Genome-wide association studies of human and rat BMI converge on synapse, epigenome, and hormone signaling networks

A vexing observation in genome-wide association studies (GWASs) is that parallel analyses in different species may not identify orthologous genes. Here, we demonstrate that cross-species translation of GWASs can be greatly improved by an analysis of co-localization within molecular networks. Using body mass index (BMI) as an example, we show that the genes associated with BMI in humans lack significant agreement with those identified in rats. However, the networks interconnecting these genes show substantial overlap, highlighting common mechanisms including synaptic signaling, epigenetic modification, and hormonal regulation. Genetic perturbations within these networks cause abnormal BMI phenotypes in mice, too, supporting their broad conservation across mammals. Other mechanisms appear species specific, including carbohydrate biosynthesis (humans) and glycerolipid metabolism (rodents). Finally, network co-localization also identifies cross-species convergence for height/body length. This study advances a general paradigm for determining whether and how phenotypes measured in model species recapitulate human biology.

Multimodal perturbation analyses of cyclin-dependent kinases reveal a network of synthetic lethalities associated with cell-cycle regulation and transcriptional regulation

Cell-cycle control is accomplished by cyclin-dependent kinases (CDKs), motivating extensive research into CDK targeting small-molecule drugs as cancer therapeutics. Here we use combinatorial CRISPR/Cas9 perturbations to uncover an extensive network of functional interdependencies among CDKs and related factors, identifying 43 synthetic-lethal and 12 synergistic interactions. We dissect CDK perturbations using single-cell RNAseq, for which we develop a novel computational framework to precisely quantify cell-cycle effects and diverse cell states orchestrated by specific CDKs. While pairwise disruption of CDK4/6 is synthetic-lethal, only CDK6 is required for normal cell-cycle progression and transcriptional activation. Multiple CDKs (CDK1/7/9/12) are synthetic-lethal in combination with PRMT5, independent of cell-cycle control. In-depth analysis of mRNA expression and splicing patterns provides multiple lines of evidence that the CDK-PRMT5 dependency is due to aberrant transcriptional regulation resulting in premature termination. These inter-dependencies translate to drug-drug synergies, with therapeutic implications in cancer and other diseases.

Abstract 1159: Predicting clinical drug responses using a few-shot learning-based interpretable AI

High-throughput screens have generated large amounts of data characterizing how thousands of cell lines respond to hundreds of anti-cancer therapies. However, predictive drug response models trained using data from cell lines often fail to translate to clinical applications. Here, we focus on two key issues to improve clinical performance: 1) Transferability: the ability of predictive models to quickly adapt to clinical contexts even with a limited number of samples from patients, and 2) Interpretability: the ability to explain how drug-response predictions are being made given an individual patient’s genotype. Notably, an interpretable AI model can also help to identify biomarkers of treatment response in individual patients. By leveraging new developments in meta-learning and interpretable AI, we have developed an interpretable drug response prediction model that is trained on large amounts of data from experiments using cell lines and then transferred to clinical applications. We assessed our model’s clinical utility using AACR Project GENIE data, which contains mutational profiles from tumors and the patient’s therapeutic responses. We have demonstrated the feasibility of applying our AI-driven predictive model to clinical settings and shown how this model can support clinical decision making for tumor boards.

Citation Format: Sungjoon Park, Akshat Singhal, Erica Silva, Jason F. Kreisberg, Trey Ideker. Predicting clinical drug responses using a few-shot learning-based interpretable AI [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1159.

A multi-scale map of cell structure fusing protein images and interactions

The cell is a multi-scale structure with modular organization across at least four orders of magnitude1. Two central approaches for mapping this structure-protein fluorescent imaging and protein biophysical association-each generate extensive datasets, but of distinct qualities and resolutions that are typically treated separately2,3. Here we integrate immunofluorescence images in the Human Protein Atlas4 with affinity purifications in BioPlex5 to create a unified hierarchical map of human cell architecture. Integration is achieved by configuring each approach as a general measure of protein distance, then calibrating the two measures using machine learning. The map, known as the multi-scale integrated cell (MuSIC 1.0), resolves 69 subcellular systems, of which approximately half are to our knowledge undocumented. Accordingly, we perform 134 additional affinity purifications and validate subunit associations for the majority of systems. The map reveals a pre-ribosomal RNA processing assembly and accessory factors, which we show govern rRNA maturation, and functional roles for SRRM1 and FAM120C in chromatin and RPS3A in splicing. By integration across scales, MuSIC increases the resolution of imaging while giving protein interactions a spatial dimension, paving the way to incorporate diverse types of data in proteome-wide cell maps.

A protein network map of head and neck cancer reveals PIK3CA mutant drug sensitivity

[Figure: see text].

Interpretation of cancer mutations using a multiscale map of protein systems

A major goal of cancer research is to understand how mutations distributed across diverse genes affect common cellular systems, including multiprotein complexes and assemblies. Two challenges—how to comprehensively map such systems and how to identify which are under mutational selection—have hindered this understanding. Accordingly, we created a comprehensive map of cancer protein systems integrating both new and published multi-omic interaction data at multiple scales of analysis. We then developed a unified statistical model that pinpoints 395 specific systems under mutational selection across 13 cancer types. This map, called NeST (Nested Systems in Tumors), incorporates canonical processes and notable discoveries, including a PIK3CA-actomyosin complex that inhibits phosphatidylinositol 3-kinase signaling and recurrent mutations in collagen complexes that promote tumor proliferation. These systems can be used as clinical biomarkers and implicate a total of 548 genes in cancer evolution and progression. This work shows how disparate tumor mutations converge on protein assemblies at different scales.

