Mechanism-related circulating proteins as biomarkers for clinical outcome in patients with unresectable hepatocellular carcinoma receiving sunitinib

<p>Abstract</p> <p>Background</p> <p>Several proteins that promote angiogenesis are overexpressed in hepatocellular carcinoma (HCC) and have been implicated in disease pathogenesis. Sunitinib has antiangiogenic activity and is an oral multitargeted inhibitor of vascular endothelial growth factor receptors (VEGFRs)-1, -2, and -3, platelet-derived growth factor receptors (PDGFRs)-α and -β, stem-cell factor receptor (KIT), and other tyrosine kinases. In a phase II study of sunitinib in advanced HCC, we evaluated the plasma pharmacodynamics of five proteins related to the mechanism of action of sunitinib and explored potential correlations with clinical outcome.</p> <p>Methods</p> <p>Patients with advanced HCC received a starting dose of sunitinib 50 mg/day administered orally for 4 weeks on treatment, followed by 2 weeks off treatment. Plasma samples from 37 patients were obtained at baseline and during treatment and were analyzed for vascular endothelial growth factor (VEGF)-A, VEGF-C, soluble VEGFR-2 (sVEGFR-2), soluble VEGFR-3 (sVEGFR-3), and soluble KIT (sKIT).</p> <p>Results</p> <p>At the end of the first sunitinib treatment cycle, plasma VEGF-A levels were significantly increased relative to baseline, while levels of plasma VEGF-C, sVEGFR-2, sVEGFR-3, and sKIT were significantly decreased. Changes from baseline in VEGF-A, sVEGFR-2, and sVEGFR-3, but not VEGF-C or sKIT, were partially or completely reversed during the first 2-week off-treatment period. High levels of VEGF-C at baseline were significantly associated with Response Evaluation Criteria in Solid Tumors (RECIST)-defined disease control, prolonged time to tumor progression (TTP), and prolonged overall survival (OS). Baseline VEGF-C levels were an independent predictor of TTP by multivariate analysis. Changes from baseline in VEGF-A and sKIT at cycle 1 day 14 or cycle 2 day 28, and change in VEGF-C at the end of the first off-treatment period, were significantly associated with both TTP and OS, while change in sVEGFR-2 at cycle 1 day 28 was an independent predictor of OS.</p> <p>Conclusions</p> <p>Baseline plasma VEGF-C levels predicted disease control (based on RECIST) and were positively associated with both TTP and OS in this exploratory analysis, suggesting that this VEGF family member may have utility in predicting clinical outcome in patients with HCC who receive sunitinib.</p> <p>Trial registration</p> <p>ClinicalTrials.gov: <a href="http://www.clinicaltrials.gov/ct2/show/NCT00247676">NCT00247676</a></p

Amphiregulin Mediates Estrogen, Progesterone, and EGFR Signaling in the Normal Rat Mammary Gland and in Hormone-Dependent Rat Mammary Cancers

Both estrogen (E) and progesterone (P) are implicated in the etiology of human breast cancer. Defining their mechanisms of action, particularly in vivo, is relevant to the prevention and therapy of breast cancer. We investigated the molecular and cellular mechanisms of E and/or P-induced in vivo proliferation, in the normal rat mammary gland and in hormone-dependent rat mammary cancers which share many characteristics with the normal human breast and hormone-dependent breast cancers. We show that E+P treatment induced significantly greater proliferation in both the normal gland and mammary cancers compared to E alone. In both the normal gland and tumors, E+P-induced proliferation was mediated through the increased production of amphiregulin (Areg), an epidermal growth factor receptor (EGFR) ligand, and the activation of intracellular signaling pathways (Erk, Akt, JNK) downstream of EGFR that regulate proliferation. In vitro experiments using rat primary mammary organoids or T47D breast cancer cells confirmed that Areg and the synthetic progestin, R5020, synergize to promote cell proliferation through EGFR signaling. Iressa, an EGFR inhibitor, effectively blocked this proliferation. These results indicate that mediators of cross talk between E, P, and EGFR pathways may be considered as relevant molecular targets for the therapy of hormone-dependent breast cancers, especially in premenopausal women

