Signaling pathway cloud regulation for in silico screening and ranking of the potential geroprotective drugs

Potential Geroprotectors - From Bench to Clinic

Geroprotectors are substances that slow down aging process and can be used for prevention of age-related diseases. Geroprotectors can improve functioning of various organ systems and enhance their homeostatic capabilities. We have developed a system of criteria for geroprotectors and proposed their classification based on the mechanisms of their action on the aging processes. Geroprotectors are required to reduce mortality, improve human aging biomarkers, have minimal side effects, and enhance quality of life. Additionally, there are approaches based on combining geroprotectors targeted to different targets and mechanisms of aging to achieve maximum effectiveness. Currently, numerous preclinical studies are being conducted to identify new molecular targets and develop new approaches to extend healthy aging, although the number of clinical trials is limited. Geroprotectors have the potential to become a new class of preventive medicines as they prevent onset of certain diseases or slow down their progression.

Precious1GPT: multimodal transformer-based transfer learning for aging clock development and feature importance analysis for aging and age-related disease target discovery

Aging is a complex and multifactorial process that increases the risk of various age-related diseases and there are many aging clocks that can accurately predict chronological age, mortality, and health status. These clocks are disconnected and are rarely fit for therapeutic target discovery. In this study, we propose a novel approach to multimodal aging clock we call Precious1GPT utilizing methylation and transcriptomic data for interpretable age prediction and target discovery developed using a transformer-based model and transfer learning for case-control classification. While the accuracy of the multimodal transformer is lower within each individual data type compared to the state of art specialized aging clocks based on methylation or transcriptomic data separately it may have higher practical utility for target discovery. This method provides the ability to discover novel therapeutic targets that hypothetically may be able to reverse or accelerate biological age providing a pathway for therapeutic drug discovery and validation using the aging clock. In addition, we provide a list of promising targets annotated using the PandaOmics industrial target discovery platform.

Altered long non-coding RNAs expression in normal and diseased primary human airway epithelial cells exposed to diesel exhaust particles

BACKGROUND

Exposure to diesel exhaust particles (DEP) has been linked to a variety of adverse health effects, including increased morbidity and mortality from cardiovascular diseases, chronic obstructive pulmonary disease (COPD), metabolic syndrome, and lung cancer. The epigenetic changes caused by air pollution have been associated with increased health risks. However, the exact molecular mechanisms underlying the lncRNA-mediated pathogenesis induced by DEP exposure have not been revealed.

METHODS

Through RNA-sequencing and integrative analysis of both mRNA and lncRNA profiles, this study investigated the role of lncRNAs in altered gene expression in healthy and diseased human primary epithelial cells (NHBE and DHBE-COPD) exposed to DEP at a dose of 30 μg/cm2.

RESULTS

We identified 503 and 563 differentially expressed (DE) mRNAs and a total of 10 and 14 DE lncRNAs in NHBE and DHBE-COPD cells exposed to DEP, respectively. In both NHBE and DHBE-COPD cells, enriched cancer-related pathways were identified at mRNA level, and 3 common lncRNAs OLMALINC, AC069234.2, and LINC00665 were found to be associated with cancer initiation and progression. In addition, we identified two cis-acting (TMEM51-AS1 and TTN-AS1) and several trans-acting lncRNAs (e.g. LINC01278, SNHG29, AC006064.4, TMEM51-AS1) only differentially expressed in COPD cells, which could potentially play a role in carcinogenesis and determine their susceptibility to DEP exposure.

CONCLUSIONS

Overall, our work highlights the potential importance of lncRNAs in regulating DEP-induced gene expression changes associated with carcinogenesis, and individuals suffering from COPD are likely to be more vulnerable to these environmental triggers.

Integrated Multi-Omics for Novel Aging Biomarkers and Antiaging Targets

Aging is closely related to the occurrence of human diseases; however, its exact biological mechanism is unclear. Advancements in high-throughput technology provide new opportunities for omics research to understand the pathological process of various complex human diseases. However, single-omics technologies only provide limited insights into the biological mechanisms of diseases. DNA, RNA, protein, metabolites, and microorganisms usually play complementary roles and perform certain biological functions together. In this review, we summarize multi-omics methods based on the most relevant biomarkers in single-omics to better understand molecular functions and disease causes. The integration of multi-omics technologies can systematically reveal the interactions among aging molecules from a multidimensional perspective. Our review provides new insights regarding the discovery of aging biomarkers, mechanism of aging, and identification of novel antiaging targets. Overall, data from genomics, transcriptomics, proteomics, metabolomics, integromics, microbiomics, and systems biology contribute to the identification of new candidate biomarkers for aging and novel targets for antiaging interventions.

Geroprotective and senoremediative strategies to reduce the comorbidity, infection rates, severity, and lethality in gerophilic and gerolavic infections

The recently identified SARS-CoV-2 betacoronavirus responsible for the COVID-19 pandemic has uncovered the age-associated vulnerability in the burden of disease and put aging research in the spotlight. The limited data available indicates that COVID-19 should be referred to as a gerolavic (from Greek, géros "old man" and epilavís, "harmful") infection because the infection rates, severity, and lethality are substantially higher in the population aged 60 and older. This is primarily due to comorbidity but may be partially due to immunosenescence, decreased immune function in the elderly, and general loss of function, fitness, and increased frailty associated with aging. Immunosenescence is a major factor affecting vaccination response, as well as the severity and lethality of infectious diseases. While vaccination reduces infection rates, and therapeutic interventions reduce the severity and lethality of infections, these interventions have limitations. Previous studies showed that postulated geroprotectors, such as sirolimus (rapamycin) and its close derivative rapalog everolimus (RAD001), decreased infection rates in a small sample of elderly patients. This article presents a review of the limited literature available on geroprotective and senoremediative interventions that may be investigated to decrease the disease burden of gerolavic infections. This article also highlights a need for rigorous clinical validation of deep aging clocks as surrogate markers of biological age. These could be used to assess the need for, and efficacy of, geroprotective and senoremediative interventions and provide better protection for elderly populations from gerolavic infections. This article does not represent medical advice and the medications described are not yet licensed or recommended as immune system boosters, as they have not undergone clinical evaluation for this purpose.

