Lewis C. Cantley

Effects of refined carbohydrates on immune markers after weight loss on a very-low-carbohydrate diet: A randomized controlled feeding trial

This study explored the effects of three diets differing in the amount and type of carbohydrates on peripheral immune markers. After a 15% weight loss with a very-low-carbohydrate diet (VLCD), participants were randomized to isocaloric diets: VLCD, high-carbohydrate diet with high starch content (HC-Starch), or high-carbohydrate diet with high sugar content (HC-Sugar). Changes in peripheral immune markers were assessed in 44 participants using multimodal analyses before randomization and after 10 weeks on the diet. In HC-Starch, cytometry by time of flight (CyTOF) revealed significant shifts in proportions of circulating natural killer (NK) cells and increased activation markers in NK cells, monocytes, T cells, dendritic cells, and neutrophils. In agreement, transcriptomics showed upregulation of immune and metabolic pathways with HC-Starch but reductions with HC-Sugar. Cytokine analysis and mouse experiments suggested that increased adipsin and complement activation could underlie these changes. Following weight loss with VLCD, starch-rich diets serve as an unrecognized driver of inflammation. This study was registered at ClinicalTrials.gov: NCT03394664.

Proteogenomic analysis of pediatric and AYA high-grade glioma reveals age-dependent biology, female-male differences, and kinase targets

High-grade gliomas (HGGs) in children and adolescents and young adults (AYA) exhibit distinct biology across the neurodevelopmental spectrum. To dissect tumor-intrinsic molecular characteristics independent of developmental variation, we perform comprehensive proteogenomic analyses of tumors from 112 HGG patients aged 0-40 years. Our multi-omics analysis identifies two AYA subgroups-adolescents (aged 15-26 years) and young adults (aged 26-40 years)-with distinct molecular profiles and survival outcomes. Tumor-normal comparisons and survival modeling highlight roles of oxidative phosphorylation and neuronal system biology in glioma progression. Causal network analysis and cell line studies provide a rationale for personalized therapies targeting candidate kinases, such as CDK8. Survival modeling, clustering, and immune-landscape analyses identify proteins, post-translational modifications, and immune signatures linked to outcomes and reveal clinically relevant differences between male and female patients.

Intestinal fructose metabolism drives unsaturated fat absorption and synergizes with GLP-1 receptor agonism to promote weight loss

High-fat, high-sucrose (HFHS) diets are established risk factors for obesity. In the intestine, sucrose is hydrolyzed into glucose and fructose, with fructose being taken up by epithelial cells and phosphorylated by ketohexokinase (KHK). We hypothesized that KHK is required for the obesogenic effects of HFHS diets and performed genetic and pharmacologic experiments in mice using diet-induced obesity (DIO) models. We show that genetic loss of KHK prevents HFHS-induced weight gain and intestinal villus elongation. Moreover, pharmacologic inhibition of KHK (KHKi) promotes weight and fat loss during continued HFHS feeding in DIO mice and enhances weight loss and weight maintenance during and after incretin-mimetic therapy. The anti-obesogenic effects of KHKi were associated with delayed intestinal lipid absorption, reprogramming of lipid metabolism in the distal intestinal epithelium, and reduced absorption of unsaturated dietary fats. Together, these findings identify fructose metabolism as a key regulator of intestinal lipid handling and suggest that fructose promotes obesity, in part, by enhancing intestinal lipid absorption and metabolism.

Very low-carbohydrate ketogenic diet in treatment-naïve women with endometrial cancer and overweight: a randomized feasibility study

Sex specific disruptions in PKCγ signaling in a mouse model of Spinocerebellar Ataxia Type 14

The Kinase Library: An Unbiased Atlas of the Human Kinome and Its Cancer Applications

Targeting Metabolism in BRCA-Deficient Tumors: Insights from Cancer Genome Atlas Analysis

PTEN Loss Promotes PI3Kβ Phosphorylation and EPHA2/SRC/p-PI3KβY962 Complex Assembly to Drive Tumorigenesis

