The reactome pathway knowledgebase

Jassal, Bijay; Matthews, Lisa; Viteri, Guilherme; Gong, Chuqiao; Lorente, Pascual; Fabregat, Antonio; Sidiropoulos, Konstantinos; Cook, Justin; Gillespie, Marc; Haw, Robin; Loney, Fred; May, Bruce; Milacic, Marija; Rothfels, Karen; Sevilla, Cristoffer; Shamovsky, Veronica; Shorser, Solomon; Varusai, Thawfeek; Weiser, Joel; Wu, Guanming; Stein, Lincoln; Hermjakob, Henning; D’Eustachio, Peter

doi:10.1093/nar/gkz1031

Cited by 1,928 publications

(2,042 citation statements)

References 10 publications

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“…We were interested whether the mutational data, when considered from the perspective of mutated pathways, could reveal new biological correlates. To test this, we mapped mutation status to important BC pathways as defined in the Reactome database [58,59]. We called a pathway mutated when at least one of the member genes had a non-synonymous mutation, and clustered samples by pathway mutation status using Ward linkage.…”

Section: Mutations In Molecular Pathwaysmentioning

confidence: 99%

The Mutational Landscape of the SCAN-B Real-World Primary Breast Cancer Transcriptome

Brueffer

Gladchuk

Winter

et al. 2020

Preprint

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Breast cancer is a disease of genomic alterations, of which the complete panorama of somatic mutations and how these relate to molecular subtypes and therapy response is incompletely understood. Within the Sweden Cancerome Analysis Network-Breast project (SCAN-B; ClinicalTrials.gov NCT02306096), an ongoing study elucidating the tumor transcriptomic profiles for thousands of breast cancers prospectively, we developed an optimized pipeline for detection of single nucleotide variants and small insertions and deletions from RNA sequencing (RNA-seq) data, and profiled a large real-world population-based cohort of 3,217 breast tumors. We use it to describe the mutational landscape of primary breast cancer viewed through the transcriptome of a large population-based cohort of patients, and relate it to patient overall survival. We demonstrate that RNA-seq can be used to call mutations in important breast cancer genes such as PIK3CA, TP53, and ERBB2, as well as the status of key molecular pathways and tumor mutational burden, and identify potentially druggable genes in 86.8% percent of tumors. To make this rich and growing mutational portraiture of breast cancer available for the wider research community, we developed an open source web-based application, the SCAN-B MutationExplorer, accessible at http://oncogenomics.bmc.lu.se/MutationExplorer. These results add another dimension to the use of RNA-seq as a potential clinical tool, where both gene expression-based and gene mutation-based biomarkers can be interrogated simultaneously and in real-time within one week of tumor sampling. and sampling of tissue for this study. We also thank the Swedish National Breast Cancer Registry and Regional Cancer Center South for clinical data. The SweGen allele frequency data was generated

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Section: Mutations In Molecular Pathwaysmentioning

confidence: 99%

The Mutational Landscape of the SCAN-B Real-World Primary Breast Cancer Transcriptome

Brueffer

Gladchuk

Winter

et al. 2020

Preprint

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“…In contrast, The JAK-STAT pathway is most active for signaling between keratinocyte stem cells and basal cells in skin. To evaluate the extent of cell type-specific wiring of signaling pathways, we examined all manually annotated signaling pathways in the Reactome database 11 . For each pathway, we computed its cell type-specific activity score using the same mammary gland and skin scRNA-Seq data sets 10 .…”

Section: Wiring Of Signaling Pathways Is Highly Cell Type-dependentmentioning

confidence: 99%

CytoTalk:De novoconstruction of signal transduction networks using single-cell RNA-Seq data

Peng

Gao

et al. 2020

Preprint

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Single-cell technology has opened the door for studying signal transduction in a complex tissue at unprecedented resolution. However, there is a lack of analytical methods for de novo construction of signal transduction pathways using single-cell omics data. Here we present CytoTalk, a computational method for de novo constructing cell type-specific signal transduction networks using single-cell RNA-Seq data. CytoTalk first constructs intracellular and intercellular gene-gene interaction networks using an information-theoretic measure between two cell types. Candidate signal transduction pathways in the integrated network are identified using the prizecollecting Steiner forest algorithm. We applied CytoTalk to a single-cell RNA-Seq data set on mouse visual cortex and evaluated predictions using high-throughput spatial transcriptomics data generated from the same tissue. Compared to published methods, genes in our inferred signaling pathways have significantly higher spatial expression correlation only in cells that are spatially closer to each other, suggesting improved accuracy of CytoTalk. Furthermore, using single-cell RNA-Seq data with receptor gene perturbation, we found that predicted pathways are enriched for differentially expressed genes between the receptor knockout and wild type cells, further validating the accuracy of CytoTalk. In summary, CytoTalk enables de novo construction of signal transduction pathways and facilitates comparative analysis of these pathways across tissues and conditions.

