Widespread variation in molecular interactions and regulatory properties among transcription factor isoforms.

Most human Transcription factors (TFs) genes encode multiple protein isoforms differing in DNA binding domains, effector domains, or other protein regions. The global extent to which this results in functional differences between isoforms remains unknown. Here, we systematically compared 693 isoforms of 246 TF genes, assessing DNA binding, protein binding, transcriptional activation, subcellular localization, and condensate formation. Relative to reference isoforms, two-thirds of alternative TF isoforms exhibit differences in one or more molecular activities, which often could not be predicted from sequence. We observed two primary categories of alternative TF isoforms: "rewirers" and "negative regulators", both of which were associated with differentiation and cancer. Our results support a model wherein the relative expression levels of, and interactions involving, TF isoforms add an understudied layer of complexity to gene regulatory networks, demonstrating the importance of isoform-aware characterization of TF functions and providing a rich resource for further studies.

["The pre-habilitation sessions gave me confidence"]. / « Les séances de préhabilitation m'ont donné confiance ¼.

Aged 45, married with two children, Marc has always lived a "healthy" lifestyle: no cigarettes, a balanced organic diet and regular exercise. He had never experienced any serious health problems until January 2023, when symptoms led him to seek medical advice. He was diagnosed with pancreatic cancer. He tells us about his journey since then.

Paired yeast one-hybrid assays to detect DNA-binding cooperativity and antagonism across transcription factors.

Cooperativity and antagonism between transcription factors (TFs) can drastically modify their binding to regulatory DNA elements. While mapping these relationships between TFs is important for understanding their context-specific functions, existing approaches either rely on DNA binding motif predictions, interrogate one TF at a time, or study individual TFs in parallel. Here, we introduce paired yeast one-hybrid (pY1H) assays to detect cooperativity and antagonism across hundreds of TF-pairs at DNA regions of interest. We provide evidence that a wide variety of TFs are subject to modulation by other TFs in a DNA region-specific manner. We also demonstrate that TF-TF relationships are often affected by alternative isoform usage and identify cooperativity and antagonism between human TFs and viral proteins from human papillomaviruses, Epstein-Barr virus, and other viruses. Altogether, pY1H assays provide a broadly applicable framework to study how different functional relationships affect protein occupancy at regulatory DNA regions.

Homo cerevisiae-Leveraging Yeast for Investigating Protein-Protein Interactions and Their Role in Human Disease.

Understanding how genetic variation affects phenotypes represents a major challenge, particularly in the context of human disease. Although numerous disease-associated genes have been identified, the clinical significance of most human variants remains unknown. Despite unparalleled advances in genomics, functional assays often lack sufficient throughput, hindering efficient variant functionalization. There is a critical need for the development of more potent, high-throughput methods for characterizing human genetic variants. Here, we review how yeast helps tackle this challenge, both as a valuable model organism and as an experimental tool for investigating the molecular basis of phenotypic perturbation upon genetic variation. In systems biology, yeast has played a pivotal role as a highly scalable platform which has allowed us to gain extensive genetic and molecular knowledge, including the construction of comprehensive interactome maps at the proteome scale for various organisms. By leveraging interactome networks, one can view biology from a systems perspective, unravel the molecular mechanisms underlying genetic diseases, and identify therapeutic targets. The use of yeast to assess the molecular impacts of genetic variants, including those associated with viral interactions, cancer, and rare and complex diseases, has the potential to bridge the gap between genotype and phenotype, opening the door for precision medicine approaches and therapeutic development.

The HTLV-1 viral oncoproteins Tax and HBZ reprogram the cellular mRNA splicing landscape.

Viral infections are known to hijack the transcription and translation of the host cell. However, the extent to which viral proteins coordinate these perturbations remains unclear. Here we used a model system, the human T-cell leukemia virus type 1 (HTLV-1), and systematically analyzed the transcriptome and interactome of key effectors oncoviral proteins Tax and HBZ. We showed that Tax and HBZ target distinct but also common transcription factors. Unexpectedly, we also uncovered a large set of interactions with RNA-binding proteins, including the U2 auxiliary factor large subunit (U2AF2), a key cellular regulator of pre-mRNA splicing. We discovered that Tax and HBZ perturb the splicing landscape by altering cassette exons in opposing manners, with Tax inducing exon inclusion while HBZ induces exon exclusion. Among Tax- and HBZ-dependent splicing changes, we identify events that are also altered in Adult T cell leukemia/lymphoma (ATLL) samples from two independent patient cohorts, and in well-known cancer census genes. Our interactome mapping approach, applicable to other viral oncogenes, has identified spliceosome perturbation as a novel mechanism coordinated by Tax and HBZ to reprogram the transcriptome.

