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  1. Article ; Online: Profiling Kinase Activities for Precision Oncology in Diffuse Gastric Cancer.

    Singh, Smrita / Parthasarathi, K T Shreya / Bhat, Mohd Younis / Gopal, Champaka / Sharma, Jyoti / Pandey, Akhilesh

    Omics : a journal of integrative biology

    2024  Volume 28, Issue 2, Page(s) 76–89

    Abstract: Gastric cancer (GC) remains a leading cause of cancer-related mortality globally. This is due to the fact that majority of the cases of GC are diagnosed at an advanced stage when the treatment options are limited and prognosis is poor. The diffuse ... ...

    Abstract Gastric cancer (GC) remains a leading cause of cancer-related mortality globally. This is due to the fact that majority of the cases of GC are diagnosed at an advanced stage when the treatment options are limited and prognosis is poor. The diffuse subtype of gastric cancer (DGC) under Lauren's classification is more aggressive and usually occurs in younger patients than the intestinal subtype. The concept of personalized medicine is leading to the identification of multiple biomarkers in a large variety of cancers using different combinations of omics technologies. Proteomic changes including post-translational modifications are crucial in oncogenesis. We analyzed the phosphoproteome of DGC by using paired fresh frozen tumor and adjacent normal tissue from five patients diagnosed with DGC. We found proteins involved in the epithelial-to-mesenchymal transition (EMT), c-MYC pathway, and semaphorin pathways to be differentially phosphorylated in DGC tissues. We identified three kinases, namely, bromodomain adjacent to the zinc finger domain 1B (
    MeSH term(s) Humans ; Stomach Neoplasms/genetics ; Precision Medicine ; Proteomics ; Phosphorylation ; Carcinogenesis ; Bromodomain Containing Proteins ; Transcription Factors/metabolism
    Chemical Substances BAZ1B protein, human ; Bromodomain Containing Proteins ; Transcription Factors
    Language English
    Publishing date 2024-01-25
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2030312-9
    ISSN 1557-8100 ; 1536-2310
    ISSN (online) 1557-8100
    ISSN 1536-2310
    DOI 10.1089/omi.2023.0173
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article: Deciphering the Interactions of SARS-CoV-2 Proteins with Human Ion Channels Using Machine-Learning-Based Methods.

    Munjal, Nupur S / Sapra, Dikscha / Parthasarathi, K T Shreya / Goyal, Abhishek / Pandey, Akhilesh / Banerjee, Manidipa / Sharma, Jyoti

    Pathogens (Basel, Switzerland)

    2022  Volume 11, Issue 2

    Abstract: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is accountable for the protracted COVID-19 pandemic. Its high transmission rate and pathogenicity led to health emergencies and economic crisis. Recent studies pertaining to the understanding ... ...

    Abstract Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is accountable for the protracted COVID-19 pandemic. Its high transmission rate and pathogenicity led to health emergencies and economic crisis. Recent studies pertaining to the understanding of the molecular pathogenesis of SARS-CoV-2 infection exhibited the indispensable role of ion channels in viral infection inside the host. Moreover, machine learning (ML)-based algorithms are providing a higher accuracy for host-SARS-CoV-2 protein-protein interactions (PPIs). In this study, PPIs of SARS-CoV-2 proteins with human ion channels (HICs) were trained on the PPI-MetaGO algorithm. PPI networks (PPINs) and a signaling pathway map of HICs with SARS-CoV-2 proteins were generated. Additionally, various U.S. food and drug administration (FDA)-approved drugs interacting with the potential HICs were identified. The PPIs were predicted with 82.71% accuracy, 84.09% precision, 84.09% sensitivity, 0.89 AUC-ROC, 65.17% Matthews correlation coefficient score (MCC) and 84.09% F1 score. Several host pathways were found to be altered, including calcium signaling and taste transduction pathway. Potential HICs could serve as an initial set to the experimentalists for further validation. The study also reinforces the drug repurposing approach for the development of host directed antiviral drugs that may provide a better therapeutic management strategy for infection caused by SARS-CoV-2.
    Language English
    Publishing date 2022-02-17
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2695572-6
    ISSN 2076-0817
    ISSN 2076-0817
    DOI 10.3390/pathogens11020259
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article: In Silico Analysis of Ion Channels and Their Correlation with Epithelial to Mesenchymal Transition in Breast Cancer.

