Publications by authors named "Feixiong Cheng"

140 Publications

Cardiac risk stratification in cancer patients: A longitudinal patient-patient network analysis.

PLoS Med 2021 Aug 2;18(8):e1003736. Epub 2021 Aug 2.

Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio, United States of America.

Background: Cardiovascular disease is a leading cause of death in general population and the second leading cause of mortality and morbidity in cancer survivors after recurrent malignancy in the United States. The growing awareness of cancer therapy-related cardiac dysfunction (CTRCD) has led to an emerging field of cardio-oncology; yet, there is limited knowledge on how to predict which patients will experience adverse cardiac outcomes. We aimed to perform unbiased cardiac risk stratification for cancer patients using our large-scale, institutional electronic medical records.

Methods And Findings: We built a large longitudinal (up to 22 years' follow-up from March 1997 to January 2019) cardio-oncology cohort having 4,632 cancer patients in Cleveland Clinic with 5 diagnosed cardiac outcomes: atrial fibrillation, coronary artery disease, heart failure, myocardial infarction, and stroke. The entire population includes 84% white Americans and 11% black Americans, and 59% females versus 41% males, with median age of 63 (interquartile range [IQR]: 54 to 71) years old. We utilized a topology-based K-means clustering approach for unbiased patient-patient network analyses of data from general demographics, echocardiogram (over 25,000), lab testing, and cardiac factors (cardiac). We performed hazard ratio (HR) and Kaplan-Meier analyses to identify clinically actionable variables. All confounding factors were adjusted by Cox regression models. We performed random-split and time-split training-test validation for our model. We identified 4 clinically relevant subgroups that are significantly correlated with incidence of cardiac outcomes and mortality. Among the 4 subgroups, subgroup I (n = 625) has the highest risk of de novo CTRCD (28%) with an HR of 3.05 (95% confidence interval (CI) 2.51 to 3.72). Patients in subgroup IV (n = 1,250) had the worst survival probability (HR 4.32, 95% CI 3.82 to 4.88). From longitudinal patient-patient network analyses, the patients in subgroup I had a higher percentage of de novo CTRCD and a worse mortality within 5 years after the initiation of cancer therapies compared to long-time exposure (6 to 20 years). Using clinical variable network analyses, we identified that serum levels of NT-proB-type Natriuretic Peptide (NT-proBNP) and Troponin T are significantly correlated with patient's mortality (NT-proBNP > 900 pg/mL versus NT-proBNP = 0 to 125 pg/mL, HR = 2.95, 95% CI 2.28 to 3.82, p < 0.001; Troponin T > 0.05 μg/L versus Troponin T ≤ 0.01 μg/L, HR = 2.08, 95% CI 1.83 to 2.34, p < 0.001). Study limitations include lack of independent cardio-oncology cohorts from different healthcare systems to evaluate the generalizability of the models. Meanwhile, the confounding factors, such as multiple medication usages, may influence the findings.

Conclusions: In this study, we demonstrated that the patient-patient network clustering methodology is clinically intuitive, and it allows more rapid identification of cancer survivors that are at greater risk of cardiac dysfunction. We believed that this study holds great promise for identifying novel cardiac risk subgroups and clinically actionable variables for the development of precision cardio-oncology.
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http://dx.doi.org/10.1371/journal.pmed.1003736DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8366997PMC
August 2021

Multimodal single-cell omics analysis identifies epithelium-immune cell interactions and immune vulnerability associated with sex differences in COVID-19.

Signal Transduct Target Ther 2021 07 30;6(1):292. Epub 2021 Jul 30.

Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA.

Sex differences in the susceptibility of SARS-CoV-2 infection and severity have been controversial, and the underlying mechanisms of COVID-19 in a sex-specific manner remain understudied. Here we inspected sex differences in SARS-CoV-2 infection, hospitalization, admission to the intensive care unit (ICU), sera inflammatory biomarker profiling, and single-cell RNA-sequencing (scRNA-seq) profiles across nasal, bronchoalveolar lavage fluid (BALF), and peripheral blood mononuclear cells (PBMCs) from COVID-19 patients with varying degrees of disease severities. Our propensity score-matching observations revealed that male individuals have a 29% elevated likelihood of SARS-CoV-2 positivity, with a hazard ratio (HR) 1.32 (95% confidence interval [CI] 1.18-1.48) for hospitalization and HR 1.51 (95% CI 1.24-1.84) for admission to ICU. Sera from male patients at hospital admission had elevated neutrophil-lymphocyte ratio and elevated expression of inflammatory markers (C-reactive protein and procalcitonin). We found that SARS-CoV-2 entry factors, including ACE2, TMPRSS2, FURIN, and NRP1, have elevated expression in nasal squamous cells from male individuals with moderate and severe COVID-19. We observed male-biased transcriptional activation in SARS-CoV-2-infected macrophages from BALF and sputum samples, which offers potential molecular mechanism for sex-biased susceptibility to viral infection. Cell-cell interaction network analysis reveals potential epithelium-immune cell interactions and immune vulnerability underlying male-elevated disease severity and mortality in COVID-19. Mechanistically, monocyte-elevated expression of Toll-like receptor 7 (TLR7) and Bruton tyrosine kinase (BTK) is associated with severe outcomes in males with COVID-19. In summary, these findings provide basis to decipher immune responses underlying sex differences and designing sex-specific targeted interventions and patient care for COVID-19.
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http://dx.doi.org/10.1038/s41392-021-00709-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8322111PMC
July 2021

Systemic Administration of Tempol Attenuates the Cardiorespiratory Depressant Effects of Fentanyl.

Front Pharmacol 2021 23;12:690407. Epub 2021 Jun 23.

Department of Pediatrics, Case Western Reserve University, Cleveland, OH, United States.

Fentanyl is a high-potency opioid receptor agonist that elicits profound analgesia and suppression of breathing in humans and animals. To date, there is limited evidence as to whether changes in oxidant stress are important factors in any of the actions of acutely administered fentanyl. This study determined whether the clinically approved superoxide dismutase mimetic, Tempol (4-hydroxy-2,2,6,6-tetramethylpiperidine-N-oxyl), or a potent antioxidant, N-acetyl-L-cysteine methyl ester (L-NACme), modify the cardiorespiratory and analgesic actions of fentanyl. We examined whether the prior systemic injection of Tempol or L-NACme affects the cardiorespiratory and/or analgesic responses elicited by the subsequent injection of fentanyl in isoflurane-anesthetized and/or freely moving male Sprague-Dawley rats. Bolus injections of Tempol (25, 50 or 100 mg/kg, IV) elicited minor increases in frequency of breathing, tidal volume and minute ventilation. The ventilatory-depressant effects of fentanyl (5 μg/kg, IV) given 15 min later were dose-dependently inhibited by prior injections of Tempol. Tempol elicited dose-dependent and transient hypotension that had (except for the highest dose) resolved when fentanyl was injected. The hypotensive responses elicited by fentanyl were markedly blunted after Tempol pretreatment. The analgesic actions of fentanyl (25 μg/kg, IV) were not affected by Tempol (100 mg/kg, IV). L-NACme did not modify any of the effects of fentanyl. We conclude that prior administration of Tempol attenuates the cardiorespiratory actions of fentanyl without affecting the analgesic effects of this potent opioid. As such, Tempol may not directly affect opioid-receptors that elicit the effects of fentanyl. Whether, the effects of Tempol are solely due to alterations in oxidative stress is in doubt since the powerful antioxidant, L-NACme, did not affect fentanyl-induced suppression of breathing.
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http://dx.doi.org/10.3389/fphar.2021.690407DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8260831PMC
June 2021

Network medicine links SARS-CoV-2/COVID-19 infection to brain microvascular injury and neuroinflammation in dementia-like cognitive impairment.

