{"id":6007,"date":"2026-08-26T06:34:24","date_gmt":"2026-08-26T06:34:24","guid":{"rendered":"https:\/\/pge2-hypothesis.com\/?page_id=6007"},"modified":"2026-08-26T06:42:33","modified_gmt":"2026-08-26T06:42:33","slug":"assessing-ep-in-pbmcs","status":"publish","type":"page","link":"https:\/\/pge2-hypothesis.com\/?page_id=6007","title":{"rendered":"Assessing EP in PBMCs"},"content":{"rendered":"\t\t
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Assessing EP receptor signatures in PBMC\u2019s<\/h2>\t\t\t\t<\/div>\n\t\t\t\t
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Biochemical measurements obtained from the plasma of the different clinical cohorts can be compared with one another. As an initial discovery approach quantification of PTGER1\u2013PTGER4 transcripts (mRNA) in whole PBMCs would already be highly informative, particularly if distinct PTGER transcript signatures correlate with the cytokine clusters previously identified in the cohort. If such signatures are observed, RT-qPCR analysis of PTGER transcripts in sorted monocytes and CD4\u207a T cells could subsequently be performed to determine whether the PBMC signature reflects intrinsic receptor regulation within specific immune cell populations, changes in the composition of the circulating immune compartment, or a combination of both.<\/p>

To independently assess T-helper cell polarization, the lineage-defining transcription factors TBX21, GATA3, RORC, and FOXP3 could be quantified by RT-qPCR in parallel. If transcript-level differences are confirmed, these findings could subsequently be validated at the protein level by intracellular flow cytometric staining for T-bet, GATA3, ROR\u03b3t, and FOXP3.<\/p>

Functional receptor studies would only be considered after transcript and protein differences have been established.<\/p>

Experimental strategy<\/strong> (not all phases have to be included)<\/em>

Phase I – PTGER transcript signatures of circulating PBMCs<\/strong><\/h4>

Measure PTGER1\u2013PTGER4 transcripts in total PBMCs using RT-qPCR<\/p>

Beginning with whole PBMCs provides a rapid, inexpensive<\/em> and unbiased assessment of the circulating immune system. The balance among PTGER1\u2013PTGER4 transcripts reflects the immune state of the patient. If PTGER transcript signatures prove informative, progressively more detailed analyses can identify the cellular origin and functional significance of these signatures.<\/p>

This approach maximizes information gained while minimizing experimental complexity and cost.<\/p>

Objective:<\/p>

Determine whether distinct PTGER transcript signatures are associated with previously identified Long COVID immune subtypes and cytokine-clusters.<\/p>

Phase II – PTGER transcript signatures in sorted monocytes and CD4\u207a T cells<\/strong>1<\/sup><\/h4>

Measure RT-qPCR of PTGER1\u2013PTGER4 in sorted monocytes and CD4\u207a T cells using RT-qPCR<\/p>

Objective:<\/p>

Determine whether distinct PTGER transcript signatures are stimulated by specific subsets of immune cells<\/p>

Phase III – Measuring factors that define Th subsets<\/strong>2<\/sup><\/strong><\/h4>

To independently assess T-helper cell polarization, lineage-defining transcription factors (TBX21, GATA3, RORC and FOXP3) could be quantified by RT-qPCR. If distinct PTGER transcript signatures are identified, these findings may subsequently be validated at the protein level by intracellular flow cytometric staining for T-bet, GATA3, ROR\u03b3t and FOXP3.<\/p>

  1. RT-qPCR analysis of T-helper cell lineage-specific transcription factors<\/li><\/ol>

    TBX21 (T-bet) \u2192 Th1<\/p>

    GATA3 \u2192 Th2<\/p>

    RORC (ROR\u03b3t) \u2192 Th17<\/p>

    FOXP3 \u2192 Treg<\/p>

    2. Flow cytometry<\/p>

    Staining intracellularly for:<\/p>

    T-bet
    GATA3
    ROR\u03b3t
    FOXP3<\/p>

    after first identifying CD4\u207a T cells.<\/p>

    Objective:<\/p>

    Determine whether PTGER transcript signatures correlate with T-helper cell polarization