A protein interaction landscape of breast cancer

[Figure: see text].

Genetic dissection of complex traits using hierarchical biological knowledge

Despite the growing constellation of genetic loci linked to common traits, these loci have yet to account for most heritable variation, and most act through poorly understood mechanisms. Recent machine learning (ML) systems have used hierarchical biological knowledge to associate genetic mutations with phenotypic outcomes, yielding substantial predictive power and mechanistic insight. Here, we use an ontology-guided ML system to map single nucleotide variants (SNVs) focusing on 6 classic phenotypic traits in natural yeast populations. The 29 identified loci are largely novel and account for ~17% of the phenotypic variance, versus <3% for standard genetic analysis. Representative results show that sensitivity to hydroxyurea is linked to SNVs in two alternative purine biosynthesis pathways, and that sensitivity to copper arises through failure to detoxify reactive oxygen species in fatty acid metabolism. This work demonstrates a knowledge-based approach to amplifying and interpreting signals in population genetic studies.

Genome-wide association studies (GWAS) have identified many important loci for common diseases and other traits. However, the loci identified by these studies are almost always many steps away from an understanding of underlying biological mechanisms. Here we develop an approach using hierarchical biological knowledge to identify genes and pathways responsible for phenotypic traits. Variants identified by the new method could explain a substantially greater fraction of heritability than previously reported. Moreover, we identified mechanistic pathways by which each causal variant affects cellular function. For example, we find that sensitivity to hydroxyurea is tied to genetic variants in two alternative purine biosynthesis pathways, and that sensitivity to copper arises through failure to detoxify reactive oxygen species in fatty acid metabolism. The new approach is a potentially transformative concept for understanding the genetic drivers of phenotypic variance, with potential applications in understanding traits in biomedicine and agriculture.

Abstract 2133: Systematic mapping of genetic interactions in human cancer cells reveals context dependent cancer signaling pathways

Genetic interaction screens have long been used to map gene functions and cellular pathways in model organisms and more recently in human cells. However, due to the technical challenges of these maps, most studies in human cells have focused on a single cell line, limiting the ability to determine how different genetic and cellular contexts influence genetic interactions. Here, we engineered a 110,728-element combinatorial CRISPR-Cas9 library to systematically map 12,282 genetic interactions among tumor suppressor genes and druggable targets. We mapped the landscape of genetic interactions in cell lines from breast cancer, head and neck squamous carcinoma, and non-small cell lung cancer as well as in non-cancerous, epithelial cells. The resulting genetic interaction maps emphasize the context dependency of these interactions. Of the interactions that are conserved across multiple cell lines, many include frequently essential genes, suggesting that these interactions may be critical for fundamental cellular functions. We found that genetic interaction maps from cancer cell lines are more similar to one another than non-cancer interaction maps, even between cancer and normal cells from the same tissue. Subsequent targeted chemogenetic screens confirmed interaction hubs across multiple cell lines while highlighting the robustness of some of the strongest interactions. Many of the identified genetic interactions suggest therapeutic interventions, such as the combination of CDK4 and MAPK inhibitors. Using the tissue-specific genetic interaction networks, we also built a deep learning model that accurately predicts patient outcomes, outperforming models that use accepted biomarkers such as MammaPrint. In summary, these genetic interaction maps provide a broad resource to investigate context dependency in cancer signaling pathways and in cancer drug response.

Citation Format: Samson H. Fong, Brent M. Kuenzi, John Lee, Kyle Sanchez, Ana Bojorquez-Gomez, Kyle Ford, Brenton P. Munson, Katherine Licon, Jeff Hager, John Paul Shen, Jason F. Kreisberg, Prashant Mali, Trey Ideker. Systematic mapping of genetic interactions in human cancer cells reveals context dependent cancer signaling pathways [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2133.

Predicting Drug Response and Synergy Using a Deep Learning Model of Human Cancer Cells

Most drugs entering clinical trials fail, often related to an incomplete understanding of the mechanisms governing drug response. Machine learning techniques hold immense promise for better drug response predictions, but most have not reached clinical practice due to their lack of interpretability and their focus on monotherapies. We address these challenges by developing DrugCell, an interpretable deep learning model of human cancer cells trained on the responses of 1,235 tumor cell lines to 684 drugs. Tumor genotypes induce states in cellular subsystems that are integrated with drug structure to predict response to therapy and, simultaneously, learn biological mechanisms underlying the drug response. DrugCell predictions are accurate in cell lines and also stratify clinical outcomes. Analysis of DrugCell mechanisms leads directly to the design of synergistic drug combinations, which we validate systematically by combinatorial CRISPR, drug-drug screening in vitro, and patient-derived xenografts. DrugCell provides a blueprint for constructing interpretable models for predictive medicine.

Abstract 223: Using physical, genetic and integrated cancer cell maps to investigate head and neck cancer and breast cancer

The Cancer Genome Atlas and similar projects have now analyzed over 10,000 tumor genomes, providing a catalog of the gene mutations, copy number variants and other genetic alterations that are present cancer. In many cases though, it remains unclear which are the key driver mutations or dependencies in a given cancer and how these influence pathogenesis and response to therapy. Although tumors of similar types and clinical outcomes can have patterns of mutations that are strikingly different, it is becoming apparent that these mutations recurrently hijack the same hallmark molecular pathways and networks. For this reason, cancer research and treatment is increasingly dependent on knowledge of biological networks of multiple types, including physical interactions among proteins and both synthetic-lethal and epistatic interactions among genes.

