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Article: Identification of PBMC-based molecular signature associational with COVID-19 disease severity.

Shaath, Hibah / Alajez, Nehad M

2021 Volume 7, Issue 5, Page(s) e06866

Abstract: The longevity of COVID-19 as a global pandemic, and the devastating effects it has had on certain subsets of individuals thus far has highlighted the importance of identifying blood-based biomarkers associated with disease severity. We employed ... ...

Abstract	The longevity of COVID-19 as a global pandemic, and the devastating effects it has had on certain subsets of individuals thus far has highlighted the importance of identifying blood-based biomarkers associated with disease severity. We employed computational and transcriptome analyses of publicly available datasets from PBMCs from 126 patients with COVID-19 admitted to ICU (n = 50), COVID-19 not admitted to ICU (n = 50), non-COVID-19 admitted to ICU (n = 16) and non-COVID-19 not admitted to ICU (n = 10), and utilized the Gencode V33 assembly to analyze protein coding mRNA and long noncoding RNA (lncRNA) transcriptomes in the context of disease severity. Our data identified several aberrantly expressed mRNA and lncRNA based biomarkers associated with SARS-CoV-2 severity, which in turn significantly affected canonical, upstream, and disease functions in each group of patients. Immune, interferon, and antiviral responses were severely suppressed in COVID-19 patients admitted to ICU versus those who were not admitted to ICU. Our data suggests a possible therapeutic approach for severe COVID-19 through administration of interferon therapy. Delving further into these biomarkers, roles and their implications on the onset and disease severity of COVID-19 could play a crucial role in patient stratification and identifying varied therapeutic options with diverse clinical implications.
Language	English
Publishing date	2021-04-20
Publishing country	England
Document type	Journal Article
ZDB-ID	2835763-2
ISSN	2405-8440
ISSN	2405-8440
DOI	10.1016/j.heliyon.2021.e06866
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Identification of PBMC-based molecular signature associational with COVID-19 disease severity

Hibah Shaath / Nehad M. Alajez

Heliyon, Vol 7, Iss 5, Pp e06866- (2021)

2021

Abstract	The longevity of COVID-19 as a global pandemic, and the devastating effects it has had on certain subsets of individuals thus far has highlighted the importance of identifying blood-based biomarkers associated with disease severity. We employed computational and transcriptome analyses of publicly available datasets from PBMCs from 126 patients with COVID-19 admitted to ICU (n = 50), COVID-19 not admitted to ICU (n = 50), non-COVID-19 admitted to ICU (n = 16) and non-COVID-19 not admitted to ICU (n = 10), and utilized the Gencode V33 assembly to analyze protein coding mRNA and long noncoding RNA (lncRNA) transcriptomes in the context of disease severity. Our data identified several aberrantly expressed mRNA and lncRNA based biomarkers associated with SARS-CoV-2 severity, which in turn significantly affected canonical, upstream, and disease functions in each group of patients. Immune, interferon, and antiviral responses were severely suppressed in COVID-19 patients admitted to ICU versus those who were not admitted to ICU. Our data suggests a possible therapeutic approach for severe COVID-19 through administration of interferon therapy. Delving further into these biomarkers, roles and their implications on the onset and disease severity of COVID-19 could play a crucial role in patient stratification and identifying varied therapeutic options with diverse clinical implications.
Keywords	COVID-19 ; Severity ; Biomarker ; Transcriptome ; PBMCs ; Science (General) ; Q1-390 ; Social sciences (General) ; H1-99
Subject code	610
Language	English
Publishing date	2021-05-01T00:00:00Z
Publisher	Elsevier
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: Identification of PBMC-based molecular signature associational with COVID-19 disease severity