Exposure to Dimethyl Selenide (DMSe)-Derived Secondary Organic Aerosol Alters Transcriptomic Profiles in Human Airway Epithelial Cells

Dimethyl selenide (DMSe) is one of the major volatile organoselenium compounds released from aquatic and terrestrial environments through microbial transformation and plant metabolism. The detailed processes of DMSe leading to secondary organic aerosol (SOA) formation and the pulmonary health effects induced by inhalation of DMSe-derived SOA remain largely unknown. In this study, we characterized the chemical composition and formation yields of SOA produced from the oxidation of DMSe with OH radicals and O₃ in controlled chamber experiments. Further, we profiled the transcriptome-wide gene expression changes in human airway epithelial cells (BEAS-2B) after exposure to DMSe-derived SOA. Our analyses indicated a significantly higher SOA yield resulting from the OH-initiated oxidation of DMSe. The oxidative potential of DMSe-derived SOA, as measured by the dithiothreitol (DTT) assay, suggested the presence of oxidizing moieties in DMSe-derived SOA at levels higher than typical ambient aerosols. Utilizing RNA sequencing (RNA-Seq) techniques, gene expression profiling followed by pathway enrichment analysis revealed several major biological pathways perturbed by DMSe-derived SOA, including elevated genotoxicity, DNA damage, and p53-mediated stress responses, as well as downregulated cholesterol biosynthesis, glycolysis, and interleukin IL-4/IL-13 signaling. This study highlights the significance of DMSe-derived SOA as a stressor in human airway epithelial cells.

Deep biomarkers of aging and longevity: from research to applications

Multiple recent advances in machine learning enabled computer systems to exceed human performance in many tasks including voice, text, and speech recognition and complex strategy games. Aging is a complex multifactorial process driven by and resulting in the many minute changes transpiring at every level of the human organism. Deep learning systems trained on the many measurable features changing in time can generalize and learn the many biological processes on the population and individual levels. The deep age predictors can help advance aging research by establishing causal relationships in non-linear systems. Deep aging clocks can be used for identification of novel therapeutic targets, evaluating the efficacy of the various interventions, data quality control, data economics, prediction of health trajectories, mortality, and many other applications. Here we present the current state of development of the deep aging clocks in the context of the pharmaceutical research and development and clinical applications.

Differences in intra-tumoral macrophage infiltration and radiotherapy response among intrinsic subtypes in pT1-T2 breast cancers treated with breast-conserving surgery

Breast cancer (BC) intrinsic subtype classification is based on the expression of estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2), and proliferation marker Ki-67. The expression of these markers depends on both the genetic background of the cancer cells and the surrounding tumor microenvironment. In this study, we explore macrophage traits in cancer cells and intra-tumoral M2-macrophage infiltration (MI) in relation to intrinsic subtypes in non-metastatic invasive BC treated with breast conserving surgery, with and without postoperative radiotherapy (RT). Immunostaining of M2-macrophage-specific antigen CD163 in cancer cells and MI were evaluated, together with ER, PR, HER2, and Ki-67-expression in cancer cells. The tumors were classified into intrinsic subtypes according to the ESMO guidelines. The immunostaining of these markers, MI, and clinical data were analyzed in relation to ipsilateral local recurrence (ILR) as well as recurrence-free (RFS) and disease-free specific (DFS) survival. BC intrinsic subtypes are associated with T-stage, Nottingham Histologic Grade (NHG), and MI. Macrophage phenotype in cancer cells is significantly associated with NHG3-tumors. Significant differences in macrophage infiltration were observed among the intrinsic subtypes of pT1-T2 stage BC. Shorter RFS was observed in luminal B HER2neg tumors after RT, suggesting that this phenotype may be more resistant to irradiation. Ki-67-expression was significantly higher in NHG3 and CD163-positive tumors, as well as those with moderate and high MI. Cancer cell ER expression is inversely related to MI and thus might affect the clinical staging and assessment of BC.

Understanding the Early Biological Effects of Isoprene-Derived Particulate Matter Enhanced by Anthropogenic Pollutants

INTRODUCTION

Airborne fine particulate matter (PM2.5; particulate matter ≤ 2.5 μm in aerodynamic diameter) plays a key role in air quality, climate, and public health. Globally, the largest mass fraction of PM2.5 is organic, dominated by secondary organic aerosol (SOA) formed from atmospheric oxidation of volatile organic compounds (VOCs). Isoprene from vegetation is the most abundant nonmethane VOC emitted into Earth's atmosphere. Isoprene has been recently recognized as one of the major sources of global SOA production that is enhanced by the presence of anthropogenic pollutants, such as acidic sulfate derived from sulfur dioxide (SO2), through multiphase chemistry of its oxidation products. Considering the abundance of isoprene-derived SOA in the atmosphere, understanding mechanisms of adverse health effects through inhalation exposure is critical to mitigating its potential impact on public health. Although previous studies have examined the toxicological effects of certain isoprene-derived gas-phase oxidation products, to date, no systematic studies have examined the potential toxicological effects of isoprene-derived SOA, its constituents, or its SOA precursors on human lung cells.

SPECIFIC AIMS

The overall objective of this study was to investigate the early biological effects of isoprene-derived SOA and its subtypes on BEAS-2B cells (a human bronchial epithelial cell line), with a particular focus on the alteration of oxidative stress- and inflammation-related genes. To achieve this objective, there were two specific aims.

1. Examine toxicity and early biological effects of SOA derived from the photochemical oxidation of isoprene, considering both urban and downwind-urban types of chemistry.

2. Examine toxicity and early biological effects of SOA derived directly from downstream oxidation products of isoprene (i.e., epoxides and hydroperoxides).

