SNP array profiling of childhood adrenocortical tumors reveals distinct pathways of tumorigenesis and highlights candidate driver genes

Childhood adrenocortical tumors (ACT) are rare malignancies, except in southern Brazil, where a higher incidence rate is associated to a high frequency of the founder R337H TP53 mutation. To date, copy number alterations in these tumors have only been analyzed by low-resolution comparative genomic hybridization.

A Faster Circular Binary Segmentation Algorithm for the Analysis of Array CGH Data

Motivation: Array CGH technologies enable the simultaneous measurement of DNA copy number for thousands of sites on a genome. We developed the circular binary segmentation (CBS) algorithm to divide the genome into regions of equal copy number (Olshen {\it et~al}, 2004). The algorithm tests for change-points using a maximal $t$-statistic with a permutation reference distribution to obtain the corresponding $p$-value. The number of computations required for the maximal test statistic is $O(N^2),$ where $N$ is the number of markers. This makes the full permutation approach computationally prohibitive for the newer arrays that contain tens of thousands markers and highlights the need for a faster. algorithm. Results: We present a hybrid approach to obtain the $p$-value of the test statistic in linear time. We also introduce a rule for stopping early when there is strong evidence for the presence of a change. We show through simulations that the hybrid approach provides a substantial gain in speed with only a negligible loss in accuracy and that the stopping rule further increases speed. We also present the analysis of array CGH data from a breast cancer cell line to show the impact of the new approaches on the analysis of real data. Availability: An R (R Development Core Team, 2006) version of the CBS algorithm has been implemented in the ``DNAcopy'' package of the Bioconductor project (Gentleman {\it et~al}, 2004). The proposed hybrid method for the $p$-value is available in version 1.2.1 or higher and the stopping rule for declaring a change early is available in version 1.5.1 or higher.

Novel sst2-selective somatostatin agonists. Three-dimensional consensus structure by NMR

The 3D NMR structures of six octapeptide agonist analogues of somatostatin (SRIF) in the free form are described. These analogues, with the basic sequence H-DPhe/Phe2-c[Cys3-Xxx7-DTrp8-Lys9-Thr10-Cys14]-Thr-NH2 (the numbering refers to the position in native SRIF), with Xxx7 being Ala/Aph, exhibit potent and highly selective binding to human SRIF type 2 (sst2) receptors. The backbone of these sst2-selective analogues have the usual type-II' beta-turn reported in the literature for sst2/3/5-subtype-selective analogues. Correlating the biological results and NMR studies led to the identification of the side chains of DPhe2, DTrp8, and Lys9 as the necessary components of the sst2 pharmacophore. This is the first study to show that the aromatic ring at position 7 (Phe7) is not critical for sst2 binding and that it plays an important role in sst3 and sst5 binding. This pharmacophore is, therefore, different from that proposed by others for sst2/3/5 analogues.

Conformational analysis of a potent SSTR3-selective somatostatin analogue by NMR in water solution

The three-dimensional structure of a potent SSTR3-selective analogue of somatostatin, cyclo(3-14)H-Cys(3)-Phe(6)-Tyr(7)-D-Agl(8)(N(beta) Me, 2-naphthoyl)-Lys(9)-Thr(10)-Phe(11)-Cys(14)-OH (des-AA(1, 2, 4, 5, 12, 13)[Tyr(7), D-Agl(8)(N(beta) Me, 2-naphthoyl)]-SRIF) (peptide 1) has been determined by (1)H NMR in water and molecular dynamics (MD) simulations. The peptide exists in two conformational isomers differing mainly by the cis/trans isomerization of the side chain in residue 8. The structure of 1 is compared with the consensus structural motifs of other somatostatin analogues that bind predominantly to SSTR1, SSTR2/SSTR5 and SSTR4 receptors, and to the 3D structure of a non-selective SRIF analogue, cyclo(3-14)H-Cys(3)-Phe(6)-Tyr(7)-D-2Nal(8)-Lys(9)-Thr(10)-Phe(11)-Cys(14)-OH (des-AA(1, 2, 4, 5, 12, 13)[Tyr(7), D-2Nal(8)]-SRIF) (peptide 2). The structural determinant factors that could explain selectivity of peptide 1 for SSTR3 receptors are discussed.

Detection of erythropoietin in exhaled breath condensate of nonhypoxic subjects using a multiplex bead array

As a noninvasive method, exhaled breath condensate (EBC) has gained importance to improve monitoring of lung diseases and to detect biomarkers. The aim of the study was to investigate, whether erythropoietin (EPO) is detectable in EBC. EBC was collected from 22 consecutive patients as well as from healthy individuals. Using a multiplex fluorescent bead immunoassay, we detected EPO in EBC, as well as tumour necrosis factor-alpha (TNF-alpha) in 13 out of 22 patients simultaneously (EPO 0.21 +/- 0.03 in U/mL and TNF-alpha 34.6 +/- 4.2 in pg/mL, mean +/- SEM). No significant differences for EPO levels or correlation between EPO and TNF-alpha were found but TNF-alpha was significantly higher in patients with chronic obstructive pulmonary disease (COPD) than in non-COPD (obstructive sleep apnoea, OSA, and lung healthy patients). This is the first report of detection of EPO in EBC. Due to the small study size more data is needed to clarify the role of EPO in EBC.

Bayesian Hidden Markov Modeling of Array CGH Data

Genomic alterations have been linked to the development and progression of cancer. The technique of Comparative Genomic Hybridization (CGH) yields data consisting of fluorescence intensity ratios of test and reference DNA samples. The intensity ratios provide information about the number of copies in DNA. Practical issues such as the contamination of tumor cells in tissue specimens and normalization errors necessitate the use of statistics for learning about the genomic alterations from array-CGH data. As increasing amounts of array CGH data become available, there is a growing need for automated algorithms for characterizing genomic profiles. Specifically, there is a need for algorithms that can identify gains and losses in the number of copies based on statistical considerations, rather than merely detect trends in the data. We adopt a Bayesian approach, relying on the hidden Markov model to account for the inherent dependence in the intensity ratios. Posterior inferences are made about gains and losses in copy number. Localized amplifications (associated with oncogene mutations) and deletions (associated with mutations of tumor suppressors) are identified using posterior probabilities. Global trends such as extended regions of altered copy number are detected. Since the posterior distribution is analytically intractable, we implement a Metropolis-within-Gibbs algorithm for efficient simulation-based inference. Publicly available data on pancreatic adenocarcinoma, glioblastoma multiforme and breast cancer are analyzed, and comparisons are made with some widely-used algorithms to illustrate the reliability and success of the technique.