An integrative multi-dimensional genetic and epigenetic strategy to identify aberrant genes and pathways in cancer

<p>Abstract</p> <p>Background</p> <p>Genomics has substantially changed our approach to cancer research. Gene expression profiling, for example, has been utilized to delineate subtypes of cancer, and facilitated derivation of predictive and prognostic signatures. The emergence of technologies for the high resolution and genome-wide description of genetic and epigenetic features has enabled the identification of a multitude of causal DNA events in tumors. This has afforded the potential for large scale integration of genome and transcriptome data generated from a variety of technology platforms to acquire a better understanding of cancer.</p> <p>Results</p> <p>Here we show how multi-dimensional genomics data analysis would enable the deciphering of mechanisms that disrupt regulatory/signaling cascades and downstream effects. Since not all gene expression changes observed in a tumor are causal to cancer development, we demonstrate an approach based on multiple concerted disruption (MCD) analysis of genes that facilitates the rational deduction of aberrant genes and pathways, which otherwise would be overlooked in single genomic dimension investigations.</p> <p>Conclusions</p> <p>Notably, this is the first comprehensive study of breast cancer cells by parallel integrative genome wide analyses of DNA copy number, LOH, and DNA methylation status to interpret changes in gene expression pattern. Our findings demonstrate the power of a multi-dimensional approach to elucidate events which would escape conventional single dimensional analysis and as such, reduce the cohort sample size for cancer gene discovery.</p

A response to Yu et al. "A forward-backward fragment assembling algorithm for the identification of genomic amplification and deletion breakpoints using high-density single nucleotide polymorphism (SNP) array", BMC Bioinformatics 2007, 8: 145

<p>Abstract</p> <p>Background</p> <p>Yu et al. (BMC Bioinformatics 2007,8: 145+) have recently compared the performance of several methods for the detection of genomic amplification and deletion breakpoints using data from high-density single nucleotide polymorphism arrays. One of the methods compared is our non-homogenous Hidden Markov Model approach. Our approach uses Markov Chain Monte Carlo for inference, but Yu et al. ran the sampler for a severely insufficient number of iterations for a Markov Chain Monte Carlo-based method. Moreover, they did not use the appropriate reference level for the non-altered state.</p> <p>Methods</p> <p>We rerun the analysis in Yu et al. using appropriate settings for both the Markov Chain Monte Carlo iterations and the reference level. Additionally, to show how easy it is to obtain answers to additional specific questions, we have added a new analysis targeted specifically to the detection of breakpoints.</p> <p>Results</p> <p>The reanalysis shows that the performance of our method is comparable to that of the other methods analyzed. In addition, we can provide probabilities of a given spot being a breakpoint, something unique among the methods examined.</p> <p>Conclusion</p> <p>Markov Chain Monte Carlo methods require using a sufficient number of iterations before they can be assumed to yield samples from the distribution of interest. Running our method with too small a number of iterations cannot be representative of its performance. Moreover, our analysis shows how our original approach can be easily adapted to answer specific additional questions (e.g., identify edges).</p

Pointed Wings, Low Wingloading and Calm Air Reduce Migratory Flight Costs in Songbirds

Migratory bird, bat and insect species tend to have more pointed wings than non-migrants. Pointed wings and low wingloading, or body mass divided by wing area, are thought to reduce energy consumption during long-distance flight, but these hypotheses have never been directly tested. Furthermore, it is not clear how the atmospheric conditions migrants encounter while aloft affect their energy use; without such information, we cannot accurately predict migratory species' response(s) to climate change. Here, we measured the heart rates of 15 free-flying Swainson's Thrushes (Catharus ustulatus) during migratory flight. Heart rate, and therefore rate of energy expenditure, was positively associated with individual variation in wingtip roundedness and wingloading throughout the flights. During the cruise phase of the flights, heart rate was also positively associated with wind speed but not wind direction, and negatively but not significantly associated with large-scale atmospheric stability. High winds and low atmospheric stability are both indicative of the presence of turbulent eddies, suggesting that birds may be using more energy when atmospheric turbulence is high. We therefore suggest that pointed wingtips, low wingloading and avoidance of high winds and turbulence reduce flight costs for small birds during migration, and that climate change may have the strongest effects on migrants' in-flight energy use if it affects the frequency and/or severity of high winds and atmospheric instability

A new classification method using array Comparative Genome Hybridization data, based on the concept of Limited Jumping Emerging Patterns