Comprehensive characterization of protein-protein interactions perturbed by disease mutations.

Technological and computational advances in genomics and interactomics have made it possible to identify how disease mutations perturb protein-protein interaction (PPI) networks within human cells. Here, we show that disease-associated germline variants are significantly enriched in sequences encoding PPI interfaces compared to variants identified in healthy participants from the projects 1000 Genomes and ExAC. Somatic missense mutations are also significantly enriched in PPI interfaces compared to noninterfaces in 10,861 tumor exomes. We computationally identified 470 putative oncoPPIs in a pan-cancer analysis and demonstrate that oncoPPIs are highly correlated with patient survival and drug resistance/sensitivity. We experimentally validate the network effects of 13 oncoPPIs using a systematic binary interaction assay, and also demonstrate the functional consequences of two of these on tumor cell growth. In summary, this human interactome network framework provides a powerful tool for prioritization of alleles with PPI-perturbing mutations to inform pathobiological mechanism- and genotype-based therapeutic discovery.

Interrogation of kinase genetic interactions provides a global view of PAK1-mediated signal transduction pathways.

Kinases are critical components of intracellular signaling pathways and have been extensively investigated with regard to their roles in cancer. p21-activated kinase-1 (PAK1) is a serine/threonine kinase that has been previously implicated in numerous biological processes, such as cell migration, cell cycle progression, cell motility, invasion, and angiogenesis, in glioma and other cancers. However, the signaling network linked to PAK1 is not fully defined. We previously reported a large-scale yeast genetic interaction screen using toxicity as a readout to identify candidate PAK1 genetic interactions. En masse transformation of the PAK1 gene into 4,653 homozygous diploid Saccharomyces cerevisiae yeast deletion mutants identified ∼400 candidates that suppressed yeast toxicity. Here we selected 19 candidate PAK1 genetic interactions that had human orthologs and were expressed in glioma for further examination in mammalian cells, brain slice cultures, and orthotopic glioma models. RNAi and pharmacological inhibition of potential PAK1 interactors confirmed that DPP4, KIF11, mTOR, PKM2, SGPP1, TTK, and YWHAE regulate PAK1-induced cell migration and revealed the importance of genes related to the mitotic spindle, proteolysis, autophagy, and metabolism in PAK1-mediated glioma cell migration, drug resistance, and proliferation. AKT1 was further identified as a downstream mediator of the PAK1-TTK genetic interaction. Taken together, these data provide a global view of PAK1-mediated signal transduction pathways and point to potential new drug targets for glioma therapy.

Yeast-Based Genetic Interaction Analysis of Human Kinome.

Kinases are critical intracellular signaling proteins. To better understand kinase-mediated signal transduction, a large-scale human-yeast genetic interaction screen was performed. Among 597 human kinase genes tested, 28 displayed strong toxicity in yeast when overexpressed. En masse transformation of these toxic kinase genes into 4653 homozygous diploid yeast deletion mutants followed by barcode sequencing identified yeast toxicity modifiers and thus their human orthologs. Subsequent network analyses and functional grouping revealed that the 28 kinases and their 676 interaction partners (corresponding to a total of 969 genetic interactions) are enriched in cell death and survival (34%), small-molecule biochemistry (18%) and molecular transport (11%), among others. In the subnetwork analyses, a few kinases were commonly associated with glioma, cell migration and cell death/survival. Our analysis enabled the creation of a first draft of the kinase genetic interactome network and identified multiple drug targets for inflammatory diseases and cancer, in which deregulated kinase signaling plays a pathogenic role.

A proactive genotype-to-patient-phenotype map for cystathionine beta-synthase.

