ReviewEMBO molecular medicine2017
Genetically engineered mouse models in oncology research and cancer medicine.
Review in EMBO molecular medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 283 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
283 citing papers in PubMed, 3 syntheses or guidelines pooled it, 482 citations in OpenAlex.
- Bibliometric analysis of genetically engineered bacteria in tumor therapy.Frontiers in microbiology · 2026Pooled it
- Meningioma animal models: a systematic review and meta-analysis.Journal of translational medicine · 2023Pooled it
- Preclinical efficacy of oncolytic VSV-IFNβ in treating cancer: A systematic review.Frontiers in immunology · 2023Pooled it
- Review
- A xeno-free human iPSC-derived prostate organoid platform for multilineage differentiation and genetic manipulation.Cell reports methods · 2026Article
- New approach methodologies (NAMs) for preclinical and translational evaluation of mRNA-lipid nanoparticle (LNP) therapeutics.Journal of controlled release : official journal of the Controlled Release Society · 2026Review
- Decoding and Overcoming Temozolomide Resistance Through CRISPR/Cas Technologies.Molecular diagnosis & therapy · 2026Review
- Engineering cuproptosis with nanomedicine: Design, combination therapy, and translation in cancer.Materials today. Bio · 2026Review
- Secreted luciferases as a minimally invasive 3R-compliant tool for accurate monitoring of tumor burden.Nature protocols · 2026Review
- Runx1 and Runx2 act in concert to suppress Wnt/β-catenin-driven mammary tumourigenesis.British journal of cancer · 2026Article
- Bridging In Vitro and Murine Breast Cancer Models: Advanced Imaging Across Multiscale Experimental Platforms.Cancers · 2026Review
- Targeting the cancer metabolism-immunity interface: update and perspectives.Experimental hematology & oncology · 2026Review
- Humanized immune system animal models and their recent applications.Animal models and experimental medicine · 2026Review
- Review
- Immune-driven stromal inflammation in pancreatic cancer within a microfluidic platform.Biofabrication · 2026Article
- Mapping prostate cancer pathobiology: A review of genetically engineered mouse models (GEMMs).Gene · 2026Review
- Experimental models in immuno-oncology and their translational impact.Discover oncology · 2026Review
- Generation of a stable mouse endometrial tumor-derived cell line using conditional reprogramming.Biological research · 2026Article
- Modeling blood-brain barrier-glioblastoma interactions: implications for chemoresistance and therapeutic targeting.Fluids and barriers of the CNS · 2026Review
- Pancreatic cancer.Nature reviews. Disease primers · 2026Review
223 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 at 1 institution in 1 country.
Funding
Abstract
Genetically engineered mouse models (GEMMs) have contributed significantly to the field of cancer research. In contrast to cancer cell inoculation models, GEMMs develop de novo tumors in a natural immune-proficient microenvironment. Tumors arising in advanced GEMMs closely mimic the histopathological and molecular features of their human counterparts, display genetic heterogeneity, and are able to spontaneously progress toward metastatic disease. As such, GEMMs are generally superior to cancer cell inoculation models, which show no or limited heterogeneity and are often metastatic from the start. Given that GEMMs capture both tumor cell-intrinsic and cell-extrinsic factors that drive de novo tumor initiation and progression toward metastatic disease, these models are indispensable for preclinical research. GEMMs have successfully been used to validate candidate cancer genes and drug targets, assess therapy efficacy, dissect the impact of the tumor microenvironment, and evaluate mechanisms of drug resistance. In vivo validation of candidate cancer genes and therapeutic targets is further accelerated by recent advances in genetic engineering that enable fast-track generation and fine-tuning of GEMMs to more closely resemble human patients. In addition, aligning preclinical tumor intervention studies in advanced GEMMs with clinical studies in patients is expected to accelerate the development of novel therapeutic strategies and their translation into the clinic.
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.