<p>Abstract</p> <p>Background</p> <p>Classification using aCGH data is an important and insufficiently investigated problem in bioinformatics. In this paper we propose a new classification method of DNA copy number data based on the concept of limited Jumping Emerging Patterns. We present the comparison of our limJEPClassifier to SVM which is considered the most successful classifier in the case of high-throughput data.</p> <p>Results</p> <p>Our results revealed that the classification performance using limJEPClassifier is significantly higher than other methods. Furthermore, we show that application of the limited JEP's can significantly improve classification, when strongly unbalanced data are given.</p> <p>Conclusion</p> <p>Nowadays, aCGH has become a very important tool, used in research of cancer or genomic disorders. Therefore, improving classification of aCGH data can have a great impact on many medical issues such as the process of diagnosis and finding disease-related genes. The performed experiment shows that the application of Jumping Emerging Patterns can be effective in the classification of high-dimensional data, including these from aCGH experiments.</p

Integrative Genomic Analyses Identify BRF2 as a Novel Lineage-Specific Oncogene in Lung Squamous Cell Carcinoma

William Lockwood and colleagues show that the focal amplification of a gene, BRF2, on Chromosome 8p12 plays a key role in squamous cell carcinoma of the lung

Divergent Genomic and Epigenomic Landscapes of Lung Cancer Subtypes Underscore the Selection of Different Oncogenic Pathways during Tumor Development

For therapeutic purposes, non-small cell lung cancer (NSCLC) has traditionally been regarded as a single disease. However, recent evidence suggest that the two major subtypes of NSCLC, adenocarcinoma (AC) and squamous cell carcinoma (SqCC) respond differently to both molecular targeted and new generation chemotherapies. Therefore, identifying the molecular differences between these tumor types may impact novel treatment strategy. We performed the first large-scale analysis of 261 primary NSCLC tumors (169 AC and 92 SqCC), integrating genome-wide DNA copy number, methylation and gene expression profiles to identify subtype-specific molecular alterations relevant to new agent design and choice of therapy. Comparison of AC and SqCC genomic and epigenomic landscapes revealed 778 altered genes with corresponding expression changes that are selected during tumor development in a subtype-specific manner. Analysis of >200 additional NSCLCs confirmed that these genes are responsible for driving the differential development and resulting phenotypes of AC and SqCC. Importantly, we identified key oncogenic pathways disrupted in each subtype that likely serve as the basis for their differential tumor biology and clinical outcomes. Downregulation of HNF4α target genes was the most common pathway specific to AC, while SqCC demonstrated disruption of numerous histone modifying enzymes as well as the transcription factor E2F1. In silico screening of candidate therapeutic compounds using subtype-specific pathway components identified HDAC and PI3K inhibitors as potential treatments tailored to lung SqCC. Together, our findings suggest that AC and SqCC develop through distinct pathogenetic pathways that have significant implication in our approach to the clinical management of NSCLC

Anticipated and experienced discrimination amongst people with schizophrenia, bipolar disorder and major depressive disorder: a cross-sectional study.

BACKGROUND: The unfair treatment of individuals with severe mental illness has been linked to poorer physical and mental health outcomes. Additionally, anticipation of discrimination may lead some individuals to avoid participation in particular life areas, leading to greater isolation and social marginalisation. This study aimed to establish the levels and clinical and socio-demographic associations of anticipated and experienced discrimination amongst those diagnosed with a schizophrenia and comparator severe mental illnesses (bipolar and major depressive disorders). METHODS: This study was a cross-sectional analysis of anticipated and experienced discrimination from 202 individuals in South London (47% with schizophrenia, 32% with depression and 20% with bipolar disorder). RESULTS: 93% of the sample anticipated discrimination and 87% of participants had experienced discrimination in at least one area of life in the previous year. There was a significant association between the anticipation and the experience of discrimination. Higher levels of experienced discrimination were reported by those of a mixed ethnicity, and those with higher levels of education. Women anticipated more discrimination than men. Neither diagnosis nor levels of functioning were associated with the extent of discrimination. Clinical symptoms of anxiety, depression and suspiciousness were associated with more experienced and anticipated discrimination respectively. CONCLUSIONS: The unfair treatment of individuals with severe mental illnesses remains unacceptably common. Population level interventions are needed to reduce levels of discrimination and to safeguard individuals. Interventions are also required to assist those with severe mental illness to reduce internalised stigma and social avoidance

Identification of novel candidate target genes, including EPHB3, MASP1 and SST at 3q26.2–q29 in squamous cell carcinoma of the lung

