Impact of Protein Stability, Cellular Localization, and Abundance on Proteomic Detection of Tumor-Derived Proteins in Plasma

Tumor-derived, circulating proteins are potentially useful as biomarkers for detection of cancer, for monitoring of disease progression, regression and recurrence, and for assessment of therapeutic response. Here we interrogated how a protein's stability, cellular localization, and abundance affect its observability in blood by mass-spectrometry-based proteomics techniques. We performed proteomic profiling on tumors and plasma from two different xenograft mouse models. A statistical analysis of this data revealed protein properties indicative of the detection level in plasma. Though 20% of the proteins identified in plasma were tumor-derived, only 5% of the proteins observed in the tumor tissue were found in plasma. Both intracellular and extracellular tumor proteins were observed in plasma; however, after normalizing for tumor abundance, extracellular proteins were seven times more likely to be detected. Although proteins that were more abundant in the tumor were also more likely to be observed in plasma, the relationship was nonlinear: Doubling the spectral count increased detection rate by only 50%. Many secreted proteins, even those with relatively low spectral count, were observed in plasma, but few low abundance intracellular proteins were observed. Proteins predicted to be stable by dipeptide composition were significantly more likely to be identified in plasma than less stable proteins. The number of tryptic peptides in a protein was not significantly related to the chance of a protein being observed in plasma. Quantitative comparison of large versus small tumors revealed that the abundance of proteins in plasma as measured by spectral count was associated with the tumor size, but the relationship was not one-to-one; a 3-fold decrease in tumor size resulted in a 16-fold decrease in protein abundance in plasma. This study provides quantitative support for a tumor-derived marker prioritization strategy that favors secreted and stable proteins over all but the most abundant intracellular proteins

Production of human factor VIII-FL in 293T cells using the bicistronic MGMT(P140K)-retroviral vector

Hemophilia A is the most common X-linked bleeding disorder; it is caused by deficiency of coagulation factor VIII (FVIII). Replacement therapy with rFVIII produced from human cell line is a major goal for treating hemophilia patients. We prepared a full-length recombinant FVIII (FVIII-FL), using the pMFG-P140K retroviral vector. The IRES DNA fragment was cloned upstream to the P140K gene, providing a 9.34-kb bicistronic vector. FVIII-FL cDNA was then cloned upstream to IRES, resulting in a 16.6-kb construct. In parallel, an eGFP control vector was generated, resulting in a 10.1-kb construct. The 293T cells were transfected with these constructs, generating the 293T-FVIII-FL/P140K and 293T-eGFP/P140K cell lines. In 293T-FVIII-FL/P140K cells, FVIII and P140K mRNAs levels were 4,410 (+/- 931.7)- and 295,400 (+/- 75,769)-fold higher than in virgin cells. In 293T-eGFP/P140K cells, the eGFP and P140K mRNAs levels were 1,501,000 (+/- 493,700)- and 308,000 (+/- 139,300)-fold higher than in virgin cells. The amount of FVIII-FL was 0.2 IU/mL and 45 ng/mL FVIII cells or 4.4 IU/mu g protein. These data demonstrate the efficacy of the bicistronic retroviral vector expressing FVIII-FL and MGMT(P140K), showing that it could be used for producing the FVIII-FL protein in a human cell line.FINEP [01.07.0652.00]FINEPFAPESPFAPESP [1998/14247-6]CNPq [314458/2009-3, 2008/57877-3]CNP

High-content screen in human pluripotent cells identifies miRNA-regulated pathways controlling pluripotency and differentiation

Background: By post-transcriptionally regulating multiple target transcripts, microRNAs (miRNAs or miR) play important biological functions. H1 embryonic stem cells (hESCs) and NTera-2 embryonal carcinoma cells (ECCs) are two of the most widely used human pluripotent model cell lines, sharing several characteristics, including the expression of miRNAs associated to the pluripotent state or with differentiation. However, how each of these miRNAs functionally impacts the biological properties of these cells has not been systematically evaluated. Methods: We investigated the effects of 31 miRNAs on NTera-2 and H1 hESCs, by transfecting miRNA mimics. Following 3-4 days of culture, cells were stained for the pluripotency marker OCT4 and the G2 cell-cycle marker Cyclin B1, and nuclei and cytoplasm were co-stained with Hoechst and Cell Mask Blue, respectively. By using automated quantitative fluorescence microscopy (i.e., high-content screening (HCS)), we obtained several morphological and marker intensity measurements, in both cell compartments, allowing the generation of a multiparametric miR-induced phenotypic profile describing changes related to proliferation, cell cycle, pluripotency, and differentiation. Results: Despite the overall similarities between both cell types, some miRNAs elicited cell-specific effects, while some related miRNAs induced contrasting effects in the same cell. By identifying transcripts predicted to be commonly targeted by miRNAs inducing similar effects (profiles grouped by hierarchical clustering), we were able to uncover potentially modulated signaling pathways and biological processes, likely mediating the effects of the microRNAs on the distinct groups identified. Specifically, we show that miR-363 contributes to pluripotency maintenance, at least in part, by targeting NOTCH1 and PSEN1 and inhibiting Notch-induced differentiation, a mechanism that could be implicated in na\uefve and primed pluripotent states. Conclusions: We present the first multiparametric high-content microRNA functional screening in human pluripotent cells. Integration of this type of data with similar data obtained from siRNA screenings (using the same HCS assay) could provide a large-scale functional approach to identify and validate microRNA-mediated regulatory mechanisms controlling pluripotency and differentiation