Alzheimers Res Ther 2021 06 9;13(1):110. Epub 2021 Jun 9.

Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, 44195, USA.

Background: Dementia-like cognitive impairment is an increasingly reported complication of SARS-CoV-2 infection. However, the underlying mechanisms responsible for this complication remain unclear. A better understanding of causative processes by which COVID-19 may lead to cognitive impairment is essential for developing preventive and therapeutic interventions.

Methods: In this study, we conducted a network-based, multimodal omics comparison of COVID-19 and neurologic complications. We constructed the SARS-CoV-2 virus-host interactome from protein-protein interaction assay and CRISPR-Cas9-based genetic assay results and compared network-based relationships therein with those of known neurological manifestations using network proximity measures. We also investigated the transcriptomic profiles (including single-cell/nuclei RNA-sequencing) of Alzheimer's disease (AD) marker genes from patients infected with COVID-19, as well as the prevalence of SARS-CoV-2 entry factors in the brains of AD patients not infected with SARS-CoV-2.

Results: We found significant network-based relationships between COVID-19 and neuroinflammation and brain microvascular injury pathways and processes which are implicated in AD. We also detected aberrant expression of AD biomarkers in the cerebrospinal fluid and blood of patients with COVID-19. While transcriptomic analyses showed relatively low expression of SARS-CoV-2 entry factors in human brain, neuroinflammatory changes were pronounced. In addition, single-nucleus transcriptomic analyses showed that expression of SARS-CoV-2 host factors (BSG and FURIN) and antiviral defense genes (LY6E, IFITM2, IFITM3, and IFNAR1) was elevated in brain endothelial cells of AD patients and healthy controls relative to neurons and other cell types, suggesting a possible role for brain microvascular injury in COVID-19-mediated cognitive impairment. Overall, individuals with the AD risk allele APOE E4/E4 displayed reduced expression of antiviral defense genes compared to APOE E3/E3 individuals.

Conclusion: Our results suggest significant mechanistic overlap between AD and COVID-19, centered on neuroinflammation and microvascular injury. These results help improve our understanding of COVID-19-associated neurological manifestations and provide guidance for future development of preventive or treatment interventions, although causal relationship and mechanistic pathways between COVID-19 and AD need future investigations.
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http://dx.doi.org/10.1186/s13195-021-00850-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8189279PMC
June 2021

A retrospective analysis of cardiovascular adverse events associated with immune checkpoint inhibitors.

Cardiooncology 2021 May 28;7(1):19. Epub 2021 May 28.

Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, 44195, USA.

Background: Modern therapies in oncology have increased cancer survivorship, as well as the incidence of cardiovascular adverse events. While immune checkpoint inhibitors have shown significant clinical impact in several cancer types, the incidence of immune-related cardiovascular (CV) adverse events poses an additional health concern and has been reported.

Methods: We performed a retrospective analysis of the FDA Adverse Event Reporting System data of suspect product reports for immunotherapy and classical chemotherapy from January 2010-March 2020. We identified 90,740 total adverse event reports related to immune checkpoint inhibitors and classical chemotherapy.

Results: We found that myocarditis was significantly associated with patients receiving anti-program cell death protein 1 (PD-1) or anti-program death ligand 1 (PD-L1), odds ratio (OR) = 23.86 (95% confidence interval [CI] 11.76-48.42, (adjusted p-value) q <  0.001), and combination immunotherapy, OR = 7.29 (95% CI 1.03-51.89, q = 0.047). Heart failure was significantly associated in chemotherapy compared to PD-(L)1, OR = 0.50 (95% CI 0.37-0.69, q <  0.001), CTLA4, OR = 0.08 (95% CI 0.03-0.20, q <  0.001), and combination immunotherapy, OR = 0.25 (95% CI 0.13-0.48, q <  0.001). Additionally, we observe a sex-specificity towards males in cardiac adverse reports for arrhythmias, OR = 0.81 (95% CI 0.75-0.87, q <  0.001), coronary artery disease, 0.63 (95% CI 0.53-0.76, q <  0.001), myocardial infarction, OR = 0.60 (95% CI 0.53-0.67, q <  0.001), myocarditis, OR = 0.59 (95% CI 0.47-0.75, q <  0.001) and pericarditis, OR = 0.5 (95% CI 0.35-0.73, q <  0.001).

Conclusion: Our study provides the current risk estimates of cardiac adverse events in patients treated with immunotherapy compared to conventional chemotherapy. Understanding the clinical risk factors that predispose immunotherapy-treated cancer patients to often fatal CV adverse events will be crucial in Cardio-Oncology management.
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http://dx.doi.org/10.1186/s40959-021-00106-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8161966PMC
May 2021

Identifying miRNAs in multiple sclerosis gray matter lesions that correlate with atrophy measures.

Ann Clin Transl Neurol 2021 06 12;8(6):1279-1291. Epub 2021 May 12.

Department of Neurosciences, Cleveland Clinic, Cleveland, Ohio, USA.

Objective: Multiple sclerosis (MS) is an inflammatory, demyelinating and neurodegenerative disease of the central nervous system (CNS). Though MS was initially considered to be a white matter demyelinating disease, myelin loss in cortical gray matter has been reported in all disease stages. We previously identified microRNAs (miRNAs) in white matter lesions (WMLs) that are detected in serum from MS patients. However, miRNA expression profiles in gray matter lesions (GMLs) from progressive MS brains are understudied.

Methods: We used a combination of global miRNAs and gene expression profiling of GMLs and independent validation using real-time quantitative polymerase chain reaction (RT-qPCR), immuno-in situ hybridization, and immunohistochemistry.

Results: Compared to matched myelinated gray matter (GM) regions, we identified 82 miRNAs in GMLs, of which 10 were significantly upregulated and 17 were significantly downregulated. Among these 82 miRNAs, 13 were also detected in serum and importantly were associated with brain atrophy in MS patients. The predicted target mRNAs of these miRNAs belonged to pathways associated with axonal guidance, TGF-β signaling, and FOXO signaling. Further, using state-of-the-art human protein-protein interactome network analysis, we mapped the four key GM atrophy-associated miRNAs (hsa-miR-149*, hsa-miR-20a, hsa-miR-29c, and hsa-miR-25) to their target mRNAs that were also changed in GMLs.

Interpretation: Our study identifies miRNAs altered in GMLs in progressive MS brains that correlate with atrophy measures. As these miRNAs were also detected in sera of MS patients, these could act as markers of GML demyelination in MS.
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http://dx.doi.org/10.1002/acn3.51365DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8164853PMC
June 2021

NHLBI-CMREF Workshop Report on Pulmonary Vascular Disease Classification: JACC State-of-the-Art Review.

