iTRAQ-based Proteomics Profiling Reveals Increased Metabolic Activity and Cellular Cross-talk in Angiogenic Compared with Invasive Glioblastoma Phenotype

Malignant gliomas (glioblastoma multiforme) have a poor prognosis with an average patient survival under current treatment regimens ranging between 12 and 14 months. The tumors are characterized by rapid cell growth, extensive neovascularization, and diffuse cellular infiltration of normal brain structures. We have developed a human glioblastoma xenograft model in nude rats that is characterized by a highly infiltrative non-angiogenic phenotype. Upon serial transplantation this phenotype will develop into a highly angiogenic tumor. Thus, we have developed an animal model where we are able to establish two characteristic tumor phenotypes that define human glioblastoma (i.e. diffuse infiltration and high neovascularization). Here we aimed at identifying potential biomarkers expressed by the non-angiogenic and the angiogenic phenotypes and elucidating the molecular pathways involved in the switch from invasive to angiogenic growth. Focusing on membrane-associated proteins, we profiled protein expression during the progression from an invasive to an angiogenic phenotype by analyzing serially transplanted glioma xenografts in rats. Applying isobaric peptide tagging chemistry (iTRAQ) combined with two-dimensional LC and MALDI-TOF/TOF mass spectrometry, we were able to identify several thousand proteins in membrane-enriched fractions of which 1460 were extracted as quantifiable proteins (isoform- and species-specific and present in more than one sample). Known and novel candidate proteins were identified that characterize the switch from a non-angiogenic to a highly angiogenic phenotype. The robustness of the data was corroborated by extensive bioinformatics analysis and by validation of selected proteins on tissue microarrays from xenograft and clinical gliomas. The data point to enhanced intercellular cross-talk and metabolic activity adopted by tumor cells in the angiogenic compared with the non-angiogenic phenotype. In conclusion, we describe molecular profiles that reflect the change from an invasive to an angiogenic brain tumor phenotype. The identified proteins could be further exploited as biomarkers or therapeutic targets for malignant gliomas.Glioblastoma multiforme (GBM)¹ is the prevalent and most fatal brain tumor in adults with an average patient survival time between 12 and 14 months under current treatment regimens. Invasion and angiogenesis are two defining hallmarks of GBM that are largely responsible for the aggressive nature of the disease (1). Invasion is likely triggered by signals that prompt tumor cells to egress from the tumor mass, including those that are activated by an acidic and hypoxic environment (e.g. hypoxia-inducible factor) (2). These highly infiltrative glioma cells escape neurosurgical resection and are the seeds for tumor recurrence. Oxygen limitation in the tumor microenvironment is also responsible for the active recruitment of new blood vessels from preexisting vessels, a process termed angiogenesis. Absence of angiogenesis is considered a rate-limiting factor in solid tumors. Although high grade gliomas show extensive infiltration of the normal brain they are also among the neoplasms with the highest degree of vascularization (3–5). Antiangiogenic treatment is considered a promising therapeutic strategy against malignant brain tumors and is currently being evaluated in clinical trials (6).In solid tumors the angiogenic switch is thought to occur when the balance between proangiogenic and antiangiogenic molecules is shifted in favor of angiogenesis, permitting rapid tumor growth and subsequent development of invasive and metastatic properties (7). Thus, aggressive tumor growth depends on a successful adaptation of the tumor cells to the host microenvironment. In brain tumors no biomarkers are currently available that define different cell populations within human GBMs (for instance tumor cells that show infiltrative growth and those that trigger angiogenesis) or that predict the propensity of low grade (non-angiogenic) gliomas to develop into malignant angiogenic gliomas. We have recently generated a xenograft model for human GBM that displays a highly invasive phenotype and stem cell characteristics (8). By serial transplantation in nude rats new cell clones eventually develop that generate a more rapidly growing aggressive, angiogenesis-dependent phenotype. The transition to an angiogenic phenotype is accompanied by a reduced infiltrative growth (8). Thus, we are able to initiate two distinct phenotypes from human GBMs that classify their growth and progression. Our model is extremely useful for identifying mechanisms causing the switch from angiogenesis-independent to angiogenesis-dependent tumor growth.This work was aimed at identifying cell membrane markers and molecular pathways that characterize the two phenotypes and may underlie the angiogenic switch. Such markers may represent potential therapeutic targets toward specific cellular subsets within GBMs. Here we applied iTRAQ peptide labeling on membrane-enriched tumor fractions followed by MALDI-TOF/TOF protein identification and bioinformatics analysis to quantify large scale species-specific protein expression over four consecutive generations of the glioma xenograft model.In a search for disease biomarkers, there has been a rapid development of quantitative protein expression technologies including isobaric peptide tagging (iTRAQ) combined with multidimensional LC and MS/MS analysis (9). This approach allows for sample multiplexing (currently 4- or 8-plex at the time). iTRAQ is particularly powerful when applied on a subfraction of the proteome, thereby increasing the possibility of identifying less abundant proteins (10). Because more than a third of all known biomarkers as well as more than two-thirds of known and potential antitumor protein targets are membrane-related proteins (11–14), we focused on membrane-enriched fractions of the tumor xenografts. In four different iTRAQ experiments we were able to identify over 7000 (redundant) proteins of which 1460 proteins were extracted based on quantifiable and species-specific expression. Correspondence analysis and unsupervised cluster analysis confirmed consistent protein expression profiles in the different xenograft phenotypes generated from different patient samples. The expression of a selection of identified candidates was confirmed by immunohistochemical methods on tissue microarrays (TMAs) from a large number of xenograft tumors and patient gliomas. The differentially expressed proteins identified in the two phenotypes represent unique candidate biomarkers that may represent novel therapeutic targets in GBMs. The information generated also provides novel insight into the molecular networks governing the infiltrative and the angiogenic tumor properties and reveals new mechanisms involved in the angiogenic switch in GBMs.