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-

Ex vivo multiplex profiling of protein tyrosine kinase activities in early stages of human lung adenocarcinoma

Despite constant improvement in existing therapeutic efforts, the overall survival rate of lung cancer patients remains low. Enzyme activities may identify new therapeutically targetable biomarkers and overcome the marked lack of correlation between cellular abundance of translated proteins and corresponding mRNA expression levels. We analysed tyrosine kinase activities to classify lung adenocarcinoma (LuAdCa) resection specimens based on their underlying changes in cellular processes and pathways that are agents of or result from malignant transformation. We characterised 71 same-patient pairs of early-stage LuAdCa and non-neoplastic LuAdCa resection specimen lysates in the presence or absence of a tyrosine kinase inhibitor. We performed ex vivo multiplex tyrosine phosphorylation assays using 144 selected microarrayed kinase substrates. The obtained 76 selected phosphotyrosine signature peptides were subsequently analysed in terms of follow-up treatments and outcomes recorded in the patient files. For tumour, node, metastasis (TNM) stage 1 LuAdCa patients, we noticed a larger tyrosine kinase inhibitor-induced decrease in tyrosine phosphorylation for long-term as opposed to short-term disease survivors, for which 26 of 76 selected peptides were significantly (p < 0.01, FDR < 3%) more inhibited in the long-term survivors. Using statistical class prediction analysis, we obtained a 'prognostic-signature' for long- versus short-term disease survivors and correctly predicted the survival status of 73% of our patients. Our translational approach may assist clinical disease management after surgical resection and may help to direct patients for an optimal treatment strategy

A strategy to analyse activity-based profiling of tyrosine kinase substrates in OCT-embedded lung cancer tissue

The use of optimal cutting temperature (OCT) medium has served to improve the long-term preservation of surgical tissue specimens. Unfortunately, the presence of polymers in OCT has been found to generate signal interference in proteomic-based techniques. Indeed the presence of OCT medium in tissue lysates precludes the analysis of activity based proteomic profiles obtained from lung adenocarcinoma (LuAdCa) resection specimens. In order to probe this question further tissue lysates were prepared from 47 lung non-neoplastic and tumour, node, metastasis (TNM) stage 1 LuAdCa resection specimens embedded with or without OCT, and data of activity based multiplex profiles of protein tyrosine kinase peptide substrates were obtained. We found that changes in overall phosphorylation level coincided with the use of OCT and subsequently developed an OCT per peptide median correcting strategy by performing median centering on the values of each peptide. Application of this post-analytical strategy not only can identify changes in kinase activity but can also assist in identifying novel targets for therapeutic intervention against LuAdCa

Differentiating Benign from Malignant Thyroid Tumors by Kinase Activity Profiling and Dabrafenib BRAF V600E Targeting

Differentiated non-medullary thyroid cancer (NMTC) can be effectively treated by surgery followed by radioactive iodide therapy. However, a small subset of patients shows recurrence due to a loss of iodide transport, a phenotype frequently associated with BRAF V600E mutations. In theory, this should enable the use of existing targeted therapies specifically designed for BRAF V600E mutations. However, in practice, generic or specific drugs aimed at molecular targets identified by next generation sequencing (NGS) are not always beneficial. Detailed kinase profiling may provide additional information to help improve therapy success rates. In this study, we therefore investigated whether serine/threonine kinase (STK) activity profiling can accurately classify benign thyroid lesions and NMTC. We also determined whether dabrafenib (BRAF V600E-specific inhibitor), as well as sorafenib and regorafenib (RAF inhibitors), can differentiate BRAF V600E from non-BRAF V600E thyroid tumors. Using 21 benign and 34 malignant frozen thyroid tumor samples, we analyzed serine/threonine kinase activity using PamChip®peptide microarrays. An STK kinase activity classifier successfully differentiated malignant (26/34; 76%) from benign tumors (16/21; 76%). Of the kinases analyzed, PKC (theta) and PKD1 in particular, showed differential activity in benign and malignant tumors, while oncocytic neoplasia or Graves’ disease contributed to erroneous classifications. Ex vivo BRAF V600E-specific dabrafenib kinase inhibition identified 6/92 analyzed peptides, capable of differentiating BRAF V600E-mutant from non-BRAF V600E papillary thyroid cancers (PTCs), an effect not seen with the generic inhibitors sorafenib and regorafenib. In conclusion, STK activity profiling differentiates benign from malignant thyroid tumors and generates unbiased hypotheses regarding differentially active kinases. This approach can serve as a model to select novel kinase inhibitors based on tissue analysis of recurrent thyroid and other cancers