Evidence map›Paper›PMID 41448831›Full record

ArticleJournal for immunotherapy of cancer2025

AstroID resource: a scalable, relational database structure for longitudinal biomarker discovery.

Elizabeth M Will, Benjamin F Green, Scott Carey, Govind Warrier, Tricia R Cottrell, Aasheen Qadri, Andrew Jorquera, Sigfredo Soto-Diaz, Daphne Wang, Joel C Sunshine and 9 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal for immunotherapy of cancer, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

19 authors.

Elizabeth M Will *Dermatology, Johns Hopkins University, Baltimore, Maryland, USA.
Benjamin F Green *Dermatology, Johns Hopkins University, Baltimore, Maryland, USA.
Scott CareyInstitute for Clinical and Translational Research, Johns Hopkins University, Baltimore, Maryland, USA.
Govind WarrierOncology, Johns Hopkins University, Baltimore, Maryland, USA.ORCID http://orcid.org/0000-0002-6625-448X
Tricia R CottrellPathology and Molecular Medicine, Queen's University, Kingston, Ontario, Canada.
Aasheen QadriDermatology, Johns Hopkins University, Baltimore, Maryland, USA.
Andrew JorqueraDermatology, Johns Hopkins University, Baltimore, Maryland, USA.
Sigfredo Soto-DiazDermatology, Johns Hopkins University, Baltimore, Maryland, USA.
Daphne WangDermatology, Johns Hopkins University, Baltimore, Maryland, USA.
Joel C SunshineDermatology, Johns Hopkins University, Baltimore, Maryland, USA.ORCID http://orcid.org/0000-0001-9987-6712
Julie Stein DeutschDermatology, Johns Hopkins University, Baltimore, Maryland, USA.
Robert A AndersPathology, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
Qingfeng C ZhuPathology, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
Ludmila DanilovaOncology, Johns Hopkins University, Baltimore, Maryland, USA.ORCID http://orcid.org/0000-0003-2813-3094
Leslie CopeOncology, Johns Hopkins University, Baltimore, Maryland, USA.
Evan J LipsonOncology, Johns Hopkins University, Baltimore, Maryland, USA.ORCID http://orcid.org/0000-0003-2976-0911
Logan L Engle *Dermatology, Johns Hopkins University, Baltimore, Maryland, USA.ORCID http://orcid.org/0000-0002-6375-9060
Janis M Taube *Dermatology, Johns Hopkins University, Baltimore, Maryland, USA jtaube1@jhmi.edu.ORCID http://orcid.org/0000-0002-8273-4395
Alexander S SzalayDermatology, Johns Hopkins University, Baltimore, Maryland, USA.

Funding

ONCOLOGY: CHEMOTHERAPY, IMMUNOLOGY, BIOLOGYT32CA009071 · NCI · JOHNS HOPKINS UNIVERSITY · PI Mary Y Armanios, Nilofer S. Azad · 1985 to 2026
$12.8M
PD-1/PD-L1 modulation in cancer therapyR01CA142779 · NCI · JOHNS HOPKINS UNIVERSITY · PI PARDOLL, DREW M., TAUBE, JANIS M · 2010 to 2025
$8.2M
Comprehensive Analysis and Multi-Omics Data Integration for Cancer-Related StudiesR50CA243627 · NCI · JOHNS HOPKINS UNIVERSITY · PI Ludmila Danilova · 2019 to 2026
$975k
NCI NIH HHS R01 CA142779NCI NIH HHS R50 CA243627NCI NIH HHS T32 CA009071
6 · The paper itself

Abstract

backgroundThe biological sciences are producing increasingly larger datasets for biomarker discovery. While common data models have been developed for medical terms as they relate to patient health outcomes, a data model that supports longitudinal tracking of biospecimens and relating them against an individual patient experience is a large, unmet need.

methodA structure and associated taxonomy were achieved through a six-tier build in Research Electronic Data CAPture (REDCap), which organizes the complexity of the therapeutic decisions, biospecimens, and outcomes that characterize a longitudinal patient experience. Modules were developed to support export of REDCap data into a Structured Query Language (SQL) format for merging with extended biomarker data, also housed in SQL.

resultsThe resultant AstroID resource is a relational structure for clinical and biospecimen data that meets several desired goals: searchable, flexible, generic, Health Insurance Portability and Accountability Act-compliant, auditable, and easy-to-use. The essential elements forming the core of the six-tiered build are provided, so others can readily adopt this schema, as well as an example of an extended, customized build to support biomarker discovery for patients with melanoma. Two examples where this data structure was used to support biomarker discovery and development are described, and example queries of the database are also presented. To the extent possible, the data dictionary was aligned with large data models, such as those for the National Institutes of Health's Human Tumor Atlas Network. The structure can readily scale to accommodate thousands of patients, multimodality data, and spatial characterization of billions of cells. Radiologic imagery can also be included along with pathology imagery to support spatial studies, including artificial intelligence-driven analyses.

conclusionsThis effort provides a database model for investigators conducting research on large volumes of biospecimens with clinical annotation. We have now deployed this structure in our laboratories and have over 1B cells spatially mapped, each effectively tagged with the clinical information from longitudinal patient experiences. While the description uses the example of cancer biomarkers, this data structure could be used to characterize longitudinal biospecimens from any disease process. In the near future, automatic synchronization between the electronic medical record and one or more AstroID databases is anticipated.

Indexed as

BiomarkersBiomarkers, TumorDatabases, FactualHumansLongitudinal StudiesBiomarkersBiomarkers, TumorBiomarkerBiopsyMelanomaPathologyTumor microenvironment - TME

Identifiers

PMID41448831
PMCPMC12742122

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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.