Identification of Glioma Neovascularization-related Proteins by Using MALDI-FTMS and Nano-LC Fractionation to Microdissected Tumor Vessels

Pericytes promote abnormal tumor angiogenesis in a rat RG2 glioma model

In glioma angiogenesis, tumor vessels cause morphological and functional abnormalities associated with malignancy and tumor progression. We hypothesized that certain structural changes or scantiness of functional pericytes may be involved in the formation of dysfunctional blood vessels in gliomas. In this study, we performed morphological examinations to elucidate the possible involvement of pericytes in brain tumor vessel abnormalities using a rat RG2 glioma model. After implantation of RG2 glioma cells in the syngeneic rat brain, gliomas were formed as early as day 7. In immunohistochemical examinations, desmin-positive pericytes, characterized by morphological abnormalities, were abundantly found on leaky vessels, as assessed by extravasation of lectin and high-molecular-weight dextrans. Interestingly, desmin-positive pericytes seemed to be characteristic of gliomas in rats. These pericytes were also found to express heat-shock protein 47, which plays an important role in the formation of the basement membrane, suggesting that RG2 pericytes promoted angiogenesis by producing basement membrane as a scaffold for newly forming blood vessels and caused functional abnormalities. We concluded that RG2 pericytes may be responsible for abnormal tumor angiogenesis lacking the functional ability to maintain the blood-brain barrier.

3-D imaging mass spectrometry of protein distributions in mouse Neurofibromatosis 1 (NF1)-associated optic glioma

Neurofibromatosis type 1 (NF1) is a common neurogenetic disorder, in which affected individuals develop tumors of the nervous system. Children with NF1 are particularly prone to brain tumors (gliomas) involving the optic pathway that can result in impaired vision. Since tumor formation and expansion requires a cooperative tumor microenvironment, it is important to identify the cellular and acellular components associated with glioma development and growth. In this study, we used 3-D matrix assisted laser desorption ionization imaging mass spectrometry (MALDI IMS) to measure the distributions of multiple molecular species throughout optic nerve tissue in mice with and without glioma, and to explore their spatial relationships within the 3-D volume of the optic nerve and chiasm. 3-D IMS studies often involve extensive workflows due to the high volume of sections required to generate high quality 3-D images. Herein, we present a workflow for 3-D data acquisition and volume reconstruction using mouse optic nerve tissue. The resulting 3-D IMS data yield both molecular similarities and differences between glioma-bearing and wild-type (WT) tissues, including protein distributions localizing to different anatomical subregions.

BIOLOGICAL SIGNIFICANCE

The current work addresses a number of challenges in 3-D MALDI IMS, driven by the small size of the mouse optic nerve and the need to maintain consistency across multiple 2-D IMS experiments. The 3-D IMS data yield both molecular similarities and differences between glioma-bearing and wild-type (WT) tissues, including protein distributions localizing to different anatomical subregions, which could then be targeted for identification and related back to the biology observed in gliomas of the optic nerve.

Heat Shock Protein 47 Promotes Glioma Angiogenesis

Heat shock protein 47 (HSP47) is a collagen-binding protein, which has been recently found to express in glioma vessels. However, the expression profile of HSP47 in glioma patients and the underlying mechanisms of HSP47 on glioma angiogenesis are not fully explored. In the current study, we found that expression of HSP47 in glioma vessels was correlated with the grades of gliomas. HSP47 knockdown by siRNAs significantly decreased cell viability in vitro and tumor volume in vivo; moreover, it reduced the microvessel density (MVD) by CD31 immunohistochemistry in vivo. HSP47 knockdown significantly inhibited tube formation, invasion and proliferation of human umbilical vein endothelial cells (HUVECs). Furthermore, conditional medium derived from HSP47 knockdown cells significantly inhibited HUVECs tube formation and migration, while it increased chemosensitivity of HUVECs cells to Avastin. Silencing of HSP47 decreased VEGF expression in glioma cells consistently, and reduced glioma vasculature. Furthermore, HSP47 promoted glioma angiogenesis through HIF1α-VEGFR2 signaling. The present study demonstrates that HSP47 promotes glioma angiogenesis and highlights the importance of HSP47 as an attractive therapeutic target of GBM.