    Parthasarathi, K T Shreya / Mandal, Susmita / Singh, Smrita / Gundimeda, Seetaramanjaneyulu / Jolly, Mohit Kumar / Pandey, Akhilesh / Sharma, Jyoti

    Cancers

    2022  Volume 14, Issue 6

    Abstract: Uncontrolled growth of breast cells due to altered gene expression is a key feature of breast cancer. Alterations in the expression of ion channels lead to variations in cellular activities, thus contributing to attributes of cancer hallmarks. Changes in ...

    Abstract Uncontrolled growth of breast cells due to altered gene expression is a key feature of breast cancer. Alterations in the expression of ion channels lead to variations in cellular activities, thus contributing to attributes of cancer hallmarks. Changes in the expression levels of ion channels were observed as a consequence of EMT. Additionally, ion channels were reported in the activation of EMT and maintenance of a mesenchymal phenotype. Here, to identify altered ion channels in breast cancer patients, differential gene expression and weighted gene co-expression network analyses were performed using transcriptomic data. Protein-protein interactions network analysis was carried out to determine the ion channels interacting with hub EMT-related genes in breast cancer. Thirty-two ion channels were found interacting with twenty-six hub EMT-related genes. The identified ion channels were further correlated with EMT scores, indicating mesenchymal phenotype. Further, the pathway map was generated to represent a snapshot of deregulated cellular processes by altered ion channels and EMT-related genes. Kaplan-Meier five-year survival analysis and Cox regressions indicated the expression of
    Language English
    Publishing date 2022-03-11
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2527080-1
    ISSN 2072-6694
    ISSN 2072-6694
    DOI 10.3390/cancers14061444
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article: Aberrations in ion channels interacting with lipid metabolism and epithelial-mesenchymal transition in esophageal squamous cell carcinoma.

    Parthasarathi, K T Shreya / Mandal, Susmita / George, John Philip / Gaikwad, Kiran Bharat / Sasidharan, Sruthi / Gundimeda, Seetaramanjaneyulu / Jolly, Mohit Kumar / Pandey, Akhilesh / Sharma, Jyoti

    Frontiers in molecular biosciences

    2023  Volume 10, Page(s) 1201459

    Abstract: Esophageal squamous cell carcinoma (ESCC) is the most prevalent malignant gastrointestinal tumor. Ion channels contribute to tumor growth and progression through interactions with their neighboring molecules including lipids. The dysregulation of ... ...

    Abstract Esophageal squamous cell carcinoma (ESCC) is the most prevalent malignant gastrointestinal tumor. Ion channels contribute to tumor growth and progression through interactions with their neighboring molecules including lipids. The dysregulation of membrane ion channels and lipid metabolism may contribute to the epithelial-mesenchymal transition (EMT), leading to metastatic progression. Herein, transcriptome profiles of patients with ESCC were analyzed by performing differential gene expression and weighted gene co-expression network analysis to identify the altered ion channels, lipid metabolism- and EMT-related genes in ESCC. A total of 1,081 differentially expressed genes, including 113 ion channels, 487 lipid metabolism-related, and 537 EMT-related genes, were identified in patients with ESCC. Thereafter, EMT scores were correlated with altered co-expressed genes. The altered co-expressed genes indicated a correlation with EMT signatures. Interactions among 22 ion channels with 3 hub lipid metabolism- and 13 hub EMT-related proteins were determined using protein-protein interaction networks. A pathway map was generated to depict deregulated signaling pathways including insulin resistance and the estrogen receptor-Ca
    Language English
    Publishing date 2023-07-17
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2814330-9
    ISSN 2296-889X
    ISSN 2296-889X
    DOI 10.3389/fmolb.2023.1201459
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Article ; Online: Deciphering the Interactions of SARS-CoV-2 Proteins with Human Ion Channels Using Machine-Learning-Based Methods

    Nupur S. Munjal / Dikscha Sapra / K. T. Shreya Parthasarathi / Abhishek Goyal / Akhilesh Pandey / Manidipa Banerjee / Jyoti Sharma

    Pathogens, Vol 11, Iss 259, p

    2022  Volume 259

    Abstract: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is accountable for the protracted COVID-19 pandemic. Its high transmission rate and pathogenicity led to health emergencies and economic crisis. Recent studies pertaining to the understanding ... ...