METHODS

Isoprene-derived SOA was first generated by photooxidation of isoprene under natural sunlight in the presence of nitric oxide (NO) and acidified sulfate aerosols. Experiments were conducted in a 120-m3 outdoor Teflon-film chamber located on the roof of the Gillings School of Global Public Health, University of North Carolina at Chapel Hill (UNC-Chapel Hill). BEAS-2B cells were exposed to chamber- generated isoprene-derived SOA using the Electrostatic Aerosol in Vitro Exposure System (EAVES). This approach allowed us to generate atmospherically relevant compositions of isoprene-derived SOA and to examine its toxicity through in vitro exposures at an air-liquid interface, providing a more biologically relevant exposure model. Isoprene-derived SOA samples were also collected, concurrently with EAVES sampling, onto Teflon membrane filters for in vitro resuspension exposures and for analysis of aerosol chemical composition by gas chromatography/electron ionization-quadrupole mass spectrometry (GC/EI-MS) with prior trimethylsilylation and ultra-performance liquid-chromatography coupled to high-resolution quadrupole time-of-flight mass spectrometry equipped with electrospray ionization (UPLC/ESI-HR-QTOFMS). Isoprene-derived SOA samples were also analyzed by the dithiothreitol (DTT) assay in order to characterize their reactive oxygen species (ROS)-generation potential.

Organic synthesis of known isoprene-derived SOA precursors, which included isoprene epoxydiols (IEPOX), methacrylic acid epoxide (MAE), and isoprene-derived hydroxyhydroperoxides (ISOPOOH), was conducted in order to isolate major isoprene-derived SOA formation pathways from each other and to determine which of these pathways (or SOA types) is potentially more toxic. Since IEPOX and MAE produce SOA through multiphase chemistry onto acidic sulfate aerosol, dark reactive uptake experiments of IEPOX and MAE in the presence of acidic sulfate aerosol were performed in a 10-m3 flexible Teflon indoor chamber at UNC-Chapel Hill. Since the generation of SOA from ISOPOOH (through a non-IEPOX route) requires a hydroxyl radical (•OH)-initiated oxidation, ozonolysis of tetramethylethylene (TME) was used to form the needed •OH radicals in the indoor chamber. The resultant low-volatility multifunctional hydroperoxides condensed onto nonacidified sulfate aerosol, yielding the ISOPOOH-derived SOA needed for exposures. Similar to the outdoor chamber SOAs, IEPOX, MAE- and ISOPOOH-derived SOAs were collected onto Teflon membrane filters and were subsequently chemically characterized by GC/EI-MS and UPLC/ESI-HR-QTOFMS as well as for ROS-generation potential using the DTT assay. These filters were also used for resuspension in vitro exposures.

By conducting gene expression profiling, we provided mechanistic insights into the potential health effects of isoprene-derived SOA. First, gene expression profiling of 84 oxidative stress- and 249 inflammation-associated human genes was performed for cells exposed to isoprene-derived SOA generated in our outdoor chamber experiments in EAVES or by resuspension. Two pathway-focused panels were utilized for this purpose: (1) nCounter GX Human Inflammation Kit comprised of 249 human genes (NanoString), and (2) Human Oxidative Stress Plus RT2 Profiler PCR Array (Qiagen) comprised of 84 oxidative stress-associated genes. We compared the gene expression levels in cells exposed to SOA generated in an outdoor chamber from photochemical oxidation of isoprene in the presence of NO and acidified sulfate seed aerosol to cells exposed to a dark control mixture of isoprene, NO, and acidified sulfate seed aerosol to isolate the effects of the isoprene-derived SOA on the cells using the EAVES and resuspension exposure methods. Pathway-based analysis was performed for significantly altered genes using the ConsensusPathDB database, which is a database system for the integration of human gene functional interactions to provide biological pathway information for a gene set of interest. Pathway annotation was performed to provide biological pathway information for each gene set. The gene-gene interaction networks were constructed and visualized using the GeneMANIA Cytoscape app (version 3.4.1) to predict the putative function of altered genes. Lastly, isoprene-derived SOA collected onto filters was used in resuspension exposures to measure select inflammatory biomarkers, including interleukin 8 (IL-8) and prostaglandin-endoperoxide synthase 2 (PTGS2) genes, in BEAS-2B cells to ensure that effects observed from EAVES exposures were attributable to particle-phase organic products. Since EAVES and resuspension exposures compared well, gene expression profiling for IEPOX-, MAE- and ISOPOOH-derived SOA were conducted using only resuspension exposures.

RESULTS AND CONCLUSIONS

Chemical characterization coupled with biological analyses show that atmospherically relevant compositions of isoprene-derived SOA alter the levels of 41 oxidative stress-related genes. Of the different composition types of isoprene-derived SOA, MAE- and ISOPOOH-derived SOA altered the greatest number of genes, suggesting that carbonyl and hydroperoxide functional groups are oxidative stress promoters. Taken together, the different composition types accounted for 34 of the genes altered by the total isoprene-derived SOA mixture, while 7 remained unique to the total mixture exposures, indicating that there is either a synergistic effect of the different isoprene-derived SOA components or an unaccounted component in the mixture.

The high-oxides of nitrogen (NOx) regime, which yielded MAE- and methacrolein (MACR)-derived SOA, had a higher ROS-generation potential (as measured by the DTT assay) than the low- NOx regime, which included IEPOX- and isoprene-derived SOA. However, ISOPOOH-derived SOA, which also formed in the low- NOx regime, had the highest ROS-generation potential, similar to 1,4-naphthoquinone (1,4-NQ). This suggests that aerosol-phase organic peroxides contribute significantly to particulate matter (PM) oxidative potential. MAE- and MACR- derived SOA showed equal or greater ROS-generation potential than was reported in prior UNC-Chapel Hill studies on diesel exhaust PM, highlighting the importance of a comprehensive investigation of the toxicity of isoprene-derived SOA. Notably, ISOPOOH-derived SOA was one order of magnitude higher in ROS-generation potential than diesel exhaust particles previously examined at UNC-Chapel Hill. As an acellular assay, the DTT assay may not be predictive of oxidative stress; therefore, we also focused on the gene expression results from the cellular exposures.

We have demonstrated that the nuclear factor (erythroid-derived 2)-like 2 (Nrf2) and the redox-sensitive activation protein-1 (AP-1) transcription factor networks have been significantly altered upon exposure to isoprene-derived SOA. The identification of Nrf2 pathway in cells exposed to isoprene-derived SOA is in accordance with our findings using the DTT assay, which measures the thiol reactivity of PM samples as a surrogate for their ROS-generation potential. Specifically, our results point to the cysteine-thiol modifications within cells that lead to activation of Nrf2-related gene expression.

