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.

Ten-year responses of ground-dwelling spiders to retention harvest in the boreal forest.

The Ecosystem Management Emulating Natural Disturbances (EMEND) project tests the hypothesis that varying levels of green tree retention maintain and retain forest biodiversity better than conventional clear-cutting. We studied epigaeic spiders to assess biodiversity changes 2, 5, and 10 yr following a range of partial retention harvests (clear-cut, 10-75% retention) and unharvested controls in four boreal mixedwood cover types. A total of 56 371 adult spiders representing 220 species was collected using pitfall traps. Lasting effects on forest structure were proportional to harvest intensity. These changes strongly influenced spider richness, abundance, and species composition, as well as assemblage recovery. Distinctive assemblages were associated with disturbance level, especially with partial harvests (≤50% retention), and these were dominated by open-habitat species even 10 yr after harvest. Assemblages were more similar to those of controls in the highest (75%) retention treatment, but significant recovery toward the structure of pre-disturbance assemblages was not detected for any prescription in any cover type. Although early responses to retention harvest suggested positive effects on spider assemblages, these are better explained as lag effects after harvest because assemblages were less similar to those of unharvested controls 5 yr post-harvest, and only minor recovery was observed 10 yr following harvest. Retention of forest biodiversity decreased over time, especially in conifer stands and the lower (10-50%) retention treatments. Overall, retention harvests retained biodiversity and promoted landscape heterogeneity somewhat better than clear-cutting; however, there was a clear gradient of response and no retention "threshold" for conservation can be recommended on the basis of our data. Furthermore, results suggest that retention harvest prescriptions should be adjusted for cover type. We show that low retention ameliorated impacts in broadleaved forests characteristic of earlier stages in mixedwood succession, but only higher retention was associated with less impact in successionally older conifer forests. Although these short-term responses (10 yr) of spider assemblages support use of retention harvests, understanding the true conservation merit of these practices, relative to conventional approaches, requires evaluation over longer time scales, with work more focused on recovery of biodiversity than on its preservation after harvest.

Lipid clustering correlates with membrane curvature as revealed by molecular simulations of complex lipid bilayers.

Cell membranes are complex multicomponent systems, which are highly heterogeneous in the lipid distribution and composition. To date, most molecular simulations have focussed on relatively simple lipid compositions, helping to inform our understanding of in vitro experimental studies. Here we describe on simulations of complex asymmetric plasma membrane model, which contains seven different lipids species including the glycolipid GM3 in the outer leaflet and the anionic lipid, phosphatidylinositol 4,5-bisphophate (PIP2), in the inner leaflet. Plasma membrane models consisting of 1500 lipids and resembling the in vivo composition were constructed and simulations were run for 5 µs. In these simulations the most striking feature was the formation of nano-clusters of GM3 within the outer leaflet. In simulations of protein interactions within a plasma membrane model, GM3, PIP2, and cholesterol all formed favorable interactions with the model α-helical protein. A larger scale simulation of a model plasma membrane containing 6000 lipid molecules revealed correlations between curvature of the bilayer surface and clustering of lipid molecules. In particular, the concave (when viewed from the extracellular side) regions of the bilayer surface were locally enriched in GM3. In summary, these simulations explore the nanoscale dynamics of model bilayers which mimic the in vivo lipid composition of mammalian plasma membranes, revealing emergent nanoscale membrane organization which may be coupled both to fluctuations in local membrane geometry and to interactions with proteins.

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.

Exploring the interactions of JAK inhibitor and S1P receptor modulator drugs with the human gut microbiome: Implications for colonic drug delivery and inflammatory bowel disease.

