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Purpose: Gene expression–based molecular subtypes of high-grade serous tubo-ovarian cancer (HGSOC), demonstrated across multiple studies, may provide improved stratification for molecularly targeted trials. However, evaluation of clinical utility has been hindered by nonstandardized methods, which are not applicable in a clinical setting. We sought to generate a clinical grade minimal gene set assay for classification of individual tumor specimens into HGSOC subtypes and confirm previously reported subtype-associated features. Experimental Design: Adopting two independent approaches, we derived and internally validated algorithms for subtype prediction using published gene expression data from 1,650 tumors. We applied resulting models to NanoString data on 3,829 HGSOCs from the Ovarian Tumor Tissue Analysis consortium. We further developed, confirmed, and validated a reduced, minimal gene set predictor, with methods suitable for a single-patient setting. Results: Gene expression data were used to derive the predictor of high-grade serous ovarian carcinoma molecular subtype (PrOTYPE) assay. We established a de facto standard as a consensus of two parallel approaches. PrOTYPE subtypes are significantly associated with age, stage, residual disease, tumor-infiltrating lymphocytes, and outcome. The locked-down clinical grade PrOTYPE test includes a model with 55 genes that predicted gene expression subtype with >95% accuracy that was maintained in all analytic and biological validations. Conclusions: We validated the PrOTYPE assay following the Institute of Medicine guidelines for the development of omics-based tests. This fully defined and locked-down clinical grade assay will enable trial design with molecular subtype stratification and allow for objective assessment of the predictive value of HGSOC molecular subtypes in precision medicine applications. See related commentary by McMullen et al., p. 5271

Curing HIV will require eliminating the reservoir of integrated, replication-competent proviruses that persist despite antiretroviral therapy (ART). Understanding the burden, genetic diversity and longevity of persisting proviruses in diverse individuals with HIV is critical to this goal, but these characteristics remain understudied in some groups. Among them are viremic controllers, individuals who naturally suppress HIV to low levels but for whom therapy is nevertheless recommended. We reconstructed within-host HIV evolutionary histories from longitudinal single-genome amplified viral sequences in four viremic controllers who eventually initiated ART, and used this information to characterize the age and diversity of proviruses persisting on therapy. We further leveraged these within-host proviral age distributions to estimate rates of proviral turnover prior to ART. This is an important yet understudied metric, since pre-ART proviral turnover dictates reservoir composition at ART initiation (and thereafter), which is when curative interventions, once developed, would be administered. Despite natural viremic control, all participants displayed significant within-host HIV evolution pre-therapy, where overall on-ART proviral burden and diversity broadly reflected the extent of viral replication and diversity pre-ART. Consistent with recent studies of non-controllers, the proviral pools of two participants were skewed towards sequences that integrated near ART initiation, suggesting dynamic proviral turnover during untreated infection. In contrast, proviruses recovered from the two other participants dated to time-points that were more evenly spread throughout infection, suggesting slow or negligible proviral decay following deposition. HIV cure strategies will need to overcome within-host proviral diversity, even in individuals who naturally controlled HIV replication before therapy.ImportanceHIV therapy is life-long because integrated, replication-competent viral copies persist within long-lived cells. To cure HIV, we need to understand when these viral reservoirs form, how large and genetically diverse they are, and how long they endure. Elite controllers, individuals who naturally suppress HIV to undetectable levels, are being intensely studied as models of HIV remission, but viremic controllers, individuals who naturally suppress HIV to low levels, remain understudied even though they too may hold valuable insights. We combined phylogenetics and mathematical modeling to reconstruct proviral seeding and decay from infection to therapy-mediated suppression in four viremic controllers. We recovered diverse proviruses persisting during therapy that broadly reflected HIV’s within-host evolutionary history, where the estimated half-lives of the persistent proviral pool during untreated infection ranged from

