Search

The plasma membrane proteome resides at the interface between the extra- and intra-cellular environment and through its various roles in signal transduction, immune recognition, nutrient transport, and cell-cell/cell-matrix interactions plays an absolutely critical role in determining the fate of a cell. Our work was aimed at exploring the cell-membrane proteome of a HER2+ breast-cancer cell line (SKBR3) to identify triggers responsible for uncontrolled cell proliferation and intrinsic resources that enable detection and therapeutic interventions. To mimic environmental conditions that enable cancer cells to evolve adaptation/survival traits, cell culture was performed under serum-rich and serum-deprived conditions. Proteomic analysis enabled the identification of similar to 2000 cell-membrane proteins. Classification into proteins with receptor/enzymatic activity, CD antigens, transporters, and cell adhesion/junction proteins uncovered overlapping roles in processes that drive cell growth, apoptosis, differentiation, immune response, adhesion and migration, as well as alternate pathways for proliferation. The large number of tumor markers (> 50) and putative drug targets (> 100) exposed a vast potential for yet unexplored detection and targeting opportunities, whereas the presence of 15 antigen immunological markers enabled an assessment of epithelial, mesenchymal or stemness characteristics. Serum-starved cells displayed altered processes related to mitochondrial OXPHOS/ATP synthesis, protein folding and localization, while serum-treated cells exhibited attributes that support tissue invasion and metastasis. Altogether, our findings advance the understanding of the biological triggers that sustain aberrant cancer cell proliferation, survival and development of resistance to therapeutic drugs, and reveal vast innate opportunities for guiding immunological profiling and precision medicine applications aimed at target selection or drug discovery. National Institute of General Medical Sciences [1R01GM121920] Published version This work was supported by an award from the National Institute of General Medical Sciences (Grant No. 1R01GM121920) to IML. We thank Dr. Joshua Nicklay and Dr. John Veneski from Thermo Scientific for analyzing a preliminary set of cell extracts on a QExactive Plus Orbitrap mass spectrometer. We also thank Dr. Samy Lamouille and Christina Wheeler from the Fralin Biomedical Research Institute at VTC for providing support with the acquisition of confocal microscopy data.

The plasma membrane proteome resides at the interface between the extra- and intra-cellular environment and through its various roles in signal transduction, immune recognition, nutrient transport, and cell-cell/cell-matrix interactions plays an absolutely critical role in determining the fate of a cell. Our work was aimed at exploring the cell-membrane proteome of a HER2+ breast-cancer cell line (SKBR3) to identify triggers responsible for uncontrolled cell proliferation and intrinsic resources that enable detection and therapeutic interventions. To mimic environmental conditions that enable cancer cells to evolve adaptation/survival traits, cell culture was performed under serum-rich and serum-deprived conditions. Proteomic analysis enabled the identification of ~ 2000 cell-membrane proteins. Classification into proteins with receptor/enzymatic activity, CD antigens, transporters, and cell adhesion/junction proteins uncovered overlapping roles in processes that drive cell growth, apoptosis, differentiation, immune response, adhesion and migration, as well as alternate pathways for proliferation. The large number of tumor markers ( 50) and putative drug targets ( 100) exposed a vast potential for yet unexplored detection and targeting opportunities, whereas the presence of 15 antigen immunological markers enabled an assessment of epithelial, mesenchymal or stemness characteristics. Serum-starved cells displayed altered processes related to mitochondrial OXPHOS/ATP synthesis, protein folding and localization, while serum-treated cells exhibited attributes that support tissue invasion and metastasis. Altogether, our findings advance the understanding of the biological triggers that sustain aberrant cancer cell proliferation, survival and development of resistance to therapeutic drugs, and reveal vast innate opportunities for guiding immunological profiling and precision medicine applications aimed at target selection or drug discovery.

