Project description:The biomarker development field within molecular medicine remains limited by the methods that are available for building predictive models. We developed an efficient method for conservatively estimating confidence intervals for the cross validation derived prediction errors of biomarker models. This new method was investigated for its ability to improve the capacity of our previously developed method, StaVarSel, for selecting stable biomarkers. Compared with the standard cross validation method StaVarSel markedly improved the estimated generalisable predictive capacity of serum miRNA biomarkers for the detection of disease states that are at increased risk of progressing to oesophageal adenocarcinoma. The incorporation of our new method for conservatively estimating confidence intervals into StaVarSel resulted in the selection of less complex models with increased stability and improved or similar predictive capacities. The methods developed in this study have the potential to improve progress from biomarker discovery to biomarker driven translational research.
Project description:Diluted urine for biomarker discovery.
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GNPS link for IIN paper:
https://gnps.ucsd.edu/ProteoSAFe/status.jsp?task=a5480529261b4a13bb867f2edad1dcbe
Project description:As part of the Dystrophia Myotonica Biomarker Discovery Initiative (DMBDI) a dataset was obtained from 35 participants, including 31 Myotonic Dystrophy type 1 (DM1) cases and four unaffected controls. All DM1 cases in this research were heterozygous for the abnormally expanded CTG repeat. The mode of the length of the DM1 CTG expansion (Modal Allele Length, MAL) was determined by small-pool PCR of blood DNA for 35/36 patients. For this work we did not attempt to measure the repeat length from muscle, due to a very high degree of repeat instability in muscle cells, and associated difficulties in its experimental measurement. One patient refused blood donation. For each of the 35 blood-donating patients mRNA expression profiling of blood was performed using Affymetrix GeneChip™ Human Exon 1.0 ST microarray. For 28 of 36 patients a successful quadriceps muscle biopsy was obtained. The muscle tissue was mRNA profiled using the same type of microarray. In total, a complete set of samples (blood and muscle) was obtained for 27 of 36 patients; samples were given a disease staging score based on muscle impairment rating. mRNA profiling was carried out by the GeneLogic service lab (on a fee-for-service basis) using standard Affymetrix hybridisation protocol.
Project description:Mass spectrometry (MS) has emerged as a valuable tool for plasma proteome profiling and disease biomarker discovery. However, wide range of plasma protein concentrations along with technical and biological variabilities, continue to present significant challenges for deep and reproducible protein quantitation across large patient cohorts. Here we demonstrate the qualitative and quantitative performance gain of the timsTOF HT over the timsTOF Pro 2 mass spectrometer in the analysis of neat (unfractionated) and Proteograph™ (PG)-processed plasma across a wide range of peptide loading masses and liquid chromatography (LC) gradients. We observed up to a 76% increase in total plasma peptide precursors identified and a >2-fold boost in quantifiable plasma peptide precursors (CV<20%) with timsTOF HT compared to timsTOF Pro 2. In an exploratory study of 20 late-stage cancer and 20 control sampleswe observed a ~50% increase in total and statistically significant plasma peptide precursors (q<0.05) with timsTOF HT compared to Pro 2. Our data demonstrated the superior performance of timsTOF HT in identifying and quantifying differences between biologically diverse samples, which can improve disease biomarker discovery in large cohort studies. Moreover, researchers can leverage datasets from this study to optimize their LCMS workflows for plasma protein profiling and biomarker discovery. See the details in a paper, entitled "timsTOF HT improves protein identification and quantitative reproducibility for deep unbiased plasma protein biomarker discovery".
Project description:Mass spectrometry (MS) has emerged as a valuable tool for plasma proteome profiling and disease biomarker discovery. However, wide range of plasma protein concentrations along with technical and biological variabilities, continue to present significant challenges for deep and reproducible protein quantitation across large patient cohorts. Here we demonstrate the qualitative and quantitative performance gain of the timsTOF HT over the timsTOF Pro 2 mass spectrometer in the analysis of neat (unfractionated) and Proteograph™ (PG)-processed plasma across a wide range of peptide loading masses and liquid chromatography (LC) gradients. We observed up to a 76% increase in total plasma peptide precursors identified and a >2-fold boost in quantifiable plasma peptide precursors (CV<20%) with timsTOF HT compared to timsTOF Pro 2. In an exploratory study of 20 late-stage cancer and 20 control sampleswe observed a ~50% increase in total and statistically significant plasma peptide precursors (q<0.05) with timsTOF HT compared to Pro 2. Our data demonstrated the superior performance of timsTOF HT in identifying and quantifying differences between biologically diverse samples, which can improve disease biomarker discovery in large cohort studies. Moreover, researchers can leverage datasets from this study to optimize their LCMS workflows for plasma protein profiling and biomarker discovery. See the details in a paper, entitled "timsTOF HT improves protein identification and quantitative reproducibility for deep unbiased plasma protein biomarker discovery".