Support for phosphoinositol 3 kinase and mTOR inhibitors as treatment for lupus using in-silico drug-repurposing analysis

Identification of new candidate drugs for primary Sjögren's syndrome using a drug repurposing transcriptomic approach

OBJECTIVES

To date, no immunomodulatory drug has demonstrated its efficacy in primary SS (pSS). We sought to analyse potential commonalities between pSS transcriptomic signatures and signatures of various drugs or specific knock-in or knock-down genes.

METHODS

Gene expression from peripheral blood samples of patients with pSS was compared with that of healthy controls in two cohorts and three public databases. In each of the five datasets, we analysed the 150 most up- and downregulated genes between pSS patients and controls with regard to the differentially expressed genes resulting from the biological action on nine cell lines of 2837 drugs, 2160 knock-in and 3799 knock-down genes in the Connectivity Map database.

RESULTS

We analysed 1008 peripheral blood transcriptomes from five independent studies (868 patients with pSS and 140 healthy controls). Eleven drugs could represent potential candidate drugs, with histone deacetylases and PI3K inhibitors among the most significantly associated. Twelve knock-in genes were associated with a pSS-like profile and 23 knock-down genes were associated with a pSS-revert profile. Most of those genes (28/35, 80%) were interferon-regulated.

CONCLUSION

This first drug repositioning transcriptomic approach in SS confirms the interest of targeting interferons and identifies histone deacetylases and PI3K inhibitors as potential therapeutic targets.

Precision medicine in systemic lupus erythematosus

Systemic lupus erythematosus (SLE) is an autoimmune disease that has diverse clinical manifestations, ranging from restricted cutaneous involvement to life-threatening systemic organ involvement. The heterogeneity of pathomechanisms that lead to SLE contributes to between-patient variation in clinical phenotype and treatment response. Ongoing efforts to dissect cellular and molecular heterogeneity in SLE could facilitate the future development of stratified treatment recommendations and precision medicine, which is a considerable challenge for SLE. In particular, some genes involved in the clinical heterogeneity of SLE and some phenotype-related loci (STAT4, IRF5, PDGF genes, HAS2, ITGAM and SLC5A11) have an association with clinical features of the disease. An important part is also played by epigenetic varation (in DNA methylation, histone modifications and microRNAs) that influences gene expression and affects cell function without modifying the genome sequence. Immune profiling can help to identify an individual's specific response to a therapy and can potentially predict outcomes, using techniques such as flow cytometry, mass cytometry, transcriptomics, microarray analysis and single-cell RNA sequencing. Furthermore, the identification of novel serum and urinary biomarkers would enable the stratification of patients according to predictions of long-term outcomes and assessments of potential response to therapy.

Molecular Taxonomy of Systemic Lupus Erythematosus Through Data-Driven Patient Stratification: Molecular Endotypes and Cluster-Tailored Drugs

Objectives

Treatment of Systemic Lupus Erythematosus (SLE) is characterized by a largely empirical approach and relative paucity of novel compound development. We sought to stratify SLE patients based on their molecular phenotype and identify putative therapeutic compounds for each molecular fingerprint.

Methods

By the use of whole blood RNA-seq data from 120 SLE patients, and in a data-driven, clinically unbiased manner, we established modules of commonly regulated genes (molecular endotypes) and re-stratified patients through hierarchical clustering. Disease activity and severity were assessed using SLEDAI-2K and Lupus Severity Index, respectively. Through an in silico drug prediction pipeline, we investigated drugs currently in use, tested in lupus clinical trials, and listed in the iLINCS prediction databases, for their ability to reverse the gene expression signatures in each molecular endotype. Drug repurposing analysis was also performed to identify perturbagens that counteract group-specific SLE signatures.

Results

Molecular taxonomy identified five lupus endotypes, each characterized by a unique gene module enrichment pattern. Neutrophilic signature group consisted primarily of patients with active lupus nephritis, while the B-cell expression group included patients with constitutional features. Patients with moderate severity and serologic activity exhibited a signature enriched for metabolic processes. Mild disease was distributed in two groups, exhibiting enhanced basic cellular functions, myelopoiesis, and autophagy. Bortezomib was predicted to reverse disturbances in the "neutrophilic" cluster, azathioprine and ixazomib in the "B-cell" cluster, and fostamatinib in the "metabolic" patient subgroup.

