Human paraneoplastic antigen Ma2 (PNMA2) forms icosahedral capsids that can be engineered for mRNA delivery.

A number of endogenous genes in the human genome encode retroviral gag-like proteins, which were domesticated from ancient retroelements. The paraneoplastic Ma antigen (PNMA) family members encode a gag-like capsid domain, but their ability to assemble as capsids and traffic between cells remains mostly uncharacterized. Here, we systematically investigate human PNMA proteins and find that a number of PNMAs are secreted by human cells. We determine that PNMA2 forms icosahedral capsids efficiently but does not naturally encapsidate nucleic acids. We resolve the cryoelectron microscopy (cryo-EM) structure of PNMA2 and leverage the structure to design engineered PNMA2 (ePNMA2) particles with RNA packaging abilities. Recombinantly purified ePNMA2 proteins package mRNA molecules into icosahedral capsids and can function as delivery vehicles in mammalian cell lines, demonstrating the potential for engineered endogenous capsids as a nucleic acid therapy delivery modality.

Epitope spreading toward wild-type melanocyte-lineage antigens rescues suboptimal immune checkpoint blockade responses.

Although immune checkpoint inhibitors (ICIs), such as anti-programmed cell death protein-1 (PD-1), can deliver durable antitumor effects, most patients with cancer fail to respond. Recent studies suggest that ICI efficacy correlates with a higher load of tumor-specific neoantigens and development of vitiligo in patients with melanoma. Here, we report that patients with low melanoma neoantigen burdens who responded to ICI had tumors with higher expression of pigmentation-related genes. Moreover, expansion of peripheral blood CD8+ T cell populations specific for melanocyte antigens was observed only in patients who responded to anti-PD-1 therapy, suggesting that ICI can promote breakdown of tolerance toward tumor-lineage self-antigens. In a mouse model of poorly immunogenic melanomas, spreading of epitope recognition toward wild-type melanocyte antigens was associated with markedly improved anti-PD-1 efficacy in two independent approaches: introduction of neoantigens by ultraviolet (UV) B radiation mutagenesis or the therapeutic combination of ablative fractional photothermolysis plus imiquimod. Complete responses against UV mutation-bearing tumors after anti-PD-1 resulted in protection from subsequent engraftment of melanomas lacking any shared neoantigens, as well as pancreatic adenocarcinomas forcibly overexpressing melanocyte-lineage antigens. Our data demonstrate that somatic mutations are sufficient to provoke strong antitumor responses after checkpoint blockade, but long-term responses are not restricted to these putative neoantigens. Epitope spreading toward T cell recognition of wild-type tumor-lineage self-antigens represents a common pathway for successful response to ICI, which can be evoked in neoantigen-deficient tumors by combination therapy with ablative fractional photothermolysis and imiquimod.

Population-scale longitudinal mapping of COVID-19 symptoms, behaviour and testing.

Despite the widespread implementation of public health measures, coronavirus disease 2019 (COVID-19) continues to spread in the United States. To facilitate an agile response to the pandemic, we developed How We Feel, a web and mobile application that collects longitudinal self-reported survey responses on health, behaviour and demographics. Here, we report results from over 500,000 users in the United States from 2 April 2020 to 12 May 2020. We show that self-reported surveys can be used to build predictive models to identify likely COVID-19-positive individuals. We find evidence among our users for asymptomatic or presymptomatic presentation; show a variety of exposure, occupational and demographic risk factors for COVID-19 beyond symptoms; reveal factors for which users have been SARS-CoV-2 PCR tested; and highlight the temporal dynamics of symptoms and self-isolation behaviour. These results highlight the utility of collecting a diverse set of symptomatic, demographic, exposure and behavioural self-reported data to fight the COVID-19 pandemic.

Population-scale Longitudinal Mapping of COVID-19 Symptoms, Behavior, and Testing Identifies Contributors to Continued Disease Spread in the United States.

Despite social distancing and shelter-in-place policies, COVID-19 continues to spread in the United States. A lack of timely information about factors influencing COVID-19 spread and testing has hampered agile responses to the pandemic. We developed How We Feel, an extensible web and mobile application that aggregates self-reported survey responses, to fill gaps in the collection of COVID-19-related data. How We Feel collects longitudinal and geographically localized information on users' health, behavior, and demographics. Here we report results from over 500,000 users in the United States from April 2, 2020 to May 12, 2020. We show that self- reported surveys can be used to build predictive models of COVID-19 test results, which may aid in identification of likely COVID-19 positive individuals. We find evidence among our users for asymptomatic or presymptomatic presentation, as well as for household and community exposure, occupation, and demographics being strong risk factors for COVID-19. We further reveal factors for which users have been SARS-CoV-2 PCR tested, as well as the temporal dynamics of self- reported symptoms and self-isolation behavior in positive and negative users. These results highlight the utility of collecting a diverse set of symptomatic, demographic, and behavioral self- reported data to fight the COVID-19 pandemic.