Humoral responses to COVID-19 vaccines in people living with HIV (PLWH) remain incompletely understood. We measured circulating antibodies against the receptor-binding domain (RBD) of the SARS-CoV-2 spike protein, ACE2 displacement and live viral neutralization activities one month following the first and second COVID-19 vaccine doses in 100 adult PLWH and 152 controls. All PLWH were receiving suppressive antiretroviral therapy, with median CD4+ T-cell counts of 710 (IQR 525-935) cells/mm3. Nadir CD4+ T-cell counts ranged as low as 3. After adjustment for sociodemographic, health and vaccine-related variables, HIV infection was significantly associated with 0.2 log10 lower anti-RBD antibody concentrations (p=0.03) and ∼11% lower ACE2 displacement activity (p=0.02), but not lower viral neutralization (p=0.1) after one vaccine dose. Following two doses however, HIV was no longer significantly associated with the magnitude of any response measured. Rather, older age, a higher burden of chronic health conditions, and having received two ChAdOx1 doses (versus a heterologous or dual mRNA vaccine regimen) were independently associated with lower responses. After two vaccine doses, no significant correlation was observed between the most recent or nadir CD4+ T-cell counts and vaccine responses in PLWH. These results suggest that PLWH with well-controlled viral loads on antiretroviral therapy and CD4+ T-cell counts in a healthy range will generally not require a third COVID-19 vaccine dose as part of their initial immunization series, though other factors such as older age, co-morbidities, vaccine regimen type, and durability of vaccine responses will influence when this group may benefit from additional doses. Further studies of PLWH who are not receiving antiretroviral treatment and/or who have low CD4+ T-cell counts are needed.

Quantitative viral load assays have transformed our understanding of – and ability to manage − viral diseases. They hold similar potential to advance COVID-19 control and prevention, but SARS-CoV-2 viral load tests are not yet widely available. SARS-CoV-2 molecular diagnostic tests, which typically employ real-time reverse transcriptase-polymerase chain reaction (RT-PCR), yield semi-quantitative results only. Reverse transcriptase droplet digital PCR (RT-ddPCR), a technology that partitions each reaction into 20,000 nanolitre-sized droplets prior to amplification, offers an attractive platform for SARS-CoV-2 RNA quantification. We evaluated eight primer/probe sets originally developed for real-time RT-PCR-based SARS-CoV-2 diagnostic tests for use in RT-ddPCR, and identified three (Charité-Berlin E-Sarbeco and Pasteur Institute IP2 and IP4) as the most efficient, precise and sensitive for RT-ddPCR-based SARS-CoV-2 RNA quantification. Analytical efficiency of the E-Sarbeco primer/probe set, for example, was ~83%, while assay precision, as measured by the coefficient of variation, was ~2% at 1000 input copies/reaction. Lower limits of quantification and detection for this primer/probe set were 18.6 and 4.4 input SARS-CoV-2 RNA copies/reaction, respectively. SARS-CoV-2 RNA viral loads in a convenience panel of 48 COVID-19-positive diagnostic specimens spanned a 6.2log10 range, confirming substantial viral load variation in vivo. We further calibrated RT-ddPCR-derived SARS-CoV-2 E gene copy numbers against cycle threshold (Ct) values from a commercial real-time RT-PCR diagnostic platform. The resulting log-linear relationship can be used to mathematically derive SARS-CoV-2 RNA copy numbers from Ct values, allowing the wealth of available diagnostic test data to be harnessed to address foundational questions in SARS-CoV-2 biology.

The HIV reservoir, which comprises diverse proviruses integrated into the genomes of infected, primarily CD4+ T cells, is the main barrier to developing an effective HIV cure. Our understanding of the genetics and dynamics of proviruses persisting within distinct CD4+ T cell subsets, however, remains incomplete. Using single-genome amplification, we characterized subgenomic proviral sequences (nef region) from naive, central memory, transitional memory, and effector memory CD4+ T cells from five HIV-infected individuals on long-term combination antiretroviral therapy (cART) and compared these to HIV RNA sequences isolated longitudinally from archived plasma collected prior to cART initiation, yielding HIV data sets spanning a median of 19.5 years (range, 10 to 20 years) per participant. We inferred a distribution of within-host phylogenies for each participant, from which we characterized proviral ages, phylogenetic diversity, and genetic compartmentalization between CD4+ T cell subsets. While three of five participants exhibited some degree of proviral compartmentalization between CD4+ T cell subsets, combined analyses revealed no evidence that any particular CD4+ T cell subset harbored the longest persisting, most genetically diverse, and/or most genetically distinctive HIV reservoir. In one participant, diverse proviruses archived within naive T cells were significantly younger than those in memory subsets, while for three other participants we observed no significant differences in proviral ages between subsets. In one participant, "old" proviruses were recovered from all subsets, and included one sequence, estimated to be 21.5 years old, that dominated (>93%) their effector memory subset. HIV eradication strategies will need to overcome within- and between-host genetic complexity of proviral landscapes, possibly via personalized approaches.IMPORTANCE The main barrier to HIV cure is the ability of a genetically diverse pool of proviruses, integrated into the genomes of infected CD4+ T cells, to persist despite long-term suppressive combination antiretroviral therapy (cART). CD4+ T cells, however, constitute a heterogeneous population due to their maturation across a developmental continuum, and the genetic "landscapes" of latent proviruses archived within them remains incompletely understood. We applied phylogenetic techniques, largely novel to HIV persistence research, to reconstruct within-host HIV evolutionary history and characterize proviral diversity in CD4+ T cell subsets in five individuals on long-term cART. Participants varied widely in terms of proviral burden, genetic diversity, and age distribution between CD4+ T cell subsets, revealing that proviral landscapes can differ between individuals and between infected cell types within an individual. Our findings expose each within-host latent reservoir as unique in its genetic complexity and support personalized strategies for HIV eradication.

