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Evaluation of a tyrosine kinase peptide microarray for tyrosine kinase inhibitor therapy selection in cancer.

ABSTRACT: Personalized cancer medicine aims to accurately predict the response of individual patients to targeted therapies, including tyrosine kinase inhibitors (TKIs). Clinical implementation of this concept requires a robust selection tool. Here, using both cancer cell lines and tumor tissue from patients, we evaluated a high-throughput tyrosine kinase peptide substrate array to determine its readiness as a selection tool for TKI therapy. We found linearly increasing phosphorylation signal intensities of peptides representing kinase activity along the kinetic curve of the assay with 7.5-10??g of lysate protein and up to 400??M adenosine triphosphate (ATP). Basal kinase activity profiles were reproducible with intra- and inter-experiment coefficients of variation of <15% and <20%, respectively. Evaluation of 14 tumor cell lines and tissues showed similar consistently high phosphorylated peptides in their basal profiles. Incubation of four patient-derived tumor lysates with the TKIs dasatinib, sunitinib, sorafenib and erlotinib primarily caused inhibition of substrates that were highly phosphorylated in the basal profile analyses. Using recombinant Src and Axl kinase, relative substrate specificity was demonstrated for a subset of peptides, as their phosphorylation was reverted by co-incubation with a specific inhibitor. In conclusion, we demonstrated robust technical specifications of this high-throughput tyrosine kinase peptide microarray. These features required as little as 5-7??g of protein per sample, facilitating clinical implementation as a TKI selection tool. However, currently available peptide substrates can benefit from an enhancement of the differential potential for complex samples such as tumor lysates. We propose that mass spectrometry-based phosphoproteomics may provide such an enhancement by identifying more discriminative peptides.

SUBMITTER: Labots M

PROVIDER: S-EPMC5192072 | biostudies-literature | 2016 Dec

REPOSITORIES: biostudies-literature

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Evaluation of a tyrosine kinase peptide microarray for tyrosine kinase inhibitor therapy selection in cancer.

Labots Mariette M Gotink Kristy J KJ Dekker Henk H Azijli Kaamar K van der Mijn Johannes C JC Huijts Charlotte M CM Piersma Sander R SR Jiménez Connie R CR Verheul Henk M W HM

Experimental & molecular medicine 20161216 12

Personalized cancer medicine aims to accurately predict the response of individual patients to targeted therapies, including tyrosine kinase inhibitors (TKIs). Clinical implementation of this concept requires a robust selection tool. Here, using both cancer cell lines and tumor tissue from patients, we evaluated a high-throughput tyrosine kinase peptide substrate array to determine its readiness as a selection tool for TKI therapy. We found linearly increasing phosphorylation signal intensities ...[more]

PMID: 27980342

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Project description:The Lung Adjuvant Cisplatin Evaluation (LACE) meta-analysis and the meta-analysis of individual participant data reported by non-small cell lung cancer (NSCLC) Meta-analysis Collaborative Group in neo-adjuvant setting validated respectively that adjuvant and neoadjuvant chemotherapy would significantly improve overall survival (OS) and recurrence-free survival for resectable NSCLC. However, chemotherapy has reached a therapeutic plateau. It has been confirmed that epidermal growth factor receptor-tyrosine kinase inhibitor (EGFR-TKI) targeting therapy provides a dramatic response to patients with advanced EGFR-mutation positive NSCLC. Researchers have paid more attention to exploring applications of TKIs to early resectable NSCLCs. Several studies on adjuvant TKI treatment concluded its safety and feasibility. But there existed certain limitations of these studies as inference factors to interpret data accurately: the BR19 study recruited patients among which almost 52% had stage IB and only 15 (3.0%, 15/503) had been confirmed with EGFR-mutant type; retrospective studies performed at Memorial Sloan Kettering Cancer Center (MSKCC) selected EGFR mutant-type NSCLC patients but couldn't avoid inherent defects inside retrospective researches; the RADIANT study revised endpoints from targeting at EGFR immunohistochemistry (IHC)+ and/or fluorescence in situ hybridization (FISH)+ mutation to only EGFR IHC+ mutation, leading to selective bias; despite that the SELECT study validated efficacy of adjuvant TKI and second round of TKI after resistance occurred, a single-arm clinical trial is not that persuasive in the absence of comparison with chemotherapy. Taking all these limitations into account, CTONG1104 in China and IMPACT in Japan have been conducted and recruiting patients to offer higher level of evidences to explore efficacy of preoperative TKI therapy for early resectable EGFR mutation positive NSCLC patients (confirmed by pathological results of tumor tissue or lymph node biopsy). On the other hand, case reports and several phase II clinical trials with small sample size tried to elbow their way on respect of preoperative TKI treatment and advised that TKI tended to improve response rate. However, no data on survival rate was present. The first phase II study of biomarker-guided neoadjuvant therapy for stage IIIA-N2 NSCLC patients stratified by EGFR mutation status, sponsored by CSLC0702, showed erlotinib tended to improve response rate, but failed to show benefits of disease-free survival (DFS) or OS. Subsequently, CTONG1103 was designed to investigate efficacy of erlotinib vs. combination of gemcitabine/cisplatin (GC) as neoadjuvant treatment in stage IIIA-N2 NSCLC with sensitizing EGFR mutation in exon 19 or 21. All these ongoing trials should be worthy of our expect to provide convincing evidences for customized therapy for patients with resectable NSCLC.

Dataset Information

Evaluation of a tyrosine kinase peptide microarray for tyrosine kinase inhibitor therapy selection in cancer.

Publications

Evaluation of a tyrosine kinase peptide microarray for tyrosine kinase inhibitor therapy selection in cancer.

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