DNA replication stress mediates APOBEC3 family mutagenesis in breast cancer

BACKGROUND: The APOBEC3 family of cytidine deaminases mutate the cancer genome in a range of cancer types. Although many studies have documented the downstream effects of APOBEC3 activity through next-generation sequencing, less is known about their upstream regulation. In this study, we sought to identify a molecular basis for APOBEC3 expression and activation. RESULTS: HER2 amplification and PTEN loss promote DNA replication stress and APOBEC3B activity in vitro and correlate with APOBEC3 mutagenesis in vivo. HER2-enriched breast carcinomas display evidence of elevated levels of replication stress-associated DNA damage in vivo. Chemical and cytotoxic induction of replication stress, through aphidicolin, gemcitabine, camptothecin or hydroxyurea exposure, activates transcription of APOBEC3B via an ATR/Chk1-dependent pathway in vitro. APOBEC3B activation can be attenuated through repression of oncogenic signalling, small molecule inhibition of receptor tyrosine kinase signalling and alleviation of replication stress through nucleoside supplementation. CONCLUSION: These data link oncogene, loss of tumour suppressor gene and drug-induced replication stress with APOBEC3B activity, providing new insights into how cytidine deaminase-induced mutagenesis might be activated in tumourigenesis and limited therapeutically

Pairwise statistical significance of local sequence alignment using multiple parameter sets and empirical justification of parameter set change penalty

Background: Accurate estimation of statistical significance of a pairwise alignment is an important problem in sequence comparison. Recently, a comparative study of pairwise statistical significance with database statistical significance was conducted. In this paper, we extend the earlier work on pairwise statistical significance by incorporating with it the use of multiple parameter sets. Results: Results for a knowledge discovery application of homology detection reveal that using multiple parameter sets for pairwise statistical significance estimates gives better coverage than using a single parameter set, at least at some error levels. Further, the results of pairwise statistical significance using multiple parameter sets are shown to be significantly better than database statistical significance estimates reported by BLAST and PSI-BLAST, and comparable and at times significantly better than SSEARCH. Using non-zero parameter set change penalty values give better performance than zero penalty. Conclusion: The fact that the homology detection performance does not degrade when using multiple parameter sets is a strong evidence for the validity of the assumption that the alignment score distribution follows an extreme value distribution even when using multiple parameter sets. Parameter set change penalty is a useful parameter for alignment using multiple parameter sets. Pairwise statistical significance using multiple parameter sets can be effectively used to determine the relatedness of a (or a few) pair(s) of sequences without performing a time-consuming database search