    Phase IV – EP receptor protein expression profile<\/strong>3<\/sup><\/p>

    Measure EP receptor protein expression using flow cytometry. Analyze individual immune cell subsets (e.g. CD14\u207a monocytes, CD4\u207a T cells, CD8\u207a T cells and NK cells)<\/p>

    Objective:<\/p>

    Determine whether transcript differences correspond to altered receptor abundance and phenotypes.<\/p>

    Phase V \u2013 signaling assays<\/strong>4<\/sup>\u00a0<\/strong><\/h4>

    Perform functional signaling assays following stimulation with PGE2 or selective EP receptor agonists.<\/p>

    Objective:<\/p>

    Determine whether differences in transcript or protein expression translate into altered receptor signaling capacity.<\/p>

    Table 4. Overview of technical options<\/p>

    RNA extraction<\/p><\/td>

    Standard kit<\/p><\/td>

    Total RNA<\/p><\/td><\/tr>

    Reverse transcription<\/p><\/td>

    cDNA synthesis<\/p><\/td>

    cDNA<\/p><\/td><\/tr>

    RT-qPCR1<\/sup><\/p>

    (qRT-PCR) in whole PMBC\u2019s<\/p><\/td>

    PTGER1\u2013PTGER4<\/p><\/td>

    Is there a PTGER transcript signature?<\/p><\/td><\/tr>

    after cell sorting<\/p><\/td>

    MACS or FACS<\/p><\/td>

    Monocytes, CD4\u207a T cells, optionally NK cells<\/p><\/td><\/tr>

    Northern blot analysis5<\/sup><\/p><\/td>

    (used before qPCR became standard)<\/p><\/td>

    EP transcripts in immune cells<\/p><\/td><\/tr>

    RT-qPCR analysis of T-helper cell lineage-specific transcription factors 2,6-9<\/sup><\/p><\/td>

    PBMC<\/p><\/td>

    Is the PBMC compartment enriched for Th1-, Th2-, Th17-, (or Treg) associated programs?<\/p><\/td><\/tr>

    Flow cytometry7<\/sup><\/p><\/td>

    CD4\u207a T cells<\/p><\/td>

    Do Th-cell signatures emerge?<\/p><\/td><\/tr>

    scRNA-seq1<\/sup>,<\/sup>10<\/sup><\/p>

    (expensive)<\/p><\/td>

    Single cell<\/p><\/td>

    Which cell types generate the PTGE signature?<\/p><\/td><\/tr>

    Western blot3<\/sup><\/p><\/td>

    Measures total receptor protein, good for cultured monocytes<\/p><\/td>

    Cannot distinguish which immune cell expresses the protein<\/p><\/td><\/tr>

    Flow cytometry3<\/sup><\/p><\/td>

    EP-receptors on monocytes (if validated antibodies are available)<\/p><\/td>

    Are the receptors actually present on the cell surface?<\/p><\/td><\/tr>

    Functional assays4<\/sup><\/p><\/td>

    cAMP, calcium, \u03b2-arrestin recruitment<\/p><\/td>

    Do the receptors signal differently?<\/p><\/td><\/tr><\/tbody><\/table>

    1\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Kashmiry, A., Tate, R., Rotondo, G., Davidson, J. & Rotondo, D. The prostaglandin EP4 receptor is a master regulator of the expression of PGE(2) receptors following inflammatory activation in human monocytic cells. Biochim Biophys Acta Mol Cell Biol Lipids<\/em> 1863<\/strong>, 1297-1304 (2018). https:\/\/doi.org\/10.1016\/j.bbalip.2018.07.003<\/a><\/p>

    2\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Wang, Y., Su, M. A. & Wan, Y. Y. An essential role of the transcription factor GATA-3 for the function of regulatory T cells. Immunity<\/em> 35<\/strong>, 337-348 (2011). https:\/\/doi.org\/10.1016\/j.immuni.2011.08.012<\/a><\/p>