Founded in 2015 by labs at UC San Diego and UCSF, the mission of the Cancer Cell Map Initiative (CCMI) is to enable a new era of cancer discovery and treatment based on the complete elucidation of the molecular networks underlying cancer. We believe that this information will be critical for developing computational models of cancer cells that will enable both basic research and clinical decision-making. Our initial research efforts are focused on head and neck cancer and breast cancer but we believe that our approach is widely applicable.

Here, I will discuss results from three of the CCMI's main research efforts. One major focus is using affinity purification followed by mass spectrometry (AP/MS) to map protein-protein interactions of frequently mutated genes in multiple, relevant cell culture models. These efforts for approximately 40 genes in both head and neck cancer and breast cancer have largely been completed leading to a range of validation and follow-up studies. To complement these context-specific structural maps, a second main research effort is to generate functional maps by measuring genetic interactions using CRISPR/Cas9 in many of the same cell culture models. Many of these screens have now been completed with data analysis ongoing. Along with these two experimental efforts, a third focus has been to use bioinformatics approaches to assemble a hierarchical map of biological subsystems in cancer, to identify which systems in which cohorts are mutated more often than expected by chance and to explore these potentially driver systems in more detail through a range of experimental studies. To share these and other network maps, the CCMI's bioinformatics core has created the network data exchange (NDEx, ndexbio.org), an open-source framework where scientists and organizations can share, store, manipulate and publish biological network knowledge.

Citation Format: Jason F. Kreisberg, Fan Zheng, Samson Fong, Brent M. Kuenzi, Kyle Ford, Danielle Swaney, Minkyu Kim, Jisoo Park, Zhiyong Wang, Dexter Pratt, Natalia Jura, Silvio Gutkind, Prashant Mali, Nevan Krogan, Trey Ideker. Using physical, genetic and integrated cancer cell maps to investigate head and neck cancer and breast cancer [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 223.

Quantitative Translation of Dog-to-Human Aging by Conserved Remodeling of the DNA Methylome

All mammals progress through similar physiological stages throughout life, from early development to puberty, aging, and death. Yet, the extent to which this conserved physiology reflects underlying genomic events is unclear. Here, we map the common methylation changes experienced by mammalian genomes as they age, focusing on comparison of humans with dogs, an emerging model of aging. Using oligo-capture sequencing, we characterize methylomes of 104 Labrador retrievers spanning a 16-year age range, achieving >150× coverage within mammalian syntenic blocks. Comparison with human methylomes reveals a nonlinear relationship that translates dog-to-human years and aligns the timing of major physiological milestones between the two species, with extension to mice. Conserved changes center on developmental gene networks, which are sufficient to translate age and the effects of anti-aging interventions across multiple mammals. These results establish methylation not only as a diagnostic age readout but also as a cross-species translator of physiological aging milestones.

Visible Machine Learning for Biomedicine

A major ambition of artificial intelligence lies in translating patient data to successful therapies. Machine learning models face particular challenges in biomedicine, however, including handling of extreme data heterogeneity and lack of mechanistic insight into predictions. Here, we argue for "visible" approaches that guide model structure with experimental biology.

Ultrahigh-Density Screens for Genome-Wide Yeast EMAPs in a Single Plate

Systematic measurements of genetic interactions have been used to classify gene functions and to categorize genes into protein complexes, functional pathways and biological processes. This protocol describes how to perform a high-throughput genetic interaction screen in S. cerevisiae using a variant of epistatic miniarray profiles (E-MAP) in which the fitnesses of 6144 colonies are measured simultaneously. We also describe the computational methods to analyze the resulting data.

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.

Abstract 1317: Multi-scale mapping of the physical and functional architecture of the cancer cell

Cancer is governed by modular systems of genes, the composition and organization of which remains poorly understood. Here, we integrate physical and functional networks from a wide range of molecular studies to assemble a comprehensive multi-scale map of human cancer cell biology. This map consists of a hierarchical catalog of protein complexes, signaling pathways and inter-pathway crosstalk implicated in cancer, and it suggests many uncharacterized functional modules as intriguing hypotheses for further validation. Analysis of the pattern of somatic mutations in The Cancer Genome Atlas (TCGA) reveals that these mutations target systems of varying scales above the level of individual genes. The map also provides a platform to integrate and interpret new 'omics data; we integrate new protein-protein interactions identified using AP-MS in multiple breast cancer cell lines, revealing how different functional modules are rewired in cancer cells. A general model browsing tool has been created to visualize and navigate these hierarchical cancer maps. This multi-scale mapping approach elucidates the molecular heterogeneity of cancer, connects tumor genotypes to phenotypes and, ultimately, enables a platform for cancer precision medicine.

Citation Format: Fan Zheng, Michael K. Yu, Minkyu Kim, Keiichiro Ono, Mitchell Flagg, Jason F. Kreisberg, Nevan Krogan, Trey Ideker. Multi-scale mapping of the physical and functional architecture of the cancer cell [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 1317.

