SARS-CoV-2 is the causative agent for coronavirus disease-19 (COVID-19) and belongs to the family Coronaviridae that causes sickness varying from the common cold to more severe illnesses such as severe acute respiratory syndrome, sudden stroke, neurological complications (Neuro-COVID), multiple organ failure, and mortality in some patients. The gene expression profiles of COVID-19 infection models can be used to decipher potential therapeutics for COVID-19 and related pathologies, such as Neuro-COVID. Here, we used the raw RNA-seq reads (Single-End) in quadruplicates derived using Illumina Next Seq 500 from SARS-CoV-infected primary human bronchial epithelium (NHBE) and mock-treated NHBE cells obtained from the Gene Expression Omnibus (GEO) (GSE147507), and the quality control (QC) was evaluated using the CLC Genomics Workbench 20.0 (Qiagen, United States) before the RNA-seq analysis using BioJupies web tool and iPathwayGuide for gene ontologies (GO), pathways, upstream regulator genes, small molecules, and natural products. Additionally, single-cell transcriptomics data (GSE163005) of meta clusters of immune cells from the cerebrospinal fluid (CSF), such as T-cells/natural killer cells (NK) (TcMeta), dendritic cells (DCMeta), and monocytes/granulocyte (monoMeta) cell types for comparison, namely, Neuro-COVID versus idiopathic intracranial hypertension (IIH), were analyzed using iPathwayGuide. L1000 fireworks display (L1000FWD) and L1000 characteristic direction signature search engine (L1000 CDS2) web tools were used to uncover the small molecules that could potentially reverse the COVID-19 and Neuro-COVID-associated gene signatures. We uncovered small molecules such as camptothecin, importazole, and withaferin A, which can potentially reverse COVID-19 associated gene signatures. In addition, withaferin A, trichostatin A, narciclasine, camptothecin, and JQ1 have the potential to reverse Neuro-COVID gene signatures. Furthermore, the gene set enrichment analysis (GSEA) preranked method and Metascape web tool were used to decipher and annotate the gene signatures that were potentially reversed by these small molecules. In conclusion, our study unravels a rapid approach for applying next-generation knowledge discovery (NGKD) platforms to discover small molecules with therapeutic potential against COVID-19 and its related disease pathologies.

Introduction: Alzheimer’s disease (AD) is a major cause of the development of cognitive decline and dementia. AD and associated dementias (ADRD) are the major contributors to the enormous burden of morbidity and mortality worldwide. To date, there are no robust therapies to alleviate or cure this debilitating disease. Most drug treatments focus on restoring the normal function of neurons and the cells that cause inflammation, such as microglia in the brain. However, the role of astrocytes, the brain’s housekeeping cells, in the development of AD and the initiation of dementia is still not well understood.Objective: To decipher the role of astrocytes in the entorhinal cortex of AD patients using single nuclear RNA sequencing (snRNASeq) datasets from the Single Cell RNA-seq Database for Alzheimer’s Disease (scREAD). The datasets were originally derived from astrocytes, isolated from the entorhinal cortex of AD brain and healthy brain to decipher disease-specific signaling pathways as well as drugs and natural products that reverse AD-specific signatures in astrocytes.Methods: We used snRNASeq datasets from the scREAD database originally derived from astrocytes isolated from the entorhinal cortex of AD and healthy brains from the Gene Expression Omnibus (GEO) (GSE138852 and GSE147528) and analyzed them using next-generation knowledge discovery (NGKD) platforms. scREAD is a user-friendly open-source interface available at https://bmbls.bmi.osumc.edu/scread/that enables more discovery-oriented strategies. snRNASeq data and metadata can also be visualized and downloaded via an interactive web application at adsn.ddnetbio.com. Differentially expressed genes (DEGs) for each snRNASeq dataset were analyzed using iPathwayGuide to compare and derive disease-specific pathways, gene ontologies, and in silico predictions of drugs and natural products that regulate AD -specific signatures in astrocytes. In addition, DEGs were analyzed using the L1000FWD and L1000CDS2 signature search programming interfaces (APIs) to identify additional drugs and natural products that mimic or reverse AD-specific gene signatures in astrocytes.Results: We found that PI3K/AKT signaling, Wnt signaling, neuroactive ligand-receptor interaction pathways, neurodegeneration pathways, etc. were significantly impaired in astrocytes from the entorhinal cortex of AD patients. Biological processes such as glutamate receptor signaling pathway, regulation of synapse organization, cell-cell adhesion via plasma membrane adhesion molecules, and chylomicrons were negatively enriched in the astrocytes from the entorhinal cortex of AD patients. Gene sets involved in cellular components such as postsynaptic membrane, synaptic membrane, postsynapse, and synapse part were negatively enriched (p < 0.01). Moreover, molecular functions such as glutamate receptor activity, neurotransmitter receptor activity, and extracellular ligand-gated ion channels were negatively regulated in the astrocytes of the entorhinal cortex of AD patients (p < 0.01). Moreover, the application of NGKD platforms revealed that antirheumatic drugs, vitamin-E, emetine, narciclasine, cephaeline, trichostatin A, withaferin A, dasatinib, etc. can potentially reverse gene signatures associated with AD.Conclusions: The present study highlights an innovative approach to use NGKD platforms to find unique disease-associated signaling pathways and specific synthetic drugs and natural products that can potentially reverse AD and ADRD-associated gene signatures.

