LINC01002 functions as a ceRNA to regulate FRMD8 by sponging miR-4324 for the development of COVID-19.

BACKGROUND: Syndrome coronavirus-2 (SARS-CoV-2) has developed various strategies to evade the antiviral impact of type I IFN. Non-structural proteins and auxiliary proteins have been extensively researched on their role in immune escape. Nevertheless, the detailed mechanisms of structural protein-induced immune evasion have not been well elucidated. METHODS: Human alveolar basal epithelial carcinoma cell line (A549) was stimulated with polyinosinic-polycytidylic acid (PIC) and independently transfected with four structural proteins expression plasmids, including nucleocapsid (N), spike (S), membrane (M) and envelope (E) proteins. By RT-qPCR and ELISA, the structural protein with the most pronounced inhibitory effects on IFN-ß induction was screened. RNA-sequencing (RNA-Seq) and two differential analysis strategies were used to obtain differentially expressed genes associated with N protein inhibition of IFN-ß induction. Based on DIANA-LncBase and StarBase databases, the interactive competitive endogenous RNA (ceRNA) network for N protein-associated genes was constructed. By combining single-cell sequencing data (GSE158055), lncRNA-miRNA-mRNA axis was further determined. Finally, RT-qPCR was utilized to illustrate the regulatory functions among components of the ceRNA axis. RESULTS: SARS-CoV-2 N protein inhibited IFN-ß induction in human alveolar epithelial cells most significantly compared with other structural proteins. RNA-Seq data analysis revealed genes related to N protein inhibiting IFNs induction. The obtained 858 differentially expressed genes formed the reliable ceRNA network. The function of LINC01002-miR-4324-FRMD8 axis in the IFN-dominated immune evasion was further demonstrated through integrating single-cell sequencing data. Moreover, we validated that N protein could reverse the effect of PIC on LINC01002, FRMD8 and miR-4324 expression, and subsequently on IFN-ß expression level. And LINC01002 could regulate the production of FRMD8 by inhibiting miR-4324. CONCLUSION: SARS-CoV-2 N protein suppressed the induction of IFN-ß by regulating LINC01002 which was as a ceRNA, sponging miR-4324 and participating in the regulation of FRMD8 mRNA. Our discovery provides new insights into early intervention therapy and drug development on SARS-CoV-2 infection.

Generation of KCNH2 heterozygous knockout induced pluripotent stem cell (iPSC) line (Long and Short QT Syndrome).

KCNH2 (Potassium Voltage-Gated Channel Subfamily H Member) encodes a voltage-activated potassium channel role as rapidly activating-delayed rectifier potassium channel that plays an essential role in the final repolarization of the ventricular action potential. Mutations in this gene can cause long QT syndrome and short QT syndrome. Transcript variants encoding distinct isoforms were also identified. In this study, we generated induced pluripotent stem cells (iPSC) from a healthy individual by electroporation of peripheral blood mononuclear cells and generated a KCNH2 heterozygous knockout human iPSC line via CRISPR/Cas9 gene editing. The resulting iPSCs had a normal karyotype, were free of genomically integrated epitomal plasmids, expressed pluripotency markers, and maintained trilineage differentiation potential.

SUV39H1 is a novel biomarker targeting oxidative phosphorylation in hepatitis B virus-associated hepatocellular carcinoma.

BACKGROUND: As a histone methyltransferase, suppressor of variegation 3-9 homolog 1 (SUV39H1) plays an important role in the occurrence and development of cancer. To explore the mechanism and biological function of SUV39H1 in hepatitis B virus-associated hepatocellular carcinoma (HBV-HCC) can gain an insight into the pathogenesis of HBV-HCC. METHODS: The effect of HBV infection on SUV39H1 in hepatoma cells was detected. CCK-8, colony growth assay and wound healing assay were used to assess the proliferation and migration of HBV-positive hepatoma cells. RNA sequencing (RNA-seq) was applied to find differential genes and enriched pathways. The serum SUV39H1 level in HBV-HCC patients was detected and its correlation with clinical indicators was analyzed. RESULTS: SUV39H1 was increased by HBV infection and promoted the proliferation and migration of hepatoma cells. SUV39H1 could upregulate the expression of mitochondrial oxidative phosphorylation (OXPHOS) pathway-related genes. OXPHOS pathway inhibitors could reduce the capacity of proliferation and migration of hepatoma cells after overexpressing SUV39H1. Serum SUV39H1 levels were higher in chronic hepatitis B (CHB) patients than in healthy controls and higher in HBV-HCC patients than in CHB patients. In the diagnosis of HCC, the predictive value of SUV39H1 combined with alpha-fetoprotein (AFP) was better than that of AFP alone. CONCLUSION: SUV39H1 is regulated by HBV infection and promotes the proliferation and migration of hepatoma cells by targeting OXPHOS pathway. It indicates that SUV39H1 may be a new biomarker of the diagnosis of HCC.

