Comparative proteomic and clinicopathological analysis of breast adenoid cystic carcinoma and basal-like triple-negative breast cancer

Front Med (Lausanne). 2022 Jul 28:9:943887. doi: 10.3389/fmed.2022.943887. eCollection 2022.

Abstract

Background: Adenoid cystic carcinoma (ACC) is a rare type of triple-negative breast cancer that has an indolent clinical behavior. Given the substantial overlapping morphological, immunohistochemical, and molecular features with other basal-like triple-negative breast cancer (BL-TNBC), accurate diagnosis of ACC is crucial for effective clinical treatment. The integrative analysis of the proteome and clinicopathological characteristics may help to distinguish these two neoplasms and provide a deep understanding on biological behaviors and potential target therapy of ACC.

Methods: We applied mass spectrometry-based quantitative proteomics to analyze the protein expression in paired tumor and adjacent normal breast tissue of five ACC and five BL-TNBC. Bioinformatic analyses and the clinicopathological characteristics, including histological features, immunohistochemistry, and FISH results, were also collected to get comprehensive information.

Results: A total of 307 differentially expressed proteins (DEPs) were identified between ACC and BL-TNBC. Clustering analysis of DEPs clearly separated ACC from BL-TNBC. GSEA found downregulation of the immune response of ACC compared with BL-TNBC, which is consistent with the negative PD-L1 expression of ACC. Vesicle-mediated transport was also inhibited, while ECM organization was enriched in ACC. The top upregulated proteins in DEPs were ITGB4, VCAN, and DPT. Moreover, in comparison with normal breast tissue, ACC showed elevated ribosome biogenesis and RNA splicing activity.

Conclusion: This study provides evidence that ACC presents a substantially different proteomic profile compared with BL-TNBC and promotes our understanding on the molecular mechanisms and biological processes of ACC, which might be useful for differential diagnosis and anticancer strategy.

Keywords: adenoid cystic carcinoma; bioinformatics; breast cancer biology; proteomics; triple-negative breast cancer.