Proteomic Assessment of SKBR3/HER2+ Breast Cancer Cellular Response to Lapatinib and Investigational Ipatasertib Kinase Inhibitors.

Modern cancer treatment approaches aim at achieving cancer remission by using targeted and personalized therapies, as well as harnessing the power of the immune system to recognize and eliminate the cancer cells. To overcome a relatively short-lived response due to the development of resistance to the administered drugs, combination therapies have been pursued, as well. To expand the outlook of combination therapies, the objective of this study was to use high-throughput data generation technologies such as mass spectrometry and proteomics to investigate the response of HER2+ breast cancer cells to a mixture of two kinase inhibitors that has not been adopted yet as a standard treatment regime. The broader landscape of biological processes that are affected by inhibiting two major pathways that sustain the growth and survival of cancer cells, i.e., EGFR and PI3K/AKT, was investigated by treating SKBR3/HER2+ breast cancer cells with Lapatinib or a mixture of Lapatinib/Ipatasertib small molecule drugs. Changes in protein expression and/or activity in response to the drug treatments were assessed by using two complementary quantitative proteomic approaches based on peak area and peptide spectrum match measurements. Over 900 proteins matched by three unique peptide sequences (FDR<0.05) were affected by the exposure of cells to the drugs. The work corroborated the anti-proliferative activity of Lapatinib and Ipatasertib, and, in addition to cell cycle and growth arrest processes enabled the identification of several multi-functional proteins with roles in cancer-supportive hallmark processes. Among these, immune response, adhesion and migration emerged as particularly relevant to the ability to effectively suppress the proliferation and dissemination of cancer cells. The supplementation of Lapatinib with Ipatasertib further affected the expression or activity of additional transcription factors and proteins involved in gene expression, trafficking, DNA repair, and development of multidrug resistance. Furthermore, over fifty of the affected proteins represented approved or investigational targets in the DrugBank database, which through their protein-protein interaction networks can inform the selection of effective therapeutic partners. Altogether, our findings exposed a broad plethora of yet untapped opportunities that can be further explored for enhancing the anti-cancer effects of each drug as well as of many other multi-drug therapies that target the EGFR/ERBB2 and PI3K/AKT pathways. The data are available via ProteomeXchange with identifier PXD051094.

Proteomic Insights into Metastatic Breast Cancer Response to Brain Cell-Secreted Factors.

The most devastating feature of cancer cells is their ability to metastasize to distant sites in the body. HER2+ and triple negative breast cancers frequently metastasize to the brain and stay potentially dormant for years, clinging to the microvasculature, until favorable environmental conditions support their proliferation. The sheltered and delicate nature of the brain prevents, however, early disease detection, diagnosis, and effective delivery of therapeutic drugs. Moreover, the challenges associated with the acquisition of brain tissues and biopsies add compounding difficulties to exploring the mechanistic aspects of tumor development, leading to slow progress in understanding the drivers of disease progression and response to therapy. To provide insights into the determinants of cancer cell behavior at the brain metastatic site, this study was aimed at exploring the growth and initial response of HER2+ breast cancer cells (SKBR3) to factors present in the brain perivascular niche. The neural microenvironment conditions were simulated by using the secretome of a set of brain cells that come first in contact with the cancer cells upon crossing the blood brain barrier, i.e., human endothelial cells (HBEC5i), human astrocytes (NHA) and human microglia (HMC3) cells. Cytokine microarrays were used to investigate the cell secretomes and explore the mediators responsible for cell-cell communication, and proteomic technologies for assessing the changes in the behavior of cancer cells upon exposure to the brain cell-secreted factors. The results of the study suggest that the exposure of SKBR3 cells to the brain secretomes altered their growth potential and drove them towards a state of quiescence. The cytokines, growth factors and enzymes detected in the brain cell-conditioned medium were supportive of mostly inflammatory conditions, indicating a collective functional contribution to cell activation, defense, inflammatory responses, chemotaxis, adhesion, angiogenesis, and ECM organization. The SKBR3 cells, on the other hand, secreted numerous cancer-promoting growth factors that were either absent or present in lower abundance in the brain cell culture media, suggesting that upon exposure the SKBR3 cells were deprived of favorable environmental conditions required for optimal growth. The findings of this study underscore the key role played by the neural niche in shaping the behavior of metastasized cancer cells, providing insights into the cancer-host cell cross-talk that contributes to driving metastasized cancer cells into dormancy and into the opportunities that exist for developing novel therapeutic strategies that target the brain metastases of breast cancer.

Anti-inflammatory cytokine stimulation of HMC3 cells: Proteome dataset.

