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There is great interest in developing selective protein kinase inhibitors by targeting allosteric sites, but these sites often involve protein-protein or protein-peptide interfaces that are very challenging to target with small molecules. Here we present a systematic approach to targeting a functionally conserved allosteric site on the protein kinase PDK1 called the PDK1-interacting fragment (PIF) tide-binding site, or PIF pocket. More than two dozen prosurvival and progrowth kinases dock a conserved peptide tail into this binding site, which recruits them to PDK1 to become activated. Using a site-directed chemical screen, we identified and chemically optimized ligand-efficient, selective, and cell-penetrant small molecules (molecular weight ~380 Da) that compete with the peptide docking motif for binding to PDK1. We solved the first high-resolution structure of a peptide docking motif (PIFtide) bound to PDK1 and mapped binding energy hot spots using mutational analysis. We then solved structures of PDK1 bound to the allosteric small molecules, which revealed a binding mode that remarkably mimics three of five hot-spot residues in PIFtide. These allosteric small molecules are substrate-selective PDK1 inhibitors when used as single agents, but when combined with an ATP-competitive inhibitor, they completely suppress the activation of the downstream kinases. This work provides a promising new scaffold for the development of high-affinity PIF pocket ligands, which may be used to enhance the anticancer activity of existing PDK1 inhibitors. Moreover, our results provide further impetus for exploring the helix aC patches of other protein kinases as potential therapeutic targets even though they involve protein-protein interfaces.

There is significant interest in identifying and characterizing allosteric sites in enzymes such as protein kinases both for understanding allosteric mechanisms as well as for drug discovery. Here, we apply a site-directed technology, disulfide trapping, to interrogate structurally and functionally how an allosteric site on the Ser/Thr kinase, 3-phosphoinositide-dependent kinase 1 (PDK1)--the PDK1-interacting-fragment (PIF) pocket--is engaged by an activating peptide motif on downstream substrate kinases (PIFtides) and by small molecule fragments. By monitoring pairwise disulfide conjugation between PIFtide and PDK1 cysteine mutants, we defined the PIFtide binding orientation in the PIF pocket of PDK1 and assessed subtle relationships between PIFtide positioning and kinase activation. We also discovered a variety of small molecule fragment disulfides (< 300 Da) that could either activate or inhibit PDK1 by conjugation to the PIF pocket, thus displaying greater functional diversity than is displayed by PIFtides conjugated to the same sites. Biochemical data and three crystal structures provided insight into the mechanism of action of the best fragment activators and inhibitors. These studies show that disulfide trapping is useful for characterizing allosteric sites on kinases and that a single allosteric site on a protein kinase can be exploited for both activation and inhibition by small molecules.

Approved antibody-drug conjugates (ADCs) for HER2-positive breast cancer include trastuzumab emtansine and trastuzumab deruxtecan. To develop a differentiated HER2 ADC, we chose an antibody that does not compete with trastuzumab or pertuzumab for binding, conjugated to a reduced potency PBD (pyrrolobenzodiazepine) dimer payload. PBDs are potent cytotoxic agents that alkylate and cross-link DNA. In our study, the PBD dimer is modified to alkylate, but not cross-link DNA. This HER2 ADC, DHES0815A, demonstrates in vivo efficacy in models of HER2-positive and HER2-low cancers and is well-tolerated in cynomolgus monkey safety studies. Mechanisms of action include induction of DNA damage and apoptosis, activity in non-dividing cells, and bystander activity. A dose-escalation study (ClinicalTrials.gov: NCT03451162) in patients with HER2-positive metastatic breast cancer, with the primary objective of evaluating the safety and tolerability of DHES0815A and secondary objectives of characterizing the pharmacokinetics, objective response rate, duration of response, and formation of anti-DHES0815A antibodies, is reported herein. Despite early signs of anti-tumor activity, patients at higher doses develop persistent, non-resolvable dermal, ocular, and pulmonary toxicities, which led to early termination of the phase 1 trial. Antibody drug conjugates (ADCs) with pyrrolobenzodiazepine (PBD) payloads are promising cancer therapeutics but are limited by toxicity. Here, the authors develop a HER2-targeted ADC (DHES0815A) with a reduced potency PBD payload that demonstrated promising preclinical efficacy and nonhuman primate tolerability, but culminated in a phase I clinical trial in patients with metastatic breast cancer which was terminated due to toxicity.

