Endogenous factors enhance HIV infection of tissue naive CD4 T cells by stimulating high molecular mass APOBEC3G complex formation

Human immunodeficiency virus (HIV) can infect resting CD4 T cells residing in lymphoid tissues but not those circulating in peripheral blood. The molecular mechanisms producing this difference remain unknown. We explored the potential role of the tissue microenvironment and its influence on the action of the antiviral factor APOBEC3G (A3G) in regulating permissivity to HIV infection. We found that endogenous IL-2 and -15 play a key role in rendering resident naive CD4 T cells susceptible to HIV infection. Infection of memory CD4 T cells also requires endogenous soluble factors, but not IL-2 or -15. A3G is found in a high molecular mass complex in HIV infection–permissive, tissue-resident naive CD4 T cells but resides in a low molecular mass form in nonpermissive, blood-derived naive CD4 T cells. Upon treatment with endogenous soluble factors, these cells become permissive for HIV infection, as low molecular mass A3G is induced to assemble into high molecular mass complexes. These findings suggest that in lymphoid tissues, endogenous soluble factors, likely including IL-2 and -15 and others, stimulate the formation of high molecular mass A3G complexes in tissue-resident naive CD4 T cells, thereby relieving the potent postentry restriction block for HIV infection conferred by low molecular mass A3G

Challenges in identifying cancer genes by analysis of exome sequencing data.

Massively parallel sequencing has permitted an unprecedented examination of the cancer exome, leading to predictions that all genes important to cancer will soon be identified by genetic analysis of tumours. To examine this potential, here we evaluate the ability of state-of-the-art sequence analysis methods to specifically recover known cancer genes. While some cancer genes are identified by analysis of recurrence, spatial clustering or predicted impact of somatic mutations, many remain undetected due to lack of power to discriminate driver mutations from the background mutational load (13-60% recall of cancer genes impacted by somatic single-nucleotide variants, depending on the method). Cancer genes not detected by mutation recurrence also tend to be missed by all types of exome analysis. Nonetheless, these genes are implicated by other experiments such as functional genetic screens and expression profiling. These challenges are only partially addressed by increasing sample size and will likely hold even as greater numbers of tumours are analysed

Epigenetic aging signatures in mice livers are slowed by dwarfism, calorie restriction and rapamycin treatment

Background: Global but predictable changes impact the DNA methylome as we age, acting as a type of molecular clock. This clock can be hastened by conditions that decrease lifespan, raising the question of whether it can also be slowed, for example, by conditions that increase lifespan. Mice are particularly appealing organisms for studies of mammalian aging; however, epigenetic clocks have thus far been formulated only in humans. Results: We first examined whether mice and humans experience similar patterns of change in the methylome with age. We found moderate conservation of CpG sites for which methylation is altered with age, with both species showing an increase in methylome disorder during aging. Based on this analysis, we formulated an epigenetic-aging model in mice using the liver methylomes of 107 mice from 0.2 to 26.0 months old. To examine whether epigenetic aging signatures are slowed by longevity-promoting interventions, we analyzed 28 additional methylomes from mice subjected to lifespan-extending conditions, including Prop1df/df dwarfism, calorie restriction or dietary rapamycin. We found that mice treated with these lifespan-extending interventions were significantly younger in epigenetic age than their untreated, wild-type age-matched controls. Conclusions: This study shows that lifespan-extending conditions can slow molecular changes associated with an epigenetic clock in mice livers

A global transcriptional network connecting noncoding mutations to changes in tumor gene expression.

Although cancer genomes are replete with noncoding mutations, the effects of these mutations remain poorly characterized. Here we perform an integrative analysis of 930 tumor whole genomes and matched transcriptomes, identifying a network of 193 noncoding loci in which mutations disrupt target gene expression. These 'somatic eQTLs' (expression quantitative trait loci) are frequently mutated in specific cancer tissues, and the majority can be validated in an independent cohort of 3,382 tumors. Among these, we find that the effects of noncoding mutations on DAAM1, MTG2 and HYI transcription are recapitulated in multiple cancer cell lines and that increasing DAAM1 expression leads to invasive cell migration. Collectively, the noncoding loci converge on a set of core pathways, permitting a classification of tumors into pathway-based subtypes. The somatic eQTL network is disrupted in 88% of tumors, suggesting widespread impact of noncoding mutations in cancer

In Vitro Derived Dendritic Cells trans-Infect CD4 T Cells Primarily with Surface-Bound HIV-1 Virions

