ReviewYonsei medical journal2015
Cancer Cell Line Panels Empower Genomics-Based Discovery of Precision Cancer Medicine.
Review in Yonsei medical journal, 2015. 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.
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Who cites it
15 citing papers in PubMed.
- Predicting gene essentiality and drug response from preclinical perturbation screens with layered ensemble of autoencoders and predictors.Scientific reports · 2026Article
- Machine learning-based multi-omic analysis identifies CEP55, DLGAP5, and EZH2 as regulated cell death biomarkers linked to immunotherapy resistance in hepatocellular carcinoma.Naunyn-Schmiedeberg's archives of pharmacology · 2026Article
- Review
- Intraline genomic heterogeneity of the triple-negative breast cancer MDA-MB-231-luc-GFP cell line.Computational and structural biotechnology journal · 2025Article
- HeLa cell segmentation using digital image processing.Heliyon · 2024Article
- Creation of an Isogenic H/N/KRAS-Less Mouse Embryonic Fibroblast Cell Line Panel Derived from a Size-Sorted Diploid Clone.Methods in molecular biology (Clifton, N.J.) · 2024Article
- The challenge of making the right choice: patient avatars in the era of cancer immunotherapies.Frontiers in immunology · 2023Article
- Article
- Improving the odds of success in antitumoral drug development using scoring approaches towards heterocyclic scaffolds.Oncology reports · 2020Article
- Conditional reprogramming: Modeling urological cancer and translation to clinics.Clinical and translational medicine · 2020Review
- Genetic Ancestry Analysis Reveals Misclassification of Commonly Used Cancer Cell Lines.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2019Article
- CLC-Pred: A freely available web-service for in silico prediction of human cell line cytotoxicity for drug-like compounds.PloS one · 2018Article
- Article
- Oxidative stress under ambient and physiological oxygen tension in tissue culture.Current pharmacology reports · 2016Article
- Anti-Proliferative and Apoptotic Activities of Müllerian Inhibiting Substance Combined with Calcitriol in Ovarian Cancer Cell Lines.Yonsei medical journal · 2016Article
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
Since the first human cancer cell line, HeLa, was established in the early 1950s, there has been a steady increase in the number and tumor type of available cancer cell line models. Cancer cell lines have made significant contributions to the development of various chemotherapeutic agents. Recent advances in multi-omics technologies have facilitated detailed characterizations of the genomic, transcriptomic, proteomic, and epigenomic profiles of these cancer cell lines. An increasing number of studies employ the power of a cancer cell line panel to provide predictive biomarkers for targeted and cytotoxic agents, including those that are already used in clinical practice. Different types of statistical and machine learning algorithms have been developed to analyze the large-scale data sets that have been produced. However, much work remains to address the discrepancies in drug assay results from different platforms and the frequent failures to translate discoveries from cell line models to the clinic. Nevertheless, continuous expansion of cancer cell line panels should provide unprecedented opportunities to identify new candidate targeted therapies, particularly for the so-called "dark matter" group of cancers, for which pharmacologically tractable driver mutations have not been identified.
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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.