J Am Coll Cardiol 2021 Apr;77(16):2040-2052

Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA.

The National Heart, Lung, and Blood Institute and the Cardiovascular Medical Research and Education Fund held a workshop on the application of pulmonary vascular disease omics data to the understanding, prevention, and treatment of pulmonary vascular disease. Experts in pulmonary vascular disease, omics, and data analytics met to identify knowledge gaps and formulate ideas for future research priorities in pulmonary vascular disease in line with National Heart, Lung, and Blood Institute Strategic Vision goals. The group identified opportunities to develop analytic approaches to multiomic datasets, to identify molecular pathways in pulmonary vascular disease pathobiology, and to link novel phenotypes to meaningful clinical outcomes. The committee suggested support for interdisciplinary research teams to develop and validate analytic methods, a national effort to coordinate biosamples and data, a consortium of preclinical investigators to expedite target evaluation and drug development, longitudinal assessment of molecular biomarkers in clinical trials, and a task force to develop a master clinical trials protocol for pulmonary vascular disease.
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http://dx.doi.org/10.1016/j.jacc.2021.02.056DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8065203PMC
April 2021

Reducing acetylated tau is neuroprotective in brain injury.

Cell 2021 May 13;184(10):2715-2732.e23. Epub 2021 Apr 13.

Department of Biomedical Informatics, College of Medicine, Ohio State University, Columbus, OH, USA.

Traumatic brain injury (TBI) is the largest non-genetic, non-aging related risk factor for Alzheimer's disease (AD). We report here that TBI induces tau acetylation (ac-tau) at sites acetylated also in human AD brain. This is mediated by S-nitrosylated-GAPDH, which simultaneously inactivates Sirtuin1 deacetylase and activates p300/CBP acetyltransferase, increasing neuronal ac-tau. Subsequent tau mislocalization causes neurodegeneration and neurobehavioral impairment, and ac-tau accumulates in the blood. Blocking GAPDH S-nitrosylation, inhibiting p300/CBP, or stimulating Sirtuin1 all protect mice from neurodegeneration, neurobehavioral impairment, and blood and brain accumulation of ac-tau after TBI. Ac-tau is thus a therapeutic target and potential blood biomarker of TBI that may represent pathologic convergence between TBI and AD. Increased ac-tau in human AD brain is further augmented in AD patients with history of TBI, and patients receiving the p300/CBP inhibitors salsalate or diflunisal exhibit decreased incidence of AD and clinically diagnosed TBI.
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http://dx.doi.org/10.1016/j.cell.2021.03.032DOI Listing
May 2021

Network medicine links SARS-CoV-2/COVID-19 infection to brain microvascular injury and neuroinflammation in dementia-like cognitive impairment.

bioRxiv 2021 Mar 22. Epub 2021 Mar 22.

Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA.

Background: Dementia-like cognitive impairment is an increasingly reported complication of SARS-CoV-2 infection. However, the underlying mechanisms responsible for this complication remain unclear. A better understanding of causative processes by which COVID-19 may lead to cognitive impairment is essential for developing preventive interventions.

Methods: In this study, we conducted a network-based, multimodal genomics comparison of COVID-19 and neurologic complications. We constructed the SARS-CoV-2 virus-host interactome from protein-protein interaction assay and CRISPR-Cas9 based genetic assay results, and compared network-based relationships therein with those of known neurological manifestations using network proximity measures. We also investigated the transcriptomic profiles (including single-cell/nuclei RNA-sequencing) of Alzheimer's disease (AD) marker genes from patients infected with COVID-19, as well as the prevalence of SARS-CoV-2 entry factors in the brains of AD patients not infected with SARS-CoV-2.

Results: We found significant network-based relationships between COVID-19 and neuroinflammation and brain microvascular injury pathways and processes which are implicated in AD. We also detected aberrant expression of AD biomarkers in the cerebrospinal fluid and blood of patients with COVID-19. While transcriptomic analyses showed relatively low expression of SARS-CoV-2 entry factors in human brain, neuroinflammatory changes were pronounced. In addition, single-nucleus transcriptomic analyses showed that expression of SARS-CoV-2 host factors ( and ) and antiviral defense genes ( , , , and ) was significantly elevated in brain endothelial cells of AD patients and healthy controls relative to neurons and other cell types, suggesting a possible role for brain microvascular injury in COVID-19-mediated cognitive impairment. Notably, individuals with the AD risk allele E4/E4 displayed reduced levels of antiviral defense genes compared to E3/E3 individuals.

Conclusion: Our results suggest significant mechanistic overlap between AD and COVID-19, strongly centered on neuroinflammation and microvascular injury. These results help improve our understanding of COVID-19-associated neurological manifestations and provide guidance for future development of preventive or treatment interventions.
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http://dx.doi.org/10.1101/2021.03.15.435423DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8010732PMC
March 2021

Glutathione ethyl ester reverses the deleterious effects of fentanyl on ventilation and arterial blood-gas chemistry while prolonging fentanyl-induced analgesia.

Sci Rep 2021 03 26;11(1):6985. Epub 2021 Mar 26.

Department of Pediatrics, Case Western Reserve University, 10900 Euclid Avenue, Cleveland, OH, 44106-4984, USA.

There is an urgent need to develop novel compounds that prevent the deleterious effects of opioids such as fentanyl on minute ventilation while, if possible, preserving the analgesic actions of the opioids. We report that L-glutathione ethyl ester (GSHee) may be such a novel compound. In this study, we measured tail flick latency (TFL), arterial blood gas (ABG) chemistry, Alveolar-arterial gradient, and ventilatory parameters by whole body plethysmography to determine the responses elicited by bolus injections of fentanyl (75 μg/kg, IV) in male adult Sprague-Dawley rats that had received a bolus injection of GSHee (100 μmol/kg, IV) 15 min previously. GSHee given alone had minimal effects on TFL, ABG chemistry and A-a gradient whereas it elicited changes in some ventilatory parameters such as an increase in breathing frequency. In vehicle-treated rats, fentanyl elicited (1) an increase in TFL, (2) decreases in pH, pO and sO and increases in pCO (all indicative of ventilatory depression), (3) an increase in Alveolar-arterial gradient (indicative of a mismatch in ventilation-perfusion in the lungs), and (4) changes in ventilatory parameters such as a reduction in tidal volume, that were indicative of pronounced ventilatory depression. In GSHee-pretreated rats, fentanyl elicited a more prolonged analgesia, relatively minor changes in ABG chemistry and Alveolar-arterial gradient, and a substantially milder depression of ventilation. GSHee may represent an effective member of a novel class of thiolester drugs that are able to prevent the ventilatory depressant effects elicited by powerful opioids such as fentanyl and their deleterious effects on gas-exchange in the lungs without compromising opioid analgesia.
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http://dx.doi.org/10.1038/s41598-021-86458-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7997982PMC
March 2021

The Epidemiological and Mechanistic Understanding of the Neurological Manifestations of COVID-19: A Comprehensive Meta-Analysis and a Network Medicine Observation.

