Evidence map›Paper›PMID 34095775›Full record

ArticleJAMIA open2021

PRoBE the cloud toolkit: finding the best biomarkers of drug response within a breast cancer clinical trial.

Nicholas O'Grady, David L Gibbs, Kawther Abdilleh, Adam Asare, Smita Asare, Sara Venters, Lamorna Brown-Swigart, Gillian L Hirst, Denise Wolf, Christina Yau and 3 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in JAMIA open, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Review
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Nicholas O'GradyDepartment of Surgery, University of California San Francisco, San Francisco, California, USA.ORCID https://orcid.org/0000-0001-8711-7508
David L GibbsShmulevich Lab, Institute for Systems Biology, Seattle, Washington, USA.
Kawther AbdillehGeneral Dynamics, Department of Information Technology (GDIT), Rockville, Maryland, USA.
Adam AsareDepartment of Surgery, University of California San Francisco, San Francisco, California, USA.
Smita AsareQuantum Leap Healthcare Collaborative, San Francisco, California, USA.
Sara VentersDepartment of Surgery, University of California San Francisco, San Francisco, California, USA.
Lamorna Brown-SwigartDepartment of Surgery, University of California San Francisco, San Francisco, California, USA.
Gillian L HirstDepartment of Surgery, University of California San Francisco, San Francisco, California, USA.ORCID https://orcid.org/0000-0002-4502-0035
Denise WolfDepartment of Surgery, University of California San Francisco, San Francisco, California, USA.
Christina YauDepartment of Surgery, University of California San Francisco, San Francisco, California, USA.
Laura J van 't VeerDepartment of Surgery, University of California San Francisco, San Francisco, California, USA.
Laura EssermanDepartment of Surgery, University of California San Francisco, San Francisco, California, USA.
Amrita BasuDepartment of Surgery, University of California San Francisco, San Francisco, California, USA.

Funding

The I SPY 2.2 TRIAL: Evolving to Imaging and Molecular Biomarker Response Directed Adaptive Sequential Treatment to Optimize Breast Cancer OutcomesP01CA210961 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Nola M. Hylton-Watson · 2017 to 2026
$22.9M
CCR NIH HHS HHSN261200800001CNCI NIH HHS HHSN261200800001ENCI NIH HHS P01 CA210961
6 · The paper itself

Abstract

objectivesIn this paper, we discuss leveraging cloud-based platforms to collect, visualize, analyze, and share data in the context of a clinical trial. Our cloud-based infrastructure, Patient Repository of Biomolecular Entities (PRoBE), has given us the opportunity for uniform data structure, more efficient analysis of valuable data, and increased collaboration between researchers. MATERIALS AND

methodsWe utilize a multi-cloud platform to manage and analyze data generated from the clinical Investigation of Serial Studies to Predict Your Therapeutic Response with Imaging And moLecular Analysis 2 (I-SPY 2 TRIAL). A collaboration with the Institute for Systems Biology Cancer Gateway in the Cloud has additionally given us access to public genomic databases. Applications to I-SPY 2 data have been built using R Shiny, while leveraging Google's BigQuery tables and SQL commands for data mining.

resultsWe highlight the implementation of PRoBE in several unique case studies including prediction of biomarkers associated with clinical response, access to the Pan-Cancer Atlas, and integrating pathology images within the cloud. Our data integration pipelines, documentation, and all codebase will be placed in a Github repository. DISCUSSION AND

conclusionWe are hoping to develop risk stratification diagnostics by integrating additional molecular, magnetic resonance imaging, and pathology markers into PRoBE to better predict drug response. A robust cloud infrastructure and tool set can help integrate these large datasets to make valuable predictions of response to multiple agents. For that reason, we are continuously improving PRoBE to advance the way data is stored, accessed, and analyzed in the I-SPY 2 clinical trial.

Indexed as

breast cancerclinical trialsclouddata analysisI-SPY 2

Identifiers

PMID34095775
PMCPMC8172495

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.