Conclusion

The clinical spectrum of SLE encompasses distinct molecular endotypes, each defined by unique pathophysiologic aberrancies potentially reversible by distinct compounds.

The Role of PI3K Isoforms in Autoimmune Disease

Aberrant overactivation of the immune system can give rise to chronic and persistent self-attack, culminating in autoimmune disease. This is currently managed therapeutically using potent immunosuppressive and anti-inflammatory drugs. Class I phosphoinositide-3-kinases (PI3Ks) have been identified as ideal therapeutic targets for autoimmune diseases given their wide-ranging roles in immunological processes. Although progress has been hampered by issues such as poor drug tolerance and drug resistance, several PI3K inhibitors have now received regulatory approval with many others in development, including several intended to suppress the immune response in autoimmune and inflammatory diseases. This chapter reviews the evidence for contribution of aberrant PI3K activity to a range of autoimmune diseases (rheumatoid arthritis, systemic lupus erythematosus, multiple sclerosis and type I diabetes) and possible therapeutic application of isoform-specific PI3K inhibitors as immunosuppressive drugs.

A Case for Phosphoinositide 3-Kinase-Targeted Therapy for Infectious Disease

PI3Ks activate critical signaling cascades and have multifaceted regulatory functions in the immune system. Loss-of-function and gain-of-function mutations in the PI3Kδ isoform have revealed that this enzyme can substantially impact immune responses to infectious agents and their products. Moreover, reports garnered from decades of infectious disease studies indicate that pharmacologic inhibition of the PI3K pathway could potentially be effective in limiting the growth of certain microbes via modulation of the immune system. In this review, we briefly highlight the development and applications of PI3K inhibitors and summarize data supporting the concept that PI3Kδ inhibitors initially developed for oncology have immune regulatory potential that could be exploited to improve the control of some infectious diseases. This repurposing of existing kinase inhibitors could lay the foundation for alternative infectious disease therapy using available therapeutic agents.

A survey of gene expression meta-analysis: methods and applications

The increasing use of high-throughput gene expression quantification technologies over the last two decades and the fact that most of the published studies are stored in public databases has triggered an explosion of studies available through public repositories. All this information offers an invaluable resource for reuse to generate new knowledge and scientific findings. In this context, great interest has been focused on meta-analysis methods to integrate and jointly analyze different gene expression datasets. In this work, we describe the main steps in the gene expression meta-analysis, from data preparation to the state-of-the art statistical methods. We also analyze the main types of applications and problems that can be approached in gene expression meta-analysis studies and provide a comparative overview of the available software and bioinformatics tools. Moreover, a practical guide for choosing the most appropriate method in each case is also provided.

Differential Treatments Based on Drug-induced Gene Expression Signatures and Longitudinal Systemic Lupus Erythematosus Stratification

Systemic lupus erythematosus (SLE) is a heterogeneous disease with unpredictable patterns of activity. Patients with similar activity levels may have different prognosis and molecular abnormalities. In this study, we aimed to measure the main differences in drug-induced gene expression signatures across SLE patients and to evaluate the potential for clinical data to build a machine learning classifier able to predict the SLE subset for individual patients. SLE transcriptomic data from two cohorts were compared with drug-induced gene signatures from the CLUE database to compute a connectivity score that reflects the capability of a drug to revert the patient signatures. Patient stratification based on drug connectivity scores revealed robust clusters of SLE patients identical to the clusters previously obtained through longitudinal gene expression data, implying that differential treatment depends on the cluster to which patients belongs. The best drug candidates found, mTOR inhibitors or those reducing oxidative stress, showed stronger cluster specificity. We report that drug patterns for reverting disease gene expression follow the cell-specificity of the disease clusters. We used 2 cohorts to train and test a logistic regression model that we employed to classify patients from 3 independent cohorts into the SLE subsets and provide a clinically useful model to predict subset assignment and drug efficacy.

