Direct-tissue SELDI-TOF mass spectrometry analysis: a new application for clinical proteomics

Advances in the application of proteomics in lung cancer

Although the incidence and mortality of lung cancer have decreased significantly in the past decade, it is still one of the leading causes of death, which greatly impairs people’s life and health. Proteomics is an emerging technology that involves the application of techniques for identifying and quantifying the overall proteins in cells, tissues and organisms, and can be combined with genomics, transcriptomics to form a multi-omics research model. By comparing the content of proteins between normal and tumor tissues, proteomics can be applied to different clinical aspects like diagnosis, treatment, and prognosis, especially the exploration of disease biomarkers and therapeutic targets. The applications of proteomics have promoted the research on lung cancer. To figure out potential applications of proteomics associated with lung cancer, we summarized the role of proteomics in studies about tumorigenesis, diagnosis, prognosis, treatment and resistance of lung cancer in this review, which will provide guidance for more rational application of proteomics and potential therapeutic strategies of lung cancer.

Multi-Omics Analysis in Initiation and Progression of Meningiomas: From Pathogenesis to Diagnosis

Meningiomas are common intracranial tumors that can be cured by surgical resection in most cases. However, the most disconcerting is high-grade meningiomas, which frequently recur despite initial successful treatment, eventually conferring poor prognosis. Therefore, the early diagnosis and classification of meningioma is necessary for the subsequent intervention and an improved prognosis. A growing body of evidence demonstrates the potential of multi-omics study (including genomics, transcriptomics, epigenomics, proteomics) for meningioma diagnosis and mechanistic links to potential pathological mechanism. This thesis addresses a neglected aspect of recent advances in the field of meningiomas at multiple omics levels, highlighting that the integration of multi-omics can reveal the mechanism of meningiomas, which provides a timely and necessary scientific basis for the treatment of meningiomas.

Advances in MALDI imaging mass spectrometry of proteins in cardiac tissue, including the heart valve

Significant progress has been made for tissue imaging of proteins using matrix-assisted laser desorption ionization imaging mass spectrometry (MALDI IMS). These advancements now facilitate mapping of a wide range of proteins, peptides, and post-translational modifications in a wide variety of tissues; however, the use of MALDI IMS to detect proteins from cardiac tissue is limited. This review discusses the most recent advances in protein imaging and demonstrates application to cardiac tissue, including the heart valve. Protein imaging by MALDI IMS allows multiplexed histological mapping of proteins and protein components that are inaccessible by antibodies and should be considered an important tool for basic and clinical cardiovascular research. This article is part of a Special Issue entitled: MALDI Imaging, edited by Dr. Corinna Henkel and Prof. Peter Hoffmann.

Potential Serum Markers for Monitoring the Progression of Hepatitis B Virus-Associated Chronic Hepatic Lesions to Liver Cirrhosis

BACKGROUND/AIMS

To screen for serum protein/peptide biomarkers of hepatitis B virus (HBV)-associated chronic hepatic lesions in an attempt to profile the progression of HBV-associated chronic hepatic lesions using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS) techniques.

METHODS

Using SELDI-TOF MS, serum protein/peptide profiles on the CM10 ProteinChip arrays were obtained from a training group including 26 HBV-associated hepatocellular carcinoma patients with liver cirrhosis (LC), 30 HBV-associated LC patients, 85 patients at different stages of liver fibrosis, and 30 asymptomatic HBV carriers. The most valuable SELDI peak for predicting the progression to LC in HBV-infected patients was identified.

RESULTS

A SELDI peak of M/Z 5805 with value for predicting LC in HBV-infected patients was found and was identified as a peptide of the C-terminal fraction of the fibrinogen a-chain precursor, isoform 1.

CONCLUSIONS

The peptide of the C-terminal fraction of the fibrinogen α-chain precursor, isoform 1 with M/Z 5805, may be a serological biomarker for progression to LC in HBV-infected patients.

MALDI TOF imaging mass spectrometry in clinical pathology: a valuable tool for cancer diagnostics (review)

Matrix-assisted laser desorption/ionization (MALDI) time-of-flight (TOF) imaging mass spectrometry (IMS) is an evolving technique in cancer diagnostics and combines the advantages of mass spectrometry (proteomics), detection of numerous molecules, and spatial resolution in histological tissue sections and cytological preparations. This method allows the detection of proteins, peptides, lipids, carbohydrates or glycoconjugates and small molecules.Formalin-fixed paraffin-embedded tissue can also be investigated by IMS, thus, this method seems to be an ideal tool for cancer diagnostics and biomarker discovery. It may add information to the identification of tumor margins and tumor heterogeneity. The technique allows tumor typing, especially identification of the tumor of origin in metastatic tissue, as well as grading and may provide prognostic information. IMS is a valuable method for the identification of biomarkers and can complement histology, immunohistology and molecular pathology in various fields of histopathological diagnostics, especially with regard to identification and grading of tumors.

