Proteomic analysis of lymphoid and haematopoietic neoplasms: There's more than biomarker discovery

Mining cancer biology through bioinformatic analysis of proteomic data

Introduction: Discovery proteomics for cancer research generates complex datasets of diagnostic, prognostic, and therapeutic significance in human cancer. With the advent of high-resolution mass spectrometers, able to identify thousands of proteins in complex biological samples, only the application of bioinformatics can lead to the interpretation of data which can be relevant for cancer research. Areas covered: Here, we give an overview of the current bioinformatic tools used in cancer proteomics. Moreover, we describe their applications in cancer proteomics studies of cell lines, serum, and tissues, highlighting recent results and critically evaluating their outcomes. Expert opinion: The use of bioinformatic tools is a fundamental step in order to manage the large amount of proteins (from hundreds to thousands) that can be identified and quantified in a cancer biological samples by proteomics. To handle this challenge and obtain useful data for translational medicine, it is important the combined use of different bioinformatic tools. Moreover, a particular attention to the global experimental design, and the integration of multidisciplinary skills are essential for best setting of tool parameters and best interpretation of bioinformatics output.

Serum amyloid A1 and plasminogen as predictory proteins to monitor the progression of preleukemic diseases towards acute lymphoblastic leukaemia

SAA1 and plasminogen as additional predictory molecules to monitor the progression of preleukemic diseases towards ALL.

Approaches for targeted proteomics and its potential applications in neuroscience

An extensive guide on practicable and significant quantitative proteomic approaches in neuroscience research is important not only because of the existing overwhelming limitations but also for gaining valuable understanding into brain function and deciphering proteomics from the workbench to the bedside. Early methodologies to understand the functioning of biological systems are now improving with high-throughput technologies, which allow analysis of various samples concurrently, or of thousand of analytes in a particular sample. Quantitative proteomic approaches include both gel-based and non-gel-based methods that can be further divided into different labelling approaches. This review will emphasize the role of existing technologies, their advantages and disadvantages, as well as their applications in neuroscience. This review will also discuss advanced approaches for targeted proteomics using isotope-coded affinity tag (ICAT) coupled with laser capture microdissection (LCM) followed by liquid chromatography tandem mass spectrometric (LC-MS/MS) analysis. This technology can further be extended to single cell proteomics in other areas of biological sciences and can be combined with other 'omics' approaches to reveal the mechanism of a cellular alterations. This approach may lead to further investigation in basic biology, disease analysis and surveillance, as well as drug discovery. Although numerous challenges still exist, we are confident that this approach will increase the understanding of pathological mechanisms involved in neuroendocrinology, neuropsychiatric and neurodegenerative disorders by delivering protein biomarker signatures for brain dysfunction.

Tissue proteomics of splenic marginal zone lymphoma

Splenic marginal zone lymphoma (SMZL) is a rare chronic B lymphoproliferative disease, whose molecular pathogenesis has still not been well established. For the first time, a proteomic approach was undertaken to analyse the protein profiles of SMZL tissue. 1D and 2D Western blot, immunohistochemical analysis, and functional data mining were also performed in order to validate results, investigate protein species specific regulation, classify proteins, and explore their potential relationships. We demonstrated that SMZL is characterized by modulation of protein species related to energetic metabolism and apoptosis pathways. We also reported specific protein species (such as biliverdin reductase A, manganese superoxide dismutase, beta-2 microglobulin, growth factor receptor-bound protein 2, acidic leucine-rich nuclear phosphoprotein 32 family member A, and Set nuclear oncogene) directly involved in NF-kB and BCR pathways, as well as in chromatin remodelling and cytoskeleton. Our findings shed new light on SMZL pathogenesis and provide a basis for the future development of novel biomarkers. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium with the dataset identifier PXD001124.

Does B cell receptor signaling in chronic lymphocytic leukaemia cells differ from that in other B cell types?

Chronic lymphocytic leukaemia (CLL) is an incurable malignancy of mature B cells. CLL is important clinically in Western countries because of its commonality and because of the significant morbidity and mortality associated with the progressive form of this incurable disease. The B cell receptor (BCR) expressed on the malignant cells in CLL contributes to disease pathogenesis by providing signals for survival and proliferation, and the signal transduction pathway initiated by engagement of this receptor is now the target of several therapeutic strategies. The purpose of this review is to outline current understanding of the BCR signal cascade in normal B cells and then question whether this understanding applies to CLL cells. In particular, this review studies the phenomenon of anergy in CLL cells, and whether certain adaptations allow the cells to overcome anergy and allow full BCR signaling to take place. Finally, this review analyzes how BCR signals can be therapeutically targeted for the treatment of CLL.

