Conditional Dependency of LP-184 on Prostaglandin Reductase 1 is Synthetic Lethal in Pancreatic Cancers with DNA Damage Repair Deficiencies.

The greater efficacy of DNA-damaging drugs for pancreatic adenocarcinoma (PDAC) relies on targeting cancer-specific vulnerabilities while sparing normal organs and tissues due to their inherent toxicities. We tested LP-184, a novel acylfulvene analog, for its activity in preclinical models of PDAC carrying mutations in the DNA damage repair (DDR) pathways. Cytotoxicity of LP-184 is solely dependent on prostaglandin reductase 1 (PTGR1), so that PTGR1 expression robustly correlates with LP-184 cytotoxicity in vitro and in vivo. Low-passage patient-derived PDAC xenografts with DDR deficiencies treated ex vivo are more sensitive to LP-184 compared with DDR-proficient tumors. Additional in vivo testing of PDAC xenografts for their sensitivity to LP-184 demonstrates marked tumor growth inhibition in models harboring pathogenic mutations in ATR, BRCA1, and BRCA2. Depletion of PTGR1, however, completely abrogates the antitumor effect of LP-184. Testing combinatorial strategies for LP-184 aimed at deregulation of nucleotide excision repair proteins ERCC3 and ERCC4 established synergy. Our results provide valuable biomarkers for clinical testing of LP-184 in a large subset of genetically defined characterized refractory carcinomas. High PTGR1 expression and deleterious DDR mutations are present in approximately one third of PDAC making these patients ideal candidates for clinical trials of LP-184.

Preclinical Efficacy of LP-184, a Tumor Site Activated Synthetic Lethal Therapeutic, in Glioblastoma.

PURPOSE: Glioblastoma (GBM) is the most common brain malignancy with median survival <2 years. Standard-of-care temozolomide has marginal efficacy in approximately 70% of patients due to MGMT expression. LP-184 is an acylfulvene-derived prodrug activated by the oxidoreductase PTGR1 that alkylates at N3-adenine, not reported to be repaired by MGMT. This article examines LP-184 efficacy against preclinical GBM models and identifies molecular predictors of LP-184 efficacy in clinical GBM. EXPERIMENTAL DESIGN: LP-184 effects on GBM cell viability and DNA damage were determined using cell lines, primary PDX-derived cells and patient-derived neurospheres. GBM cell sensitivities to LP-184 relative to temozolomide and MGMT expression were examined. Pharmacokinetics and CNS bioavailability were evaluated in mice with GBM xenografts. LP-184 effects on GBM xenograft growth and animal survival were determined. Machine learning, bioinformatic tools, and clinical databases identified molecular predictors of GBM cells and tumors to LP-184 responsiveness. RESULTS: LP-184 inhibited viability of multiple GBM cell isolates including temozolomide-resistant and MGMT-expressing cells at IC50 = approximately 22-310 nmol/L. Pharmacokinetics showed favorable AUCbrain/plasma and AUCtumor/plasma ratios of 0.11 (brain Cmax = 839 nmol/L) and 0.2 (tumor Cmax = 2,530 nmol/L), respectively. LP-184 induced regression of GBM xenografts and prolonged survival of mice bearing orthotopic xenografts. Bioinformatic analyses identified PTGR1 elevation in clinical GBM subtypes and associated LP-184 sensitivity with EGFR signaling, low nucleotide excision repair (NER), and low ERCC3 expression. Spironolactone, which induces ERCC3 degradation, decreased LP-184 IC50 3 to 6 fold and enhanced GBM xenograft antitumor responses. CONCLUSIONS: These results establish LP-184 as a promising chemotherapeutic for GBM with enhanced efficacy in intrinsic or spironolactone-induced TC-NER-deficient tumors.

Diagnostic Evaluation of Hypoglycemia Due To an Insulinoma in a Deployed Infantryman: Significance of Neuroglycopenia and the Role of the Military Health System.

