The hallmarks of cancer provide a highly cited and well-used conceptual framework for describing the processes involved in cancer cell development. However, methods for translating these high-level concepts into data-level associations between hallmarks and genes (for high throughput analysis), vary widely between studies. In this investigation we compare cancer hallmark mapping strategies from different studies, based on Gene Ontology and biological pathway annotation. By analysing the semantic similarity between annotations, and the resulting gene set overlap, we identify emerging consensus knowledge.
SEEK ID: https://fairdomhub.org/investigations/441
Projects: Consensus Hallmark Annotation
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Created: 22nd Jan 2021 at 15:43
Last updated: 9th Feb 2021 at 09:03
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Projects: Consensus Hallmark Annotation, FAIR Functional Enrichment, The evolution of Gene Ontology
Institutions: University of Leiden, LIACS
Projects: SysMO DB, HUMET Startup, FAIRDOM, Consensus Hallmark Annotation, NL-Bioimaging FAIR Metadata Templates, FAIR Functional Enrichment, Benefit for All FAIR Data
Institutions: University of Leiden, LIACS
https://orcid.org/0000-0002-1279-5133Expertise: Biochemistry, Bioinformatics, Data Management
Tools: Data Management, Transcriptomics, Databases, Workflows, Web services, Taverna, Ontologies, semantic web
I am an Assistant Professor at Leiden University in the Leiden Institute of Advanced Computer Science. I am a bioinformatician and my research interests are in data integration. I use scientific workflows and semantic web technologies to integrate and analyse data in systems biology and functional genomics.
Projects: Consensus Hallmark Annotation, The evolution of Gene Ontology
Web page: Not specified
Data and experimental methods to support the work in the following paper:
Establishing Consensus Annotation for the Hallmarks of Cancer, 2020, Yi Chen, F.J.Verbeek and K.Wolstencroft, in submission
Programme: Hallmarks of cancer
Public web page: Not specified
Organisms: Homo sapiens
The hallmarks mapping schemes under comparison were developed over the period of 7 years and therefore were developed using different versions of the Gene Ontology and associated annotation. Understanding which differences between mapping schemes were the result of topological or annotation changes to GO could therefore help to further refine consensus and make results and conclusions more comparable between studies.
Submitter: Katy Wolstencroft
Investigation: Cancer Hallmark Consensus
Snapshots: No snapshots
Multiple studies have devised mapping schemes to associate cancer hallmarks with Gene Ontology terms and biological pathway. This study compares the similarities and differences between them, in order to establish consensus knowledge.
Submitter: Katy Wolstencroft
Investigation: Cancer Hallmark Consensus
Snapshots: No snapshots
This study examines how different hallmark gene datasets intersect with prognostic cancer genes
Submitter: Katy Wolstencroft
Investigation: Cancer Hallmark Consensus
Assays: Hub genes of modules and enriched GO terms, Jaccard Index Prognostic Hallmark Genes, WGCNA Prognostic Hallmark Genes
Snapshots: No snapshots
Submitter: Katy Wolstencroft
Biological problem addressed: Annotation
Investigation: Cancer Hallmark Consensus
Organisms: No organisms
Models: No Models
SOPs: No SOPs
Data files: GO Consensus terms, Genes annotated to selected GO terms belonging ..., Hallmark genes, Mapping from Gene Ontology terms to individual ..., Mapping from MSigDB pathways to GO terms, Mapping from pathways to individual cancer hall..., The number of genes annotated to individual can...
Snapshots: No snapshots
A Weighted Gene Co-Expression Network Analysis (WGCNA) of breast cancer prognostic genes (derived from transcriptome data from the TCGA Genomics Data Commons (GDC) data portal (https://portal.gdc.cancer.gov/)), and cancer hallmark genes.
Submitter: Katy Wolstencroft
Biological problem addressed: Biological Network Analysis
Investigation: Cancer Hallmark Consensus
Organisms: No organisms
Models: No Models
SOPs: No SOPs
Data files: FPKM value of breast cancer patient, Prognostic-hallmark genes of GO1 with log trans..., Prognostic-hallmark genes of GO2 with log trans..., Prognostic-hallmark genes of GO3 with log trans..., Prognostic-hallmark genes of GO4 with log trans...
