Linked Cancer Genome Atlas Database

Linked Cancer Genome Atlas
Database
Muhammad Saleem, Shanmukha
Sampath Padmanabhuni, Axel-Cyrille
Ngonga Ngomo, Jonas S. Almeida,
Stefan Decker, Helena F. Deus.
Linked Data Cup, I-Semantics 2013, September 04 - 06 2013, Graz, Austria

Agenda
• Cancer Genome Atlas (TCGA) introduction
• Problem statement
• Linked TCGA a scalable solution
• Cancer treatment using Linked TCGA
• Demo of the use cases
• Conclusion

TCGA Introduction
• A publicly accessible atlas of cancer related data
from National Cancer Institute (NCI)
– 9000 patients
– 33 cancer types
– 147,645 raw data files
– total of 12.7 terabytes of data
• Only a 46% of the total expected data with new
data being submitted every day
• Goal is to enable cancer researchers to make and
validate important discoveries

Problem Statement
• Data in the TCGA is organized as text archives
with no remote querying interface
– Download very large archives and waiting in queues
– Parse the relevant text
– Collect the critical co-variates necessary for analysis
• Various types of experimental results are not
connected biologically
• TCGA data should be made publicly available for
remote querying and virtual integration

Linked TCGA a Scalable Solution:
RDFization

chromosome position beta_value
16 28890100 0.439271303584937
3 57743543 0.245147665381461
7 15725862 0.0440161061196347
2 177029073 0.741342927038953
11 93862594 0.0290713821114479
14 93813777 0.985555436681019
18 11980953 0.0109832005732912
14 89290921 0.0104525957219692
composite
element REF gene_symbolchromosome position beta_value
cg00000292 ATP2A1 16 288901000.439271303584937
cg00002426 SLMAP 3 577435430.245147665381461
cg00003994 MEOX2 7 157258620.0440161061196347
cg00005847 HOXD3 2 1770290730.741342927038953
cg00006414 ZNF425 7 148822837NA
cg00007981 PANX1 11 938625940.0290713821114479
cg00008493 COX8C 14 938137770.985555436681019
cg00008713 IMPA2 18 119809530.0109832005732912
cg00009407 TTC8 14 892909210.0104525957219692
Text to RDF Conversion
Data Refiner
Refined
Raw

chromosome position beta_value
16 28890100 0.439271303584937
3 57743543 0.245147665381461
7 15725862 0.0440161061196347
2 177029073 0.741342927038953
11 93862594 0.0290713821114479
14 93813777 0.985555436681019
18 11980953 0.0109832005732912
14 89290921 0.0104525957219692
composite
element REF gene_symbolchromosome position beta_value
cg00000292 ATP2A1 16 288901000.439271303584937
cg00002426 SLMAP 3 577435430.245147665381461
cg00003994 MEOX2 7 157258620.0440161061196347
cg00005847 HOXD3 2 1770290730.741342927038953
cg00006414 ZNF425 7 148822837NA
cg00007981 PANX1 11 938625940.0290713821114479
cg00008493 COX8C 14 938137770.985555436681019
cg00008713 IMPA2 18 119809530.0109832005732912
cg00009407 TTC8 14 892909210.0104525957219692
@prefix b:<http://tcga.deri.ie/>.
@prefix d:<http://tcga.deri.ie/schema/bcr_patient_barcode>.
@prefix r:<http://tcga.deri.ie/schema/result>.
@prefix c:<http://www.w3.org/1999/02/22-rdf-syntax-ns#type>.
@prefix w:<http://tcga.deri.ie/schema/dna_methylation_result>.
@prefix m:<http://tcga.deri.ie/schema/chromosome>.
@prefix v:<http://tcga.deri.ie/schema/position>.
@prefix u:<http://tcga.deri.ie/schema/beta_value>.
b:TCGA-A2-A0CX d: "TCGA-A2-A0CX".
b:TCGA-A2-A0CX r: b:TCGA-A2-A0CX-d1 .
b:TCGA-A2-A0CX-d1 c: w: ; m: "16"; v: "28890100"; u: "0.439271303584937".
Text to RDF Conversion
Data Refiner
RDFizer
Refined
RDFizedRaw

