Immune checkpoint inhibitors have been successful across several tumor types; however, their efficacy has been uncommon and unpredictable in glioblastomas (GBM), where <10% of patients show long-term responses. To understand the molecular determinants of immunotherapeutic response in GBM, we longitudinally profiled 66 patients, including 17 long-term responders, during standard therapy and after treatment with PD-1 inhibitors (nivolumab or pembrolizumab). Genomic and transcriptomic analysis revealed a significant enrichment of PTEN mutations associated with immunosuppressive expression signatures in non-responders, and an enrichment of MAPK pathway alterations (PTPN11, BRAF) in responders. Responsive tumors were also associated with branched patterns of evolution from the elimination of neoepitopes, as well as differences in T cell clonal diversity and tumor microenvironment profiles. Our study shows that clinical response to anti-PD-1 immunotherapy in GBM is associated with specific molecular alterations, immune expression signatures, and immune infiltration that reflect the tumor’s clonal evolution during treatment.

Motivation The human leukocyte antigen (HLA) locus plays a critical role in tissue compatibility and regulates the host response to many diseases, including cancers and autoimmune di3orders. Recent improvements in the quality and accessibility of next-generation sequencing have made HLA typing from standard short-read data practical. However, this task remains challenging given the high level of polymorphism and homology between HLA genes. HLA typing from RNA sequencing is further complicated by post-transcriptional modifications and bias due to amplification. Results Here, we present arcasHLA: a fast and accurate in silico tool that infers HLA genotypes from RNA-sequencing data. Our tool outperforms established tools on the gold-standard benchmark dataset for HLA typing in terms of both accuracy and speed, with an accuracy rate of 100% at two-field resolution for Class I genes, and over 99.7% for Class II. Furthermore, we evaluate the performance of our tool on a new biological dataset of 447 single-end total RNA samples from nasopharyngeal swabs, and establish the applicability of arcasHLA in metatranscriptome studies. Availability and implementation arcasHLA is available at https://github.com/RabadanLab/arcasHLA. Supplementary information Supplementary data are available at Bioinformatics online.

Plasmablastic lymphoma (PBL) is an aggressive B-cell non-Hodgkin lymphoma associated with immunodeficiency in the context of human immunodeficiency virus (HIV) infection or iatrogenic immunosuppression. While a rare disease in general, the incidence is dramatically increased in regions of the world with high HIV prevalence. The molecular pathogenesis of this disease is poorly characterized. Here, we defined the genomic features of PBL in a cohort of 110 patients from South Africa (15 by whole-exome sequencing and 95 by deep targeted sequencing). We identified recurrent mutations in genes of the JAK-STAT signaling pathway, including STAT3 (42%), JAK1 (14%), and SOCS1 (10%), leading to its constitutive activation. Moreover, 24% of cases harbored gain-of-function mutations in RAS family members (NRAS and KRAS). Comparative analysis with other B-cell malignancies uncovered PBL-specific somatic mutations and transcriptional programs. We also found recurrent copy number gains encompassing the CD44 gene (37%), which encodes for a cell surface receptor involved in lymphocyte activation and homing, and was found expressed at high levels in all tested cases, independent of genetic alterations. These findings have implications for the understanding of the pathogenesis of this disease and the development of personalized medicine approaches. SIGNIfICANCe: Plasmablastic lymphoma is a poorly studied and extremely aggressive tumor. Here we define the genomic landscape of this lymphoma in HIV-positive individuals from South Africa and identify pervasive mutations in JAK-STAT3 and RAS-MAPK signaling pathways. These data offer a genomic framework for the design of improved treatment strategies targeting these circuits.

Background Respiratory viral infections are a major cause of morbidity and mortality worldwide. However, their characterization is incomplete because prevalence estimates are based on syndromic surveillance data. Here, we address this shortcoming through the analysis of infection rates among individuals tested regularly for respiratory viral infections, irrespective of their symptoms. Methods We carried out longitudinal sampling and analysis among 214 individuals enrolled at multiple New York City locations from fall 2016 to spring 2018. We combined personal information with weekly nasal swab collection to investigate the prevalence of 18 respiratory viruses among different age groups and to assess risk factors associated with infection susceptibility. Results 17.5% of samples were positive for respiratory viruses. Some viruses circulated predominantly during winter, whereas others were found year round. Rhinovirus and coronavirus were most frequently detected. Children registered the highest positivity rates, and adults with daily contacts with children experienced significantly more infections than their counterparts without children. Conclusion Respiratory viral infections are widespread among the general population with the majority of individuals presenting multiple infections per year. The observations identify children as the principal source of respiratory infections. These findings motivate further active surveillance and analysis of differences in pathogenicity among respiratory viruses.