However, based on our gene expression results showing no clear relationship between DTT activity and the number of altered oxidative stress-related genes, the DTT activity of isoprene-derived SOA may not be directly indicative of toxicity relative to other SOA types. While activation of Nrf2-associated genes has been identified with responses to oxidative stress and linked to traffic related air pollution exposure in both toxicological and epidemiological studies, their implicit involvement in this study suggests that activation of Nrf2-related gene expression may occur with exposures to all sorts of PM types.

By controlling the exposure time, method, and dose we demonstrated that among the SOA derived from previously identified individual precursors of isoprene-derived SOA, ISOPOOH-derived SOA alters more oxidative stress related genes than does IEPOX-derived SOA, but fewer than MAE-derived SOA. This suggests that the composition of MAE-derived SOA may be the greatest contributor to alterations of oxidative stress-related gene expression observed due to isoprene-derived SOA exposure. Further study on induced levels of protein expression and specific toxicological endpoints is necessary to determine if the observed gene expression changes lead to adverse health effects. In addition, such studies have implications for pollution-control strategies because NOx and SO2 are controllable pollutants that can alter the composition of SOA, and in turn alter its effects on gene expression. The mass fraction of different components of atmospheric isoprene derived SOA should be considered, but altering the fraction of high- NOx isoprene-derived SOA (e.g., MAE derived SOA) may yield greater changes in gene expression than altering the fraction of low- NOx isoprene derived SOA types (ISOPOOH- or IEPOX-derived SOA). Finally, this study confirms that total isoprene-derived SOA alters the expression of a greater number of genes than does SOA derived from the tested precursors. This warrants further work to determine the underlying explanation for this observation, which may be uncharacterized components of isoprene-derived SOA or the potential for synergism between the studied components.

Using the drug-protein interactome to identify anti-ageing compounds for humans

Advancing age is the dominant risk factor for most of the major killer diseases in developed countries. Hence, ameliorating the effects of ageing may prevent multiple diseases simultaneously. Drugs licensed for human use against specific diseases have proved to be effective in extending lifespan and healthspan in animal models, suggesting that there is scope for drug repurposing in humans. New bioinformatic methods to identify and prioritise potential anti-ageing compounds for humans are therefore of interest. In this study, we first used drug-protein interaction information, to rank 1,147 drugs by their likelihood of targeting ageing-related gene products in humans. Among 19 statistically significant drugs, 6 have already been shown to have pro-longevity properties in animal models (p < 0.001). Using the targets of each drug, we established their association with ageing at multiple levels of biological action including pathways, functions and protein interactions. Finally, combining all the data, we calculated a ranked list of drugs that identified tanespimycin, an inhibitor of HSP-90, as the top-ranked novel anti-ageing candidate. We experimentally validated the pro-longevity effect of tanespimycin through its HSP-90 target in Caenorhabditis elegans.

Human life expectancy is continuing to increase worldwide, as a result of successive improvements in living conditions and medical care. Although this trend is to be celebrated, advancing age is the major risk factor for multiple impairments and chronic diseases. As a result, the later years of life are often spent in poor health and lowered quality of life. However, these effects of ageing are not inevitable, because very long-lived people often suffer rather little ill-health at the end of their lives. Furthermore, laboratory experiments have shown that animals fed with specific drugs can live longer and with fewer age-related diseases than their untreated companions. We therefore need to identify drugs with anti-ageing properties for humans. We have used publically available data and a computer-based approach to search for drugs that affect components and processes known to be important in human ageing. This approach worked, because it was able to re-discover several drugs known to increase lifespan in animal models, plus some new ones, including one that we tested experimentally and validated in this study. These drugs are now a high priority for animal testing and for exploring effects on human ageing.

Gene expression-based drug repurposing to target aging

Aging is the largest risk factor for a variety of noncommunicable diseases. Model organism studies have shown that genetic and chemical perturbations can extend both lifespan and healthspan. Aging is a complex process, with parallel and interacting mechanisms contributing to its aetiology, posing a challenge for the discovery of new pharmacological candidates to ameliorate its effects. In this study, instead of a target‐centric approach, we adopt a systems level drug repurposing methodology to discover drugs that could combat aging in human brain. Using multiple gene expression data sets from brain tissue, taken from patients of different ages, we first identified the expression changes that characterize aging. Then, we compared these changes in gene expression with drug‐perturbed expression profiles in the Connectivity Map. We thus identified 24 drugs with significantly associated changes. Some of these drugs may function as antiaging drugs by reversing the detrimental changes that occur during aging, others by mimicking the cellular defence mechanisms. The drugs that we identified included significant number of already identified prolongevity drugs, indicating that the method can discover de novo drugs that meliorate aging. The approach has the advantages that using data from human brain aging data, it focuses on processes relevant in human aging and that it is unbiased, making it possible to discover new targets for aging studies.

Effects of Abies sibirica terpenes on cancer- and aging-associated pathways in human cells

A large number of terpenoids exhibit potential geroprotector and anti-cancer properties. Here, we studied whole transcriptomic effects of Abisil, the extract of fir (Abies sibirica) terpenes, on normal and cancer cell lines. We used early passaged and senescent none-immortalized fibroblasts as cellular aging models. It was revealed that in normal fibroblasts, terpenes induced genes of stress response, apoptosis regulation and tissue regeneration. The restoration of the expression level of some prolongevity genes after fir extract treatment was shown in old cells. In Caco-2 and AsPC-1 cancer cell lines, Abisil induced expression of both onco-suppressors (members of GADD45, DUSP, and DDIT gene families), and proto-oncogenes (c-Myc, c-Jun, EGR and others). Thus, the study demonstrates the potential anti-aging and anti-cancer effects of Abisil on senescent and cancer cell lines.