The gut microbiota is a complex ecosystem, home to hundreds of bacterial species and a vast repository of enzymes capable of metabolising a wide range of pharmaceuticals. Several drugs have been shown to affect negatively the composition and function of the gut microbial ecosystem. Janus Kinase (JAK) inhibitors and Sphingosine-1-phosphate (S1P) receptor modulators are drugs recently approved for inflammatory bowel disease through an immediate release formulation and would potentially benefit from colonic targeted delivery to enhance the local drug concentration at the diseased site. However, their impact on the human gut microbiota and susceptibility to bacterial metabolism remain unexplored. With the use of calorimetric, optical density measurements, and metagenomics next-generation sequencing, we show that JAK inhibitors (tofacitinib citrate, baricitinib, filgotinib) have a minor impact on the composition of the human gut microbiota, while ozanimod exerts a significant antimicrobial effect, leading to a prevalence of the Enterococcus genus and a markedly different metabolic landscape when compared to the untreated microbiota. Moreover, ozanimod, unlike the JAK inhibitors, is the only drug subject to enzymatic degradation by the human gut microbiota sourced from six healthy donors. Overall, given the crucial role of the gut microbiome in health, screening assays to investigate the interaction of drugs with the microbiota should be encouraged for the pharmaceutical industry as a standard in the drug discovery and development process.

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.

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.

Preferential MGMT hypermethylation in SDH-deficient wild-type GIST.

AIMS: Wild-type gastrointestinal stromal tumours (wtGIST) are frequently caused by inherited pathogenic variants, or somatic alterations in the succinate dehydrogenase subunit genes (SDHx). Succinate dehydrogenase is a key enzyme in the citric acid cycle. SDH deficiency caused by SDHx inactivation leads to an accumulation of succinate, which inhibits DNA and histone demethylase enzymes, resulting in global hypermethylation. Epigenetic silencing of the DNA repair gene MGMT has proven utility as a positive predictor of the therapeutic efficacy of the alklyating drug temozolomide (TMZ) in tumours such as glioblastoma multiforme. The aim of this study was to examine MGMT promoter methylation status in a large cohort of GIST. METHODS: MGMT methylation analysis was performed on 65 tumour samples including 47 wtGIST (33 SDH-deficient wtGIST and 11 SDH preserved wtGIST) and 21 tyrosine kinase (TK) mutant GIST. RESULTS: MGMT promoter methylation was detected in 8 cases of SDH-deficient (dSDH) GIST but in none of the 14 SDH preserved wild-type GIST or 21 TK mutant GIST samples analysed. Mean MGMT methylation was significantly higher (p 0.0449) and MGMT expression significantly lower (p<0.0001) in dSDH wtGIST compared with TK mutant or SDH preserved GIST. No correlation was identified between SDHx subunit gene mutations or SDHC epimutation status and mean MGMT methylation levels. CONCLUSION: MGMT promoter hypermethylation occurs exclusively in a subset of dSDH wtGIST. Data from this study support testing of tumour MGMT promoter methylation in patients with dSDH wtGIST to identify those patients who may benefit from most from TMZ therapy.

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.

HOXA9 has the hallmarks of a biological switch with implications in blood cancers.

Blood malignancies arise from the dysregulation of haematopoiesis. The type of blood cell and the specific order of oncogenic events initiating abnormal growth ultimately determine the cancer subtype and subsequent clinical outcome. HOXA9 plays an important role in acute myeloid leukaemia (AML) prognosis by promoting blood cell expansion and altering differentiation; however, the function of HOXA9 in other blood malignancies is still unclear. Here, we highlight the biological switch and prognosis marker properties of HOXA9 in AML and chronic myeloproliferative neoplasms (MPN). First, we establish the ability of HOXA9 to stratify AML patients with distinct cellular and clinical outcomes. Then, through the use of a computational network model of MPN, we show that the self-activation of HOXA9 and its relationship to JAK2 and TET2 can explain the branching progression of JAK2/TET2 mutant MPN patients towards divergent clinical characteristics. Finally, we predict a connection between the RUNX1 and MYB genes and a suppressive role for the NOTCH pathway in MPN diseases.

The disambiguation of people names in biological collections.