In the prevailing model of HIV-1 trans-infection, dendritic cells (DCs) capture and internalize intact virions and transfer these virions to interacting T cells at the virological synapse. Here, we show that HIV-1 virions transmitted in trans from in vitro derived DCs to T cells principally originate from the surface of DCs. Selective neutralization of surface-bound virions abrogated trans-infection by monocyte-derived DCs and CD34-derived Langerhans cells. Under conditions mimicking antigen recognition by the interacting T cells, most transferred virions still derived from the cell surface, although a few were transferred from an internal compartment. Our findings suggest that attachment inhibitors could neutralize trans-infection of T cells by DCs in vivo

Methylome-wide Analysis of Chronic HIV Infection Reveals Five-Year Increase in Biological Age and Epigenetic Targeting of HLA

HIV-infected individuals are living longer on antiretro-viral therapy, but many patients display signs that in some ways resemble premature aging. To investigate and quantify the impact of chronic HIV infection on aging, we report a global analysis of the whole-blood DNA methylomes of 137 HIV+ individuals under sustained therapy along with 44 matched HIV- individuals. First,we develop and validate epigenetic models of aging that are independent of blood cell composition. Using these models, we find that both chronic and recent HIV infection lead to an average aging advancement of 4.9 years, increasing expected mortality risk by 19%. In addition, sustained infection results in global deregulation of the methylome across \u3e80,000 CpGs and specific hypomethylation of the region encoding the human leukocyte antigen locus (HLA).We find that decreased HLA methylation is predictive of lower CD4/CD8T cell ratio, linking molecular aging, epigenetic regulation, and disease progression

Multiple Routes to Oncogenesis Are Promoted by the Human Papillomavirus-Host Protein Network.

We have mapped a global network of virus-host protein interactions by purification of the complete set of human papillomavirus (HPV) proteins in multiple cell lines followed by mass spectrometry analysis. Integration of this map with tumor genome atlases shows that the virus targets human proteins frequently mutated in HPV- but not HPV+ cancers, providing a unique opportunity to identify novel oncogenic events phenocopied by HPV infection. For example, we find that the NRF2 transcriptional pathway, which protects against oxidative stress, is activated by interaction of the NRF2 regulator KEAP1 with the viral protein E1. We also demonstrate that the L2 HPV protein physically interacts with the RNF20/40 histone ubiquitination complex and promotes tumor cell invasion in an RNF20/40-dependent manner. This combined proteomic and genetic approach provides a systematic means to study the cellular mechanisms hijacked by virally induced cancers.Significance: In this study, we created a protein-protein interaction network between HPV and human proteins. An integrative analysis of this network and 800 tumor mutation profiles identifies multiple oncogenesis pathways promoted by HPV interactions that phenocopy recurrent mutations in cancer, yielding an expanded definition of HPV oncogenic roles. Cancer Discov; 8(11); 1474-89. ©2018 AACR.This article is highlighted in the In This Issue feature, p. 1333

Combinatorial CRISPR-Cas9 screens for de novo mapping of genetic interactions.

We developed a systematic approach to map human genetic networks by combinatorial CRISPR-Cas9 perturbations coupled to robust analysis of growth kinetics. We targeted all pairs of 73 cancer genes with dual guide RNAs in three cell lines, comprising 141,912 tests of interaction. Numerous therapeutically relevant interactions were identified, and these patterns replicated with combinatorial drugs at 75% precision. From these results, we anticipate that cellular context will be critical to synthetic-lethal therapies

Multiplatform Analysis of 12 Cancer Types Reveals Molecular Classification within and across Tissues of Origin

Recent genomic analyses of pathologically-defined tumor types identify “within-a-tissue” disease subtypes. However, the extent to which genomic signatures are shared across tissues is still unclear. We performed an integrative analysis using five genome-wide platforms and one proteomic platform on 3,527 specimens from 12 cancer types, revealing a unified classification into 11 major subtypes. Five subtypes were nearly identical to their tissue-of-origin counterparts, but several distinct cancer types were found to converge into common subtypes. Lung squamous, head & neck, and a subset of bladder cancers coalesced into one subtype typified by TP53 alterations, TP63 amplifications, and high expression of immune and proliferation pathway genes. Of note, bladder cancers split into three pan-cancer subtypes. The multi-platform classification, while correlated with tissue-of-origin, provides independent information for predicting clinical outcomes. All datasets are available for data-mining from a unified resource to support further biological discoveries and insights into novel therapeutic strategies