563 research outputs found
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Identification of cancer genes that are independent of dominant proliferation and lineage programs
Large, multidimensional cancer datasets provide a resource that can be mined to identify candidate therapeutic targets for specific subgroups of tumors. Here, we analyzed human breast cancer data to identify transcriptional programs associated with tumors bearing specific genetic driver alterations. Using an unbiased approach, we identified thousands of genes whose expression was enriched in tumors with specific genetic alterations. However, expression of the vast majority of these genes was not enriched if associations were analyzed within individual breast tumor molecular subtypes, across multiple tumor types, or after gene expression was normalized to account for differences in proliferation or tumor lineage. Together with linear modeling results, these findings suggest that most transcriptional programs associated with specific genetic alterations in oncogenes and tumor suppressors are highly context-dependent and are predominantly linked to differences in proliferation programs between distinct breast cancer subtypes. We demonstrate that such proliferation-dependent gene expression dominates tumor transcriptional programs relative to matched normal tissues. However, we also identified a relatively small group of cancer-associated genes that are both proliferation- and lineage-independent. A subset of these genes are attractive candidate targets for combination therapy because they are essential in breast cancer cell lines, druggable, enriched in stem-like breast cancer cells, and resistant to chemotherapy-induced down-regulation
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Characteristics and Predictive Value of Blood Transcriptome Signature in Males with Autism Spectrum Disorders
Autism Spectrum Disorders (ASD) is a spectrum of highly heritable neurodevelopmental disorders in which known mutations contribute to disease risk in 20% of cases. Here, we report the results of the largest blood transcriptome study to date that aims to identify differences in 170 ASD cases and 115 age/sex-matched controls and to evaluate the utility of gene expression profiling as a tool to aid in the diagnosis of ASD. The differentially expressed genes were enriched for the neurotrophin signaling, long-term potentiation/depression, and notch signaling pathways. We developed a 55-gene prediction model, using a cross-validation strategy, on a sample cohort of 66 male ASD cases and 33 age-matched male controls (P1). Subsequently, 104 ASD cases and 82 controls were recruited and used as a validation set (P2). This 55-gene expression signature achieved 68% classification accuracy with the validation cohort (area under the receiver operating characteristic curve (AUC): 0.70 [95% confidence interval [CI]: 0.62–0.77]). Not surprisingly, our prediction model that was built and trained with male samples performed well for males (AUC 0.73, 95% CI 0.65–0.82), but not for female samples (AUC 0.51, 95% CI 0.36–0.67). The 55-gene signature also performed robustly when the prediction model was trained with P2 male samples to classify P1 samples (AUC 0.69, 95% CI 0.58–0.80). Our result suggests that the use of blood expression profiling for ASD detection may be feasible. Further study is required to determine the age at which such a test should be deployed, and what genetic characteristics of ASD can be identified
Hyperfine Spectroscopy of Isotopically Engineered Group-IV Color Centers in Diamond
A quantum register coupled to a spin-photon interface is a key component in
quantum communication and information processing. Group-IV color centers in
diamond (SiV, GeV, and SnV) are promising candidates for this application,
comprising an electronic spin with optical transitions coupled to a nuclear
spin as the quantum register. However, the creation of a quantum register for
these color centers with deterministic and strong coupling to the spin-photon
interface remains challenging. Here, we make first-principles predictions of
the hyperfine parameters of the group-IV color centers, which we verify
experimentally with a comprehensive comparison between the spectra of spin
active and spin neutral intrinsic dopant nuclei in single GeV and SnV emitters.
In line with the theoretical predictions, detailed spectroscopy on large sample
sizes reveals that hyperfine coupling causes a splitting of the optical
transition of SnV an order of magnitude larger than the optical linewidth and
provides a magnetic-field insensitive transition. This strong coupling provides
access to a new regime for quantum registers in diamond color centers, opening
avenues for novel spin-photon entanglement and quantum sensing schemes for
these well-studied emitters
Design, recruitment, and retention of African-American smokers in a pharmacokinetic study
<p>Abstract</p> <p>Background</p> <p>African-Americans remain underrepresented in clinical research despite experiencing a higher burden of disease compared to all other ethnic groups in the United States. The purpose of this article is to describe the study design and discuss strategies used to recruit and retain African-American smokers in a pharmacokinetic study.</p> <p>Methods</p> <p>The parent study was designed to evaluate the differences in the steady-state concentrations of bupropion and its three principal metabolites between African-American menthol and non-menthol cigarette smokers. Study participation consisted of four visits at a General Clinical Research Center (GCRC) over six weeks. After meeting telephone eligibility requirements, phone-eligible participants underwent additional screening during the first two GCRC visits. The last two visits (pharmacokinetic study phase) required repeated blood draws using an intravenous catheter over the course of 12 hours.</p> <p>Results</p> <p>Five hundred and fifteen African-American smokers completed telephone screening; 187 were phone-eligible and 92 were scheduled for the first GCRC visit. Of the 81 who attended the first visit, 48 individuals were enrolled in the pharmacokinetic study, and a total of 40 individuals completed the study (83% retention rate).</p> <p>Conclusions</p> <p>Although recruitment of African-American smokers into a non-treatment, pharmacokinetic study poses challenges, retention is feasible. The results provide valuable information for investigators embarking on non-treatment laboratory-based studies among minority populations.</p
Global-scale climate impact functions: the relationship between climate forcing and impact
Although there is a strong policy interest in the impacts of climate change corresponding to different degrees of climate change, there is so far little consistent empirical evidence of the relationship between climate forcing and impact. This is because the vast majority of impact assessments use emissions-based scenarios with associated socio-economic assumptions, and it is not feasible to infer impacts at other temperature changes by interpolation. This paper presents an assessment of the global-scale impacts of climate change in 2050 corresponding to defined increases in global mean temperature, using spatially-explicit impacts models representing impacts in the water resources, river flooding, coastal, agriculture, ecosystem and built environment sectors. Pattern-scaling is used to construct climate scenarios associated with specific changes in global mean surface temperature, and a relationship between temperature and sea level used to construct sea level rise scenarios. Climate scenarios are constructed from 21 climate models to give an indication of the uncertainty between forcing and response. The analysis shows that there is considerable uncertainty in the impacts associated with a given increase in global mean temperature, due largely to uncertainty in the projected regional change in precipitation. This has important policy implications. There is evidence for some sectors of a non-linear relationship between global mean temperature change and impact, due to the changing relative importance of temperature and precipitation change. In the socio-economic sectors considered here, the relationships are reasonably consistent between socio-economic scenarios if impacts are expressed in proportional terms, but there can be large differences in absolute terms. There are a number of caveats with the approach, including the use of pattern-scaling to construct scenarios, the use of one impacts model per sector, and the sensitivity of the shape of the relationships between forcing and response to the definition of the impact indicator
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