Abstract 1310: Systematic evaluation of gene networks for discovery of disease genes

Gene networks are rapidly growing in size and number, raising the question of which networks are most appropriate for a particular application. Here, we evaluate 21 human genome-wide interaction networks for their ability to recover gene sets associated with 446 different diseases and 9 cancer hallmarks. While all networks have some ability in these recovery tasks, we observe a wide range of performance with STRING, GeneMANIA and GIANT networks having the best performance overall. A general tendency is that performance scales with network size, suggesting that new interaction discovery currently outweighs the detrimental effects of false positives. Correcting for size, we find that the DIP network provides the highest efficiency (value per interaction). Based on these results we create a parsimonious composite network with both high efficiency and absolute performance, which outperforms any single resource. This work provides a benchmark for selection of molecular networks in human disease research.

Citation Format: Justin K. Huang, Daniel E. Carlin, Michael K. Yu, Wei Zhang, Jason F. Kreisberg, Pablo Tamayo, Trey Ideker. Systematic evaluation of gene networks for discovery of disease genes [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 1310.

Disruption of NSD1 in Head and Neck Cancer Promotes Favorable Chemotherapeutic Responses Linked to Hypomethylation

Human papillomavirus (HPV)-negative head and neck squamous cell carcinoma (HNSCC) represents a distinct classification of cancer with worse expected outcomes. Of the 11 genes recurrently mutated in HNSCC, we identify a singular and substantial survival advantage for mutations in the gene encoding Nuclear Set Domain Containing Protein 1 (NSD1), a histone methyltransferase altered in approximately 10% of patients. This effect, a 55% decrease in risk of death in NSD1-mutated versus non-mutated patients, can be validated in an independent cohort. NSD1 alterations are strongly associated with widespread genome hypomethylation in the same tumors, to a degree not observed for any other mutated gene. To address whether NSD1 plays a causal role in these associations, we use CRISPR-Cas9 to disrupt NSD1 in HNSCC cell lines and find that this leads to substantial CpG hypomethylation and sensitivity to cisplatin, a standard chemotherapy in head and neck cancer, with a 40% to 50% decrease in the IC₅₀ value. Such results are reinforced by a survey of 1,001 cancer cell lines, in which loss-of-function NSD1 mutations have an average 23% decrease in cisplatin IC₅₀ value compared with cell lines with wild-type NSD1Significance: This study identifies a favorable subtype of HPV-negative HNSCC linked to NSD1 mutation, hypomethylation, and cisplatin sensitivity. Mol Cancer Ther; 17(7); 1585-94. ©2018 AACR.

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 antiretroviral 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 >80,000 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 / CD8 T cell ratio, linking molecular aging, epigenetic regulation, and disease progression.

A platinum-resistant subtype of high-grade serous ovarian cancer identified by a network of somatic mutations

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Background: High-grade serous ovarian carcinoma (HGS-OvCa) is a heterogeneous entity with a widely variable clinical course even among patients of the same stage and histological subtype. Although most patients will achieve remission with platinum-based chemotherapy, ~20% will display primary platinum resistance. Currently no biomarker exists to identify these platinum resistant patients. Methods: We have recently developed a method called Network-based Stratification (NBS), which combines genome-scale somatic mutation profiles with genetic interaction networks and performs unsupervised clustering of patients into subtypes. Results: Using NBS HGSOC patients were stratified into subtype, in both TCGA (n = 330) and the ICGC (n = 92) a high-risk (HR) subtype consisting of ~20% of the patients was identified (see table). Propagated mutation scores of the HR tumors from TCGA and ICGC cohorts we remarkably correlated (Pearson r2 = 0.94, p < 0.001), relative to the correlation between HR and standard risk subtypes within TGCA cohort (r2 = 0.18). We then identified molecularly matched cell line models for in vitro study, finding that HR cell lines (Kuramochi, Ovkate, OAW28, 59M) were significantly more resistant to cisplatin relative standard risk cell lines (COV318, TYK-NU, OVCAR4), (IC50 14.4 vs. 3.3 µM, p < 0.0001). There was no significant difference in sensitivity to paclitaxel. A genome-wide knockout screen using CRISPR-Cas9 has identified several candidate genes mediating this observed platinum resistance. Conclusions: NBS can be used to identify a molecularly distinct subtype of HGSOC characterized by poor patient survival and primary platinum resistance. [Table: see text]

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 Prop1^df/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.

Interaction Landscape of Inherited Polymorphisms with Somatic Events in Cancer

Recent studies have characterized the extensive somatic alterations that arise during cancer. However, the somatic evolution of a tumor may be significantly affected by inherited polymorphisms carried in the germline. Here, we analyze genomic data for 5,954 tumors to reveal and systematically validate 412 genetic interactions between germline polymorphisms and major somatic events, including tumor formation in specific tissues and alteration of specific cancer genes. Among germline-somatic interactions, we found germline variants in RBFOX1 that increased incidence of SF3B1 somatic mutation by 8-fold via functional alterations in RNA splicing. Similarly, 19p13.3 variants were associated with a 4-fold increased likelihood of somatic mutations in PTEN. In support of this association, we found that PTEN knockdown sensitizes the MTOR pathway to high expression of the 19p13.3 gene GNA11 Finally, we observed that stratifying patients by germline polymorphisms exposed distinct somatic mutation landscapes, implicating new cancer genes. This study creates a validated resource of inherited variants that govern where and how cancer develops, opening avenues for prevention research.Significance: This study systematically identifies germline variants that directly affect tumor evolution, either by dramatically increasing alteration frequency of specific cancer genes or by influencing the site where a tumor develops. Cancer Discovery; 7(4); 410-23. ©2017 AACR.See related commentary by Geeleher and Huang, p. 354This article is highlighted in the In This Issue feature, p. 339.