Respiratory viral infections are a leading cause of disease worldwide. A variety of respiratory viruses produce infections in humans with effects ranging from asymptomatic to life-treathening. Standard surveillance systems typically only target severe infections (ED outpatients, hospitalisations, deaths) and fail to track asymptomatic or mild infections. Here we performed a large-scale community study across multiple age groups to assess the pathogenicity of 18 respiratory viruses. We enrolled 214 individuals at multiple New York City locations and tested weekly for respiratory viral pathogens, irrespective of symptom status, from fall 2016 to spring 2018. We combined these test results with participant-provided daily records of cold and flu symptoms and used this information to characterise symptom severity by virus and age category. Asymptomatic infection rates exceeded 70% for most viruses, excepting influenza and human metapneumovirus, which produced significantly more severe outcomes. Symptoms were negatively associated with infection frequency, with children displaying the lowest score among age groups. Upper respiratory manifestations were most common for all viruses, whereas systemic effects were less typical. These findings indicate a high burden of asymptomatic respiratory virus infection exists in the general population.

Respiratory viruses are common in human populations, causing significant levels of morbidity. Understanding the distribution of these viruses is critical for designing control methods. However, most data available are from medical records and thus predominantly represent symptomatic infections. Estimates for asymptomatic prevalence are sparse and span a broad range. In this study, we aimed to measure more precisely the proportion of infections that are asymptomatic in a general, ambulatory adult population. We recruited participants from a New York City tourist attraction and administered nasal swabs, testing them for adenovirus, coronavirus, human metapneumovirus, rhinovirus, influenza virus, respiratory syncytial virus, and parainfluenza virus. At recruitment, participants completed surveys on demographics and symptomology. Analysis of these data indicated that over 6% of participants tested positive for shedding of respiratory virus. While participants who tested positive were more likely to report symptoms than those who did not, over half of participants who tested positive were asymptomatic.

The recent outbreak of a new coronavirus (SARS-CoV-2) in Wuhan, China, underscores the need for understanding the evolutionary processes that drive the emergence and adaptation of zoonotic viruses in humans. Here, we show that recombination in betacoronaviruses, including human-infecting viruses like SARS-CoV and MERS-CoV, frequently encompasses the Receptor Binding Domain (RBD) in the Spike gene. We find that this common process likely led to a recombination event at least 11 years ago in an ancestor of the SARS-CoV-2 involving the RBD. As a result of this recombination event, SARS-CoV and SARS-CoV-2 share a similar genotype in RBD, including two insertions (positions 432-436 and 460-472), and alleles 427N and 436Y. Both 427N and 436Y belong to a helix that interacts with the human ACE2 receptor. Ancestral state analyses revealed that SARS-CoV-2 differentiated from its most recent common ancestor with RaTG13 by accumulating a significant number of amino acid changes in the RBD. In sum, we propose a two-hit scenario in the emergence of the SARS-CoV-2 virus whereby the SARS-CoV-2 ancestors in bats first acquired genetic characteristics of SARS-CoV by incorporation of a SARS-like RBD through recombination before 2009, and subsequently, the lineage that led to SARS-CoV-2 accumulated further, unique changes specifically in the RBD.

Fifty percent of diffuse large B cell lymphoma (DLBCL) cases lack cell-surface expression of the class I major histocompatibility complex (MHC-I), thus escaping recognition by cytotoxic T cells. Here we show that, across B cell lymphomas, loss of MHC-I, but not MHC-II, is preferentially restricted to DLBCL. To identify the involved mechanisms, we performed whole exome and targeted HLA deep-sequencing in 74 DLBCL samples, and found somatic inactivation of B2M and the HLA-I loci in 80% (34 of 42) of MHC-INEG tumors. Furthermore, 70% (22 of 32) of MHC-IPOS DLBCLs harbored monoallelic HLA-I genetic alterations (MHC-IPOS/mono), indicating allele-specific inactivation. MHC-INEG and MHC-IPOS/mono cases harbored significantly higher mutational burden and inferred neoantigen load, suggesting potential coselection of HLA-I loss and sustained neoantigen production. Notably, the analysis of >500,000 individuals across different cancer types revealed common germline HLA-I homozygosity, preferentially in DLBCL. In mice, germinal-center B cells lacking HLA-I expression did not progress to lymphoma and were counterselected in the context of oncogene-driven lymphomagenesis, suggesting that additional events are needed to license immune evasion. These results suggest a multistep process of HLA-I loss in DLBCL development including both germline and somatic events, and have direct implications for the pathogenesis and immunotherapeutic targeting of this disease.