Insulinoma, the prototype of endogenous hyperinsulinemic hypoglycemia, is a very rare condition, with an incidence of four cases per million person-years. Its rate of occurrence in the U.S. military population is unknown. Two cases of insulinomas involving active duty service members have been published. However, there has been no reported case of an insulinoma in a deployed service member. We report the case of a 21-year-old infantryman with clinical hypoglycemia of insidious onset, manifesting with overt neuroglycopenic symptoms during his deployment as a combatant soldier, and the ultimate diagnosis of an insulinoma as the underlying cause. The series of multiple clinical evaluations and the unique circumstances leading to the formal evaluation of the patient's hypoglycemia and treatment are chronicled. The significance of neuroglycopenia and the diagnostic approach to any suspected case of hypoglycemia, the potential challenges and opportunities, and educational aspects of evaluation and management of the insulinoma are elaborated. The potential role of the Military Health System in facilitating the detection and treatment of this rare condition in the service member is discussed as well.

The acylfulvene alkylating agent, LP-184, retains nanomolar potency in non-small cell lung cancer carrying otherwise therapy-refractory mutations.

More than 40% of non-small cell lung cancer (NSCLC) patients lack actionable targets and require non-targeted chemotherapeutics. Many become refractory to drugs due to underlying resistance-associated mutations. KEAP1 mutant NSCLCs further activate NRF2 and upregulate its client PTGR1. LP-184, a novel alkylating agent belonging to the acylfulvene class is a prodrug dependent upon PTGR1. We hypothesized that NSCLC with KEAP1 mutations would continue to remain sensitive to LP-184. LP-184 demonstrated highly potent anticancer activity both in primary NSCLC cell lines and in those originating from brain metastases of primary lung cancers. LP-184 activity correlated with PTGR1 transcript levels but was independent of mutations in key oncogenes (KRAS and KEAP1) and tumor suppressors (TP53 and STK11). LP-184 was orders of magnitude more potent in vitro than cisplatin and pemetrexed. Correlative analyses of sensitivity with cell line gene expression patterns indicated that alterations in NRF2, MET, EGFR and BRAF consistently modulated LP-184 sensitivity. These correlations were then extended to TCGA analysis of 517 lung adenocarcinoma patients, out of which 35% showed elevated PTGR1, and 40% of those further displayed statistically significant co-occurrence of KEAP1 mutations. The gene correlates of LP-184 sensitivity allow additional personalization of therapeutic options for future treatment of NSCLC.

A machine learning-based gene signature of response to the novel alkylating agent LP-184 distinguishes its potential tumor indications.

BACKGROUND: Non-targeted cytotoxics with anticancer activity are often developed through preclinical stages using response criteria observed in cell lines and xenografts. A panel of the NCI-60 cell lines is frequently the first line to define tumor types that are optimally responsive. Open data on the gene expression of the NCI-60 cell lines, provides a unique opportunity to add another dimension to the preclinical development of such drugs by interrogating correlations with gene expression patterns. Machine learning can be used to reduce the complexity of whole genome gene expression patterns to derive manageable signatures of response. Application of machine learning in early phases of preclinical development is likely to allow a better positioning and ultimate clinical success of molecules. LP-184 is a highly potent novel alkylating agent where the preclinical development is being guided by a dedicated machine learning-derived response signature. We show the feasibility and the accuracy of such a signature of response by accurately predicting the response to LP-184 validated using wet lab derived IC50s on a panel of cell lines. RESULTS: We applied our proprietary RADR® platform to an NCI-60 discovery dataset encompassing LP-184 IC50s and publicly available gene expression data. We used multiple feature selection layers followed by the XGBoost regression model and reduced the complexity of 20,000 gene expression values to generate a 16-gene signature leading to the identification of a set of predictive candidate biomarkers which form an LP-184 response gene signature. We further validated this signature and predicted response to an additional panel of cell lines. Considering fold change differences and correlation between actual and predicted LP-184 IC50 values as validation performance measures, we obtained 86% accuracy at four-fold cut-off, and a strong (r = 0.70) and significant (p value 1.36e-06) correlation between actual and predicted LP-184 sensitivity. In agreement with the perceived mechanism of action of LP-184, PTGR1 emerged as the top weighted gene. CONCLUSION: Integration of a machine learning-derived signature of response with in vitro assessment of LP-184 efficacy facilitated the derivation of manageable yet robust biomarkers which can be used to predict drug sensitivity with high accuracy and clinical value.