Control of vascular permeability by adhesion molecules

Vascular permeability is a vital function of the circulatory system that is regulated in large part by the limited flux of solutes, water, and cells through the endothelial cell layer. One major pathway through this barrier is via the inter-endothelial junction, which is driven by the regulation of cadherin-based adhesions. The endothelium also forms attachments with surrounding proteins and cells via 2 classes of adhesion molecules, the integrins and IgCAMs. Integrins and IgCAMs propagate activation of multiple downstream signals that potentially impact cadherin adhesion. Here we discuss the known contributions of integrin and IgCAM signaling to the regulation of cadherin adhesion stability, endothelial barrier function, and vascular permeability. Emphasis is placed on known and prospective crosstalk signaling mechanisms between integrins, the IgCAMs- ICAM-1 and PECAM-1, and inter-endothelial cadherin adhesions, as potential strategic signaling nodes for multipartite regulation of cadherin adhesion.

Collagen peptides in urine: a new promising biomarker for the detection of colorectal liver metastases

Introduction

For both patients and the outpatient clinic the frequent follow-up visits after a resection of colorectal cancer (CRC) are time consuming and due to large patient numbers expensive. Therefore it is important to develop an effective non-invasive test for the detection of colorectal liver metastasis (CRLM) which could be used outside the hospital. The urine proteome is known to provide detailed information for monitoring changes in the physiology of humans. Urine collection is non-invasive and urine naturally occurring peptides (NOPs) have the advantage of being easily accessible without labour-intensive sample preparation. These advantages make it potentially useful for a quick and reliable application in clinical settings. In this study, we will focus on the identification and validation of urine NOPs to discriminate patients with CRLM from healthy controls.

Materials and Methods

Urine samples were collected from 24 patients with CRLM and 25 healthy controls. In the first part of the study, samples were measured with a nano liquid chromatography (LC) system (Thermo Fisher Scientific, Germaring, Germany) coupled on-line to a hybrid linear ion trap/Orbitrap mass spectrometer (LTQ-Orbitrap-XL, Thermo Fisher Scientific, Bremen, Germany). A discovery set was used to construct the model and consecutively the validation set, being independent from the discovery set, to check the acquired model. From the peptides which were selected, multiple reaction monitoring (MRM's) were developed on a UPLC-MS/MS system.

Results

Seven peptides were selected and applied in a discriminant analysis a sensitivity of 84.6% and a specificity of 92.3% were established (Canonical correlation:0.797, Eigenvalue:1.744, F:4.49, p:0.005). The peptides AGPP(-OH)GEAGKP(-OH)GEQGVP(-OH)GDLGA P(-OH)GP and KGNSGEP(-OH)GAPGSKGDTGAKGEP(-OH)GPVG were selected for further quantitative analysis which showed a sensitivity of 88% and a specificity of 88%.

Conclusion

Urine proteomic analysis revealed two very promising peptides, both part from collagen type 1, AGPP(-OH)GEAGKP(-OH)GEQGVP(-OH)GDLGAP(-OH)GP and KGNSGEP(-OH)GAPGSKGDTGAKGEP(-OH)GPVG which could detect CRLM in a non-invasive manner.

Proteomic analysis of glioblastomas: what is the best brain control sample?

Glioblastoma (GB) is the most frequent and aggressive tumor of the central nervous system. There is currently growing interest in proteomic studies of GB, particularly with the aim of identifying new prognostic or therapeutic response markers. However, comparisons between different proteomic analyses of GB have revealed few common differentiated proteins. The types of control samples used to identify such proteins may in part explain the different results obtained. We therefore tried to determine which control samples would be most suitable for GB proteomic studies. We used an isotope-coded protein labeling (ICPL) method followed by mass spectrometry to reveal and compare the protein patterns of two commonly used types of control sample: GB peritumoral brain zone samples (PBZ) from six patients and epilepsy surgery brain samples (EB) pooled from three patients. The data obtained were processed using AMEN software for network analysis. We identified 197 non-redundant proteins and 35 of them were differentially expressed. Among these 35 differentially expressed proteins, six were over-expressed in PBZ and 29 in EB, showing different proteomic patterns between the two samples. Surprisingly, EB appeared to display a tumoral-like expression pattern in comparison to PBZ. In our opinion, PBZ may be more appropriate control sample for GB proteomic analysis.

BIOLOGICAL SIGNIFICANCE

This manuscript describes an original study in which we used an isotope-coded protein labeling method followed by mass spectrometry to identify and compare the protein patterns in two types of sample commonly used as control for glioblastoma (GB) proteomic analysis: peritumoral brain zone and brain samples obtained during surgery for epilepsy. The choice of control samples is critical for identifying new prognostic and/or diagnostic markers in GB.

