{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,25]],"date-time":"2026-08-25T06:22:42Z","timestamp":1787638962209,"version":"build-2736575974"},"reference-count":73,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,8,25]],"date-time":"2026-08-25T00:00:00Z","timestamp":1787616000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Immunol."],"abstract":"<jats:sec>\n                    <jats:title>Introduction<\/jats:title>\n                    <jats:p>An increasing number of studies focus on anti-tumor immune responses. In acute myeloid leukemia (AML), blasts and immune cells, such as T cells, are frequently studied together in the same leukocyte sample. While hemolysis is the clinical standard for leukocyte isolation because it preserves the native leukocyte composition, Ficoll-based density gradient centrifugation is widely used in research and biobanking.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Using hemolysis as a reference, we assessed whether Ficoll processing introduces biases into AML and immune cell profiling through analytical methods frequently applied in AML research.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Flow cytometry analyses showed that Ficoll systematically alters the composition of AML samples by enriching lymphocytes and AML blasts while depleting granulocytes. In RNA sequencing analysis, Ficoll isolation altered the expression of 1,136 genes, notably leading to an overestimation of the expression of leukemic stem cell gene sets. Immunogenomic deconvolution highlighted that Ficoll leads to an overestimation of CD8\n                      <jats:sup>+<\/jats:sup>\n                      T-cell and monocyte abundances. Mutation calling from RNA-seq data revealed substantial discrepancies between methods, including failure to detect a clinically relevant DNMT3A R882 mutation in a Ficoll-processed sample. While Ficoll isolation had minimal impact on\n                      <jats:italic>ex vivo<\/jats:italic>\n                      AML blast expansion or chemotherapy response, it appeared to affect AML engraftment in NSG mice, possibly through the enrichment of T cells mediating graft-versus-host disease.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Discussion<\/jats:title>\n                    <jats:p>Together, these findings show that Ficoll isolation introduces bias in the cellular and molecular characterization of AML samples while having only a moderate impact on functional assays. We provide recommendations on which method to use depending on the investigator's objectives.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fimmu.2026.1920697","type":"journal-article","created":{"date-parts":[[2026,8,25]],"date-time":"2026-08-25T05:35:26Z","timestamp":1787636126000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Ficoll-based isolation biases the profiling of immune cells and leukemic blasts in AML samples"],"prefix":"10.3389","volume":"17","author":[{"given":"Bianca","family":"E Silva","sequence":"first","affiliation":[{"name":"GIGA Institute, Laboratory of Hematology, University of Li\u00e8ge","place":["Li\u00e8ge, Belgium"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alison","family":"Daubry","sequence":"additional","affiliation":[{"name":"GIGA Institute, Laboratory of Hematology, University of Li\u00e8ge","place":["Li\u00e8ge, 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