Large-scale profiling of signalling pathways reveals an asthma specific signature in bronchial smooth muscle cells

Background

Bronchial smooth muscle (BSM) cells from asthmatic patients maintain in vitro a distinct hyper-reactive (“primed”) phenotype, characterized by increased release of pro-inflammatory factors and mediators, as well as hyperplasia and/or hypertrophy. This “primed” phenotype helps to understand pathogenesis of asthma, as changes in BSM function are essential for manifestation of allergic and inflammatory responses and airway wall remodelling.

Objective

To identify signalling pathways in cultured primary BSMs of asthma patients and non-asthmatic subjects by genome wide profiling of differentially expressed mRNAs and activated intracellular signalling pathways (ISPs).

Methods

Transcriptome profiling by cap-analysis-of-gene-expression (CAGE), which permits selection of preferentially capped mRNAs most likely to be translated into proteins, was performed in human BSM cells from asthmatic (n=8) and non-asthmatic (n=6) subjects and OncoFinder tool were then exploited for identification of ISP deregulations.

Results

CAGE revealed >600 RNAs differentially expressed in asthma vs control cells (p≤0.005), with asthma samples showing a high degree of similarity among them. Comprehensive ISP activation analysis revealed that among 269 pathways analysed, 145 (p<0.05) or 103 (p<0.01) are differentially active in asthma, with profiles that clearly characterize BSM cells of asthmatic individuals. Notably, we identified 7 clusters of coherently acting pathways functionally related to the disease, with ISPs down-regulated in asthma mostly targeting cell death-promoting pathways and up-regulated ones affecting cell growth and proliferation, inflammatory response, control of smooth muscle contraction and hypoxia-related signalization.

Conclusions

These first-time results can now be exploited toward development of novel therapeutic strategies targeting ISP signatures linked to asthma pathophysiology.

In search for geroprotectors: in silico screening and in vitro validation of signalome-level mimetics of young healthy state

Populations in developed nations throughout the world are rapidly aging, and the search for geroprotectors, or anti-aging interventions, has never been more important. Yet while hundreds of geroprotectors have extended lifespan in animal models, none have yet been approved for widespread use in humans. GeroScope is a computational tool that can aid prediction of novel geroprotectors from existing human gene expression data. GeroScope maps expression differences between samples from young and old subjects to aging-related signaling pathways, then profiles pathway activation strength (PAS) for each condition. Known substances are then screened and ranked for those most likely to target differential pathways and mimic the young signalome. Here we used GeroScope and shortlisted ten substances, all of which have lifespan-extending effects in animal models, and tested 6 of them for geroprotective effects in senescent human fibroblast cultures. PD-98059, a highly selective MEK1 inhibitor, showed both life-prolonging and rejuvenating effects. Natural compounds like N-acetyl-L-cysteine, Myricetin and Epigallocatechin gallate also improved several senescence-associated properties and were further investigated with pathway analysis. This work not only highlights several potential geroprotectors for further study, but also serves as a proof-of-concept for GeroScope, Oncofinder and other PAS-based methods in streamlining drug prediction, repurposing and personalized medicine.

Towards natural mimetics of metformin and rapamycin

Aging is now at the forefront of major challenges faced globally, creating an immediate need for safe, widescale interventions to reduce the burden of chronic disease and extend human healthspan. Metformin and rapamycin are two FDA-approved mTOR inhibitors proposed for this purpose, exhibiting significant anti-cancer and anti-aging properties beyond their current clinical applications. However, each faces issues with approval for off-label, prophylactic use due to adverse effects. Here, we initiate an effort to identify nutraceuticals-safer, naturally-occurring compounds-that mimic the anti-aging effects of metformin and rapamycin without adverse effects. We applied several bioinformatic approaches and deep learning methods to the Library of Integrated Network-based Cellular Signatures (LINCS) dataset to map the gene- and pathway-level signatures of metformin and rapamycin and screen for matches among over 800 natural compounds. We then predicted the safety of each compound with an ensemble of deep neural network classifiers. The analysis revealed many novel candidate metformin and rapamycin mimetics, including allantoin and ginsenoside (metformin), epigallocatechin gallate and isoliquiritigenin (rapamycin), and withaferin A (both). Four relatively unexplored compounds also scored well with rapamycin. This work revealed promising candidates for future experimental validation while demonstrating the applications of powerful screening methods for this and similar endeavors.

Data aggregation at the level of molecular pathways improves stability of experimental transcriptomic and proteomic data

High throughput technologies opened a new era in biomedicine by enabling massive analysis of gene expression at both RNA and protein levels. Unfortunately, expression data obtained in different experiments are often poorly compatible, even for the same biologic samples. Here, using experimental and bioinformatic investigation of major experimental platforms, we show that aggregation of gene expression data at the level of molecular pathways helps to diminish cross- and intra-platform bias otherwise clearly seen at the level of individual genes. We created a mathematical model of cumulative suppression of data variation that predicts the ideal parameters and the optimal size of a molecular pathway. We compared the abilities to aggregate experimental molecular data for the 5 alternative methods, also evaluated by their capacity to retain meaningful features of biologic samples. The bioinformatic method OncoFinder showed optimal performance in both tests and should be very useful for future cross-platform data analyses.

Gene Expression Profiling in Human Lung Cells Exposed to Isoprene-Derived Secondary Organic Aerosol

Secondary organic aerosol (SOA) derived from the photochemical oxidation of isoprene contributes a substantial mass fraction to atmospheric fine particulate matter (PM2.5). The formation of isoprene SOA is influenced largely by anthropogenic emissions through multiphase chemistry of its multigenerational oxidation products. Considering the abundance of isoprene SOA in the troposphere, understanding mechanisms of adverse health effects through inhalation exposure is critical to mitigating its potential impact on public health. In this study, we assessed the effects of isoprene SOA on gene expression in human airway epithelial cells (BEAS-2B) through an air-liquid interface exposure. Gene expression profiling of 84 oxidative stress and 249 inflammation-associated human genes was performed. Our results show that the expression levels of 29 genes were significantly altered upon isoprene SOA exposure under noncytotoxic conditions (p < 0.05), with the majority (22/29) of genes passing a false discovery rate threshold of 0.3. The most significantly affected genes belong to the nuclear factor (erythroid-derived 2)-like 2 (Nrf2) transcription factor network. The Nrf2 function is confirmed through a reporter cell line. Together with detailed characterization of SOA constituents, this study reveals the impact of isoprene SOA exposure on lung responses and highlights the importance of further understanding its potential health outcomes.