Front Neurosci 2021 24;15:606926. Epub 2021 Feb 24.

Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, United States.

The clinical characteristics and biological effects on the nervous system of infection with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) remain poorly understood. The aim of this study is to advance epidemiological and mechanistic understanding of the neurological manifestations of coronavirus disease 2019 (COVID-19) using stroke as a case study. In this study, we performed a meta-analysis of clinical studies reporting stroke history, intensive inflammatory response, and procoagulant state C-reactive protein (CRP), Procalcitonin (PCT), and coagulation indicator (D-dimer) in patients with COVID-19. Via network-based analysis of SARS-CoV-2 host genes and stroke-associated genes in the human protein-protein interactome, we inspected the underlying inflammatory mechanisms between COVID-19 and stroke. Finally, we further verified the network-based findings using three RNA-sequencing datasets generated from SARS-CoV-2 infected populations. We found that the overall pooled prevalence of stroke history was 2.98% (95% CI, 1.89-4.68; =69.2%) in the COVID-19 population. Notably, the severe group had a higher prevalence of stroke (6.06%; 95% CI 3.80-9.52; = 42.6%) compare to the non-severe group (1.1%, 95% CI 0.72-1.71; = 0.0%). There were increased levels of CRP, PCT, and D-dimer in severe illness, and the pooled mean difference was 40.7 mg/L (95% CI, 24.3-57.1), 0.07 μg/L (95% CI, 0.04-0.10) and 0.63 mg/L (95% CI, 0.28-0.97), respectively. Vascular cell adhesion molecule 1 (VCAM-1), one of the leukocyte adhesion molecules, is suspected to play a vital role of SARS-CoV-2 mediated inflammatory responses. RNA-sequencing data analyses of the SARS-CoV-2 infected patients further revealed the relative importance of inflammatory responses in COVID-19-associated neurological manifestations. In summary, we identified an elevated vulnerability of those with a history of stroke to severe COVID-19 underlying inflammatory responses (i.e., VCAM-1) and procoagulant pathways, suggesting monotonic relationships, thus implicating causality.
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http://dx.doi.org/10.3389/fnins.2021.606926DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7959722PMC
February 2021

Network-based drug repurposing for novel coronavirus 2019-nCoV/SARS-CoV-2.

Cell Discov 2020 Mar 16;6(1):14. Epub 2020 Mar 16.

Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, 44195, USA.

Human coronaviruses (HCoVs), including severe acute respiratory syndrome coronavirus (SARS-CoV) and 2019 novel coronavirus (2019-nCoV, also known as SARS-CoV-2), lead global epidemics with high morbidity and mortality. However, there are currently no effective drugs targeting 2019-nCoV/SARS-CoV-2. Drug repurposing, representing as an effective drug discovery strategy from existing drugs, could shorten the time and reduce the cost compared to de novo drug discovery. In this study, we present an integrative, antiviral drug repurposing methodology implementing a systems pharmacology-based network medicine platform, quantifying the interplay between the HCoV-host interactome and drug targets in the human protein-protein interaction network. Phylogenetic analyses of 15 HCoV whole genomes reveal that 2019-nCoV/SARS-CoV-2 shares the highest nucleotide sequence identity with SARS-CoV (79.7%). Specifically, the envelope and nucleocapsid proteins of 2019-nCoV/SARS-CoV-2 are two evolutionarily conserved regions, having the sequence identities of 96% and 89.6%, respectively, compared to SARS-CoV. Using network proximity analyses of drug targets and HCoV-host interactions in the human interactome, we prioritize 16 potential anti-HCoV repurposable drugs (e.g., melatonin, mercaptopurine, and sirolimus) that are further validated by enrichment analyses of drug-gene signatures and HCoV-induced transcriptomics data in human cell lines. We further identify three potential drug combinations (e.g., sirolimus plus dactinomycin, mercaptopurine plus melatonin, and toremifene plus emodin) captured by the "Complementary Exposure" pattern: the targets of the drugs both hit the HCoV-host subnetwork, but target separate neighborhoods in the human interactome network. In summary, this study offers powerful network-based methodologies for rapid identification of candidate repurposable drugs and potential drug combinations targeting 2019-nCoV/SARS-CoV-2.
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http://dx.doi.org/10.1038/s41421-020-0153-3DOI Listing
March 2020

A rational design of a multi-epitope vaccine against SARS-CoV-2 which accounts for the glycan shield of the spike glycoprotein.

J Biomol Struct Dyn 2021 Mar 10:1-15. Epub 2021 Mar 10.

Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio, USA.

The ongoing global health crisis caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), the virus which leads to Coronavirus Disease 2019 (COVID-19) has impacted not only the health of people everywhere, but the economy in nations across the world. While vaccine candidates and therapeutics are currently undergoing clinical trials, there is a lack of proven effective treatments or cures for COVID-19. In this study, we have presented a synergistic computational platform, including molecular dynamics simulations and immunoinformatics techniques, to rationally design a multi-epitope vaccine candidate for COVID-19. This platform combines epitopes across Linear B Lymphocytes (LBL), Cytotoxic T Lymphocytes (CTL) and Helper T Lymphocytes (HTL) derived from both mutant and wild-type spike glycoproteins from SARS-CoV-2 with diverse protein conformations. In addition, this vaccine construct also takes the considerable glycan shield of the spike glycoprotein into account, which protects it from immune response. We have identified a vaccine candidate (a 35.9 kDa protein), named COVCCF, which is composed of 5 LBL, 6 HTL, and 6 CTL epitopes from the spike glycoprotein of SARS-CoV-2. Using multi-dose immune simulations, COVCCF induces elevated levels of immunoglobulin activity (IgM, IgG1, IgG2), and induces strong responses from B lymphocytes, CD4 T-helper lymphocytes, and CD8 T-cytotoxic lymphocytes. COVCCF induces cytokines important to innate immunity, including IFN-γ, IL4, and IL10. Additionally, COVCCF has ideal pharmacokinetic properties and low immune-related toxicities. In summary, this study provides a powerful, computational vaccine design platform for rapid development of vaccine candidates (including COVCCF) for effective prevention of COVID-19.Communicated by Ramaswamy H. Sarma.
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http://dx.doi.org/10.1080/07391102.2021.1894986DOI Listing
March 2021

Multimodal single-cell/nucleus RNA sequencing data analysis uncovers molecular networks between disease-associated microglia and astrocytes with implications for drug repurposing in Alzheimer's disease.

Genome Res 2021 Feb 24. Epub 2021 Feb 24.

Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio 44195, USA.

