Most of our most common and difficult-to-cure diseases — cancer, diabetes, neurological disorders — involve many genes at the same time. So when working with gene networks, it can be hugely valuable to manipulate multiple genes within a network or pathway at the same time.
In his lab, genetic engineer Molecular marvelsAlbert Cheng, Ph.D., is taking the key attributes of CRISPR/Cas and making it more versatile. Albert Cheng is making genome editing technology more useful and versatile for researchers, so scientists around the world will be able to learn much more about the genome dynamics and gene networks at play in complex diseases.
The human genome folds itself in coils and loops, and the 3D genomics laboratory at JAX is a leader in the discovery of just how important that three-dimensional organization is to health and disease.
Researchers aim to fast-track research in all human disease, including cancer and epilepsy, by developing advanced genome technologies that have been eagerly adopted by the worldwide scientific community. These tools cut through the complexity of genomic data and are providing brand-new insights into how variations in the genome may lead to disease.
In patient-derived tumor xenograft (PDX) clinical trials, tumor models are created using fragments of a patient’s tumor that can be grown in mice to supply test tissue that can be used for research.
These xenografts are powerful models for assessing the drug efficacy of anti-cancer agents and understanding the molecular mechanisms of drug resistance. To realize the potential of this breakthrough, researchers must address the challenges with standardizing the processes and sharing the PDX specimens and data.
To meet this challenge, JAX computational biologist Jeff Chuang is on the front lines of big dataComputational biologist Jeffrey Chuang applies the power of big data to big problems in biology — from how cancer cells evolve to how computational tools and knowledge can be broadly shared.Jeffrey Chuang is building a data platform to coordinate large-scale testing for preclinical therapeutic cancer drugs in PDX trials. The project is using innovative cloud computing and bioinformatic approaches to organize the analysis of new PDX studies being led by scientists at multiple institutes.