Proteomics in atherothrombosis: a future perspective

Atherothrombosis is the primary cause of death in Western countries. The cellular and molecular mechanisms underlying atherosclerosis remain widely unknown. The complex nature of atherosclerotic cardiovascular diseases demands the development of novel technologies that enable discovery of new biomarkers for early disease detection and risk stratification, which may predict clinical outcome. In this review, we outline potential sources and recent proteomic approaches that could be applied in the search of novel biomarkers of cardiovascular risk. In addition, we describe some issues raised in relation to the application of proteomics to blood samples, as well as two novel emerging concepts, such as peptidomics and population proteomics. In the future, the use of high-throughput techniques (proteomic, genomics and metabolomics) will potentially identify novel patterns of biomarkers, which, along with traditional risk factors and imaging techniques, could help to target vulnerable patients and monitor the beneficial effects of pharmacological agents.

SPIN: Development of sample-specific protein integrity numbers as an index of biospecimen quality

It is widely accepted that variable biorepository specimen handling conditions can significantly alter outcomes of clinical research studies, suggesting the need for a metric for sample analyte protein integrity. In line with the National Cancer Institute (NCI) Best Practices, it is vital that the integrity of specimens used for biomarker studies are of the highest standard to ensure validity of the data they generate and confidence in the application of new findings to clinical management. We describe the creation of a program to discover proteins in biorepository samples that can be utilized to assess the integrity of stored specimens for protein-based biomarker studies, similar to the universally accepted quality metric for RNA, the RNA Integrity Number, or RIN. The study mimics potential variation in pre-analytical conditions which may result in proteolysis and other proteome-associated changes and employs surface-enhanced laser desorption time-of-flight mass spectrometry (SELDI-TOF MS) to assess changes in multiple proteins and peptides in a high-throughput manner. Candidate peaks from SELDI spectra of representative sample types (e.g., serum, urine, tissue extracts) which demonstrate differing but reproducible sensitivity to suboptimal processing and storage were selected and quantified in a series of specimens stored in the BioBank within the Beaumont Health System. We then assigned a relative index known here as Sample-specific Protein Integrity Number, or SPIN, which is derived from a ratio of nonstable vs. stable proteins for each sample type in the investigation. This methodology can be applied to every sample type and, once refined and established, the SPIN could be used by any biobank or laboratory using biobanked samples without specialized equipment and irrespective of the sample pre-analytical collection conditions.

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.

Enriched sera protein profiling for detection of non-small cell lung cancer biomarkers

Background

Non Small Cell Lung Cancer (NSCLC) is the major cause of cancer related-death. Many patients receive diagnosis at advanced stage leading to a poor prognosis. At present, no satisfactory screening tests are available in clinical practice and the discovery and validation of new biomarkers is mandatory. Surface Enhanced Laser Desorption/Ionization Time-of-Flight Mass Spectrometry (SELDI-ToF-MS) is a recent high-throughput technique used to detect new tumour markers. In this study we performed SELDI-ToF-MS analysis on serum samples treated with the ProteoMiner™ kit, a combinatorial library of hexapeptide ligands coupled to beads, to reduce the wide dynamic range of protein concentration in the sample. Serum from 44 NSCLC patients and 19 healthy controls were analyzed with IMAC30-Cu and H50 ProteinChip Arrays.

Results

Comparing SELDI-ToF-MS protein profiles of NSCLC patients and healthy controls, 28 protein peaks were found significantly different (p < 0.05), and were used as predictors to build decision classification trees. This statistical analysis selected 10 protein peaks in the low-mass range (2-24 kDa) and 6 in the high-mass range (40-80 kDa). The classification models for the low-mass range had a sensitivity and specificity of 70.45% (31/44) and 68.42% (13/19) for IMAC30-Cu, and 72.73% (32/44) and 73.68% (14/19) for H50 ProteinChip Arrays.

Conclusions

These preliminary results suggest that SELDI-ToF-MS protein profiling of serum samples pretreated with ProteoMiner™ can improve the discovery of protein peaks differentially expressed between NSCLC patients and healthy subjects, useful to build classification algorithms with high sensitivity and specificity. However, identification of the significantly different protein peaks needs further study in order to provide a better understanding of the biological nature of these potential biomarkers and their role in the underlying disease process.

