Core-Shell Hydrogel Particles Harvest, Concentrate and Preserve Labile Low Abundance Biomarkers

Background: The blood proteome is thought to represent a rich source of biomarkers for early stage disease detection. Nevertheless, three major challenges have hindered biomarker discovery: a) candidate biomarkers exist at extremely low concentrations in blood; b) high abundance resident proteins such as albumin mask the rare biomarkers; c) biomarkers are rapidly degraded by endogenous and exogenous proteinases. Methodology and Principal Findings: Hydrogel nanoparticles created with a N-isopropylacrylamide based core (365 nm)-shell (167 nm) and functionalized with a charged based bait (acrylic acid) were studied as a technology for addressing all these biomarker discovery problems, in one step, in solution. These harvesting core-shell nanoparticles are designed to simultaneously conduct size exclusion and affinity chromatography in solution. Platelet derived growth factor (PDGF), a clinically relevant, highly labile, and very low abundance biomarker, was chosen as a model. PDGF, spiked in human serum, was completely sequestered from its carrier protein albumin, concentrated, and fully preserved, within minutes by the particles. Particle sequestered PDGF was fully protected from exogenously added tryptic degradation. When the nanoparticles were added to a 1 mL dilute solution of PDGF at non detectable levels (less than 20 picograms per mL) the concentration of the PDGF released from the polymeric matrix of the particles increased within the detection range of ELISA and mass spectrometry. Beyond PDGF, the sequestration and protection from degradation for a series of additional very low abundance and very labile cytokines were verified. Conclusions and Significance: We envision the application of harvesting core-shell nanoparticles to whole blood for concentration and immediate preservation of low abundance and labile analytes at the time of venipuncture. © 2009 Longo et al

Feature selection in the reconstruction of complex network representations of spectral data

Complex networks have been extensively used in the last decade to characterize and analyze complex systems, and they have been recently proposed as a novel instrument for the analysis of spectra extracted from biological samples. Yet, the high number of measurements composing spectra, and the consequent high computational cost, make a direct network analysis unfeasible. We here present a comparative analysis of three customary feature selection algorithms, including the binning of spectral data and the use of information theory metrics. Such algorithms are compared by assessing the score obtained in a classification task, where healthy subjects and people suffering from different types of cancers should be discriminated. Results indicate that a feature selection strategy based on Mutual Information outperforms the more classical data binning, while allowing a reduction of the dimensionality of the data set in two orders of magnitud

Proteomic analysis of nipple aspirate fluid to detect biologic markers of breast cancer.

The early detection of breast cancer is the best means to minimise disease-related mortality. Current screening techniques have limited sensitivity and specificity. Breast nipple aspirate fluid can be obtained noninvasively and contains proteins secreted from ductal and lobular epithelia. Nipple aspirate fluid proteins are breast specific and generally more concentrated than corresponding blood levels. Proteomic analysis of 1 microl of diluted nipple aspirate fluid over a 5-40 kDa range from 20 subjects with breast cancer and 13 with nondiseased breasts identified five differentially expressed proteins. The most sensitive and specific proteins were 6500 and 15 940 Da, found in 75-84% of samples from women with cancer but in only 0-9% of samples from normal women. These findings suggest that (1) differential expression of nipple aspirate fluid proteins exists between women with normal and diseased breasts, and (2) analysis of these proteins may predict the presence of breast cancer

Accurate peak list extraction from proteomic mass spectra for identification and profiling studies

<p>Abstract</p> <p>Background</p> <p>Mass spectrometry is an essential technique in proteomics both to identify the proteins of a biological sample and to compare proteomic profiles of different samples. In both cases, the main phase of the data analysis is the procedure to extract the significant features from a mass spectrum. Its final output is the so-called peak list which contains the mass, the charge and the intensity of every detected biomolecule. The main steps of the peak list extraction procedure are usually preprocessing, peak detection, peak selection, charge determination and monoisotoping operation.</p> <p>Results</p> <p>This paper describes an original algorithm for peak list extraction from low and high resolution mass spectra. It has been developed principally to improve the precision of peak extraction in comparison to other reference algorithms. It contains many innovative features among which a sophisticated method for managing the overlapping isotopic distributions.</p> <p>Conclusions</p> <p>The performances of the basic version of the algorithm and of its optional functionalities have been evaluated in this paper on both SELDI-TOF, MALDI-TOF and ESI-FTICR ECD mass spectra. Executable files of MassSpec, a MATLAB implementation of the peak list extraction procedure for Windows and Linux systems, can be downloaded free of charge for nonprofit institutions from the following web site: <url>http://aimed11.unipv.it/MassSpec</url></p

Protein pathway activation mapping of colorectal metastatic progression reveals metastasis-specific network alterations