Loss of the tumor-suppressor PTEN drives cancer progression and therapeutic resistance, yet no targeted therapies exist for PTEN-deficient tumors. In this study, we identify a critical druggable mechanism in which PTEN loss induces PI3Kβ phosphorylation for tumorigenesis. Using the BioID interactome, we uncovered a phosphorylation-dependent PI3Kβ-EPHA2 interaction in PTEN-null cells, driven by p-PI3KβY962. PTEN functions as a tyrosine phosphatase that normally dephosphorylates p-PI3KβY962. In PTEN-deficient contexts, enhanced p-PI3KβY962 forms a complex with EPHA2 and SRC, in which both kinases contribute to PI3Kβ phosphorylation, activating oncogenic pERK/c-MYC and pAKT pathways. We developed a selective p-PI3KβY962 antibody detecting p-PI3KβY962 in PTEN-deficient tumors across preclinical models and clinical tumor specimens. Disrupting p-PI3KβY962 suppressed tumor growth in multiple PTEN-null models. Dasatinib, an FDA-approved SRC/EPHA2 inhibitor, effectively reduced p-PI3KβY962 and inhibited tumor progression in PTEN-null but not PTEN wild-type tumors. These findings establish p-PI3KβY962 as a druggable target and biomarker for developing targeted therapy in PTEN-deficient cancers beyond conventional PI3K kinase inhibition. SIGNIFICANCE: We revealed a critical new mechanism that PTEN loss induces PI3Kβ phosphorylation and EPHA2/SRC/p-PI3KβY962 complex signaling to drive tumorigenesis. This work directs pharmaceutical development of p-PI3KβY962 inhibitors and biomarker-driven clinical trials repurposing dasatinib for PTEN-deficient solid tumor treatment, with potential to significantly improve outcomes of broad patients with PTEN-deficient tumors.

A Structure-Guided Kinase-Transcription Factor Interactome Atlas Reveals Docking Landscapes of the Kinome

Abstract B004: EMT-associated integrin signaling drives resistance to RAS-GTP inhibition in pancreatic cancer

Structural Identification of Major Molecular Determinants for Phosphotyrosine Recognition in Tyrosine Kinases Reveals Tumour Promoting and Suppressive Functions

Protein tyrosine kinases activate signaling pathways by catalyzing the phosphorylation of tyrosine residues in their substrates. Mounting evidence suggests that, in addition to recognizing phosphorylated tyrosine (pTyr) residues through specific phosphobinding modules, many protein kinases selectively recognize pTyr directly adjacent to the tyrosine residue they phosphorylate and catalyze the formation of twin pTyr-pTyr sites. Here, we demonstrate the importance of this phosphopriming-driven twin pTyr signaling in promoting cell cycle progression through the cell cycle-inhibitory protein p27 Kip1 . We identify, structurally resolve, and tune two distinct molecular determinants driving the selective recognition of pTyr directly N- and C-terminal to the target phospho-acceptor tyrosine site. We further show structural and biochemical conservation in this recognition, and identify cancer-associated alterations to these determinants that are unable to recognize phosphoprimed substrates. Finally, using an in vivo mouse model of leukemia we show that Bcr-Abl mutants unable to recognize phosphoprimed substrates paradoxically result in enhanced tumor development and progression. These data indicate that Bcr-Abl, like other proto-oncogenes such as Ras or Myc, engages both pro- and anti-oncogenic programs – but in the case of Bcr-Abl, this is accomplished through a mechanism involving traditional and phosphoprimed substrate recognition.