Linked TCGA Tumors Statistics
Tumor Type
Original
Size(GB)
Refined
Size (GB)
RDFized
Size (GB)
Triples
(Million)
Cervical (CESC) 8.75 2.44 8.86 400.19
Rectal adenocarcinoma (READ) 8.07 2.25 9.04 413.31
Papillary Kidney (KIRP) 10.40 2.90 10.4 469.65
Bladder cancer (BLCA) 12.16 3.39 12.3 556.38
Acute Myeloid Leukemia (LAML) 14.85 4.14 15.1 684.05
Lower Grade Glioma (LGG) 17.08 4.76 17.1 778.82
Prostate adenocarcinoma (PRAD) 18.05 5.03 18.1 821.01
Lung squamous carcinoma (LUSC) 20.63 5.75 20.5 927.08
Cutaneous melanoma (SKCM) 23.22 6.47 23.2 1050.94
Head and neck squamous cell(HNSC) 27.6 7.69 27.5 1245.37
• A total of 7.36 Billion Triples for 10 small tumors
• Total Linked TCGA > 30 billion triples (Largest Dataset of LOD)

Linking to Linked Open Data
Source Target Class #Links
DNA27 HGNC Gene 23181
DNA27 Homologene Gene 27654
DNA27 HGNC Gene 15171
DNA450 Homologene Gene 489643
DNA450 OMIM Gene 212284
DNA27 HGNC Chromosome 108662
DNA27 OMIM Chromosome 16039535
Methylation HGNC Chromosome 97530
Methylation OMIM Chromosome 14407269
Gene Expression HGNC Chromosome 86052
Gene Expression OMIM Chromosome 12535829
• Links are generated using LIMES
http://aksw.org/Projects/LIMES.html

Cancer Treatment using Linked TCGA

Linked TCGA Use Cases
1. Targeted cancer treatment
– Whether a specific drug can be used to treat a tumour
using the genomic data of patients with same tumor
2. Mechanism-based treatment
– Whether a combination of drugs can be applied to treat
a specific tumor using similar patients data
3. Survival outcome
– Using mathematical model to predict future signs such
as survival outcome for a new patient

Use case 1,2 SPARQL query
SELECT ?patient ?mean
WHERE
{
?uri tcga:tumour_type "BRCA".
?uri tcga:bcr_patient_barcode ?patient.
?patient rdf:type tcga:expression_gene_results.
?patient tcga:gene_symbol "HER2","ER".
?patient tcga:scaled_estimate ?mean
}

Use Case 1,2 Querying LOD DrugBank
SELECT ?drugname
WHERE
{
?patient rdf:type tcga:expression_gene_results.
?patient tcga:gene_symbol ?targetname .
?patient tcga:scaled_estimate ?mean.
FILTER (?mean > Threshold)
?drug drugbank:target ?target.
?drug drugbank:genericName ?drugname .
?target drugbank:synonym ?targetname .
FILTER REGEX (?targetname, "HER2||estrogenreceptor||ERBB2", "i")
}

Use Case 3 Query
SELECT ?patient ?mean
WHERE
{
?uri tcga:tumour_type "BRCA".
?uri tcga:bcr_patient_barcode ?patient.
?patient rdf:type tcga:clinical.
?patient tcga:tumour_stage ?tumour_stage.
?patient tcga:age_at_initial_patalogical_diagnosis ?age.
?patient tcga:relevant_biomarker "BRCA1","CDKN2A", "CDH1".
?patient tcga:beta_value ?mean
}

Everything is Public
• TopFed: https://code.google.com/p/topfed/
• Linked TCGA : http://tcga.deri.ie/
saleem@informatik.uni-leipzig.de
AKSW, University of Leipzig, Germany

Thanks
Muhammad Saleem
saleem.muhammd@gmail.com

Linked Cancer Genome Atlas Database

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