The immunoprotective functions of microglia in the brain are mediated by the inflammatory M1 phenotype. This phenotype is challenged by anti-inflammatory cytokines which polarize the microglia cells to an immunosuppressive M2 phenotype, a trait that is often exploited by cancer cells to evade immune recognition and promote tumor growth. Investigating the molecular determinants of this behavior is crucial for advancing the understanding of the mechanisms that cancer cells use to escape immune attack. In this article, we describe liquid chromatography (LC)-mass spectrometry (MS)/proteomic data acquired with an EASY-nanoLC 1200-Q ExactiveTM OrbitrapTM mass spectrometer that reflect the response of human microglia cells (HMC3) to stimulation with potential cancer-released anti-inflammatory cytokines known to be key players in promoting tumorigenesis in the brain (IL-4, IL-13, IL-10, TGFB and MCP-1). The MS files were processed with the Proteome Discoverer v.2.4 software package. The cell culture conditions, the sample preparation protocols, the MS acquisition parameters, and the data processing approach are described in detail. The RAW and processed MS files associated with this work were deposited in the PRIDE partner repository of the ProteomeXchange Consortium with the dataset identifiers PXD023163 and PXD023166, and the analyzed data in the Mendeley Data cloud-based repository with DOI 10.17632/fvhw2zwt5d.1. The biological interpretation of the data can be accessed in the research article "Systems-Level Proteomics Evaluation of Microglia Response to Tumor-Supportive Anti-inflammatory Cytokines" (Shreya Ahuja and Iulia M. Lazar, Frontiers in Immunology 2021 [1]). The proteome data described in this article will benefit researchers who are either interested in re-processing the data with alternative search engines and filtering criteria, and/or exploring the data in more depth to advance the understanding of cancer progression and the discovery of novel biomarkers or drug targets.

Mapping the cell-membrane proteome of the SKBR3/HER2+ cell line to the cancer hallmarks.

The hallmarks of biological processes that underlie the development of cancer have been long recognized, yet, existing therapeutic treatments cannot prevent cancer from continuing to be one of the leading causes of death worldwide. This work was aimed at exploring the extent to which the cell-membrane proteins are implicated in triggering cancer hallmark processes, and assessing the ability to pinpoint tumor-specific therapeutic targets through a combined membrane proteome/cancer hallmark perspective. By using GO annotations, a database of human proteins associated broadly with ten cancer hallmarks was created. Cell-membrane cellular subfractions of SKBR3/HER2+ breast cancer cells, used as a model system, were analyzed by high resolution mass spectrometry, and high-quality proteins (FDR<3%) identified by at least two unique peptides were mapped to the cancer hallmark database. Over 1,400 experimentally detected cell-membrane or cell-membrane associated proteins, representing ~18% of the human cell-membrane proteome, could be matched to the hallmark database. Representative membrane constituents such as receptors, CDs, adhesion and transport proteins were distributed over the entire genome and present in every hallmark category. Sustained proliferative signaling/cell cycle, adhesion/tissue invasion, and evasion of immune destruction emerged as prevalent hallmarks represented by the membrane proteins. Construction of protein-protein interaction networks uncovered a high level of connectivity between the hallmark members, with some receptor (EGFR, ERBB2, FGFR, MTOR, CSF1R), antigen (CD44), and adhesion (MUC1) proteins being implicated in most hallmark categories. An illustrative subset of 138 hallmark proteins that included 42 oncogenes, 24 tumor suppressors, 9 oncogene/tumor suppressor, and 45 approved drug targets was subjected to a more in-depth analysis. The existing drug targets were implicated mainly in signaling processes. Network centrality analysis revealed that nodes with high degree, rather than betweenness, represent a good resource for informing the selection of putative novel drug targets. Through heavy involvement in supporting cancer hallmark processes, we show that the functionally diverse and networked landscape of cancer cell-membrane proteins fosters unique opportunities for guiding the development of novel therapeutic interventions, including multi-agent, immuno-oncology and precision medicine applications.

The SKBR3 cell-membrane proteome reveals telltales of aberrant cancer cell proliferation and targets for precision medicine applications.

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.

Systems-Level Proteomics Evaluation of Microglia Response to Tumor-Supportive Anti-Inflammatory Cytokines.

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, TGFß, 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 ~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, TGFß, 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.

XMAn v2-a database of Homo sapiens mutated peptides.

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.

Proteogenomic Analysis of Protein Sequence Alterations in Breast Cancer Cells.

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.

Preferential phosphatidylinositol 5-phosphate binding contributes to a destabilization of the VHS domain structure of Tom1.

Tom1 transports endosomal ubiquitinated proteins that are targeted for degradation in the lysosomal pathway. Infection of eukaryotic cells by Shigella flexneri boosts oxygen consumption and promotes the synthesis of phosphatidylinositol-5-phosphate (PtdIns5P), which triggers Tom1 translocation to signaling endosomes. Removing Tom1 from its cargo trafficking function hinders protein degradation in the host and, simultaneously, enables bacterial survival. Tom1 preferentially binds PtdIns5P via its VHS domain, but the effects of a reducing environment as well as PtdIns5P on the domain structure and function are unknown. Thermal denaturation studies demonstrate that, under reducing conditions, the monomeric Tom1 VHS domain switches from a three-state to a two-state transition behavior. PtdIns5P reduced thermostability, interhelical contacts, and conformational compaction of Tom1 VHS, suggesting that the phosphoinositide destabilizes the protein domain. Destabilization of Tom1 VHS structure was also observed with other phospholipids. Isothermal calorimetry data analysis indicates that, unlike ubiquitin, Tom1 VHS endothermically binds to PtdIns5P through two noncooperative binding sites, with its acyl chains playing a relevant role in the interaction. Altogether, these findings provide mechanistic insights about the recognition of PtdIns5P by the VHS domain that may explain how Tom1, when in a different VHS domain conformational state, interacts with downstream effectors under S. flexneri infection.