Structure-Based Analysis Reveals Cancer Missense Mutations Target Protein Interaction Interfaces

Recently it has been shown that cancer mutations selectively target protein-protein interactions. We hypothesized that mutations affecting distinct protein interactions involving established cancer genes could contribute to tumor heterogeneity, and that novel mechanistic insights might be gained into tumorigenesis by investigating protein interactions under positive selection in cancer. To identify protein interactions under positive selection in cancer, we mapped over 1.2 million nonsynonymous somatic cancer mutations onto 4,896 experimentally determined protein structures and analyzed their spatial distribution. In total, 20% of mutations on the surface of known cancer genes perturbed protein-protein interactions (PPIs), and this enrichment for PPI interfaces was observed for both tumor suppressors (Odds Ratio 1.28, P-value < 10⁻⁴) and oncogenes (Odds Ratio 1.17, P-value < 10⁻³). To study this further, we constructed a bipartite network representing structurally resolved PPIs from all available human complexes in the Protein Data Bank (2,864 proteins, 3,072 PPIs). Analysis of frequently mutated cancer genes within this network revealed that tumor-suppressors, but not oncogenes, are significantly enriched with functional mutations in homo-oligomerization regions (Odds Ratio 3.68, P-Value < 10⁻⁸). We present two important examples, TP53 and beta-2-microglobulin, for which the patterns of somatic mutations at interfaces provide insights into specifically perturbed biological circuits. In patients with TP53 mutations, patient survival correlated with the specific interactions that were perturbed. Moreover, we investigated mutations at the interface of protein-nucleotide interactions and observed an unexpected number of missense mutations but not silent mutations occurring within DNA and RNA binding sites. Finally, we provide a resource of 3,072 PPI interfaces ranked according to their mutation rates. Analysis of this list highlights 282 novel candidate cancer genes that encode proteins participating in interactions that are perturbed recurrently across tumors. In summary, mutation of specific protein interactions is an important contributor to tumor heterogeneity and may have important implications for clinical outcomes.

Evidence for a common evolutionary rate in metazoan transcriptional networks

Genome sequences diverge more rapidly in mammals than in other animal lineages, such as birds or insects. However, the effect of this rapid divergence on transcriptional evolution remains unclear. Recent reports have indicated a faster divergence of transcription factor binding in mammals than in insects, but others found the reverse for mRNA expression. Here, we show that these conflicting interpretations resulted from differing methodologies. We performed an integrated analysis of transcriptional network evolution by examining mRNA expression, transcription factor binding and cis-regulatory motifs across >25 animal species, including mammals, birds and insects. Strikingly, we found that transcriptional networks evolve at a common rate across the three animal lineages. Furthermore, differences in rates of genome divergence were greatly reduced when restricting comparisons to chromatin-accessible sequences. The evolution of transcription is thus decoupled from the global rate of genome sequence evolution, suggesting that a small fraction of the genome regulates transcription.

DOI:http://dx.doi.org/10.7554/eLife.11615.001

The genetic information that makes each individual unique is encoded in DNA molecules. Cells read this molecular instruction manual by a process called transcription, in which proteins called transcription factors bind to DNA in specific places and regulate which sections of the DNA will be expressed. These 'transcripts' are active molecules that determine the cell’s – and ultimately the individual’s – characteristics. However, it is not well understood how alterations in the DNA of different individuals or species can lead to changes in where the transcription factors bind, and in which transcripts are expressed.

Carvunis, Wang, Skola et al. set out to determine if there is a relationship between how often DNA changes and how often transcription changes during the evolution of animals. The experiments examined the abundance of transcripts in the cells of a variety of animal species with close or distant evolutionary relationships. For example, the house mouse was compared to a close relative called the Algerian mouse, to another species of rodent (rat) and to humans.

The experiments show that the changes in transcript abundances are happening at similar rates in mammals, birds and insects, even though DNA changes at very different rates in these groups of animals. This similarity was also observed for other aspects of transcription, such as in changes to where transcription factors bind to DNA. The next challenges are to find out what makes transcription evolve at such similar rates in these groups of animals, and whether these findings extend to other species and to other processes in cells.

DOI:http://dx.doi.org/10.7554/eLife.11615.002

Analysis of Matched Tumor and Normal Profiles Reveals Common Transcriptional and Epigenetic Signals Shared across Cancer Types

To identify the transcriptional regulatory changes that are most widespread in solid tumors, we performed a pan-cancer analysis using over 600 pairs of tumors and adjacent normal tissues profiled in The Cancer Genome Atlas (TCGA). Frequency of upregulation was calculated across mRNA expression levels, microRNA expression levels and CpG methylation sites and is provided here as a resource. Frequent tumor-associated alterations were identified using a simple statistical approach. Many of the identified changes were consistent with the increased rate of cell division in cancer, such as the overexpression of cell cycle genes and hypermethylation of PRC2 binding sites. However, we also identified proliferation-independent alterations, which highlight novel pathways essential to tumor formation. Nearly all of the GABA receptors are frequently downregulated, with the gene encoding the delta subunit (GABRD) strongly upregulated as the notable exception. Metabolic genes are also frequently downregulated, particularly alcohol dehydrogenases and others consistent with the decreased role of oxidative phosphorylation in cancerous cells. Alterations in the composition of GABA receptors and metabolism may play a key role in the differentiation of cancer cells, independent of proliferation.