The plasma membrane proteome resides at the interface between the extra- and intra-cellular environment and through its various roles in signal transduction, immune recognition, nutrient transport, and cell-cell and cell-matrix interactions plays an absolutely critical role in determining the fate of a cell. Our work was aimed at exploring the landscape of the cancer cell-membrane proteome responsible for sustaining uncontrolled cell proliferation, and its intrinsic resources for enabling detection and therapeutic interventions. SKBR3/HER2+ breast cancer cells were used as a model system and mass spectrometry for characterizing the proteome. The number of identified cell-membrane proteins exceeded 2,000, with ~1,300 being matched by two or more unique peptides. Classification in four major categories, i.e., proteins with receptor or enzymatic activity, CD antigens, transporters, and cell adhesion proteins, uncovered overlapping roles in biological processes that drive cell growth, apoptosis, differentiation, immune response, adhesion and migration, as well as capabilities for signaling crosstalk and alternate pathways for proliferation. The large number of tumor markers (>50) and putative drug targets (>100) exposed a vast potential for yet unexplored detection and targeting opportunities, whereas the presence of 15 antigen immunological markers enabled an assessment of epithelial, mesenchymal or stemness characteristics. Serum-starved cells displayed altered processes related to mitochondrial OXPHOS/ATP synthesis, protein folding and localization, while serum-treated cells exhibited attributes that support tissue invasion and metastasis. Altogether, our findings advance the understanding of the biological triggers that sustain aberrant cancer cell proliferation, survival and development of resistance to therapeutic drugs, and reveal the vast innate opportunities for guiding immunological profiling and precision medicine applications aimed at target selection or drug discovery.

Background Microglia safeguard the CNS against injuries and pathogens, and in the presence of certain harmful stimuli are capable of inducing a disease-dependent inflammatory response. When exposed to anti-inflammatory cytokines, however, these cells possess the ability to switch from an inflammatory to an immunosuppressive phenotype. Cancer cells exploit this property to evade the immune system, and elicit an anti-inflammatory microenvironment that facilitates tumor attachment and growth. Objective The tumor-supportive biological processes that are activated in microglia cells in response to anti-inflammatory cytokines released from cancer cells were explored with mass spectrometry and proteomic technologies. Methods Serum-depleted and non-depleted human microglia cells (HMC3) were treated with a cocktail of IL-4, IL-13, IL-10, TGF beta, and CCL2. The cellular protein extracts were analyzed by LC-MS/MS. Using functional annotation clustering tools, statistically significant proteins that displayed a change in abundance between cytokine-treated and non-treated cells were mapped to their biological networks and pathways. Results The proteomic analysis of HMC3 cells enabled the identification of similar to 10,000 proteins. Stimulation with anti-inflammatory cytokines resulted in the activation of distinct, yet integrated clusters of proteins that trigger downstream a number of tumor-promoting biological processes. The observed changes could be classified into four major categories, i.e., mitochondrial gene expression, ECM remodeling, immune response, and impaired cell cycle progression. Intracellular immune activation was mediated mainly by the transducers of MAPK, STAT, TGF beta, NFKB, and integrin signaling pathways. Abundant collagen formation along with the expression of additional receptors, matrix components, growth factors, proteases and protease inhibitors, was indicative of ECM remodeling processes supportive of cell-cell and cell-matrix adhesion. Overexpression of integrins and their modulators was reflective of signaling processes that link ECM reorganization with cytoskeletal re-arrangements supportive of cell migration. Antigen processing/presentation was represented by HLA class I histocompatibility antigens, and correlated with upregulated proteasomal subunits, vesicular/viral transport, and secretory processes. Immunosuppressive and proangiogenic chemokines, as well as anti-angiogenic factors, were detectable in low abundance. Pronounced pro-inflammatory, chemotactic or phagocytic trends were not observed, however, the expression of certain receptors, signaling and ECM proteins indicated the presence of such capabilities. Conclusions Comprehensive proteomic profiling of HMC3 cells stimulated with anti-inflammatory cytokines revealed a spectrum of microglia phenotypes supportive of cancer development in the brain via microenvironment-dependent biological mechanisms. National Institute of General Medical SciencesUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Institute of General Medical Sciences (NIGMS) [1R01GM121920] Published version This work was supported by an award from the National Institute of General Medical Sciences (Grant No. 1R01GM121920) to IL.

