseases, along with supporting literature. We utilize three case studies to demonstrate the feasibility and effectiveness of predictively repositioned drugs within DrugRepoBank. The establishment of the DrugRepoBank database will significantly accelerate the pace of drug repositioning. Database URL:  https://awi.cuhk.edu.cn/DrugRepoBank.

Mechanism of Sophorae Flavescentis Radix (Kushen) in treating NSCLC: Insights from miRNA-mRNA network analysis.

ETHNOPHARMACOLOGICAL RELEVANCE: Sophorae Flavescentis Radix (Kushen) is the primary herb component of Compound Kushen Injection (CKI), an approved clinical treatment for tumors. Despite CKI's widespread use, the underlying mechanisms of Kushen regarding microRNA-target and pathway remain unclear in non-small cell lung cancer (NSCLC). AIM OF THE STUDY: This study aimed to elucidate the crucial miRNAs-targets and pathways responsible for the Kushen's impact on NSCLC. MATERIALS AND METHODS: CCK8, colony formation, and apoptosis assays were performed to assess the effects of Kushen on NSCLC cells. Subsequently, we treated the A549 cell line with varying concentrations of Kushen to obtain mRNA and miRNA expression profiles. A DE (differentially expressed) miRNAs-DEGs network was then constructed to identify the critical miRNA-mRNA interaction influenced by Kushen. Furthermore, we performed clinical significance and prognosis analyses of hub genes to narrow down key genes and their corresponding miRNAs. Finally, the effects of Kushen on critical miRNA-mRNA interaction and related pathway were verified by in vitro and in vivo experiments. RESULTS: In this study, we initially demonstrated that Kushen significantly inhibited cell proliferation, suppressed colony formation, and induced apoptosis in the A549 cells, PC9 cells, and the A549 zebrafish xenograft model. Through expression profile analysis, a DE miRs-DEGs network was constructed with 16 DE miRs and 68 DEGs. Through the network analysis and expression validation, we found Kushen could significantly down-regulate miR-183-5p expression and up-regulate EGR1 expression. Additionally, Kushen affected the PTEN/Akt pathway, increasing PTEN expression and decreasing pAkt expression. Finally, matrine, the essential active compound of Kushen, also inhibited cell growth, induced apoptosis, and regulated miR-183-5p/EGR1 and PTEN/AKT pathway. CONCLUSIONS: Altogether, these findings supported the critical role of miR-183-5p/EGR1 and the PTEN/AKT pathway in the beneficial effects of Kushen on NSCLC, highlighting the therapeutic potential of Kushen in NSCLC treatment.

Cinnamomi ramulus inhibits cancer cells growth by inducing G2/M arrest.

Introduction: Cinnamomi ramulus (CR) is one of the most widely used traditional Chinese medicine (TCM) with anti-cancer effects. Analyzing transcriptomic responses of different human cell lines to TCM treatment is a promising approach to understand the unbiased mechanism of TCM. Methods: This study treated ten cancer cell lines with different CR concentrations, followed by mRNA sequencing. Differential expression (DE) analysis and gene set enrichment analysis (GSEA) were utilized to analyze transcriptomic data. Finally, the in silico screening results were verified by in vitro experiments. Results: Both DE and GSEA analysis suggested the Cell cycle pathway was the most perturbated pathway by CR across these cell lines. By analyzing the clinical significance and prognosis of G2/M related genes (PLK1, CDK1, CCNB1, and CCNB2) in various cancer tissues, we found that they were up-regulated in most cancer types, and their down-regulation showed better overall survival rates in cancer patients. Finally, in vitro experiments validation on A549, Hep G2, and HeLa cells suggested that CR can inhibit cell growth by suppressing the PLK1/CDK1/ Cyclin B axis. Discussion: This is the first study to apply transcriptomic analysis to investigate the cancer cell growth inhibition of CR on various human cancer cell lines. The core effect of CR on ten cancer cell lines is to induce G2/M arrest by inhibiting the PLK1/CDK1/Cyclin B axis.