The precursor of PI(3,4,5)P3 alleviates aging by activating daf-18(Pten) and independent of daf-16.

Aging is characterized by the loss of homeostasis and the general decline of physiological functions, accompanied by various degenerative diseases and increased rates of mortality. Aging targeting small molecule screens have been performed many times, however, few have focused on endogenous metabolic intermediates-metabolites. Here, using C. elegans lifespan assays, we conducted a worm metabolite screen and identified an eukaryotes conserved metabolite, myo-inositol (MI), to extend lifespan, increase mobility and reduce fat content. Genetic analysis of enzymes in MI metabolic pathway suggest that MI alleviates aging through its derivative PI(4,5)P2. MI and PI(4,5)P2 are precursors of PI(3,4,5)P3, which is negatively related to longevity. The longevity effect of MI is dependent on the tumor suppressor gene, daf-18 (homologous to mouse Pten), independent of its classical pathway downstream genes, akt or daf-16. Furthermore, we found MI effects on aging and lifespan act through mitophagy regulator PTEN induced kinase-1 (pink-1) and mitophagy. MI's anti-aging effect is also conserved in mouse, indicating a conserved mechanism in mammals.

Accurate loop calling for 3D genomic data with cLoops.

MOTIVATION: Sequencing-based 3D genome mapping technologies can identify loops formed by interactions between regulatory elements hundreds of kilobases apart. Existing loop-calling tools are mostly restricted to a single data type, with accuracy dependent on a predefined resolution contact matrix or called peaks, and can have prohibitive hardware costs. RESULTS: Here, we introduce cLoops ('see loops') to address these limitations. cLoops is based on the clustering algorithm cDBSCAN that directly analyzes the paired-end tags (PETs) to find candidate loops and uses a permuted local background to estimate statistical significance. These two data-type-independent processes enable loops to be reliably identified for both sharp and broad peak data, including but not limited to ChIA-PET, Hi-C, HiChIP and Trac-looping data. Loops identified by cLoops showed much less distance-dependent bias and higher enrichment relative to local regions than existing tools. Altogether, cLoops improves accuracy of detecting of 3D-genomic loops from sequencing data, is versatile, flexible, efficient, and has modest hardware requirements. AVAILABILITY AND IMPLEMENTATION: cLoops with documentation and example data are freely available at: https://github.com/YaqiangCao/cLoops. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The strand-biased mitochondrial DNA methylome and its regulation by DNMT3A.

How individual genes are regulated from a mitochondrial polycistronic transcript to have variable expression remains an enigma. Here, through bisulfite sequencing and strand-specific mapping, we show mitochondrial genomes in humans and other animals are strongly biased to light (L)-strand non-CpG methylation with conserved peak loci preferentially located at gene-gene boundaries, which was also independently validated by MeDIP and FspEI digestion. Such mtDNA methylation patterns are conserved across different species and developmental stages but display dynamic local or global changes during development and aging. Knockout of DNMT3A alone perturbed mtDNA regional methylation patterns, but not global levels, and altered mitochondrial gene expression, copy number, and oxygen respiration. Overexpression of DNMT3A strongly increased mtDNA methylation and strand bias. Overall, methylation at gene bodies and boundaries was negatively associated with mitochondrial transcript abundance and also polycistronic transcript processing. Furthermore, HPLC-MS confirmed the methylation signals on mitochondria DNA. Together, these data provide high-resolution mtDNA methylation maps that revealed a strand-specific non-CpG methylation, its dynamic regulation, and its impact on the polycistronic mitochondrial transcript processing.

Immune Cell Types and Secreted Factors Contributing to Inflammation-to-Cancer Transition and Immune Therapy Response.