Establishment of a novel whole animal HTS technology platform for melioidosis drug discovery

Melioidosis is a serious emerging endemic infectious disease caused by Burkholderia pseudomallei, a gram-negative pathogen. Septicemic melioidosis has a mortality rate of 50% even with treatment. Like other gram-negative bacteria, B. pseudomallei is resistant to a number of antibiotics and multi-drug resistant B. pseudomallei is beginning to be encountered in hospitals. There is a clear medical need to develop new treatment options to manage this disease. We used Burkholderia thailandensis (a BSL-2 class organism) to infect Caenorhabditis elegans and set up a surrogate whole animal infection model of melioidosis that we could run in a 384 microtitre plate and establish a whole animal HTS assay. We have optimized and validated this assay in a fluorescence-based format that can be run on our automated screening platforms. This assay has now been used to screen over 300,000 compounds from our small molecule library and we are in the process of characterizing the hits obtained and select compounds for further studies. We have thus established a biologically relevant assay technology platform to screen for antibacterial compounds and used this platform to identify new compounds that may find application in treating melioidosis infections.

The condition-dependent transcriptional landscape of Burkholderia pseudomallei

Burkholderia pseudomallei (Bp), the causative agent of the often-deadly infectious disease melioidosis, contains one of the largest prokaryotic genomes sequenced to date, at 7.2 Mb with two large circular chromosomes (1 and 2). To comprehensively delineate the Bp transcriptome, we integrated whole-genome tiling array expression data of Bp exposed to >80 diverse physical, chemical, and biological conditions. Our results provide direct experimental support for the strand-specific expression of 5,467 Sanger protein-coding genes, 1,041 operons, and 766 non-coding RNAs. A large proportion of these transcripts displayed condition-dependent expression, consistent with them playing functional roles. The two Bp chromosomes exhibited dramatically different transcriptional landscapes — Chr 1 genes were highly and constitutively expressed, while Chr 2 genes exhibited mosaic expression where distinct subsets were expressed in a strongly condition-dependent manner. We identified dozens of cis-regulatory motifs associated with specific condition-dependent expression programs, and used the condition compendium to elucidate key biological processes associated with two complex pathogen phenotypes — quorum sensing and in vivo infection. Our results demonstrate the utility of a Bp condition-compendium as a community resource for biological discovery. Moreover, the observation that significant portions of the Bp virulence machinery can be activated by specific in vitro cues provides insights into Bp's capacity as an “accidental pathogen”, where genetic pathways used by the bacterium to survive in environmental niches may have also facilitated its ability to colonize human hosts.

Bacterial transcriptomes are dynamic, context-specific and condition-dependent. Infection by the soil bacterium, Burkholderia pseudomallei, causes melioidosis, an often fatal infectious disease of humans and animals. Possessing a large multi-chromosomal genome, B. pseudomallei is able to persist and survive in a multitude of environments. To obtain a comprehensive overview of B. pseudomallei expressed transcripts, we initiated whole-genome transcriptome profiling covering a broad spectrum of conditions and exposures — a so-called “condition compendium”. Using the compendium, we confirmed many previously-annotated genes and operons, and also identified hundreds of novel transcripts including anti-sense transcripts and non-coding RNAs. By systematically examining genes exhibiting highly similar expression patterns, we ascribed putative functions to previously uncharacterized genes, and identified novel regulatory elements controlling these expression patterns. We also used the compendium to elucidate candidate virulence pathways associated with quorum-sensing and infection in mice. Our study showcases the power of a B. pseudomallei condition compendium as a valuable resource for understanding microbial physiology and the pathogenesis of melioidosis.

Modulation of Caenorhabditis elegans infection sensitivity by the LIN-7 cell junction protein

In Caenorhabditis elegans, the LIN-2/7/10 protein complex regulates the activity of signalling proteins. We found that inhibiting lin-7 function, and also lin-2 and lin-10, resulted in enhanced C. elegans survival after infection by Burkholderia spp., implicating a novel role for these genes in modulating infection outcomes. Genetic experiments suggested that this infection phenotype is likely caused by modulation of the DAF-2 insulin/IGF-1 signalling pathway. Supporting these observations, yeast two-hybrid assays confirmed that the LIN-2 PDZ domain can physically bind to the DAF-2 C-terminus. Loss of lin-7 activity also altered DAF-16 nuclear localization kinetics, indicating an additional contribution by hsf-1. Unexpectedly, silencing lin-7 in the hypodermis, but not the intestine, was protective against infection, implicating the hypodermis as a key tissue in this phenomenon. Finally, consistent with lin-7 acting as a general host infection factor, lin-7 mutants also exhibited enhanced survival upon infectionby two other Gram-negative pathogens, Pseudomonas and Salmonella spp.

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.

Dendritic cells (DCs) patrol peripheral mucosal sites, capturing and processing potential pathogens into antigenic peptides for presentation to T cells of lymphoid organs, and thereby initiating an immune response. HIV-1 had been proposed to use DCs as “Trojan horses,” hiding inside the DCs and surviving the degradation pathway to gain access to the lymph nodes and spread to the T cells. Our study challenges this “Trojan horse” model by showing that only HIV-1 virions bound to the surface of DCs, and not internalized virions, are transmitted to T cells. Even when T cells specifically recognized the antigen presented by DCs, the infection of T cells was principally mediated by virions remaining at the surface of the DCs. Interestingly, in this context of antigen-specific recognition, which increases the trafficking toward the immunological synapse of DC internal vesicles, where HIV-1 virions seem to hide, a few internal virions could infect T cells. Our findings suggest that in vivo transmission to T cells of HIV-1 virions captured by DCs should be more sensitive to neutralization than previously expected.