Geroprotectors: A Unified Concept and Screening Approaches

Although the geroprotectors discovery is a new biomedicine trend and more than 200 compounds can slow aging and increase the lifespan of the model organism, there are still no geroprotectors on the market. The reasons may be partly related to the lack of a unified concept of geroprotector, accepted by the scientific community. Such concept as a system of criteria for geroprotector identification and classification can form a basis for an analytical model of anti-aging drugs, help to consolidate the efforts of various research initiatives in this area and compare their results. Here, we review the existing classification and characteristics of geroprotectors based on their effect on the survival of a group of individuals or pharmaceutics classes, according to the proposed mechanism of their geroprotective action or theories of aging. After discussing advantages and disadvantages of these approaches, we offer a new concept based on the maintenance of homeostatic capacity because aging can be considered as exponential shrinkage of homeostatic capacity leading to the onset of age-related diseases and death. Besides, we review the most promising current screening approaches to finding new geroprotectors. Establishing the classification of existing geroprotectors based on physiology and current understanding of the nature of aging is essential for putting the existing knowledge into a single system. This system could be useful to formulate standards for finding and creating new geroprotectors. Standardization, in turn, would allow easier comparison and combination of experimental data obtained by different research groups.

Mathematical Justification of Expression-Based Pathway Activation Scoring (PAS)

Although modeling of activation kinetics for various cell signaling pathways has reached a high grade of sophistication and thoroughness, most such kinetic models still remain of rather limited practical value for biomedicine. Nevertheless, recent advancements have been made in application of signaling pathway science for real needs of prescription of the most effective drugs for individual patients. The methods for such prescription evaluate the degree of pathological changes in the signaling machinery based on two types of data: first, on the results of high-throughput gene expression profiling, and second, on the molecular pathway graphs that reflect interactions between the pathway members. For example, our algorithm OncoFinder evaluates the activation of molecular pathways on the basis of gene/protein expression data in the objects of the interest.Yet, the question of assessment of the relative importance for each gene product in a molecular pathway remains unclear unless one call for the methods of parameter sensitivity /stiffness analysis in the interactomic kinetic models of signaling pathway activation in terms of total concentrations of each gene product.Here we show two principal points: 1. First, the importance coefficients for each gene in pathways that were obtained using the extremely time- and labor-consuming stiffness analysis of full-scaled kinetic models generally differ from much easier-to-calculate expression-based pathway activation score (PAS) not more than by 30%, so the concept of PAS is kinetically justified. 2. Second, the use of pathway-based approach instead of distinct gene analysis, due to the law of large numbers, allows restoring the correlation between the similar samples that were examined using different transcriptome investigation techniques.

MiRImpact, a new bioinformatic method using complete microRNA expression profiles to assess their overall influence on the activity of intracellular molecular pathways

MicroRNAs (miRs) are short noncoding RNA molecules that regulate expression of target mRNAs. Many published sources provide information about miRs and their targets. However, bioinformatic tools elucidating higher level impact of the established total miR profiles, are still largely missing. Recently, we developed a method termed OncoFinder enabling quantification of the activities of intracellular molecular pathways basing on gene expression data. Here we propose a new technique, MiRImpact, which enables to link miR expression data with its estimated outcome on the regulation of molecular pathways, like signaling, metabolic, cytoskeleton rearrangement, and DNA repair pathways. MiRImpact uses OncoFinder rationale for pathway activity calculations, with the major distinctions that (i) it deals with the concentrations of miRs - known regulators of gene products participating in molecular pathways, and (ii) miRs are considered as negative regulators of target molecules, if other is not specified. MiRImpact operates with 2 types of databases: for molecular targets of miRs and for gene products participating in molecular pathways. We applied MiRImpact to compare regulation of human bladder cancer-specific signaling pathways at the levels of mRNA and miR expression. We took 2 most complete alternative databases of experimentally validated miR targets – miRTarBase and DianaTarBase, and an OncoFinder database featuring 2725 gene products and 271 signaling pathways. We showed that the impact of miRs is orthogonal to pathway regulation at the mRNA level, which stresses the importance of studying posttranscriptional regulation of gene expression. We also report characteristic set of miR and mRNA regulation features linked with bladder cancer.

Combinatorial high-throughput experimental and bioinformatic approach identifies molecular pathways linked with the sensitivity to anticancer target drugs

Effective choice of anticancer drugs is important problem of modern medicine. We developed a method termed OncoFinder for the analysis of new type of biomarkers reflecting activation of intracellular signaling and metabolic molecular pathways. These biomarkers may be linked with the sensitivity to anticancer drugs. In this study, we compared the experimental data obtained in our laboratory and in the Genomics of Drug Sensitivity in Cancer (GDS) project for testing response to anticancer drugs and transcriptomes of various human cell lines. The microarray-based profiling of transcriptomes was performed for the cell lines before the addition of drugs to the medium, and experimental growth inhibition curves were built for each drug, featuring characteristic IC₅₀ values. We assayed here four target drugs - Pazopanib, Sorafenib, Sunitinib and Temsirolimus, and 238 different cell lines, of which 11 were profiled in our laboratory and 227 - in GDS project. Using the OncoFinder-processed transcriptomic data on ∼600 molecular pathways, we identified pathways showing significant correlation between pathway activation strength (PAS) and IC₅₀ values for these drugs. Correlations reflect relationships between response to drug and pathway activation features. We intersected the results and found molecular pathways significantly correlated in both our assay and GDS project. For most of these pathways, we generated molecular models of their interaction with known molecular target(s) of the respective drugs. For the first time, our study uncovered mechanisms underlying cancer cell response to drugs at the high-throughput molecular interactomic level.

