Tumor-induced stromal reprogramming drives lymph node transformation.

Lymph node (LN) stromal cells, particularly fibroblastic reticular cells (FRCs), provide critical structural support and regulate immunity, tolerance and the transport properties of LNs. For many tumors, metastasis to the LNs is predictive of poor prognosis. However, the stromal contribution to the evolving microenvironment of tumor-draining LNs (TDLNs) remains poorly understood. Here we found that FRCs specifically of TDLNs proliferated in response to tumor-derived cues and that the network they formed was remodeled. Comparative transcriptional analysis of FRCs from non-draining LNs and TDLNs demonstrated reprogramming of key pathways, including matrix remodeling, chemokine and/or cytokine signaling, and immunological functions such as the recruitment, migration and activation of leukocytes. In particular, downregulation of the expression of FRC-derived chemokine CCL21 and cytokine IL-7 were accompanied by altered composition and aberrant localization of immune-cell populations. Our data indicate that following exposure to tumor-derived factors, the stroma of TDLNs adapts on multiple levels to exhibit features typically associated with immunosuppression.

Interpreting the effect of mutations to protein binding sites from large-scale genomic screens.

Predicting the functionality of missense mutations is extremely difficult. Large-scale genomic screens are commonly performed to identify mutational correlates or drivers of disease and treatment resistance, but interpretation of how these mutations impact protein function is limited. One such consequence of mutations to a protein is to impact its ability to bind and interact with partners or small molecules such as ATP, thereby modulating its function. Multiple methods exist for predicting the impact of a single mutation on protein-protein binding energy, but it is difficult in the context of a genomic screen to understand if these mutations with large impacts on binding are more common than statistically expected. We present a methodology for taking mutational data from large-scale genomic screens and generating functional and statistical insights into their role in the binding of proteins both with each other and their small molecule ligands. This allows a quantitative and statistical analysis to determine whether mutations impacting protein binding or ligand interactions are occurring more or less frequently than expected by chance. We achieve this by calculating the potential impact of any possible mutation and comparing an expected distribution to the observed mutations. This method is applied to examples demonstrating its ability to interpret mutations involved in protein-protein binding, protein-DNA interactions, and the evolution of therapeutic resistance.

Lung tumors with distinct p53 mutations respond similarly to p53 targeted therapy but exhibit genotype-specific statin sensitivity.

Lung adenocarcinoma accounts for ∼40% of lung cancers, the leading cause of cancer-related death worldwide, and current therapies provide only limited survival benefit. Approximately half of lung adenocarcinomas harbor mutations in TP53 (p53), making these mutants appealing targets for lung cancer therapy. As mutant p53 remains untargetable, mutant p53-dependent phenotypes represent alternative targeting opportunities, but the prevalence and therapeutic relevance of such effects (gain of function and dominant-negative activity) in lung adenocarcinoma are unclear. Through transcriptional and functional analysis of murine KrasG12D -p53null , -p53R172H (conformational), and -p53R270H (contact) mutant lung tumors, we identified genotype-independent and genotype-dependent therapeutic sensitivities. Unexpectedly, we found that wild-type p53 exerts a dominant tumor-suppressive effect on mutant tumors, as all genotypes were similarly sensitive to its restoration in vivo. These data show that the potential of p53 targeted therapies is comparable across all p53-deficient genotypes and may explain the high incidence of p53 loss of heterozygosity in mutant tumors. In contrast, mutant p53 gain of function and their associated vulnerabilities can vary according to mutation type. Notably, we identified a p53R270H -specific sensitivity to simvastatin in lung tumors, and the transcriptional signature that underlies this sensitivity was also present in human lung tumors, indicating that this therapeutic approach may be clinically relevant.

Heterogeneity of the cancer cell line metabolic landscape.