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.

Human immunodeficiency virus fusion to dendritic cells declines as cells mature

The maturation of dendritic cells (DCs) is associated with a diminished ability to support human immunodeficiency virus (HIV) replication; however, the precise step in the HIV life cycle impaired by DC maturation remains uncertain. Using an HIV virion-based fusion assay, we now show that HIV fusion to monocyte-derived DCs (MDDCs) both decreases and kinetically slows when DCs are induced to mature with poly(I:C) and tumor necrosis factor alpha. Specifically, laboratory-adapted CCR5-tropic 81A virions fused with markedly lower efficiency to mature MDDCs than immature DCs. In contrast, fusion of NL4-3, the isogenic CXCR4-tropic counterpart of 81A, was low in both immature and mature MDDCs. Fusion mediated by primary HIV envelopes, including seven CCR5- and four CXCR4-tropic envelopes, also decreased with DC maturation. The kinetics of virion fusion were also altered by both the state of DC maturation and the coreceptor utilized. Fusion of 81A and NL4-3 virions was delayed in mature compared to immature MDDCs, and NL4-3 fused more slowly than 81A in both mature and immature MDDCs. Surprisingly, primary envelopes with CXCR4 tropism mediated fusion to immature MDDCs with efficiencies similar to those of primary CCR5-tropic envelopes. This result contrasted with the marked preferential fusion of the laboratory-adapted 81A over NL4-3 in immature MDDCs and in ex vivo Langerhans cells, indicating that these laboratory-adapted HIV strains do not fully recapitulate all of the properties of primary HIV isolates. In conclusion, our results demonstrate that the defect in HIV replication observed in mature MDDCs stems at least in part from a decline in viral fusion.

Cellular APOBEC3G restricts HIV-1 infection in resting CD4+ T cells

In contrast to activated CD4+ T cells, resting human CD4+ T cells circulating in blood are highly resistant to infection with human immunodeficiency virus (HIV). Whether the inability of HIV to infect these resting CD4+ T cells is due to the lack of a key factor, or alternatively reflects the presence of an efficient mechanism for defence against HIV, is not clear. Here we show that the anti-retroviral deoxycytidine deaminase APOBEC3G strongly protects unstimulated peripheral blood CD4+ T cells against HIV-1 infection. In activated CD4+ T cells, cytoplasmic APOBEC3G resides in an enzymatically inactive, high-molecular-mass (HMM) ribonucleoprotein complex that converts to an enzymatically active low-molecular-mass (LMM) form after treatment with RNase. In contrast, LMM APOBEC3G predominates in unstimulated CD4+ T cells, where HIV-1 replication is blocked and reverse transcription is impaired. Mitogen activation induces the recruitment of LMM APOBEC3G into the HMM complex, and this correlates with a sharp increase in permissivity for HIV infection in these stimulated cells. Notably, when APOBEC3G-specific small interfering RNAs are introduced into unstimulated CD4+ T cells, the early replication block encountered by HIV-1 is greatly relieved. Thus, LMM APOBEC3G functions as a potent post-entry restriction factor for HIV-1 in unstimulated CD4+ T cells. Surprisingly, sequencing of the reverse transcripts slowly formed in unstimulated CD4+ T cells reveals only low levels of dG dA hypermutation, raising the possibility that the APOBEC3G-restricting activity may not be strictly dependent on deoxycytidine deamination

HIV-1 Vpr displays natural protein-transducing properties: implications for viral pathogenesis

The 14-kDa Vpr protein of human immunodeficiency virus type 1 (HIV-1) serves multiple functions in the retroviral life cycle, including the enhancement of viral replication in nondividing macrophages, the induction of G2 cell-cycle arrest in proliferating T lymphocytes, and the modulation of HIV-1-induced apoptosis. Extracellular Vpr has been detected in the sera and cerebral spinal fluid of HIV-infected patients. However, it is not known whether such forms of Vpr are biologically active. Vpr contains a carboxy-terminal basic amino acid rich segment stretch that is homologous to domains that mediate the energy- and receptor-independent cellular uptake of polypeptides by a process termed protein transduction. Similar functional protein-transducing domains are present in HIV-1 Tat, herpes simplex virus-1 DNA-binding protein VP22, and the Drosophila antennapedia homeotic transcription factor. We now demonstrate effective transduction of biologically active, synthetic Vpr (sVpr) as well as the Vpr-beta-galactosidase fusion protein. However, in contrast to other transducing proteins, Vpr transduction is not enhanced by protein denaturation, and Vpr's carboxy-terminal basic domain alone is not sufficient for its transduction across biological membranes. In contrast, the full-length Vpr protein effectively transduces a broad array of cells, leading to dose-dependent G2 cell-cycle arrest and apoptosis. Addition of Vpr into the extracellular medium also rescues the replication of Vpr-deficient strains of HIV-1 in human macrophage cultures. Native Vpr may thus be optimized for protein transduction, a feature that might enhance and extend the pathological effects of HIV infection.

