Definition of valid proteomic biomarkers: a bayesian solution

Clinical proteomics is suffering from high hopes generated by reports on apparent biomarkers, most of which could not be later substantiated via validation. This has brought into focus the need for improved methods of finding a panel of clearly defined biomarkers. To examine this problem, urinary proteome data was collected from healthy adult males and females, and analysed to find biomarkers that differentiated between genders. We believe that models that incorporate sparsity in terms of variables are desirable for biomarker selection, as proteomics data typically contains a huge number of variables (peptides) and few samples making the selection process potentially unstable. This suggests the application of a two-level hierarchical Bayesian probit regression model for variable selection which assumes a prior that favours sparseness. The classification performance of this method is shown to improve that of the Probabilistic K-Nearest Neighbour model

Phosphoproteomic Landscaping Identifies Non-canonical cKIT Signaling in Polycythemia Vera Erythroid Progenitors

Although stem cell factor (SCF)/cKIT interaction plays key functions in erythropoiesis, cKIT signaling in human erythroid cells is still poorly defined. To provide new insights into cKIT-mediated erythroid expansion in development and disease, we performed phosphoproteomic profiling of primary erythroid progenitors from adult blood (AB), cord blood (CB), and Polycythemia Vera (PV) at steady-state and upon SCF stimulation. While AB and CB, respectively, activated transient or sustained canonical cKIT-signaling, PV showed a non-canonical signaling including increased mTOR and ERK1 and decreased DEPTOR. Accordingly, screening of FDA-approved compounds showed increased PV sensitivity to JAK, cKIT, and MEK inhibitors. Moreover, differently from AB and CB, in PV the mature 145kDa-cKIT constitutively associated with the tetraspanin CD63 and was not endocytosed upon SCF stimulation, contributing to unrestrained cKIT signaling. These results identify a clinically exploitable variegation of cKIT signaling/metabolism that may contribute to the great erythroid output occurring during development and in PV

Application of analyte harvesting nanoparticle technology to the measurement of urinary HGH in healthy individuals

Urine represents a valuable biofluid for noninvasive measurement of Human Growth Hormone (HGH) secretion. Unfortunately, currently available commercial HGH immunoassays do not achieve the sensitivity needed for urinary HGH measurement in the low picogram per milliliter range, the expected normal concentration range of HGH in urine. A nanotechnology based sample preprocessing step was used to extract and concentrate HGH in urine so that urinary HGH could be measured with a clinical grade standard immunoassay designed for serum (Immulite 1000, Siemens). We applied the nanoparticle enhanced immunoassay to evaluate the baseline value of urinary HGH in a population of healthy young adults (age 18-30, N=33, median 21, M: F=39%:61%, with no reported medical therapies). Nanoparticle sample preprocessing effectively improved the lower limit of detection of the Immulite HGH assay by more than 50 fold, shifting the linear range of the assay to encompass the expected value of urinary HGH. The full process between run and within run CV% was 7.9 and 9.0%, respectively. On 33 healthy volunteers, the 95% reference values for hGH in spot urine normalized to specific gravity were 0.64 - 16.85 pg/mL (0.05-5.82 ng/g creatinine). Nanoparticle preprocessing constitutes a reliable means of measuring urinary HGH with a clinical grade immunoassay, now establishing a normal baseline value for HGH in urine. Nanoparticles can be used to study the kinetics of HGH excretion in urine, and the factors that influence urinary HGH secretion and HGH isoform proportions

