Large Plasma Proteomics Dataset for Breast Cancer Research
Author Information
Author(s): Riley Catherine P, Zhang Xiang, Nakshatri Harikrishna, Schneider Bryan, Regnier Fred E, Adamec Jiri, Buck Charles
Primary Institution: Purdue University
Hypothesis
Can a standardized proteomics platform generate consistent plasma profiles from breast cancer patients and healthy volunteers?
Conclusion
A consistent LC-MS proteomics dataset has been generated from over 800 plasma profiles, aiding breast cancer biomarker discovery.
Supporting Evidence
- Over 800 LC-MS plasma proteomic profiles were obtained from 420 individuals.
- The average coefficient of variability for peptide peaks was less than 15%.
- Peptide identification was achieved with high confidence using a spectral library from 150 LC-MS/MS runs.
Takeaway
Researchers collected blood samples from healthy people and breast cancer patients to create a big database of proteins, which can help find new ways to diagnose and treat cancer.
Methodology
Plasma samples were collected from 204 healthy volunteers and 216 breast cancer patients, followed by LC-MS profiling and LC-MS/MS for protein identification.
Potential Biases
Potential biases may arise from sample collection methods and the variability in proteomics technology.
Limitations
The study may not account for all variables affecting proteomic profiles, and the reliance on specific technology may limit generalizability.
Participant Demographics
Participants included 204 healthy volunteers and 216 breast cancer patients, all female and aged 18 or older.
Statistical Information
P-Value
<0.05
Statistical Significance
p<0.05
Digital Object Identifier (DOI)
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