Comprehensive evaluation of phosphoproteomic-based kinase activity inference

Kinases regulate cellular processes and are essential for understanding cellular function and disease. To investigate the regulatory state of a kinase, numerous methods have been developed to infer kinase activities from phosphoproteomics data using kinase-substrate libraries. However, few phosphorylation sites can be attributed to an upstream kinase in these libraries, limiting the scope of kinase activity inference. Moreover, inferred activities vary across methods, necessitating evaluation for accurate interpretation. Here, we present benchmarKIN, an R package enabling comprehensive evaluation of kinase activity inference methods. Alongside classical perturbation experiments, benchmarKIN introduces a tumor-based benchmarking approach utilizing multi-omics data to identify highly active or inactive kinases. We used benchmarKIN to evaluate kinase-substrate libraries, inference algorithms and the potential of adding predicted kinase-substrate interactions to overcome the coverage limitations. Our evaluation shows most computational methods perform similarly, but the choice of library impacts the inferred activities with a combination of manually curated libraries demonstrating superior performance in recapitulating kinase activities. Additionally, in the tumor-based evaluation, adding predicted targets from NetworKIN further boosts the performance. We then demonstrate how kinase activity inference aids characterize kinase inhibitor responses in cell lines. Overall, benchmarKIN helps researchers to select reliable methods for identifying deregulated kinases.

Multi-node inhibition targeting mTORC1, mTORC2 and PI3Kα potently inhibits the PI3K/AKT/mTOR pathway in endometrial and breast cancer models

BACKGROUND: While PI3K/AKT/mTOR signalling plays a critical role in cancer, targeting this pathway with single node inhibitors has limited efficacy due to several known factors such as pathway feedback reactivation, co-occurring pathway mutations, and systemic glucose dysregulation leading to hyperinsulinemia. While multi-node inhibition approaches have shown promising clinical efficacy, they require further mechanistic characterisation. METHODS: Using models of endometrial and breast cancer, we evaluated the efficacy of a multi-node PI3K/AKT/mTOR pathway inhibitor approach utilising the dual mTORC1/mTORC2 inhibitor sapanisertib, PI3Kα inhibitor serabelisib and an insulin-supressing diet. Pathway signalling inhibition versus a range of single-node inhibitors was measured via S6, AKT and 4E-BP1 phosphorylation. RESULTS: The serabelisib-sapanisertib combination more effectively suppressed PI3K/AKT/mTOR pathway signalling, particularly 4E-BP1, than single-node inhibitors, including alpelisib, capivasertib, inavolisib, everolimus and mutant-specific PI3K inhibitors RLY-2608 and STX-478. Serabelisib plus sapanisertib combined effectively with a range of other therapeutics, such as chemotherapies, hormone targeted therapies and CDK4/6 inhibitors. In xenograft models, sapanisertib, serabelisib plus paclitaxel/insulin supressing diet achieved complete inhibition of tumour growth/tumour regression. CONCLUSION: Multi-node PI3K/AKT/mTOR pathway inhibition with serabelisib, sapanisertib and ISD is highly effective in preclinical models of endometrial and breast cancer, supporting continued clinical development in these and other solid tumours.

An atlas of bacterial serine-threonine kinases reveals functional diversity and key distinctions from eukaryotic kinases

Bacterial serine-threonine kinases (STKs) regulate diverse cellular processes associated with cell growth, virulence, and pathogenicity and are evolutionarily related to the druggable eukaryotic STKs. A deeper understanding of how bacterial STKs differ from their eukaryotic counterparts and how they have evolved to regulate diverse bacterial signaling functions is crucial for advancing the discovery and development of new antibiotic therapies. Here, we classified more than 300,000 bacterial STK sequences from the NCBI RefSeq nonredundant and UniProt protein databases into 35 canonical and seven pseudokinase families on the basis of the patterns of evolutionary constraints in the conserved catalytic domain and flanking regulatory domains. Through statistical comparisons, we identified features distinguishing bacterial STKs from eukaryotic STKs, including an arginine residue in a regulatory helix (C helix) that dynamically couples the ATP- and substrate-binding lobes of the kinase domain. Biochemical and peptide library screens demonstrated that evolutionarily constrained residues contributed to substrate specificity and kinase activation in the Mycobacterium tuberculosis kinase PknB. Together, these findings open previously unidentified avenues for investigating bacterial STK functions in cellular signaling and for developing selective bacterial STK inhibitors.