Because disease-associated microglia (DAM) and disease-associated astrocytes (DAA) are involved in the pathophysiology of Alzheimer's disease (AD), we systematically identified molecular networks between DAM and DAA to uncover novel therapeutic targets for AD. Specifically, we develop a network-based methodology that leverages single-cell/nucleus RNA sequencing data from both transgenic mouse models and AD patient brains, as well as drug-target network, metabolite-enzyme associations, the human protein-protein interactome, and large-scale longitudinal patient data. Through this approach, we find both common and unique gene network regulators between DAM (i.e., , , and ) and DAA (i.e., , , and ) that are significantly enriched by neuro-inflammatory pathways and well-known genetic variants (i.e., ). We identify shared immune pathways between DAM and DAA, including Th17 cell differentiation and chemokine signaling. Last, integrative metabolite-enzyme network analyses suggest that fatty acids and amino acids may trigger molecular alterations in DAM and DAA. Combining network-based prediction and retrospective case-control observations with 7.2 million individuals, we identify that usage of fluticasone (an approved glucocorticoid receptor agonist) is significantly associated with a reduced incidence of AD (hazard ratio [HR] = 0.86, 95% confidence interval [CI] 0.83-0.89, < 1.0 × 10). Propensity score-stratified cohort studies reveal that usage of mometasone (a stronger glucocorticoid receptor agonist) is significantly associated with a decreased risk of AD (HR = 0.74, 95% CI 0.68-0.81, < 1.0 × 10) compared to fluticasone after adjusting age, gender, and disease comorbidities. In summary, we present a network-based, multimodal methodology for single-cell/nucleus genomics-informed drug discovery and have identified fluticasone and mometasone as potential treatments in AD.
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http://dx.doi.org/10.1101/gr.272484.120DOI Listing
February 2021

Comprehensive characterization of protein-protein interactions perturbed by disease mutations.

Nat Genet 2021 03 8;53(3):342-353. Epub 2021 Feb 8.

Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.

Technological and computational advances in genomics and interactomics have made it possible to identify how disease mutations perturb protein-protein interaction (PPI) networks within human cells. Here, we show that disease-associated germline variants are significantly enriched in sequences encoding PPI interfaces compared to variants identified in healthy participants from the projects 1000 Genomes and ExAC. Somatic missense mutations are also significantly enriched in PPI interfaces compared to noninterfaces in 10,861 tumor exomes. We computationally identified 470 putative oncoPPIs in a pan-cancer analysis and demonstrate that oncoPPIs are highly correlated with patient survival and drug resistance/sensitivity. We experimentally validate the network effects of 13 oncoPPIs using a systematic binary interaction assay, and also demonstrate the functional consequences of two of these on tumor cell growth. In summary, this human interactome network framework provides a powerful tool for prioritization of alleles with PPI-perturbing mutations to inform pathobiological mechanism- and genotype-based therapeutic discovery.
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http://dx.doi.org/10.1038/s41588-020-00774-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8237108PMC
March 2021

My personal mutanome: a computational genomic medicine platform for searching network perturbing alleles linking genotype to phenotype.

Genome Biol 2021 01 29;22(1):53. Epub 2021 Jan 29.

Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, 44195, USA.

Massive genome sequencing data have inspired new challenges in personalized treatments and facilitated oncological drug discovery. We present a comprehensive database, My Personal Mutanome (MPM), for accelerating the development of precision cancer medicine protocols. MPM contains 490,245 mutations from over 10,800 tumor exomes across 33 cancer types in The Cancer Genome Atlas mapped to 94,563 structure-resolved/predicted protein-protein interaction interfaces ("edgetic") and 311,022 functional sites ("nodetic"), including ligand-protein binding sites and 8 types of protein posttranslational modifications. In total, 8884 survival results and 1,271,132 drug responses are obtained for these mapped interactions. MPM is available at https://mutanome.lerner.ccf.org .
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http://dx.doi.org/10.1186/s13059-021-02269-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7845113PMC
January 2021

AlzGPS: a genome-wide positioning systems platform to catalyze multi-omics for Alzheimer's drug discovery.

Alzheimers Res Ther 2021 01 13;13(1):24. Epub 2021 Jan 13.

Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, 44195, USA.

Background: Recent DNA/RNA sequencing and other multi-omics technologies have advanced the understanding of the biology and pathophysiology of AD, yet there is still a lack of disease-modifying treatments for AD. A new approach to integration of the genome, transcriptome, proteome, and human interactome in the drug discovery and development process is essential for this endeavor.

Methods: In this study, we developed AlzGPS (Genome-wide Positioning Systems platform for Alzheimer's Drug Discovery, https://alzgps.lerner.ccf.org ), a comprehensive systems biology tool to enable searching, visualizing, and analyzing multi-omics, various types of heterogeneous biological networks, and clinical databases for target identification and development of effective prevention and treatment for AD.

Results: Via AlzGPS: (1) we curated more than 100 AD multi-omics data sets capturing DNA, RNA, protein, and small molecule profiles underlying AD pathogenesis (e.g., early vs. late stage and tau or amyloid endophenotype); (2) we constructed endophenotype disease modules by incorporating multi-omics findings and human protein-protein interactome networks; (3) we provided possible treatment information from ~ 3000 FDA approved/investigational drugs for AD using state-of-the-art network proximity analyses; (4) we curated nearly 300 literature references for high-confidence drug candidates; (5) we included information from over 1000 AD clinical trials noting drug's mechanisms-of-action and primary drug targets, and linking them to our integrated multi-omics view for targets and network analysis results for the drugs; (6) we implemented a highly interactive web interface for database browsing and network visualization.

Conclusions: Network visualization enabled by AlzGPS includes brain-specific neighborhood networks for genes-of-interest, endophenotype disease module networks for omics-of-interest, and mechanism-of-action networks for drugs targeting disease modules. By virtue of combining systems pharmacology and network-based integrative analysis of multi-omics data, AlzGPS offers actionable systems biology tools for accelerating therapeutic development in AD.
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http://dx.doi.org/10.1186/s13195-020-00760-wDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7804907PMC
January 2021

A network-based deep learning methodology for stratification of tumor mutations.

Bioinformatics 2021 Jan 8. Epub 2021 Jan 8.

Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, 44106, USA.

Motivation: Tumor stratification has a wide range of biomedical and clinical applications, including diagnosis, prognosis and personalized treatment. However, cancer is always driven by the combination of mutated genes, which are highly heterogeneous across patients. Accurately subdividing the tumors into subtypes is challenging.

Results: We developed a network-embedding based stratification (NES) methodology to identify clinically relevant patient subtypes from large-scale patients' somatic mutation profiles. The central hypothesis of NES is that two tumors would be classified into the same subtypes if their somatic mutated genes located in the similar network regions of the human interactome. We encoded the genes on the human protein-protein interactome with a network embedding approach and constructed the patients' vectors by integrating the somatic mutation profiles of 7,344 tumor exomes across 15 cancer types. We firstly adopted the lightGBM classification algorithm to train the patients' vectors. The AUC value is around 0.89 in the prediction of the patient's cancer type and around 0.78 in the prediction of the tumor stage within a specific cancer type. The high classification accuracy suggests that network embedding-based patients' features are reliable for dividing the patients. We conclude that we can cluster patients with a specific cancer type into several subtypes by using an unsupervised clustering algorithm to learn the patients' vectors. Among the 15 cancer types, the new patient clusters (subtypes) identified by the NES are significantly correlated with patient survival across 12 cancer types. In summary, this study offers a powerful network-based deep learning methodology for personalized cancer medicine.

Availability And Implementation: Source code and data can be downloaded from https://github.com/ChengF-Lab/NES.