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“…We utilized Gitools (v1.8.4) for enrichment analysis and heatmap generation [36]. We have utilized the Gene Ontology Biological Processes (GOBP) [37], Reactome pathway [38], Bioplanet pathways [39], HumanCyc database [40], DisGeNet [41], KEGG pathway [42] modules, and a custom in house built combined module (Supplementary file 4) for the overrepresentation analysis. Resulting p-values were adjusted for multiple testing using the Benjamin and Hochberg's method of False Discovery Rate (FDR) [25].…”

Section: Functional Enrichment Analysismentioning

confidence: 99%

“…We have utilized Reactome pathway browser [38] for the mapping of deregulated genes of SARS-CoV-2 infection in different cellular pathways. We then searched and targeted the pathways which are found to be enriched for lung related functionalities.…”

Section: Mapping Of the Deregulated Genes In Cellular Pathwaysmentioning

confidence: 99%

Lung biopsy cells transcriptional landscape from COVID-19 patient stratified lung injury in SARS-CoV-2 infection through impaired pulmonary surfactant metabolism

Islam

Khan

2020

Preprint

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Clinical management of COVID-19 is still complicated due to the lack of therapeutic interventions to reduce the breathing problems, respiratory complications and acute lung injury -which are the major complications of most of the mild to critically affected patients and the molecular mechanisms behind these clinical features are still largely unknown. In this study, we have used the RNA-seq gene expression pattern in the COVID-19 affected lung biopsy cells and compared it with the effects observed in typical cell lines infected with SARS-CoV-2 and SARS-CoV. We performed functional overrepresentation analyses using these differentially expressed genes to signify the processes/pathways which could be deregulated during SARS-CoV-2 infection resulting in the symptomatic impairments observed in COVID-19. Our results showed that the significantly altered processes include inflammatory responses, antiviral cytokine signaling, interferon responses, and interleukin signaling etc. along with downmodulated processes related to lung's functionality likeresponses to hypoxia, lung development, respiratory processes, cholesterol biosynthesis and surfactant metabolism. We also found that the viral protein interacting host's proteins involved in similar pathways like: respiratory failure, lung diseases, asthma, and hypoxia responses etc., suggesting viral proteins might be deregulating the processes related to acute lung injury/breathing complications in COVID-19 patients. Protein-protein interaction networks of these processes and map of gene expression of deregulated genes revealed that several viral proteins can directly or indirectly modulate the host genes/proteins of those lung related processes along with several host transcription factors and miRNAs. Surfactant proteins and their regulators SPD, SPC, TTF1 etc. which maintains the stability of the pulmonary tissue are found to be downregulated through viral NSP5, NSP12 that could lead to deficient gaseous exchange by the surface films. Mitochondrial dysfunction owing to the aberration of NDUFA10, NDUFAF5, SAMM50 etc. by NSP12; abnormal thrombosis in lungs through atypical PLAT, EGR1 functions by viral ORF8, NSP12; dulled hypoxia responses due to unusual shift in HIF-1 downstream signaling might be the causative elements behind the acute lung injury in COVID-19 patients. Our study put forward a distinct mechanism of probable virus induced lung damage apart from cytokine storm and advocate the need of further research for alternate therapy in this direction.

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The reactome pathway knowledgebase

Cited by 1,928 publications

References 10 publications

The Mutational Landscape of the SCAN-B Real-World Primary Breast Cancer Transcriptome

The Mutational Landscape of the SCAN-B Real-World Primary Breast Cancer Transcriptome

CytoTalk:De novoconstruction of signal transduction networks using single-cell RNA-Seq data

Lung biopsy cells transcriptional landscape from COVID-19 patient stratified lung injury in SARS-CoV-2 infection through impaired pulmonary surfactant metabolism

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