OncoboxPD: human 51 672 molecular pathways database with tools for activity calculating and visualization

Zolotovskaia, Marianna; Tkachev, Victor; Guryanova, Anastasia A.; Simonov, Alexander M.; Raevskiy, Mikhail; Efimov, Victor; Wang, Ye; Sekacheva, Marina; Garazha, Andrew; Borisov, Nicolas; Kuzmin, Denis; Sorokin, Maxim; Buzdin, Anton

doi:10.1016/j.csbj.2022.05.006

Cited by 21 publications

(27 citation statements)

References 51 publications

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“…Using the OncoboxPD [ 18 ], we detected activated and inhibited pathways in the CSF and PBMC of MS patients ( Figure 1 ). Unique pathways were grouped into categories based on integrating categories from multiple databases (Bicarta, Qiagen, Reactome, NCI, KEGG).…”

Section: Resultsmentioning

confidence: 99%

“…Activation/inhibition of biological pathways was determined by geometric mean for all genes in the pathway for all cells annotated as one cell type. Activated pathways were determined using the OncoboxPD [ 18 ], in which the activation level of the regulatory pathway (PAL) is calculated for each biological pathway from six databases (Biocarta [ 58 ], Reactome [ 59 ], KEGG [ 60 ], Qiagen Pathway Central [ 61 ], NCI [ 62 ] and HumanCYC [ 63 ]) based on expressed genes. Ten pathways with the highest PAL were selected as the main processes taking place in cells.…”

Section: Methodsmentioning

confidence: 99%

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In Silico Drug Repurposing in Multiple Sclerosis Using scRNA-Seq Data

Shevtsov¹,

Raevskiy

Stupnikov

et al. 2023

IJMS

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Multiple sclerosis (MS) is an autoimmune disease of the central nervous system still lacking a cure. Treatment typically focuses on slowing the progression and managing MS symptoms. Single-cell transcriptomics allows the investigation of the immune system—the key player in MS onset and development—in great detail increasing our understanding of MS mechanisms and stimulating the discovery of the targets for potential therapies. Still, de novo drug development takes decades; however, this can be reduced by drug repositioning. A promising approach is to select potential drugs based on activated or inhibited genes and pathways. In this study, we explored the public single-cell RNA data from an experiment with six patients on single-cell RNA peripheral blood mononuclear cells (PBMC) and cerebrospinal fluid cells (CSF) of patients with MS and idiopathic intracranial hypertension. We demonstrate that AIM2 inflammasome, SMAD2/3 signaling, and complement activation pathways are activated in MS in different CSF and PBMC immune cells. Using genes from top-activated pathways, we detected several promising small molecules to reverse MS immune cells’ transcriptomic signatures, including AG14361, FGIN-1-27, CA-074, ARP 101, Flunisolide, and JAK3 Inhibitor VI. Among these molecules, we also detected an FDA-approved MS drug Mitoxantrone, supporting the reliability of our approach.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

In Silico Drug Repurposing in Multiple Sclerosis Using scRNA-Seq Data

Shevtsov¹,

Raevskiy

Stupnikov

et al. 2023

IJMS

Self Cite

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“…Gene-regulatory network analysis was performed as described by S. Jung et al [ 52 ]. Pathway activation levels (PALs) were calculated and visualized with the Oncobox bioinformatical platform [ 53 ]. The molecular function of pathway components was algorithmically annotated according to Ref [ 54 ].…”

Section: Methodsmentioning

confidence: 99%

Human Blood Serum Inhibits Ductal Carcinoma Cells BT474 Growth and Modulates Effect of HER2 Inhibition

et al. 2022

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Trastuzumab, a HER2-targeted antibody, is widely used for targeted therapy of HER2-positive breast cancer (BC) patients; yet, not all of them respond to this treatment. We investigated here whether trastuzumab activity on the growth of HER2-overexpressing BT474 cells may interfere with human peripheral blood endogenous factors. Among 33 individual BC patient blood samples supplemented to the media, BT474 sensitivity to trastuzumab varied up to 14 times. In the absence of trastuzumab, human peripheral blood serum samples could inhibit growth of BT474, and this effect varied ~10 times for 50 individual samples. In turn, the epidermal growth factor (EGF) suppressed the trastuzumab effect on BT474 cell growth. Trastuzumab treatment increased the proportion of BT474 cells in the G0/G1 phases of cell cycle, while simultaneous addition of EGF decreased it, yet not to the control level. We used RNA sequencing profiling of gene expression to elucidate the molecular mechanisms involved in EGF- and human-sera-mediated attenuation of the trastuzumab effect on BT474 cell growth. Bioinformatic analysis of the molecular profiles suggested that trastuzumab acts similarly to the inhibition of PI3K/Akt/mTOR signaling axis, and the mechanism of EGF suppression of trastuzumab activity may be associated with parallel activation of PKC and transcriptional factors ETV1-ETV5.

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“…EMT score was established with the GSVA algorithm by separately inferring the activities of up-regulated and down-regulated EMT signature genes in individual samples and then calculating the differences between these two activities. DEGs between the high ICD score and low ICD score group in the TCGA-COAD cohort were further analyzed with the online tool Oncobox pathway databank (OncoboxPD) ( , accessed on 10 November 2022) [ 36 ], a collection of seven databases measuring the pathway activation levels (PALs).…”

Section: Methodsmentioning

confidence: 99%

Comprehensive Pan-Cancer Analyses of Immunogenic Cell Death as a Biomarker in Predicting Prognosis and Therapeutic Response

Wang

Huang

Yang

et al. 2022

Cancers

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Immunogenic cell death (ICD), a form of regulated cell death, is related to anticancer therapy. Due to the absence of widely accepted markers, characterizing ICD-related phenotypes across cancer types remained unexplored. Here, we defined the ICD score to delineate the ICD landscape across 33 cancerous types and 31 normal tissue types based on transcriptomic, proteomic and epigenetics data from multiple databases. We found that ICD score showed cancer type-specific association with genomic and immune features. Importantly, the ICD score had the potential to predict therapy response and patient prognosis in multiple cancer types. We also developed an ICD-related prognostic model by machine learning and cox regression analysis. Single-cell level analysis revealed intra-tumor ICD state heterogeneity and communication between ICD-based clusters of T cells and other immune cells in the tumor microenvironment in colon cancer. For the first time, we identified IGF2BP3 as a potential ICD regulator in colon cancer. In conclusion, our study provides a comprehensive framework for evaluating the relation between ICD and clinical relevance, gaining insights into identification of ICD as a potential cancer-related biomarker and therapeutic target.

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OncoboxPD: human 51 672 molecular pathways database with tools for activity calculating and visualization

Cited by 21 publications

References 51 publications

In Silico Drug Repurposing in Multiple Sclerosis Using scRNA-Seq Data

In Silico Drug Repurposing in Multiple Sclerosis Using scRNA-Seq Data

Human Blood Serum Inhibits Ductal Carcinoma Cells BT474 Growth and Modulates Effect of HER2 Inhibition

Comprehensive Pan-Cancer Analyses of Immunogenic Cell Death as a Biomarker in Predicting Prognosis and Therapeutic Response

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