Scientific collections have been built by people. For hundreds of years, people have collected, studied, identified, preserved, documented and curated collection specimens. Understanding who those people are is of interest to historians, but much more can be made of these data by other stakeholders once they have been linked to the people's identities and their biographies. Knowing who people are helps us attribute work correctly, validate data and understand the scientific contribution of people and institutions. We can evaluate the work they have done, the interests they have, the places they have worked and what they have created from the specimens they have collected. The problem is that all we know about most of the people associated with collections are their names written on specimens. Disambiguating these people is the challenge that this paper addresses. Disambiguation of people often proves difficult in isolation and can result in staff or researchers independently trying to determine the identity of specific individuals over and over again. By sharing biographical data and building an open, collectively maintained dataset with shared knowledge, expertise and resources, it is possible to collectively deduce the identities of individuals, aggregate biographical information for each person, reduce duplication of effort and share the information locally and globally. The authors of this paper aspire to disambiguate all person names efficiently and fully in all their variations across the entirety of the biological sciences, starting with collections. Towards that vision, this paper has three key aims: to improve the linking, validation, enhancement and valorisation of person-related information within and between collections, databases and publications; to suggest good practice for identifying people involved in biological collections; and to promote coordination amongst all stakeholders, including individuals, natural history collections, institutions, learned societies, government agencies and data aggregators.

Tumor-Derived Lactic Acid Modulates Activation and Metabolic Status of Draining Lymph Node Stroma.

Communication between tumors and the stroma of tumor-draining lymph nodes (TDLN) exists before metastasis arises, altering the structure and function of the TDLN niche. Transcriptional profiling of fibroblastic reticular cells (FRC), the dominant stromal population of lymph nodes, has revealed that FRCs in TDLNs are reprogrammed. However, the tumor-derived factors driving the changes in FRCs remain to be identified. Taking an unbiased approach, we have shown herein that lactic acid (LA), a metabolite released by cancer cells, was not only secreted by B16.F10 and 4T1 tumors in high amounts, but also that it was enriched in TDLNs. LA supported an upregulation of Podoplanin (Pdpn) and Thy1 and downregulation of IL7 in FRCs of TDLNs, making them akin to activated fibroblasts found at the primary tumor site. Furthermore, we found that tumor-derived LA altered mitochondrial function of FRCs in TDLNs. Thus, our results demonstrate a mechanism by which a tumor-derived metabolite connected with a low pH environment modulates the function of fibroblasts in TDLNs. How lymph node function is perturbed to support cancer metastases remains unclear. The authors show that tumor-derived LA drains to lymph nodes where it modulates the function of lymph node stromal cells, prior to metastatic colonization.

The NALCN channel regulates metastasis and nonmalignant cell dissemination.

We identify the sodium leak channel non-selective protein (NALCN) as a key regulator of cancer metastasis and nonmalignant cell dissemination. Among 10,022 human cancers, NALCN loss-of-function mutations were enriched in gastric and colorectal cancers. Deletion of Nalcn from gastric, intestinal or pancreatic adenocarcinomas in mice did not alter tumor incidence, but markedly increased the number of circulating tumor cells (CTCs) and metastases. Treatment of these mice with gadolinium-a NALCN channel blocker-similarly increased CTCs and metastases. Deletion of Nalcn from mice that lacked oncogenic mutations and never developed cancer caused shedding of epithelial cells into the blood at levels equivalent to those seen in tumor-bearing animals. These cells trafficked to distant organs to form normal structures including lung epithelium, and kidney glomeruli and tubules. Thus, NALCN regulates cell shedding from solid tissues independent of cancer, divorcing this process from tumorigenesis and unmasking a potential new target for antimetastatic therapies.

A botanical demonstration of the potential of linking data using unique identifiers for people.

Natural history collection data available digitally on the web have so far only made limited use of the potential of semantic links among themselves and with cross-disciplinary resources. In a pilot study, botanical collections of the Consortium of European Taxonomic Facilities (CETAF) have therefore begun to semantically annotate their collection data, starting with data on people, and to link them via a central index system. As a result, it is now possible to query data on collectors across different collections and automatically link them to a variety of external resources. The system is being continuously developed and is already in production use in an international collection portal.