Recent single-cell studies of cancer in both mice and humans have identified the emergence of a myofibroblast population specifically marked by the highly restricted leucine-rich-repeat-containing protein 15 (LRRC15) 1 – 3 . However, the molecular signals that underlie the development of LRRC15 + cancer-associated fibroblasts (CAFs) and their direct impact on anti-tumour immunity are uncharacterized. Here in mouse models of pancreatic cancer, we provide in vivo genetic evidence that TGFβ receptor type 2 signalling in healthy dermatopontin + universal fibroblasts is essential for the development of cancer-associated LRRC15 + myofibroblasts. This axis also predominantly drives fibroblast lineage diversity in human cancers. Using newly developed Lrrc15– diphtheria toxin receptor knock-in mice to selectively deplete LRRC15 + CAFs, we show that depletion of this population markedly reduces the total tumour fibroblast content. Moreover, the CAF composition is recalibrated towards universal fibroblasts. This relieves direct suppression of tumour-infiltrating CD8 + T cells to enhance their effector function and augments tumour regression in response to anti-PDL1 immune checkpoint blockade. Collectively, these findings demonstrate that TGFβ-dependent LRRC15 + CAFs dictate the tumour-fibroblast setpoint to promote tumour growth. These cells also directly suppress CD8 + T cell function and limit responsiveness to checkpoint blockade. Development of treatments that restore the homeostatic fibroblast setpoint by reducing the population of pro-disease LRRC15 + myofibroblasts may improve patient survival and response to immunotherapy. LRRC15-positive cancer-associated fibroblasts constitute a pivotal axis in tumorigenesis and are potential therapeutic targets to improve responses to immune checkpoint blockade.

Tau is a hallmark pathology of Alzheimer’s disease, and animal models have suggested that tau spreads from cell to cell through neuronal connections, facilitated by β -amyloid (A β ). We test this hypothesis in humans using an epidemic spreading model (ESM) to simulate tau spread, and compare these simulations to observed patterns measured using tau-PET in 312 individuals along Alzheimer’s disease continuum. Up to 70% of the variance in the overall spatial pattern of tau can be explained by our model. Surprisingly, the ESM predicts the spatial patterns of tau irrespective of whether brain A β is present, but regions with greater A β burden show greater tau than predicted by connectivity patterns, suggesting a role of A β in accelerating tau spread. Altogether, our results provide evidence in humans that tau spreads through neuronal communication pathways even in normal aging, and that this process is accelerated by the presence of brain A β . The tau protein is theorized to spread transneuronally in Alzheimers disease, though this theory remains unproven in humans. Our simulations of epidemic-like protein spreading across human brain networks support this theory, and suggest the spreading dynamics are modified by β -amyloid

In Alzheimer’s diseases (AD), tau pathology is strongly associated with cognitive decline. Preclinical evidence suggests that tau spreads across connected neurons in an activity-dependent manner. Supporting this, cross-sectional AD studies show that tau deposition patterns resemble functional brain networks. However, whether higher functional connectivity is associated with higher rates of tau accumulation is unclear. Here, we combine resting-state fMRI with longitudinal tau-PET in two independent samples including 53 (ADNI) and 41 (BioFINDER) amyloid-biomarker defined AD subjects and 28 (ADNI) vs. 16 (BioFINDER) amyloid-negative healthy controls. In both samples, AD subjects show faster tau accumulation than controls. Second, in AD, higher fMRI-assessed connectivity between 400 regions of interest (ROIs) is associated with correlated tau-PET accumulation in corresponding ROIs. Third, we show that a model including baseline connectivity and tau-PET is associated with future tau-PET accumulation. Together, connectivity is associated with tau spread in AD, supporting the view of transneuronal tau propagation. Tau accumulation is associated with disease progression in Alzheimer’s disease. Here the authors use resting state fMRI and tau-PET to demonstrate that baseline connectivity in Alzheimer's disease is associated with tau spreading.

