Applying unmixing to gene expression data for tumor phylogeny inference

<p>Abstract</p> <p>Background</p> <p>While in principle a seemingly infinite variety of combinations of mutations could result in tumor development, in practice it appears that most human cancers fall into a relatively small number of "sub-types," each characterized a roughly equivalent sequence of mutations by which it progresses in different patients. There is currently great interest in identifying the common sub-types and applying them to the development of diagnostics or therapeutics. Phylogenetic methods have shown great promise for inferring common patterns of tumor progression, but suffer from limits of the technologies available for assaying differences between and within tumors. One approach to tumor phylogenetics uses differences between single cells within tumors, gaining valuable information about intra-tumor heterogeneity but allowing only a few markers per cell. An alternative approach uses tissue-wide measures of whole tumors to provide a detailed picture of averaged tumor state but at the cost of losing information about intra-tumor heterogeneity.</p> <p>Results</p> <p>The present work applies "unmixing" methods, which separate complex data sets into combinations of simpler components, to attempt to gain advantages of both tissue-wide and single-cell approaches to cancer phylogenetics. We develop an unmixing method to infer recurring cell states from microarray measurements of tumor populations and use the inferred mixtures of states in individual tumors to identify possible evolutionary relationships among tumor cells. Validation on simulated data shows the method can accurately separate small numbers of cell states and infer phylogenetic relationships among them. Application to a lung cancer dataset shows that the method can identify cell states corresponding to common lung tumor types and suggest possible evolutionary relationships among them that show good correspondence with our current understanding of lung tumor development.</p> <p>Conclusions</p> <p>Unmixing methods provide a way to make use of both intra-tumor heterogeneity and large probe sets for tumor phylogeny inference, establishing a new avenue towards the construction of detailed, accurate portraits of common tumor sub-types and the mechanisms by which they develop. These reconstructions are likely to have future value in discovering and diagnosing novel cancer sub-types and in identifying targets for therapeutic development.</p

Broad Spectrum Antiviral Activity of Favipiravir (T-705): Protection from Highly Lethal Inhalational Rift Valley Fever

Background:Development of antiviral drugs that have broad-spectrum activity against a number of viral infections would be of significant benefit. Due to the evolution of resistance to currently licensed antiviral drugs, development of novel anti-influenza drugs is in progress, including Favipiravir (T-705), which is currently in human clinical trials. T-705 displays broad-spectrum in vitro activity against a number of viruses, including Rift Valley Fever virus (RVFV). RVF is an important neglected tropical disease that causes human, agricultural, and economic losses in endemic regions. RVF has the capacity to emerge in new locations and also presents a potential bioterrorism threat. In the current study, the in vivo efficacy of T-705 was evaluated in Wistar-Furth rats infected with the virulent ZH501 strain of RVFV by the aerosol route.Methodology/Principal Findings:Wistar-Furth rats are highly susceptible to a rapidly lethal disease after parenteral or inhalational exposure to the pathogenic ZH501 strain of RVFV. In the current study, two experiments were performed: a dose-determination study and a delayed-treatment study. In both experiments, all untreated control rats succumbed to disease. Out of 72 total rats infected with RVFV and treated with T-705, only 6 succumbed to disease. The remaining 66 rats (92%) survived lethal infection with no significant weight loss or fever. The 6 treated rats that succumbed survived significantly longer before succumbing to encephalitic disease.Conclusions/Significance:Currently, there are no licensed antiviral drugs for treating RVF. Here, T-705 showed remarkable efficacy in a highly lethal rat model of Rift Valley Fever, even when given up to 48 hours post-infection. This is the first study to show protection of rats infected with the pathogenic ZH501 strain of RVFV. Our data suggest that T-705 has potential to be a broad-spectrum antiviral drug. © 2014 Caroline et al

Association of breast cancer risk in BRCA1 and BRCA2 mutation carriers with genetic variants showing differential allelic expression:Identification of a modifier of breast cancer risk at locus 11q22.3

Cis-acting regulatory SNPs resulting in differential allelic expression (DAE) may, in part, explain the underlying phenotypic variation associated with many complex diseases. To investigate whether common variants associated with DAE were involved in breast cancer susceptibility among BRCA1 and BRCA2 mutation carriers, a list of 175 genes was developed based of their involvement in cancer-related pathways.Using data from a genome-wide map of SNPs associated with allelic expression, we assessed the association of similar to 320 SNPs located in the vicinity of these genes with breast and ovarian cancer risks in 15,252 BRCA1 and 8211 BRCA2 mutation carriers ascertained from 54 studies participating in the Consortium of Investigators of Modifiers of BRCA1/2.We identified a region on 11q22.3 that is significantly associated with breast cancer risk in BRCA1 mutation carriers (most significant SNP rs228595 p = 7 x 10(-6)). This association was absent in BRCA2 carriers (p = 0.57). The 11q22.3 region notably encompasses genes such as ACAT1, NPAT, and ATM. Expression quantitative trait loci associations were observed in both normal breast and tumors across this region, namely for ACAT1, ATM, and other genes. In silico analysis revealed some overlap between top risk-associated SNPs and relevant biological features in mammary cell data, which suggests potential functional significance.We identified 11q22.3 as a new modifier locus in BRCA1 carriers. Replication in larger studies using estrogen receptor (ER)-negative or triple-negative (i.e., ER-, progesterone receptor-, and HER2-negative) cases could therefore be helpful to confirm the association of this locus with breast cancer risk.</p