ReviewDisease models & mechanisms2021
Engineering chromosome rearrangements in cancer.
Review in Disease models & mechanisms, 2021. 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, 10 citations in OpenAlex.
- Integrative analysis of SEC13: a prognostic predictor and immunotherapeutic target.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026Article
- Targeting fusion proteins in solid tumors: from oncogenic mechanisms to clinical interventions.Acta pharmacologica Sinica · 2026Review
- Bioinformatics Identification of SPAG5 as a Potential Prognostic Biomarker in Diffuse Large B-Cell Lymphoma.Journal of blood medicine · 2025Article
- Article
- How CRISPR Is Revolutionizing the Generation of New Models for Cancer Research.Cold Spring Harbor perspectives in medicine · 2024Review
- Fixed Allele Differences Associated With the Centromere Reveal Chromosome Morphology and Rearrangements in a Reptile (Varanus acanthurus BOULENGER).Molecular biology and evolution · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 2 institutions in 1 country.
Funding
Abstract
The identification of large chromosomal rearrangements in cancers has multiplied exponentially over the last decade. These complex and often rare genomic events have traditionally been challenging to study, in part owing to lack of tools that efficiently engineer disease-associated inversions, deletions and translocations in model systems. The emergence and refinement of genome editing technologies, such as CRISPR, have significantly expanded our ability to generate and interrogate chromosomal aberrations to better understand the networks that govern cancer growth. Here we review how existing technologies are employed to faithfully model cancer-associated chromosome rearrangements in the laboratory, with the ultimate goal of developing more accurate pre-clinical models of and therapeutic strategies for cancers driven by these genomic events.
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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.