ELECTROENCEPHALOGRAPHY (EEG) AND ITS USE IN MOTOR LEARNING AND CONTROL

Electroencephalography (EEG) is a non-invasive technique of measuring electric currents generated from active brain regions and is a useful tool for researchers interested in motor control. The study of motor learning and control seeks to understand the way the brain understands, plans and executes movement both physical and imagined. Thus, the purpose of this study was to better understand the ways in which electroencephalography can be used to measure regions of the brain involved with motor control and learning. For this purpose, two independent studies were completed using EEG to monitor brain activity during both executed and imagined actions. The first study sought to understand the cognitive demand of altering a running gait and provides EEG evidence of motor learning. 13 young healthy runners participated in a 6-week in-field gait-retraining program that altered running gait by increasing step rate (steps per minute) by 5-10%. EEG was collected while participants ran on a treadmill with their original gait as a baseline measurement. After the baseline collection, participants ran for one minute at the same speed with a 5-10% step rate increase while EEG was collected. Participants then participated in a 6-week in-field gait-retraining program in which they received bandwith feedback while running in order to learn the new gait. After completing the 6-week training protocol, participants returned to the lab for post training EEG collection while running with the new step rate. Power spectral density plots were generated to measure frequency band power in all gait-retraining phases. Results in the right prefrontal cortex showed a significant increase in beta (13-30 Hz) while initially running with the new gait compared to the baseline step rate. Previous work suggests the right prefrontal cortex is involved with the inhibition of a previously learned behavior and thus, our results suggest an increase in cognitive load to inhibit the previous full stride motion. After training, this increase in beta over the right prefrontal cortex decreased, suggesting motor adaptations had occurred as a result of motor learning. These results give promising evidence for a new method of ensuring permanent changes in performance that will benefit rehabilitation and athletic performance training programs. The second study in this project sought to understand differences in right and left-handers as they mentally simulate movement. 24 right and left-handed individuals (12 right-handers, 12 left-handers) were shown pictures of individual hands on a screen while EEG was collected. Previous research has shown than while solving this task, participants mentally rotate a mental representation of their own hand to determine the handedness of the image. Event-related potential results showed that right-handers had an earlier and greater activation in the parietal regions than left-handers, whereas left-handers had a later and greater activation in the motor related brain regions compared to right-handers. These results suggest differing strategies while mentally solving motor related tasks between right and left-handers. We speculate this is a result of left-handers' need to adapt to a majorly right-hand dominant environment. Both these studies show the benefits of using EEG to understand the motor system in physically executed and imagined actions

Local sequence alignments statistics: deviations from Gumbel statistics in the rare-event tail

<p>Abstract</p> <p>Background</p> <p>The optimal score for ungapped local alignments of infinitely long random sequences is known to follow a Gumbel extreme value distribution. Less is known about the important case, where gaps are allowed. For this case, the distribution is only known empirically in the high-probability region, which is biologically less relevant.</p> <p>Results</p> <p>We provide a method to obtain numerically the biologically relevant rare-event tail of the distribution. The method, which has been outlined in an earlier work, is based on generating the sequences with a parametrized probability distribution, which is biased with respect to the original biological one, in the framework of Metropolis Coupled Markov Chain Monte Carlo. Here, we first present the approach in detail and evaluate the convergence of the algorithm by considering a simple test case. In the earlier work, the method was just applied to one single example case. Therefore, we consider here a large set of parameters:</p> <p>We study the distributions for protein alignment with different substitution matrices (BLOSUM62 and PAM250) and affine gap costs with different parameter values. In the logarithmic phase (large gap costs) it was previously assumed that the Gumbel form still holds, hence the Gumbel distribution is usually used when evaluating p-values in databases. Here we show that for all cases, provided that the sequences are not too long (<it>L </it>> 400), a "modified" Gumbel distribution, i.e. a Gumbel distribution with an additional Gaussian factor is suitable to describe the data. We also provide a "scaling analysis" of the parameters used in the modified Gumbel distribution. Furthermore, via a comparison with BLAST parameters, we show that significance estimations change considerably when using the true distributions as presented here. Finally, we study also the distribution of the sum statistics of the <it>k </it>best alignments.</p> <p>Conclusion</p> <p>Our results show that the statistics of gapped and ungapped local alignments deviates significantly from Gumbel in the rare-event tail. We provide a Gaussian correction to the distribution and an analysis of its scaling behavior for several different scoring parameter sets, which are commonly used to search protein data bases. The case of sum statistics of <it>k </it>best alignments is included.</p

Potassium Starvation in Yeast: Mechanisms of Homeostasis Revealed by Mathematical Modeling

The intrinsic ability of cells to adapt to a wide range of environmental conditions is a fundamental process required for survival. Potassium is the most abundant cation in living cells and is required for essential cellular processes, including the regulation of cell volume, pH and protein synthesis. Yeast cells can grow from low micromolar to molar potassium concentrations and utilize sophisticated control mechanisms to keep the internal potassium concentration in a viable range. We developed a mathematical model for Saccharomyces cerevisiae to explore the complex interplay between biophysical forces and molecular regulation facilitating potassium homeostasis. By using a novel inference method (“the reverse tracking algorithm”) we predicted and then verified experimentally that the main regulators under conditions of potassium starvation are proton fluxes responding to changes of potassium concentrations. In contrast to the prevailing view, we show that regulation of the main potassium transport systems (Trk1,2 and Nha1) in the plasma membrane is not sufficient to achieve homeostasis