The HIV accessory protein Nef downregulates the viral entry receptor CD4, the Human Leukocyte Antigen (HLA)-A and -B molecules, the Serine incorporator 5 (SERINC5) protein and other molecules from the infected cell surface, thereby promoting viral infectivity, replication and immune evasion. Theneflocus also represents one of the most genetically variable regions in the HIV genome, andnefsequences undergo substantial evolution within a single individual over the course of infection. Few studies however have simultaneously characterized the impact of within-hostnefsequence evolution on Nef protein function over prolonged timescales. Here, we isolated 50 unique Nef clones by single-genome amplification over an 11-year period from the plasma of an individual who was largely naïve to antiretroviral treatment during this time. Together, these clones harbored nonsynonymous substitutions at 13% ofnef’s codons. We assessed their ability to downregulate cell-surface CD4, HLA and SERINC5 and observed that all three Nef functions declined modestly over time, where the reductions in CD4 and HLA downregulation (an average of 0.6% and 2.0% per year, respectively) achieved statistical significance. The results from this case study support all three Nef activities as being important to maintain throughout untreated HIV infection, but nevertheless suggest that, despitenef’s mutational plasticity, within-host viral evolution can compromise Nef function, albeit modestly, over prolonged periods.

The HIV reservoir, which comprises diverse proviruses integrated into the genomes of infected, primarily CD4(+) T cells, is the main barrier to developing an effective HIV cure. Our understanding of the genetics and dynamics of proviruses persisting within distinct CD4(+) T cell subsets, however, remains incomplete. Using single-genome amplification, we characterized subgenomic proviral sequences (nef region) from naive, central memory, transitional memory, and effector memory CD4(+) T cells from five HIV-infected individuals on long-term combination antiretroviral therapy (cART) and compared these to HIV RNA sequences isolated longitudinally from archived plasma collected prior to cART initiation, yielding HIV data sets spanning a median of 19.5 years (range, 10 to 20 years) per participant. We inferred a distribution of within-host phylogenies for each participant, from which we characterized proviral ages, phylogenetic diversity, and genetic compartmentalization between CD4(+) T cell subsets. While three of five participants exhibited some degree of proviral compartmentalization between CD4(+) T cell subsets, combined analyses revealed no evidence that any particular CD4(+) T cell subset harbored the longest persisting, most genetically diverse, and/or most genetically distinctive HIV reservoir. In one participant, diverse proviruses archived within naive T cells were significantly younger than those in memory subsets, while for three other participants we observed no significant differences in proviral ages between subsets. In one participant, “old” proviruses were recovered from all subsets, and included one sequence, estimated to be 21.5 years old, that dominated (>93%) their effector memory subset. HIV eradication strategies will need to overcome within- and between-host genetic complexity of proviral landscapes, possibly via personalized approaches. IMPORTANCE The main barrier to HIV cure is the ability of a genetically diverse pool of proviruses, integrated into the genomes of infected CD4(+) T cells, to persist despite long-term suppressive combination antiretroviral therapy (cART). CD4(+) T cells, however, constitute a heterogeneous population due to their maturation across a developmental continuum, and the genetic “landscapes” of latent proviruses archived within them remains incompletely understood. We applied phylogenetic techniques, largely novel to HIV persistence research, to reconstruct within-host HIV evolutionary history and characterize proviral diversity in CD4(+) T cell subsets in five individuals on long-term cART. Participants varied widely in terms of proviral burden, genetic diversity, and age distribution between CD4(+) T cell subsets, revealing that proviral landscapes can differ between individuals and between infected cell types within an individual. Our findings expose each within-host latent reservoir as unique in its genetic complexity and support personalized strategies for HIV eradication.