Heterozygous mutations in the X-linked gene CASK are associated with intellectual disability, microcephaly, pontocerebellar hypoplasia, optic nerve hypoplasia and partially penetrant seizures in girls. The Cask(+/−) heterozygous knockout female mouse phenocopies the human disorder and exhibits postnatal microencephaly, cerebellar hypoplasia and optic nerve hypoplasia. It is not known if Cask(+/−) mice also display seizures, nor is known the molecular mechanism by which CASK haploinsufficiency produces the numerous documented phenotypes. 24-hour video electroencephalography demonstrates that despite sporadic seizure activity, the overall electrographic patterns remain unaltered in Cask(+/−) mice. Additionally, seizure threshold to the commonly used kindling agent, pentylenetetrazol, remains unaltered in Cask(+/−) mice, indicating that even in mice the seizure phenotype is only partially penetrant and may have an indirect mechanism. RNA sequencing experiments on Cask(+/−) mouse brain uncovers a very limited number of changes, with most differences arising in the transcripts of extracellular matrix proteins and the transcripts of a group of nuclear proteins. In contrast to limited changes at the transcript level, quantitative whole-brain proteomics using iTRAQ quantitative mass-spectrometry reveals major changes in synaptic, metabolic/mitochondrial, cytoskeletal, and protein metabolic pathways. Unbiased protein-protein interaction mapping using affinity chromatography demonstrates that CASK may form complexes with proteins belonging to the same functional groups in which altered protein levels are observed. We discuss the mechanism of the observed changes in the context of known molecular function/s of CASK. Overall, our data indicate that the phenotypic spectrum of female Cask(+/−) mice includes sporadic seizures and thus closely parallels that of CASK haploinsufficient girls; the Cask(+/−) mouse is thus a face-validated model for CASK-related pathologies. We therefore surmise that CASK haploinsufficiency is likely to affect brain structure and function due to dysregulation of several cellular pathways including synaptic signaling and cellular metabolism.

RATIONALE Biological studies are conducted at ever-increasing rates by relying on proteomic workflows. Although data acquisition by mass spectrometry is highly automated and rapid, sample preparation continues to be the bottleneck of developing high-throughput workflows. Enzymatic protein processing, in particular, involves time-consuming protocols that can extend from one day to another. To address this gap, we developed and evaluated simple, in-solution tryptic enzymatic reactions that unfold within a few minutes, and demonstrate the utility of the methodology for the rapid analysis of proteins originating from cancer cell extracts. METHODS Tryptic enzymatic reactions were conducted for 7-60 min, and the results were compared with that of a routine approach conducted for 18 h. No other reaction conditions were changed relative to the 18 h procedure. The reaction products were analyzed by nanospray high-performance liquid chromatography/tandem mass spectrometry (nano-HPLC/MS/MS), and the quality of the products was assessed in terms of peptide/protein identifications, sequence coverage, peptide length, missed-cleavage sites, quality of generated ions, and peptide hydrophilic/hydrophobic properties. RESULTS The results demonstrate that brief, and therefore incomplete, enzymatic processes lead to a large number of peptide fragments that improve protein sequence and proteome coverage, that the tandem mass spectra produced from these peptides are of high quality for reliable protein identifications, and that the physical properties of peptides are prone to supporting the development of alternative multi-dimensional separations and middle-down proteomics analysis strategies. The reproducibility of generating the same peptides within a few minutes of enzymatic digestion was remarkably close to that obtained from 18 h long reactions, and the combined results of short and long reactions increased proteome coverage by ~40%. CONCLUSIONS We demonstrate that partial enzymatic reactions conducted on short time-scales represent a valuable asset to proteomic studies, and propose their implementation either as simple, cost-effective, stand-alone protocols for substantially streamlining the analysis of biological samples, or as complementary protocols, for improving protein sequence and proteome coverage.

Summary The ‘Unknown Mutation Analysis (XMAn)’ database is a compilation of Homo sapiens mutated peptides in FASTA format, that was constructed for facilitating the identification of protein sequence alterations by tandem mass spectrometry detection. The database comprises 2 539 031 non-redundant mutated entries from 17 599 proteins, of which 2 377 103 are missense and 161 928 are nonsense mutations. It can be used in conjunction with search engines that seek the identification of peptide amino acid sequences by matching experimental tandem mass spectrometry data to theoretical sequences from a database. Availability and implementation XMAn v2 can be accessed from github.com/lazarlab/XMAnv2. Supplementary information Supplementary data are available at Bioinformatics online.

The proteome data provided in this article were acquired from MCF7 breast cancer cells stimulated with insulin, and were generated by using a 2D-SCX (strong cation exchange)/RPLC (reversed phase liquid chromatography) separation protocol followed by tandem mass spectrometry (MS) detection. To facilitate data reprocessing by more advanced search engines and the extraction of additional information from already existing files, both raw and processed data are provided. The sample preparation, data acquisition and processing protocols are described in detail. The raw data relate to work published in “Proteome profile of the MCF7 cancer cell line: a mass spectrometric evaluation” (Sarvaiya et al., 2006) [1] and are made available through the PRIDE (PRoteomics IDEntifications)/ProteomeXchange public repository with identifier PRIDE: PXD004051 (“2016 update of the PRIDE database and tools” (Vizcaino et al., 2016) [2]). This work was supported by grants from NSF to IML (BES-0448840 and DBI-1255991).

