Researchers in this study wanted to improve how scientists study proteins in blood samples from people with breast cancer. Blood contains thousands of proteins and measuring them consistently can be difficult because differences in how samples are collected or processed may affect the results. The goal of this research was to create a large, reliable dataset of blood proteins that scientists could use to better understand breast cancer and identify potential biomarkers.
To do this, the researchers collected plasma samples from 204 healthy volunteers and 216 breast cancer patients using a standardized protocol designed to minimize variation in sample handling. Some breast cancer patients also provided follow-up samples every three months so researchers could observe changes over time. The team analyzed these samples using advanced mass spectrometry–based proteomics, which allows scientists to measure many proteins simultaneously and detect differences between groups. By carefully standardizing sample collection and using a consistent analytical platform, the researchers produced a large and highly reproducible dataset of plasma protein profiles. This data set allows scientists to compare protein patterns between healthy individuals and breast cancer patients and to identify proteins that may be associated with disease.A large, consistent plasma proteomics data set from prospectively collected breast cancer patient and healthy volunteer samples.
What did they study?
In this study, researchers examined whether standardized methods could improve large-scale analysis of blood proteins in breast cancer research. They investigated:
- Plasma samples from healthy volunteers and breast cancer patients
- Changes in protein patterns detected using mass spectrometry proteomics
- Whether standardized collection and processing methods improve consistency
- Longitudinal samples collected from some patients every three months to monitor changes over time
What did they find?
- Standardized protocols improved the consistency of blood protein measurements.
- Researchers created a large plasma proteomics dataset from hundreds of participants.
The dataset allowed reliable comparison between healthy individuals and breast cancer patients. - Repeated samples from patients made it possible to track changes in protein levels over time.
- The study demonstrated that large-scale proteomics datasets can be generated using carefully controlled sample collection and analysis methods.
Why is this study important?
This study is important because it provides a reliable foundation for future breast cancer biomarker research. By creating a large and consistent dataset of blood proteins, scientists can more accurately identify protein patterns linked to cancer.
Such datasets can help researchers develop better diagnostic tools, blood tests for early detection, and ways to monitor disease progression or treatment response. Standardizing how samples are collected and analyzed also improves the ability to compare results across different studies, which is critical for advancing cancer research.
Full citation
Riley CP,Zhang X,Nakshatri H,Schneider B,Regnier FE,Adamec J,Buck C A large, consistent plasma proteomics data set from prospectively collected breast cancer patient and healthy volunteer samples.. Journal of translational medicine 2011 May; 9. PMID:21619653.
