Mass spectrometry-based phosphoproteomics of cancer cell and tissue lysates provides insight in aberrantly activated signaling pathways and potential drug targets. For improved understanding of individual patient's tumor biology and to allow selection of tyrosine kinase inhibitors in individual patients, phosphoproteomics of small clinical samples should be feasible and reproducible. We aimed to scale down a pTyr-phosphopeptide enrichment protocol to biopsy-level protein input and assess reproducibility and applicability to tumor needle biopsies. To this end, phosphopeptide immunoprecipitation using anti-phosphotyrosine beads was performed using 10, 5 and 1mg protein input from lysates of colorectal cancer (CRC) cell line HCT116. Multiple needle biopsies from 7 human CRC resection specimens were analyzed at the 1mg-level. The total number of phosphopeptides captured and detected by LC-MS/MS ranged from 681 at 10mg input to 471 at 1mg HCT116 protein. ID-reproducibility ranged from 60.5% at 10mg to 43.9% at 1mg. Per 1mg-level biopsy sample, >200 phosphopeptides were identified with 57% ID-reproducibility between paired tumor biopsies. Unsupervised analysis clustered biopsies from individual patients together and revealed known and potential therapeutic targets.
Significance: This study demonstrates the feasibility of label-free pTyr-phosphoproteomics at the tumor biopsy level based on reproducible analyses using 1mg of protein input. The considerable number of identified phosphopeptides at this level is attributed to an effective down-scaled immuno-affinity protocol as well as to the application of ID propagation in the data processing and analysis steps. Unsupervised cluster analysis reveals patient-specific profiles. Together, these findings pave the way for clinical trials in which pTyr-phosphoproteomics will be performed on pre- and on-treatment biopsies. Such studies will improve our understanding of individual tumor biology and may enable future pTyr-phosphoproteomics-based personalized medicine.
Keywords: Cancer; MS/MS; Personalized medicine; Phosphoproteomics; Phosphotyrosine signaling; Targeted therapy; Treatment selection.
Copyright © 2017. Published by Elsevier B.V.