Candidate biomarker discovery for angiogenesis by automatic integration of Orbitrap MS1 spectral- and X!Tandem MS2 sequencing information

Candidate protein biomarker discovery by full automatic integration of Orbitrap full MS1 spectral peptide profiling and X!Tandem MS2 peptide sequencing is investigated by analyzing mass spectra from brain tumor samples using Peptrix. Potential protein candidate biomarkers found for angiogenesis are compared with those previously reported in the literature and obtained from previous Fourier transform ion cyclotron resonance (FT-ICR) peptide profiling. Lower mass accuracy of peptide masses measured by Orbitrap compared to those measured by FT-ICR is compensated by the larger number of detected masses separated by liquid chromatography (LC), which can be directly linked to protein identifications. The number of peptide sequences divided by the number of unique sequences is 9248/6911 ≈ 1.3. Peptide sequences appear 1.3 times redundant per up-regulated protein on average in the peptide profile matrix, and do not seem always up-regulated due to tailing in LC retention time (40%), modifications (40%) and mass determination errors (20%). Significantly up-regulated proteins found by integration of X!Tandem are described in the literature as tumor markers and some are linked to angiogenesis. New potential biomarkers are found, but need to be validated independently. Eventually more proteins could be found by actively involving MS2 sequence information in the creation of the MS1 peptide profile matrix.

Small hydrophobic protein of human metapneumovirus does not affect virus replication and host gene expression in vitro

Human metapneumovirus (HMPV) encodes a small hydrophobic (SH) protein of unknown function. HMPV from which the SH open reading frame was deleted (HMPVΔSH) was viable and displayed similar replication kinetics, cytopathic effect and plaque size compared with wild type HMPV in several cell-lines. In addition, no differences were observed in infection efficiency or cell-to-cell spreading in human primary bronchial epithelial cells (HPBEC) cultured at an air-liquid interphase. Host gene expression was analyzed in A549 cells infected with HMPV or HMPVΔSH using microarrays and mass spectrometry (MS) based techniques at multiple time points post infection. Only minor differences were observed in mRNA or protein expression levels. A possible function of HMPV SH as apoptosis blocker, as proposed for several members of the family Paramyxoviridae, was rejected based on this analysis. So far, a clear phenotype of HMPV SH deletion mutants in vitro at the virus and host levels is absent.

Transcriptional profiling of human glioblastoma vessels indicates a key role of VEGF-A and TGFβ2 in vascular abnormalization

Glioblastoma are aggressive astrocytic brain tumours characterized by microvascular proliferation and an abnormal vasculature, giving rise to brain oedema and increased patient morbidity. Here, we have characterized the transcriptome of tumour-associated blood vessels and describe a gene signature clearly associated with pleomorphic, pathologically altered vessels in human glioblastoma (grade IV glioma). We identified 95 genes differentially expressed in glioblastoma vessels, while no significant differences in gene expression were detected between vessels in non-malignant brain and grade II glioma. Differential vascular expression of ANGPT2, CD93, ESM1, ELTD1, FILIP1L and TENC1 in human glioblastoma was validated by immunohistochemistry, using a tissue microarray. Through qPCR analysis of gene induction in primary endothelial cells, we provide evidence that increased VEGF-A and TGFβ2 signalling in the tumour microenvironment is sufficient to invoke many of the changes in gene expression noted in glioblastoma vessels. Notably, we found an enrichment of Smad target genes within the distinct gene signature of glioblastoma vessels and a significant increase of Smad signalling complexes in the vasculature of human glioblastoma in situ. This indicates a key role of TGFβ signalling in regulating vascular phenotype and suggests that, in addition to VEGF-A, TGFβ2 may represent a new target for vascular normalization therapy.

The challenge of gene expression profiling in heterogeneous clinical samples

Almost all samples used in tumor biology, such as tissues and bodily fluids, are heterogeneous, i.e., consist of different cell types. Evaluating the degree of heterogeneity in samples can increase our knowledge on processes such as clonal selection and metastasis. In addition, generating expression profiles from specific sub populations of cells can reveal their distinct functions. Tissue heterogeneity also poses a challenge, as it can confound the interpretation of gene expression data. This chapter will (1) give a brief overview on how heterogeneity may influence gene expression profiling data and (2) describe the methods that are currently available to assess transcriptional biomarkers in a heterogeneous cell population.

