Meningioma (University of Toronto, Nature 2021)
Meningioma DNA somatic copy number, somatic point mutations, DNA methylation, RNA abundance, protein abundance
Can it answer your research question?
0 of 6 supportedOverall survival
Not measuredClinical field completeness has not been measured for this record.
Progression or recurrence
Not measuredClinical field completeness has not been measured for this record.
Treatment response
Not measuredClinical field completeness has not been measured for this record.
Which drug was given
Not measuredClinical field completeness has not been measured for this record.
Stage-adjusted modelling
Not measuredClinical field completeness has not been measured for this record.
Analysis by race or ethnicity
Not measuredClinical field completeness has not been measured for this record.
At a glance
Every percentage is the repository’s own record of what is filled inSubjectCALC
As filed by the repository
Who is in the cohortAPI
The repository’s harmonized records carry no demographics for this dataset.
What was measured, and on how many
- Mutation calls (panel, exome or genome)115 of 121 samples · 95%
- Copy number alterations121 of 121 samples · 100%
- Mass spectrometry proteomics96 of 121 samples · 79%
Access
Processed data download from the cBioPortal study page or its public REST API; no account required. Primary raw data remain wherever the original investigators deposited them.
- Open components
- harmonized mutation, copy-number, expression and clinical files
- License
- Per-study terms; cBioPortal asks that the original study be cited
- Citation requirement
- Cite the original publication, and cite cBioPortal if the portal's harmonized files were used.
What it is good for
Written and checked by a reviewer, not generated from metadata.
No reviewed research questions yet. The measurements and field completeness above are machine-extracted and still useful for judging fit.
What it cannot tell you
Written by a reviewer against the source, not inferred from what is missing.
No reviewed limitations yet. Check the field completeness chart above before committing to an analysis. Low coverage on an endpoint you need is the most common blocker.
Who has used it
Articles that analyzed these data, counted separately from articles that only cited the paper. Only the first counts as reuse.
- Not assessed: this dataset has no accession specific enough for citation-based reuse tracing, so a shortfall cannot be measured.
Original publication
Articles that analyzed the data
Not searchable. See the note above.
Community examples
Share your exampleAnalyses someone ran on these data end to end, each with a receipt recording when it ran, against which packages and for how long.
Nobody has shared an analysis of this dataset yet. The examples on other datasets cover the common patterns and can be adapted - and if you adapt one, it belongs here.
Start here
Starter code generated from this record’s own identifiers, then the access steps.
Get the data in code
cBioPortal: clinical data and the full study bundlepython
import requests, pandas as pd
STUDY = "mng_utoronto_2021"
base = "https://www.cbioportal.org/api"
clin = requests.get(f"{base}/studies/{STUDY}/clinical-data",
params={"clinicalDataType": "PATIENT", "projection": "SUMMARY"}, timeout=60).json()
patients = pd.DataFrame(clin).pivot_table(index="patientId", columns="clinicalAttributeId",
values="value", aggfunc="first")
print(patients.shape)
profiles = requests.get(f"{base}/studies/{STUDY}/molecular-profiles", timeout=60).json()
print([p["molecularProfileId"] for p in profiles])
# Whole study as flat files: https://cbioportal-datahub.s3.amazonaws.com/mng_utoronto_2021.tar.gzThis page as data: limitations firstbash
curl -s https://cd2s.vercel.app/data/datasets/cbio-mng-utoronto-2021.json | python3 -c '
import json, sys
r = json.load(sys.stdin)
for l in r["limitations"]:
print(l["severity"].upper(), "-", l["statement"][:120])
print("survival endpoint:", r["longitudinal"]["has_survival_endpoint"], "| treatment response:", r["longitudinal"]["has_treatment_response"])'Access steps
- Open the study in cBioPortalFor people
Harmonized molecular and clinical files are open. Cite the original publication, and cite cBioPortal if the portal's harmonized files were used.
https://www.cbioportal.org/study/summary?id=mng_utoronto_2021 - Download the whole study as a zipFor people
The datasets page carries the staging files used by the portal.
https://www.cbioportal.org/datasets - Or pull the staging files with git-lfsFor people
Study folders are named by study id under public/.
https://github.com/cBioPortal/datahubgit clone https://github.com/cBioPortal/datahub.git && cd datahub git -c lfs.fetchexclude="" lfs pull -I public/mng_utoronto_2021 - Read the study straight from the REST APIFor agents
No key is required; pace requests when sweeping many studies.
https://docs.cbioportal.org/web-api-and-clients/curl -s 'https://www.cbioportal.org/api/studies/mng_utoronto_2021/clinical-data?clinicalDataType=PATIENT&projection=SUMMARY'
Provenance
All of it, and more, is in this record’s JSON.
Identifiers
- cBioPortal studymng_utoronto_2021API
Versions and verification
- Metadata retrieved
- 18 Sept 2026
- Review status
- Machine-extracted
- Data generation funding
- Funded data generation
Funding
Funded data generation
- U24CA248265Advancing method benchmarking and data sharing through crowd-sourced competitions in cancer researchPaul Christopher Boutros, Susheel VarmaAPI
- P50CA211015Administrative CoreLinda M Liau, GANG LIAPI
- P30CA016042Epigenomics, RNA, and Gene Regulation (ERGR)Kathrin Plath, Richard S FinnAPI