BRAFV600E restructures cellular lactylation to promote anaplastic thyroid cancer proliferation.

Anaplastic thyroid cancer (ATC) is a rare but fatal cancer with BRAF mutation ranging from 30 to 50%. Histone lysine lactylation represents a novel epigenetic mark that translates cellular metabolic signals into transcriptional regulation. It is not clear whether the Warburg effect can promote the proliferation of ATC with BRAFV600E mutation via metabolite-mediated histone lactylation. Our study aimed at illustrating how BRAFV600E restructures the cellular protein lactylation landscape to boost ATC proliferation, and determining whether blockade of protein lactylation can sensitize mutant ATC to BRAFV600E inhibitors. Western blotting was used to evaluate lactylation status. Aerobic glycolysis was intervened by adding cell-permeable ethyl lactate or using metabolic inhibitors. Chromatin immunoprecipitation and RT-qPCR were applied to analyze the expression of growth-related genes. Different chemical inhibitors were used to inhibit BRAFV600E and other enzymes. ATC cell line-derived xenograft model was employed to examine the efficacy of mono and combinatorial therapies. The results showed that aerobic glycolysis in ATC increased global protein lactylation via improving cellular lactate availability. In particular, lactylation on Histone 4 Lysine 12 residue (H4K12La) activated the expression of multiple genes essential for ATC proliferation. Furthermore, oncogenic BRAFV600E boosted glycolytic flux to restructure the cellular lactylation landscape, leading to H4K12La-driven gene transcription and cell cycle deregulation. Accordingly, the blockade of cellular lactylation machinery synergized with BRAFV600E inhibitor to impair ATC progression both in vitro and in vivo. Our results demonstrated an extra beneficial effect of aerobic glycolysis on ATC, revealing a novel metabolism-epigenetics axis suitable for combinatorial therapy with BRAFV600E inhibition.

FraudAuditor: A Visual Analytics Approach for Collusive Fraud in Health Insurance.

Collusive fraud, in which multiple fraudsters collude to defraud health insurance funds, threatens the operation of the healthcare system. However, existing statistical and machine learning-based methods have limited ability to detect fraud in the scenario of health insurance due to the high similarity of fraudulent behaviors to normal medical visits and the lack of labeled data. To ensure the accuracy of the detection results, expert knowledge needs to be integrated with the fraud detection process. By working closely with health insurance audit experts, we propose FraudAuditor, a three-stage visual analytics approach to collusive fraud detection in health insurance. Specifically, we first allow users to interactively construct a co-visit network to holistically model the visit relationships of different patients. Second, an improved community detection algorithm that considers the strength of fraud likelihood is designed to detect suspicious fraudulent groups. Finally, through our visual interface, users can compare, investigate, and verify suspicious patient behavior with tailored visualizations that support different time scales. We conducted case studies in a real-world healthcare scenario, i.e., to help locate the actual fraud group and exclude the false positive group. The results and expert feedback proved the effectiveness and usability of the approach.

CohortVA: A Visual Analytic System for Interactive Exploration of Cohorts based on Historical Data.

In history research, cohort analysis seeks to identify social structures and figure mobilities by studying the group-based behavior of historical figures. Prior works mainly employ automatic data mining approaches, lacking effective visual explanation. In this paper, we present CohortVA, an interactive visual analytic approach that enables historians to incorporate expertise and insight into the iterative exploration process. The kernel of CohortVA is a novel identification model that generates candidate cohorts and constructs cohort features by means of pre-built knowledge graphs constructed from large-scale history databases. We propose a set of coordinated views to illustrate identified cohorts and features coupled with historical events and figure profiles. Two case studies and interviews with historians demonstrate that CohortVA can greatly enhance the capabilities of cohort identifications, figure authentications, and hypothesis generation.

HetVis: A Visual Analysis Approach for Identifying Data Heterogeneity in Horizontal Federated Learning.