Identification of human serum peptides in fourier transform ion cyclotron resonance precision profiles

The continuous efforts to find new prognostic or diagnostic biomarkers have stimulated the use of mass spectrometry (MS) profiles in a clinical setting. In the early days (about one decade ago), a single low-resolution mass spectrum derived from an individual's body fluid was used for comparative studies. However, a peptide profile of a complex mixture is most informative when recorded on an ultrahigh resolution instrument such as a Fourier transform ion cyclotron resonance (FTICR) mass spectrometer. In this study we show the benefits of the ultrahigh resolving power and the high mass accuracy and precision provided by an FTICR mass spectrometer equipped with a 15-tesla magnet. The ultrahigh-resolution data not only allow assignment of fragment ions with high charge states (4+, 5+) but also enhance confidence of human serum peptide identifications from tandem MS experiments. This is exemplified with collision-induced dissociation (CID) and electron transfer dissociation (ETD) data of middle-down-sized endogenous or protein-breakdown peptides that are of interest in biomarker discovery studies.

A proteome comparison between physiological angiogenesis and angiogenesis in glioblastoma

The molecular pathways involved in neovascularization of regenerating tissues and tumor angiogenesis resemble each other. However, the regulatory mechanisms of neovascularization under neoplastic circumstances are unbalanced leading to abnormal protein expression patterns resulting in the formation of defective and often abortive tumor vessels. Because gliomas are among the most vascularized tumors, we compared the protein expression profiles of proliferating vessels in glioblastoma with those in tissues in which physiological angiogenesis takes place. By using a combination of laser microdissection and LTQ Orbitrap mass spectrometry comparisons of protein profiles were made. The approach yielded 29 and 12 differentially expressed proteins for glioblastoma and endometrium blood vessels, respectively. The aberrant expression of five proteins, i.e. periostin, tenascin-C, TGF-beta induced protein, integrin alpha-V, and laminin subunit beta-2 were validated by immunohistochemistry. In addition, pathway analysis of the differentially expressed proteins was performed and significant differences in the usage of angiogenic pathways were found. We conclude that there are essential differences in protein expression profiles between tumor and normal physiological angiogenesis.

Proteomics of gliomas: initial biomarker discovery and evolution of technology

Gliomas are a group of aggressive brain tumors that diffusely infiltrate adjacent brain tissues, rendering them largely incurable, even with multiple treatment modalities and agents. Mostly asymptomatic at early stages, they present in several subtypes with astrocytic or oligodendrocytic features and invariably progress to malignant forms. Gliomas are difficult to classify precisely because of interobserver variability during histopathologic grading. Identifying biological signatures of each glioma subtype through protein biomarker profiling of tumor or tumor-proximal fluids is therefore of high priority. Such profiling not only may provide clues regarding tumor classification but may identify clinical biomarkers and pathologic targets for the development of personalized treatments. In the past decade, differential proteomic profiling techniques have utilized tumor, cerebrospinal fluid, and plasma from glioma patients to identify the first candidate diagnostic, prognostic, predictive, and therapeutic response markers, highlighting the potential for glioma biomarker discovery. The number of markers identified, however, has been limited, their reproducibility between studies is unclear, and none have been validated for clinical use. Recent technological advancements in methodologies for high-throughput profiling, which provide easy access, rapid screening, low sample consumption, and accurate protein identification, are anticipated to accelerate brain tumor biomarker discovery. Reliable tools for biomarker verification forecast translation of the biomarkers into clinical diagnostics in the foreseeable future. Herein we update the reader on the recent trends and directions in glioma proteomics, including key findings and established and emerging technologies for analysis, together with challenges we are still facing in identifying and verifying potential glioma biomarkers.

Influence of the tumor microenvironment on angiogenesis

It is becoming increasingly recognized that the host microenvironment is essential for regulating tumor cell behavior. The cellular stromal compartment can modulate angiogenesis either directly through enhanced secretion of pro-angiogenic factors or reduced secretion of antiangiogenic factors, or indirectly by modulating the surrounding extracellular matrix. Control of angiogenesis represents a critical step in cancer progression and is a potential therapeutic target. This article focuses on the role of the tumor microenvironment in the control of angiogenesis and how dissection of the molecular interactions may enhance prognostic and predictive power and facilitate therapeutic targeting.