The mechanism by which tissue microecology influences invasion and metastasis is largely unknown. Recent studies have indicated differences in the molecular architecture of the metastatic lesion compared to the primary tumor, however, systemic analysis of the alterations within the activated protein signaling network has not been described. Using laser capture microdissection, protein microarray technology, and a unique specimen collection of 34 matched primary colorectal cancers (CRC) and synchronous hepatic metastasis, the quantitative measurement of the total and activated/phosphorylated levels of 86 key signaling proteins was performed. Activation of the EGFR\u2013PDGFR-cKIT network, in addition to PI3K/AKT pathway, was found uniquely activated in the hepatic metastatic lesions compared to the matched primary tumors. If validated in larger study sets, these findings may have potential clinical relevance since many of these activated signaling proteins are current targets for molecularly targeted therapeutics. Thus, these findings could lead to liver metastasis specific molecular therapies for CRC

Low-Dose Vertical Inhibition of the RAF-MEK-ERK Cascade Causes Apoptotic Death of KRAS Mutant Cancers

We address whether combinations with a pan-RAF inhibitor (RAFi) would be effective in KRAS mutant pancreatic ductal adenocarcinoma (PDAC). Chemical library and CRISPR genetic screens identify combinations causing apoptotic anti-tumor activity. The most potent combination, concurrent inhibition of RAF (RAFi) and ERK (ERKi), is highly synergistic at low doses in cell line, organoid, and rat models of PDAC, whereas each inhibitor alone is only cytostatic. Comprehensive mechanistic signaling studies using reverse phase protein array (RPPA) pathway mapping and RNA sequencing (RNA-seq) show that RAFi/ERKi induced insensitivity to loss of negative feedback and system failures including loss of ERK signaling, FOSL1, and MYC; shutdown of the MYC transcriptome; and induction of mesenchymal-to-epithelial transition. We conclude that low-dose vertical inhibition of the RAF-MEK-ERK cascade is an effective therapeutic strategy for KRAS mutant PDAC.Peer reviewe

Inhibition of Notch3 signalling induces rhabdomyosarcoma cell differentiation promoting p38 phosphorylation and p21Cip1 expression and hampers tumour cell growth in vitro and in vivo

Rhabdomyosarcoma (RMS) is a paediatric soft-tissue sarcoma arising from skeletal muscle precursors coexpressing markers of proliferation and differentiation. Inducers of myogenic differentiation suppress RMS tumourigenic phenotype. The Notch target gene HES1 is upregulated in RMS and prevents tumour cell differentiation in a Notch-dependent manner. However, Notch receptors regulating this phenomenon are unknown. In agreement with data in RMS primary tumours, we show here that the Notch3 receptor is overexpressed in RMS cell lines versus normal myoblasts. Notch3-targeted downregulation in RMS cells induces hyper-phosphorylation of p38 and Akt essential for myogenesis, resulting in the differentiation of tumour cells into multinucleated myotubes expressing Myosin Heavy Chain. These phenomena are associated to a marked decrease in HES1 expression, an increase in p21Cip1 level and the accumulation of RMS cells in the G1 phase. HES1-forced overexpression in RMS cells reverses, at least in part, the pro-differentiative effects of Notch3 downregulation. Notch3 depletion also reduces the tumourigenic potential of RMS cells both in vitro and in vivo. These results indicate that downregulation of Notch3 is sufficient to force RMS cells into completing a correct full myogenic program providing evidence that it contributes, partially through HES1 sustained expression, to their malignant phenotype. Moreover, they suggest Notch3 as a novel potential target in human RMS

The significance of PTEN and AKT aberrations in pediatric T-cell acute lymphoblastic leukemia

Background PI3K/AKT pathway mutations are found in T-cell acute lymphoblastic leukemia, but their overall impact and associations with other genetic aberrations is unknown. PTEN mutations have been proposed as secondary mutations that follow NOTCH1-activating mutations and cause cellular resistance to γ-secretase inhibitors. Design and Methods The impact of PTEN, PI3K and AKT aberrations was studied in a genetically well-characterized pediatric T-cell leukemia patient cohort (n=146) treated on DCOG or COALL protocols. Results PTEN and AKT E17K aberrations were detected in 13% and 2% of patients, respectively. Defective PTEN-splicing was identified in incidental cases. Patients without PTEN protein but lacking exon-, splice-, promoter mutations or promoter hypermethylation were present. PTEN/AKTmutations were especially abundant in TAL- or LMO-rearranged leukemia but nearly absent in TLX3-rearranged patients (P=0.03), the opposite to that observed for NOTCH1- activating mutations. Most PTEN/AKT mutant patients either lacked NOTCH1-activating mutations (P=0.006) or had weak NOTCH1-activating mutations (P=0.011), and consequently expressed low intracellular NOTCH1, cMYC and MUSASHI levels. T-cell leukemia patients without PTEN/AKT and NOTCH1-activating mutations fared well, with a cumulative incidence of relapse of only 8% versus 35% for PTEN/AKT and/or NOTCH1-activated patients (P=0.005). Conclusions PI3K/AKT pathway aberrations are present in 18% of pediatric T-cell acute lymphoblastic leukemia patients. Absence of strong NOTCH1-activating mutations in these cases may explain cellular insensitivity to γ-secretase inhibitors