The HIV accessory protein Nef modulates key immune evasion and pathogenic functions, and its encoding gene region exhibits high sequence diversity. Given the recent identification of early HIV-specific adaptive immune responses as novel correlates of HIV reservoir size, we hypothesized that viral factors that facilitate the evasion of such responses—namely, Nef genetic and functional diversity—might also influence reservoir establishment and/or persistence. We isolated baseline plasma HIV RNA-derived nef clones from 30 acute/early-infected individuals who participated in a clinical trial of early combination antiretroviral therapy (cART) (

OBJECTIVE: Timely initiation of combination antiretroviral therapy (ART) limits latent HIV reservoir size and should also limit reservoir genetic complexity. However, the relationship between these two factors remains unclear, particularly among HIV-infected youth. DESIGN: Retrospective analysis of replication-competent latent HIV clones serially isolated by limiting-dilution culture from resting CD4+ T-cell reservoirs from ART-suppressed, young adult participants of a historic phase I therapeutic vaccine trial (PACTG/IMPAACT-P1059). METHODS: Replication-competent latent HIV clones isolated from resting CD4+ T-cells of 4 perinatally- and 10 non-perinatally-infected young adults (average 22 versus 6 years uncontrolled infection, respectively) were sequenced in Pol and Nef. Within-host HIV sequence datasets were characterized with respect to their genetic diversity and inferred immune escape mutation burden. RESULTS: While participants were comparable in terms of sociodemographic and HIV sampling characteristics (e.g. on average, a mean 17 Pol sequences were recovered at 5 timepoints over up to 70 weeks) and the length of ART suppression at study entry (average 3 years), replication-competent HIV reservoir size, genetic diversity, immune escape mutation burden and variant complexity were significantly higher among the perinatally-infected participants who experienced longer durations of uncontrolled viremia. Nevertheless, viral sequences inferred to retain susceptibility to host cellular immune responses were detected in all participants, irrespective of uncontrolled viremia duration. CONCLUSIONS: HIV elimination in late-suppressed youth may be doubly challenged by larger and more genetically complex reservoirs. Strategies that integrate host and viral genetic complexity to achieve HIV remission or cure may merit consideration in such cases.

Background: Median overall survival (OS) for women with high-grade serous ovarian cancer (HGSOC) is similar to 4 years, yet survival varies widely between patients. There are no well-established, gene expression signatures associated with prognosis. The aim of this study was to develop a robust prognostic signature for OS in patients with HGSOC. Patients and methods: Expression of 513 genes, selected from a meta-analysis of 1455 tumours and other candidates, was measured using NanoString technology from formalin-fixed paraffin-embedded tumour tissue collected from 3769 women with HGSOC from multiple studies. Elastic net regularization for survival analysis was applied to develop a prognostic model for 5-year OS, trained on 2702 tumours from 15 studies and evaluated on an independent set of 1067 tumours from six studies. Results: Expression levels of 276 genes were associated with OS (false discovery rate < 0.05) in covariate-adjusted single-gene analyses. The top five genes were TAP1, ZFHX4, CXCL9, FBN1 and PTGER3 (P < 0.001). The best performing prognostic signature included 101 genes enriched in pathways with treatment implications. Each gain of one standard deviation in the gene expression score conferred a greater than twofold increase in risk of death [hazard ratio (HR) 2.35, 95% confidence interval (CI) 2.02-2.71; P < 0.001]. Median survival [HR (95% CI)] by gene expression score quintile was 9.5 (8.3 to -), 5.4 (4.6-7.0), 3.8 (3.3-4.6), 3.2 (2.9-3.7) and 2.3 (2.1-2.6) years. Conclusion: The OTTA-SPOT (Ovarian Tumor Tissue Analysis consortium - Stratified Prognosis of Ovarian Tumours) gene expression signature may improve risk stratification in clinical trials by identifying patients who are least likely to achieve 5-year survival. The identified novel genes associated with the outcome may also yield opportunities for the development of targeted therapeutic approaches.