Label-free peptide profiling of Orbitrap™ full mass spectra

BACKGROUND

We developed a new version of the open source software package Peptrix that can yet compare large numbers of Orbitrap™ LC-MS data. The peptide profiling results for Peptrix on MS1 spectra were compared with those obtained from a small selection of open source and commercial software packages: msInspect, Sieve™ and Progenesis™. The properties compared in these packages were speed, total number of detected masses, redundancy of masses, reproducibility in numbers and CV of intensity, overlap of masses, and differences in peptide peak intensities. Reproducibility measurements were taken for the different MS1 software applications by measuring in triplicate a complex peptide mixture of immunoglobulin on the Orbitrap™ mass spectrometer. Values of peptide masses detected from the high intensity peaks of the MS1 spectra by peptide profiling were verified with values of the MS2 fragmented and sequenced masses that resulted in protein identifications with a significant score.

FINDINGS

Peptrix finds about the same number of peptide features as the other packages, but peptide masses are in some cases approximately 5 to 10 times less redundant present in the peptide profile matrix. The Peptrix profile matrix displays the largest overlap when comparing the number of masses in a pair between two software applications. The overlap of peptide masses between software packages of low intensity peaks in the spectra is remarkably low with about 50% of the detected masses in the individual packages. Peptrix does not differ from the other packages in detecting 96% of the masses that relate to highly abundant sequenced proteins. MS1 peak intensities vary between the applications in a non linear way as they are not processed using the same method.

CONCLUSIONS

Peptrix is capable of peptide profiling using Orbitrap™ files and finding differential expressed peptides in body fluid and tissue samples. The number of peptide masses detected in Orbitrap™ files can be increased by using more MS1 peptide profiling applications, including Peptrix, since it appears from the comparison of Peptrix with the other applications that all software packages have likely a high false negative rate of low intensity peptide peaks (missing peptides).

Overexpression of Colligin 2 in Glioma Vasculature is Associated with Overexpression of Heat Shock Factor 2

In previous studies we found expression of the protein colligin 2 (heat shock protein 47 (HSP47), SERPINH1) in glioma neovasculature while not in normal brain tissue. Generally, the regulation of heat shock gene expression in eukaryotes is mediated by heat shock factors (HSF). In mammals, three heat shock transcription factors, HSF-1, -2, and -4, have been isolated. Here we investigated the relation between the expression of colligin 2 and these heat shock factors at the mRNA level using real-time reverse transcriptase PCR (qRT-PCR) in different grades of astrocytic tumorigenesis, viz., low-grade glioma and glioblastoma. Endometrium samples, representing physiological angiogenesis, were included as controls. Since colligin 2 is a chaperon for collagens, the gene expression of collagen I (COL1A1) was also investigated. The blood vessel density of the samples was monitored by expression of the endothelial marker CD31 (PECAM1). Because NG2-immunopositive pericytic cells are involved in glioma neovascularization, the expression of NG2 (CSPG4) was also measured.

We demonstrate overexpression of HSF2 in both stages of glial tumorigenesis (reaching significance only in low-grade glioma) and also minor elevated levels of HSF1 as compared to normal brain. There were no differences in expression of HSF4 between low-grade glioma and normal brain while HSF4 was downregulated in glioblastoma. In the endometrium samples, none of the HSFs were upregulated. In the low-grade gliomas SERPINH appeared to be slightly overexpressed with a parallel 4-fold upregulation of COL1A1, while in glioblastoma there was over 5-fold overexpression of SERPINH1 and more than 150-fold overexpression of COL1A1. In both the lowgrade gliomas and the glioblastomas overexpression of CSPG4 was found and overexpression of PECAM1 was only found in the latter. Our data suggest that the upregulated expression of colligin 2 in glioma is accompanied by upregulation of COL1A1, CSPG4, HSF2 and to a lesser extent, HSF1. Further studies will unravel the association of these factors with colligin 2 expression, possibly leading to keys for therapeutic intervention.

Protein analysis of laser capture micro-dissected tissues revealed cell-type specific biological functions in developing barley grains

Both the nucellar projection (NP) and endosperm transfer cells (ETC) of the developing barley grain (harvested 8 days after flowering) were isolated by laser capture micro-dissection combined with pressure catapulting. Protein extracts were analyzed by nanoUPLC separation combined with ESI-Q-TOF mass spectrometry. The majority of the ~160 proteins identified were involved in translation, protein synthesis, or protein destination. The NP proteome was enriched for stress defense molecules, while proteins involved in assimilate transport and the mobilization of nutrients were common to both the NP and the ETC. The combined qualitative and quantitative protein profiling allowed for the identification of several proteins showing tissue specificity in their expression, which underlines the distinct biological functions of these two tissues within the developing barley grain.