Mobile element insertions in rare diseases: a comparative benchmark and reanalysis of 60,000 exome samples

Mobile element insertions (MEIs) are a known cause of genetic disease but have been underexplored due to technical limitations of genetic testing methods. Various bioinformatic tools have been developed to identify MEIs in Next Generation Sequencing data. However, most tools have been developed specifically for genome sequencing (GS) data rather than exome sequencing (ES) data, which remains more widely used for routine diagnostic testing. In this study, we benchmarked six MEI detection tools (ERVcaller, MELT, Mobster, SCRAMble, TEMP2 and xTea) on ES data and on GS data from publicly available genomic samples (HG002, NA12878). For all the tools we evaluated sensitivity and precision of different filtering strategies. Results show that there were substantial differences in tool performance between ES and GS data. MELT performed best with ES data and its combination with SCRAMble increased substantially the detection rate of MEIs. By applying both tools to 10,890 ES samples from Solve-RD and 52,624 samples from Radboudumc we were able to diagnose 10 patients who had remained undiagnosed by conventional ES analysis until now. Our study shows that MELT and SCRAMble can be used reliably to identify clinically relevant MEIs in ES data. This may lead to an additional diagnosis for 1 in 3000 to 4000 patients in routine clinical ES

Persistent inequalities in 90-day colon cancer mortality: an English cohort study.

BACKGROUND: Variation in colon cancer mortality occurring shortly after diagnosis is widely reported between socio-economic status (SES) groups: we investigated the role of different prognostic factors in explaining variation in 90-day mortality. METHODS: National cancer registry data were linked with national clinical audit data and Hospital Episode Statistics records for 69 769 adults diagnosed with colon cancer in England between January 2010 and March 2013. By gender, logistic regression was used to estimate the effects of SES, age and stage at diagnosis, comorbidity and surgical treatment on probability of death within 90 days from diagnosis. Multiple imputations accounted for missing stage. We predicted conditional probabilities by prognostic factor patterns and estimated the effect of SES (deprivation) from the difference between deprivation-specific average predicted probabilities. RESULTS: Ninety-day probability of death rose with increasing deprivation, even after accounting for the main prognostic factors. When setting the deprivation level to the least deprived group for all patients and keeping all other prognostic factors as observed, the differences between deprivation-specific averaged predicted probabilities of death were greatly reduced but persisted. Additional analysis suggested stage and treatment as potential contributors towards some of these inequalities. CONCLUSIONS: Further examination of delayed diagnosis, access to treatment and post-operative care by deprivation group may provide additional insights into understanding deprivation disparities in mortality

Rapidity and Centrality Dependence of Proton and Anti-proton Production from Au+Au Collisions at sqrt(sNN) = 130GeV

We report on the rapidity and centrality dependence of proton and anti-proton transverse mass distributions from Au+Au collisions at sqrt(sNN) = 130GeV as measured by the STAR experiment at RHIC. Our results are from the rapidity and transverse momentum range of |y|<0.5 and 0.35 <p_t<1.00GeV/c. For both protons and anti-protons, transverse mass distributions become more convex from peripheral to central collisions demonstrating characteristics of collective expansion. The measured rapidity distributions and the mean transverse momenta versus rapidity are flat within |y|<0.5. Comparisons of our data with results from model calculations indicate that in order to obtain a consistent picture of the proton(anti-proton) yields and transverse mass distributions the possibility of pre-hadronic collective expansion may have to be taken into account.Comment: 4 pages, 3 figures, 1 table, submitted to PR

Seasonal Changes in Colour: A Comparison of Structural, Melanin- and Carotenoid-Based Plumage Colours