    Abstract Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is accountable for the protracted COVID-19 pandemic. Its high transmission rate and pathogenicity led to health emergencies and economic crisis. Recent studies pertaining to the understanding of the molecular pathogenesis of SARS-CoV-2 infection exhibited the indispensable role of ion channels in viral infection inside the host. Moreover, machine learning (ML)-based algorithms are providing a higher accuracy for host-SARS-CoV-2 protein–protein interactions (PPIs). In this study, PPIs of SARS-CoV-2 proteins with human ion channels (HICs) were trained on the PPI-MetaGO algorithm. PPI networks (PPINs) and a signaling pathway map of HICs with SARS-CoV-2 proteins were generated. Additionally, various U.S. food and drug administration (FDA)-approved drugs interacting with the potential HICs were identified. The PPIs were predicted with 82.71% accuracy, 84.09% precision, 84.09% sensitivity, 0.89 AUC-ROC, 65.17% Matthews correlation coefficient score (MCC) and 84.09% F1 score. Several host pathways were found to be altered, including calcium signaling and taste transduction pathway. Potential HICs could serve as an initial set to the experimentalists for further validation. The study also reinforces the drug repurposing approach for the development of host directed antiviral drugs that may provide a better therapeutic management strategy for infection caused by SARS-CoV-2.
    Keywords virus and host ; protein interaction networks ; cellular pathways ; antiviral compounds ; Medicine ; R
    Subject code 572
    Language English
    Publishing date 2022-02-01T00:00:00Z
    Publisher MDPI AG
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

    Full text online

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  6. Article: Deciphering the Interactions of SARS-CoV-2 Proteins with Human Ion Channels Using Machine-Learning-Based Methods

    Munjal, Nupur S. / Sapra, Dikscha / Parthasarathi, K. T. Shreya / Goyal, Abhishek / Pandey, Akhilesh / Banerjee, Manidipa / Sharma, Jyoti

    Pathogens. 2022 Feb. 17, v. 11, no. 2

    2022  

    Abstract: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is accountable for the protracted COVID-19 pandemic. Its high transmission rate and pathogenicity led to health emergencies and economic crisis. Recent studies pertaining to the understanding ... ...

    Abstract Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is accountable for the protracted COVID-19 pandemic. Its high transmission rate and pathogenicity led to health emergencies and economic crisis. Recent studies pertaining to the understanding of the molecular pathogenesis of SARS-CoV-2 infection exhibited the indispensable role of ion channels in viral infection inside the host. Moreover, machine learning (ML)-based algorithms are providing a higher accuracy for host-SARS-CoV-2 protein–protein interactions (PPIs). In this study, PPIs of SARS-CoV-2 proteins with human ion channels (HICs) were trained on the PPI-MetaGO algorithm. PPI networks (PPINs) and a signaling pathway map of HICs with SARS-CoV-2 proteins were generated. Additionally, various U.S. food and drug administration (FDA)-approved drugs interacting with the potential HICs were identified. The PPIs were predicted with 82.71% accuracy, 84.09% precision, 84.09% sensitivity, 0.89 AUC-ROC, 65.17% Matthews correlation coefficient score (MCC) and 84.09% F1 score. Several host pathways were found to be altered, including calcium signaling and taste transduction pathway. Potential HICs could serve as an initial set to the experimentalists for further validation. The study also reinforces the drug repurposing approach for the development of host directed antiviral drugs that may provide a better therapeutic management strategy for infection caused by SARS-CoV-2.
    Keywords COVID-19 infection ; Food and Drug Administration ; Severe acute respiratory syndrome coronavirus 2 ; algorithms ; calcium ; drugs ; economic crises ; humans ; pathogenesis ; pathogenicity ; taste ; therapeutics
    Language English
    Dates of publication 2022-0217
    Publishing place Multidisciplinary Digital Publishing Institute
    Document type Article
    ZDB-ID 2695572-6
    ISSN 2076-0817
    ISSN 2076-0817
    DOI 10.3390/pathogens11020259
    Database NAL-Catalogue (AGRICOLA)

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  7. Article ; Online: Aberrations in ion channels interacting with lipid metabolism and epithelial–mesenchymal transition in esophageal squamous cell carcinoma

    K. T. Shreya Parthasarathi / Susmita Mandal / John Philip George / Kiran Bharat Gaikwad / Sruthi Sasidharan / Seetaramanjaneyulu Gundimeda / Mohit Kumar Jolly / Akhilesh Pandey / Jyoti Sharma

    Frontiers in Molecular Biosciences, Vol

    2023  Volume 10

    Abstract: Esophageal squamous cell carcinoma (ESCC) is the most prevalent malignant gastrointestinal tumor. Ion channels contribute to tumor growth and progression through interactions with their neighboring molecules including lipids. The dysregulation of ... ...

