{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,16]],"date-time":"2026-06-16T20:55:02Z","timestamp":1781643302767,"version":"3.54.5"},"reference-count":22,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2026,3,16]],"date-time":"2026-03-16T00:00:00Z","timestamp":1773619200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2026,4,23]],"date-time":"2026-04-23T00:00:00Z","timestamp":1776902400000},"content-version":"vor","delay-in-days":38,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Transl Med"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>The transcription factor interferon-regulatory factor-4 (IRF4) has recently been highlighted as a valuable biomarker due to its common dysregulation and association with poor prognoses in hematological malignancies such as multiple myeloma (MM). With several clinical programs for the inhibition of IRF4 currently in development, determination of the optimal sample collection conditions and quantification methods will facilitate optimal selection of patients for these treatments, along with enabling robust monitoring of their molecular responses to IRF4 inhibitory agents over time.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      Using peripheral blood samples from healthy donors, we evaluated IRF4 mRNA and protein stability across a range of pre-analytical conditions including blood collection tube type (comparing EDTA, Paxgene ccfDNA, and Na Citrate), sample processing interval (24 to 48\u2009hours after sample collection), and cell population isolated (total mononuclear cells, CD3\n                      <jats:sup>+<\/jats:sup>\n                      T lymphocytes, CD14\n                      <jats:sup>+<\/jats:sup>\n                      monocytes, and CD19\n                      <jats:sup>+<\/jats:sup>\n                      B lymphocytes). We sought to further determine the extent to which post-processing variables such as cell yield, RNA yield, and housekeeping gene (\n                      <jats:italic>ACTB<\/jats:italic>\n                      versus\n                      <jats:italic>HSPA5<\/jats:italic>\n                      and\n                      <jats:italic>ATF4<\/jats:italic>\n                      ) selection may influence measurements of IRF4 mRNA and protein abundance. RNA and protein quantification endpoints included qRT-PCR and intranuclear flow cytometric analyses, respectively, to characterize the cell surface and intracellular molecular signatures.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      In qRT-PCR biomarker studies, we found that human IRF4 expression was detectable in all cell fractions (PBMCs, CD19\n                      <jats:sup>+<\/jats:sup>\n                      B cells and CD3\n                      <jats:sup>+<\/jats:sup>\n                      T cells) evaluated and tube types tested (Na Citrate, EDTA, Paxgene ccfDNA). However, transcript stability of hIRF4 and the well-established reference gene \u03b2-actin (\n                      <jats:italic>ACTB<\/jats:italic>\n                      ), as inferred from raw quantification cycle (Cq) values, varied substantially across tube types and between processing delay time points. mRNA levels of IRF4 along with an alternate, MM-optimized, reference gene,\n                      <jats:italic>HSPA5<\/jats:italic>\n                      , were determined to exhibit optimal stability in samples collected in Na Citrate preservative tubes. This tube type also offered the highest stability of immune cell surface antigens across 24\u201348-hour processing delays. Intranuclear IRF4 protein levels were remarkably stable in all cell populations tested across all tube types, with the highest relative expression in CD14\n                      <jats:sup>+<\/jats:sup>\n                      and CD19\n                      <jats:sup>+<\/jats:sup>\n                      fractions, and lowest in CD3\n                      <jats:sup>+<\/jats:sup>\n                      fractions, in this cohort of healthy donors.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Overall, Na Citrate tubes maintained the stability of IRF4 mRNA and protein expression even after sample processing intervals of up to 48\u2009hours post-collection. Furthermore, IRF4 protein appears to be slightly more stable than mRNA after variable processing delays, but both analytes are expected to be detectable and relatively stable in clinical samples, thus enabling reliable analysis of IRF4 as a molecular biomarker in clinical samples collected from multiple sites and shipped to a central laboratory.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1186\/s12967-026-07803-0","type":"journal-article","created":{"date-parts":[[2026,3,16]],"date-time":"2026-03-16T16:09:03Z","timestamp":1773677343000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Optimal conditions for quantification of IRF4 mRNA and protein as a correlative biomarker in clinical cancer studies"],"prefix":"10.1186","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0664-5630","authenticated-orcid":false,"given":"Joshua D.","family":"Hartman","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Silvia","family":"Vicenzi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alexander A.","family":"Tong","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lara C.","family":"Avsharian","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ashni A.","family":"Vora","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Caitlin","family":"Costello","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ida","family":"Deichaite","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0704-0067","authenticated-orcid":false,"given":"Leslie A.","family":"Crews","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,3,16]]},"reference":[{"key":"7803_CR1","doi-asserted-by":"publisher","first-page":"568","DOI":"10.1016\/j.clinbiochem.2017.02.021","volume":"50","author":"D Giavarina","year":"2017","unstructured":"Giavarina D, Lippi G. 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All other authors declare no competing interests.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"575"}}