The Urinary Transcriptome as a Source of Biomarkers for Prostate Cancer.

Prostate cancer (PCa) is the second most common cancer of men and is typically slow-growing and asymptomatic. The use of blood PSA as a screening method has greatly improved PCa diagnosis, but high levels of false positives has raised much interest in alternative biomarkers. We used next-generation sequencing (NGS) to elucidate the urinary transcriptome of whole urine collected from high-stage and low-stage PCa patients as well as from patients with the confounding diagnosis of benign hyperplasia (BPH).

The Circulating Transcriptome as a Source of Biomarkers for Melanoma.

The circulating transcriptome is a valuable source of cancer biomarkers, which, with the exception of microRNAs (miRNAs), remains relatively unexplored. To elucidate which RNAs are present in plasma from melanoma patients and which could be used to distinguish cancer patients from healthy individuals, we used next generation sequencing (NGS), and validation was carried out by qPCR and/or ddPCR. We identified 442 different microRNAs in samples, eleven of which were differentially expressed ( < 0.

Pervasive Protein Thermal Stability Variation during the Cell Cycle.

Quantitative mass spectrometry has established proteome-wide regulation of protein abundance and post-translational modifications in various biological processes. Here, we used quantitative mass spectrometry to systematically analyze the thermal stability and solubility of proteins on a proteome-wide scale during the eukaryotic cell cycle. We demonstrate pervasive variation of these biophysical parameters with most changes occurring in mitosis and G1.

Systematic analysis of protein turnover in primary cells.

A better understanding of proteostasis in health and disease requires robust methods to determine protein half-lives. Here we improve the precision and accuracy of peptide ion intensity-based quantification, enabling more accurate protein turnover determination in non-dividing cells by dynamic SILAC-based proteomics. This approach allows exact determination of protein half-lives ranging from 10 to >1000 h.