Horizontal federated learning (HFL) enables distributed clients to train a shared model and keep their data privacy. In training high-quality HFL models, the data heterogeneity among clients is one of the major concerns. However, due to the security issue and the complexity of deep learning models, it is challenging to investigate data heterogeneity across different clients. To address this issue, based on a requirement analysis we developed a visual analytics tool, HetVis, for participating clients to explore data heterogeneity. We identify data heterogeneity through comparing prediction behaviors of the global federated model and the stand-alone model trained with local data. Then, a context-aware clustering of the inconsistent records is done, to provide a summary of data heterogeneity. Combining with the proposed comparison techniques, we develop a novel set of visualizations to identify heterogeneity issues in HFL. We designed three case studies to introduce how HetVis can assist client analysts in understanding different types of heterogeneity issues. Expert reviews and a comparative study demonstrate the effectiveness of HetVis.

DPVisCreator: Incorporating Pattern Constraints to Privacy-preserving Visualizations via Differential Privacy.

Data privacy is an essential issue in publishing data visualizations. However, it is challenging to represent multiple data patterns in privacy-preserving visualizations. The prior approaches target specific chart types or perform an anonymization model uniformly without considering the importance of data patterns in visualizations. In this paper, we propose a visual analytics approach that facilitates data custodians to generate multiple private charts while maintaining user-preferred patterns. To this end, we introduce pattern constraints to model users' preferences over data patterns in the dataset and incorporate them into the proposed Bayesian network-based Differential Privacy (DP) model PriVis. A prototype system, DPVisCreator, is developed to assist data custodians in implementing our approach. The effectiveness of our approach is demonstrated with quantitative evaluation of pattern utility under the different levels of privacy protection, case studies, and semi-structured expert interviews.

CXCL8, CXCL9, CXCL10, and CXCL11 as biomarkers of liver injury caused by chronic hepatitis B.

Background: Chronic hepatitis B (CHB) remains a significant global health problem, leading to recurrent inflammation and liver-damaging diseases such as fibrosis, cirrhosis, and hepatocellular carcinoma (HCC). Currently, although diagnostic markers for CHB are well established, the indicators for predicting liver injury caused by hepatitis B virus (HBV) infection still need to be further explored. Thus, the identification of credible infectious indicators is urgently needed to facilitate timely clinical intervention and avoid the progression of disease malignancy. Methods: The Gene Expression Omnibus (GEO) database GSE83148 data set was used to explore the hub genes for HBV infection. The quantitative real-time polymerase chain reaction (qPCR) was used to identify the impact of HBV infection on the expression of hub gene at the cell level. At the same time, serum samples and clinical information were collected from healthy, HBV-free and CHB patients. The enzyme-linked immunosorbent assay (ELISA) was used to verify the results of cell experiments and Pearson correlation analysis was used to clarify hub genes correlation with HBV infection indicators and liver injury-related indicators. Finally, the Gene Expression Profiling Interactive Analysis (GEPIA) database was used to analyze the differences in the expression of hub gene in liver injury diseases. Results: Chemokine (C-X-C motif) ligand (CXCL)8, CXCL9, CXCL10, and CXCL11 were identified as hub genes in HBV infection. After HBV infection, the expression of the four chemokines was significantly increased and the concentrations secreted into serum were also increased. Moreover, the four chemokines were significantly correlated with HBV infection-related indicators and liver injury-related indicators, which were positively correlated with alanine aminotransferase (ALT), aspartate aminotransferase (AST) and hepatitis B e antigen (HBeAg), and negatively correlated with AST/ALT ratio and hepatitis B core antibody (HBcAb). In addition, the expression of CXCL9, CXCL10, and CXCL11 in HCC tissues was significantly higher than in normal tissues. Conclusion: Using a combination of bioinformatics, cell experiments, and clinical correlation analysis, this study showed that CXCL8, CXCL9, CXCL10, and CXCL11 can be used as serum biomarkers to forecast liver injury caused by HBV infection.

Designing a multi-epitope vaccine against coxsackievirus B based on immunoinformatics approaches.

