Antineoplastic effects of selective CDK9 inhibition with atuveciclib on cancer stem-like cells in triple-negative breast cancer.

Treatment options for triple-negative breast cancer (TNBC) are limited due to the lack of efficient targeted therapies, frequently resulting in recurrence and metastatic disease. Accumulating evidence suggests that a small population of cancer stem-like cells (CSLCs) is responsible for tumor recurrence and therapy resistance. Here we investigated the role of cyclin-dependent kinase 9 (CDK9) in TNBC. Using The Cancer Genome Atlas (TCGA) data we found high-CDK9 expression correlates with worse overall survival in TNBC patients. Pharmacologic inhibition of CDK9 with atuveciclib in high-CDK9 expressing TNBC cell lines reduced expression of CDK9 targets MYC and MCL1 and decreased cell proliferation and survival. Importantly, atuveciclib inhibited the growth of mammospheres and reduced the percentage of CD24low/CD44high cells, indicating disruption of breast CSLCs (BCSLCs). Furthermore, atuveciclib impaired 3D invasion of tumorspheres suggesting inhibition of both invasion and metastatic potential. Finally, atuveciclib enhanced the antineoplastic effects of Cisplatin and promoted inhibitory effects on BCSLCs grown as mammospheres. Together, these findings suggest CDK9 as a potential therapeutic target in aggressive forms of CDK9-high TNBC.

IDPpi: Protein-Protein Interaction Analyses of Human Intrinsically Disordered Proteins.

Intrinsically disordered proteins (IDPs) are characterized by the lack of a fixed tertiary structure and are involved in the regulation of key biological processes via binding to multiple protein partners. IDPs are malleable, adapting to structurally different partners, and this flexibility stems from features encoded in the primary structure. The assumption that universal sequence information will facilitate coverage of the sparse zones of the human interactome motivated us to explore the possibility of predicting protein-protein interactions (PPIs) that involve IDPs based on sequence characteristics. We developed a method that relies on features of the interacting and non-interacting protein pairs and utilizes machine learning to classify and predict IDP PPIs. Consideration of both sequence determinants specific for conformational organizations and the multiplicity of IDP interactions in the training phase ensured a reliable approach that is superior to current state-of-the-art methods. By applying a strict evaluation procedure, we confirm that our method predicts interactions of the IDP of interest even on the proteome-scale. This service is provided as a web tool to expedite the discovery of new interactions and IDP functions with enhanced efficiency.

BASP1 interacts with oestrogen receptor α and modifies the tamoxifen response.

Tamoxifen binds to oestrogen receptor α (ERα) to elicit distinct responses that vary by cell/tissue type and status, but the factors that determine these differential effects are unknown. Here we report that the transcriptional corepressor BASP1 interacts with ERα and in breast cancer cells, this interaction is enhanced by tamoxifen. We find that BASP1 acts as a major selectivity factor in the transcriptional response of breast cancer cells to tamoxifen. In all, 40% of the genes that are regulated by tamoxifen in breast cancer cells are BASP1 dependent, including several genes that are associated with tamoxifen resistance. BASP1 elicits tumour-suppressor activity in breast cancer cells and enhances the antitumourigenic effects of tamoxifen treatment. Moreover, BASP1 is expressed in breast cancer tissue and is associated with increased patient survival. Our data have identified BASP1 as an ERα cofactor that has a central role in the transcriptional and antitumourigenic effects of tamoxifen.

PIM1 kinase inhibition as a targeted therapy against triple-negative breast tumors with elevated MYC expression.

Triple-negative breast cancer (TNBC), in which cells lack expression of the estrogen receptor (ER), the progesterone receptor (PR) and the ERBB2 (also known as HER2) receptor, is the breast cancer subtype with the poorest outcome. No targeted therapy is available against this subtype of cancer owing to a lack of validated molecular targets. We previously reported that signaling involving MYC-an essential, pleiotropic transcription factor that regulates the expression of hundreds of genes-is disproportionally higher in triple-negative (TN) tumors than in receptor-positive (RP) tumors. Direct inhibition of the oncogenic transcriptional activity of MYC has been challenging to achieve. Here, by conducting a shRNA screen targeting the kinome, we identified PIM1, a non-essential serine-threonine kinase, in a synthetic lethal interaction with MYC. PIM1 expression was higher in TN tumors than in RP tumors and was associated with poor prognosis in patients with hormone- and HER2-negative tumors. Small-molecule PIM kinase inhibitors halted the growth of human TN tumors with elevated MYC expression in patient-derived tumor xenograft (PDX) and MYC-driven transgenic mouse models of breast cancer by inhibiting the oncogenic transcriptional activity of MYC and restoring the function of the endogenous cell cycle inhibitor, p27. Our findings warrant clinical evaluation of PIM kinase inhibitors in patients with TN tumors that have elevated MYC expression.