Integration of MRI radiomics with immune profiling to predict response to CDK6 inhibitors in high-grade glioma.

BACKGROUND

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-Immune Score (R/I-Score), combining MRI-derived tumor heterogeneity with peripheral immune profiling, would predict progression-free survival (PFS) benefit from CDK6 inhibitor-containing therapy (CDK6i).

METHODS

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 = 116) was partitioned into a training set (n = 81) and an independent testing set (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's ability to stratify therapeutic responders.

RESULTS

In the overall matched cohort (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 vs. 3.5 months; HR 0.72, P = 0.091), objective response rate (19.4% vs. 9.7%; P = 0.180), and disease control rate (44.4% vs. 30.6%; P = 0.165). The Combined R/I-Clinical Model demonstrated exceptional diagnostic performance in the independent testing cohort (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 0.25-0.91; P = 0.008), whereas those with a Low R/I-Score did not (HR 1.05; 95% CI 0.58-1.92). The interaction between the R/I-Score and treatment was statistically significant (Pinteraction = 0.012). Furthermore, High R/I-Score patients achieved superior objective response rates (33.3% vs. 5.6%) and sustained treatment duration (median 6 vs. 3 cycles) without increased toxicity (Grade ≥3 AEs: P>0.05). Biological interpretability analysis revealed that the score was driven by tumor morphological complexity and NK/CD8+ T-cell infiltration.

CONCLUSIONS

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.