Glycoproteomic Comparison of Clinical Triple-Negative and Luminal Breast Tumors

Triple-negative
(TN) breast cancer accounts for ∼15% of
breast cancers and is characterized by a high likelihood of relapse
and a lack of targeted therapies. In contrast, luminal-type tumors
that express the estrogen and progesterone receptors (ER+/PR+) and
lack expression of human epidermal growth factor receptor 2 (Her2−)
are treated with targeted hormonal therapy and carry a better prognosis.
To identify potential targets for the development of future therapeutics
aimed specifically at TN breast cancers, we have used a hydrazide-based
glycoproteomic workflow to compare protein expression in clinical
tumors from nine TN (Her2–/ER-/PR-) and nine luminal (Her2–/ER+/PR+)
patients. Using a label-free LC–MS based approach, we identified
and quantified 2264 proteins. Of these, 90 proteins were more highly
expressed and 86 proteins were underexpressed in the TN tumors relative
to the luminal tumors. The expression level of four of these potential
targets was verified in the original set of tumors by Western blot
and correlated well with our mass-spectrometry-based quantification.
Furthermore, 30% of the proteins differentially expressed between
luminal and TN tumors were validated in a larger cohort of 406 TN
and 469 luminal tumors through corresponding differences in their
mRNA expression in publically available microarray data. A group of
29 of these differentially expressed proteins was shown to correctly
classify 88% of TN and luminal tumors using microarray data of their
associated mRNA levels. Interestingly, even within a group of TN breast
cancer patients, the expression levels of these same mRNAs were able
to significantly predict patient survival, suggesting that these proteins
play a role in the aggressiveness seen in TN tumors. This study provides
a comprehensive list of potential targets for the development of diagnostic
and therapeutic agents specifically aimed at treating TN breast cancer
and demonstrates the utility of using publicly available microarray
data to further prioritize potential targets.