Despite decades of speculation that inhibiting endogenous insulin degradation might treat type-2 diabetes1, 2, and the identification of IDE (insulin-degrading enzyme) as a diabetes susceptibility gene3, 4, the relationship between the activity of the zinc metalloprotein IDE and glucose homeostasis remains unclear. Although Ide−/− mice have elevated insulin levels, they exhibit impaired, rather than improved, glucose tolerance that may arise from compensatory insulin signalling dysfunction5, 6. IDE inhibitors that are active in vivo are therefore needed to elucidate IDE’s physiological roles and to determine its potential to serve as a target for the treatment of diabetes. Here we report the discovery of a physiologically active IDE inhibitor identified from a DNA-templated macrocycle library. An X-ray structure of the macrocycle bound to IDE reveals that it engages a binding pocket away from the catalytic site, which explains its remarkable selectivity. Treatment of lean and obese mice with this inhibitor shows that IDE regulates the abundance and signalling of glucagon and amylin, in addition to that of insulin. Under physiological conditions that augment insulin and amylin levels, such as oral glucose administration, acute IDE inhibition leads to substantially improved glucose tolerance and slower gastric emptying. These findings demonstrate the feasibility of modulating IDE activity as a new therapeutic strategy to treat type-2 diabetes and expand our understanding of the roles of IDE in glucose and hormone regulation.

Protein tyrosine kinases are attractive drug targets because many human diseases are associated with deregulation of kinase activity. However, how the catalytic kinase domain integrates different signals and switches from an active to an inactive conformation remains incompletely understood. Here we identify an allosteric network of dynamically coupled amino acids in Src kinase that connects regulatory sites to the ATP- and substrate-binding sites. Surprisingly, reactants (ATP and peptide substrates) bind with negative cooperativity to Src kinase while products (ADP and phospho-peptide) bind with positive cooperativity. We confirm the molecular details of the signal relay through the allosteric network by biochemical studies. Experiments on two additional protein tyrosine kinases indicate that the allosteric network may be largely conserved among these enzymes. Our work provides new insights into the regulation of protein tyrosine kinases and establishes a potential conduit by which resistance mutations to ATP competitive kinase inhibitors can affect their activity.

Tissue necrosis as a consequence of ischemia-reperfusion injury and oxidative damage is a leading cause of permanent disability and death worldwide. The complete mechanism by which cells undergo necrosis upon oxidative stress is not understood. In response to an oxidative insult, wildtype p53 has been implicated as a central regulatory component of the mitochondrial permeability transition (mPT), triggering necrosis. This process is associated with cellular stabilization and translocation of p53 into the mitochondrial matrix. Here, we probe the mechanism by which p53 activates the key mPT regulator cyclophilin D (CypD). We explore the involvement of Trap1, an Hsp90-related mitochondrial matrix protein and member of the mitochondrial unfolded protein response (mtUPR), and its ability to suppress mPT in a p53-dependent manner. Our study finds that catalytically active CypD causes strong aggregation of wildtype p53 protein (both full length and isolated DNA binding domain) into amyloid-type fibrils in vitro. The responsible CypD residues for this activity were mapped by NMR to the active site amino acids R55, F60, F113 and W121. The data also present a new proline-isomerization assay for CypD by monitoring the aggregation of p53 as an indicator of CypD activity. Moreover, we find that inhibition of Trap1 by the mitochondria-specific HSP90 ATPase antagonist gamitrinib strongly sensitizes primary mouse embryonic fibroblasts (MEFs) to mPT and permeability transition pore (mPTP) opening in a p53- and CypD-dependent manner. We propose a mechanism by which influx of unfolded p53 into the mitochondrial matrix in response to oxidative stress indirectly activates the normally inhibited CypD by displacing it from Trap1 complexes. This activates CypD’s isomerase activity. Liberated CypD then isomerizes multiple proteins including p53 (causing p53 aggregation) and the structural components of the mPTP pore, inducing pore opening. This working model can now be tested in the future.

Liver cancer is a major cause of cancer mortality worldwide. Screening individuals at high-risk, including those with cirrhosis and viral hepatitis, provides an avenue for improved survival, but current screening methods are inadequate. In this study, we used whole-genome cell-free DNA fragmentome analyses to evaluate 724 individuals from the US, EU, or Hong Kong with hepatocellular carcinoma (HCC) or who were at average or high-risk for HCC. Using a machine learning model that incorporated multi-feature fragmentome data, the sensitivity for detecting cancer was 88% in an average risk population at 98% specificity, and 85% among high-risk individuals at 80% specificity. We validated these results in an independent population. cfDNA fragmentation changes reflected genomic and chromatin changes in liver cancer, including from transcription factor binding sites. These findings provide a biological basis for changes in cfDNA fragmentation in patients with liver cancer and provide an accessible approach for non-invasive cancer detection.