    3\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Klasen, C. et al.<\/em> Prostaglandin receptor EP4 expression by Th17 cells is associated with high disease activity in ankylosing spondylitis. Arthritis Res Ther<\/em> 21<\/strong>, 159 (2019). https:\/\/doi.org\/10.1186\/s13075-019-1948-1<\/a><\/p>

    4\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Lone, A. M. et al.<\/em> Systems approach reveals distinct and shared signaling networks of the four PGE. Sci Signal<\/em> 14<\/strong>, eabc8579 (2021). https:\/\/doi.org\/10.1126\/scisignal.abc8579<\/a><\/p>

    5\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Mori, K. et al.<\/em> Gene expression of the human prostaglandin E receptor EP4 subtype: differential regulation in monocytoid and lymphoid lineage cells by phorbol ester. J Mol Med (Berl)<\/em> 74<\/strong>, 333-336 (1996). https:\/\/doi.org\/10.1007\/bf00207510<\/a><\/p>

    6\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Sadeghalvad, M., Khijakadze, D., Orangi, M. & Takei, F. Flow cytometric analysis of innate lymphoid cells: challenges and solutions. Frontiers in Immunology<\/em> Volume 14 – 2023<\/strong> (2023). https:\/\/doi.org\/10.3389\/fimmu.2023.1198310<\/a><\/p>

    7\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Cossarizza, A. et al.<\/em> Guidelines for the use of flow cytometry and cell sorting in immunological studies. European Journal of Immunology<\/em> 47<\/strong>, 1584-1797 (2017). https:\/\/doi.org\/https:\/\/doi.org\/10.1002\/eji.201646632<\/a><\/p>

    8\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Yu, F., Sharma, S., Edwards, J., Feigenbaum, L. & Zhu, J. Dynamic expression of transcription factors T-bet and GATA-3 by regulatory T cells maintains immunotolerance. Nat Immunol<\/em> 16<\/strong>, 197-206 (2015). https:\/\/doi.org\/10.1038\/ni.3053<\/a><\/p>

    9\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Lu, Y. et al.<\/em> Expansion of CD4+CD25+ and CD25- T-Bet, GATA-3, Foxp3 and ROR\u03b3t Cells in Allergic Inflammation, Local Lung Distribution and Chemokine Gene Expression. PLOS ONE<\/em> 6<\/strong>, e19889 (2011). https:\/\/doi.org\/10.1371\/journal.pone.0019889<\/a><\/p>

    10\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Punyawatthananukool, S. et al.<\/em> Prostaglandin E2-EP2\/EP4 signaling induces immunosuppression in human cancer by impairing bioenergetics and ribosome biogenesis in immune cells. Nature Communications<\/em> 15<\/strong>, 9464 (2024). https:\/\/doi.org\/10.1038\/s41467-024-53706-3<\/a><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"

    Assessing EP receptor signatures in PBMC\u2019s Biochemical measurements obtained from the plasma of the different clinical cohorts can be compared […]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"site-sidebar-layout":"no-sidebar","site-content-layout":"","ast-site-content-layout":"full-width-container","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"disabled","footer-sml-layout":"","ast-disable-related-posts":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"footnotes":""},"class_list":["post-6007","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/pge2-hypothesis.com\/index.php?rest_route=\/wp\/v2\/pages\/6007","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/pge2-hypothesis.com\/index.php?rest_route=\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/pge2-hypothesis.com\/index.php?rest_route=\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/pge2-hypothesis.com\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/pge2-hypothesis.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=6007"}],"version-history":[{"count":19,"href":"https:\/\/pge2-hypothesis.com\/index.php?rest_route=\/wp\/v2\/pages\/6007\/revisions"}],"predecessor-version":[{"id":6028,"href":"https:\/\/pge2-hypothesis.com\/index.php?rest_route=\/wp\/v2\/pages\/6007\/revisions\/6028"}],"wp:attachment":[{"href":"https:\/\/pge2-hypothesis.com\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=6007"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}