Supplementary Information: Supplementary data are available at Bioinformatics online.
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http://dx.doi.org/10.1093/bioinformatics/btaa1099DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8034530PMC
January 2021

A new precision medicine initiative at the dawn of exascale computing.

Signal Transduct Target Ther 2021 Jan 6;6(1). Epub 2021 Jan 6.

Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, 44106, USA.

Which signaling pathway and protein to select to mitigate the patient's expected drug resistance? The number of possibilities facing the physician is massive, and the drug combination should fit the patient status. Here, we briefly review current approaches and data and map an innovative patient-specific strategy to forecast drug resistance targets that centers on parallel (or redundant) proliferation pathways in specialized cells. It considers the availability of each protein in each pathway in the specific cell, its activating mutations, and the chromatin accessibility of its encoding gene. The construction of the resulting Proliferation Pathway Network Atlas will harness the emerging exascale computing and advanced artificial intelligence (AI) methods for therapeutic development. Merging the resulting set of targets, pathways, and proteins, with current strategies will augment the choice for the attending physicians to thwart resistance.
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http://dx.doi.org/10.1038/s41392-020-00420-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7785737PMC
January 2021

Reprogramming immunosuppressive myeloid cells facilitates immunotherapy for colorectal cancer.

EMBO Mol Med 2021 Jan 7;13(1):e12798. Epub 2020 Dec 7.

Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, China.

Immune checkpoint blockade (ICB) has a limited effect on colorectal cancer, underlining the requirement of co-targeting the complementary mechanisms. Here, we identified prostaglandin E2 (PGE ) receptor 4 (EP4) as the master regulator of immunosuppressive myeloid cells (IMCs), which are the major driver of resistance to ICB therapy. PGE -bound EP4 promotes the differentiation of immunosuppressive M2 macrophages and myeloid-derived suppressor cells (MDSCs) and reduces the expansion of immunostimulated M1 macrophages. To explore the immunotherapeutic role of EP4 signaling, we developed a novel and selective EP4 antagonist TP-16. TP-16 effectively blocked the function of IMCs and enhanced cytotoxic T-cell-mediated tumor elimination in vivo. Cell co-culture experiments revealed that TP-16 promoted T-cell proliferation, which was impaired by tumor-derived CD11b myeloid cells. Notably, TP-16 and anti-PD-1 combination therapy significantly impeded tumor progression and prolonged mice survival. We further demonstrated that TP-16 increased responsiveness to anti-PD-1 therapy in an IMC-related spontaneous colorectal cancer mouse model. In summary, this study demonstrates that inhibition of EP4-expressing IMCs may offer a potential strategy for enhancing the efficacy of immunotherapy for colorectal cancer.
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http://dx.doi.org/10.15252/emmm.202012798DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7799360PMC
January 2021

Impact of timing of atrial fibrillation, CHADS-VASc score and cancer therapeutics on mortality in oncology patients.

Open Heart 2020 11;7(2)

Department of Cardiovascular Medicine, Heart, Vascular and Thoracic Institute, Cleveland Clinic Foundation, Cleveland, Ohio, USA

Objectives: To investigate timing and age distribution of atrial fibrillation (AF) in selected oncology patients, and the impact of AF timing, CHADS-VASc score and cancer therapeutics on mortality.

Methods: This is a retrospective cohort study of oncology patients referred to the cardio-oncology service from 2011 to 2018 for echocardiographic cardiosurveillance and/or pre-existing cardiovascular risk factor/disease management. Rates of first AF diagnosis was assessed using a parametric multiphase hazard model (predictive modelling) and non-parametrically by Kaplan-Meier with transformations tested using a bootstrap methodology.

Results: Among 6754 patients identified, 174 patients had their first AF diagnosis cancer while 609 patients had their first diagnosis of AF cancer. Most first AF diagnosis occurred at/early after cancer diagnosis. Increasing AF prevalence at time of cancer diagnosis was seen across older age groups ranges. Diagnosis of cancer at an older age and exposure to cardiotoxic treatment (anthracyclines, HER2-neu inhibitors, tyrosine kinase inhibitors including ibrutinib and radiation) were associated with an increased risk of AF.Modelling of the hazard function of AF identified a high left-skewed peak within 3 years after cancer diagnosis ('early phase'), followed by a gradual late slight rise 3 years after cancer diagnosis ('late phase'). AF diagnosis was only associated with death in the early phase (p<0.001), while CHADS-VASc score was only associated with death in the late phase (p<0.001).

Conclusions: This study reports a nuanced/complex relationship between AF and cancer. First diagnosis of AF in patients with cancer was more common at/early after cancer diagnosis, especially in older patients and those exposed to cardiotoxic treatment. Pre-existing AF or a diagnosis of AF within 3 years after cancer diagnosis carried a negative prognosis. CHADS-VASc score did not relate to mortality in those that developed AF within 3 years of cancer diagnosis.
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http://dx.doi.org/10.1136/openhrt-2020-001412DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7692982PMC
November 2020

Machine Learning-Based Risk Assessment for Cancer Therapy-Related Cardiac Dysfunction in 4300 Longitudinal Oncology Patients.

J Am Heart Assoc 2020 12 26;9(23):e019628. Epub 2020 Nov 26.

Genomic Medicine Institute Lerner Research InstituteCleveland Clinic Cleveland OH.

Background The growing awareness of cardiovascular toxicity from cancer therapies has led to the emerging field of cardio-oncology, which centers on preventing, detecting, and treating patients with cardiac dysfunction before, during, or after cancer treatment. Early detection and prevention of cancer therapy-related cardiac dysfunction (CTRCD) play important roles in precision cardio-oncology. Methods and Results This retrospective study included 4309 cancer patients between 1997 and 2018 whose laboratory tests and cardiovascular echocardiographic variables were collected from the Cleveland Clinic institutional electronic medical record database (Epic Systems). Among these patients, 1560 (36%) were diagnosed with at least 1 type of CTRCD, and 838 (19%) developed CTRCD after cancer therapy (de novo). We posited that machine learning algorithms can be implemented to predict CTRCDs in cancer patients according to clinically relevant variables. Classification models were trained and evaluated for 6 types of cardiovascular outcomes, including coronary artery disease (area under the receiver operating characteristic curve [AUROC], 0.821; 95% CI, 0.815-0.826), atrial fibrillation (AUROC, 0.787; 95% CI, 0.782-0.792), heart failure (AUROC, 0.882; 95% CI, 0.878-0.887), stroke (AUROC, 0.660; 95% CI, 0.650-0.670), myocardial infarction (AUROC, 0.807; 95% CI, 0.799-0.816), and de novo CTRCD (AUROC, 0.802; 95% CI, 0.797-0.807). Model generalizability was further confirmed using time-split data. Model inspection revealed several clinically relevant variables significantly associated with CTRCDs, including age, hypertension, glucose levels, left ventricular ejection fraction, creatinine, and aspartate aminotransferase levels. Conclusions This study suggests that machine learning approaches offer powerful tools for cardiac risk stratification in oncology patients by utilizing large-scale, longitudinal patient data from healthcare systems.
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http://dx.doi.org/10.1161/JAHA.120.019628DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7763760PMC
December 2020

Pik3c3 deficiency in myeloid cells imparts partial resistance to experimental autoimmune encephalomyelitis associated with reduced IL-1β production.