The past two decades have witnessed remarkable advances in the development of microfluidic devices as bioanalytical platforms for the analysis of biological molecules. The implementation of mass spectrometry (MS) detection systems on these devices has become inevitable, and various chip-MS ionization interfaces have been developed. As electrospray ionization (ESI) is particularly relevant for the analysis of large biological molecules such as proteins or peptides, efforts have focused on advancing interfaces that meet the demands of nano-separation techniques that are typically used prior to MS detection. Achieving stable ESI conditions that enable sensitive MS detection is, however, not trivial, especially when the spray is generated from a microfabricated platform. This chapter is aimed at providing a step-by-step protocol for producing stable and efficient electrospray sample ionization from microfluidic chips that are used for capillary electrophoresis (CE) separations.

Cancer evolves as a result of an accumulation of mutations and chromosomal aberrations. Developments in sequencing technologies have enabled the discovery and cataloguing of millions of such mutations. The identification of protein-level alterations, typically by using reversed-phase protein arrays or mass spectrometry, has lagged, however, behind gene and transcript-level observations. In this study, we report the use of mass spectrometry for detecting the presence of mutations-missense, indels and frame shifts-in MCF7 and SKBR3 breast cancer, and non-tumorigenic MCF10A cells. The mutations were identified by expanding the database search process of raw mass spectrometry files by including an in-house built database of mutated peptides (XMAn-v1) that complemented a minimally redundant, canonical database of Homo sapiens proteins. The work resulted in the identification of nearly 300 mutated peptide sequences, of which ~50 were characterized by quality tandem mass spectra. We describe the criteria that were used to select the mutated peptide sequences, evaluate the parameters that characterized these peptides, and assess the artifacts that could have led to false peptide identifications. Further, we discuss the functional domains and biological processes that may be impacted by the observed peptide alterations, and how protein-level detection can support the efforts of identifying cancer driving mutations and genes. Mass spectrometry data are available via ProteomeXchange with identifier PXD014458.

The response of cells to physical or chemical stimuli is complex, unfolding on time-scales from seconds to days, with or without de novo protein synthesis, and involving signaling processes that are transient or sustained. By combining the technology of microfluidics that supports fast and precise execution of a variety of cell handling operations, with that of mass spectrometry detection that facilitates an accurate and complex characterization of the protein complement of cells, in this work, we developed a platform that supports (near) real-time sampling and proteome-level capturing of cellular responses to a perturbation such as treatment with mitogens. The geometric design of the chip supports three critical features: (a) capture of a sufficient number of cells to meet the detection limit requirements of mass spectrometry instrumentation, (b) fluid delivery for uniform stimulation of the resident cells, and (c) fast cell recovery, lysis and processing for accurate sampling of time-sensitive cellular responses to a stimulus. COMSOL simulations and microscopy were used to predict and evaluate the flow behavior inside the microfluidic device. Proteomic analysis of the cellular extracts generated by the chip experiments revealed that the identified proteins were representative of all cellular locations, exosomes, and major biological processes related to proliferation and signaling, demonstrating that the device holds promising potential for integration into complex lab-on-chip work-flows that address systems biology questions. The applicability of the chips to study time-sensitive cellular responses is discussed in terms of technological challenges and biological relevance. Chip-scale devices that quickly deliver proteins expressed by cells to mass spectrometers may bring quantitative insights into the early stages of cancer. Many proteins generated by cells during signaling events are transient and present in numbers too small to be detected by typical analytical instruments. Iulia Lazar and colleagues from Virginia Tech in Blacksburg, United States have developed a microfluidic system that improves the capture of these biomolecules by exposing cells, held in high-capacity chambers, to a crosswise flow of stimulating agents. This setup yielded faster and more accurate mass spectrometry analysis of the cellular protein content than the systems that delivered agents lengthwise along the sample chambers. Experiments with breast cancer cells enabled the team to identify hundreds of proteins involved in growth and division processes in the few minutes following exposure to mitosis-triggering substances.