Microfluidic reactors for advancing the MS analysis of fast biological responses.

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.

Achieving Stable Electrospray Ionization Mass Spectrometry Detection from Microfluidic Chips.

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.

Partial enzymatic reactions: A missed opportunity in proteomics research.

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.

Streamlined microfluidic analysis of phosphopeptides using stable isotope-labeled synthetic peptides and MRM-MS detection.

Modern high-throughput and high-content biological research is performed with advanced instrumentation and complex and time-consuming protocols, which, as a whole, pose a challenge for routine implementation in a research laboratory. In support of a "bioanalytical toolbox" with potential utility for exploring cellular functions mediated via protein phosphorylation-a post-translational modification (PTM) with essential regulatory roles in a variety of cellular processes-in this work, we describe the development of a simple, integrated microfluidic chip that can perform targeted, quantitative analysis of phosphopeptides involved in cancer-relevant signaling pathways. The microfluidic device comprises microreactors packed with C18 and TiO2 particles for on-chip solid phase extraction (SPE) and phosphopeptide enrichment, and an ESI interface for facilitating multiple reaction monitoring (MRM)-mass spectrometry (MS) detection. The chips are demonstrated for the detection of three phosphopeptides involved in ERBB2/MAPK signaling pathways, selected from the outcome of a proteomic study involving EGF stimulation of SKBR3/HER2+ breast cancer cells. The data demonstrate that the proposed microfluidic strategy can be used for the MS quantification of phosphopeptides in the low nM range from cell lysates without any prior sample pretreatment, fractionation or bioaffinity enrichment, and is generally applicable to the analysis of any phosphopeptide targets.

Cell Cycle Model System for Advancing Cancer Biomarker Research.

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.

Bioinformatics Resources for Interpreting Proteomics Mass Spectrometry Data.

Developments in mass spectrometry (MS) instrumentation have supported the advance of a variety of proteomic technologies that have enabled scientists to assess differences between healthy and diseased states. In particular, the ability to identify altered biological processes in a cell has led to the identification of novel drug targets, the development of more effective therapeutic drugs, and the growth of new diagnostic approaches and tools for personalized medicine applications. Nevertheless, large-scale proteomic data generated by modern mass spectrometers are extremely complex and necessitate equally complex bioinformatics tools and computational algorithms for their interpretation. A vast number of commercial and public resources have been developed for this purpose, often leaving the researcher perplexed at the overwhelming list of choices that exist. To address this challenge, the aim of this chapter is to provide a roadmap to the basic steps that are involved in mass spectrometry data acquisition and processing, and to describe the most common tools that are available for placing the results in biological context.

Structural, thermodynamic, and phosphatidylinositol 3-phosphate binding properties of Phafin2.

Phafin2 is a phosphatidylinositol 3-phosphate (PtdIns(3)P) binding protein involved in the regulation of endosomal cargo trafficking and lysosomal induction of autophagy. Binding of Phafin2 to PtdIns(3)P is mediated by both its PH and FYVE domains. However, there are no studies on the structural basis, conformational stability, and lipid interactions of Phafin2 to better understand how this protein participates in signaling at the surface of endomembrane compartments. Here, we show that human Phafin2 is a moderately elongated monomer of ∼28 kDa with an intensity-average hydrodynamic diameter of ∼7 nm. Circular dichroism (CD) analysis indicates that Phafin2 exhibits an α/ß structure and predicts ∼40% random coil content in the protein. Heteronuclear NMR data indicates that a unique conformation of Phafin2 is present in solution and dispersion of resonances suggests that the protein exhibits random coiled regions, in agreement with the CD data. Phafin2 is stable, displaying a melting temperature of 48.4°C. The folding-unfolding curves, obtained using urea- and guanidine hydrochloride-mediated denaturation, indicate that Phafin2 undergoes a two-state native-to-denatured transition. Analysis of these transitions shows that the free energy change for urea- and guanidine hydrochloride-induced Phafin2 denaturation in water is ∼4 kcal mol-1 . PtdIns(3)P binding to Phafin2 occurs with high affinity, triggering minor conformational changes in the protein. Taken together, these studies represent a platform for establishing the structural basis of Phafin2 molecular interactions and the role of the two potentially redundant PtdIns(3)P-binding domains of the protein in endomembrane compartments.

Insulin stimulated MCF7 breast cancer cells: Proteome dataset.

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 re-processing 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]).

Fast Enzymatic Processing of Proteins for MS Detection with a Flow-through Microreactor.

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.

Recurrent chimeric fusion RNAs in non-cancer tissues and cells.

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.