Shaath, Hibah / Alajez, Nehad M

Heliyon. 2021 May, v. 7, no. 5

2021

Abstract	The longevity of COVID-19 as a global pandemic, and the devastating effects it has had on certain subsets of individuals thus far has highlighted the importance of identifying blood-based biomarkers associated with disease severity. We employed computational and transcriptome analyses of publicly available datasets from PBMCs from 126 patients with COVID-19 admitted to ICU (n = 50), COVID-19 not admitted to ICU (n = 50), non-COVID-19 admitted to ICU (n = 16) and non-COVID-19 not admitted to ICU (n = 10), and utilized the Gencode V33 assembly to analyze protein coding mRNA and long noncoding RNA (lncRNA) transcriptomes in the context of disease severity. Our data identified several aberrantly expressed mRNA and lncRNA based biomarkers associated with SARS-CoV-2 severity, which in turn significantly affected canonical, upstream, and disease functions in each group of patients. Immune, interferon, and antiviral responses were severely suppressed in COVID-19 patients admitted to ICU versus those who were not admitted to ICU. Our data suggests a possible therapeutic approach for severe COVID-19 through administration of interferon therapy. Delving further into these biomarkers, roles and their implications on the onset and disease severity of COVID-19 could play a crucial role in patient stratification and identifying varied therapeutic options with diverse clinical implications.
Keywords	COVID-19 infection ; Severe acute respiratory syndrome coronavirus 2 ; biomarkers ; data collection ; disease severity ; interferons ; longevity ; non-coding RNA ; pandemic ; patients ; therapeutics ; transcriptome
Language	English
Dates of publication	2021-05
Publishing place	Elsevier Ltd
Document type	Article
Note	NAL-AP-2-clean
ZDB-ID	2835763-2
ISSN	2405-8440
ISSN	2405-8440
DOI	10.1016/j.heliyon.2021.e06866
Database	NAL-Catalogue (AGRICOLA)

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Article: Computational and Transcriptome Analyses Revealed Preferential Induction of Chemotaxis and Lipid Synthesis by SARS-CoV-2.

Shaath, Hibah / Alajez, Nehad M

Biology

2020 Volume 9, Issue 9

Abstract: The continuous and rapid emergence of new viral strains calls for a better understanding of the fundamental changes occurring within the host cell upon viral infection. In this study, we analyzed RNA-seq transcriptome data from Calu-3 human lung ... ...

Abstract	The continuous and rapid emergence of new viral strains calls for a better understanding of the fundamental changes occurring within the host cell upon viral infection. In this study, we analyzed RNA-seq transcriptome data from Calu-3 human lung epithelial cells infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) compared to five other viruses namely, severe acute respiratory syndrome coronavirus (SARS-CoV), Middle East Respiratory Syndrome (SARS-MERS), influenzavirus A (FLUA), influenzavirus B (FLUB), and rhinovirus (RHINO) compared to mock-infected cells and characterized their coding and noncoding RNA transcriptional portraits. The induction of interferon, inflammatory, and immune response was a hallmark of SARS-CoV-2 infection. Comprehensive bioinformatics revealed the activation of immune response and defense response to the virus as a common feature of viral infection. Interestingly however, the degree of functional categories and signaling pathways activation varied among different viruses. Ingenuity pathways analysis highlighted altered conical and casual pathways related to TNF, IL1A, and TLR7, which are seen more predominantly during SARS-CoV-2 infection. Nonetheless, the activation of chemotaxis and lipid synthesis was prominent in SARS-CoV-2-infected cells. Despite the commonality among all viruses, our data revealed the hyperactivation of chemotaxis and immune cell trafficking as well as the enhanced fatty acid synthesis as plausible mechanisms that could explain the inflammatory cytokine storms associated with severe cases of COVID-19 and the rapid spread of the virus, respectively.
Keywords	covid19
Language	English
Publishing date	2020-09-01
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2661517-4
ISSN	2079-7737
ISSN	2079-7737
DOI	10.3390/biology9090260
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Article ; Online: Computational and Transcriptome Analyses Revealed Preferential Induction of Chemotaxis and Lipid Synthesis by SARS-CoV-2