<p>Abstract</p> <p>Background</p> <p>The underlying genetic alterations for squamous cell carcinoma (SCC) and adenocarcinoma (AC) carcinogenesis are largely unknown.</p> <p>Methods</p> <p>High-resolution array- CGH was performed to identify the differences in the patterns of genomic imbalances between SCC and AC of non-small cell lung cancer (NSCLC).</p> <p>Results</p> <p>On a genome-wide profile, SCCs showed higher frequency of gains than ACs (<it>p </it>= 0.067). More specifically, statistically significant differences were observed across the histologic subtypes for gains at 2q14.2, 3q26.2–q29, 12p13.2–p13.33, and 19p13.3, as well as losses at 3p26.2–p26.3, 16p13.11, and 17p11.2 in SCC, and gains at 7q22.1 and losses at 15q22.2–q25.2 occurred in AC (<it>P </it>< 0.05). The most striking difference between SCC and AC was gains at the 3q26.2–q29, occurring in 86% (19/22) of SCCs, but in only 21% (3/14) of ACs. Many significant genes at the 3q26.2–q29 regions previously linked to a specific histology, such as EVI1,<it>MDS1, PIK3CA </it>and <it>TP73L</it>, were observed in SCC (<it>P </it>< 0.05). In addition, we identified the following possible target genes (> 30% of patients) at 3q26.2–q29: <it>LOC389174 </it>(3q26.2),<it>KCNMB3 </it>(3q26.32),<it>EPHB3 </it>(3q27.1), <it>MASP1 </it>and <it>SST </it>(3q27.3), <it>LPP </it>and <it>FGF12 </it>(3q28), and <it>OPA1</it>,<it>KIAA022</it>,<it>LOC220729</it>, <it>LOC440996</it>,<it>LOC440997</it>, and <it>LOC440998 </it>(3q29), all of which were significantly targeted in SCC (<it>P </it>< 0.05). Among these same genes, high-level amplifications were detected for the gene, <it>EPHB3</it>, at 3q27.1, and <it>MASP1 </it>and <it>SST</it>, at 3q27.3 (18, 18, and 14%, respectively). Quantitative real time PCR demonstrated array CGH detected potential candidate genes that were over expressed in SCCs.</p> <p>Conclusion</p> <p>Using whole-genome array CGH, we have successfully identified significant differences and unique information of chromosomal signatures prevalent between the SCC and AC subtypes of NSCLC. The newly identified candidate target genes may prove to be highly attractive candidate molecular markers for the classification of NSCLC histologic subtypes, and could potentially contribute to the pathogenesis of the squamous cell carcinoma of the lung.</p

Arsenic-related DNA copy-number alterations in lung squamous cell carcinomas

BACKGROUND: Lung squamous cell carcinomas (SqCCs) occur at higher rates following arsenic exposure. Somatic DNA copy-number alterations (CNAs) are understood to be critical drivers in several tumour types. We have assembled a rare panel of lung tumours from a population with chronic arsenic exposure, including SqCC tumours from patients with no smoking history. METHODS: Fifty-two lung SqCCs were analysed by whole-genome tiling-set array comparative genomic hybridisation. Twenty-two were derived from arsenic-exposed patients from Northern Chile (10 never smokers and 12 smokers). Thirty additional cases were obtained for comparison from North American smokers without arsenic exposure. Twenty-two blood samples from healthy individuals from Northern Chile were examined to identify germline DNA copy-number variations (CNVs) that could be excluded from analysis. RESULTS: We identified multiple CNAs associated with arsenic exposure. These alterations were not attributable to either smoking status or CNVs. DNA losses at chromosomes 1q21.1, 7p22.3, 9q12, and 19q13.31 represented the most recurrent events. An arsenic-associated gain at 19q13.33 contains genes previously identified as oncogene candidates. CONCLUSIONS: Our results provide a comprehensive approach to molecular characteristics of the arsenic-exposed lung cancer genome and the non-smoking lung SqCC genome. The distinct and recurrent arsenic-related alterations suggest that this group of tumours may be considered as a separate disease subclass

Opposing effects of cancer-type-specific SPOP mutants on BET protein degradation and sensitivity to BET inhibitors.

It is generally assumed that recurrent mutations within a given cancer driver gene elicit similar drug responses. Cancer genome studies have identified recurrent but divergent missense mutations affecting the substrate-recognition domain of the ubiquitin ligase adaptor SPOP in endometrial and prostate cancers. The therapeutic implications of these mutations remain incompletely understood. Here we analyzed changes in the ubiquitin landscape induced by endometrial cancer-associated SPOP mutations and identified BRD2, BRD3 and BRD4 proteins (BETs) as SPOP-CUL3 substrates that are preferentially degraded by endometrial cancer-associated SPOP mutants. The resulting reduction of BET protein levels sensitized cancer cells to BET inhibitors. Conversely, prostate cancer-specific SPOP mutations resulted in impaired degradation of BETs, promoting their resistance to pharmacologic inhibition. These results uncover an oncogenomics paradox, whereby mutations mapping to the same domain evoke opposing drug susceptibilities. Specifically, we provide a molecular rationale for the use of BET inhibitors to treat patients with endometrial but not prostate cancer who harbor SPOP mutations