Chromosomal Instability Confers Intrinsic Multidrug Resistance

Aneuploidy is associated with poor prognosis in solid tumors. Spontaneous chromosome missegregation events in aneuploid cells promote chromosomal instability (CIN) that may contribute to the acquisition of multidrug resistance in vitro and heighten risk for tumor relapse in animal models. Identification of distinct therapeutic agents that target tumor karyotypic complexity has important clinical implications. To identify distinct therapeutic approaches to specifically limit the growth of CIN tumors, we focused on a panel of colorectal cancer (CRC) cell lines, previously classified as either chromosomally unstable (CIN+) or diploid/near-diploid (CIN-), and treated them individually with a library of kinase inhibitors targeting components of signal transduction, cell cycle, and transmembrane receptor signaling pathways. CIN+ cell lines displayed significant intrinsic multidrug resistance compared with CIN- cancer cell lines, and this seemed to be independent of somatic mutation status and proliferation rate. Confirming the association of CIN rather than ploidy status with multidrug resistance, tetraploid isogenic cells that had arisen from diploid cell lines displayed lower drug sensitivity than their diploid parental cells only with increasing chromosomal heterogeneity and isogenic cell line models of CIN+ displayed multidrug resistance relative to their CIN- parental cancer cell line derivatives. In a meta-analysis of CRC outcome following cytotoxic treatment, CIN+ predicted worse progression-free or disease-free survival relative to patients with CIN- disease. Our results suggest that stratifying tumor responses according to CIN status should be considered within the context of clinical trials to minimize the confounding effects of tumor CIN status on drug sensitivity. Cancer Res; 71(5); 1858-70. (c) 2011 AACR

Chromosomal instability determines taxane sensitivity - supplementary materials

Microtubule-stabilizing (MTS) agents, such as taxanes, are important chemotherapeutics with a poorly understood mechanism of action. We identified a set of genes repressed in multiple cell lines in response to MTS agents and observed that these genes are overexpressed in tumors exhibiting chromosomal instability (CIN). Silencing 22/50 of these genes, many of which are involved in DNA repair, caused cancer cell death, suggesting that these genes are involved in the survival of aneuploid cells. Overexpression of these ‘‘CIN-survival’’ genes is associated with poor outcome in estrogen receptor–positive breast cancer and occurs frequently in basal-like and Her2-positive cases. In diploid cells, but not in chromosomally unstable cells, paclitaxel causes repression of CIN-survival genes, followed by cell death. In the OV01 ovarian cancer clinical trial, a high level of CIN was associated with taxane resistance but carboplatin sensitivity, indicating that CIN may determine MTS response in vivo. Thus, pretherapeutic assessment of CIN may optimize treatment stratification and clinical trial design using these agents

Mutational signatures in TN1 and ER2, and ctDNA assays in ER2.

<p>(A) Reconstruction of mutational context plot with deconstructSigs for TN1 using COSMIC signatures 17, 24, and 29. 5′ and 3′ nucleotides are indicated by colour code on <i>x</i>-axis. (B) Contribution of each signature per sample. (C) Subclonal phylogeny for TN1 showing private and public subclones. Private subclones in dark blue. Mutations arising from signature 17 represented in pink along branches. (D) Reconstruction of mutational context for ER2 using APOBEC signatures 2 and 13 detected with deconstructSigs, with origin of key mutations overlaid. Colour codings as for (A). (E) Subclonal phylogeny for ER2, with private subclones in dark blue. (F) Bar charts show ctDNA results at time of liver biopsy and later at death. <i>y</i>-axis unit is copies per millilitre.</p