Co-targeting CDK2 and CDK4/6 overcomes resistance to aromatase and CDK4/6 inhibitors in ER+ breast cancer.

Resistance to aromatase inhibitor (AI) treatment and combined CDK4/6 inhibitor (CDK4/6i) and endocrine therapy (ET) are crucial clinical challenges in treating estrogen receptor-positive (ER+) breast cancer. Understanding the resistance mechanisms and identifying reliable predictive biomarkers and novel treatment combinations to overcome resistance are urgently needed. Herein, we show that upregulation of CDK6, p-CDK2, and/or cyclin E1 is associated with adaptation and resistance to AI-monotherapy and combined CDK4/6i and ET in ER+ advanced breast cancer.

Quantitative Phosphoproteomics of the Angiotensin AT-Receptor Signaling Network Identifies HDAC1 (Histone-Deacetylase-1) and p53 as Mediators of Antiproliferation and Apoptosis.

Background: Angiotensin AT-receptor signaling is atypical for a G-protein coupled receptor and incompletely understood. To obtain novel insights into AT-receptor signaling, we mapped changes in the phosphorylation status of the entire proteome of human aortic endothelial cells in response to AT-receptor stimulation.

Methods: Phosphorylation status of human aortic endothelial cells after stimulation with C21 (1 µM; 0, 1, 3, 5, 20 minutes) was determined utilizing time-resolved quantitative phosphoproteomics.

Co-targeting CDK4/6 and AKT with endocrine therapy prevents progression in CDK4/6 inhibitor and endocrine therapy-resistant breast cancer.

CDK4/6 inhibitors (CDK4/6i) combined with endocrine therapy have shown impressive efficacy in estrogen receptor-positive advanced breast cancer. However, most patients will eventually experience disease progression on this combination, underscoring the need for effective subsequent treatments or better initial therapies. Here, we show that triple inhibition with fulvestrant, CDK4/6i and AKT inhibitor (AKTi) durably impairs growth of breast cancer cells, prevents progression and reduces metastasis of tumor xenografts resistant to CDK4/6i-fulvestrant combination or fulvestrant alone.

MCM3 upregulation confers endocrine resistance in breast cancer and is a predictive marker of diminished tamoxifen benefit.

Resistance to endocrine therapy in estrogen receptor-positive (ER) breast cancer is a major clinical problem with poorly understood mechanisms. There is an unmet need for prognostic and predictive biomarkers to allow appropriate therapeutic targeting. We evaluated the mechanism by which minichromosome maintenance protein 3 (MCM3) influences endocrine resistance and its predictive/prognostic potential in ER breast cancer.

Discriminating isogenic cancer cells and identifying altered unsaturated fatty acid content as associated with metastasis status, using k-means clustering and partial least squares-discriminant analysis of Raman maps.

Raman spectroscopy is a label-free, real-time diagnostic tool that shows great promise in identifying cell differences. We have evaluated the discriminatory power of Raman spectroscopy using a unique model system consisting of two isogenic cancer cell lines derived from the MDA-MB-435 cell line. The two cell lines are equally tumorigenic in mice, but while M-4A4 gives rise to metastasis, NM-2C5 only disseminates single cells that remain dormant in distant organs.

Identification of genes with altered expression in medullary breast cancer vs. ductal breast cancer and normal breast epithelia.

Medullary breast cancer (MCB) is a morphologically and biologically distinct subtype that, despite cytologically highly malignant characteristics, has a favorable prognosis compared to the more common infiltrating ductal breast carcinoma. MCB metastasizes less frequently, which has been attributed to both immunological and endogenous cellular factors, although little is known about the distinct biology of MCB that may contribute to the improved outcome of MCB patients. To identify candidate genes, we performed gene array expression analysis of cell lines of MCB, ductal breast cancer and normal breast epithelia, and the differential expression of a panel of candidate genes was further validated by quantitative PCR and immunohistochemical analysis of cell lines and tumor biopsies.

Systematic identification of protein complexes in Saccharomyces cerevisiae by mass spectrometry.

The recent abundance of genome sequence data has brought an urgent need for systematic proteomics to decipher the encoded protein networks that dictate cellular function. To date, generation of large-scale protein-protein interaction maps has relied on the yeast two-hybrid system, which detects binary interactions through activation of reporter gene expression. With the advent of ultrasensitive mass spectrometric protein identification methods, it is feasible to identify directly protein complexes on a proteome-wide scale.