Identification of serum protein markers for breast cancer relapse with SELDI-TOF MS

Surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS) was used to screen serum samples to identify protein markers for early breast cancer relapse. We collected 67 serum samples from patients with breast cancer (24 preoperative; 23 postoperative without breast cancer relapse; 20 postoperative with breast cancer relapse). Eight protein peaks varied between the presurgical group and the postsurgical group without breast cancer relapse; 4 protein peaks were differentially expressed between the postsurgical patients without relapse and patients with relapse. The peak at 3964 m/z dropped after surgery and rebounded after relapse (P < 0.01). These results indicate that there are differences in serum protein expression among the three different groups of patients. SELDI-TOF MS could be used to screen blood samples for the early detection of relapse in primary breast cancer patients. Specifically, protein peak at 3964 m/z is a potential biomarker for the detection of early breast cancer relapse.

Identification of proteomic signatures of mantle cell lymphoma, small lymphocytic lymphoma, and marginal zone lymphoma biopsies by surface enhanced laser desorption/ionization-time of flight mass spectrometry

Mantle cell lymphoma (MCL), small lymphocytic lymphoma (SLL), and marginal zone lymphoma (MZL) are small B-cell non-Hodgkin lymphomas (NHLs) that may be difficult to distinguish. In order to identify specific proteomic biomarkers, differential proteomic analysis of these three NHLs was performed using surface enhanced laser desorption/ionization-time of flight mass spectrometry (SELDI-TOF-MS). Whole cell lysates obtained from 18 MCL, 20 SLL, and 20 MZL biopsies were applied on two different ProteinChips (cationic and anionic). Hierarchical clustering and discriminating scores combined with an innovative bio-informatics microdissection strategy allowed us to distinguish specific lymphoma proteomic signatures based on the expression of 37 protein peaks. SELDI-assisted protein purification combined with nano-liquid chromatography (LC) quadrupole-time of flight tandem mass spectrometry (Q-TOF MS/MS) was used to identify proteins overexpressed in both MCL and SLL tumors. Among them two histones, H2B and H4, were identified in MCL tumor biopsies and the signal recognition particle 9 kDa protein, SRP9, in SLL tumor biopsies.

Reference spectra from squamous epithelium and connective tissue allow whole section proteomics analysis

We reasoned that micro-dissection of tumour cells for protein expression studies should be omitted since tumour-stroma interactions are an important part of the biology of solid tumours. To study such interactions in head and neck squamous cell carcinoma (HNSCC) development, we generated reference protein spectra for normal squamous epithelium and connective tissue by SELDI-TOF-MS. Calgranulins A and B, Annexin1 and Histone H4 were found to be strongly enriched in the epithelium. The alpha-defensins 1-3 and the haemoglobin subunits were identified in the connective tissue. Tumour-distant epithelia, representing early pre-malignant lesions, showed up-regulated expression of the stromal alpha-defensins, whereas the epithelial Annexin 1 was down-regulated. Thus, tumour microenvironment interactions occur very early in the carcinogenic process. These data demonstrate that omitting micro-dissection is actually beneficial for studying changes in protein expression during development and progression of solid tumours.

Effects of post-mortem intervals on regional brain protein profiles in rats using SELDI-TOF-MS analysis

Identification of disease-associated proteins is critical for elucidating CNS disease mechanisms and elaborating novel treatment strategies. It requires post-mortem tissue analysis which can be significantly affected by the collection process, post-mortem intervals (PMIs), and storage conditions. To assess the effect of time and storage conditions on brain protein stability, SELDI-TOF-MS protein profiles were assessed in rat frontal cortex, caudate-putamen, hippocampus and medulla samples collected after various PMIs (0, 6, 12, 24, 48, and 72 h) at 4 °C or at room temperature (RT) storage. Regions of interest were isolated from cryosections (tissue apposition, TA), or micropunched from cryosections apposed on filter paper (paper apposition, PA), and applied onto an NP20 ProteinChip array. Protein alterations, while greater at RT than at 4 °C, were detected at 6h then differentially evolved in the various brain regions, with greater alterations in the caudate-putamen (60%) and the cortex (48%). Overall, our sensitive analytical method allowed unveiling of different patterns of protein susceptibility to PMI and to storage temperature in the various brain regions. Some protein peaks were altered in all brain regions and may potentially serve as markers of the PMI status of the brain, or for reference values when studying new proteins. Changes in disease-related proteins within post-mortem samples can be greatly affected by PMI and storage conditions, particularly when studying fragile and/or low abundant protein/peptides in tissues sampled from the caudate-putamen and neocortex.