Quantitative proteomics to characterize specific histone H2A proteolysis in chronic lymphocytic leukemia and the myeloid THP-1 cell line

Proteome studies on hematological malignancies contribute to the understanding of the disease mechanism and to the identification of new biomarker candidates. With the isobaric tag for relative and absolute quantitation (iTRAQ) method we analyzed the protein expression between B-cells of healthy people and chronic lymphocytic leukemia (CLL) B-cells. CLL is the most common lymphoid cancer of the blood and is characterized by a variable clinical course. By comparing samples of patients with an aggressive vs. indolent disease, we identified a limited list of differentially regulated proteins. The enhanced sensitivity attributed to the iTRAQ labels led to the discovery of a previously reported but still not clarified proteolytic product of histone H2A (cH2A) which we further investigated in light of the suggested functional properties of this modification. In the exploratory proteome study the Histone H2A peptide was up-regulated in CLL samples but a more specific and sensitive screening of a larger patient cohort indicated that cH2A is of myeloid origin. Our subsequent quantitative analysis led to a more profound characterization of the clipping in acute monocytic leukemia THP-1 cells subjected to induced differentiation.

Profiling the potential tumor markers of pancreatic ductal adenocarcinoma using 2D-DIGE and MALDI-TOF-MS: up-regulation of Complement C3 and alpha-2-HS-glycoprotein

BACKGROUND/AIMS

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal disease with an increasing incidence worldwide. Due to lack of early diagnosis and poor prognosis, it is rather critical to improve the early diagnosis of PDAC. A comparative proteomic method was used to analyze serum proteins to find a new potential specific marker.

METHODS

Comparative analysis of the pancreatic peripheral blood protein profiling from 40 pancreatic cancer patients, 10 pancreatic benign tumor patients, 10 chronic pancreatitis patients and 40 cancer-free controls. The samples were carried out by 2D-differential gel electrophoresis (2D-DIGE) and differentially expressed proteins were identified by matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF-MS). Two up-regulated proteins were further validation by real time RT-PCR, Western blot analysis and Immunohistochemistry (IHC).

RESULTS

We identified fourteen differently expressed proteins in PDAC group compared with cancer-free control group, including 9 up-regulation and 5 down-regulation proteins. Increased Complement C3 and alpha-2-HS-glycoprotein (AHSG) were further confirmed by real time RT-PCR, Western blot analysis and IHC. The expressions of Complement C3 and AHSG were higher in PDAC than that in other groups.

CONCLUSIONS

These results suggest that Complement C3 and AHSG might be the potential tumor markers in PDAC screening and diagnosis. The finding of inflammation mediated factor Complement C3 revealed that inflammation might be closely related with the occurrence and development process of PDAC.

Discovery and verification of gelsolin as a potential biomarker of colorectal adenocarcinoma in the Chinese population: Examining differential protein expression using an iTRAQ labelling-based proteomics approach

OBJECTIVE

To identify and validate potential biomarkers of colorectal adenocarcinoma using a proteomic approach.

METHODS

Multidimensional liquid chromatography⁄mass spectrometry was used to analyze biological samples labelled with isobaric mass tags for relative and absolute quantitation to identify differentially expressed proteins in human colorectal adenocarcinoma and paired normal mucosa for the discovery of cancerous biomarkers. Cancerous and noncancerous samples were compared using online and offline separation. Protein identification was performed using mass spectrometry. The downregulation of gelsolin protein in colorectal adenocarcinoma samples was confirmed by Western blot analysis and validated using immunohistochemistry.

RESULTS

A total of 802 nonredundant proteins were identified in colorectal adenocarcinoma samples, 82 of which fell outside the expression range of 0.8 to 1.2, and were considered to be potential cancer-specific proteins. Immunohistochemistry revealed a complete absence of gelsolin expression in 86.89% of samples and a reduction of expression in 13.11% of samples, yielding a sensitivity of 86.89% and a specificity of 100% for distinguishing colorectal adenocarcinoma from normal tissue.

CONCLUSIONS

These findings suggest that decreased expression of gelsolin is a potential biomarker of colorectal adenocarcinoma.