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Somatic mutations are a hallmark of tumorigenesis and may be useful for non-invasive diagnosis of cancer. We analyzed whole-genome sequencing data from 2,511 individuals in the Pan-Cancer Analysis of Whole Genomes (PCAWG) study as well as 489 individuals from four prospective cohorts and found distinct regional mutation type-specific frequencies in tissue and cell-free DNA from patients with cancer that were associated with replication timing and other chromatin features. A machine-learning model using genome-wide mutational profiles combined with other features and followed by CT imaging detected >90% of patients with lung cancer, including those with stage I and II disease. The fixed model was validated in an independent cohort, detected patients with cancer earlier than standard approaches and could be used to monitor response to therapy. This approach lays the groundwork for non-invasive cancer detection using genome-wide mutation features that may facilitate cancer screening and monitoring.

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Introduction: Ovarian cancer is the leading cause of death from gynecological related cancers worldwide. Most patients are diagnosed at late stages due to asymptomatic disease and lack of effective screening modalities. Additionally, in women with an ovarian mass the diagnosis of ovarian cancer can be challenging with many women having surgery only to discover a benign pathology. Liquid biopsies, including analyses of cell-free DNA (cfDNA) fragmentomes in the circulation, have shown promise for the early detection of cancer and may provide a useful avenue for detection of ovarian cancer. Methods: To evaluate cfDNA fragmentomes for detecting ovarian cancer, we assessed plasma from 507 women, including 128 with ovarian cancers comprising high grade serous, endometrioid, mucinous and clear cell subtypes, 48 with benign masses, and 223 without cancer, as well as a validation cohort of 108 women with (n=14) and without (n=94) ovarian cancers from a separate institution. We obtained cfDNA from each individual and performed low-coverage (1-2x) whole genome sequencing. The cfDNA fragmentome data were analyzed with our DELFI (DNA evaluation of fragments for early interception) approach optimized for high specificity. We used a cross-validated machine learning model, and the fixed DELFI model was evaluated in the external validation cohort. Results: Individuals with ovarian cancer had significantly higher DELFI scores than those without cancer (mean 0.59 vs 0.18, respectively, p < 0.0001) resulting in an AUC of 0.85 (95% CI = 0.80-0.90). DELFI was successful in identifying high-grade serous ovarian cancer across all stages, with sensitivities of 56%, 60%, 58% and 100% for stages I - IV, respectively, at 99% specificity. We further applied DELFI to evaluate women with ovarian masses in a prospective observational cohort (NL58253.031.16). Women with benign masses had DELFI scores lower than those with ovarian cancer (mean 0.23 vs 0.59, p< .0001) and were distinguished with an overall AUC of 0.80 (95% CI = 0.73-0.86). In the external validation cohort, women with cancer were distinguished from women without cancer with an AUC of 0.88 (95% CI = 0.72 - 1.0). At the DELFI score threshold with 99% specificity in the cross-validated cohort, the external validation cohort had specificity of 97% with an overall sensitivity of 79%. The cfDNA fragmentome profiles reflected chromosomal, chromatin, transcription factor binding site, and disease-specific pathway changes known to be altered in ovarian cancer. We are extending these efforts to over 1000 individuals with and without ovarian cancer and the integrated results will be presented. Conclusion: Overall, we demonstrate the utility of cfDNA fragmentomes for noninvasive detection of ovarian cancer. These results may provide a feasible approach for ovarian cancer screening and management of patients with ovarian masses. Citation Format: Akshaya V. Annapragada, Jamie E. Medina, Pien Lof, Dimitrios Mathios, Zachariah H. Foda, Michaël Noë, Sarah Short, Adrianna Bartolomucci, Daniel C. Bruhm, Euihye Jung, Jenna Canzoniero, Noushin Niknafs, Stephen Cristiano, Vilmos Adleff, Heather Symecko, Daan van de Broek, Stephen B. Baylin, Michael F. Press, Dennis Slamon, Gottfried Konecny, Susan Domchek, Ronny Drapkin, Jillian Phallen, Robert B. Scharpf, Christianne Lok, Victor E. Velculescu. Early detection of ovarian cancer using cell-free DNA fragmentomes [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 773.