Cell-intrinsic insulin signaling defects in human iPS cell–derived hepatocytes in type 2 diabetes

Hepatic insulin resistance is central to type 2 diabetes (T2D) and metabolic syndrome, but defining the molecular basis of this defect in humans is challenging because of limited tissue access. Utilizing inducible pluripotent stem cells differentiated into hepatocytes from control individuals and patients with T2D and liquid chromatography with tandem mass spectrometry-based (LC-MS/MS-based) phosphoproteomics analysis, we identified a large network of cell-intrinsic alterations in signaling in T2D. Over 300 phosphosites showed impaired or reduced insulin signaling, including losses in the classical insulin-stimulated PI3K/AKT cascade and their downstream targets. In addition, we identified over 500 phosphosites of emergent, i.e., new or enhanced, signaling. These occurred on proteins involved in the Rho-GTPase pathway, RNA metabolism, vesicle trafficking, and chromatin modification. Kinome analysis indicated that the impaired phosphorylation sites represented reduced actions of AKT2/3, PKCθ, CHK2, PHKG2, and/or STK32C kinases. By contrast, the emergent phosphorylation sites were predicted to be mediated by increased action of the Rho-associated kinases 1 and 2 (ROCK1/2), mammalian STE20-like protein kinase 4 (MST4), and/or branched-chain α-ketoacid dehydrogenase kinase (BCKDK). Inhibiting ROCK1/2 activity in T2D induced pluripotent stem cell-derived hepatocytes restored some of the alterations in insulin action. Thus, insulin resistance in the liver in T2D did not simply involve a loss of canonical insulin signaling but the also appearance of new phosphorylations representing a change in the balance of multiple kinases. Together, these led to altered insulin action in the liver and identified important targets for the therapy of hepatic insulin resistance.

Precision proteogenomics reveals pan-cancer impact of germline variants

We investigate the impact of germline variants on cancer patients' proteomes, encompassing 1,064 individuals across 10 cancer types. We introduced an approach, "precision peptidomics," mapping 337,469 coding germline variants onto peptides from patients' mass spectrometry data, revealing their potential impact on post-translational modifications, protein stability, allele-specific expression, and protein structure by leveraging the relevant protein databases. We identified rare pathogenic and common germline variants in cancer genes potentially affecting proteomic features, including variants altering protein abundance and structure and variants in kinases (ERBB2 and MAP2K2) impacting phosphorylation. Precision peptidome analysis predicted destabilizing events in signal-regulatory protein alpha (SIRPA) and glial fibrillary acid protein (GFAP), relevant to immunomodulation and glioblastoma diagnostics, respectively. Genome-wide association studies identified quantitative trait loci for gene expression and protein levels, spanning millions of SNPs and thousands of proteins. Polygenic risk scores correlated with distal effects from risk variants. Our findings emphasize the contribution of germline genetics to cancer heterogeneity and high-throughput precision peptidomics.

Deciphering the dark cancer phosphoproteome using machine-learned co-regulation of phosphosites

Mass spectrometry-based phosphoproteomics offers a comprehensive view of protein phosphorylation, yet our limited knowledge about the regulation and function of most phosphosites hampers the extraction of meaningful biological insights. To address this challenge, we integrate machine learning with phosphoproteomic data from 1195 tumor specimens spanning 11 cancer types to construct CoPheeMap, a network that maps the co-regulation of 26,280 phosphosites. By incorporating network features from CoPheeMap into a second machine learning model, namely CoPheeKSA, we achieve superior performance in predicting kinase-substrate associations. CoPheeKSA uncovers 24,015 associations between 9399 phosphosites and 104 serine/threonine kinases, shedding light on many unannotated phosphosites and understudied kinases. We validate the accuracy of these predictions using experimentally determined kinase-substrate specificities. Through the application of CoPheeMap and CoPheeKSA to phosphosites with high computationally predicted functional significance and those associated with cancer, we demonstrate their effectiveness in systematically elucidating phosphosites of interest. These analyses unveil dysregulated signaling processes in human cancer and identify understudied kinases as potential therapeutic targets. Phosphoproteomics data analysis is limited by poor phosphosite annotation. Here, the authors use machine learning with pan-cancer data to build a co-regulation network of phosphosites and a model for predicting kinase-substrate associations, providing a framework for systematic data interpretation.