The unravelling of the complexity of cellular metabolism is in its infancy. Cancer-associated genetic alterations may result in changes to cellular metabolism that aid in understanding phenotypic changes, reveal detectable metabolic signatures, or elucidate vulnerabilities to particular drugs. To understand cancer-associated metabolic transformation, we performed untargeted metabolite analysis of 173 different cancer cell lines from 11 different tissues under constant conditions for 1,099 different species using mass spectrometry (MS). We correlate known cancer-associated mutations and gene expression programs with metabolic signatures, generating novel associations of known metabolic pathways with known cancer drivers. We show that metabolic activity correlates with drug sensitivity and use metabolic activity to predict drug response and synergy. Finally, we study the metabolic heterogeneity of cancer mutations across tissues, and find that genes exhibit a range of context specific, and more general metabolic control.

Cancer-causing BRCA2 missense mutations disrupt an intracellular protein assembly mechanism to disable genome maintenance.

Cancer-causing missense mutations in the 3418 amino acid BRCA2 breast and ovarian cancer suppressor protein frequently affect a short (∼340 residue) segment in its carboxyl-terminal domain (DBD). Here, we identify a shared molecular mechanism underlying their pathogenicity. Pathogenic BRCA2 missense mutations cluster in the DBD's helical domain (HD) and OB1-fold motifs, which engage the partner protein DSS1. Pathogenic - but not benign - DBD mutations weaken or abolish DSS1-BRCA2 assembly, provoking mutant BRCA2 oligomers that are excluded from the cell nucleus, and disable DNA repair by homologous DNA recombination (HDR). DSS1 inhibits the intracellular oligomerization of wildtype, but not mutant, forms of BRCA2. Remarkably, DSS1 expression corrects defective HDR in cells bearing pathogenic BRCA2 missense mutants with weakened, but not absent, DSS1 binding. Our findings identify a DSS1-mediated intracellular protein assembly mechanism that is disrupted by cancer-causing BRCA2 missense mutations, and suggest an approach for its therapeutic correction.

SARS-CoV-2 Variants Are Selecting for Spike Protein Mutations That Increase Protein Stability.

The emergence of variants of SARS-CoV-2 with mutations in their spike protein are a major cause for concern for the efficacy of vaccines and control of the pandemic. We show that mutations in the spike protein of SARS-CoV-2 are selecting for amino acid changes that result in a more thermodynamically stable protein than expected from background. We suggest that the computationally efficient analysis of mutational stability may aid in early screening of variants.

Computational Saturation Screen Reveals the Landscape of Mutations in Human Fumarate Hydratase.

Single amino acid substitutions within protein structures often manifest with clinical conditions in humans. The mutation of a single amino can significantly alter protein folding and stability, or change protein dynamics to influence function. The chemical engineering field has developed a large toolset for predicting the influence of point mutations with the aim of guiding the design of improved and more stable proteins. Here, we reverse this general protocol and adapt these tools for the prediction of damaging mutations within proteins. Mutations to fumarate hydratase (FH), an enzyme of the citric acid cycle, can lead to human diseases. The inactivation of FH by mutation causes leiomyomas and renal cell carcinoma by subsequent fumarate buildup and reduction in available malate. We present a scheme for accurately predicting the clinical effects of every possible mutation in FH by adaptation to a database of characterized damaging and benign mutations. Using energy prediction tools Rosetta and FoldX coupled with molecular dynamics simulations, we accurately predict individual mutations as well as mutational hotspots with a high disruptive capability in FH. Furthermore, through dynamic analysis, we find that hinge regions of the protein can be stabilized or destabilized by mutations, with mechanistic implications for the functional ability of the enzyme. Finally, we categorize all potential mutations in FH into functional groups, predicting which known mutations in the human population are loss of function, therefore having clinical implications, and validate our findings through metabolomics data of characterized human cell lines.

Probing the Solution Structure of IκB Kinase (IKK) Subunit γ and Its Interaction with Kaposi Sarcoma-associated Herpes Virus Flice-interacting Protein and IKK Subunit ß by EPR Spectroscopy.

