BiomarkerKB Resource Integration

BiomarkerKB collects data from many different resources. The data that is collected is not always directly integrated into the data model and data from a resource is sometimes just added as valuable contextual annotations or cross references.

Other resources to be explored: MetaKB, CADSR Cancer, https://themarker.idrblab.cn/, biomarker.org, ResMarkerDB, SalivaDB, https://glycanage.com/publications, https://www.cancergenomeinterpreter.org/biomarkers, Glycan Biomarkers (code)

Please contact us at mazumder_lab@gwu.edu and daniallmasood@gwu.edu if you have any other resources that may contain biomarker data

CIViC

Status: Direct Integration into Data Model

• Clinical Interpretation of Variants in Cancer (CIViC).
• Provides cancer biomarkers in form of DNA mutations (dbSNPs).
• Platform provides clinicians treatment options for patients based on unique tumor profile.
• License: Creative Commons Attribution-NonCommercial 4.0 International License.

ClinVar

Status: Direct Integration into Data Model

• Public archive of reports of human variations classified for diseases and drug responses.
• Provides biomarkers for all disease, but we have only curated cancer biomarkers for now.
  • dbSNPs
  • File is really big but will go back and use existing script to map all biomarkers from here into the data model.
• License: Creative Commons Attribution-NonCommercial 4.0 International License.

EDRN

Status: Sample Integration into Data Model

• Cancer biomarkers.

GWAS

Status: Direct Integration into Data Model

• Published genome-wide association studies (GWAS).
• Provides biomarkers in form of SNPs.
• GWAS Catalog contains SNPs for a vast amount of diseases.
  • Preliminary curation only focused on cancer.
  • Will use existing script to map all biomarkers into data model.
• License: Creative Commons Attribution-NonCommercial 4.0 International License.

HPO

Status: Cross-Reference

• HPO provides disease and entity associations.
• Does not provide a change within the entity so we cannot collect biomarker data from here.
• However we can use it as a cross-reference within our cross-referencing section.
• Provides cross-reference to OMIM, SNOMED, and MONDO.

LOINC

Status: Cross-Reference

Data provided by Metabolomics Workbench

MarkerDB

Status: Direct Integration into Data Model

• Provides a lot of useful biomarker data and cross-references other resources as well.
• Information includes: panel information, abnormal levels of biomarkers by disease, structural information, etc.
• Annotations that can be cross-referenced include the above.
• By cross-referencing, BiomarkerKB will allow users to find more information for specific biomarkers and move towards the goal of being a comprehensive resource for biomarkers.
• License: Creative Commons Attribution-NonCommercial 4.0 International License.

Metabolomics Workbench

Status: Direct Integration into Data Model

Data provided by Metabolomics Workbench

• Metabolite biomarkers utilized in the uniform newborn screening program.
• Detect treatable disorders that are life threatening or having long-term morbidity, before they become symptomatic.

OncoKB

Status: Cross-Reference

• Provides useful information on drugs and therapy options for different biomarker entities.
• Also provides information based on what condition the entity is related to.
• License: A license is required to use OncoKB for commercial and/or clinical purposes, and to access OncoKB data programmatically for academic purposes.
• Paid license is required
• Cross-reference from biomarkers in BiomarkerKB to the appropriate drug information and therapy information is the best solution.

OncoMX

Status: Direct Integration into Data Model

• integrated cancer mutation and expression resource for exploring cancer biomarkers
• Manual curation effort by GWU and JPL
• Over 600 single and panel biomarkers
• License: Creative Commons Attribution-NonCommercial 4.0 International License.

OpenTargets

Status: Direct Integration into Data Model

• Collects potential drug targets and therapeutic targets.
• Some effort was required to find the correct biomarker data.
• 1200 biomarkers collected.
  • dbSNPs related to cancer and other disease
• License: Creative Commons Attribution-NonCommercial 4.0 International License.

PubMed Central Biomarker Gene Set Curation

Status: Direct Integration into Data Model

Data provided by Avi Ma'ayan's LINCS group

• This data set was created through manual curation of biomarker gene sets on Pubmed Central using the results of gene sets returned from Rummagene.
• Using the outputted search results within the Rummagene web server, we manually identified publications that associated different conditions and environmental exposures to biomarker gene sets.
• The biomarker gene sets were retrieved through the validation of the gene mentioned within each of the publications.
• The primary use case for this data is to identify biomarker panels/ gene sets associated with conditions.

UniProtKB

Status: Direct Integration into Data Model

• Can provide biomarker (change in entity), entity, condition, and sampling data.
• This data is in a text file that has to be reviewed fully and to make sure it will be able to be automatically extracted.
• Contextual information can be imputed if necessary.
• In UniProt there are found_in and entries that are actual biomarkers:
  • found_in will get a cross-reference;
  • actual biomarkers will be directly integrated.
• Manual curation of 56 reviewed entries with mention of "biomarker" in flat text file.
• License is Creative Commons Attribution 4.0 International (CC BY 4.0).