ReviewNPJ precision oncology2017
Live-single-cell phenotypic cancer biomarkers-future role in precision oncology?
Review in NPJ precision oncology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
What it found
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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
15 citing papers in PubMed.
- Explainable radiomics based on association of histopathological cell density and multiparametric MR radiomic features for high-risk stratification of prostate cancer patients.Magma (New York, N.Y.) · 2025Article
- Liprin-α1 Expression in Tumor-Infiltrating Lymphocytes Associates with Improved Survival in Patients with HPV-Positive Oropharyngeal Squamous Cell Carcinoma.Head and neck pathology · 2023Article
- Review
- Recent Trends in Metal Nanoparticles Decorated 2D Materials for Electrochemical Biomarker Detection.Biosensors · 2023Review
- From imaging a single cell to implementing precision medicine: an exciting new era.Emerging topics in life sciences · 2021Article
- Quantitative Approach for Protein Analysis in Small Cell Ensembles by an Integrated Microfluidic Chip with MALDI Mass Spectrometry.Analytical chemistry · 2021Article
- Review
- Advances of single-cell genomics and epigenomics in human disease: where are we now?Mammalian genome : official journal of the International Mammalian Genome Society · 2020Review
- Quantitative scoring of epithelial and mesenchymal qualities of cancer cells using machine learning and quantitative phase imaging.Journal of biomedical optics · 2020Article
- Application of Artificial Intelligence/Machine Vision & Learning for the Development of a Live Single-cell Phenotypic Biomarker Test to Predict Prostate Cancer Tumor Aggressiveness.Reviews in urology · 2020Article
- Review
- Article
- Live-cell phenotypic-biomarker microfluidic assay for the risk stratification of cancer patients via machine learning.Nature biomedical engineering · 2018Article
- Potent effect of the MDM2 inhibitor AMG232 on suppression of glioblastoma stem cells.Cell death & disease · 2018Article
- What Is the Storage Effect, Why Should It Occur in Cancers, and How Can It Inform Cancer Therapy?Cancer control : journal of the Moffitt Cancer CenterArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The promise of precision and personalized medicine is rooted in accurate, highly sensitive, and specific disease biomarkers. This is particularly true for cancer-a disease characterized by marked tumor heterogeneity and diverse molecular signatures. Although thousands of biomarkers have been described, only a very small number have been successfully translated into clinical use. Undoubtedly, there is need for rapid, quantitative, and more cost effective biomarkers for tumor diagnosis and prognosis, to allow for better risk stratification and aid clinicians in making personalized treatment decisions. This is particularly true for cancers where specific biomarkers are either not available (e.g., renal cell carcinoma) or where current biomarkers tend to classify individuals into broad risk categories unable to accurately assess individual tumor aggressiveness and adverse pathology potential (e.g., prostate cancer), thereby leading to problems of over-diagnosis and over-treatment of indolent cancer and under-treatment of aggressive cancer. This perspective highlights an emerging class of cancer biomarkers-live-single-cell phenotypic biomarkers, as compared to genomic biomarkers, and their potential application for cancer diagnosis, risk-stratification, and prognosis.
Identifiers
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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.