Public Maps

PancanAtlas

As its concluding project, The Cancer Genome Atlas (TCGA) Research Network has completed the most comprehensive cross-cancer analysis to date with analysis of 10,000 tumors from 33 types of cancer: The TCGA Pan-Cancer Atlas (PanCanAtlas). This project aims to answer big, overarching questions about cancer by examining the full set of tumors characterized in the robust TCGA dataset.

https://www.ncbi.nlm.nih.gov/m/pubmed/29625048/

Pancan12

The diverse tumor set called “Pan-Cancer-12,” is composed of 12 different malignancies. It comprises 3,527 cases assayed by at least four of the six possible data types routinely generated by The Cancer Genome Atlas: whole-exome DNA sequence (Illumina HiSeq and GAII), DNA copy number variation (Affymetrix 6.0 microarrays), DNA methylation (Illumina 450,000-feature microarrays), genome-wide mRNA levels (Illumina mRNA-seq), microRNA levels (Illumina microRNA-seq), and protein levels for 131 proteins and/or phosphorylated proteins (Reverse Phase Protein Arrays; RPPA).

The Sample Map layouts are composed of tumor samples collected in the study. Attributes that can be explored on the Sample Map are described at Pancan12/SampleMap Attributes.

The Gene Map layouts are composed of genes mapping to a probe from the data collection platforms. E.g. MYC on the mRNA Gene Map, corresponds to the probe mapping to MYC on the micro array platform. Attributes that can be explored on the Gene Map are described at Pancan12/GeneMap Attributes.

Hoadley,K.A., Yau,C., Wolf,D.M., Cherniack,A.D., Tamborero,D., Ng,S., Leiserson,M.D.M., Niu,B., McLellan,M.D., Uzunangelov,V., et al. (2014) Multiplatform analysis of 12 cancer types reveals molecular classification within and across tissues of origin. Cell, 158, 929–44.

Gliomas

We assembled a dataset comprising all TCGA newly diagnosed diffuse glioma consisting of 1,122 patients and comprehensively analyzed using sequencing and array-based molecular profiling approaches.

We extended our analysis using TumorMap to perform integrated co-clustering analysis of the combined gene expression (n = 1,196) and DNA methylation (n = 867) profiles. Clusters in the map indicate groups of samples with high similarity of integrated gene expression and DNA methylation profiles.

Ceccarelli,M., Barthel,F.P., Malta,T.M., Sabedot,T.S., Salama,S.R., Murray,B.A., Morozova,O., Newton,Y., Radenbaugh,A., Pagnotta,S.M., et al. (2016) Molecular Profiling Reveals Biologically Discrete Subsets and Pathways of Progression in Diffuse Glioma. Cell, 164, 550–63.

QuakeBrain

We used single cell RNA sequencing on 466 cells to capture the cellular complexity of the adult and fetal human brain at a whole transcriptome level. Healthy adult temporal lobe tissue was obtained during surgical procedures where otherwise normal tissue was removed to gain access to deeper hippocampal pathology in patients with medical refractory seizures. We were able to classify individual cells into all of the major neuronal, glial, and vascular cell types in the brain. We were able to divide neurons into individual communities and show that these communities preserve the categorization of interneuron subtypes that is typically observed with the use of classic interneuron markers.

Darmanis,S., Sloan,S.A., Zhang,Y., Enge,M., Caneda,C., Shuer,L.M., Hayden Gephart,M.G., Barres,B.A. and Quake,S.R. (2015) A survey of human brain transcriptome diversity at the single cell level. Proc. Natl. Acad. Sci. U. S. A., 112, 7285–90.

pCHIPS

The presented pChips data set is a subset of Pancan12 data supplemented by clinical tissue from lethal metastatic castration-resistant prostate cancer patients obtained at rapid autopsy.

Drake,J.M., Paull,E.O., Graham,N.A., Lee,J.K., Smith,B.A., Titz,B., Stoyanova,T., Faltermeier,C.M., Uzunangelov,V., Carlin,D.E., et al. (2016) Phosphoproteome Integration Reveals Patient-Specific Networks in Prostate Cancer. Cell, 166, 1041–1054.

mgmarin_public/PCAWG_JuncBASE

TBD

Attribute Descriptions

Pancan12/SampleMap Attributes

Tissue

BRCA Subtype

COADREAD Subtype

GBM Subtype

OV subtype

UCEC Subtype

gender

number_of_lymphnodes_positive

colon_polyps_present

microsatellite_instability

metastasis_pathological_spread

height

weight

age_at_initial_pathologic_diagnosis

icd_10

lymphovascular_invasion_present

karnofsky_performance_score

neoplasm_histologic_grade

icd_o_3_site

primary_tumor_t_stage

lymphnode_pathologic_spread

acute_myeloid_leukemia_calgb_cytogenetics_risk_category

tumor_stage_and_substage

neoplasm_disease_lymph_node_stage

primary_tumor_pathologic_spread

history_of_colon_polyps

tumor_stage

pancan subtype integrated

pancan subtype methylation

pancan subtype RPPA

pancan subtype mRNA

pancan subtype miRNA

pancan subtype mutations

Met vs Primary

…_MUTATION (313 mutation flags for high-confidence mutations, where * is a gene symbol in HUGO space)

…_AMPLIFICATION (999 gene-level or chromosomal amplification events)

…_DELETION (1987 gene-level or chromosomal deletion events)

TF_IPL_* (774 transcription factors with their activities summarized in the PARADIGM IPL space per each sample; * is a gene symbol in HUGO space)

* program (42 drug programs inferred from the gene expression data, where * is a molecular process or function name)

Mutation Signature 1

Mutation Signature 2

Mutation Signature 3

Mutation Signature 4

Mutation Signature 5

Mutation Signature 6

Mutation Signature 7

Mutation Signature 8

Mutation Signature 10

Mutation Signature 13

Mutation Signature 14

Mutation Signature 17

Mutation Signature 20

Mutation Signature 26

Mutation Signature 27

Pancan12/GeneMap Attributes

Database name	Number of sets	Variable type
MSigDB Positional Gene Sets	326	Binary
MSigDB Hallmark gene sets	50	Binary
MSigDB Canonical gene sets	1330	Binary
GO:Biological Process	825	Binary
GO:Cellular Component	233	Binary
GO:Molecular Function	396	Binary