ArticleHuman genomics2016
The clinical trial landscape in oncology and connectivity of somatic mutational profiles to targeted therapies.
Article in Human genomics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 82 papers, 3 of them syntheses that pooled 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.
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.
Who cites it
82 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- A harmonized meta-knowledgebase of clinical interpretations of somatic genomic variants in cancer.Nature genetics · 2020Pooled it
- Text-mining clinically relevant cancer biomarkers for curation into the CIViC database.Genome medicine · 2019Pooled it
- mTOR Inhibitors in Castration-Resistant Prostate Cancer: A Systematic Review.Targeted oncology · 2017Pooled it
- Operationalizing Next-Generation Sequencing in a Community-Based Academic Cancer Center: Workflow, Integration, and Impact.Cancers · 2026Article
- Tutorial for variant interrogation in tumor samples.PLoS computational biology · 2026Article
- The Knowledge Connector decision support system for multiomics-based precision oncology.Nature communications · 2026Article
- Saturation mutagenesis identifies activating and resistance-inducing FGFR kinase domain mutations.Nature genetics · 2026Article
- Data-driven discovery of gene expression markers distinguishing pediatric acute lymphoblastic leukemia subtypes.Molecular oncology · 2025Article
- Evaluating Language Models for Biomedical Fact-Checking: A Benchmark Dataset for Cancer Variant Interpretation Verification.bioRxiv : the preprint server for biology · 2025Article
- Need Analysis of Clinician-Oriented Integrated Precision Oncology Decision Support Tools: Qualitative Descriptive Study.JMIR human factors · 2025Article
- Towards Personalized Precision Oncology: A Feasibility Study of NGS-Based Variant Analysis of FFPE CRC Samples in a Chilean Public Health System Laboratory.Current issues in molecular biology · 2025Article
- A comprehensive database for identifying and interpreting ctDNA driver genes and variants in cancer.Scientific data · 2025Article
- High-precision information retrieval for rapid clinical guideline updates.NPJ digital medicine · 2025Article
- OKAIN: A comprehensive oncology knowledge base for the interpretation of clinically actionable alterations.Open medicine (Warsaw, Poland) · 2025Article
- Cancer genomics and bioinformatics in Latin American countries: applications, challenges, and perspectives.Frontiers in oncology · 2025Review
- Analysis of mutations in precision oncology using the automated, accurate, and user-friendly web tool PredictONCO.Computational and structural biotechnology journal · 2024Article
- Genomic profiling and expanded use of targeted anticancer drugs in solid cancers with exhausted evidence-based treatment options (PRECODE): study protocol of a prospective, non-randomized, cohort study.BMC medical genomics · 2024Article
- Precision oncology platforms: practical strategies for genomic database utilization in cancer treatment.Molecular cytogenetics · 2024Review
- A computational workflow for analysis of missense mutations in precision oncology.Journal of cheminformatics · 2024Article
- Methylation-Based Characterization of a NewInternational journal of molecular sciences · 2024Article
22 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundPrecision medicine in oncology relies on rapid associations between patient-specific variations and targeted therapeutic efficacy. Due to the advancement of genomic analysis, a vast literature characterizing cancer-associated molecular aberrations and relative therapeutic relevance has been published. However, data are not uniformly reported or readily available, and accessing relevant information in a clinically acceptable time-frame is a daunting proposition, hampering connections between patients and appropriate therapeutic options. One important therapeutic avenue for oncology patients is through clinical trials. Accordingly, a global view into the availability of targeted clinical trials would provide insight into strengths and weaknesses and potentially enable research focus. However, data regarding the landscape of clinical trials in oncology is not readily available, and as a result, a comprehensive understanding of clinical trial availability is difficult.
resultsTo support clinical decision-making, we have developed a data loader and mapper that connects sequence information from oncology patients to data stored in an in-house database, the JAX Clinical Knowledgebase (JAX-CKB), which can be queried readily to access comprehensive data for clinical reporting via customized reporting queries. JAX-CKB functions as a repository to house expertly curated clinically relevant data surrounding our 358-gene panel, the JAX Cancer Treatment Profile (JAX CTP), and supports annotation of functional significance of molecular variants. Through queries of data housed in JAX-CKB, we have analyzed the landscape of clinical trials relevant to our 358-gene targeted sequencing panel to evaluate strengths and weaknesses in current molecular targeting in oncology. Through this analysis, we have identified patient indications, molecular aberrations, and targeted therapy classes that have strong or weak representation in clinical trials.
conclusionsHere, we describe the development and disseminate system methods for associating patient genomic sequence data with clinically relevant information, facilitating interpretation and providing a mechanism for informing therapeutic decision-making. Additionally, through customized queries, we have the capability to rapidly analyze the landscape of targeted therapies in clinical trials, enabling a unique view into current therapeutic availability in oncology.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.