Geroprotectors.org: a new, structured and curated database of current therapeutic interventions in aging and age-related disease

As the level of interest in aging research increases, there is a growing number of geroprotectors, or therapeutic interventions that aim to extend the healthy lifespan and repair or reduce aging-related damage in model organisms and, eventually, in humans. There is a clear need for a manually-curated database of geroprotectors to compile and index their effects on aging and age-related diseases and link these effects to relevant studies and multiple biochemical and drug databases. Here, we introduce the first such resource, Geroprotectors (http://geroprotectors.org). Geroprotectors is a public, rapidly explorable database that catalogs over 250 experiments involving over 200 known or candidate geroprotectors that extend lifespan in model organisms. Each compound has a comprehensive profile complete with biochemistry, mechanisms, and lifespan effects in various model organisms, along with information ranging from chemical structure, side effects, and toxicity to FDA drug status. These are presented in a visually intuitive, efficient framework fit for casual browsing or in-depth research alike. Data are linked to the source studies or databases, providing quick and convenient access to original data. The Geroprotectors database facilitates cross-study, cross-organism, and cross-discipline analysis and saves countless hours of inefficient literature and web searching. Geroprotectors is a one-stop, knowledge-sharing, time-saving resource for researchers seeking healthy aging solutions.

Developing criteria for evaluation of geroprotectors as a key stage toward translation to the clinic

In the coming decades, a massive shift in the aging segment of the population will have major social and economic consequences around the world. One way to offset this increase is to expedite the development of geroprotectors, substances that slow aging, repair age‐associated damage and extend healthy lifespan, or healthspan. While over 200 geroprotectors are now reported in model organisms and some are in human use for specific disease indications, the path toward determining whether they affect aging in humans remains obscure. Translation to the clinic is hampered by multiple issues including absence of a common set of criteria to define, select, and classify these substances, given the complexity of the aging process and their enormous diversity in mechanism of action. Translational research efforts would benefit from the formation of a scientific consensus on the following: the definition of ‘geroprotector’, the selection criteria for geroprotectors, a comprehensive classification system, and an analytical model. Here, we review current approaches to selection and put forth our own suggested selection criteria. Standardizing selection of geroprotectors will streamline discovery and analysis of new candidates, saving time and cost involved in translation to clinic.

Aging Chart: a community resource for rapid exploratory pathway analysis of age-related processes

Aging research is a multi-disciplinary field encompassing knowledge from many areas of basic, applied and clinical research. Age-related processes occur on molecular, cellular, tissue, organ, system, organismal and even psychological levels, trigger the onset of multiple debilitating diseases and lead to a loss of function, and there is a need for a unified knowledge repository designed to track, analyze and visualize the cause and effect relationships and interactions between the many elements and processes on all levels. Aging Chart (http://agingchart.org/) is a new, community-curated collection of aging pathways and knowledge that provides a platform for rapid exploratory analysis. Building on an initial content base constructed by a team of experts from peer-reviewed literature, users can integrate new data into biological pathway diagrams for a visible, intuitive, top-down framework of aging processes that fosters knowledge-building and collaboration. As the body of knowledge in aging research is rapidly increasing, an open visual encyclopedia of aging processes will be useful to both the new entrants and experts in the field.

Classifying aging as a disease in the context of ICD-11

Aging is a complex continuous multifactorial process leading to loss of function and crystalizing into the many age-related diseases. Here, we explore the arguments for classifying aging as a disease in the context of the upcoming World Health Organization's 11th International Statistical Classification of Diseases and Related Health Problems (ICD-11), expected to be finalized in 2018. We hypothesize that classifying aging as a disease with a "non-garbage" set of codes will result in new approaches and business models for addressing aging as a treatable condition, which will lead to both economic and healthcare benefits for all stakeholders. Actionable classification of aging as a disease may lead to more efficient allocation of resources by enabling funding bodies and other stakeholders to use quality-adjusted life years (QALYs) and healthy-years equivalent (HYE) as metrics when evaluating both research and clinical programs. We propose forming a Task Force to interface the WHO in order to develop a multidisciplinary framework for classifying aging as a disease with multiple disease codes facilitating for therapeutic interventions and preventative strategies.

Novel robust biomarkers for human bladder cancer based on activation of intracellular signaling pathways

We recently proposed a new bioinformatic algorithm called OncoFinder for quantifying the activation of intracellular signaling pathways. It was proved advantageous for minimizing errors of high-throughput gene expression analyses and showed strong potential for identifying new biomarkers. Here, for the first time, we applied OncoFinder for normal and cancerous tissues of the human bladder to identify biomarkers of bladder cancer. Using Illumina HT12v4 microarrays, we profiled gene expression in 17 cancer and seven non-cancerous bladder tissue samples. These experiments were done in two independent laboratories located in Russia and Canada. We calculated pathway activation strength values for the investigated transcriptomes and identified signaling pathways that were regulated differently in bladder cancer (BC) tissues compared with normal controls. We found, for both experimental datasets, 44 signaling pathways that serve as excellent new biomarkers of BC, supported by high area under the curve (AUC) values. We conclude that the OncoFinder approach is highly efficient in finding new biomarkers for cancer. These markers are mathematical functions involving multiple gene products, which distinguishes them from “traditional” expression biomarkers that only assess concentrations of single genes.

Signaling pathways activation profiles make better markers of cancer than expression of individual genes

Identification of reliable and accurate molecular markers remains one of the major challenges of contemporary biomedicine. We developed a new bioinformatic technique termed OncoFinder that for the first time enables to quantatively measure activation of intracellular signaling pathways basing on transcriptomic data. Signaling pathways regulate all major cellular events in health and disease. Here, we showed that the Pathway Activation Strength (PAS) value itself may serve as the biomarker for cancer, and compared it with the "traditional" molecular markers based on the expression of individual genes. We applied OncoFinder to profile gene expression datasets for the nine human cancer types including bladder cancer, basal cell carcinoma, glioblastoma, hepatocellular carcinoma, lung adenocarcinoma, oral tongue squamous cell carcinoma, primary melanoma, prostate cancer and renal cancer, totally 292 cancer and 128 normal tissue samples taken from the Gene expression omnibus (GEO) repository. We profiled activation of 82 signaling pathways that involve ~2700 gene products. For 9/9 of the cancer types tested, the PAS values showed better area-under-the-curve (AUC) scores compared to the individual genes enclosing each of the pathways. These results evidence that the PAS values can be used as a new type of cancer biomarkers, superior to the traditional gene expression biomarkers.

