1328P - Dynamic blood immune-inflammatory and radiomic profiling to decode distinct patterns of acquired resistance to immunotherapy in NSCLC patients

Background

Decoding the heterogeneity of tumor-host interactions underlying acquired resistance (AR) to immunotherapy (IO) is critical to timely introduce treatment changes and expand the population of IO-responsive patients. To uncover the underpinnings of AR to IO, we determined whether distinctive clinico-pathological, radiomic and peripheral blood (PB) immune-inflammatory features reflect oligo- and systemic (sys)-AR in advanced NSCLC patients undergoing immune checkpoints inhibitors.

Methods

On 105 consecutive IO-treated advanced NSCLC, PB immunophenotypes, cytokines and CT-derived radiomic features (RFs), extracted from primary and merged metastatic lesions, were prospectively collected at baseline (T0) and at first disease assessment (T1, 9-12 weeks) and their delta (Δ) variation [(T1-T0)/T0] computed. AR, defined as progression after initial response (complete/partial) or stable disease ≥ 6 months, was subdivided according to the number of new and/or progressive lesions in oligoAR (≤3) and sysAR (>3). Clinico-pathological, PB and radiomic parameters and survival outcome were statistically correlated to AR patterns.

Results

OligoAR and sysAR involved 24% and 12.4% of cases, respectively. While baseline PB immune profiles were comparable, a Δ+ cytotoxic (NK, CD8+GnzB+) and Δ- immunosuppressive (CD14+ monocytes) dynamic coupled with different modulation of IL-6, IFNγ, TGF-β1, TNFα and sPD-L1 were distinctive features of oligoAR vs sysAR (P<0.05). Significantly longer post-progression survival characterized oligoAR vs sysAR (median 20.3 vs 5.6 months; HR:0.22; P<0.001). The number and sites of oligoAR involvement appeared to condition blood immune background (P<0.05) and survival. Delta radiomic outperformed baseline RFs, with 24 Δ-RFs sharply discriminating oligoAR from sysAR (P range: <0.001-0.04). ROC analysis confirmed the optimal performance of top-ranked Δ-RFs (AUC range: 0.88-0.99).

Conclusions

Longitudinal analysis of blood immune hallmarks and radiomic descriptors may decipher distinct patterns of AR to IO in advanced NSCLC patients, thus representing a non-invasive approach to track AR onset and evolution and guide clinical decision making.

Clinical trial identification

Editorial acknowledgement

Legal entity responsible for the study

University of Parma.

Funding

AIRC - Associazione Italiana per la Ricerca sul Cancro.

Disclosure

All authors have declared no conflicts of interest.