Although chronic inflammation increases many cancers' risk, how inflammation facilitates cancer development is still not well studied. Recognizing whether and when inflamed tissues transition to cancerous tissues is of utmost importance. To unbiasedly infer molecular events, immune cell types, and secreted factors contributing to the inflammation-to-cancer (I2C) transition, we develop a computational package called "SwitchDetector" based on liver, gastric, and colon cancer I2C data. Using it, we identify angiogenesis associated with a common critical transition stage for multiple I2C events. Furthermore, we infer infiltrated immune cell type composition and their secreted or suppressed extracellular proteins to predict expression of important transition stage genes. This identifies extracellular proteins that may serve as early-detection biomarkers for pre-cancer and early-cancer stages. They alone or together with I2C hallmark angiogenesis genes are significantly related to cancer prognosis and can predict immune therapy response. The SwitchDetector and I2C database are publicly available at www.inflammation2cancer.org.

Widespread roles of enhancer-like transposable elements in cell identity and long-range genomic interactions.

A few families of transposable elements (TEs) have been shown to evolve into cis-regulatory elements (CREs). Here, to extend these studies to all classes of TEs in the human genome, we identified widespread enhancer-like repeats (ELRs) and find that ELRs reliably mark cell identities, are enriched for lineage-specific master transcription factor binding sites, and are mostly primate-specific. In particular, elements of MIR and L2 TE families whose abundance co-evolved across chordate genomes, are found as ELRs in most human cell types examined. MIR and L2 elements frequently share long-range intra-chromosomal interactions and binding of physically interacting transcription factors. We validated that eight L2 and nine MIR elements function as enhancers in reporter assays, and among 20 MIR-L2 pairings, one MIR repressed and one boosted the enhancer activity of L2 elements. Our results reveal a previously unappreciated co-evolution and interaction between two TE families in shaping regulatory networks.

Accurate Drug Repositioning through Non-tissue-Specific Core Signatures from Cancer Transcriptomes.

Experimental large-scale screens for drug repositioning are limited by restriction to in vitro conditions and lack of applicability to real human conditions. Here, we developed an in silico screen in human in vivo conditions using a reference of single gene mutations' non-tissue-specific "core transcriptome signatures" (CSs) of 8,476 genes generated from the TCGA database. We developed the core-signature drug-to-gene (csD2G) software to scan 3,546 drug treatment profiles against the reference signatures. csD2G significantly outperformed conventional cell line-based gene perturbation signatures and existing drug-repositioning methods in both coverage and specificity. We highlight this with 3 demonstrated applications: (1) repositioned category of psychiatric drugs to inhibit the TGF-ß pathway; (2) antihypertensive calcium channel blockers predicted to activate AMPK and inhibit AKT pathways, and validated by clinical electronic medical records; and (3) 7 drugs predicted and validated to selectively target the AKT-FOXO and AMPK pathways and thus regulate worm lifespan.

Repression of human and mouse brain inflammaging transcriptome by broad gene-body histone hyperacetylation.

Brain "inflammaging," a low-grade and chronic inflammation, is a major hallmark for aging-related neurodegenerative diseases. Here, by profiling H3K27ac and gene expression patterns in human and mouse brains, we found that age-related up-regulated (Age-Up) and down-regulated (Age-Down) genes have distinct H3K27ac patterns. Although both groups show promoter H3K27ac, the Age-Up genes, enriched for inflammation-related functions, are additionally marked by broad H3K27ac distribution over their gene bodies, which is progressively reduced during aging. Age-related gene expression changes can be predicted by gene-body H3K27ac level. Contrary to the presumed transcription activation function of promoter H3K27ac, we found that broad gene-body hyper H3K27ac suppresses overexpression of inflammaging genes. Altogether, our findings revealed opposite regulations by H3K27ac of Age-Up and Age-Down genes and a mode of broad gene-body H3K27ac in repressing transcription.

Aging and Alzheimer's disease: Comparison and associations from molecular to system level.