Glioma proteomics: status and perspectives

High grade gliomas are the most common brain tumors in adults and their malignant nature makes them the fourth biggest cause of cancer death. Major efforts in neuro-oncology research are needed to reach similar progress in treatment efficacy as that achieved for other cancers in recent years. In addition to the urgent need to identify novel effective drug targets against malignant gliomas, the search for glioma biomarkers and grade specific protein signatures will provide a much needed contribution to diagnosis, prognosis, treatment decision and assessment of treatment response. Over the past years glioma proteomics has been attempted at different levels, including proteome analysis of patient biopsies and bodily fluids, of glioma cell lines and animal models. Here we provide an extensive review of the outcome of these studies in terms of protein identifications (protein numbers and regulated proteins), with an emphasis on the methods used and the limitations of the studies with regard to biomarker discovery. This is followed by a perspective on novel technologies and on the potential future contribution of proteomics in a broad sense to understanding glioma biology.

Application of mass spectrometry-based proteomics for biomarker discovery in neurological disorders

Mass spectrometry-based quantitative proteomics has emerged as a powerful approach that has the potential to accelerate biomarker discovery, both for diagnostic as well as therapeutic purposes. Proteomics has traditionally been synonymous with 2D gels but is increasingly shifting to the use of gel-free systems and liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS). Quantitative proteomic approaches have already been applied to investigate various neurological disorders, especially in the context of identifying biomarkers from cerebrospinal fluid and serum. This review highlights the scope of different applications of quantitative proteomics in understanding neurological disorders with special emphasis on biomarker discovery.

Glioma pathophysiology: insights emerging from proteomics

Proteomics is increasingly employed in both neurological and oncological research to provide insight into the molecular basis of disease but rarely has a coherent, novel pathophysiological insight emerged. Gliomas account for >50% of adult primary intracranial tumors, with malignant gliomas (anaplastic astrocytomas and glioblastoma multiforme) being the most common. In glioma, the application of proteomic technology has identified altered protein expression but without consistency of these alterations or their biological significance being established. A systematic review of multiple independent proteomic analyses of glioma has demonstrated alterations of 99 different proteins. Importantly 10 of the 99 proteins found differentially expressed in glioma [PHB, Hsp20, serum albumin, epidermal growth factor receptor (EGFR), EA-15, RhoGDI, APOA1, GFAP, HSP70, PDIA3] were identified in multiple publications. An assessment of protein-protein interactions between these proteins compiled using novel web-based technology, revealed a robust and cohesive network for glioblastoma. The protein network discovered (containing TP53 and RB1 at its core) compliments recent findings in genomic studies of malignant glioma. The novel perspective provided by network analysis indicates that the potential of this technology to explore crucial aspects of glioma pathophysiology can now be realized but only if the conceptual and technical limitations highlighted in this review are addressed.

Expression sites of colligin 2 in glioma blood vessels

In a previous study using state-of-the-art proteomic techniques, we identified colligin 2 (HSP47) as a glioma blood vessel-specific protein. In the present study we precisely localized the expression of colligin 2 in the blood vessels of diffusely infiltrating gliomas and relate the expression to the distinct cellular components of the vessels by using multiple immunolabeling and confocal microscopy. We grouped the glioma blood vessels into morphological categories ranging from normal looking capillaries to vessels with hypertrophic and sclerotic changes. The expression patterns of various markers of endothelial and pericytic differentiation were correlated with the position of the cells in the vessels and the expression of colligin 2. We found that colligin 2 is expressed in all categories of glioma blood vessels in cells with endothelial and pericytic lineage. Expression of colligin 2 was also found in cells scattered around blood vessels and in few glial fibrillary acidic protein-positive cells within the blood vessels. There is overlap in the expression of colligin 2 and the collagens type I and IV for which colligin 2 is a chaperon. We conclude that colligin 2 is expressed in all cellular components of glioma blood vessels and may serve as a general marker for active angiogenesis.

