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  1. Article ; Online: COVID-19: complexity of disease severity revealed by systemic and localized single cell immune atlas.

    Alajez, Nehad M

    Signal transduction and targeted therapy

    2021  Volume 6, Issue 1, Page(s) 156

    MeSH term(s) COVID-19 ; Humans ; SARS-CoV-2 ; Severity of Illness Index ; Single-Cell Analysis ; Transcriptome
    Language English
    Publishing date 2021-04-16
    Publishing country England
    Document type Journal Article ; Research Support, Non-U.S. Gov't ; Comment
    ZDB-ID 2886872-9
    ISSN 2059-3635 ; 2095-9907
    ISSN (online) 2059-3635
    ISSN 2095-9907
    DOI 10.1038/s41392-021-00587-3
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article: Long non-coding RNA AC099850.4 correlates with advanced disease state and predicts worse prognosis in triple-negative breast cancer.

    Vishnubalaji, Radhakrishnan / Alajez, Nehad M

    Frontiers in medicine

    2023  Volume 10, Page(s) 1149860

    Abstract: Our understanding of the function of long non-coding RNAs (lncRNAs) in health and disease states has evolved over the past decades due to the many advances in genome research. In the current study, we characterized the lncRNA transcriptome enriched in ... ...

    Abstract Our understanding of the function of long non-coding RNAs (lncRNAs) in health and disease states has evolved over the past decades due to the many advances in genome research. In the current study, we characterized the lncRNA transcriptome enriched in triple-negative breast cancer (TNBC,
    Language English
    Publishing date 2023-08-31
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2775999-4
    ISSN 2296-858X
    ISSN 2296-858X
    DOI 10.3389/fmed.2023.1149860
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  3. Article ; Online: Single-Cell Transcriptome Analysis Revealed Heterogeneity and Identified Novel Therapeutic Targets for Breast Cancer Subtypes.

    Vishnubalaji, Radhakrishnan / Alajez, Nehad M

    Cells

    2023  Volume 12, Issue 8

    Abstract: Breast cancer (BC) is a heterogeneous disease, which is primarily classified according to hormone receptors and HER2 expression. Despite the many advances in BC diagnosis and management, the identification of novel actionable therapeutic targets ... ...

    Abstract Breast cancer (BC) is a heterogeneous disease, which is primarily classified according to hormone receptors and HER2 expression. Despite the many advances in BC diagnosis and management, the identification of novel actionable therapeutic targets expressed by cancerous cells has always been a daunting task due to the large heterogeneity of the disease and the presence of non-cancerous cells (i.e., immune cells and stromal cells) within the tumor microenvironment. In the current study, we employed computational algorithms to decipher the cellular composition of estrogen receptor-positive (ER
    MeSH term(s) Humans ; Triple Negative Breast Neoplasms/pathology ; Single-Cell Gene Expression Analysis ; Neoplasm Recurrence, Local ; Gene Expression Profiling ; Transcriptome/genetics ; Tumor Microenvironment/genetics ; Chaperonin Containing TCP-1/genetics
    Chemical Substances CCT6A protein, human ; Chaperonin Containing TCP-1 (EC 3.6.1.-)
    Language English
    Publishing date 2023-04-18
    Publishing country Switzerland
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2661518-6
    ISSN 2073-4409 ; 2073-4409
    ISSN (online) 2073-4409
    ISSN 2073-4409
    DOI 10.3390/cells12081182
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  4. Article ; Online: COVID-19

    Nehad M. Alajez

    Signal Transduction and Targeted Therapy, Vol 6, Iss 1, Pp 1-

    complexity of disease severity revealed by systemic and localized single cell immune atlas

    2021  Volume 2

    Keywords Medicine ; R ; Biology (General) ; QH301-705.5
    Language English
    Publishing date 2021-04-01T00:00:00Z
    Publisher Nature Publishing Group
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  5. Article ; Online: Unified mRNA Subcellular Localization Predictor based on machine learning techniques.

    Musleh, Saleh / Arif, Muhammad / Alajez, Nehad M / Alam, Tanvir

    BMC genomics

    2024  Volume 25, Issue 1, Page(s) 151

    Abstract: Background: The mRNA subcellular localization bears substantial impact in the regulation of gene expression, cellular migration, and adaptation. However, the methods employed for experimental determination of this localization are arduous, time- ... ...