Hibah Shaath / Nehad M. Alajez

Biology, Vol 9, Iss 260, p

2020 Volume 260

Abstract	The continuous and rapid emergence of new viral strains calls for a better understanding of the fundamental changes occurring within the host cell upon viral infection. In this study, we analyzed RNA-seq transcriptome data from Calu-3 human lung epithelial cells infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) compared to five other viruses namely, severe acute respiratory syndrome coronavirus (SARS-CoV), Middle East Respiratory Syndrome (SARS-MERS), influenzavirus A (FLUA), influenzavirus B (FLUB), and rhinovirus (RHINO) compared to mock-infected cells and characterized their coding and noncoding RNA transcriptional portraits. The induction of interferon, inflammatory, and immune response was a hallmark of SARS-CoV-2 infection. Comprehensive bioinformatics revealed the activation of immune response and defense response to the virus as a common feature of viral infection. Interestingly however, the degree of functional categories and signaling pathways activation varied among different viruses. Ingenuity pathways analysis highlighted altered conical and casual pathways related to TNF, IL1A, and TLR7, which are seen more predominantly during SARS-CoV-2 infection. Nonetheless, the activation of chemotaxis and lipid synthesis was prominent in SARS-CoV-2-infected cells. Despite the commonality among all viruses, our data revealed the hyperactivation of chemotaxis and immune cell trafficking as well as the enhanced fatty acid synthesis as plausible mechanisms that could explain the inflammatory cytokine storms associated with severe cases of COVID-19 and the rapid spread of the virus, respectively.
Keywords	COVID-19 ; SARS-CoV-2 ; SARS-CoV ; SARS-MERS ; influenza A ; influenza B ; Biology (General) ; QH301-705.5 ; covid19
Subject code	570 ; 572
Language	English
Publishing date	2020-09-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: Molecular Classification of Breast Cancer Utilizing Long Non-Coding RNA (lncRNA) Transcriptomes Identifies Novel Diagnostic lncRNA Panel for Triple-Negative Breast Cancer.

Shaath, Hibah / Elango, Ramesh / Alajez, Nehad M

Cancers

2021 Volume 13, Issue 21

Abstract: Breast cancer remains the world's most prevalent cancer, responsible for around 685,000 deaths globally despite international research efforts and advances in clinical management. While estrogen receptor positive (ER+), progesterone receptor positive (PR+ ...

Abstract	Breast cancer remains the world's most prevalent cancer, responsible for around 685,000 deaths globally despite international research efforts and advances in clinical management. While estrogen receptor positive (ER+), progesterone receptor positive (PR+), and human epidermal growth factor receptor positive (HER2+) subtypes are easily classified and can be targeted, there remains no direct diagnostic test for triple-negative breast cancer (TNBC), except for the lack of receptors expression. The identification of long non-coding RNAs (lncRNAs) and the roles they play in cancer progression has recently proven to be beneficial. In the current study, we utilize RNA sequencing data to identify lncRNA-based biomarkers associated with TNBC, ER+ subtypes, and normal breast tissue. The Marker Finder algorithm identified the lncRNA transcript panel most associated with each molecular subtype and the receiver operating characteristic (ROC) analysis was used to validate the diagnostic potential (area under the curve (AUC) of ≥8.0 and
Language	English
Publishing date	2021-10-26
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2527080-1
ISSN	2072-6694
ISSN	2072-6694
DOI	10.3390/cancers13215350
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Article: Computational and Transcriptome Analyses Revealed Preferential Induction of Chemotaxis and Lipid Synthesis by SARS-CoV-2

Shaath, Hibah / Alajez, Nehad M

Biology. 2020 Sept. 01, v. 9, no. 9

2020

Abstract	The continuous and rapid emergence of new viral strains calls for a better understanding of the fundamental changes occurring within the host cell upon viral infection. In this study, we analyzed RNA-seq transcriptome data from Calu-3 human lung epithelial cells infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) compared to five other viruses namely, severe acute respiratory syndrome coronavirus (SARS-CoV), Middle East Respiratory Syndrome (SARS-MERS), influenzavirus A (FLUA), influenzavirus B (FLUB), and rhinovirus (RHINO) compared to mock-infected cells and characterized their coding and noncoding RNA transcriptional portraits. The induction of interferon, inflammatory, and immune response was a hallmark of SARS-CoV-2 infection. Comprehensive bioinformatics revealed the activation of immune response and defense response to the virus as a common feature of viral infection. Interestingly however, the degree of functional categories and signaling pathways activation varied among different viruses. Ingenuity pathways analysis highlighted altered conical and casual pathways related to TNF, IL1A, and TLR7, which are seen more predominantly during SARS-CoV-2 infection. Nonetheless, the activation of chemotaxis and lipid synthesis was prominent in SARS-CoV-2-infected cells. Despite the commonality among all viruses, our data revealed the hyperactivation of chemotaxis and immune cell trafficking as well as the enhanced fatty acid synthesis as plausible mechanisms that could explain the inflammatory cytokine storms associated with severe cases of COVID-19 and the rapid spread of the virus, respectively.
Keywords	Alphainfluenzavirus ; Betainfluenzavirus ; Coronavirus infections ; Enterovirus ; Severe acute respiratory syndrome coronavirus ; bioinformatics ; chemotaxis ; cytokines ; epithelial cells ; fatty acids ; humans ; immune response ; infection ; interferons ; lungs ; non-coding RNA ; sequence analysis ; signal transduction ; strains ; synthesis ; transcription (genetics) ; transcriptome ; viruses
Language	English
Dates of publication	2020-0901
Publishing place	Multidisciplinary Digital Publishing Institute
Document type	Article
Note	NAL-light
ZDB-ID	2661517-4
ISSN	2079-7737
ISSN	2079-7737
DOI	10.3390/biology9090260
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: Therapeutic targeting of the TPX2/TTK network in colorectal cancer.

