A mouse xenograft model to the fore in a GI tract-wide search for cancer biomarkers

Introduction

Biomarkers are physiological indicators of diseased tissue and have value in diagnosis, prognosis and in the evaluation of a treatment regimen. The larger goal of this project is to identify and validate serum-based N-Glycoprotein markers of human GI cancers early enough for a treatment to be effected successfully. N-Glycosylation is frequently indicative of perturbations in cellular physiology and this makes the glycosylated proteins clinically valuable. The biomarker discovery phase is being performed in a mouse xenograft model, for a couple of reasons. First, the mouse has a blood volume that is several times lesser than a human‘s and this makes detection of a marker that much easier, and second, because any human protein observed in the mouse serum necessarily comes from the tumor.

Materials/methods

Cell-culture and Xenograft- Cancer cell-lines were purchased from DSMZ (Germany) and cultured as per the company‘s instructions. These were then grafted in immunocompromised (SCID) mice and allowed to grow. When the xenograft/tumors reached a size of approximately 1 cubic cm, the mice were sacrificed, and blood and tumor tissue collected for analysis of protein, RNA and DNA. Purification of N-Glycopeptides, LC-MS/MS and computational data analysis- N-Glycopeptides are isolated from mouse serum using a solid-phase purification procedure (Solid-phase extraction of N-glycoproteins, Tian et al, 2007, Nature Protocols). The N-Glycopeptides are then separated by liquid chromatography and analyzed in an Orbitrap Fusion mass spectrometer (Thermo). The peptide database search is performed by software developed in-house and human N-Glycopeptide identified. Mutations in the identified peptides are also identified using the same software.

Results and conclusions

We have xenografted 30 different cell lines and some patient derived tumors representing a range of cancers of the GI-tract, in SCID mice. Multiple cell-lines from each cancer type have been chosen. Sera from these mice have been analyzed using an established proteomic workflow. Preliminary analyses have yielded several biomarkers, some of which are novel and some of which have been previously reported. The presence of two of these N-glycoproteins in a recently published diagnostic signature attests to the validity of our workflow. It will be interesting to see if any of the biomarkers are representative of more than one type of cancer. Biomarker candidates that are promising will be measured in patient serum using a mass-spectrometric procedure called SRM. The candidates will also be analyzed for the presence of sequence alterations using a software suite developed inhouse.