Coxsackievirus B (CVB) is one of the major viral pathogens of human myocarditis and cardiomyopathy without any effective preventive measures; therefore, it is necessary to develop a safe and efficacious vaccine against CVB. Immunoinformatics methods are both economical and convenient as in-silico simulations can shorten the development time. Herein, we design a novel multi-epitope vaccine for the prevention of CVB by using immunoinformatics methods. With the help of advanced immunoinformatics approaches, we predicted different B-cell, cytotoxic T lymphocyte (CTL), and helper T lymphocyte (HTL) epitopes, respectively. Subsequently, we constructed the multi-epitope vaccine by fusing all conserved epitopes with appropriate linkers and adjuvants. The final vaccine was found to be antigenic, non-allergenic, and stable. The 3D structure of the vaccine was then predicted, refined, and evaluated. Molecular docking and dynamics simulation were performed to reveal the interactions between the vaccine with the immune receptors MHC-I, MHC-II, TLR3, and TLR4. Finally, to ensure the complete expression of the vaccine protein, the sequence of the designed vaccine was optimized and further performed in-silico cloning. In conclusion, the molecule designed in this study could be considered a potential vaccine against CVB infection and needed further experiments to evaluate its safety and efficacy.

Chronic exposure to low-dose cadmium facilitated nonalcoholic steatohepatitis in mice by suppressing fatty acid desaturation.

Exposure to cadmium (Cd), a toxic metal, is epidemiologically linked to nonalcoholic steatohepatitis (NASH) in humans. However, the role of Cd in NASH remains to be fully elucidated. This study employed a novel murine NASH model to investigate the effects of chronic low-dose Cd on hepatic pathology and its underlying mechanisms. NASH is characterized by lipid accumulation, extensive cell death, and persistent inflammation in the liver. We found that treatment with Cd in drinking water (10 mg/L) for 6 or 12 weeks significantly boosted hepatic fat deposition, increased hepatocyte destruction, and amplified inflammatory responses in mice, confirming that low-dose Cd can facilitate NASH development in vivo. Mechanistically, chronic Cd exposure reshaped the hepatic transcriptional landscape, with PPAR-mediated fatty acid metabolic pathways being the most significantly altered. In particular, Cd repressed fatty acid desaturation, leading to the accumulation of saturated fatty acids whose lipotoxicity exacerbated cell death and, consequently, inflammatory activation. In summary, we validated the causal effects of chronic low-dose Cd on NASH in vivo and identified the fatty acid desaturation program as a novel target for Cd to instigate hepatopathological alterations.

Umbra: A Visual Analysis Approach for Defense Construction Against Inference Attacks on Sensitive Information.

Collecting and analyzing anonymous personal information is required as a part of data analysis processes, such as medical diagnosis and restaurant recommendation. Such data should ostensibly be stored so that specific individual information cannot be disclosed. Unfortunately, inference attacks-integrating background knowledge and intelligent models-hinder classic sanitization techniques like syntactic anonymity and differential privacy from exhaustively protecting sensitive information. As a solution, we introduce a three-stage approach empowered within a visual interface, which depicts underlying inference behaviors via a Bayesian Network and supports a customized defense against inference attacks from unknown adversaries. In particular, our approach visually explains the process details of the underlying privacy preserving models, allowing users to verify if the results sufficiently satisfy the requirements of privacy preservation. We demonstrate the effectiveness of our approach through two case studies and expert reviews.

Integrative Methylome and Transcriptome Characterization Identifies SERINC2 as a Tumor-Driven Gene for Papillary Thyroid Carcinoma.

Most papillary thyroid carcinomas (PTCs) can be diagnosed preoperatively by routine evaluation, such as thyroid ultrasonography and fine-needle aspiration biopsy. Nevertheless, understanding how to differentiate indolent thyroid tumors from aggressive thyroid cancers remains a challenge, which may cause overtreatment. This study aimed to identify papillary thyroid cancer-specific indicators with whole-genome DNA methylation and gene expression profiles utilizing Infinium Methylation EPIC BeadChip (850k) and RNA arrays. In this paper, we report SERINC2 as a potential tumor-driven indicator in PTC. The up-regulated expression levels of SERINC2 were verified in PTC cell lines via qPCR. Then, cell counting kit 8 (CCK-8), wound healing, and flow cytometric assays were performed to confirm the influence of SERINC2 on proliferation and apoptosis in PTC cell lines after intervention or overexpression. Moreover, the investigation of data from the Cancer Dependency Map (DepMap) provided a potential pathway targeted by SERINC2. The activation of the tryptophan metabolic pathway may reduce the dependency of SERINC2 in thyroid cancers. In conclusion, our results demonstrate the whole-genome DNA methylation and gene expression profiles of papillary thyroid carcinoma, identify SERINC2 as a potential tumor-driven biomarker, and preliminarily verify its function in PTC.