BACKGROUND: For the majority of rare clinical missense variants, pathogenicity status cannot currently be classified. Classical homocystinuria, characterized by elevated homocysteine in plasma and urine, is caused by variants in the cystathionine beta-synthase (CBS) gene, most of which are rare. With early detection, existing therapies are highly effective. METHODS: Damaging CBS variants can be detected based on their failure to restore growth in yeast cells lacking the yeast ortholog CYS4. This assay has only been applied reactively, after first observing a variant in patients. Using saturation codon-mutagenesis, en masse growth selection, and sequencing, we generated a comprehensive, proactive map of CBS missense variant function. RESULTS: Our CBS variant effect map far exceeds the performance of computational predictors of disease variants. Map scores correlated strongly with both disease severity (Spearman's ϱ = 0.9) and human clinical response to vitamin B6 (ϱ = 0.93). CONCLUSIONS: We demonstrate that highly multiplexed cell-based assays can yield proactive maps of variant function and patient response to therapy, even for rare variants not previously seen in the clinic.

A genome-wide positioning systems network algorithm for in silico drug repurposing.

Recent advances in DNA/RNA sequencing have made it possible to identify new targets rapidly and to repurpose approved drugs for treating heterogeneous diseases by the 'precise' targeting of individualized disease modules. In this study, we develop a Genome-wide Positioning Systems network (GPSnet) algorithm for drug repurposing by specifically targeting disease modules derived from individual patient's DNA and RNA sequencing profiles mapped to the human protein-protein interactome network. We investigate whole-exome sequencing and transcriptome profiles from ~5,000 patients across 15 cancer types from The Cancer Genome Atlas. We show that GPSnet-predicted disease modules can predict drug responses and prioritize new indications for 140 approved drugs. Importantly, we experimentally validate that an approved cardiac arrhythmia and heart failure drug, ouabain, shows potential antitumor activities in lung adenocarcinoma by uniquely targeting a HIF1α/LEO1-mediated cell metabolism pathway. In summary, GPSnet offers a network-based, in silico drug repurposing framework for more efficacious therapeutic selections.

Network Analysis of UBE3A/E6AP-Associated Proteins Provides Connections to Several Distinct Cellular Processes.

Perturbations in activity and dosage of the UBE3A ubiquitin-ligase have been linked to Angelman syndrome and autism spectrum disorders. UBE3A was initially identified as the cellular protein hijacked by the human papillomavirus E6 protein to mediate the ubiquitylation of p53, a function critical to the oncogenic potential of these viruses. Although a number of substrates have been identified, the normal cellular functions and pathways affected by UBE3A are largely unknown. Previously, we showed that UBE3A associates with HERC2, NEURL4, and MAPK6/ERK3 in a high-molecular-weight complex of unknown function that we refer to as the HUN complex (HERC2, UBE3A, and NEURL4). In this study, the combination of two complementary proteomic approaches with a rigorous network analysis revealed cellular functions and pathways in which UBE3A and the HUN complex are involved. In addition to finding new UBE3A-associated proteins, such as MCM6, SUGT1, EIF3C, and ASPP2, network analysis revealed that UBE3A-associated proteins are connected to several fundamental cellular processes including translation, DNA replication, intracellular trafficking, and centrosome regulation. Our analysis suggests that UBE3A could be involved in the control and/or integration of these cellular processes, in some cases as a component of the HUN complex, and also provides evidence for crosstalk between the HUN complex and CAMKII interaction networks. This study contributes to a deeper understanding of the cellular functions of UBE3A and its potential role in pathways that may be affected in Angelman syndrome, UBE3A-associated autism spectrum disorders, and human papillomavirus-associated cancers.

Domain-based prediction of the human isoform interactome provides insights into the functional impact of alternative splicing.

Alternative splicing is known to remodel protein-protein interaction networks ("interactomes"), yet large-scale determination of isoform-specific interactions remains challenging. We present a domain-based method to predict the isoform interactome from the reference interactome. First, we construct the domain-resolved reference interactome by mapping known domain-domain interactions onto experimentally-determined interactions between reference proteins. Then, we construct the isoform interactome by predicting that an isoform loses an interaction if it loses the domain mediating the interaction. Our prediction framework is of high-quality when assessed by experimental data. The predicted human isoform interactome reveals extensive network remodeling by alternative splicing. Protein pairs interacting with different isoforms of the same gene tend to be more divergent in biological function, tissue expression, and disease phenotype than protein pairs interacting with the same isoforms. Our prediction method complements experimental efforts, and demonstrates that integrating structural domain information with interactomes provides insights into the functional impact of alternative splicing.