Shaath, Hibah / Vishnubalaji, Radhakrishnan / Elango, Ramesh / Velayutham, Dinesh / Jithesh, Puthen Veettil / Alajez, Nehad M

Cell communication and signaling : CCS

2023 Volume 21, Issue 1, Page(s) 265

Abstract: Background: While the increased screening, changes in lifestyle, and recent advances in treatment regimen have decreased colorectal cancer (CRC) mortality, metastatic disease and recurrence remains a major clinical challenge. In the era of precision ... ...

Abstract	Background: While the increased screening, changes in lifestyle, and recent advances in treatment regimen have decreased colorectal cancer (CRC) mortality, metastatic disease and recurrence remains a major clinical challenge. In the era of precision medicine, the identification of actionable novel therapeutic targets could ultimately offer an alternative treatment strategy for CRC. Methods: RNA-Seq was conducted using the illumina platform, while bioinformatics analyses were conducted using CLC genomics workbench and iDEP.951. Colony forming unit, flow cytometry, and fluorescent microscopy were used to assess cell proliferation, cell cycle distribution, and cell death, respectively. The growth potential of CRC cells under 3-dimensional (3D) conditions was assessed using Matrigel. STRING database (v11.5) and Ingenuity Pathway Analysis (IPA) tool were used for network and pathway analyses. CRISPR-Cas9 perturbational effects database was used to identify potential therapeutic targets for CRC, through integration with gene-drug interaction database. Structural modeling and molecular docking were used to assess the interaction between candidate drugs and their targets. Results: In the current study, we investigated the therapeutic potential of targeting TPX2, TTK, DDX39A, and LRP8, commonly upregulated genes in CRC identified through differential expression analysis in CRC and adjacent non-cancerous tissue. Targeted depletion of TPX2 and TTK impaired CRC proliferation, cell cycle progression, and organoid formation under 3D culture conditions, while suppression of DDX39A and LRP8 had modest effects on CRC colony formation. Differential expression analysis and bioinformatics on TPX2 and TTK-deficient cells identified cell cycle regulation as the hallmark associated with loss of TPX2 and TTK. Elevated expression of TPX2 and TTK correlated with an oncogenic state in tumor tissue from patients with colon adenocarcinoma, thus corroborating an oncogenic role for the TPX2/TTK network in the pathogenesis of CRC. Gene set enrichment and pathway analysis of TPX2 Conclusions: Our data has implicated an essential role for TPX2 and TTK in CRC pathogenesis and identified numerous potential therapeutic targets and their drug interactions, suggesting their potential clinical use as a novel therapeutic strategy for patients with CRC. Video Abstract.
MeSH term(s)	Humans ; Colonic Neoplasms/genetics ; Colorectal Neoplasms/drug therapy ; Colorectal Neoplasms/genetics ; Colorectal Neoplasms/metabolism ; Adenocarcinoma/pathology ; Molecular Docking Simulation ; Cell Proliferation ; Gene Expression Regulation, Neoplastic ; Microtubule-Associated Proteins/genetics ; Microtubule-Associated Proteins/metabolism ; Cell Cycle Proteins/genetics ; Cell Cycle Proteins/metabolism ; Protein-Tyrosine Kinases/metabolism ; Protein Serine-Threonine Kinases/metabolism
Chemical Substances	TPX2 protein, human ; Microtubule-Associated Proteins ; Cell Cycle Proteins ; TTK protein, human (EC 2.7.12.1) ; Protein-Tyrosine Kinases (EC 2.7.10.1) ; Protein Serine-Threonine Kinases (EC 2.7.11.1)
Language	English
Publishing date	2023-09-28
Publishing country	England
Document type	Video-Audio Media ; Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2126315-2
ISSN	1478-811X ; 1478-811X
ISSN (online)	1478-811X
ISSN	1478-811X
DOI	10.1186/s12964-023-01290-2
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Article ; Online: Therapeutic targeting of the TPX2/TTK network in colorectal cancer

Hibah Shaath / Radhakrishnan Vishnubalaji / Ramesh Elango / Dinesh Velayutham / Puthen Veettil Jithesh / Nehad M. Alajez

Cell Communication and Signaling, Vol 21, Iss 1, Pp 1-

2023 Volume 17

Abstract: Abstract Background While the increased screening, changes in lifestyle, and recent advances in treatment regimen have decreased colorectal cancer (CRC) mortality, metastatic disease and recurrence remains a major clinical challenge. In the era of ... ...

