The structure of a cancer drug resistance factor, cataloging non-canonical proteins, family history helps polygenic scoring, and more
Research Roundup: July 18, 2022
Welcome to the July 18, 2022 installment of Research Roundup, a recurring snapshot of recent studies published by scientists at the Broad Institute and their collaborators.
Solving the structure of a cancer-enabling protein
Some of the most infamous cancer drivers are mutations in RAS genes, which lead to tumor growth in about a quarter of all cancer patients. In 2019, Broad and Dana-Farber scientists discovered that a protein called SHOC2 enabled tumors to resist cancer drugs targeting RAS-mutated cancers. In Nature, Jason Kwon, Behnoush Hajian, Yuemin Bian, Lucy Young, director of protein science and structural biology at the Center for the Development of Therapeutics Christopher Lemke, institute member William Hahn and associate member Andrew Aguirre of the Cancer Program, and colleagues reveal the molecular structure of SHOC2 and two proteins it binds to, MRAS and PP1C. The structure of this three-protein complex suggests possible targets for drugs that can inhibit the RAS pathway and block cancer growth. Read more in a Broad news story and tweetorials from Kwon and Haijian.
Cataloging the dark matter of the human genome
Ribosome profiling (Ribo-seq) has helped researchers discover thousands of non-canonical open reading frames (Ribo-seq ORFs) — regions of protein-coding DNA found in parts of the genome traditionally labeled as noncoding. However, to date there has been no coordinated effort to incorporate ORFs in gene annotation projects. Now, an international team of collaborators including postdoctoral researcher and associated scientist John Prensner, Jonathan Mudge (EMBL-EBI), Jorge Ruiz-Orera (MDC), and Sebastiaan van Heesch (PMC) is working to generate a catalog of ORFs for the global research community. Read more about the motivations and challenges associated with their plans to incorporate Ribo-seq ORFs in reference databases in Nature Biotechnology, John’s tweetorial, coverage in Genetic Engineering and Biotechnology News, and a Broad Q&A.
Polygenic risk scores (PRS) perform poorly when applied to diverse populations, but incorporating family history of disease may improve disease risk predictions. Margaux Hujoel and associate member Alkes Price in the Program in Medical and Population Genetics and of the Harvard T.H. Chan School of Public Health explored methods for combining both PRS and family history (PRS-FH). They found that PRS trained using all British individuals poorly predicted risk for three well-powered diseases (type 2 diabetes, hypertension, and depression) in non-British Europeans, South Asians, and Africans. PRS-FH more accurately predicted risk in those groups, representing a large improvement for Europeans and a massive improvement in Africans. Read more in Cell Genomics and GenomeWeb.
Getting to the heart of gene-environment interactions
A more precise, quantitative picture of how environment (lifestyle, demography, etc.) and genetics interact could pave the way for better preventive measures, diagnostics, and treatments for a host of common, complex diseases. In Nature Communications, Kenny Westerman and Joanne Cole of the Metabolism Program and colleagues describe an approach combining variance-quantitative trait loci (vQTLs) analysis with an exposome-wide interaction study to explore gene-environment interactions affecting 20 cardiometabolic blood biomarkers. Using UK Biobank data, they identify more than 800 gene-environment interactions at 136 vQTLs, findings that could support the development of precision medicine approaches for cardiometabolic health. Learn more in a tweetorial by Westerman.
Bypassing neuroblastoma drug resistance
Neuroblastomas are the most common solid tumor outside the brain in children, causing about 10 percent of pediatric cancer deaths. Immunotherapeutic antibodies that target GD2 — an immune system regulatory protein — have shown promise in treating children with high-risk neuroblastoma, but many patients develop resistance to the medication and relapse. Nathanial Mabe, institute member Kimberly Stegmaier of the Cancer Program, and colleagues found a specific cell state that downregulates GD2 in neuroblastoma patients, enabling resistance to GD2-binding antibodies. They found that treatment with EZH2 protein inhibitors reprogrammed neuroblastoma cells to express more GD2, suggesting a therapeutic approach that circumvents GD2 antibody resistance. Read more in Nature Cancer.