The interdigitated beta-helix domain of the P22 tailspike protein acts as a molecular clamp in trimer stabilization

The P22 tailspike adhesin is an elongated thermostable trimer resistant to protease digestion and to denaturation in sodium dodecyl sulfate. Monomeric, dimeric, and protrimeric folding and assembly intermediates lack this stability and are thermolabile. In the native trimer, three right-handed parallel beta-helices (residues 143-540), pack side-by-side around the three-fold axis. After residue 540, these single chain beta-helices terminate and residues 541-567 of the three polypeptide chains wrap around each other to form a three-stranded interdigitated beta-helix. Three mutants located in this region -- G546D, R563Q, and A575T -- blocked formation of native tailspike trimers, and accumulated soluble forms of the mutant polypeptide chains within cells. The substitutions R563Q and A575T appeared to prevent stable association of partially folded monomers. G546D, in the interdigitated region of the chain, blocked tailspike folding at the transition from the partially-folded protrimer to the native trimer. The protrimer-like species accumulating in the G546D mutant melted out at 42 degrees C and was trypsin and SDS sensitive. The G546D defect was not corrected by introduction of global suppressor mutations, which correct kinetic defects in beta-helix folding. The simplest interpretation of these results is that the very high thermostability (T(m) = 88 degrees C), protease and detergent resistance of the native tailspike acquired in the protrimer-to-trimer transition, depends on the formation of the three-stranded interdigitated region. This interdigitated beta-helix appears to function as a molecular clamp insuring thermostable subunit association in the native trimer.

HIV-1 actively replicates in naive CD4(+) T cells residing within human lymphoid tissues

Although HIV-1 gene expression is detected in naive, resting T cells in vivo, such cells are resistant to productive infection in vitro. However, we found that the endogenous microenvironment of human lymphoid tissues supports de novo infection and depletion of this population. Cell cycle analysis and DNA labeling experiments established that these cells were definitively quiescent and thus infected de novo. Quantitation of the "burst size" within naive cells further demonstrated that these cells were productively infected and contributed to the local viral burden. These findings demonstrate that lymphoid tissues support active HIV-1 replication in resting, naive T cells. Moreover, these cells are not solely reservoirs of latent virus but are permissive hosts for viral replication that likely targets them for elimination.

Cytopathicity of human immunodeficiency virus type 1 primary isolates depends on coreceptor usage and not patient disease status

It has been hypothesized that human immunodeficiency virus type 1 (HIV-1) evolves toward increased cytopathicity in conjunction with disease progression in infected patients. A viral property known to evolve in some but not all patients is coreceptor utilization, and it has been shown that a switch in coreceptor utilization is sufficient for the development of increased cytopathicity. To test the hypothesis that the evolution of other viral properties also contributes to accelerating cytopathicity in vivo, we used human lymphoid tissue explants to assay the cytopathicity of a panel of primary HIV-1 isolates derived from various stages of disease characterized by the presence or absence of changes in coreceptor preference. We found no evidence of coreceptor-independent increases in cytopathicity in isolates obtained either before coreceptor preference changes or from patients who progressed to AIDS despite an absence of coreceptor evolution. Instead, the cytopathicity of all HIV-1 isolates was determined solely by their coreceptor utilization. These results argue that HIV-1 does not evolve toward increased cytopathicity independently of changes in coreceptor utilization.

Folate receptor-alpha is a cofactor for cellular entry by Marburg and Ebola viruses

Human infections by Marburg (MBG) and Ebola (EBO) viruses result in lethal hemorrhagic fever. To identify cellular entry factors employed by MBG virus, noninfectible cells transduced with an expression library were challenged with a selectable pseudotype virus packaged by MBG glycoproteins (GP). A cDNA encoding the folate receptor-alpha (FR-alpha) was recovered from cells exhibiting reconstitution of viral entry. A FR-alpha cDNA was recovered in a similar strategy employing EBO pseudotypes. FR-alpha expression in Jurkat cells facilitated MBG or EBO entry, and FR-blocking reagents inhibited infection by MBG or EBO. Finally, FR-alpha bound cells expressing MBG or EBO GP and mediated syncytia formation triggered by MBG GP. Thus, FR-alpha is a significant cofactor for cellular entry for MBG and EBO viruses.

Beta-helix core packing within the triple-stranded oligomerization domain of the P22 tailspike

A right-handed parallel beta-helix of 400 residues in 13 tightly packed coils is a major motif of the chains forming the trimeric P22 tailspike adhesin. The beta-helix domains of three identical subunits are side-by-side in the trimer and make predominantly hydrophilic inter-subunit contacts (Steinbacher S et al., 1994, Science 265:383-386). After the 13th coil the three individual beta-helices terminate and the chains wrap around each other to form three interdigitated beta-sheets organized into the walls of a triangular prism. The beta-strands then separate and form antiparallel beta-sheets, but still defining a triangular prism in which each side is a beta-sheet from a different subunit (Seckler R, 1998, J Struct Biol 122:216-222). The subunit interfaces are buried in the triangular core of the prism, which is densely packed with hydrophobic side chains from the three beta-sheets. Examination of this structure reveals that its packed core maintains the same pattern of interior packing found in the left-handed beta-helix, a single-chain structure. This packing is maintained in both the interdigitated parallel region of the prism and the following antiparallel sheet section. This oligomerization motif for the tailspike beta-helices presumably contributes to the very high thermal and detergent stability that is a property of the native tailspike adhesin.