Diagnostics Devastating illnesses such as cancer, immune/infectious diseases, cardiovascular and neurological disorders claim and affect the lives of millions of people each year. Early detection is key to increasing survivability rates, preventing the onset of debilitating symptoms and various risk factors, improving disease management and treatment outcomes, and, ultimately, to reducing emotional and financial burden. Key to enabling early disease detection is the availability of diagnostic and prognostic biomarkers, as well as of adequate technologies that enable cost-effective diagnostics, discovery and large-scale population screening applications. For example, in the case of cancer, detection technologies have evolved from classical immunohistochemical staining (IHS), fluorescent in situ hybridization (FISH), tissue monitoring, genetic testing (BRCA1/BRCA2 mutations) or protein assaying (PSA-prostate cancer, CA125ovarian/colon cancer), to more advanced approaches that involve searching for circulating tumor cells (CTCs), and, rather recently, toward technologies involving the use of qRT-PCR, microarrays (DNA, protein, antigen, lectin, tissue), nanoprobes, and of next generation sequencing (NGS) and microfluidic and mass spectrometry (MS) platforms. Likewise, the molecular markers have evolved from single gene/ single protein species to comprehensive panels that include whole-genome expression, transcriptional (RNA, miRNA), epigenetic (DNA methylation) or other omic profiles (proteome, secretome, exosome, glycome, metabolome). Altogether, it has become evident that information-rich data will also support the development of system-level computational models that can help elucidate not only the molecular pathways that control cell functionality, but also the identification of novel biomarkers and drug targets. As a result, the development of modern technologies that will enable the generation of such data in a discovery, screening or diagnostic context is essential to advancing our ability to detect, prevent and manage a disease.

Progress in understanding the complexity of a devastating disease such as cancer has underscored the need for developing comprehensive panels of molecular markers for early disease detection and precision medicine applications. The present study was conducted to assess whether a cohesive biological context can be assigned to protein markers derived from public data mining, and whether mass spectrometry can be utilized to screen for the co-expression of functionally related biomarkers to be recommended for further exploration in clinical context. Cell cycle arrest/release experiments of MCF7/SKBR3 breast cancer and MCF10 non-tumorigenic cells were used as a surrogate to support the production of proteins relevant to aberrant cell proliferation. Information downloaded from the scientific public domain was queried with bioinformatics tools to generate an initial list of 1038 cancer-associated proteins. Mass spectrometric analysis of cell extracts identified 352 proteins that could be matched to the public list. Differential expression, enrichment, and protein-protein interaction analysis of the proteomic data revealed several functionally-related clusters of relevance to cancer. The results demonstrate that public data derived from independent experiments can be used to inform biological research and support the development of molecular assays for probing the characteristics of a disease. NCI [R21CA126669-01A1]; NSF [BES-0448840, DBI-1255991] This work was supported by grants from NCI (R21CA126669-01A1) and NSF (BES-0448840, DBI-1255991) to IML. The authors thank Jingren Deng and Fumio Ikenishi for providing support with various aspects of SKBR3 cell culture experiments.

The biological processes that unfold during the G1-phase of the cell cycle are dependent on extracellular mitogenic factors that signal the cell to enter a state of quiescence, or commit to a cell-cycle round by passing the restriction point (R-point) and enter the S-phase. Unlike normal cells, cancer cells evolved the ability to evade the R-point and continue through the cell cycle even in the presence of extensive DNA damage or absence of mitogenic signals. The purpose of this study was to perform a quantitative proteomic evaluation of the biological processes that are responsible for driving MCF-7 breast cancer cells into division even when molecular checkpoints such as the G1/S R-point are in place. Nuclear and cytoplasmic fractions of the G1 and S cell-cycle phases were analyzed by LC-MS/MS to result in the confident identification of more than 2700 proteins. Statistical evaluation of the normalized data resulted in the selection of proteins that displayed twofold or more change in spectral counts in each cell state. Pathway mapping, functional annotation clustering, and protein interaction network analysis revealed that the top-scoring clusters that could play a role in overriding the G1/S transition point included DNA damage response, chromatin remodeling, transcription/translation regulation, and signaling proteins.

