Evolution of chromosome-arm aberrations in breast cancer through genetic network rewiring.

The basal breast cancer subtype is enriched for triple-negative breast cancer (TNBC) and displays consistent large chromosomal deletions. Here, we characterize evolution and maintenance of chromosome 4p (chr4p) loss in basal breast cancer. Analysis of The Cancer Genome Atlas data shows recurrent deletion of chr4p in basal breast cancer. Phylogenetic analysis of a panel of 23 primary tumor/patient-derived xenograft basal breast cancers reveals early evolution of chr4p deletion. Mechanistically we show that chr4p loss is associated with enhanced proliferation. Gene function studies identify an unknown gene, C4orf19, within chr4p, which suppresses proliferation when overexpressed-a member of the PDCD10-GCKIII kinase module we name PGCKA1. Genome-wide pooled overexpression screens using a barcoded library of human open reading frames identify chromosomal regions, including chr4p, that suppress proliferation when overexpressed in a context-dependent manner, implicating network interactions. Together, these results shed light on the early emergence of complex aneuploid karyotypes involving chr4p and adaptive landscapes shaping breast cancer genomes.

Accelerated waning of immunity to SARS-CoV-2 mRNA vaccines in patients with immune-mediated inflammatory diseases.

BACKGROUNDLimited information is available on the impact of immunosuppressants on COVID-19 vaccination in patients with immune-mediated inflammatory diseases (IMID).METHODSThis observational cohort study examined the immunogenicity of SARS-CoV-2 mRNA vaccines in adult patients with inflammatory bowel disease, rheumatoid arthritis, ankylosing spondylitis, or psoriatic disease, with or without maintenance immunosuppressive therapies. Ab and T cell responses to SARS-CoV-2, including neutralization against SARS-CoV-2 variants, were determined before and after 1 and 2 vaccine doses.RESULTSWe prospectively followed 150 subjects, 26 healthy controls, 9 patients with IMID on no treatment, 44 on anti-TNF, 16 on anti-TNF with methotrexate/azathioprine (MTX/AZA), 10 on anti-IL-23, 28 on anti-IL-12/23, 9 on anti-IL-17, and 8 on MTX/AZA. Ab and T cell responses to SARS-CoV-2 were detected in all participants, increasing from dose 1 to dose 2 and declining 3 months later, with greater attrition in patients with IMID compared with healthy controls. Ab levels and neutralization efficacy against variants of concern were substantially lower in anti-TNF-treated patients than in healthy controls and were undetectable against Omicron by 3 months after dose 2.CONCLUSIONSOur findings support the need for a third dose of the mRNA vaccine and for continued monitoring of immunity in these patient groups.FUNDINGFunded by a donation from Juan and Stefania Speck and by Canadian Institutes of Health (CIHR)/COVID-Immunity Task Force (CITF) grants VR-1 172711 and VS1-175545 (to THW and ACG), CIHR FDN-143250 (to THW), GA2-177716 (to VC, ACG, and THW), and GA1-177703 (to ACG) and the CIHR rapid response network to SARS-CoV-2 variants, CoVaRR-Net (to ACG).

A simple protein-based surrogate neutralization assay for SARS-CoV-2.

Most of the patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) mount a humoral immune response to the virus within a few weeks of infection, but the duration of this response and how it correlates with clinical outcomes has not been completely characterized. Of particular importance is the identification of immune correlates of infection that would support public health decision-making on treatment approaches, vaccination strategies, and convalescent plasma therapy. While ELISA-based assays to detect and quantitate antibodies to SARS-CoV-2 in patient samples have been developed, the detection of neutralizing antibodies typically requires more demanding cell-based viral assays. Here, we present a safe and efficient protein-based assay for the detection of serum and plasma antibodies that block the interaction of the SARS-CoV-2 spike protein receptor binding domain (RBD) with its receptor, angiotensin-converting enzyme 2 (ACE2). The assay serves as a surrogate neutralization assay and is performed on the same platform and in parallel with an ELISA for the detection of antibodies against the RBD, enabling a direct comparison. The results obtained with our assay correlate with those of 2 viral-based assays, a plaque reduction neutralization test (PRNT) that uses live SARS-CoV-2 virus and a spike pseudotyped viral vector-based assay.

Getting to know the neighborhood: using proximity-dependent biotinylation to characterize protein complexes and map organelles.

The use of proximity-dependent biotinylation approaches combined with mass spectrometry (e.g. BioID and APEX) has revolutionized the study of protein-protein interactions and organellar proteomics. These powerful techniques are based on the fusion of an enzyme (e.g. a biotin ligase or peroxidase) to a 'bait' protein of interest, which is then expressed in a relevant biological setting. Addition of enzyme substrate enables covalent biotin labeling of proteins in the vicinity of the bait in vivo. These approaches thus allow for the capture and identification of 'neighborhood' proteins in the context of a living cell, and provide data that are complementary to more established techniques such as fractionation or affinity purification. As compared to standard affinity-based purification approaches, proximity-dependent biotinylation (PDB) can help to: first, identify interactions with and amongst membrane proteins, and other polypeptide classes that are less amenable to study by standard pulldown techniques; second, enrich for transient and/or low affinity interactions that are not readily captured using affinity purification approaches; third, avoid post-lysis artefacts associated with standard biochemical purification experiments and; fourth, provide deep insight into the organization of membrane-less organelles and other subcellular structures that cannot be easily isolated or purified. Given the increasing use of these techniques to answer a variety of different types of biological questions, it is important to understand how best to design PDB-MS experiments, what type of data they generate, and how to analyze and interpret the results.