    Abstract Background: The mRNA subcellular localization bears substantial impact in the regulation of gene expression, cellular migration, and adaptation. However, the methods employed for experimental determination of this localization are arduous, time-intensive, and come with a high cost.
    Methods: In this research article, we tackle the essential challenge of predicting the subcellular location of messenger RNAs (mRNAs) through Unified mRNA Subcellular Localization Predictor (UMSLP), a machine learning (ML) based approach. We embrace an in silico strategy that incorporate four distinct feature sets: kmer, pseudo k-tuple nucleotide composition, nucleotide physicochemical attributes, and the 3D sequence depiction achieved via Z-curve transformation for predicting subcellular localization in benchmark dataset across five distinct subcellular locales, encompassing nucleus, cytoplasm, extracellular region (ExR), mitochondria, and endoplasmic reticulum (ER).
    Results: The proposed ML model UMSLP attains cutting-edge outcomes in predicting mRNA subcellular localization. On independent testing dataset, UMSLP ahcieved over 87% precision, 94% specificity, and 94% accuracy. Compared to other existing tools, UMSLP outperformed mRNALocator, mRNALoc, and SubLocEP by 11%, 21%, and 32%, respectively on average prediction accuracy for all five locales. SHapley Additive exPlanations analysis highlights the dominance of k-mer features in predicting cytoplasm, nucleus, ER, and ExR localizations, while Z-curve based features play pivotal roles in mitochondria subcellular localization detection.
    Availability: We have shared datasets, code, Docker API for users in GitHub at: https://github.com/smusleh/UMSLP .
    MeSH term(s) RNA, Messenger/genetics ; Mitochondria/genetics ; Endoplasmic Reticulum ; Computational Biology/methods ; Machine Learning ; Nucleotides
    Chemical Substances RNA, Messenger ; Nucleotides
    Language English
    Publishing date 2024-02-07
    Publishing country England
    Document type Journal Article
    ZDB-ID 2041499-7
    ISSN 1471-2164 ; 1471-2164
    ISSN (online) 1471-2164
    ISSN 1471-2164
    DOI 10.1186/s12864-024-10077-9
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  6. Article ; Online: Genome-wide differential expression profiling of long non-coding RNAs in FOXA2 knockout iPSC-derived pancreatic cells.

    Elsayed, Ahmed K / Alajez, Nehad M / Abdelalim, Essam M

    Cell communication and signaling : CCS

    2023  Volume 21, Issue 1, Page(s) 229

    Abstract: Background: Our recent studies have demonstrated the crucial involvement of FOXA2 in the development of human pancreas. Reduction of FOXA2 expression during the differentiation of induced pluripotent stem cells (iPSCs) into pancreatic islets has been ... ...

    Abstract Background: Our recent studies have demonstrated the crucial involvement of FOXA2 in the development of human pancreas. Reduction of FOXA2 expression during the differentiation of induced pluripotent stem cells (iPSCs) into pancreatic islets has been found to reduce α-and β-cell masses. However, the extent to which such changes are linked to alterations in the expression profile of long non-coding RNAs (lncRNAs) remains unraveled.
    Methods: Here, we employed our recently established FOXA2-deficient iPSCs (FOXA2
    Results: Our results showed that 442 lncRNAs were downregulated, and 114 lncRNAs were upregulated in PPs lacking FOXA2 compared to controls. Similarly, 177 lncRNAs were downregulated, and 59 lncRNAs were upregulated in islet cells lacking FOXA2 compared to controls. At both stages, we observed a strong correlation between lncRNAs and several crucial pancreatic genes and TFs during pancreatic differentiation. Correlation analysis revealed 12 DE-lncRNAs that strongly correlated with key downregulated pancreatic genes in both PPs and islet cell stages. Selected DE-lncRNAs were validated using RT-qPCR.
    Conclusions: Our data indicate that the observed defects in pancreatic islet development due to the FOXA2 loss is associated with significant alterations in the expression profile of lncRNAs. Therefore, our findings provide novel insights into the role of lncRNA and mRNA networks in regulating pancreatic islet development, which warrants further investigations. Video Abstract.
    MeSH term(s) Humans ; RNA, Long Noncoding ; Induced Pluripotent Stem Cells ; Pancreas ; Cell Differentiation ; Insulin-Secreting Cells ; RNA, Messenger ; Hepatocyte Nuclear Factor 3-beta
    Chemical Substances RNA, Long Noncoding ; RNA, Messenger ; FOXA2 protein, human ; Hepatocyte Nuclear Factor 3-beta (135845-92-0)
    Language English
    Publishing date 2023-09-05
    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/s12964-023-01212-2
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  7. Article ; Online: Correction: MSLP: mRNA subcellular localization predictor based on machine learning techniques.