A Systematic Analysis of Eluted Fraction of Plasma Post Immunoaffinity Depletion: Implications in Biomarker Discovery

Plasma is the most easily accessible source for biomarker discovery in clinical proteomics. However, identifying potential biomarkers from plasma is a challenge given the large dynamic range of proteins. The potential biomarkers in plasma are generally present at very low abundance levels and hence identification of these low abundance proteins necessitates the depletion of highly abundant proteins. Sample pre-fractionation using immuno-depletion of high abundance proteins using multi-affinity removal system (MARS) has been a popular method to deplete multiple high abundance proteins. However, depletion of these abundant proteins can result in concomitant removal of low abundant proteins. Although there are some reports suggesting the removal of non-targeted proteins, the predominant view is that number of such proteins is small. In this study, we identified proteins that are removed along with the targeted high abundant proteins. Three plasma samples were depleted using each of the three MARS (Hu-6, Hu-14 and Proteoprep 20) cartridges. The affinity bound fractions were subjected to gelC-MS using an LTQ-Orbitrap instrument. Using four database search algorithms including MassWiz (developed in house), we selected the peptides identified at <1% FDR. Peptides identified by at least two algorithms were selected for protein identification. After this rigorous bioinformatics analysis, we identified 101 proteins with high confidence. Thus, we believe that for biomarker discovery and proper quantitation of proteins, it might be better to study both bound and depleted fractions from any MARS depleted plasma sample

Spectral counting assessment of protein dynamic range in cerebrospinal fluid following depletion with plasma-designed immunoaffinity columns

<p>Abstract</p> <p>Background</p> <p>In cerebrospinal fluid (CSF), which is a rich source of biomarkers for neurological diseases, identification of biomarkers requires methods that allow reproducible detection of low abundance proteins. It is therefore crucial to decrease dynamic range and improve assessment of protein abundance.</p> <p>Results</p> <p>We applied LC-MS/MS to compare the performance of two CSF enrichment techniques that immunodeplete either albumin alone (IgYHSA) or 14 high-abundance proteins (IgY14). In order to estimate dynamic range of proteins identified, we measured protein abundance with APEX spectral counting method.</p> <p>Both immunodepletion methods improved the number of low-abundance proteins detected (3-fold for IgYHSA, 4-fold for IgY14). The 10 most abundant proteins following immunodepletion accounted for 41% (IgY14) and 46% (IgYHSA) of CSF protein content, whereas they accounted for 64% in non-depleted samples, thus demonstrating significant enrichment of low-abundance proteins. Defined proteomics experiment metrics showed overall good reproducibility of the two immunodepletion methods and MS analysis. Moreover, offline peptide fractionation in IgYHSA sample allowed a 4-fold increase of proteins identified (520 vs. 131 without fractionation), without hindering reproducibility.</p> <p>Conclusions</p> <p>The novelty of this study was to show the advantages and drawbacks of these methods side-to-side. Taking into account the improved detection and potential loss of non-target proteins following extensive immunodepletion, it is concluded that both depletion methods combined with spectral counting may be of interest before further fractionation, when searching for CSF biomarkers. According to the reliable identification and quantitation obtained with APEX algorithm, it may be considered as a cheap and quick alternative to study sample proteomic content.</p

Current challenges in software solutions for mass spectrometry-based quantitative proteomics

This work was in part supported by the PRIME-XS project, grant agreement number 262067, funded by the European Union seventh Framework Programme; The Netherlands Proteomics Centre, embedded in The Netherlands Genomics Initiative; The Netherlands Bioinformatics Centre; and the Centre for Biomedical Genetics (to S.C., B.B. and A.J.R.H); by NIH grants NCRR RR001614 and RR019934 (to the UCSF Mass Spectrometry Facility, director: A.L. Burlingame, P.B.); and by grants from the MRC, CR-UK, BBSRC and Barts and the London Charity (to P.C.

