LC-MS/MS of MDA-MB468 breast cancer cells grown under normal and glucose deprivation conditions

ABSTRACT: Mass spectrometry-based spectral count has been a common choice of label-free proteome quantification as its simplicity for the sample preparation and data generation. The discriminatory nature of spectral count in the MS data-dependent acquisition, however, inherently introduces the spectral count variation for low-abundance proteins in multiplicative LC-MS/MS analysis, which hampers sensitive proteome quantification. We implemented the error model in the spectral count refinement as a post PLGEM-STN for improving sensitivity for quantitation of low-abundance proteins by reducing spectral count variability. In the statistical framework, automated spectral count refinement by integrating the two statistical tools was tested with triplicate LC-MS/MS datasets of MDA-MB468 breast cancer cells grown under normal and glucose deprivation conditions. We identified about 30% more quantifiable proteins that were found to be low-abundance proteins, which were initially filtered out by the PLGEM-STN analysis.

INSTRUMENT(S):

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Permanent Cell Line Cell, Cell Culture

DISEASE(S): Breast Cancer

SUBMITTER: Hayun Lee  

LAB HEAD: Eugene C. Yi

PROVIDER: PXD013966 | Pride | 2019-09-25

REPOSITORIES: Pride