{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,15]],"date-time":"2026-09-15T15:53:31Z","timestamp":1789487611947,"version":"build-2803163510"},"reference-count":44,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,9,15]],"date-time":"2026-09-15T00:00:00Z","timestamp":1789430400000},"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>Background<\/jats:title>\n                    <jats:p>Predictive biomarkers are needed to identify patients with high-grade glioma who benefit from cyclin-dependent kinase 6 (CDK6) inhibition. We hypothesized that an integrated Radiomics\u2013Immune Score (R\/I-Score), combining MRI-derived tumor heterogeneity with peripheral immune profiling, would predict progression-free survival (PFS) benefit from CDK6 inhibitor\u2013containing therapy (CDK6i).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      We conducted a two-center, retrospective cohort study utilizing longitudinal data from departmental neuro-oncology registries. The final study population comprised 116 adult patients with measurable disease who had undergone baseline contrast-enhanced MRI within 21 days prior to treatment initiation. To ensure methodological rigor and internal consistency, we adopted a two-stage study design. In the first stage (Biological Modeling), the total cohort (\n                      <jats:italic>N<\/jats:italic>\n                      = 116) was partitioned into a training set (\n                      <jats:italic>n<\/jats:italic>\n                      = 81) and an independent testing set (\n                      <jats:italic>n<\/jats:italic>\n                      = 35) to develop and validate the R\/I-Score. In the second stage (Clinical Validation), we addressed the selection bias inherent in observational data by performing 1:2 Propensity Score Matching (PSM). This yielded a balanced analytical cohort of 108 patients (36 treated with CDK6i and 72 concurrent contro\\ls). The primary endpoint was the treatment-by-biomarker interaction for progression-free survival (PFS), specifically assessing the R\/I-Score\u2019s ability to stratify therapeutic responders.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      In the overall matched cohort (\n                      <jats:italic>N<\/jats:italic>\n                      = 108), patients treated with CDK6i exhibited numerical but statistically non-significant trends toward improved efficacy compared to concurrent controls in terms of median PFS (4.8\n                      <jats:italic>vs<\/jats:italic>\n                      . 3.5 months; HR 0.72,\n                      <jats:italic>P<\/jats:italic>\n                      = 0.091), objective response rate (19.4%\n                      <jats:italic>vs<\/jats:italic>\n                      . 9.7%;\n                      <jats:italic>P<\/jats:italic>\n                      = 0.180), and disease control rate (44.4%\n                      <jats:italic>vs<\/jats:italic>\n                      . 30.6%;\n                      <jats:italic>P<\/jats:italic>\n                      = 0.165). The Combined R\/I-Clinical Model demonstrated exceptional diagnostic performance in the independent testing cohort (\n                      <jats:italic>N<\/jats:italic>\n                      = 108), achieving a Treatment-Effect AUC of 0.97 and excellent calibration. In the PSM efficacy analysis, the R\/I-Score successfully identified a distinct responder subpopulation: patients with a High R\/I-Score derived significant survival benefit from CDK6i compared to concurrent controls (HR 0.48; 95% CI 0.25\u20130.91;\n                      <jats:italic>P<\/jats:italic>\n                      = 0.008), whereas those with a Low R\/I-Score did not (HR 1.05; 95% CI 0.58\u20131.92). The interaction between the R\/I-Score and treatment was statistically significant (\n                      <jats:italic>\n                        P\n                        <jats:sub>interaction<\/jats:sub>\n                      <\/jats:italic>\n                      = 0.012). Furthermore, High R\/I-Score patients achieved superior objective response rates (33.3%\n                      <jats:italic>vs.<\/jats:italic>\n                      5.6%) and sustained treatment duration (median 6\n                      <jats:italic>vs.<\/jats:italic>\n                      3 cycles) without increased toxicity (Grade \u22653 AEs:\n                      <jats:italic>P<\/jats:italic>\n                      &amp;gt;0.05). Biological interpretability analysis revealed that the score was driven by tumor morphological complexity and NK\/CD8+ T-cell infiltration.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>The multi-modal R\/I-Score serves as a robust, non-invasive predictive biomarker for CDK6i therapy in GBM. By selecting patients based on specific radiomic-immune phenotypes, this tool facilitates precision oncology, maximizing therapeutic efficacy while avoiding futile treatment in non-responders.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fimmu.2026.1735070","type":"journal-article","created":{"date-parts":[[2026,9,15]],"date-time":"2026-09-15T14:59:31Z","timestamp":1789484371000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Integration of MRI radiomics with immune profiling to predict response to CDK6 inhibitors in high-grade glioma"],"prefix":"10.3389","volume":"17","author":[{"given":"Jianfang","family":"Wang","sequence":"first","affiliation":[{"name":"Department of Neurosurgery, The Fifth People\u2019s Hospital of Datong","place":["Datong, Shanxi, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Peng","family":"Li","sequence":"additional","affiliation":[{"name":"Department 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