Integrative Analysis of DNA Methylation and Gene Expression Identified Follicular Thyroid Cancer-Specific Diagnostic Biomarkers.

The diagnosis of follicular thyroid carcinoma (FTC) prior surgical resection remains a challenge, as routine screening methods, such as ultrasound or even FNAB, could not diagnose FTC preoperatively. Here, we performed an integrative analysis of DNA methylation and RNA array data from our own cohort (14 Follicular thyroid carcinoma vs 16 Benign thyroid lesion) to identify thyroid cancer-specific DNA methylation markers. We first identified differentially methylated and expressed genes and examined their correlations. Candidate DNA methylation sites were selected and further verified in validation set. Among all candidate methylation sites, cg06928209 was the most promising site as a molecular marker for early diagnosis, with a sensitivity of 90%, a specificity of 80% and an AUC of 0.77. Overall, our study demonstrates the potential use of methylation markers in FTC diagnosis and may boost the development of new epigenetic therapies.

Advances in endocrine and targeted therapy for hormone-receptor-positive, human epidermal growth factor receptor 2-negative advanced breast cancer.

Nearly 70% of breast cancer (BC) is hormone-receptor (HR)-positive, human epidermal growth factor receptor 2 (HER2)-negative, and endocrine therapy is the mainstay of treatment for this subtype. However, intrinsic or acquired endocrine resistance can occur during the endocrine treatment. Based on insights of endocrine resistance mechanisms, a number of targeted therapies have been and continue to be developed. With regard to HR-positive, HER2-negative advanced BC, aromatase inhibitor (AI) is superior to tamoxifen, and fulvestrant is a better option for patients previously exposed to endocrine therapy. Targeted drugs, such as cyclin-dependent kinases (CDK) 4/6 inhibitors, mammalian target of rapamycin (mTOR) inhibitors, phosphoinositide-3-kinase (PI3K) inhibitors, and histone deacetylase (HDAC) inhibitors, play a significant role in the present and show a promising future. With the application of CDK4/6 inhibitors becoming common, mechanisms of acquired resistance to them should also be taken into consideration.

VCAM-1 Upregulation Contributes to Insensitivity of Vemurafenib in BRAF-Mutant Thyroid Cancer.

Vemurafenib, an inhibitor of mutant BRAF activity, is a promising anticancer agent for patients with BRAF-mutant metastatic melanoma. However, it is less effective in BRAF-mutant thyroid cancer, and the reason for this discrepancy is not yet fully elucidated. By RNA sequencing analysis, we identified vascular cell adhesion molecular-1 (VCAM-1) to be highly upregulated in both time- and dose-dependent manners during BRAF inhibition (BRAFi) in a BRAF-mutant papillary thyroid cancer cell line (BCPAP). Cell cytotoxicity and apoptosis assays showed that knockdown of the induced VCAM-1 in BCPAP cells augmented the antitumor effects of vemurafenib, with decreased IC50 values of 1.4 to 0.8 µM. Meanwhile, overexpression of VCAM-1 in a BRAF-mutant anaplastic thyroid cancer cell line (FRO) reduced the sensitivity to vemurafenib, with increased IC50 values of 1.9 to 5.8 µM. Further investigation showed that PI3K-Akt-mTOR pathway was activated during BRAFi. Co-treatment with Akt signaling inhibitor MK2206 decreased the induced expression of VCAM-1 during BRAFi. This combination further improved the efficacy of vemurafenib. Moreover, VCAM-1 promoted migration and invasion in thyroid cancer cells in vitro, which was also indicated in thyroid cancer patients. The present study is the first to demonstrate that VCAM-1 is upregulated in thyroid cancer cells treated with vemurafenib and contributes to vemurafenib resistance in BRAF-mutant thyroid cancer cells. Targeting the PI3K-Akt-mTOR pathway-mediated VCAM-1 response may be an alternative strategy to sensitize BRAF-mutant thyroid cancers to vemurafenib.

The Sensitivity of Orthopaedic Surgeons to the Secondary Prevention of Fragility Fractures.