Viral flice-interacting protein (vFLIP), encoded by the oncogenic Kaposi sarcoma-associated herpes virus (KSHV), constitutively activates the canonical nuclear factor κ-light-chain-enhancer of activated B cells (NF-κB) pathway. This is achieved through subversion of the IκB kinase (IKK) complex (or signalosome), which involves a physical interaction between vFLIP and the modulatory subunit IKKγ. Although this interaction has been examined both in vivo and in vitro, the mechanism by which vFLIP activates the kinase remains to be determined. Because IKKγ functions as a scaffold, recruiting both vFLIP and the IKKα/ß subunits, it has been proposed that binding of vFLIP could trigger a structural rearrangement in IKKγ conducive to activation. To investigate this hypothesis we engineered a series of mutants along the length of the IKKγ molecule that could be individually modified with nitroxide spin labels. Subsequent distance measurements using electron paramagnetic resonance spectroscopy combined with molecular modeling and molecular dynamics simulations revealed that IKKγ is a parallel coiled-coil whose response to binding of vFLIP or IKKß is localized twisting/stiffening and not large-scale rearrangements. The coiled-coil comprises N- and C-terminal regions with distinct registers accommodated by a twist: this structural motif is exploited by vFLIP, allowing it to bind and subsequently activate the NF-κB pathway. In vivo assays confirm that NF-κB activation by vFLIP only requires the N-terminal region up to the transition between the registers, which is located directly C-terminal of the vFLIP binding site.

Emergent stem cell homeostasis in the C. elegans germline is revealed by hybrid modeling.

The establishment of homeostasis among cell growth, differentiation, and apoptosis is of key importance for organogenesis. Stem cells respond to temporally and spatially regulated signals by switching from mitotic proliferation to asymmetric cell division and differentiation. Executable computer models of signaling pathways can accurately reproduce a wide range of biological phenomena by reducing detailed chemical kinetics to a discrete, finite form. Moreover, coordinated cell movements and physical cell-cell interactions are required for the formation of three-dimensional structures that are the building blocks of organs. To capture all these aspects, we have developed a hybrid executable/physical model describing stem cell proliferation, differentiation, and homeostasis in the Caenorhabditis elegans germline. Using this hybrid model, we are able to track cell lineages and dynamic cell movements during germ cell differentiation. We further show how apoptosis regulates germ cell homeostasis in the gonad, and propose a role for intercellular pressure in developmental control. Finally, we use the model to demonstrate how an executable model can be developed from the hybrid system, identifying a mechanism that ensures invariance in fate patterns in the presence of instability.

Primary and secondary dimer interfaces of the fibroblast growth factor receptor 3 transmembrane domain: characterization via multiscale molecular dynamics simulations.

Receptor tyrosine kinases are single-pass membrane proteins that form dimers within the membrane. The interactions of their transmembrane domains (TMDs) play a key role in dimerization and signaling. Fibroblast growth factor receptor 3 (FGFR3) is of interest as a G380R mutation in its TMD is the underlying cause of ~99% of the cases of achondroplasia, the most common form of human dwarfism. The structural consequences of this mutation remain uncertain: the mutation shifts the position of the TMD relative to the lipid bilayer but does not alter the association free energy. We have combined coarse-grained and all-atom molecular dynamics simulations to study the dimerization of wild-type, heterodimer, and mutant FGFR3 TMDs. The simulations reveal that the helices pack together in the dimer to form a flexible interface. The primary packing mode is mediated by a Gx3G motif. There is also a secondary dimer interface that is more highly populated in heterodimer and mutant configurations that may feature in the molecular mechanism of pathology. Both coarse-grained and atomistic simulations reveal a significant shift of the G380R mutant dimer TMD relative to the bilayer to allow interactions of the arginine side chain with lipid headgroup phosphates.

Understanding large scale sequencing datasets through changes to protein folding.