[Research progress in SELDI-TOF MS and its clinical applications]

Proteinchip profiling is a powerful and innovative proteomic technology for the discovery of biomarkers and the development of diagnostic/prognostic assays. On the basis of surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS), Ciphergen’s proteinchip system offers a single, unified, and high throughput platform for a multitude of proteomic research applications. Proteins are the major functional components of the cell. The study of proteomics helps to better understand the mechanism of a disease. Remarkable findings in disease biomarkers have shed light on the early diagnosis, monitoring, and prognosis of various diseases, especially for cancer. In this paper, the development and technology of SELDI-TOF MS are introduced. The research progress and encouraging research results in malignancies, infectious diseases, neurological diseases, and diabetes mellitus using SELDI-TOF MS are reviewed. This paper concludes by evaluating the pros and cons, and the future perspectives are also expounded.

Increased phosphorylation of vimentin in noninfiltrative meningiomas

BACKGROUND

Tissue invasion or tissue infiltration are clinical behaviors of a poor-prognosis subset of meningiomas. We carried out proteomic analyses of tissue extracts to discover new markers to accurately distinguish between infiltrative and noninfiltrative meningiomas.

METHODOLOGY/PRINCIPAL FINDINGS

Protein lysates of 64 different tissue samples (including two brain-invasive and 32 infiltrative tumors) were submitted to SELDI-TOF mass spectrometric analysis. Mass profiles were used to build up both unsupervised and supervised hierarchical clustering. One marker was found at high levels in noninvasive and noninfiltrative tumors and appeared to be a discriminative marker for clustering infiltrative and/or invasive meningiomas versus noninvasive meningiomas in two distinct subsets. Sensitivity and specificity were 86.7% and 100%, respectively. This marker was purified and identified as a multiphosphorylated form of vimentin, a cytoskeletal protein expressed in meningiomas.

CONCLUSIONS/SIGNIFICANCE

Specific forms of vimentin can be surrogate molecular indicators of the invasive/infiltrative phenotype in tumors.

Mass spectrometry based proteomics profiling as diagnostic tool in oncology: current status and future perspective

Proteomics analysis has been heralded as a novel tool for identifying new and specific biomarkers that may improve diagnosis and monitoring of various disease states. Recent years have brought a number of proteomics profiling technologies. Although proteomics profiling has resulted in the detection of disease-associated differences and modification of proteins, current proteomics technologies display certain limitations that are hampering the introduction of these new technologies into clinical laboratory diagnostics and routine applications. In this review, we summarize current advances in mass spectrometry based biomarker discovery. The promises and challenges of this new technology are discussed with particular emphasis on diagnostic perspectives of mass-spectrometry based proteomics profiling for malignant diseases.

SELDI-TOF MS profiling of serum for detection of nasopharyngeal carcinoma

Background

No satisfactory biomarkers are currently available to screen for nasopharyngeal carcinoma (NPC). We have developed and evaluated surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS) for detection and analysis of multiple proteins for distinguishing individuals with NPC from control individuals.

Methods

A preliminary learning set and a classification tree of spectra derived from 24 patients with NPC and a group of 24 noncancer controls were used to develop a proteomic model that discriminated cancer from noncancer effectively. Then, the validity of the classification tree was challenged with a blind test set, which included another 20 patients with NPC and 12 noncancer controls.

Results

A panel of 3 biomarkers ranging m/z 3–20 k was selected to establish Decision Tree model by BPS with sensitivity of 91.66% and specificity of 95.83%. The ability to detect NPC patients was evaluated, a sensitivity of 95.0% and specificity of 83.33% were validated in blind testing set.

Conclusion

This high-flux proteomic classification system will provide a highly accurate and innovative approach for the detection/diagnosis of NPC.