Alzheimer's disease is the most prevalent cause of dementia, which is defined by the combined presence of amyloid and tau, but researchers are gradually moving away from the simple assumption of linear causality proposed by the original amyloid hypothesis. Aging is the main risk factor for Alzheimer's disease that cannot be explained by amyloid hypothesis. To evaluate how aging and Alzheimer's disease are intrinsically interwoven with each other, we review and summarize evidence from molecular, cellular, and system level. In particular, we focus on study designs, treatments, or interventions in Alzheimer's disease that could also be insightful in aging and vice versa.

Inference of differentiation time for single cell transcriptomes using cell population reference data.

Single-cell RNA sequencing (scRNA-seq) is a powerful method for dissecting intercellular heterogeneity during development. Conventional trajectory analysis provides only a pseudotime of development, and often discards cell-cycle events as confounding factors. Here using matched cell population RNA-seq (cpRNA-seq) as a reference, we developed an "iCpSc" package for integrative analysis of cpRNA-seq and scRNA-seq data. By generating a computational model for reference "biological differentiation time" using cell population data and applying it to single-cell data, we unbiasedly associated cell-cycle checkpoints to the internal molecular timer of single cells. Through inferring a network flow from cpRNA-seq to scRNA-seq data, we predicted a role of M phase in controlling the speed of neural differentiation of mouse embryonic stem cells, and validated it through gene knockout (KO) experiments. By linking temporally matched cpRNA-seq and scRNA-seq data, our approach provides an effective and unbiased approach for identifying developmental trajectory and timing-related regulatory events.

Role of AQP9 in transport of monomethyselenic acid and selenite.

AQP9 is an aquaglyceroporin with a very broad substrate spectrum. In addition to its orthodox nutrient substrates, AQP9 also transports multiple neutral and ionic arsenic species including arsenic trioxide, monomethylarsenous acid (MAsIII) and dimethylarsenic acid (DMAV). Here we discovered a new group of AQP9 substrates which includes two clinical relevant selenium species. We showed that AQP9 efficiently transports monomethylselenic acid (MSeA) with a preference for acidic pH, which has been demonstrated in Xenopus laevis oocyte following the overexpression of human AQP9. Specific inhibitors that dissipate transmembrane proton potential or change the transmembrane pH gradient, such as FCCP, valinomycin and nigericin did not significantly inhibit MSeA uptake, suggesting MSeA transport is not proton coupled. AQP9 was also found to transport ionic selenite and lactate, with much less efficiency compared with MSeA uptake. Selenite and lactate uptake via AQP9 is pH dependent and inhibited by FCCP and nigericin, but not valinomycin. The selenite and lactate uptake via AQP9 can be inhibited by different lactate analogs, indicating that their translocation share similar mechanisms. AQP9 transport of MSeA, selenite and lactate is all inhibited by a previously identified AQP9 inhibitor, phloretin, and the AQP9 substrate arsenite (AsIII). These newly identified AQP9 selenium substrates imply that AQP9 play a significant role in MSeA uptake and possibly selenite uptake involved in cancer therapy under specific microenvironments.

Molecular and phenotypic biomarkers of aging.

Individuals of the same age may not age at the same rate. Quantitative biomarkers of aging are valuable tools to measure physiological age, assess the extent of 'healthy aging', and potentially predict health span and life span for an individual. Given the complex nature of the aging process, the biomarkers of aging are multilayered and multifaceted. Here, we review the phenotypic and molecular biomarkers of aging. Identifying and using biomarkers of aging to improve human health, prevent age-associated diseases, and extend healthy life span are now facilitated by the fast-growing capacity of multilevel cross-sectional and longitudinal data acquisition, storage, and analysis, particularly for data related to general human populations. Combined with artificial intelligence and machine learning techniques, reliable panels of biomarkers of aging will have tremendous potential to improve human health in aging societies.

Seroprevalence of Toxoplasma gondii in American Black Bears ( Ursus americanus ) of the Central Appalachians, USA.

We assessed Toxoplasma gondii seroprevalence in 53 free-ranging American black bears ( Ursus americanus ) in the Central Appalachian Mountains, US. Seroprevalence was 62% with no difference between males and females or between juvenile and adult bears. Wildlife agencies should consider warnings in hunter education programs to reduce the chances for human infection from this source.