The expansion of high-quality, low-cost sequencing has created an enormous opportunity to understand how genetic variants alter cellular behaviour in disease. The high diversity of mutations observed has however drawn a spotlight onto the need for predictive modelling of mutational effects on phenotype from variants of uncertain significance. This is particularly important in the clinic due to the potential value in guiding clinical diagnosis and patient treatment. Recent computational modelling has highlighted the importance of mutation induced protein misfolding as a common mechanism for loss of protein or domain function, aided by developments in methods that make large computational screens tractable. Here we review recent applications of this approach to different genes, and how they have enabled and supported subsequent studies. We further discuss developments in the approach and the role for the approach in light of increasingly high throughput experimental approaches.

Large-scale computational modelling of the M1 and M2 synovial macrophages in rheumatoid arthritis.

Macrophages play an essential role in rheumatoid arthritis. Depending on their phenotype (M1 or M2), they can play a role in the initiation or resolution of inflammation. The M1/M2 ratio in rheumatoid arthritis is higher than in healthy controls. Despite this, no treatment targeting specifically macrophages is currently used in clinics. Thus, devising strategies to selectively deplete proinflammatory macrophages and promote anti-inflammatory macrophages could be a promising therapeutic approach. State-of-the-art molecular interaction maps of M1 and M2 macrophages in rheumatoid arthritis are available and represent a dense source of knowledge; however, these maps remain limited by their static nature. Discrete dynamic modelling can be employed to study the emergent behaviours of these systems. Nevertheless, handling such large-scale models is challenging. Due to their massive size, it is computationally demanding to identify biologically relevant states in a cell- and disease-specific context. In this work, we developed an efficient computational framework that converts molecular interaction maps into Boolean models using the CaSQ tool. Next, we used a newly developed version of the BMA tool deployed to a high-performance computing cluster to identify the models' steady states. The identified attractors are then validated using gene expression data sets and prior knowledge. We successfully applied our framework to generate and calibrate the M1 and M2 macrophage Boolean models for rheumatoid arthritis. Using KO simulations, we identified NFkB, JAK1/JAK2, and ERK1/Notch1 as potential targets that could selectively suppress proinflammatory macrophages and GSK3B as a promising target that could promote anti-inflammatory macrophages in rheumatoid arthritis.

SMAD4 and KCNQ3 alterations are associated with lymph node metastases in oesophageal adenocarcinoma.

Metastasis in oesophageal adenocarcinoma (OAC) is an important predictor of survival. Radiological staging is used to stage metastases in patients, and guide treatment selection, but is limited by the accuracy of the approach. Improvements in staging will lead to improved clinical decision making and patient outcomes. Sequencing studies on primary tumours and pre-cancerous tissue have revealed the mutational landscape of OAC, and increasingly cheap and widespread sequencing approaches offer the potential to improve staging assessment. In this work we present an analysis of lymph node metastases found by radiological and pathological sampling, identifying new roles of the genes SMAD4 and KCNQ3 in metastasis. Through transcriptomic analysis we find that both genes are associated with canonical Wnt pathway activity, but KCNQ3 is uniquely associated with changes in planar cell polaritiy associated with non-canonical Wnt signalling. We go on to validate our observations in KCNQ3 in cell line and xenograph systems, showing that overexpression of KCNQ3 reduces wound closure and the number of metastases observed. Our results suggest both genes as novel biomarkers of metastatic risk and offer new potential routes to drug targeting.

Mechanism of bacterial signal transduction revealed by molecular dynamics of Tsr dimers and trimers of dimers in lipid vesicles.