Proteomic profiles differ between bone invasive and noninvasive benign meningiomas of fibrous and meningothelial subtype

Meningiomas of WHO grade I can usually be cured by surgical resection. However, some tumors may, despite their benign appearance, display invasive growth behavior. These tumors constitute a difficult clinical problem to handle. By histology alone, bone invasive meningiomas may be indistinguishable from their noninvasive counterparts. In this study we have examined the protein spectra in a series of meningiomas in search of protein expression patterns that may distinguish between bone invasive and noninvasive meningiomas. Tumor tissue from 13 patients with fibrous (6 invasive and 7 noninvasive) and 29 with meningothelial (10 invasive and 19 noninvasive) grade I meningiomas were analyzed by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI). Multivariate statistical methods were applied for data analyses. Comparing the protein spectra from invasive and noninvasive fibrous meningioma we found 22 peaks whose intensities were significantly different between the two groups (P < 0.001). Based on the expression pattern of these peaks we were able to perfectly separate the two entities (area under ROC curve = 1.0). In meningothelial meningioma the same comparison yielded six significantly differentially expressed peaks (P < 0.001), which to a large degree separated the invasive from noninvasive tissue (area under ROC curve = 0.873). By analyzing the protein spectra in benign meningiomas we could differentiate between invasive and noninvasive growth behavior in both fibrous and meningothelial meningiomas of grade I. A possibility for early identification of invasive grade I meningiomas may have a strong influence on the follow-up policy and the issue of early or late radiotherapy.

Applications of emerging molecular technologies in glioblastoma multiforme

Glioblastoma multiforme (GBM) is the most common primary brain tumor in adults. Median survival from the time of diagnosis is less than a year, with less than 5% of patients surviving 5 years. These tumors are thought to arise through two different pathways. Primary GBMs represent de novo tumors, while secondary GBMs represent the malignant progression of lower-grade astrocytomas. Moreover, despite improvements in deciphering the complex biology of these tumors, the overall prognosis has not changed in the past three decades. The hope for improving the outlook for these glial-based malignancies is centered on the successful clinical application of current high-throughput technologies. For example, the complete sequencing of the human genome has brought both genomics and proteomics to the forefront of cancer research as a powerful approach to systematically identify large volumes of data that can be utilized to study the molecular and cellular basis of oncology. The organization of these data into a comprehensive view of tumor growth and progression translates into a unique opportunity to diagnose and treat cancer patients. In this review, we summarize current genomic and proteomic alterations associated with GBM and how these modalities may ultimately impact treatment and survival.

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.

Recent advances in protein profiling of tissues and tissue fluids

Creating protein profiles of tissues and tissue fluids, which contain secreted proteins and peptides released from various cells, is critical for biomarker discovery as well as drug and vaccine target selection. It is extremely difficult to obtain pure samples from tissues or tissue fluids, however, and identification of complex protein mixtures is still a challenge for mass spectrometry analysis. Here, we summarize recent advances in techniques for extracting proteins from tissues for mass spectrometry profiling and imaging. We also introduce a novel technique using a capillary ultrafiltration (CUF) probe to enable in vivo collection of proteins from the tissue microenvironment. The CUF probe technique is compared with existing sampling techniques, including perfusion, saline wash, fine-needle aspiration and microdialysis. In this review, we also highlight quantitative mass spectrometric proteomic approaches with, and without, stable-isotope labels. Advances in quantitative proteomics will significantly improve protein profiling of tissue and tissue fluid samples collected by CUF probes.

Proteomic analysis of bone cancer: a review of current and future developments

The ability of sophisticated proteomic approaches to scrutinize the dynamic nature of protein expression, cellular and subcellular protein distribution, post-translational modifications, and protein-protein interactions has culminated in the identification of many potential new therapeutic targets and an abundance of cancer-related biomarkers. From a proteomics perspective, amongst the most under-studied diseases are bone cancers, such as myeloma, osteosarcoma and breast and prostate cancer bony metastases. This review focuses on the recent advances in proteomic technology that have thrust the skeletal cancer field into this exciting age of proteomics, and highlights the future work that is required to adapt this technology to specifically interrogate the skeletal consequences of malignancy.

Oncoproteomics: current trends and future perspectives

Oncoproteomics is the application of proteomics technologies in oncology. Functional proteomics is a promising technique for the rational identification of biomarkers and novel therapeutic targets for cancers. Recent progress in proteomics has opened new avenues for tumor-associated biomarker discovery. With the advent of new and improved proteomics technologies, such as the development of quantitative proteomic methods, high-resolution, -speed and -sensitivity mass spectrometry and protein arrays, as well as advanced bioinformatics for data handling and interpretation, it is now possible to discover biomarkers that can reliably and accurately predict outcomes during cancer management and treatment. However, there are several difficulties in the study of proteins/peptides that are not inherent in the study of nucleic acids. New challenges arise in large-scale proteomic profiling when dealing with complex biological mixtures. Nevertheless, oncoproteomics offers great promise for unveiling the complex molecular events of tumorigenesis, as well as those that control clinically important tumor behaviors, such as metastasis, invasion and resistance to therapy. In this review, the development and advancement of oncoproteomics technologies for cancer research in recent years are expounded.