Cell Mol Immunol 2021 Aug 24;18(8):2024-2039. Epub 2020 Nov 24.

Department of Pathology, Microbiology and Immunology, Vanderbilt University School of Medicine, Nashville, TN, 37232, USA.

The PIK3C3/VPS34 subunit of the class III phosphatidylinositol 3-kinase (PtdIns3K) complex plays a role in both canonical and noncanonical autophagy, key processes that control immune-cell responsiveness to a variety of stimuli. Our previous studies found that PIK3C3 is a critical regulator that controls the development, homeostasis, and function of dendritic and T cells. In this study, we investigated the role of PIK3C3 in myeloid cell biology using myeloid cell-specific Pik3c3-deficient mice. We found that Pik3c3-deficient macrophages express increased surface levels of major histocompatibility complex (MHC) class I and class II molecules. In addition, myeloid cell-specific Pik3c3 ablation in mice caused a partial impairment in the homeostatic maintenance of macrophages expressing the apoptotic cell uptake receptor TIM-4. Pik3c3 deficiency caused phenotypic changes in myeloid cells that were dependent on the early machinery (initiation/nucleation) of the classical autophagy pathway. Consequently, myeloid cell-specific Pik3c3-deficient animals showed significantly reduced severity of experimental autoimmune encephalomyelitis (EAE), a primarily CD4 T-cell-mediated mouse model of multiple sclerosis (MS). This disease protection was associated with reduced accumulation of myelin-specific CD4 T cells in the central nervous system and decreased myeloid cell IL-1β production. Further, administration of SAR405, a selective PIK3C3 inhibitor, delayed disease progression. Collectively, our studies establish PIK3C3 as an important regulator of macrophage functions and myeloid cell-mediated regulation of EAE. Our findings also have important implications for the development of small-molecule inhibitors of PIK3C3 as therapeutic modulators of MS and other autoimmune diseases.
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http://dx.doi.org/10.1038/s41423-020-00589-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8322046PMC
August 2021

A network medicine approach to investigation and population-based validation of disease manifestations and drug repurposing for COVID-19.

PLoS Biol 2020 11 6;18(11):e3000970. Epub 2020 Nov 6.

Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio, United States of America.

The global coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has led to unprecedented social and economic consequences. The risk of morbidity and mortality due to COVID-19 increases dramatically in the presence of coexisting medical conditions, while the underlying mechanisms remain unclear. Furthermore, there are no approved therapies for COVID-19. This study aims to identify SARS-CoV-2 pathogenesis, disease manifestations, and COVID-19 therapies using network medicine methodologies along with clinical and multi-omics observations. We incorporate SARS-CoV-2 virus-host protein-protein interactions, transcriptomics, and proteomics into the human interactome. Network proximity measurement revealed underlying pathogenesis for broad COVID-19-associated disease manifestations. Analyses of single-cell RNA sequencing data show that co-expression of ACE2 and TMPRSS2 is elevated in absorptive enterocytes from the inflamed ileal tissues of Crohn disease patients compared to uninflamed tissues, revealing shared pathobiology between COVID-19 and inflammatory bowel disease. Integrative analyses of metabolomics and transcriptomics (bulk and single-cell) data from asthma patients indicate that COVID-19 shares an intermediate inflammatory molecular profile with asthma (including IRAK3 and ADRB2). To prioritize potential treatments, we combined network-based prediction and a propensity score (PS) matching observational study of 26,779 individuals from a COVID-19 registry. We identified that melatonin usage (odds ratio [OR] = 0.72, 95% CI 0.56-0.91) is significantly associated with a 28% reduced likelihood of a positive laboratory test result for SARS-CoV-2 confirmed by reverse transcription-polymerase chain reaction assay. Using a PS matching user active comparator design, we determined that melatonin usage was associated with a reduced likelihood of SARS-CoV-2 positive test result compared to use of angiotensin II receptor blockers (OR = 0.70, 95% CI 0.54-0.92) or angiotensin-converting enzyme inhibitors (OR = 0.69, 95% CI 0.52-0.90). Importantly, melatonin usage (OR = 0.48, 95% CI 0.31-0.75) is associated with a 52% reduced likelihood of a positive laboratory test result for SARS-CoV-2 in African Americans after adjusting for age, sex, race, smoking history, and various disease comorbidities using PS matching. In summary, this study presents an integrative network medicine platform for predicting disease manifestations associated with COVID-19 and identifying melatonin for potential prevention and treatment of COVID-19.
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http://dx.doi.org/10.1371/journal.pbio.3000970DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7728249PMC
November 2020

Importance of scientific collaboration in contemporary drug discovery and development: a detailed network analysis.

BMC Biol 2020 10 13;18(1):138. Epub 2020 Oct 13.

Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, 75 Francis St., Boston, MA, 02115, USA.

Background: Growing evidence shows that scientific collaboration plays a crucial role in transformative innovation in the life sciences. For example, contemporary drug discovery and development reflects the work of teams of individuals from academic centers, the pharmaceutical industry, the regulatory science community, health care providers, and patients. However, public understanding of how collaborations between academia and industry catalyze novel target identification and first-in-class drug discovery is limited.

Results: We perform a comprehensive network analysis on a large scientific corpus of collaboration and citations (97,688 papers with 1,862,500 citations from 170 million scientific records) to quantify the success trajectory of innovative drug development. By focusing on four types of cardiovascular drugs, we demonstrate how knowledge flows between institutions to highlight the underlying contributions of many different institutions in the development of a new drug. We highlight how such network analysis could help to increase industrial and governmental support, and improve the efficiency or accelerate decision-making in drug discovery and development.

Conclusion: We demonstrate that network analysis of large public databases can identify and quantify investigator and institutional relationships in drug discovery and development. If broadly applied, this type of network analysis may help to enhance public understanding of and support for biomedical research, and could identify factors that facilitate decision-making in first-in-class drug discovery among academia, the pharmaceutical industry, and healthcare systems.
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http://dx.doi.org/10.1186/s12915-020-00868-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7556984PMC
October 2020

Temporal Trends of Cardiac Outcomes and Impact on Survival in Patients With Cancer.

Am J Cardiol 2020 12 28;137:118-124. Epub 2020 Sep 28.