    Abstract Esophageal squamous cell carcinoma (ESCC) is the most prevalent malignant gastrointestinal tumor. Ion channels contribute to tumor growth and progression through interactions with their neighboring molecules including lipids. The dysregulation of membrane ion channels and lipid metabolism may contribute to the epithelial–mesenchymal transition (EMT), leading to metastatic progression. Herein, transcriptome profiles of patients with ESCC were analyzed by performing differential gene expression and weighted gene co-expression network analysis to identify the altered ion channels, lipid metabolism- and EMT-related genes in ESCC. A total of 1,081 differentially expressed genes, including 113 ion channels, 487 lipid metabolism-related, and 537 EMT-related genes, were identified in patients with ESCC. Thereafter, EMT scores were correlated with altered co-expressed genes. The altered co-expressed genes indicated a correlation with EMT signatures. Interactions among 22 ion channels with 3 hub lipid metabolism- and 13 hub EMT-related proteins were determined using protein–protein interaction networks. A pathway map was generated to depict deregulated signaling pathways including insulin resistance and the estrogen receptor-Ca2+ signaling pathway in ESCC. The relationship between potential ion channels and 5-year survival rates in ESCC was determined using Kaplan–Meier plots and Cox proportional hazard regression analysis. Inositol 1,4,5-trisphosphate receptor type 3 (ITPR3) was found to be associated with poor prognosis of patients with ESCC. Additionally, drugs interacting with potential ion channels, including GJA1 and ITPR3, were identified. Understanding alterations in ion channels with lipid metabolism and EMT in ESCC pathophysiology would most likely provide potential targets for the better treatment of patients with ESCC.
    Keywords esophageal cancer ; RNA-seq ; membrane proteins ; fatty acids ; interaction networks ; Biology (General) ; QH301-705.5
    Language English
    Publishing date 2023-07-01T00:00:00Z
    Publisher Frontiers Media S.A.
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  8. Article: A pathway map of signaling events triggered upon SARS-CoV infection.

    Parthasarathi, K T Shreya / Munjal, Nupur S / Dey, Gourav / Kumar, Abhishek / Pandey, Akhilesh / Balakrishnan, Lavanya / Sharma, Jyoti

    Journal of cell communication and signaling

    2021  Volume 15, Issue 4, Page(s) 595–600

    Abstract: Severe acute respiratory syndrome coronaviruses (SARS-CoVs) caused worldwide epidemics over the past few decades. Extensive studies on various strains of coronaviruses provided a basic understanding of the pathogenesis of the disease. Presently, severe ... ...

    Abstract Severe acute respiratory syndrome coronaviruses (SARS-CoVs) caused worldwide epidemics over the past few decades. Extensive studies on various strains of coronaviruses provided a basic understanding of the pathogenesis of the disease. Presently, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is leading a global pandemic with unprecedented challenges. This is the third coronavirus outbreak of this century. A signaling pathway map of signaling events induced by SARS-CoV infection is not yet available. In this study, we present a literature-annotated signaling pathway map of reactions induced by SARS-CoV infected cells. Multiple signaling modules were found to be orchestrated including PI3K-AKT, Ras-MAPK, JAK-STAT, Type 1 IFN and NFκB. The signaling pathway map of SARS-CoV consists of 110 molecules and 101 reactions mediated by SARS-CoV proteins. The pathway reaction data are available in various community standard data exchange formats including Systems Biology Graphical Notation (SBGN). The pathway map is publicly available through the GitHub repository and data in various formats can be freely downloadable.
    Language English
    Publishing date 2021-09-06
    Publishing country Netherlands
    Document type Journal Article
    ZDB-ID 2299380-0
    ISSN 1873-961X ; 1873-9601
    ISSN (online) 1873-961X
    ISSN 1873-9601
    DOI 10.1007/s12079-021-00642-2
    Database MEDical Literature Analysis and Retrieval System OnLINE

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