Search anything and hit enter
  • Teams
  • Members
  • Projects
  • Events
  • Calls
  • Jobs
  • publications
  • Software
  • Tools
  • Network
  • Equipment

A little guide for advanced search:

  • Tip 1. You can use quotes "" to search for an exact expression.
    Example: "cell division"
  • Tip 2. You can use + symbol to restrict results containing all words.
    Example: +cell +stem
  • Tip 3. You can use + and - symbols to force inclusion or exclusion of specific words.
    Example: +cell -stem
e.g. searching for members in projects tagged cancer
Search for
Count
IN
OUT
Content 1
  • member
  • team
  • department
  • center
  • program_project
  • nrc
  • whocc
  • project
  • software
  • tool
  • patent
  • Administrative Staff
  • Assistant Professor
  • Associate Professor
  • Clinical Research Assistant
  • Full Professor
  • Graduate Student
  • Lab assistant
  • Non-permanent Researcher
  • Permanent Researcher
  • Pharmacist
  • PhD Student
  • Physician
  • Post-doc
  • Project Manager
  • Research Associate
  • Research Engineer
  • Retired scientist
  • Technician
  • Undergraduate Student
  • Veterinary
  • Visiting Scientist
  • Deputy Director of Center
  • Deputy Director of Department
  • Deputy Director of National Reference Center
  • Deputy Head of Facility
  • Director of Center
  • Director of Department
  • Director of Institute
  • Director of National Reference Center
  • Group Leader
  • Head of Facility
  • Head of Operations
  • Head of Structure
  • Honorary President of the Departement
  • Labex Coordinator
Content 2
  • member
  • team
  • department
  • center
  • program_project
  • nrc
  • whocc
  • project
  • software
  • tool
  • patent
  • Administrative Staff
  • Assistant Professor
  • Associate Professor
  • Clinical Research Assistant
  • Full Professor
  • Graduate Student
  • Lab assistant
  • Non-permanent Researcher
  • Permanent Researcher
  • Pharmacist
  • PhD Student
  • Physician
  • Post-doc
  • Project Manager
  • Research Associate
  • Research Engineer
  • Retired scientist
  • Technician
  • Undergraduate Student
  • Veterinary
  • Visiting Scientist
  • Deputy Director of Center
  • Deputy Director of Department
  • Deputy Director of National Reference Center
  • Deputy Head of Facility
  • Director of Center
  • Director of Department
  • Director of Institute
  • Director of National Reference Center
  • Group Leader
  • Head of Facility
  • Head of Operations
  • Head of Structure
  • Honorary President of the Departement
  • Labex Coordinator
Search
Go back
Scroll to top
Share
© Research
Publication : Journal of proteome research

Large-Scale SRM Screen of Urothelial Bladder Cancer Candidate Biomarkers in Urine

Scientific Fields
Diseases
Organisms
Applications
Technique

Published in Journal of proteome research - 23 Mar 2017

Duriez E, Masselon CD, Mesmin C, Court M, Demeure K, Allory Y, Malats N, Matondo M, Radvanyi F, Garin J, Domon B

Link to Pubmed [PMID] – 28287737

J. Proteome Res. 2017 04;16(4):1617-1631

Urothelial bladder cancer is a condition associated with high recurrence and substantial morbidity and mortality. Noninvasive urinary tests that would detect bladder cancer and tumor recurrence are required to significantly improve patient care. Over the past decade, numerous bladder cancer candidate biomarkers have been identified in the context of extensive proteomics or transcriptomics studies. To translate these findings in clinically useful biomarkers, the systematic evaluation of these candidates remains the bottleneck. Such evaluation involves large-scale quantitative LC-SRM (liquid chromatography-selected reaction monitoring) measurements, targeting hundreds of signature peptides by monitoring thousands of transitions in a single analysis. The design of highly multiplexed SRM analyses is driven by several factors: throughput, robustness, selectivity and sensitivity. Because of the complexity of the samples to be analyzed, some measurements (transitions) can be interfered by coeluting isobaric species resulting in biased or inconsistent estimated peptide/protein levels. Thus the assessment of the quality of SRM data is critical to allow flagging these inconsistent data. We describe an efficient and robust method to process large SRM data sets, including the processing of the raw data, the detection of low-quality measurements, the normalization of the signals for each protein, and the estimation of protein levels. Using this methodology, a variety of proteins previously associated with bladder cancer have been assessed through the analysis of urine samples from a large cohort of cancer patients and corresponding controls in an effort to establish a priority list of most promising candidates to guide subsequent clinical validation studies.

https://www.ncbi.nlm.nih.gov/pubmed/28287737