The helicase-like transcription factor (HLTF) gene—a tumor suppressor in human colorectal cancer (CRC)—is regulated by alternative splicing and promoter hypermethylation. In this study, we used the AOM/DSS-induced mouse model to show Hltf-deletion caused poor survival concomitant with increased tumor multiplicity, and dramatically shifted the topographic distribution of lesions into the rectum. Differential isoform expression analysis revealed both the truncated isoform that lacks a DNA-repair domain and the full length isoform capable of DNA damage repair are present during adenocarcinoma formation in controls. iPathwayGuide identified 51 dynamically regulated genes of 10,967 total genes with measured expression. Oxidative Phosphorylation (Kegg: 00190), the top biological pathway perturbed by Hltf-deletion, resulted from increased transcription of Atp5e, Cox7c, Uqcr11, Ndufa4 and Ndufb6 genes, concomitant with increased endogenous levels of ATP (p = 0.0062). Upregulation of gene expression, as validated with qRT-PCR, accompanied a stable mtDNA/nDNA ratio. This is the first study to show Hltf-deletion in an inflammation-associated CRC model elevates mitochondrial bioenergetics.

Cuffdiff, part of Cufflinks, uses RPKM values to calculate changes in gene expression. Cuffdiff data were input into iPathwayGuide. Met-analysis calculated long fold change (logFC) and an adjusted p-value (adjpv) for each comparison. The minus sign in the column for logFC shows 136 genes were downregulated and 15 genes were upregulated. (CSV)

IntroductionOvarian cancer recurs in most High Grade Serous Ovarian Cancer (HGSOC) patients, including initial responders, after standard of care. To improve patient survival, we need to identify and understand the factors contributing to early or late recurrence and therapeutically target these mechanisms. We hypothesized that in HGSOC, the response to chemotherapy is associated with a specific gene expression signature determined by the tumor microenvironment. In this study, we sought to determine the differences in gene expression and the tumor immune microenvironment between patients who show early recurrence (within 6 months) compared to those who show late recurrence following chemotherapy.MethodsPaired tumor samples were obtained before and after Carboplatin and Taxol chemotherapy from 24 patients with HGSOC. Bioinformatic transcriptomic analysis was performed on the tumor samples to determine the gene expression signature associated with differences in recurrence pattern. Gene Ontology and Pathway analysis was performed using AdvaitaBio’s iPathwayGuide software. Tumor immune cell fractions were imputed using CIBERSORTx. Results were compared between late recurrence and early recurrence patients, and between paired pre-chemotherapy and post-chemotherapy samples.ResultsThere was no statistically significant difference between early recurrence or late recurrence ovarian tumors pre-chemotherapy. However, chemotherapy induced significant immunological changes in tumors from late recurrence patients but had no impact on tumors from early recurrence patients. The key immunological change induced by chemotherapy in late recurrence patients was the reversal of pro-tumor immune signature.DiscussionWe report for the first time, the association between immunological modifications in response to chemotherapy and the time of recurrence. Our findings provide novel opportunities to ultimately improve ovarian cancer patient survival.