Modeling the evolution space of breakage fusion bridge cycles with a stochastic folding process.

Breakage-fusion-bridge cycles in cancer arise when a broken segment of DNA is duplicated and an end from each copy joined together. This structure then 'unfolds' into a new piece of palindromic DNA. This is one mechanism responsible for the localised amplicons observed in cancer genome data. Here we study the evolution space of breakage-fusion-bridge structures in detail. We firstly consider discrete representations of this space with 2-d trees to demonstrate that there are [Formula: see text] qualitatively distinct evolutions involving [Formula: see text] breakage-fusion-bridge cycles. Secondly we consider the stochastic nature of the process to show these evolutions are not equally likely, and also describe how amplicons become localized. Finally we highlight these methods by inferring the evolution of breakage-fusion-bridge cycles with data from primary tissue cancer samples.

Exact, time-independent estimation of clone size distributions in normal and mutated cells.

Biological tools such as genetic lineage tracing, three-dimensional confocal microscopy and next-generation DNA sequencing are providing new ways to quantify the distribution of clones of normal and mutated cells. Understanding population-wide clone size distributions in vivo is complicated by multiple cell types within observed tissues, and overlapping birth and death processes. This has led to the increased need for mathematically informed models to understand their biological significance. Standard approaches usually require knowledge of clonal age. We show that modelling on clone size independent of time is an alternative method that offers certain analytical advantages; it can help parametrize these models, and obtain distributions for counts of mutated or proliferating cells, for example. When applied to a general birth-death process common in epithelial progenitors, this takes the form of a gambler's ruin problem, the solution of which relates to counting Motzkin lattice paths. Applying this approach to mutational processes, alternative, exact, formulations of classic Luria-Delbrück-type problems emerge. This approach can be extended beyond neutral models of mutant clonal evolution. Applications of these approaches are twofold. First, we resolve the probability of progenitor cells generating proliferating or differentiating progeny in clonal lineage tracing experiments in vivo or cell culture assays where clone age is not known. Second, we model mutation frequency distributions that deep sequencing of subclonal samples produce.

LKB1/KRAS mutant lung cancers constitute a genetic subset of NSCLC with increased sensitivity to MAPK and mTOR signalling inhibition.

LKB1/STK11 is a multitasking tumour suppressor kinase. Germline inactivating mutations of the gene are responsible for the Peutz-Jeghers hereditary cancer syndrome. It is also somatically inactivated in approximately 30% of non-small-cell lung cancer (NSCLC). Here, we report that LKB1/KRAS mutant NSCLC cell lines are sensitive to the MEK inhibitor CI-1040 shown by a dose-dependent reduction in proliferation rate, whereas LKB1 and KRAS mutations alone do not confer similar sensitivity. We show that this subset of NSCLC is also sensitised to the mTOR inhibitor rapamycin. Importantly, the data suggest that LKB1/KRAS mutant NSCLCs are a genetically and functionally distinct subset and further suggest that this subset of lung cancers might afford an opportunity for exploitation of anti-MAPK/mTOR-targeted therapies.

AutoCSA, an algorithm for high throughput DNA sequence variant detection in cancer genomes.

UNLABELLED: The undertaking of large-scale DNA sequencing screens for somatic variants in human cancers requires accurate and rapid processing of traces for variants. Due to their often aneuploid nature and admixed normal tissue, heterozygous variants found in primary cancers are often subtle and difficult to detect. To address these issues, we have developed a mutation detection algorithm, AutoCSA, specifically optimized for the high throughput screening of cancer samples. AVAILABILITY: http://www.sanger.ac.uk/genetics/CGP/Software/AutoCSA.

Reversal of stress-induced analgesia by apomorphine, but not by amphetamine.

Acute exposure to severe stressors induce profound analgesia as well as depleting catecholamine levels. The present study examined whether d-amphetamine and apomorphine, agents which increase catecholamine availability, would alter the analgesic effectiveness of cold-water swims (CWS) and 2-deoxy-D-glucose (2-DG) as measured by an operant liminal escape procedure. Two groups of 10 rats each were tested to determine alterations in liminal escape threshold functions following amphetamine at doses of 0.25, 0.5, 1, 2 mg/kg and following apomorphine at doses of 0.025, 0.05, 0.1, 0.2 mg/kg. Half of the amphetamine and half of the apomorphine groups were tested across their respective dose ranges for the drug effects upon CWS analgesia. The remaining animals in each group received 2-DG (600 mg/kg IP) alone followed by 2-DG paired with each stimulant dose. No dose of amphetamine or apomorphine alone altered escape thresholds. While amphetamine produced slight potentiations of 2-DG analgesia at the two low doses, apomorphine at the 0.05 and 0.1 mg/kg doses returned CWS and 2-DG analgesia to within normal placebo values. These results provide indirect evidence for a role for brain norepinephrine and dopamine in stress-induced analgesia, and these data are discussed with respect to catecholamine involvement in pain-inhibitory processes.