ReviewSeminars in oncology2015
Genetic Testing and Tissue Banking for Personalized Oncology: Analytical and Institutional Factors.
Review in Seminars in oncology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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
6 citing papers in PubMed, 13 citations in OpenAlex.
- Single-Cell Transcriptomics Sheds Light on Tumor Evolution: Perspectives from City of Hope's Clinical Trial Teams.Journal of clinical medicine · 2024Article
- Unveiling the genetic and epigenetic landscape of colorectal cancer: new insights into pathogenic pathways.Medical oncology (Northwood, London, England) · 2023Review
- Precision Oncology Comes of Age: Tumor-Agnostic Approaches.Journal of the advanced practitioner in oncology · 2020Article
- Genetic Research Using Archival Tissue: Ethical, Social, and Legal Considerations in the United Arab Emirates.Asian bioethics review · 2018Article
- In vitro patient-derived 3D mesothelioma tumor organoids facilitate patient-centric therapeutic screening.Scientific reports · 2018Article
- Organoid-on-a-chip and body-on-a-chip systems for drug screening and disease modeling.Drug discovery today · 2016Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 3 institutions in 1 country.
Funding
Abstract
Personalized oncology, or more aptly precision oncogenomics, refers to the identification and implementation of clinically actionable targets tailored to an individual patient's cancer genomic information. Banking of human tissue and other biospecimens establishes a framework to extract and collect the data essential to our understanding of disease pathogenesis and treatment. Cancer cooperative groups in the United States have led the way in establishing robust biospecimen collection mechanisms to facilitate translational research, and combined with technological advances in molecular testing, tissue banking has expanded from its traditional base in academic research and is assuming an increasingly pivotal role in directing the clinical care of cancer patients. Comprehensive screening of tumors by DNA sequencing and the ability to mine and interpret these large data sets from well-organized tissue banks have defined molecular subtypes of cancer. Such stratification by genomic criteria has revolutionized our perspectives on cancer diagnosis and treatment, offering insight into prognosis, progression, and susceptibility or resistance to known therapeutic agents. In turn, this has enabled clinicians to offer treatments tailored to patients that can greatly improve their chances of survival. Unique challenges and opportunities accompany the rapidly evolving interplay between tissue banking and genomic sequencing, and are the driving forces underlying the revolution in precision medicine. Molecular testing and precision medicine clinical trials are now becoming the major thrust behind the cooperative groups' clinical research efforts.
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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.