    Musleh, Saleh / Islam, Mohammad Tariqul / Qureshi, Rizwan / Alajez, Nehad M / Alam, Tanvir

    BMC bioinformatics

    2023  Volume 24, Issue 1, Page(s) 156

    Language English
    Publishing date 2023-04-18
    Publishing country England
    Document type Published Erratum
    ZDB-ID 2041484-5
    ISSN 1471-2105 ; 1471-2105
    ISSN (online) 1471-2105
    ISSN 1471-2105
    DOI 10.1186/s12859-023-05276-2
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  8. Article: Transcriptional landscape associated with TNBC resistance to neoadjuvant chemotherapy revealed by single-cell RNA-seq.

    Vishnubalaji, Radhakrishnan / Alajez, Nehad M

    Molecular therapy oncolytics

    2021  Volume 23, Page(s) 151–162

    Abstract: Triple-negative breast cancer (TNBC) resistance to neoadjuvant chemotherapy (NAC) represents a major clinical challenge; therefore, delineating tumor heterogeneity can provide novel insight into resistance mechanisms and potential therapeutic targets. ... ...

    Abstract Triple-negative breast cancer (TNBC) resistance to neoadjuvant chemotherapy (NAC) represents a major clinical challenge; therefore, delineating tumor heterogeneity can provide novel insight into resistance mechanisms and potential therapeutic targets. Herein, we identified the transcriptional landscape associated with TNBC resistance to NAC at the single-cell level by analyzing publicly available transcriptome data from more than 5,000 single cells derived from four extinction (responders) and four persistence (non-responders) patients, revealing remarkable tumor heterogeneity. Employing iterative clustering and guide-gene selection (ICGS) and uniform manifold approximation and projection (UMAP), we classified TNBC single cells into several clusters based on their distinct gene signatures. The presence of clusters indicative of immune cell activation was a hallmark of the extinction group pre-NAC, while post NAC, the extinction tissue consisted mostly of breast, omental fat, and fibroblasts. The persistent gene signatures of pre-NAC resembled the gene signature of lung epithelial, mammary, and salivary glands and acute myeloid leukemia blast cells, which were associated with enhanced cellular movement and activation of FOXM1, NOTCH1, and MYC and suppression of tumor necrosis factor (TNF) and IFNG mechanistic networks. Multivariate survival analysis identified persistence-derived three-gene signature (KIF5B
    Language English
    Publishing date 2021-09-14
    Publishing country United States
    Document type Journal Article
    ISSN 2372-7705
    ISSN 2372-7705
    DOI 10.1016/j.omto.2021.09.002
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  9. Article: Identification of PBMC-based molecular signature associational with COVID-19 disease severity.

    Shaath, Hibah / Alajez, Nehad M

    Heliyon

    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
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  10. Article ; Online: iPSC-Derived Pancreatic Progenitors Lacking FOXA2 Reveal Alterations in miRNA Expression Targeting Key Pancreatic Genes.

    Aldous, Noura / Elsayed, Ahmed K / Alajez, Nehad M / Abdelalim, Essam M

    Stem cell reviews and reports

    2023  Volume 19, Issue 4, Page(s) 1082–1097

    Abstract: Recently, we reported that forkhead box A2 (FOXA2) is required for the development of human pancreatic α- and β-cells. However, whether miRNAs play a role in regulating pancreatic genes during pancreatic development in the absence of FOXA2 expression is ... ...

    Abstract Recently, we reported that forkhead box A2 (FOXA2) is required for the development of human pancreatic α- and β-cells. However, whether miRNAs play a role in regulating pancreatic genes during pancreatic development in the absence of FOXA2 expression is largely unknown. Here, we aimed to capture the dysregulated miRNAs and to identify their pancreatic-specific gene targets in pancreatic progenitors (PPs) derived from wild-type induced pluripotent stem cells (WT-iPSCs) and from iPSCs lacking FOXA2 (FOXA2
    MeSH term(s) Induced Pluripotent Stem Cells/cytology ; Induced Pluripotent Stem Cells/metabolism ; Hepatocyte Nuclear Factor 3-beta/genetics ; Hepatocyte Nuclear Factor 3-beta/physiology ; MicroRNAs/genetics ; Humans ; Islets of Langerhans/cytology ; Islets of Langerhans/growth & development ; Islets of Langerhans/metabolism ; Cell Differentiation/genetics ; Cell Line ; Gene Expression Regulation, Developmental
    Chemical Substances FOXA2 protein, human ; Hepatocyte Nuclear Factor 3-beta (135845-92-0) ; MicroRNAs
    Language English
    Publishing date 2023-02-07
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2495577-2
    ISSN 2629-3277 ; 1558-6804 ; 1550-8943
    ISSN (online) 2629-3277 ; 1558-6804
    ISSN 1550-8943
    DOI 10.1007/s12015-023-10515-3
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