Identification of a putative protein profile associated with tamoxifen therapy resistance in breast cancer

Tamoxifen resistance is a major cause of death in patients with recurrent breast cancer. Current clinical factors can correctly predict therapy response in only half of the treated patients. Identification of proteins that are associated with tamoxifen resistance is a first step toward better response prediction and tailored treatment of patients. In the present study we intended to identify putative protein biomarkers indicative of tamoxifen therapy resistance in breast cancer using nano-LC coupled with FTICR MS. Comparative proteome analysis was performed on ∼5,500 pooled tumor cells (corresponding to ∼550 ng of protein lysate/analysis) obtained through laser capture microdissection (LCM) from two independently processed data sets (n = 24 and n = 27) containing both tamoxifen therapy-sensitive and therapy-resistant tumors. Peptides and proteins were identified by matching mass and elution time of newly acquired LC-MS features to information in previously generated accurate mass and time tag reference databases. A total of 17,263 unique peptides were identified that corresponded to 2,556 non-redundant proteins identified with ≥2 peptides. 1,713 overlapping proteins between the two data sets were used for further analysis. Comparative proteome analysis revealed 100 putatively differentially abundant proteins between tamoxifen-sensitive and tamoxifen-resistant tumors. The presence and relative abundance for 47 differentially abundant proteins were verified by targeted nano-LC-MS/MS in a selection of unpooled, non-microdissected discovery set tumor tissue extracts. ENPP1, EIF3E, and GNB4 were significantly associated with progression-free survival upon tamoxifen treatment for recurrent disease. Differential abundance of our top discriminating protein, extracellular matrix metalloproteinase inducer, was validated by tissue microarray in an independent patient cohort (n = 156). Extracellular matrix metalloproteinase inducer levels were higher in therapy-resistant tumors and significantly associated with an earlier tumor progression following first line tamoxifen treatment (hazard ratio, 1.87; 95% confidence interval, 1.25–2.80; p = 0.002). In summary, comparative proteomics performed on laser capture microdissection-derived breast tumor cells using nano-LC-FTICR MS technology revealed a set of putative biomarkers associated with tamoxifen therapy resistance in recurrent breast cancer.

Clinical biomarkers of angiogenesis inhibition

INTRODUCTION

An expanding understanding of the importance of angiogenesis in oncology and the development of numerous angiogenesis inhibitors are driving the search for biomarkers of angiogenesis. We review currently available candidate biomarkers and surrogate markers of anti-angiogenic agent effect.

DISCUSSION

A number of invasive, minimally invasive, and non-invasive tools are described with their potential benefits and limitations. Diverse markers can evaluate tumor tissue or biological fluids, or specialized imaging modalities.

CONCLUSIONS

The inclusion of these markers into clinical trials may provide insight into appropriate dosing for desired biological effects, appropriate timing of additional therapy, prediction of individual response to an agent, insight into the interaction of chemotherapy and radiation following exposure to these agents, and perhaps most importantly, a better understanding of the complex nature of angiogenesis in human tumors. While many markers have potential for clinical use, it is not yet clear which marker or combination of markers will prove most useful.

Biomarker discovery in psychiatric disorders

Schizophrenia is a multifaceted neuropsychiatric disorder. Its onset is the result of complex interactions between genetic, developmental and environmental factors. It almost certainly presents a heterogeneous group of aetiologies which may not be reflected in the symptomatic/clinical presentation of patients. Therefore, a better molecular understanding of the disease onset and progression is urgently needed. The high complexity of the disorder and the heterogeneity of patient populations account for the slow progress of biomarker discovery approaches. Multi-omics profiling approaches can be employed to investigate large numbers of patient and control samples in a single experiment. These large scale experiments are required to identify disease intrinsic molecular signatures as well as patient subgroups with potentially distinct biochemical pathways underpinning their symptoms. In this overview, we describe some of the most important challenges for biomarker discovery for psychiatric disorders and emphasize how these problems contribute to the requirement of large sample numbers. Results of MS-based protein profiling studies in schizophrenia research are reviewed and technical advantages and difficulties of the methodologies described. We outline recent technological advances that generated impressive results in other areas of research and point to their applicability for biomarker discovery in psychiatric disorders.

Microproteomics: analysis of protein diversity in small samples

Proteomics, the large-scale study of protein expression in organisms, offers the potential to evaluate global changes in protein expression and their post-translational modifications that take place in response to normal or pathological stimuli. One challenge has been the requirement for substantial amounts of tissue in order to perform comprehensive proteomic characterization. In heterogeneous tissues, such as brain, this has limited the application of proteomic methodologies. Efforts to adapt standard methods of tissue sampling, protein extraction, arraying, and identification are reviewed, with an emphasis on those appropriate to smaller samples ranging in size from several microliters down to single cells. The effects of miniaturization on these analyses are highlighted using neuroscience-related examples, as are statistical issues unique to the high-dimensional datasets generated by proteomic experiments.