Signaling pathway activation drift during aging: Hutchinson-Gilford Progeria Syndrome fibroblasts are comparable to normal middle-age and old-age cells

For the past several decades, research in understanding the molecular basis of human aging has progressed significantly with the analysis of premature aging syndromes. Progerin, an altered form of lamin A, has been identified as the cause of premature aging in Hutchinson-Gilford Progeria Syndrome (HGPS), and may be a contributing causative factor in normal aging. However, the question of whether HGPS actually recapitulates the normal aging process at the cellular and organismal level, or simply mimics the aging phenotype is widely debated. In the present study we analyzed publicly available microarray datasets for fibroblasts undergoing cellular aging in culture, as well as fibroblasts derived from young, middle-age, and old-age individuals, and patients with HGPS. Using GeroScope pathway analysis and drug discovery platform we analyzed the activation states of 65 major cellular signaling pathways. Our analysis reveals that signaling pathway activation states in cells derived from chronologically young patients with HGPS strongly resemble cells taken from normal middle-aged and old individuals. This clearly indicates that HGPS may truly represent accelerated aging, rather than being just a simulacrum. Our data also points to potential pathways that could be targeted to develop drugs and drug combinations for both HGPS and normal aging.

Longevity expectations in the pension fund, insurance, and employee benefits industries

Considerable progress has been made in many areas of biomedical science since the 1960s, suggesting likely increases in life expectancy and decreases in morbidity and mortality in the adult population. These changes may pose substantial risks to the pensions and benefits industries. While there is no significant statistical evidence demonstrating rapid decreases in mortality rates, there are conflicting opinions among demographers and biogerontologists on the biological limits of the human lifespan and trends in life expectancy. We administered a survey of the International Employee Benefits Association (IEBA), a large, international industry group. Industry professionals employed by consulting (35%), insurance (24%), pension (14%), and other (27%) companies responded to 32 questions. Respondents showed reasonably conservative views on the future of longevity and retirement, including that for women. The respondents formed their personal longevity expectations based on their family history and, to a lesser degree, on the actuarial life tables. Most of the sample expressed no desire to life past age 100 years, even if the enabling technologies required to maintain a healthy youthful state were available, and only a few respondents in the sample expressed a desire to live for the maximum period (at least) offered by the survey question. The majority of the respondents would not undergo any invasive procedures, and only 56% of the respondents would opt for noninvasive therapies to extend their healthy lifespans to 150 years of age if these were available.

The OncoFinder algorithm for minimizing the errors introduced by the high-throughput methods of transcriptome analysis

The diversity of the installed sequencing and microarray equipment make it increasingly difficult to compare and analyze the gene expression datasets obtained using the different methods. Many applications requiring high-quality and low error rates cannot make use of available data using traditional analytical approaches. Recently, we proposed a new concept of signalome-wide analysis of functional changes in the intracellular pathways termed OncoFinder, a bioinformatic tool for quantitative estimation of the signaling pathway activation (SPA). We also developed methods to compare the gene expression data obtained using multiple platforms and minimizing the error rates by mapping the gene expression data onto the known and custom signaling pathways. This technique for the first time makes it possible to analyze the functional features of intracellular regulation on a mathematical basis. In this study we show that the OncoFinder method significantly reduces the errors introduced by transcriptome-wide experimental techniques. We compared the gene expression data for the same biological samples obtained by both the next generation sequencing (NGS) and microarray methods. For these different techniques we demonstrate that there is virtually no correlation between the gene expression values for all datasets analyzed (R² < 0.1). In contrast, when the OncoFinder algorithm is applied to the data we observed clear-cut correlations between the NGS and microarray gene expression datasets. The SPA profiles obtained using NGS and microarray techniques were almost identical for the same biological samples allowing for the platform-agnostic analytical applications. We conclude that this feature of the OncoFinder enables to characterize the functional states of the transcriptomes and interactomes more accurately as before, which makes OncoFinder a method of choice for many applications including genetics, physiology, biomedicine, and molecular diagnostics.

Molecular aspects of development and regulation of endometriosis

Endometriosis is a common and painful condition affecting women of reproductive age. While the underlying pathophysiology is still largely unknown, much advancement has been made in understanding the progression of the disease. In recent years, a great deal of research has focused on non-invasive diagnostic tools, such as biomarkers, as well as identification of potential therapeutic targets. In this article, we will review the etiology and cellular mechanisms associated with endometriosis as well as the current diagnostic tools and therapies. We will then discuss the more recent genomic and proteomic studies and how these data may guide development of novel diagnostics and therapeutics. The current diagnostic tools are invasive and current therapies primarily treat the symptoms of endometriosis. Optimally, the advancement of "-omic" data will facilitate the development of non-invasive diagnostic biomarkers as well as therapeutics that target the pathophysiology of the disease and halt, or even reverse, progression. However, the amount of data generated by these types of studies is vast and bioinformatics analysis, such as we present here, will be critical to identification of appropriate targets for further study.

Oncofinder, a new method for the analysis of intracellular signaling pathway activation using transcriptomic data

We propose a new biomathematical method, OncoFinder, for both quantitative and qualitative analysis of the intracellular signaling pathway activation (SPA). This method is universal and may be used for the analysis of any physiological, stress, malignancy and other perturbed conditions at the molecular level. In contrast to the other existing techniques for aggregation and generalization of the gene expression data for individual samples, we suggest to distinguish the positive/activator and negative/repressor role of every gene product in each pathway. We show that the relative importance of each gene product in a pathway can be assessed using kinetic models for “low-level” protein interactions. Although the importance factors for the pathway members cannot be so far established for most of the signaling pathways due to the lack of the required experimental data, we showed that ignoring these factors can be sometimes acceptable and that the simplified formula for SPA evaluation may be applied for many cases. We hope that due to its universal applicability, the method OncoFinder will be widely used by the researcher community.