Plasma Proteome Profiles Associated with Inflammation, Angiogenesis, and Cancer

Tumor development is accompanied by a complex host systemic response, which includes inflammatory and angiogenic reactions. Both tumor-derived and systemic response proteins are detected in plasma from cancer patients. However, given their non-specific nature, systemic response proteins can confound the detection or diagnosis of neoplasia. Here, we have applied an in-depth quantitative proteomic approach to analyze plasma protein changes in mouse models of subacute irritant-driven inflammation, autoreactive inflammation, and matrix associated angiogenesis and compared results to previously described findings from mouse models of polyoma middle T-driven breast cancer and Pdx1-Cre KrasG12D Ink4a/Arf lox/lox -induced pancreatic cancer. Among the confounding models, approximately 1/3 of all quantified plasma proteins exhibited a significant change in abundance compared to control mice. Of the proteins that changed in abundance, the majority were unique to each model. Altered proteins included those involved in acute phase response, inflammation, extracellular matrix remodeling, angiogenesis, and TGFβ signaling. Comparison of changes in plasma proteins between the confounder models and the two cancer models revealed proteins that were restricted to the cancer-bearing mice, reflecting the known biology of these tumors. This approach provides a basis for distinguishing between protein changes in plasma that are cancer-related and those that are part of a non-specific host response

Activated Leukocyte Cell Adhesion Molecule Expression and Shedding in Thyroid Tumors

Activated leukocyte cell adhesion molecule (ALCAM, CD166) is expressed in various tissues, cancers, and cancer-initiating cells. Alterations in expression of ALCAM have been reported in several human tumors, and cell adhesion functions have been proposed to explain its association with cancer. Here we documented high levels of ALCAM expression in human thyroid tumors and cell lines. Through proteomic characterization of ALCAM expression in the human papillary thyroid carcinoma cell line TPC-1, we identified the presence of a full-length membrane-associated isoform in cell lysate and of soluble ALCAM isoforms in conditioned medium. This finding is consistent with proteolytically shed ALCAM ectodomains. Nonspecific agents, such as phorbol myristate acetate (PMA) or ionomycin, provoked increased ectodomain shedding. Epidermal growth factor receptor stimulation also enhanced ALCAM secretion through an ADAM17/TACE-dependent pathway. ADAM17/TACE was expressed in the TPC-1 cell line, and ADAM17/TACE silencing by specific small interfering RNAs reduced ALCAM shedding. In addition, the CGS27023A inhibitor of ADAM17/TACE function reduced ALCAM release in a dose-dependent manner and inhibited cell migration in a wound-healing assay. We also provide evidence for the existence of novel O-glycosylated forms and of a novel 60-kDa soluble form of ALCAM, which is particularly abundant following cell stimulation by PMA. ALCAM expression in papillary and medullary thyroid cancer specimens and in the surrounding non-tumoral component was studied by western blot and immunohistochemistry, with results demonstrating that tumor cells overexpress ALCAM. These findings strongly suggest the possibility that ALCAM may have an important role in thyroid tumor biology

Secretome-Based Identification of ULBP2 as a Novel Serum Marker for Pancreatic Cancer Detection

BACKGROUND: To discover novel markers for improving the efficacy of pancreatic cancer (PC) diagnosis, the secretome of two PC cell lines (BxPC-3 and MIA PaCa-2) was profiled. UL16 binding protein 2 (ULBP2), one of the proteins identified in the PC cell secretome, was selected for evaluation as a biomarker for PC detection because its mRNA level was also found to be significantly elevated in PC tissues. METHODS: ULBP2 expression in PC tissues from 67 patients was studied by immunohistochemistry. ULBP2 serum levels in 154 PC patients and 142 healthy controls were measured by bead-based immunoassay, and the efficacy of serum ULBP2 for PC detection was compared with the widely used serological PC marker carbohydrate antigen 19-9 (CA 19-9). RESULTS: Immunohistochemical analyses revealed an elevated expression of ULPB2 in PC tissues compared with adjacent non-cancerous tissues. Meanwhile, the serum levels of ULBP2 among all PC patients (n = 154) and in early-stage cancer patients were significantly higher than those in healthy controls (p<0.0001). The combination of ULBP2 and CA 19-9 outperformed each marker alone in distinguishing PC patients from healthy individuals. Importantly, an analysis of the area under receiver operating characteristic curves showed that ULBP2 was superior to CA 19-9 in discriminating patients with early-stage PC from healthy controls. CONCLUSIONS: Collectively, our results indicate that ULBP2 may represent a novel and useful serum biomarker for pancreatic cancer primary screening

Comparison of Extensive Protein Fractionation and Repetitive LC-MS/MS Analyses on Depth of Analysis for Complex Proteomes

In-depth, reproducible coverage of complex proteomes is challenging because the complexity of tryptic digests subjected to LC-MS/MS analysis frequently exceeds mass spectrometer analytical capacity, which results in undersampling of data. In this study, we used cancer cell lysates to systematically compare the commonly used GeLC-MS/MS (1-D protein + 1-D peptide separation) method using four repetitive injections (2-D/repetitive) with a 3-D method that included solution isoelectric focusing and involved an equal number of LC-MS/MS runs. The 3-D method detected substantially more unique peptides and proteins, including higher numbers of unique peptides from low-abundance proteins, demonstrating that additional fractionation at the protein level is more effective than repetitive analyses at overcoming LC-MS/MS undersampling. Importantly, more than 90 % of the 2-D/repetitive protein identifications were found in the 3-D method data in a direct protein level comparison, and the reproducibility between data sets increased to greater than 96 % when factors such as database redundancy and use of rigid scoring thresholds were considered. Hence, high reproducibility of complex proteomes, such as human cancer cell lysates, readily can be achieved when using multidimensional separation methods with good depth of analysis