Blood-based kinase activity profiling: a potential predictor of response to immune checkpoint inhibition in metastatic cancer.

BACKGROUND

Many cancer patients do not obtain clinical benefit from immune checkpoint inhibition. Checkpoint blockade targets T cells, suggesting that tyrosine kinase activity profiling of baseline peripheral blood mononuclear cells may predict clinical outcome.

METHODS

Here a total of 160 patients with advanced melanoma or non-small-cell lung cancer (NSCLC), treated with anti-cytotoxic T-lymphocyte-associated protein 4 (anti-CTLA-4) or anti-programmed cell death 1 (anti-PD-1), were divided into five discovery and cross-validation cohorts. The kinase activity profile was generated by analyzing phosphorylation of peripheral blood mononuclear cell lysates in a microarray comprising of 144 peptides derived from sites that are substrates for protein tyrosine kinases. Binary grouping into patients with or without clinical benefit was based on Response Evaluation Criteria in Solid Tumors V.1.1. Predictive models were trained using partial least square discriminant analysis (PLS-DA), performance of the models was evaluated by estimating the correct classification rate (CCR) using cross-validation.

RESULTS

The kinase phosphorylation signatures segregated responders from non-responders by differences in canonical pathways governing T-cell migration, infiltration and co-stimulation. PLS-DA resulted in a CCR of 100% and 93% in the anti-CTLA-4 and anti-PD1 melanoma discovery cohorts, respectively. Cross-validation cohorts to estimate the accuracy of the predictive models showed CCRs of 83% for anti-CTLA-4 and 78% or 68% for anti-PD-1 in melanoma or NSCLC, respectively.

CONCLUSION

Blood-based kinase activity profiling for response prediction to immune checkpoint inhibitors in melanoma and NSCLC revealed increased kinase activity in pathways associated with T-cell function and led to a classification model with a highly accurate classification rate in cross-validation groups. The predictive value of kinase activity profiling is prospectively verified in an ongoing trial.

Informations de copyright

© Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY. Published by BMJ.

Déclaration de conflit d'intérêts

Competing interests: EMEV and SHvdB hold a patent on the assay to predict clinical response to checkpoint blockade therapy. RdW, LH, DMAvdH, RR, HMP and JPG are employees of PamGene International BV and MPL have research funds from Roche and Novartis for projects outside the submitted work. RD has intermittent, project focused consulting and/or advisory relationships with Novartis, MSD, BMS, Roche, Amgen, Takeda, Pierre Fabre, Sun Pharma, Sanofi, Catalym, Second Genome, Regeneron and Alligator outside the submitted work. RHJM reports grants from Astellas, Bayer and Boehringer Ingelheim, Cristal Therapeutics, Pamgene, Novartis, Servier, Pfizer, Roche and Sanofi, outside the submitted work, and has a patent biomarker for immunotherapy pending. JGJVA reports personal fees from MSD, BMS, Amphera, Eli-Lilly, Takeda, Bayer, Roche, Boehringer Ingelheim and AstraZeneca outside the submitted work, and has a patent allogenic tumor cell lysate licensed to Amphera, a patent combination immunotherapy in cancer and a patent biomarker for immunotherapy pending. HMP has an advisory relationship with Qurin Diagnostics, VitrOmics HealthCare Holding and Experimental Biotherapeutics. The authors declare that there are no other conflicts of interest.