BACKGROUND: Orthopaedic surgeons must play an important role in the secondary prevention of fragility fractures; however, some surgeons are more aware than others of their responsibility regarding fracture prevention. The purpose of the present study was to identify which factors can lead to a higher sensitivity for fracture prevention. METHODS: A cross-sectional survey was distributed to orthopaedic surgeons via online invitation or at academic conferences in China from July through October 2015. A total of 452 surgeons responded. As the primary outcome measure, we created a sensitivity scoring system for fracture prevention based on the respondents' answers to 5 questions regarding behavior in the following areas: risk-factor evaluation, pharmacologic therapy, nonpharmacologic therapy, patient education, and follow-up. Multivariable linear regression and multivariable logistic regression analyses were used to identify factors related to surgeon sensitivity to fracture prevention. RESULTS: Very few surgeons reported having received adequate training regarding fracture prevention or reading guidelines or other fracture prevention literature (22% and 30%, respectively). Most respondents initiated pharmacologic or nonpharmacologic therapy (82% and 75%, respectively) for the treatment of confirmed osteoporosis among patients with fragility fractures, but only half performed a risk-factor evaluation, patient education, or timely patient follow-up (51%, 52%, and 48%, respectively). In the multivariable linear regression model, the orthopaedic surgeon's age (ß = 0.09, p = 0.003), self-rated knowledge level regarding osteoporosis or related issues (ß = 0.16, p < 0.001), self-perceived effectiveness in using preventive measures for patients with a fragility fracture (ß = 0.62, p < 0.001), and use of clinical pathways for fragility fractures in his or her workplace (ß = 1.24, p < 0.001) were independently associated with sensitivity scores for fracture prevention. Similar results were obtained from a multivariable logistic regression model. CONCLUSIONS: In China, the sensitivity of orthopaedic surgeons to the secondary prevention of fragility fractures is relatively low. Implementation of a comprehensive prevention approach and targeted continuing medical education are required to encourage surgeons to take greater responsibility for screening, treating, educating, and following their patients with fragility fractures.

GraphProtector: A Visual Interface for Employing and Assessing Multiple Privacy Preserving Graph Algorithms.

Analyzing social networks reveals the relationships between individuals and groups in the data. However, such analysis can also lead to privacy exposure (whether intentionally or inadvertently): leaking the real-world identity of ostensibly anonymous individuals. Most sanitization strategies modify the graph's structure based on hypothesized tactics that an adversary would employ. While combining multiple anonymization schemes provides a more comprehensive privacy protection, deciding the appropriate set of techniques-along with evaluating how applying the strategies will affect the utility of the anonymized results-remains a significant challenge. To address this problem, we introduce GraphProtector, a visual interface that guides a user through a privacy preservation pipeline. GraphProtector enables multiple privacy protection schemes which can be simultaneously combined together as a hybrid approach. To demonstrate the effectiveness of GraphProtector, we report several case studies and feedback collected from interviews with expert users in various scenarios.

A Utility-Aware Visual Approach for Anonymizing Multi-Attribute Tabular Data.

Sharing data for public usage requires sanitization to prevent sensitive information from leaking. Previous studies have presented methods for creating privacy preserving visualizations. However, few of them provide sufficient feedback to users on how much utility is reduced (or preserved) during such a process. To address this, we design a visual interface along with a data manipulation pipeline that allows users to gauge utility loss while interactively and iteratively handling privacy issues in their data. Widely known and discussed types of privacy models, i.e., syntactic anonymity and differential privacy, are integrated and compared under different use case scenarios. Case study results on a variety of examples demonstrate the effectiveness of our approach.

Cell-based phenotypic screening of mast cell degranulation unveils kinetic perturbations of agents targeting phosphorylation.

Mast cells play an essential role in initiating allergic diseases. The activation of mast cells are controlled by a complicated signal network of reversible phosphorylation, and finding the key regulators involved in this network has been the focus of the pharmaceutical industry. In this work, we used a method named Time-dependent cell responding profile (TCRP) to track the process of mast cell degranulation under various perturbations caused by agents targeting phosphorylation. To test the feasibility of this high-throughput cell-based phenotypic screening method, a variety of biological techniques were used. We further screened 145 inhibitors and clustered them based on the similarities of their TCRPs. Stat3 phosphorylation has been widely reported as a key step in mast cell degranulation. Interestingly, our TCRP results showed that a Stat3 inhibitor JSI124 did not inhibit degranulation like other Stat3 inhibitors, such as Stattic, clearly inhibited degranulation. Regular endpoint assays demonstrated that the distinctive TCRP of JSI124 potentially correlated with the ability to induce apoptosis. Consequently, different agents possibly have disparate functions, which can be conveniently detected by TCRP. From this perspective, our TCRP screening method is reliable and sensitive when it comes to discovering and selecting novel compounds for new drug developments.