A subgroup of lupus patients with nephritis, innate T cell activation and low vitamin D is identified by the enhancement of circulating MHC class I-related chain A

The major histocompatibility complex (MHC) class I-related chain A (MICA) is induced upon stress, and labels malfunctioning cells for their recognition by cytotoxic lymphocytes. Alterations in this recognition and also abnormal natural killer (NK) functions have been found in systemic lupus erythematosus (SLE). MICA can be shed from cells, subsequently acting as a soluble decoy receptor (sMICA). Our purpose was to study circulating sMICA levels in relationship with the activation of innate pathways in PBMC in a cohort of lupus patients. NK cells were characterized by flow cytometry. Gene expression of Toll-like receptors (TLR), interferon (IFN)-I sensitive genes and MICA were separately analyzed in monocytes, T cells and B cells. Serum sMICA was measured with enzyme-linked immunosorbent assay (ELISA). In our cohort, NK cell counts dropped in relationship with disease activity. sMICA showed an inverse trend with NK cell counts, as well as a significant association with activity indices, but not with complement decrease. Levels of sMICA associated to proteinuria and active nephritis. A multivariate regression model revealed anti-nuclear antibody (ANA) titres, the up-regulation of TLR-4 in T cells and lower vitamin D as predictors of sMICA enhancement. Interestingly, vitamin D showed an inverse association with proteinuria and a strong correlation with T cell MICA mRNA levels. According to our data, circulating sMICA identifies a subgroup of lupus patients with low vitamin D, innate activation of T cells and nephritis. We propose that lymphocyte shedding could account for the enhancement of sMICA and reflect an immune evasion mechanism driving disease activation in lupus.

New Attempts to Define and Clarify Lupus

Purpose of Review

The purpose is to discuss the advances that genetics and genomics have provided to better understand the molecular mechanisms behind SLE and how to solve its heterogeneity. I propose new ideas that can help us stratify lupus in order to find the best therapies for each patient, and the idea of substituting clinical diagnosis with molecular diagnosis according to their molecular patterns, an idea that may not only include lupus but also other diseases.

Recent Findings

The study of rare mutations may provide insight into groups of lupus patients where type I interferon signature is important and help understand those with an atypical clinical presentation. Recent papers used longitudinal blood transcriptome data correlating with disease activity scores to stratify lupus into molecular clusters. The implication of neutrophils in the risk to develop nephritis was established, but also that neutrophils and lymphocytes may correlate with activity differentiating the mechanisms of flares and separating patients into clinically separate groups.

Summary

The role of type I interferon signature is important; however, the stratification of SLE patients according to the genes and cellular compartments being modulated during disease activity may be even more important to define those patients who may benefit the most with new anti-type I IFN receptor therapies.

Methods and approaches to disease mechanisms using systems kinomics

All cellular functions, ranging from regular cell maintenance and homeostasis, specialized functions specific to cellular types, or generating responses due to external stimulus, are mediated by proteins within the cell. Regulation of these proteins allows the cell to alter its behavior under different circumstances. A major mechanism of protein regulation is utilizing protein kinases and phosphatases; enzymes that catalyze the transfer of phosphates between substrates [1]. Proteins involved in phosphate signaling are well studied and include kinases and phosphatases that catalyze opposing reactions regulating both structure and function of the cell. Kinomics is the study of kinases, phosphatases and their targets, and has been used to study the functional changes in numerous diseases and infectious diseases with aims to delineate the cellular functions affected. Identifying the phosphate signaling pathways changed by certain diseases or infections can lead to novel therapeutic targets. However, a daunting 518 putative protein kinase genes have been identified [2], indicating that this protein family is very large and complex. Identifying which enzymes are specific to a particular disease can be a laborious task. In this review, we will provide information on large-scale systems biology methodologies that allow global screening of the kinome to more efficiently identify which kinase pathways are pertinent for further study.

The benefits of in silico modeling to identify possible small-molecule drugs and their off-target interactions

The research into the use of small molecules as drugs continues to be a key driver in the development of molecular databases, computer-aided drug design software and collaborative platforms. The evolution of computational approaches is driven by the essential criteria that a drug molecule has to fulfill, from the affinity to targets to minimal side effects while having adequate absorption, distribution, metabolism, and excretion (ADME) properties. A combination of ligand- and structure-based drug development approaches is already used to obtain consensus predictions of small molecule activities and their off-target interactions. Further integration of these methods into easy-to-use workflows informed by systems biology could realize the full potential of available data in the drug discovery and reduce the attrition of drug candidates.