Predicting response to immune checkpoint blockade in NSCLC with tumour-only RNA-seq.

Background: Targeted RNA sequencing (RNA-seq) from FFPE specimens is used clinically in cancer for its ability to estimate gene expression and to detect fusions. Using a cohort of NSCLC patients, we sought to determine whether targeted RNA-seq could be used to measure tumour mutational burden (TMB) and the expression of immune-cell-restricted genes from FFPE specimens and whether these could predict response to immune checkpoint blockade.

Methods: Using The Cancer Genome Atlas LUAD dataset, we developed a method for determining TMB from tumour-only RNA-seq and showed a correlation with DNA sequencing derived TMB calculated from tumour/normal sample pairs (Spearman correlation = 0.

De novo transcriptome assembly for the spiny mouse (Acomys cahirinus).

Spiny mice of the genus Acomys display several unique physiological traits, including menstruation and scar-free wound healing; characteristics that are exceedingly rare in mammals, and of considerable interest to the scientific community. These unique attributes, and the potential for spiny mice to accurately model human diseases, are driving increased use of this genus in biomedical research, however little genetic information is accessible for this species. This project aimed to generate a draft transcriptome for the Common spiny mouse (Acomys cahirinus).

Hyperdiploid tumor cells increase phenotypic heterogeneity within Glioblastoma tumors.

Here we report the identification of a proliferative, viable, and hyperdiploid tumor cell subpopulation present within Glioblastoma (GB) patient tumors. Using xenograft tumor models, we demonstrate that hyperdiploid cell populations are maintained in xenograft tumors and that clonally expanded hyperdiploid cells support tumor formation and progression in vivo. In some patient tumorsphere lines, hyperdiploidy is maintained during long-term culture and in vivo within xenograft tumor models, suggesting that hyperdiploidy can be a stable cell state.

Arabidopsis defense against Botrytis cinerea: chronology and regulation deciphered by high-resolution temporal transcriptomic analysis.

Transcriptional reprogramming forms a major part of a plant's response to pathogen infection. Many individual components and pathways operating during plant defense have been identified, but our knowledge of how these different components interact is still rudimentary. We generated a high-resolution time series of gene expression profiles from a single Arabidopsis thaliana leaf during infection by the necrotrophic fungal pathogen Botrytis cinerea.

Metabolic switches and adaptations deduced from the proteomes of Streptomyces coelicolor wild type and phoP mutant grown in batch culture.

Bacteria in the genus Streptomyces are soil-dwelling oligotrophs and important producers of secondary metabolites. Previously, we showed that global messenger RNA expression was subject to a series of metabolic and regulatory switches during the lifetime of a fermentor batch culture of Streptomyces coelicolor M145. Here we analyze the proteome from eight time points from the same fermentor culture and, because phosphate availability is an important regulator of secondary metabolite production, compare this to the proteome of a similar time course from an S.

High-resolution temporal profiling of transcripts during Arabidopsis leaf senescence reveals a distinct chronology of processes and regulation.

Leaf senescence is an essential developmental process that impacts dramatically on crop yields and involves altered regulation of thousands of genes and many metabolic and signaling pathways, resulting in major changes in the leaf. The regulation of senescence is complex, and although senescence regulatory genes have been characterized, there is little information on how these function in the global control of the process. We used microarray analysis to obtain a high-resolution time-course profile of gene expression during development of a single leaf over a 3-week period to senescence.

Enhancing data integration with text analysis to find proteins implicated in plant stress response.

High throughput genomic studies can identify large numbers of potential candidate genes, which must be interpreted and filtered by investigators to select the best ones for further analysis. Prioritization is generally based on evidence that supports the role of a gene product in the biological process being investigated. The two most important bodies of information providing such evidence are bioinformatics databases and the scientific literature.

The dynamic architecture of the metabolic switch in Streptomyces coelicolor.

Background: During the lifetime of a fermenter culture, the soil bacterium S. coelicolor undergoes a major metabolic switch from exponential growth to antibiotic production. We have studied gene expression patterns during this switch, using a specifically designed Affymetrix genechip and a high-resolution time-series of fermenter-grown samples.