Department of Cardiovascular Medicine, Heart and Vascular Institute, Cleveland Clinic, Cleveland, Ohio; Department of Molecular Medicine, Cleveland Clinic Lerner College of Medicine, Case Western Reserve University, Cleveland, Ohio. Electronic address:

To evaluate the temporal relations of cardiovascular disease in oncology patients referred to cardio-oncology and describe the impact of cardiovascular disease and cardiovascular risk factors on outcomes. All adult oncology patients referred to the cardio-oncology service at the Cleveland Clinic from January 2011 to June 2018 were included in the study. Comprehensive clinical information were collected. The impact on survival of temporal trends of cardiovascular disease in oncology patients were assessed with a Cox proportional hazards model and time-varying covariate adjustment for confounders. In total, 6,754 patients were included in the study (median age, 57 years; [interquartile range, 47 to 65 years]; 3,898 women [58%]; oncology history [60% - breast cancer, lymphoma, and leukemia]). Mortality and diagnosis of clinical cardiac disease peaked around the time of chemotherapy. 2,293 patients (34%) were diagnosed with a new cardiovascular risk factor after chemotherapy, over half of which were identified in the first year after cancer diagnosis. Patients with preexisting and post-chemotherapy cardiovascular disease had significantly worse outcomes than patients that did not develop any cardiovascular disease (p < 0.0001). The highest 1-year hazard ratios (HR) of post-chemotherapy cardiovascular disease were significantly associated with male (HR 1.81; 95% confidence interval 1.55 to 2.11; p < 0.001] and diabetes [HR 1.51; 95% confidence interval 1.26 to 1.81; p < 0.001]. In conclusion, patients referred to cardio-oncology, first diagnosis of cardiac events peaked around the time of chemotherapy. Those with preexisting or post-chemotherapy cardiovascular disease had worse survival. In addition to a high rate of cardiovascular risk factors at baseline, risk factor profile worsened over course of follow-up.
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http://dx.doi.org/10.1016/j.amjcard.2020.09.030DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7704696PMC
December 2020

Artificial intelligence in COVID-19 drug repurposing.

Lancet Digit Health 2020 12 18;2(12):e667-e676. Epub 2020 Sep 18.

Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA.

Drug repurposing or repositioning is a technique whereby existing drugs are used to treat emerging and challenging diseases, including COVID-19. Drug repurposing has become a promising approach because of the opportunity for reduced development timelines and overall costs. In the big data era, artificial intelligence (AI) and network medicine offer cutting-edge application of information science to defining disease, medicine, therapeutics, and identifying targets with the least error. In this Review, we introduce guidelines on how to use AI for accelerating drug repurposing or repositioning, for which AI approaches are not just formidable but are also necessary. We discuss how to use AI models in precision medicine, and as an example, how AI models can accelerate COVID-19 drug repurposing. Rapidly developing, powerful, and innovative AI and network medicine technologies can expedite therapeutic development. This Review provides a strong rationale for using AI-based assistive tools for drug repurposing medications for human disease, including during the COVID-19 pandemic.
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http://dx.doi.org/10.1016/S2589-7500(20)30192-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7500917PMC
December 2020

Repurposing of FDA-Approved Toremifene to Treat COVID-19 by Blocking the Spike Glycoprotein and NSP14 of SARS-CoV-2.

J Proteome Res 2020 11 27;19(11):4670-4677. Epub 2020 Sep 27.

Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio 44195, United States.

The global pandemic of Coronavirus Disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has led to the death of more than 675,000 worldwide and over 150,000 in the United States alone. However, there are currently no approved effective pharmacotherapies for COVID-19. Here, we combine homology modeling, molecular docking, molecular dynamics simulation, and binding affinity calculations to determine potential targets for toremifene, a selective estrogen receptor modulator which we have previously identified as a SARS-CoV-2 inhibitor. Our results indicate the possibility of inhibition of the spike glycoprotein by toremifene, responsible for aiding in fusion of the viral membrane with the cell membrane, via a perturbation to the fusion core. An interaction between the dimethylamine end of toremifene and residues Q954 and N955 in heptad repeat 1 (HR1) perturbs the structure, causing a shift from what is normally a long, helical region to short helices connected by unstructured regions. Additionally, we found a strong interaction between toremifene and the methyltransferase nonstructural protein (NSP) 14, which could be inhibitory to viral replication via its active site. These results suggest potential structural mechanisms for toremifene by blocking the spike protein and NSP14 of SARS-CoV-2, offering a drug candidate for COVID-19.
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http://dx.doi.org/10.1021/acs.jproteome.0c00397DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7640961PMC
November 2020

A Rational Design of a Multi-Epitope Vaccine Against SARS-CoV-2 Which Accounts for the Glycan Shield of the Spike Glycoprotein.

ChemRxiv 2020 Aug 7. Epub 2020 Aug 7.

Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA.

The ongoing global health crisis caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), the virus which leads to Coronavirus Disease 2019 (COVID-19) has impacted not only the health of people everywhere, but the economy in nations across the world. While vaccine candidates and therapeutics are currently undergoing clinical trials, there is yet to be a proven effective treatment or cure for COVID-19. In this study, we have presented a synergistic computational platform, including molecular dynamics simulations and immunoinformatics techniques, to rationally design a multi-epitope vaccine candidate for COVID-19. This platform combines epitopes across Linear B Lymphocytes (LBL), Cytotoxic T Lymphocytes (CTL) and Helper T Lymphocytes (HTL) derived from both mutant and wild-type spike glycoproteins from SARS-CoV-2 with diverse protein conformations. In addition, this vaccine construct also takes the considerable glycan shield of the spike glycoprotein into account, which protects it from immune response. We have identified a vaccine candidate (a 35.9 kDa protein), named COVCCF, which is composed of 5 LBL, 6 HTL, and 6 CTL epitopes from the spike glycoprotein of SARS-CoV-2. Using multi-dose immune simulations, COVCCF induces elevated levels of immunoglobulin activity (IgM, IgG1, IgG2), and induces strong responses from B lymphocytes, CD4 T-helper lymphocytes, and CD8 T-cytotoxic lymphocytes. COVCCF induces cytokines important to innate immunity, including IFN-γ, IL4, and IL10. Additionally, COVCCF has ideal pharmacokinetic properties and low immune-related toxicities. In summary, this study provides a powerful, computational vaccine design platform for rapid development of vaccine candidates (including COVCCF) for effective prevention of COVID-19.
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http://dx.doi.org/10.26434/chemrxiv.12770225DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7418723PMC
August 2020

SARS-CoV-2 and ACE2: The biology and clinical data settling the ARB and ACEI controversy.

EBioMedicine 2020 Aug 6;58:102907. Epub 2020 Aug 6.

Heart, Vascular and Thoracic Institute, United States; Cleveland Clinic Lerner College of Medicine, United States; Case Western Reserve University, United States.

Background: SARS-CoV-2 enters cells by binding of its spike protein to angiotensin-converting enzyme 2 (ACE2). Angiotensin-converting enzyme inhibitors (ACEIs) or angiotensin II receptor blockers (ARBs) have been reported to increase ACE2 expression in animal models, and worse outcomes are reported in patients with co-morbidities commonly treated with these agents, leading to controversy during the COVID-19 pandemic over whether these drugs might be helpful or harmful.

Methods: Animal, in vitro and clinical data relevant to the biology of the renin-angiotensin system (RAS), its interaction with the kallikrein-kinin system (KKS) and SARS-CoV-2, and clinical studies were reviewed.

Findings And Interpretation: SARS-CoV-2 hijacks ACE2to invade and damage cells, downregulating ACE2, reducing its protective effects and exacerbating injurious Ang II effects. However, retrospective observational studies do not show higher risk of infection with ACEI or ARB use. Nevertheless, study of the RAS and KKS in the setting of coronaviral infection may yield therapeutic targets.
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http://dx.doi.org/10.1016/j.ebiom.2020.102907DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7415847PMC
August 2020
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