For optimal design of anti-amyloid-β (Aβ) and anti-tau clinical trials, we need to better understand the pathophysiological cascade of Aβ- and tau-related processes. Therefore, we set out to investigate how Aβ and soluble phosphorylated tau (p-tau) relate to the accumulation of tau aggregates assessed with PET and subsequent cognitive decline across the Alzheimer’s disease (AD) continuum. Using human cross-sectional and longitudinal neuroimaging and cognitive assessment data, we show that in early stages of AD, increased concentration of soluble CSF p-tau is strongly associated with accumulation of insoluble tau aggregates across the brain, and CSF p-tau levels mediate the effect of Aβ on tau aggregation. Further, higher soluble p-tau concentrations are mainly related to faster accumulation of tau aggregates in the regions with strong functional connectivity to individual tau epicenters. In this early stage, higher soluble p-tau concentrations is associated with cognitive decline, which is mediated by faster increase of tau aggregates. In contrast, in AD dementia, when Aβ fibrils and soluble p-tau levels have plateaued, cognitive decline is related to the accumulation rate of insoluble tau aggregates. Our data suggest that therapeutic approaches reducing soluble p-tau levels might be most favorable in early AD, before widespread insoluble tau aggregates. The interplay between amyloid and tau pathology in Alzheimer’s disease is still not well understood. Here, the authors show that amyloid-related increased in soluble p-tau is related to subsequent accumulation of tau aggregates and cognitive decline in early stage of the disease.

Causal Structure Discovery (CSD) is the problem of identifying causal relationships from large quantities of data through computational methods. With the limited ability of traditional association-based computational methods to discover causal relationships, CSD methodologies are gaining popularity. The goal of the study was to systematically examine whether (i) CSD methods can discover the known causal relationships from observational clinical data and (ii) to offer guidance to accurately discover known causal relationships. We used Alzheimer’s disease (AD), a complex progressive disease, as a model because the well-established evidence provides a “gold-standard” causal graph for evaluation. We evaluated two CSD methods, Fast Causal Inference (FCI) and Fast Greedy Equivalence Search (FGES) in their ability to discover this structure from data collected by the Alzheimer’s Disease Neuroimaging Initiative (ADNI). We used structural equation models (which is not designed for CSD) as control. We applied these methods under three scenarios defined by increasing amounts of background knowledge provided to the methods. The methods were evaluated by comparing the resulting causal relationships with the “gold standard” graph that was constructed from literature. Dedicated CSD methods managed to discover graphs that nearly coincided with the gold standard. For best results, CSD algorithms should be used with longitudinal data providing as much prior knowledge as possible.

Time-dependent data collected in studies of Alzheimer's disease usually has missing and irregularly sampled data points. For this reason time series methods which assume regular sampling cannot be applied directly to the data without a pre-processing step. In this paper we use a random forest to learn the relationship between pairs of data points at different time separations. The input vector is a summary of the time series history and it includes both demographic and non-time varying variables such as genetic data. To test the method we use data from the TADPOLE grand challenge, an initiative which aims to predict the evolution of subjects at risk of Alzheimer's disease using demographic, physical and cognitive input data. The task is to predict diagnosis, ADAS-13 score and normalised ventricles volume. While the competition proceeds, forecasting methods may be compared using a leaderboard dataset selected from the Alzheimer's Disease Neuroimaging Initiative (ADNI) and with standard metrics for measuring accuracy. For diagnosis, we find an mAUC of 0.82, and a classification accuracy of 0.73 compared with a benchmark SVM predictor which gives mAUC = 0.62 and BCA = 0.52. The results show that the method is effective and comparable with other methods.

The Flint, MI, water crisis brought significant suffering to the primarily Black community, including outbreaks of Legionnaires’ disease (6). A person’s race provides no biological basis for the observed health disparities, and to assert otherwise will slow the identification of solutions to these disparities. A recent analysis of research project (R01) proposals reviewed by the National Institutes of Health found that the community- and population-level research topics of interest to Black scientists placed them at a disadvantage for a fundable outcome and accounts for much of the reduced success rate of Black scientists (13). Numerous Black microbiologists have had significant impacts on topics that are particularly relevant to Black communities and beyond, including Drs. William Hinton, Ruth Moore, Jane Hinton, and many others.