Snapshots: No snapshots
A Jaccard Index of the overlap between prognostic and hallmark genes for 17 cancer types across different mapping schemes. The impact of selecting different mapping schemes was assessed by pairwise comparisons where there were 5 or more shared genes.
Submitter: Katy Wolstencroft
Biological problem addressed: Biological Network Analysis
Investigation: Cancer Hallmark Consensus
Organisms: No organisms
Models: No Models
SOPs: No SOPs
Data files: Abbreviations of 17 cancer types, Jaccard index score, prognostic genes of 17 cancer types
Snapshots: No snapshots
Submitter: Katy Wolstencroft
Biological problem addressed: Biological Network Analysis
Investigation: Cancer Hallmark Consensus
Organisms: No organisms
Models: No Models
SOPs: No SOPs
Data files: Edge data of GO terms in 2012, Edge data of GO terms in 2016, GO hierarchical network comparison between methods, Gene product count of GO terms in June 2012., Species data in June,2012, Term description and ID in June 2016, Term description and ID in June,2012, The number of annotations belongs to selected G..., species data in June, 2016, species data of GO in 2016, species data of GO in 2016
Snapshots: No snapshots
this assay include the hub genes of modules from different mapping schemes with highly functional similarities.
Submitter: Yi Chen
Assay type: Experimental Assay Type
Technology type: Technology Type
Investigation: Cancer Hallmark Consensus
Organisms: No organisms
SOPs: No SOPs
Data files: Gene enrichment analysis output of modules, Modules and hub genes, Semantic similarity between pairwise modules
Snapshots: No snapshots
1222 patients
Investigations: Cancer Hallmark Consensus
Studies: Prognostic and Hallmark Gene Networks
Assays: WGCNA Prognostic Hallmark Genes
Investigations: Cancer Hallmark Consensus
For each module, GSEA analysis was conducted by using web-tool g:profiler and only biological process (BP) were retained. Parameters for GSEA are default.
Investigations: Cancer Hallmark Consensus
Calculated by using R package GOSemSim.
Investigations: Cancer Hallmark Consensus
Modules were identified by WGCNA. hub genes of each modules were identified based on intramodular degree.
Investigations: Cancer Hallmark Consensus
Investigations: Cancer Hallmark Consensus
Investigations: Cancer Hallmark Consensus
Including 91 genes and 1222 Breast cancer patient This is an input data for WGCNA
Investigations: Cancer Hallmark Consensus
Studies: Prognostic and Hallmark Gene Networks
Assays: WGCNA Prognostic Hallmark Genes
Including 289 genes and 1222 Breast cancer patient This is an input data for WGCNA
Investigations: Cancer Hallmark Consensus
Studies: Prognostic and Hallmark Gene Networks
Assays: WGCNA Prognostic Hallmark Genes
Including 277 genes and 1222 Breast cancer patients. This is an input data for WGCNA.
Investigations: Cancer Hallmark Consensus
Studies: Prognostic and Hallmark Gene Networks
Assays: WGCNA Prognostic Hallmark Genes
Including 294 genes and 1222 Breast cancer Patient. This is an input data for WGCNA
Investigations: Cancer Hallmark Consensus
Studies: Prognostic and Hallmark Gene Networks
Assays: WGCNA Prognostic Hallmark Genes
Consensus between selected mapping methods.
Investigations: Cancer Hallmark Consensus
Additional file 2
Investigations: Cancer Hallmark Consensus
Additional File 1
Investigations: Cancer Hallmark Consensus
Hallmark gene sets belong to different mapping schemes.
Investigations: Cancer Hallmark Consensus
derived from Ulhen's research published in 2017.
Investigations: Cancer Hallmark Consensus
The excel presents the mapping from GO terms to individual cancer hallmarks retrieved from selected papers.
Investigations: Cancer Hallmark Consensus
It includes annotation number data at June 2012, June 2016 and Jan 2021.
Investigations: Cancer Hallmark Consensus
Studies: Evolution of Gene Ontology Terms
related to Figure 6 and additional file 6
Investigations: Cancer Hallmark Consensus
Studies: Evolution of Gene Ontology Terms
Investigations: Cancer Hallmark Consensus