Evidence map›Paper›PMID 37811874›Full record

ArticleNucleic acids research2024

ClinicalOmicsDB: exploring molecular associations of oncology drug responses in clinical trials.

Chang In Moon, John Michael Elizarraras, Jonathan Thomas Lei, Byron Jia, Bing Zhang

Open access · goldAbstract read
In one paragraph

Article in Nucleic acids research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
2.0field-weighted citation impact, top 13% of its field
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

9 citing papers in PubMed, 13 citations in OpenAlex.

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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

5 authors at 2 institutions in 1 country.

Chang In MoonLester and Sue Smith Breast Center and Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX 77030, USA.
John Michael ElizarrarasLester and Sue Smith Breast Center and Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX 77030, USA.
Jonathan Thomas LeiLester and Sue Smith Breast Center and Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX 77030, USA.
Byron JiaDepartment of Chemistry, Carleton College, Northfield, MN 55057, USA.
Bing ZhangLester and Sue Smith Breast Center and Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX 77030, USA.ORCID 0000-0001-8676-2425
Baylor College of Medicine · USCarleton College · US

Funding

The Clinical Translational Research Certificate of Added Qualification ProgramT32GM136554 · NIGMS · BAYLOR COLLEGE OF MEDICINE · PI Melissa Suter, IGNATIA B VAN DEN VEYVER · 2020 to 2026
$3.0M
NIGMS NIH HHS T32 GM136554NIGMS NIH HHS T32GM136554
6 · The paper itself

Abstract

Matching patients to optimal treatment is challenging, in part due to the limited availability of real-world clinical datasets for predictive biomarker identification. The growing integration of omics profiling into clinical trials presents a new opportunity to tackle this challenge. Here, we introduce ClinicalOmicsDB, a web application for exploring molecular associations of oncology drug responses in clinical trials. This database includes transcriptomic data from 40 clinical trial studies, with 5913 patients spanning 11 cancer types. These studies include 67 treatment arms with a variety of chemotherapy, targeted therapy and immunotherapy drugs, and their combinations, which we organize based on an established ontology for easier navigation. The web application provides users with three options to explore molecular associations of oncology drug responses, focusing on studies, treatments or genes, respectively. Gene set analysis further connects treatment response to pathway activity and tumor microenvironment attributes. The user-friendly web interface of ClinicalOmicsDB streamlines interactive analysis. A Rust-based backend speeds up response time, and application programming interfaces and an R package enable programmatic access. We use three case studies to demonstrate the utility of this resource in human cancer studies. ClinicalOmicsDB is freely available at http://trials.linkedomics.org/.

Indexed as

Databases, FactualNeoplasmsSoftwareClinical Trials as TopicGene Expression ProfilingHumansTumor Microenvironment

Identifiers

PMID37811874
PMCPMC10767859
OpenAlexW4387440937

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.