A software application for comparing large numbers of high resolution MALDI-FTICR MS spectra demonstrated by searching candidate biomarkers for glioma blood vessel formation

BACKGROUND

A Java application is presented, which compares large numbers (n > 100) of raw FTICR mass spectra from patients and controls. Two peptide profile matrices can be produced simultaneously, one with occurrences of peptide masses in samples and another with the intensity of common peak masses in all the measured samples, using the peak- and background intensities of the raw data. In latter way, more significantly differentially expressed peptides are found between groups than just using the presence or absence in samples of common peak masses. The software application is tested by searching angiogenesis related proteins in glioma by comparing laser capture micro dissected- and enzymatic by trypsin digested tissue sections.

RESULTS

By hierarchical clustering of the presence-absence matrix, it appears that proteins, such as hemoglobin alpha and delta subunit, fibrinogen beta and gamma chain precursor, tubulin specific chaperone A, epidermal fatty acid binding protein, neutrophil gelatinase-associated lipocalin precursor, peptidyl tRNA hydrolase 2 mitochondrial precursor, placenta specific growth hormone, and zinc finger CCHC domain containing protein 13 are significantly different expressed in glioma vessels. The up-regulated proteins in the glioma vessels with respect to the normal vessels determined by the Wilcoxon-Mann-Whitney test on the intensity matrix are vimentin, glial fibrillary acidic protein, serum albumin precursor, annexin A5, alpha cardiac and beta actin, type I cytoskeletal 10 keratin, calcium binding protein p22, and desmin. Peptide masses of calcium binding protein p22, Cdc42 effector protein 3, fibronectin precursor, and myosin-9 are exclusively present in glioma vessels. Some peptide fragments of non-muscular myosin-9 at the C-terminus are strongly up-regulated in the glioma vessels with respect to the normal vessels.

CONCLUSION

The less rigorous than in general used commercial propriety software de-isotope algorithm results in more mono-isotopic peptide masses and consequently more proteins. Centroiding of peptide masses takes place by taking the average over more spectra in the profile matrix. Cytoskeleton proteins and proteins involved in the calcium signaling pathway seem to be most up-regulated in glioma vessels. The finding that peptides at the C-terminus of myosin-9 are up-regulated could be ascribed to splicing or fragmentation by proteases.

Combining laser capture microdissection and proteomics techniques

Laser microdissection is an effective technique to harvest pure cell populations from complex tissue sections. In addition to using the microdissected cells in several DNA and RNA studies, it has been shown that the small number of cells obtained by this technique can also be used for proteomics analysis. Combining laser capture microdissection and different types of mass spectrometers opened ways to find and identify proteins that are specific for various cell types, tissues, and their morbid alterations. Although the combination of microdissection followed by the currently available techniques of proteomics has not yet reached the stage of genome wide representation of all proteins present in a tissue, it is a feasible way to find significant differentially expressed proteins in target tissues. Recent developments in mass spectrometric detection followed by proper statistics and bioinformatics enable to analyze the proteome of not more than 100-200 cells. Obviously, validation of result is essential. The present review describes and discusses the various methods developed to target cell populations of interest by laser microdissection, followed by analysis of their proteome.

Quantitative proteomics for identification of cancer biomarkers

Quantitative proteomics can be used for the identification of cancer biomarkers that could be used for early detection, serve as therapeutic targets, or monitor response to treatment. Several quantitative proteomics tools are currently available to study differential expression of proteins in samples ranging from cancer cell lines to tissues to body fluids. 2-DE, which was classically used for proteomic profiling, has been coupled to fluorescence labeling for differential proteomics. Isotope labeling methods such as stable isotope labeling with amino acids in cell culture (SILAC), isotope-coded affinity tagging (ICAT), isobaric tags for relative and absolute quantitation (iTRAQ), and (18) O labeling have all been used in quantitative approaches for identification of cancer biomarkers. In addition, heavy isotope labeled peptides can be used to obtain absolute quantitative data. Most recently, label-free methods for quantitative proteomics, which have the potential of replacing isotope-labeling strategies, are becoming popular. Other emerging technologies such as protein microarrays have the potential for providing additional opportunities for biomarker identification. This review highlights commonly used methods for quantitative proteomic analysis and their advantages and limitations for cancer biomarker analysis.