PSKH1 kinase activity is differentially modulated via allosteric binding of Ca 2+ sensor proteins

Protein Serine Kinase H1 (PSKH1) was recently identified as a crucial factor in kidney development and is overexpressed in prostate, lung, and kidney cancers. However, little is known about PSKH1 regulatory mechanisms, leading to its classification as a “dark” kinase. Here, we used biochemistry and mass spectrometry to define PSKH1’s consensus substrate motif, protein interactors, and how interactors, including Ca 2+ sensor proteins, promote or suppress activity. Intriguingly, despite the absence of a canonical Calmodulin binding motif, Ca 2+ -Calmodulin activated PSKH1 while, in contrast, the ER-resident Ca 2+ sensor of the Cab45, Reticulocalbin, Erc55, Calumenin (CREC) family, Reticulocalbin-3, suppressed PSKH1 catalytic activity. In addition to antagonistic regulation of the PSKH1 kinase domain by Ca 2+ sensing proteins, we identified UNC119B as a protein interactor that activates PSKH1 via direct engagement of the kinase domain. Our findings identify complementary allosteric mechanisms by which regulatory proteins tune PSKH1’s catalytic activity and raise the possibility that different Ca 2+ sensors may act more broadly to tune kinase activities by detecting and decoding extremes of intracellular Ca 2+ concentrations.

Atlas of the Bacterial Serine-Threonine Kinases expands the functional diversity of the kinome

Bacterial serine-threonine protein kinases (STKs) regulate diverse cellular processes associated with cell growth, virulence, and pathogenicity. They are evolutionarily related to the druggable eukaryotic STKs. However, an incomplete knowledge of how bacterial STKs differ from their eukaryotic counterparts and how they have diverged to regulate diverse bacterial signaling functions presents a bottleneck in targeting them for drug discovery efforts. Here, we classified over 300,000 bacterial STK sequences from the NCBI RefSeq non-redundant and UniProt protein databases into 35 canonical and seven non-canonical (pseudokinase) families based on the patterns of evolutionary constraints in the conserved catalytic domain and flanking regulatory domains. Through statistical comparisons, we identified distinguishing features of bacterial STKs, including a distinctive arginine residue in a regulatory helix (C-Helix) that dynamically couples ATP and substrate binding lobes of the kinase domain. Biochemical and peptide-library screens demonstrated that constrained residues contribute to substrate specificity and kinase activation in the Mycobacterium tuberculosis kinase PknB. Collectively, these findings open new avenues for investigating bacterial STK functions in cellular signaling and for the development of selective bacterial STK inhibitors.

PSKH1 kinase activity is differentially modulated via allosteric binding of Ca 2+ sensor proteins

Protein Serine Kinase H1 (PSKH1) was recently identified as a crucial factor in kidney development and is overexpressed in prostate, lung and kidney cancers. However, little is known about PSKH1 regulatory mechanisms, leading to its classification as a “dark” kinase. Here, we used biochemistry and mass spectrometry to define PSKH1’s consensus substrate motif, protein interactors, and how interactors, including Ca 2+ sensor proteins, promote or suppress activity. Intriguingly, despite the absence of a canonical Calmodulin binding motif, Ca 2+ -Calmodulin activated PSKH1 while, in contrast, the ER-resident Ca 2+ sensor of the CREC family, Reticulocalbin-3, suppressed PSKH1 catalytic activity. In addition to antagonistic regulation of the PSKH1 kinase domain by Ca 2+ sensing proteins, we identified UNC119B as a protein interactor that activates PSKH1 via direct engagement of the kinase domain. Our findings identify complementary allosteric mechanisms by which regulatory proteins tune PSKH1’s catalytic activity, and raise the possibility that different Ca 2+ sensors may act more broadly to tune kinase activities by detecting and decoding extremes of intracellular Ca 2+ concentrations.