Abstract	Abstract Background While the increased screening, changes in lifestyle, and recent advances in treatment regimen have decreased colorectal cancer (CRC) mortality, metastatic disease and recurrence remains a major clinical challenge. In the era of precision medicine, the identification of actionable novel therapeutic targets could ultimately offer an alternative treatment strategy for CRC. Methods RNA-Seq was conducted using the illumina platform, while bioinformatics analyses were conducted using CLC genomics workbench and iDEP.951. Colony forming unit, flow cytometry, and fluorescent microscopy were used to assess cell proliferation, cell cycle distribution, and cell death, respectively. The growth potential of CRC cells under 3-dimensional (3D) conditions was assessed using Matrigel. STRING database (v11.5) and Ingenuity Pathway Analysis (IPA) tool were used for network and pathway analyses. CRISPR-Cas9 perturbational effects database was used to identify potential therapeutic targets for CRC, through integration with gene-drug interaction database. Structural modeling and molecular docking were used to assess the interaction between candidate drugs and their targets. Results In the current study, we investigated the therapeutic potential of targeting TPX2, TTK, DDX39A, and LRP8, commonly upregulated genes in CRC identified through differential expression analysis in CRC and adjacent non-cancerous tissue. Targeted depletion of TPX2 and TTK impaired CRC proliferation, cell cycle progression, and organoid formation under 3D culture conditions, while suppression of DDX39A and LRP8 had modest effects on CRC colony formation. Differential expression analysis and bioinformatics on TPX2 and TTK-deficient cells identified cell cycle regulation as the hallmark associated with loss of TPX2 and TTK. Elevated expression of TPX2 and TTK correlated with an oncogenic state in tumor tissue from patients with colon adenocarcinoma, thus corroborating an oncogenic role for the TPX2/TTK network in the pathogenesis of CRC. Gene ...
Keywords	Colorectal cancer ; Precision medicine ; TPX2 ; TTK ; DDX39A ; LRP8 ; Medicine ; R ; Cytology ; QH573-671
Subject code	610
Language	English
Publishing date	2023-09-01T00:00:00Z
Publisher	BMC
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: Molecular subtyping and functional validation of TTK, TPX2, UBE2C, and LRP8 in sensitivity of TNBC to paclitaxel.

Elango, Ramesh / Vishnubalaji, Radhakrishnan / Shaath, Hibah / Alajez, Nehad M

Molecular therapy. Methods & clinical development

2021 Volume 20, Page(s) 601–614

Abstract: Triple-negative breast cancer (TNBC) patients exhibit variable responses to chemotherapy, suggesting an underlying molecular heterogeneity. In the current study, we analyzed publicly available transcriptome data from 360 TNBC and 88 normal breast tissues, ...

Abstract	Triple-negative breast cancer (TNBC) patients exhibit variable responses to chemotherapy, suggesting an underlying molecular heterogeneity. In the current study, we analyzed publicly available transcriptome data from 360 TNBC and 88 normal breast tissues, which revealed activation of nucleosome and cell cycle as the hallmarks of TNBC. Mechanistic network analysis identified activation of FOXM1 and ERBB2, and suppression of TP53 and NURP1 networks in TNBC. Employing Iterative Clustering and Guide-gene Selection (ICGS), Uniform Manifold Approximation and Projection (UMAP), and dimensionality reduction analyses, we classified TNBC into seven molecular subtypes, each exhibiting a unique molecular signature, including immune infiltration (CD19, CD8, and macrophages) and mesenchymal signature, which correlated with variable disease outcomes in a larger cohort (1,070) of BC. Mechanistically, depletion of
Language	English
Publishing date	2021-01-26
Publishing country	United States
Document type	Journal Article
ZDB-ID	2872938-9
ISSN	2329-0501 ; 2329-0501
ISSN (online)	2329-0501
ISSN	2329-0501
DOI	10.1016/j.omtm.2021.01.013
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