The vast majority of mass spectrometry (MS)-based protein analysis methods involve an enzymatic digestion step prior to detection, typically with trypsin. This step is necessary for the generation of small molecular weight peptides, generally with MW < 3,000-4,000 Da, that fall within the effective scan range of mass spectrometry instrumentation. Conventional protocols involve O/N enzymatic digestion at 37 ºC. Recent advances have led to the development of a variety of strategies, typically involving the use of a microreactor with immobilized enzymes or of a range of complementary physical processes that reduce the time necessary for proteolytic digestion to a few minutes (e.g., microwave or high-pressure). In this work, we describe a simple and cost-effective approach that can be implemented in any laboratory for achieving fast enzymatic digestion of a protein. The protein (or protein mixture) is adsorbed on C18-bonded reversed-phase high performance liquid chromatography (HPLC) silica particles preloaded in a capillary column, and trypsin in aqueous buffer is infused over the particles for a short period of time. To enable on-line MS detection, the tryptic peptides are eluted with a solvent system with increased organic content directly in the MS ion source. This approach avoids the use of high-priced immobilized enzyme particles and does not necessitate any aid for completing the process. Protein digestion and complete sample analysis can be accomplished in less than ~3 min and ~30 min, respectively.

Gene fusions and their products (RNA and protein) were once thought to be unique features to cancer. However, chimeric RNAs can also be found in normal cells. Here, we performed, curated and analyzed nearly 300 RNA-Seq libraries covering 30 different non-neoplastic human tissues and cells as well as 15 mouse tissues. A large number of fusion transcripts were found. Most fusions were detected only once, while 291 were seen in more than one sample. We focused on the recurrent fusions and performed RNA and protein level validations on a subset. We characterized these fusions based on various features of the fusions, and their parental genes. They tend to be expressed at higher levels relative to their parental genes than the non-recurrent ones. Over half of the recurrent fusions involve neighboring genes transcribing in the same direction. A few sequence motifs were found enriched close to the fusion junction sites. We performed functional analyses on a few widely expressed fusions, and found that silencing them resulted in dramatic reduction in normal cell growth and/or motility. Most chimeras use canonical splicing sites, thus are likely products of 'intergenic splicing'. We also explored the implications of these non-pathological fusions in cancer and in evolution. NCI [CA190713]; American Cancer Society [126405-RSG-14-065-01-RMC] NCI [CA190713]; American Cancer Society [Research Scholar Grant 126405-RSG-14-065-01-RMC to H.L.]; St. Baldrick's V Scholar. Funding for open access charge: NCI [CA190713].

Recent developments in bioanalytical instrumentation, MS detection, and computational data analysis approaches have provided researchers with capabilities for interrogating the complex cellular glycoproteome, to help gain a better insight into the cellular and physiological processes that are associated with a disease and to facilitate the efforts centered on identifying disease-specific biomarkers. This review describes the progress achieved in the characterization of protein glycosylation by using advanced capillary and microfluidic MS technologies. The major steps involved in large-scale glycoproteomic analysis approaches are discussed, with special emphasis given to workflows that have evolved around complex MS detection functions. In addition, quantitative analysis strategies are assessed, and the bioinformatics aspects of glycoproteomic data processing are summarized. The developments in commercial and custom fabricated microfluidic front-end platforms to ESI- and MALDI-MS instrumentation, for addressing major challenges in carbohydrate analysis such as sensitivity, throughput, and ability to perform structural characterization, are further evaluated and illustrated with relevant examples.

Background Cancer cells are characterized by a deregulated cell cycle that facilitates abnormal proliferation by allowing cells to by-pass tightly regulated molecular checkpoints such as the G1/S restriction point. To facilitate early diagnosis and the identification of new drug targets, current research efforts focus on studies that could lead to the development of protein panels that collectively can improve the effectiveness of our response to the detection of a life-threatening disease. Methods Estrogen-responsive MCF-7 cells were cultured and arrested by serum deprivation in the G1-stage of the cell cycle, and fractionated into nuclear and cytoplasmic fractions. The protein extracts were trypsinized and analyzed by liquid chromatography - mass spectrometry (MS), and the data were interpreted with the Thermo Electron Bioworks software. Biological characterization of the data, selection of cancer markers, and identification of protein interaction networks was accomplished with a combination of bioinformatics tools provided by GoMiner, DAVID and STRING. Results The objective of this work was to explore via MS proteomic profiling technologies and bioinformatics data mining whether randomly identified cancer markers can be associated with the G1-stage of the cell cycle, i.e., the stage in which cancer cells differ most from normal cells, and whether any functional networks can be identified between these markers and placed in the broader context of cell regulatory pathways. The study enabled the identification of over 2000 proteins and 153 cancer markers, and revealed for the first time that the G1-stage of the cell cycle is not only a rich source of cancer markers, but also a host to an intricate network of functional relationships within the majority of these markers. Three major clusters of interacting proteins emerged: (a) signaling, (b) DNA repair, and (c) oxidative phosphorylation. Conclusions The identification of cancer marker regulatory components that act not alone, but within networks, represents an invaluable resource for elucidating the moxlecular mechanisms that govern the uncontrolled proliferation of cancer cells, as well as for catalyzing the development of protein panels with biomarker and drug target potential, screening tests with improved sensitivity and specificity, and novel cancer therapies aimed at pursuing multiple drug targets. Electronic supplementary material The online version of this article (doi:10.1186/1471-2407-14-710) contains supplementary material, which is available to authorized users.