HSP90 Shapes the Consequences of Human Genetic Variation.

HSP90 acts as a protein-folding buffer that shapes the manifestations of genetic variation in model organisms. Whether HSP90 influences the consequences of mutations in humans, potentially modifying the clinical course of genetic diseases, remains unknown. By mining data for >1,500 disease-causing mutants, we found a strong correlation between reduced phenotypic severity and a dominant (HSP90 ≥ HSP70) increase in mutant engagement by HSP90. Examining the cancer predisposition syndrome Fanconi anemia in depth revealed that mutant FANCA proteins engaged predominantly by HSP70 had severely compromised function. In contrast, the function of less severe mutants was preserved by a dominant increase in HSP90 binding. Reducing HSP90's buffering capacity with inhibitors or febrile temperatures destabilized HSP90-buffered mutants, exacerbating FA-related chemosensitivities. Strikingly, a compensatory FANCA somatic mutation from an "experiment of nature" in monozygotic twins both prevented anemia and reduced HSP90 binding. These findings provide one plausible mechanism for the variable expressivity and environmental sensitivity of genetic diseases.

Proteome-scale Binary Interactomics in Human Cells.

Because proteins are the main mediators of most cellular processes they are also prime therapeutic targets. Identifying physical links among proteins and between drugs and their protein targets is essential in order to understand the mechanisms through which both proteins themselves and the molecules they are targeted with act. Thus, there is a strong need for sensitive methods that enable mapping out these biomolecular interactions. Here we present a robust and sensitive approach to screen proteome-scale collections of proteins for binding to proteins or small molecules using the well validated MAPPIT (Mammalian Protein-Protein Interaction Trap) and MASPIT (Mammalian Small Molecule-Protein Interaction Trap) assays. Using high-density reverse transfected cell microarrays, a close to proteome-wide collection of human ORF clones can be screened for interactors at high throughput. The versatility of the platform is demonstrated through several examples. With MAPPIT, we screened a 15k ORF library for binding partners of RNF41, an E3 ubiquitin protein ligase implicated in receptor sorting, identifying known and novel interacting proteins. The potential related to the fact that MAPPIT operates in living human cells is illustrated in a screen where the protein collection is scanned for interactions with the glucocorticoid receptor (GR) in its unliganded versus dexamethasone-induced activated state. Several proteins were identified the interaction of which is modulated upon ligand binding to the GR, including a number of previously reported GR interactors. Finally, the screening technology also enables detecting small molecule target proteins, which in many drug discovery programs represents an important hurdle. We show the efficiency of MASPIT-based target profiling through screening with tamoxifen, a first-line breast cancer drug, and reversine, an investigational drug with interesting dedifferentiation and antitumor activity. In both cases, cell microarray screens yielded known and new potential drug targets highlighting the utility of the technology beyond fundamental biology.

The transcription factor ERG recruits CCR4-NOT to control mRNA decay and mitotic progression.

Control of mRNA levels, a fundamental aspect in the regulation of gene expression, is achieved through a balance between mRNA synthesis and decay. E26-related gene (Erg) proteins are canonical transcription factors whose previously described functions are confined to the control of mRNA synthesis. Here, we report that ERG also regulates gene expression by affecting mRNA stability and identify the molecular mechanisms underlying this function in human cells. ERG is recruited to mRNAs via interaction with the RNA-binding protein RBPMS, and it promotes mRNA decay by binding CNOT2, a component of the CCR4-NOT deadenylation complex. Transcriptome-wide mRNA stability analysis revealed that ERG controls the degradation of a subset of mRNAs highly connected to Aurora signaling, whose decay during S phase is necessary for mitotic progression. Our data indicate that control of gene expression by mammalian transcription factors may follow a more complex scheme than previously anticipated, integrating mRNA synthesis and degradation.

MECP2 Is a Frequently Amplified Oncogene with a Novel Epigenetic Mechanism That Mimics the Role of Activated RAS in Malignancy.