Bacterial chemoreceptors provide an important model for understanding signalling processes. In the serine receptor Tsr from E. coli, a binding event in the periplasmic domain of the receptor dimer causes a shift in a single transmembrane helix of roughly 0.15 nm towards the cytoplasm. This small change is propagated through the ≈ 22 nm length of the receptor, causing downstream inhibition of the kinase CheA. This requires interactions within a trimer of receptor dimers. Additionally, the signal is amplified across a 53,000 nm(2) array of chemoreceptor proteins, including ≈ 5,200 receptor trimers-of-dimers, at the cell pole. Despite a wealth of experimental data on the system, including high resolution structures of individual domains and extensive mutagenesis data, it remains uncertain how information is communicated across the receptor from the binding event to the downstream effectors. We present a molecular model of the entire Tsr dimer, and examine its behaviour using coarse-grained molecular dynamics and elastic network modelling. We observe a large bending in dimer models between the linker domain HAMP and coiled-coil domains, which is supported by experimental data. Models of the trimer of dimers, built from the dimer models, are more constrained and likely represent the signalling state. Simulations of the models in a 70 nm diameter vesicle with a biologically realistic lipid mixture reveal specific lipid interactions and oligomerisation of the trimer of dimers. The results indicate a mechanism whereby small motions of a single helix can be amplified through HAMP domain packing, to initiate large changes in the whole receptor structure.

Mutations observed in somatic evolution reveal underlying gene mechanisms.

Highly sensitive DNA sequencing techniques have allowed the discovery of large numbers of somatic mutations in normal tissues. Some mutations confer a competitive advantage over wild-type cells, generating expanding clones that spread through the tissue. Competition between mutant clones leads to selection. This process can be considered a large scale, in vivo screen for mutations increasing cell fitness. It follows that somatic missense mutations may offer new insights into the relationship between protein structure, function and cell fitness. We present a flexible statistical method for exploring the selection of structural features in data sets of somatic mutants. We show how this approach can evidence selection of specific structural features in key drivers in aged tissues. Finally, we show how drivers may be classified as fitness-enhancing and fitness-suppressing through different patterns of mutation enrichment. This method offers a route to understanding the mechanism of protein function through in vivo mutant selection.

Notch1 mutations drive clonal expansion in normal esophageal epithelium but impair tumor growth.

NOTCH1 mutant clones occupy the majority of normal human esophagus by middle age but are comparatively rare in esophageal cancers, suggesting NOTCH1 mutations drive clonal expansion but impede carcinogenesis. Here we test this hypothesis. Sequencing NOTCH1 mutant clones in aging human esophagus reveals frequent biallelic mutations that block NOTCH1 signaling. In mouse esophagus, heterozygous Notch1 mutation confers a competitive advantage over wild-type cells, an effect enhanced by loss of the second allele. Widespread Notch1 loss alters transcription but has minimal effects on the epithelial structure and cell dynamics. In a carcinogenesis model, Notch1 mutations were less prevalent in tumors than normal epithelium. Deletion of Notch1 reduced tumor growth, an effect recapitulated by anti-NOTCH1 antibody treatment. Notch1 null tumors showed reduced proliferation. We conclude that Notch1 mutations in normal epithelium are beneficial as wild-type Notch1 favors tumor expansion. NOTCH1 blockade may have therapeutic potential in preventing esophageal squamous cancer.

Somatic mutations in facial skin from countries of contrasting skin cancer risk.

The incidence of keratinocyte cancer (basal cell and squamous cell carcinomas of the skin) is 17-fold lower in Singapore than the UK1-3, despite Singapore receiving 2-3 times more ultraviolet (UV) radiation4,5. Aging skin contains somatic mutant clones from which such cancers develop6,7. We hypothesized that differences in keratinocyte cancer incidence may be reflected in the normal skin mutational landscape. Here we show that, compared to Singapore, aging facial skin from populations in the UK has a fourfold greater mutational burden, a predominant UV mutational signature, increased copy number aberrations and increased mutant TP53 selection. These features are shared by keratinocyte cancers from high-incidence and low-incidence populations8-13. In Singaporean skin, most mutations result from cell-intrinsic processes; mutant NOTCH1 and NOTCH2 are more strongly selected than in the UK. Aging skin in a high-incidence country has multiple features convergent with cancer that are not found in a low-risk country. These differences may reflect germline variation in UV-protective genes.

KCNQ potassium channels modulate Wnt activity in gastro-oesophageal adenocarcinomas.

