A systematic search strategy identifies cubilin as independent prognostic marker for renal cell carcinoma

$\textbf{Background:}$ There is an unmet clinical need for better prognostic and diagnostic tools for renal cell carcinoma (RCC). $\textbf{Methods:}$ Human Protein Atlas data resources, including the transcriptomes and proteomes of normal and malignant human tissues, were searched for RCC-specific proteins and cubilin (CUBN) identified as a candidate. Patient tissue representing various cancer types was constructed into a tissue microarray ($n$ = 940) and immunohistochemistry used to investigate the specificity of CUBN expression in RCC as compared to other cancers. Two independent RCC cohorts ($n$ = 181; $n$ = 114) were analyzed to further establish the sensitivity of CUBN as RCC-specific marker and to explore if the fraction of RCCs lacking CUBN expression could predict differences in patient survival. $\textbf{Results:}$ CUBN was identified as highly RCC-specific protein with 58% of all primary RCCs staining positive for CUBN using immunohistochemistry. In venous tumor thrombi and metastatic lesions, the frequency of CUBN expression was increasingly lost. Clear cell RCC (ccRCC) patients with CUBN positive tumors had a significantly better prognosis compared to patients with CUBN negative tumors, independent of T-stage, Fuhrman grade and nodal status (HR 0.382, CI 0.203–0.719, $P$ = 0.003). $\textbf{Conclusions:}$ CUBN expression is highly specific to RCC and loss of the protein is significantly and independently associated with poor prognosis. CUBN expression in ccRCC provides a promising positive prognostic indicator for patients with ccRCC. The high specificity of CUBN expression in RCC also suggests a role as a new diagnostic marker in clinical cancer differential diagnostics to confirm or rule out RCC.This work was supported by the Swedish Cancer Society and the Knut and Alice Wallenberg Foundation. The work of DJH and GDS was funded by the Chief Scientist Office (grant number ETM37), Renal Cancer Research Fund and Kidney Cancer Scotland

PREDICTORS OF HYPERTENSION

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/74570/1/j.1749-6632.1978.tb25565.x.pd

Impact of inactivity and exercise on the vasculature in humans

The effects of inactivity and exercise training on established and novel cardiovascular risk factors are relatively modest and do not account for the impact of inactivity and exercise on vascular risk. We examine evidence that inactivity and exercise have direct effects on both vasculature function and structure in humans. Physical deconditioning is associated with enhanced vasoconstrictor tone and has profound and rapid effects on arterial remodelling in both large and smaller arteries. Evidence for an effect of deconditioning on vasodilator function is less consistent. Studies of the impact of exercise training suggest that both functional and structural remodelling adaptations occur and that the magnitude and time-course of these changes depends upon training duration and intensity and the vessel beds involved. Inactivity and exercise have direct “vascular deconditioning and conditioning” effects which likely modify cardiovascular risk

Discovery of widespread transcription initiation at microsatellites predictable by sequence-based deep neural network

Using the Cap Analysis of Gene Expression (CAGE) technology, the FANTOM5 consortium provided one of the most comprehensive maps of transcription start sites (TSSs) in several species. Strikingly, ~72% of them could not be assigned to a specific gene and initiate at unconventional regions, outside promoters or enhancers. Here, we probe these unassigned TSSs and show that, in all species studied, a significant fraction of CAGE peaks initiate at microsatellites, also called short tandem repeats (STRs). To confirm this transcription, we develop Cap Trap RNA-seq, a technology which combines cap trapping and long read MinION sequencing. We train sequence-based deep learning models able to predict CAGE signal at STRs with high accuracy. These models unveil the importance of STR surrounding sequences not only to distinguish STR classes, but also to predict the level of transcription initiation. Importantly, genetic variants linked to human diseases are preferentially found at STRs with high transcription initiation level, supporting the biological and clinical relevance of transcription initiation at STRs. Together, our results extend the repertoire of non-coding transcription associated with DNA tandem repeats and complexify STR polymorphism

High throughput generation of a resource of the human secretome in mammalian cells

The proteins secreted by human tissues and blood cells, the secretome, are important both for the basic understanding of human biology and for identification of potential targets for future diagnosis and therapy. Here, a high-throughput mammalian cell factory is presented that was established to create a resource of recombinant full-length proteins covering the majority of those annotated as ‘secreted’ in humans. The full-length DNA sequences of each of the predicted secreted proteins were generated by gene synthesis, the constructs were transfected into Chinese hamster ovary (CHO) cells and the recombinant proteins were produced, purified and analyzed. Almost 1,300 proteins were successfully generated and proteins predicted to be secreted into the blood were produced with a success rate of 65%, while the success rates for the other categories of secreted proteins were somewhat lower giving an overall one-pass success rate of ca. 58%. The proteins were used to generate targeted proteomics assays and several of the proteins were shown to be active in a phenotypic assay involving pancreatic β-cell dedifferentiation. Many of the proteins that failed during production in CHO cells could be rescued in human embryonic kidney (HEK 293) cells suggesting that a cell factory of human origin can be an attractive alternative for production in mammalian cells. In conclusion, a high-throughput protein production and purification system has been successfully established to create a unique resource of the human secretome.ISSN:1871-6784ISSN:1876-434