ReviewMolecular cancer research : MCR2016
Tumor-Derived Cell Lines as Molecular Models of Cancer Pharmacogenomics.
Review in Molecular cancer research : MCR, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05177432 (Quadratic Phenotypic Optimisation Platform), which is not on this map. Cited by 164 papers, 2 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.
Quadratic Phenotypic Optimisation Platform (QPOP) Utilisation to Enhance Selection of Patient Therapy Through Patient Derived Organoids in Breast Cancer
Who cites it
164 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- An integrated landscape of protein expression in human cancer.Scientific data · 2021Pooled it
- Tissue specificity of in vitro drug sensitivity.Journal of the American Medical Informatics Association : JAMIA · 2018Pooled it
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- Study of Cytotoxicity of Pyrrolo[3,4-International journal of molecular sciences · 2026Article
- Deep Unsupervised Domain Adaptation for Translating Cancer Dependency Maps From Cell Lines to Breast Cancer Tumor Genomics.Genetic epidemiology · 2026Article
- Drug response profile-based machine learning enables strategic cell line and compound selection for drug development.Bioinformatics (Oxford, England) · 2026Article
- Multi-omics evaluation of cell lines as models for metastatic prostate cancer.Communications biology · 2026Article
- Unraveling the Enigma of Melanoma Brain Metastasis: New Molecular Insights and Therapeutic Directions.International journal of molecular sciences · 2026Review
- Mechanistic and preclinical evaluation of SIRT3 as a therapeutic target in melanoma.Journal of dermato-oncology · 2026Article
- A Roadmap for the Future of Systems Biology in Cancer Research.Cancer research · 2025Review
- Challenges and opportunities for oncology drug repurposing informed by synthetic lethality.NPJ systems biology and applications · 2025Article
- Current State-of-the-Art Animal Models of Pediatric Brain Tumors.Brain sciences · 2025Review
- Dual-Dynamic Covalently Cross-Linked Polyglycerol Hydrogels for Tumor Spheroid Culture.Biomacromolecules · 2025Article
- Advances and challenges in human 3D solid tumor models.Advanced functional materials · 2025Article
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- Celebrating World Cancer Day: Innovative Biological Approaches to Cancer and their Alignment with Sustainable Development Goals (SDGs).Biological procedures online · 2025Article
- Establishment and characterization of NCC-SFT1-C1: a novel patient-derived cell line of solitary fibrous tumor.Human cell · 2025Article
104 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
4 authors.
Funding
Abstract
Compared with normal cells, tumor cells have undergone an array of genetic and epigenetic alterations. Often, these changes underlie cancer development, progression, and drug resistance, so the utility of model systems rests on their ability to recapitulate the genomic aberrations observed in primary tumors. Tumor-derived cell lines have long been used to study the underlying biologic processes in cancer, as well as screening platforms for discovering and evaluating the efficacy of anticancer therapeutics. Multiple -omic measurements across more than a thousand cancer cell lines have been produced following advances in high-throughput technologies and multigroup collaborative projects. These data complement the large, international cancer genomic sequencing efforts to characterize patient tumors, such as The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC). Given the scope and scale of data that have been generated, researchers are now in a position to evaluate the similarities and differences that exist in genomic features between cell lines and patient samples. As pharmacogenomics models, cell lines offer the advantages of being easily grown, relatively inexpensive, and amenable to high-throughput testing of therapeutic agents. Data generated from cell lines can then be used to link cellular drug response to genomic features, where the ultimate goal is to build predictive signatures of patient outcome. This review highlights the recent work that has compared -omic profiles of cell lines with primary tumors, and discusses the advantages and disadvantages of cancer cell lines as pharmacogenomic models of anticancer therapies.
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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.