BCAR4 induces antioestrogen resistance but sensitises breast cancer to lapatinib

Background: High BCAR4 and ERBB2 mRNA levels in primary breast cancer associate with tamoxifen resistance and poor patient outcome. We determined whether BCAR4 expression sensitises breast cancer cells to lapatinib, and identifies a subgroup of patients who possibly may benefit from ERBB2-targeted therapies despite having tumours with low ERBB2 expression. Methods :Proliferation assays were applied to determine the effect of BCAR4 expression on lapatinib treatment. Changes in cell signalling were quantified with reverse-phase protein microarrays. Quantitative reverse-transcriptase polymerase chain reaction (RT-PCR) of ERBB2 and BCAR4 was performed in 1418 primary breast cancers. Combined BCAR4 and ERBB2 mRNA levels were evaluated for association with progression-free survival (PFS) in 293 oestrogen receptor-α (ER)-positive patients receiving tamoxifen as first-line monotherapy for recurrent disease.Results:BCAR4 expression strongly sensitised ZR-75-1 and MCF7 breast cancer cells to the combination of lapatinib and antioestrogens. Lapatinib interfered with phosphorylation of ERBB2 and its downstream mediators AKT, FAK, SHC, STAT5, and STAT6. Reverse transcriptase-PCR analysis showed that 27.6% of the breast cancers were positive for BCAR4 and 22% expressed also low levels of ERBB2. The clinical significance of combining BCAR4 and ERBB2 mRNA status was underscored by the finding that the group of patients having BCAR4-positive/ERBB2-low-expressing cancers had a shorter PFS on tamoxifen treatment than the BCAR4-negative group. Conclusion :This study shows that BCAR4 expression identifies a subgroup of ER-positive breast cancer patients without overexpression of ERBB2 who have a poor outcome and might benefit from combined ERBB2-targeted and antioestrogen therapy

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

Gain-of-function RHOA mutations promote focal adhesion kinase activation and dependency in diffuse gastric cancer

Diffuse gastric cancer (DGC) is a lethal malignancy lacking effective systemic therapy. Among the most provocative recent results in DGC has been that of highly recurrent missense mutations in the GTPase RHOA. The function of these mutations has remained unresolved. We demonstrate that RHOAY42C, the most common RHOA mutation in DGC, is a gain-of-function oncogenic mutant, and that expression of RHOAY42C with inactivation of the canonical tumor suppressor Cdh1 induces metastatic DGC in a mouse model. Biochemically, RHOAY42C exhibits impaired Y42C GTP hydrolysis and enhances interaction with its effector ROCK. RHOA mutation and Cdh1 loss induce actin/cytoskeletal rearrangements and activity of focal adhesion kinase (FAK), which activates YAP–TAZ, PI3K–AKT, and β-catenin. RHOAY42C murine models were sensitive to FAK inhibition and to combined YAP and PI3K pathway blockade. These results, coupled with sensitivity to FAK inhibition in patient-derived DGC cell lines, nominate FAK as a novel target for these cancers. SIGNIFICANCE: The functional significance of recurrent RHOA mutations in DGC has remained unresolved. Through biochemical studies and mouse modeling of the hotspot RHOAY42C mutation, we establish that these mutations are activating, detail their effects upon cell signaling, and define how RHOA-mediated FAK activation imparts sensitivity to pharmacologic FAK inhibitors

Modeling of protein signaling networks in clinical proteomics

Molecular interactions that underlie pathophysiological states are being elucidated using techniques that profile proteomicend points in cellular systems. Within the field of cancer research, protein interaction networks play pivotal roles in the establishment and maintenance of the hallmarks of malignancy, including cell division, invasion, and migration. Multiple complementary tools enable a multifaceted view of how signal protein pathway alterations contribute to pathophysiological states.One pivotal technique is signal pathway profiling of patient tissue specimens. This microanalysis technology provides a proteomic snapshot at one point in time of cells directly procured from the native context of a tumor micro environment. To study the adaptive patterns of signal pathway events over time, before and after experimental therapy, it is necessary to obtain biopsies from patients before, during, and after therapy. A complementary approach is the profiling of cultured cell lines with and without treatment. Cultured cell models provide the opportunity to study short-term signal changes occurring over minutes to hours. Through this type of system, the effects of particular pharmacological agents may be used to test the effects of signal pathway inhibition or activation on multiple endpoints within a pathway. The complexity of the data generated has necessitated the development of mathematical models for optimal interpretation of interrelated signaling pathways. In combination,clinical proteomic biopsy profiling, tissue culture proteomic profiling, and mathematical modeling synergistically enable a deeper understanding of how protein associations lead to disease states and present new insights into the design of therapeutic regimens