HSPBP1 9 bp insertion mutation concurrent with pro-apoptosis and NF-κB genomic integrity predicts response to bortezomib-mediated proteasome inhibition in recurrent glioblastoma treated in NCT03643549 trial

Resistance to cytotoxic therapy in glioblastoma (GBM) is largely driven by DNA repair mechanisms. Proteasome inhibition may sensitize tumors through suppression of NF-κB survival signaling and MGMT transcription. However, biological mechanisms that modulate tumor-intrinsic sensitivity remain poorly understood. 58 patients with recurrent MGMT-unmethylated GBM, undergoing sequential bortezomib-temozolomide in an ongoing Phase II trial were analyzed. Prospective machine learning (ML) response prediction employed multimodal features, integrating whole-exome sequencing, longitudinal deep learning tumor segmentation (n=116 mpMRIs), clinical variables, and quality-of-life measures. Patients were split chronologically into training (n=43) and prospective validation (n=15) cohorts. Post hoc pathway burden analysis stratified non-objective responders by unsupervised clustering, identifying distinct genomic resistance mechanisms. 14/58 patients (24%) achieved objective RANO response. ML modelling achieved validation AUC 0.91 (permutation p=0.0260), where HSPBP1 9 bp insertion emerged as the dominant predictor, consistent with impaired chaperone-mediated protein folding and accumulation of nascent proteins for degradation. This finding aligns with prior preclinical evidence that disruption of HSP70-dependent protein quality control amplifies proteasome-inhibitor-induced proteotoxic stress. The mutation was present in 100% of RANO-responders versus 59% in the remaining patients (p=0.0027, OR>100) suggesting this mutation confers sensitivity to proteasome inhibition. However, objective response was only observed when accompanied by preserved downstream apoptosis and NF-κB signaling. Responders exhibited significantly lower loss-of-function (LoF) mutation burden in apoptosis, NF-κB, cell cycle regulation, and RTK signaling (all p<0.03). Pathway burden clustering identified three distinct resistance mechanisms: I) deficient apoptosis machinery; II) proteasome-independent survival pathways; and III) insufficient proteotoxic stress. Survival differed across groups (overall log rank p=0.013), where cluster I yielded the poorest OS (median 15.5 months vs 20.9 in RANO-responders, p<0.01). A radiogenomic association also emerged: baseline contrast-enhancing (CE) /non-enhancing (NE) volume ratio correlated with apoptosis LoF burden (Spearman's ρ=0.454, p<0.001), where lower CE/NE ratios denoted preserved apoptotic capacity and greater treatment sensitivity. This manifested clinically by 4.7-fold higher response rate in patients with CE/NE ratio ≤0.324 and low LoF burden (OR=13.42, p=0.0026). Although clinical trials are inherently not powered for ML endpoints, our unique use of primary data in a prospective clinical treatment setting provides actionable insights. HSPBP1 mutation, concurrent with preserved apoptosis and NF-κB pathway integrity, emerged as predictive biomarker of clinical benefit from proteasome inhibition in recurrent MGMT-unmethylated GBM.