Electrostatic repulsion-hydrophilic interaction chromatography (ERLIC) versus strong cation exchange (SCX) for fractionation of iTRAQ-labeled peptides

The iTRAQ technique is popular for the comparative analysis of proteins in different complex samples. To increase the dynamic range and sensitivity of peptide identification in shotgun proteomics, SCX chromatography is generally used for the fractionation of iTRAQ-labeled peptides before LC-MS/MS analysis. However, SCX suffers from clustering of similarly charged peptides and the need to desalt fractions. In this report, SCX is compared with the alternative ERLIC method for fractionating iTRAQ-labeled peptides. The simultaneous effect of electrostatic repulsion and hydrophilic interaction in ERLIC results in peptide elution in order of decreasing pI and GRAVY values (increasing polarity). Volatile solvents can be used. We applied ERLIC to iTRAQ-labeled peptides from rat liver tissue, and 2745 proteins and 30,016 unique peptides were identified with high confidence from three technical replicates. This was 12.9 and 49.4% higher, respectively, than was obtained using SCX. In addition, ERLIC is appreciably better at the identification of highly hydrophobic peptides. The results indicate that ERLIC is a more convenient and more effective alternative to SCX for the fractionation of iTRAQ-labeled peptides. Quantification data show that both SCX and ERLIC fractionation have no significant effect on protein quantification by iTRAQ.

iTRAQ analysis reveals mechanisms of growth defects due to excess zinc in Arabidopsis

The micronutrient zinc is essential for all living organisms, but it is toxic at high concentrations. Here, to understand the effects of excess zinc on plant cells, we performed an iTRAQ (for isobaric tags for relative and absolute quantification)-based quantitative proteomics approach to analyze microsomal proteins from Arabidopsis (Arabidopsis thaliana) roots. Our approach was sensitive enough to identify 521 proteins, including several membrane proteins. Among them, IRT1, an iron and zinc transporter, and FRO2, a ferric-chelate reductase, increased greatly in response to excess zinc. The expression of these two genes has been previously reported to increase under iron-deficient conditions. Indeed, the concentration of iron was significantly decreased in roots and shoots under excess zinc. Also, seven subunits of the vacuolar H(+)-ATPase (V-ATPase), a proton pump on the tonoplast and endosome, were identified, and three of them decreased significantly in response to excess zinc. In addition, excess zinc in the wild type decreased V-ATPase activity and length of roots and cells to levels comparable to those of the untreated de-etiolated3-1 mutant, which bears a mutation in V-ATPase subunit C. Interestingly, excess zinc led to the formation of branched and abnormally shaped root hairs, a phenotype that correlates with decreased levels of proteins of several root hair-defective mutants. Our results point out mechanisms of growth defects caused by excess zinc in which cross talk between iron and zinc homeostasis and V-ATPase activity might play a central role.

Proteomics in pancreatic cancer research

In this review, we give an overview of the actual role of proteomic technologies in the study of pancreatic cancers (PCs). We describe PC proteomics on the basis of sample origins, i.e. tissues, body fluids, and PC cell lines. As regards PC tissues, we report the identification of a number of candidate biomarkers of precursor lesions that may allow early diagnosis of this neoplasia. Moreover, we describe cytoskeletal and hypoxia-regulated proteins that confirm the involvement of cytoskeleton modifications and metabolism adaptations in carcinogenesis. We also discuss the most important biomarkers identified by proteomic analysis involved in local invasion and distant metastasis, and in the cross-talk between pancreatic tumor and the surrounding stroma. Furthermore, we report novel candidate biomarkers identified in serum, plasma, and pancreatic juice of cancer patients compared with cancer-free controls. Proteomic alterations in PC cell line models as compared to normal controls and studies on cell lines treated with drugs or new agents to understand their mechanism of pharmacological action or the onset of drug resistance are also presented. Finally, we discuss the recent improvements obtained in classical 2-DE and high-throughput proteomic strategies able to allow the overcoming of relevant proteomic drawbacks.

Mass spectrometric-based quantitative proteomics using SILAC

One of the main goals of comparative cell signaling analyses is the characterization of protein changes between different biological samples, either globally or by targeting specific proteins of interest. Highly accurate and precise strategies are thus required for the relative quantification of proteins extracted from two or more different cell populations. Stable isotope labeling with amino acids in cell culture (SILAC) is a general method for mass spectrometric quantitative proteomics based on metabolic incorporation of stable isotope-labeled amino acids into the cellular protein pool. This method has been applied with great success to a variety of quantitative proteomics problems aimed at gaining further insight into cell signaling pathways. In this chapter, we describe how SILAC can be used for the elucidation of cellular mechanisms, including temporal proteome profiling and the quantitative analysis of the extent of specific posttranslational modifications.