Voltage-sensitive potassium channels play an important role in controlling membrane potential and ionic homeostasis in the gut and have been implicated in gastrointestinal (GI) cancers. Through large-scale analysis of 897 patients with gastro-oesophageal adenocarcinomas (GOAs) coupled with in vitro models, we find KCNQ family genes are mutated in ∼30% of patients, and play therapeutically targetable roles in GOA cancer growth. KCNQ1 and KCNQ3 mediate the WNT pathway and MYC to increase proliferation through resultant effects on cadherin junctions. This also highlights novel roles of KCNQ3 in non-excitable tissues. We also discover that activity of KCNQ3 sensitises cancer cells to existing potassium channel inhibitors and that inhibition of KCNQ activity reduces proliferation of GOA cancer cells. These findings reveal a novel and exploitable role of potassium channels in the advancement of human cancer, and highlight that supplemental treatments for GOAs may exist through KCNQ inhibitors.

How lipid headgroups sense the membrane environment: an application of ¹4N NMR.

The orientation of lipid headgroups may serve as a powerful sensor of electrostatic interactions in membranes. As shown previously by (2)H NMR measurements, the headgroup of phosphatidylcholine (PC) behaves like an electrometer and varies its orientation according to the membrane surface charge. Here, we explored the use of solid-state (14)N NMR as a relatively simple and label-free method to study the orientation of the PC headgroup in model membrane systems of varying composition. We found that (14)N NMR is sufficiently sensitive to detect small changes in headgroup orientation upon introduction of positively and negatively charged lipids and we developed an approach to directly convert the (14)N quadrupolar splittings into an average orientation of the PC polar headgroup. Our results show that inclusion of cholesterol or mixing of lipids with different length acyl chains does not significantly affect the orientation of the PC headgroup. In contrast, measurements with cationic (KALP), neutral (Ac-KALP), and pH-sensitive (HALP) transmembrane peptides show very systematic changes in headgroup orientation, depending on the amount of charge in the peptide side chains and on their precise localization at the interface, as modulated by varying the extent of hydrophobic peptide/lipid mismatch. Finally, our measurements suggest an unexpectedly strong preferential enrichment of the anionic lipid phosphatidylglycerol around the cationic KALP peptide in ternary mixtures with PC. We believe that these results are important for understanding protein/lipid interactions and that they may help parametrization of membrane properties in computational studies.

Coarse-grain simulations reveal movement of the synaptobrevin C-terminus in response to piconewton forces.

Fusion of neurosecretory vesicles with the plasma membrane is mediated by SNARE proteins, which transfer a force to the membranes. However, the mechanism by which this force transfer induces fusion pore formation is still unknown. The neuronal vesicular SNARE protein synaptobrevin 2 (syb2) is anchored in the vesicle membrane by a single C-terminal transmembrane (TM) helix. In coarse-grain molecular-dynamics simulations, self-assembly of the membrane occurred with the syb2 TM domain inserted, as expected from experimental data. The free-energy profile for the position of the syb2 membrane anchor in the membrane was determined using umbrella sampling. To predict the free-energy landscapes for a reaction pathway pulling syb2 toward the extravesicular side of the membrane, which is the direction of the force transfer from the SNARE complex, harmonic potentials were applied to the peptide in its unbiased position, pulling it toward new biased equilibrium positions. Application of piconewton forces to the extravesicular end of the TM helix in the simulation detached the synaptobrevin C-terminus from the vesicle's inner-leaflet lipid headgroups and pulled it deeper into the membrane. This C-terminal movement was facilitated and hindered by specific mutations in parallel with experimentally observed facilitation and inhibition of fusion. Direct application of such forces to the intravesicular end of the TM domain resulted in tilting motion of the TM domain through the membrane with an activation energy of ∼70 kJ/mol. The results suggest a mechanism whereby fusion pore formation is induced by movement of the charged syb2 C-terminus within the membrane in response to pulling and tilting forces generated by C-terminal zippering of the SNARE complex.