UNLABELLED: An unbiased genome-scale screen for unmutated genes that drive cancer growth when overexpressed identified methyl cytosine-guanine dinucleotide (CpG) binding protein 2 (MECP2) as a novel oncogene. MECP2 resides in a region of the X-chromosome that is significantly amplified across 18% of cancers, and many cancer cell lines have amplified, overexpressed MECP2 and are dependent on MECP2 expression for growth. MECP2 copy-number gain and RAS family member alterations are mutually exclusive in several cancer types. The MECP2 splicing isoforms activate the major growth factor pathways targeted by activated RAS, the MAPK and PI3K pathways. MECP2 rescued the growth of a KRAS(G12C)-addicted cell line after KRAS downregulation, and activated KRAS rescues the growth of an MECP2-addicted cell line after MECP2 downregulation. MECP2 binding to the epigenetic modification 5-hydroxymethylcytosine is required for efficient transformation. These observations suggest that MECP2 is a commonly amplified oncogene with an unusual epigenetic mode of action. SIGNIFICANCE: MECP2 is a commonly amplified oncogene in human malignancies with a unique epigenetic mechanism of action. Cancer Discov; 6(1); 45-58. ©2015 AACR.This article is highlighted in the In This Issue feature, p. 1.

Protein domain-level landscape of cancer-type-specific somatic mutations.

Identifying driver mutations and their functional consequences is critical to our understanding of cancer. Towards this goal, and because domains are the functional units of a protein, we explored the protein domain-level landscape of cancer-type-specific somatic mutations. Specifically, we systematically examined tumor genomes from 21 cancer types to identify domains with high mutational density in specific tissues, the positions of mutational hotspots within these domains, and the functional and structural context where possible. While hotspots corresponding to specific gain-of-function mutations are expected for oncoproteins, we found that tumor suppressor proteins also exhibit strong biases toward being mutated in particular domains. Within domains, however, we observed the expected patterns of mutation, with recurrently mutated positions for oncogenes and evenly distributed mutations for tumor suppressors. For example, we identified both known and new endometrial cancer hotspots in the tyrosine kinase domain of the FGFR2 protein, one of which is also a hotspot in breast cancer, and found new two hotspots in the Immunoglobulin I-set domain in colon cancer. Thus, to prioritize cancer mutations for further functional studies aimed at more precise cancer treatments, we have systematically correlated mutations and cancer types at the protein domain level.

Global Edgetic Rewiring in Cancer Networks.

Two recent papers in Cell interpret lists of cancer genomic alterations in terms of how mutations rewire interactome networks.

Selecting causal genes from genome-wide association studies via functionally coherent subnetworks.

Genome-wide association (GWA) studies have linked thousands of loci to human diseases, but the causal genes and variants at these loci generally remain unknown. Although investigators typically focus on genes closest to the associated polymorphisms, the causal gene is often more distal. Reliance on published work to prioritize candidates is biased toward well-characterized genes. We describe a 'prix fixe' strategy and software that uses genome-scale shared-function networks to identify sets of mutually functionally related genes spanning multiple GWA loci. Using associations from ∼100 GWA studies covering ten cancer types, our approach outperformed the common alternative strategy in ranking known cancer genes. As more GWA loci are discovered, the strategy will have increased power to elucidate the causes of human disease.

Systematic screening reveals a role for BRCA1 in the response to transcription-associated DNA damage.

BRCA1 is a breast and ovarian tumor suppressor. Given its numerous incompletely understood functions and the possibility that more exist, we performed complementary systematic screens in search of new BRCA1 protein-interacting partners. New BRCA1 functions and/or a better understanding of existing ones were sought. Among the new interacting proteins identified, genetic interactions were detected between BRCA1 and four of the interactors: TONSL, SETX, TCEANC, and TCEA2. Genetic interactions were also detected between BRCA1 and certain interactors of TONSL, including both members of the FACT complex. From these results, a new BRCA1 function in the response to transcription-associated DNA damage was detected. Specifically, new roles for BRCA1 in the restart of transcription after UV damage and in preventing or repairing damage caused by stabilized R loops were identified. These roles are likely carried out together with some of the newly identified interactors. This new function may be important in BRCA1 tumor suppression, since the expression of several interactors, including some of the above-noted transcription proteins, is repeatedly aberrant in both breast and ovarian cancers.