Deciphering squamous cell carcinoma using multidimensional genomic approaches

Squamous cell carcinomas (SqCCs) arise in a wide range of tissues including skin, lung, and oral mucosa. Although all SqCCs are epithelial in origin and share common nomenclature, these cancers differ greatly with respect to incidence, prognosis, and treatment. Current knowledge of genetic similarities and differences between SqCCs is insufficient to describe the biology of these cancers, which arise from diverse tissue origins. In this paper we provide a general overview of whole genome approaches for gene and pathway discovery and highlight the advancement of integrative genomics as a state-of-the-art technology in the study of SqCC genetics.

Reconstructing the pipeline by introducing multiplexed multiple reaction monitoring mass spectrometry for cancer biomarker verification: an NCI-CPTC initiative perspective

Proteomics holds great promise in personalized medicine for cancer in the post-genomic era. In the past decade, clinical proteomics has significantly evolved in terms of technology development, optimization and standardization, as well as in advanced bioinformatics data integration and analysis. Great strides have been made for characterizing a large number of proteins qualitatively and quantitatively in a proteome, including the use of sample fractionation, protein microarrays and MS. It is believed that differential proteomic analysis of high-quality clinical biospecimen (tissue and biofluids) can potentially reveal protein/peptide biomarkers responsible for cancer by means of their altered levels of expression and/or PTMs. Multiple reaction monitoring, a multiplexed platform using stable isotope dilution-MS with sensitivity and reproducibility approaching that of traditional ELISAs commonly used in the clinical setting, has emerged as a potentially promising technique for next-generation high-throughput protein biomarker measurements for diagnostics and therapeutics.

Assessment of pre-diagnosis biomarkers of immune activation and inflammation: insights on the etiology of lymphoma

The DNA-modifying processes that are involved in B lymphocyte activation, somatic hypermutation (SHM), and IgH class switch recombination (CSR) have the potential to lead to genetic errors that lead to the genesis of B cell cancers, such as lymphoma. Given the potential contribution of these immune mechanisms to the development of cancer, assessment of the expression of cytokines, and other immune stimulatory molecules that drive B cell activation, prior to lymphoma diagnosis, may provide insights into the etiology of these cancers. Here, we review studies that have examined prediagnosis protein biomarkers for non-Hodgkin lymphoma (NHL), both AIDS-related NHL, as well as NHL seen in immunocompetent populations. Overall, these studies provide support for the notion that B cell hyper-activation is elevated preceding the appearance of AIDS-NHL, particularly those forms of AIDS-NHL that are not driven by EBV infection and that presumably arise from errors in IgH CSR and SHM. In more limited studies, it appears that dysregulation of cytokine production also precedes the diagnosis of NHL in HIV-negative persons. The availability of prediagnosis serum/plasma from cohort studies provides unique opportunities for proteomic approaches to identify novel prediagnosis etiologic biomarkers for NHL.

Host proteome research in HIV infection

Proteomics has been widely used in the last few years to look for new biomarkers and decipher the mechanism of HIV–host interaction. Herein, we review the recent developments of HIV/AIDS proteomic research, including the samples used in HIV/AIDS related research, the technologies used for proteomic study, the diagnosis biomarkers of HIV-associated disease especially HIV-associated neurocognitive impairment, the mechanisms of HIV–host interaction, HIV-associated dementia, substance abuse, and so on. In the end of this review, we also give some prospects about the limitation and future improvement of HIV/AIDS proteomic research.

Integrating the multiple dimensions of genomic and epigenomic landscapes of cancer

Advances in high-throughput, genome-wide profiling technologies have allowed for an unprecedented view of the cancer genome landscape. Specifically, high-density microarrays and sequencing-based strategies have been widely utilized to identify genetic (such as gene dosage, allelic status, and mutations in gene sequence) and epigenetic (such as DNA methylation, histone modification, and microRNA) aberrations in cancer. Although the application of these profiling technologies in unidimensional analyses has been instrumental in cancer gene discovery, genes affected by low-frequency events are often overlooked. The integrative approach of analyzing parallel dimensions has enabled the identification of (a) genes that are often disrupted by multiple mechanisms but at low frequencies by any one mechanism and (b) pathways that are often disrupted at multiple components but at low frequencies at individual components. These benefits of using an integrative approach illustrate the concept that the whole is greater than the sum of its parts. As efforts have now turned toward parallel and integrative multidimensional approaches for studying the cancer genome landscape in hopes of obtaining a more insightful understanding of the key genes and pathways driving cancer cells, this review describes key findings disseminating from such high-throughput, integrative analyses, including contributions to our understanding of causative genetic events in cancer cell biology.