{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,17]],"date-time":"2026-10-17T23:43:32Z","timestamp":1792280612283,"version":"4.4.0"},"reference-count":44,"publisher":"American Society of Clinical Oncology (ASCO)","issue":"21","content-domain":{"domain":["ascopubs.org"],"crossmark-restriction":true},"short-container-title":["J Clin Oncol"],"published-print":{"date-parts":[[2026,7,20]]},"abstract":"<jats:sec>\n                    <jats:title>PURPOSE<\/jats:title>\n                    <jats:p>Treatment-free remission (TFR) is a major therapeutic objective in chronic myeloid leukemia (CML). However, nearly 50% of patients relapse after tyrosine kinase inhibitor (TKI) discontinuation, and no robust predictive biomarker is currently available.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>METHODS<\/jats:title>\n                    <jats:p>We profiled peripheral blood cell transcriptomes at imatinib (IMA) discontinuation in patients from the multicenter STIM2 trial (n = 96) to develop a transcriptome-based model predicting TFR by 2 years. A DESEQ2-based machine learning approach was compared with classical machine learning algorithms. The signature was then externally validated in an independent real-world cohort of patients attempting IMA or nilotinib cessation (n = 70). The biologic processes associated with the signature were further explored.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>RESULTS<\/jats:title>\n                    <jats:p>\n                      We identified a 50-gene signature discriminating patients with sustained 2-year TFR from those experiencing molecular relapse (area under the receiver operating characteristic curve [AUROC], 0.83 [95% CI, 0.73 to 0.93] and 0.75 [95% CI, 0.55 to 1.00] in the training and internal validation cohorts, respectively). The discriminative performance was confirmed in the external test cohort, both as a binary predictor of 2-year TFR (AUROC, 0.71 [95% CI, 0.58 to 0.83] overall; 0.77 [95% CI, 0.61 to 0.92] in IMA-treated patients) and as a time-to-event predictor (log-rank\n                      <jats:italic toggle=\"yes\">P<\/jats:italic>\n                      = .0042). The high TFR-signature group showed a higher proportion of myeloid immune cells and natural killer T cells, with an enrichment in Hedgehog signaling, whereas the low TFR-signature group demonstrated a higher proportion of lymphoid cells with an enrichment in mTOR signaling and a trend for oxidative phosphorylation activation. T-cell receptor and immunoglobulin heavy-chain repertoire analyses showed significantly greater polyclonality in the high TFR-signature group.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>CONCLUSION<\/jats:title>\n                    <jats:p>These findings demonstrate that transcriptomic profiling at TKI discontinuation can predict TFR outcomes in patients with CML and provide biologic insights into the mechanisms underlying sustained TFR.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1200\/jco-25-02948","type":"journal-article","created":{"date-parts":[[2026,6,9]],"date-time":"2026-06-09T20:00:09Z","timestamp":1781035209000},"page":"1992-2005","update-policy":"https:\/\/doi.org\/10.1200\/crossmark","source":"Crossref","is-referenced-by-count":2,"title":["Development and External Validation of a Transcriptome-Based Multivariable Prediction Model for Treatment-Free Remission in Chronic Myeloid Leukemia"],"prefix":"10.1200","volume":"44","clinical-trial-number":[{"clinical-trial-number":"nct01343173","registry":"10.18810\/clinical-trials-gov"}],"author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1843-6286","authenticated-orcid":false,"given":"Vincent","family":"Alcazer","sequence":"first","affiliation":[{"name":"Service d\u2019H\u00e9matologie Clinique, Hospices Civils de Lyon, Pierre-B\u00e9nite, France"},{"name":"Centre International de Recherche en Infectiologie (CIRI), INSERM U1111, Lyon, France"},{"name":"Universit\u00e9 Claude Bernard Lyon 1, Lyon, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2728-7243","authenticated-orcid":false,"given":"St\u00e9phanie","family":"Dulucq","sequence":"additional","affiliation":[{"name":"Laboratoire d\u2019H\u00e9matologie, CHU de Bordeaux, INSERM, U1312 BRIC, Universit\u00e9 de Bordeaux, Bordeaux, 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