A microfluidic device that enables on-chip matrix assisted laser desorption ionization-mass spectrometry (MALDI-MS) detection for liquid chromatography (LC) separations is described. The device comprises an array of functional elements to carry out LC separations, integrates a novel microchip-MS interface to facilitate the orthogonal transposition of the microfluidic LC channel into an array of reservoirs, and enables sensitive MALDI-MS detection directly from the chip. Essentially, the device provides a snapshot MALDI-MS map of the content of the separation channel present on the chip. The detection of proteins with biomarker potential from MCF10A breast epithelial cell extracts, and detection limits in the low fmol range, are demonstrated. In addition, the design of the novel LC-MALDI-MS chip entices the promotion of a new concept for performing sample separations within the limited time-frame that accompanies the dead-volume of a separation channel.

Protein glycosylation is involved in a broad range of biological processes that regulate protein function and control cell fate. As aberrant glycosylation has been found to be implicated in numerous diseases, the study and large-scale characterization of protein glycosylation is of great interest not only to the biological and biomedical research community, but also to the pharmaceutical and biotechnology industry. Due to the complex chemical structure and differing chemical properties of the protein/peptide and glycan moieties, the analysis and structural characterization of glycoproteins has been proven to be a difficult task. Large-scale endeavors have been further limited by the dynamic outcome of the glycosylation process itself, and, occasionally, by the low abundance of glycoproteins in biological samples. Recent advances in mass spectrometry (MS) instrumentation, and progress in miniaturized technologies for sample handling, enrichment and separation, have resulted in robust and compelling analysis strategies that effectively address the challenges of the glycoproteome. This review summarizes the key steps that are involved in the development of efficient glycoproteomic analysis methods, and the latest innovations that led to successful strategies for the characterization of glycoproteins and their corresponding glycans. As a follow-up to this work, we review innovative capillary and microfluidic-MS workflows for the identification, sequencing, and characterization of glycoconjugates.

The advance of novel technologies that will enable the detection of large sets of biomarker proteins, to greatly improve the sensitivity and specificity of an assay, represents a major objective in biomedical research. To demonstrate the power of mass spectrometry (MS) detection for large-scale biomarker screening in cancer research, a simple, one-step approach for fast biomarker fingerprinting in complex cellular extracts is described. MCF-7 breast cancer cells were used as a model system. Fast proteomic profiling of whole cellular extracts was achieved on a linear trap quadrupole (LTQ) mass spectrometer by one of the following techniques: (a) data-dependent liquid chromatography (LC)-MS/MS of un-labeled cell extracts, (b) data-dependent LC-MS/MS with pulsed Q dissociation (PQD) detection of iTRAQ labeled samples, and (c) multiple reaction monitoring (MRM)-MS of low abundant proteins that could not be detected with data-dependent MS/MS. The data-dependent LC-MS/MS analysis of MCF-7 cells enabled the identification of 796 proteins (p0.001) and the simultaneous detection of 156 previously reported putative cancer biomarkers. PQD detection of iTRAQ labeled cells resulted in the detection of 389 proteins and 64 putative biomarkers. MRM-MS analysis enabled the successful monitoring of a panel of low-abundance proteins in one single experiment, highlighting the utility of this technique for targeted analysis in cancer investigations. These results demonstrate that MS-based technologies relying on a one-step separation protocol have the potential to revolutionize biomarker research and screening applications by enabling fast, sensitive and reliable detection of large panels of putative biomarkers. To further stimulate the exploration of proteins that have been previously reported in the literature to be differentially expressed in a variety of cancers, an extensive list of approximately 1100 candidate biomarkers has been compiled and included in the manuscript.