Plumage coloration is important for bird communication, most notably in sexual signalling. Colour is often considered a good quality indicator, and the expression of exaggerated colours may depend on individual condition during moult. After moult, plumage coloration has been deemed fixed due to the fact that feathers are dead structures. Still, many plumage colours change after moult, although whether this affects signalling has not been sufficiently assessed.) displaying various coloration types (melanin-, carotenoid-based and structural). Birds were caught regularly during three years to measure plumage reflectance. We used models of avian colour vision to derive two variables, one describing chromatic and the other achromatic variation over the year that can be compared in magnitude among different colour types. All studied plumage patches but one (yellow breast of the blue tit) showed significant chromatic changes over the year, although these were smaller than for a typical dynamic trait (bill colour). Overall, structural colours showed a reduction in relative reflectance at shorter wavelengths, carotenoid-based colours the opposite pattern, while no general pattern was found for melanin-based colours. Achromatic changes were also common, but there were no consistent patterns of change for the different types of colours.Changes of plumage coloration independent of moult are probably widespread; they should be perceivable by birds and have the potential to affect colour signalling

Progesterone Receptor Activates Msx2 Expression by Downregulating TNAP/Akp2 and Activating the Bmp Pathway in EpH4 Mouse Mammary Epithelial Cells

Previously we demonstrated that EpH4 mouse mammary epithelial cells induced the homeobox transcription factor Msx2 either when transfected with the progesterone receptor (PR) or when treated with Bmp2/4. Msx2 upregulation was unaffected by Wnt inhibitors s-FRP or Dkk1, but was inhibited by the Bmp antagonist Noggin. We therefore hypothesized that PR signaling to Msx2 acts through the Bmp receptor pathway. Herein, we confirm that transcripts for Alk2/ActR1A, a non-canonical BmpR Type I, are upregulated in mammary epithelial cells overexpressing PR (EpH4-PR). Increased phosphorylation of Smads 1,5, 8, known substrates for Alk2 and other BmpR Type I proteins, was observed as was their translocation to the nucleus in EpH4-PR cells. Analysis also showed that Tissue Non-Specific Alkaline Phosphatase (TNAP/Akp2) was also found to be downregulated in EpH4-PR cells. When an Akp2 promoter-reporter construct containing a ½PRE site was transfected into EpH4-PR cells, its expression was downregulated. Moreover, siRNA mediated knockdown of Akp2 increased both Alk2 and Msx2 expression. Collectively these data suggest that PR inhibition of Akp2 results in increased Alk2 activity, increased phosphorylation of Smads 1,5,8, and ultimately upregulation of Msx2. These studies imply that re-activation of the Akp2 gene could be helpful in downregulating aberrant Msx2 expression in PR+ breast cancers

An Extended Gene Protein/Products Boolean Network Model Including Post-Transcriptional Regulation

Background: Networks Biology allows the study of complex interactions between biological systems using formal, well structured, and computationally friendly models. Several different network models can be created, depending on the type of interactions that need to be investigated. Gene Regulatory Networks (GRN) are an effective model commonly used to study the complex regulatory mechanisms of a cell. Unfortunately, given their intrinsic complexity and non discrete nature, the computational study of realistic-sized complex GRNs requires some abstractions. Boolean Networks (BNs), for example, are a reliable model that can be used to represent networks where the possible state of a node is a boolean value (0 or 1). Despite this strong simplification, BNs have been used to study both structural and dynamic properties of real as well as randomly generated GRNs. Results: In this paper we show how it is possible to include the post-transcriptional regulation mechanism (a key process mediated by small non-coding RNA molecules like the miRNAs) into the BN model of a GRN. The enhanced BN model is implemented in a software toolkit (EBNT) that allows to analyze boolean GRNs from both a structural and a dynamic point of view. The open-source toolkit is compatible with available visualization tools like Cytoscape and allows to run detailed analysis of the network topology as well as of its attractors, trajectories, and state-space. In the paper, a small GRN built around the mTOR gene is used to demonstrate the main capabilities of the toolkit. Conclusions: The extended model proposed in this paper opens new opportunities in the study of gene regulation. Several of the successful researches done with the support of BN to understand high-level characteristics of regulatory networks, can now be improved to better understand the role of post-transcriptional regulation for example as a network-wide noise-reduction or stabilization mechanism