Instrument miniaturization is one way of addressing the issues of sensitivity, speed, throughput, and cost of analysis in DNA diagnostics, proteomics, and related biotechnology areas. Microfluidics is of special interest for handling very small sample amounts, with minimal concerns related to sample loss and cross-contamination, problems typical for standard fluidic manipulations. Furthermore, the small footprint of these microfabricated structures leads to instrument designs suitable for high-density, parallel sample processing, and high-throughput analyses. In addition to miniaturized systems designed with optical or electrochemical detection, microfluidic devices interfaced to mass spectrometry have also been demonstrated. Instruments for automated sample infusion analysis are now commercially available, and microdevices utilizing chromatographic or capillary electrophoresis separation techniques are under development. This review aims at documenting the technologies and applications of microfluidic mass spectrometry for the analysis of proteomic samples.

The effect of the electrospray ionization (ESI) needle voltage on the electroosmotic flow (EOF) in capillary electrophoresis (CE)-mass spectrometry (MS) was investigated. The radial electric field that penetrates across the CE capillary wall imposed by the ESI needle voltage modifies the typical EOF. This effect was investigated for buffers commonly used in CE-MS. Variations as high as ±30% were observed.

An isotope tags for relative and absolute quantitation (iTRAQ)-based reversed-phase liquid chromatography (RPLC)-tandem mass spectrometry (MS/MS) method was developed for differential protein expression profiling in complex cellular extracts. The estrogen positive MCF-7 cell line, cultured in the presence of 17beta-estradiol (E2) and tamoxifen (Tam), was used as a model system. MS analysis was performed with a linear trap quadrupole (LTQ) instrument operated by using pulsed Q dissociation (PQD) detection. Optimization experiments were conducted to maximize the iTRAQ labeling efficiency and the number of quantified proteins. MS data filtering criteria were chosen to result in a false positive identification rate of4%. The reproducibility of protein identifications was approximately 60%-67% between duplicate, and approximately 50% among triplicate LC-MS/MS runs, respectively. The run-to-run reproducibility, in terms of relative standard deviations (RSD) of global mean iTRAQ ratios, was better than 10%. The quantitation accuracy improved with the number of peptides used for protein identification. From a total of 530 identified proteins (P0.001) in the E2/Tam treated MCF-7 cells, a list of 255 proteins (quantified by at least two peptides) was generated for differential expression analysis. A method was developed for the selection, normalization, and statistical evaluation of such datasets. An approximate approximately 2-fold change in protein expression levels was necessary for a protein to be selected as a biomarker candidate. According to this data processing strategy, approximately 16 proteins involved in biological processes such as apoptosis, RNA processing/metabolism, DNA replication/transcription/repair, cell proliferation and metastasis, were found to be up- or down-regulated.

Background The discovery of novel protein biomarkers is essential in the clinical setting to enable early disease diagnosis and increase survivability rates. To facilitate differential expression analysis and biomarker discovery, a variety of tandem mass spectrometry (MS/MS)-based protein profiling techniques have been developed. For achieving sensitive detection and accurate quantitation, targeted MS screening approaches, such as multiple reaction monitoring (MRM), have been implemented. Methods MCF-7 breast cancer protein cellular extracts were analyzed by 2D-strong cation exchange (SCX)/reversed phase liquid chromatography (RPLC) separations interfaced to linear ion trap MS detection. MS data were interpreted with the Sequest-based Bioworks software (Thermo Electron). In-house developed Perl-scripts were used to calculate the spectral counts and the representative fragment ions for each peptide. Results In this work, we report on the generation of a library of 9,677 peptides (p < 0.001), representing ~1,572 proteins from human breast cancer cells, that can be used for MRM/MS-based biomarker screening studies. For each protein, the library provides the number and sequence of detectable peptides, the charge state, the spectral count, the molecular weight, the parameters that characterize the quality of the tandem mass spectrum (p-value, DeltaM, Xcorr, DeltaCn, Sp, no. of matching a, b, y ions in the spectrum), the retention time, and the top 10 most intense product ions that correspond to a given peptide. Only proteins identified by at least two spectral counts are listed. The experimental distribution of protein frequencies, as a function of molecular weight, closely matched the theoretical distribution of proteins in the human proteome, as provided in the SwissProt database. The amino acid sequence coverage of the identified proteins ranged from 0.04% to 98.3%. The highest-abundance proteins in the cellular extract had a molecular weight (MW) Conclusion Preliminary experiments have demonstrated that putative biomarkers, that are not detectable by conventional data dependent MS acquisition methods in complex un-fractionated samples, can be reliable identified with the information provided in this library. Based on the spectral count, the quality of a tandem mass spectrum and the m/z values for a parent peptide and its most abundant daughter ions, MRM conditions can be selected to enable the detection of target peptides and proteins.