Triple-negative breast cancers (TNBCs) account for ~25% of all invasive carcinomas and represent a large subset of aggressive, high-grade tumors. Despite current research focused on understanding the genetic landscape of TNBCs, reliable prognostic and predictive biomarkers remain limited. Although dysregulated microRNAs (miRNAs) have emerged as key players in many cancer types, the role of miRNAs in TNBC disease progression is unclear. We performed miRNA profiling of 51 TNBCs by next-generation sequencing to reveal differentially expressed miRNAs. A total of 228 miRNAs were identified. Three miRNAs (miR-224–5p, miR-375, and miR-205–5p) separated the tumors based on basal status. Six miRNAs (high let-7d-3p, miR-203b-5p, and miR-324–5p; low miR-30a-3p, miR-30a-5p, and miR-199a-5p) were significantly associated with decreased overall survival (OS) and 5 miRNAs (high let-7d-3p; low miR-30a-3p, miR-30a-5p, miR-30c-5p, and miR-128–3p) with decreased relapse-free survival (RFS). On multivariate analysis, high expression of let-7d-3p and low expression of miR-30a were independent predictors of decreased OS and RFS. High expression of miR-95–3p was significantly associated with decreased OS and RFS in patients treated with anthracycline-based chemotherapy. Five miRNAs (let-7d-3p, miR-30a-3p, miR-30c-5p, miR-128–3p, and miR-95–3p) were validated by quantitative RT-PCR. Our findings unveil novel prognostic and predictive miRNA targets for TNBC, including a miRNA signature that predicts patient response to anthracycline-based chemotherapy. This may improve clinical management and/or lead to the development of novel therapies.—Turashvili, G., Lightbody, E. D., Tyryshkin, K., SenGupta, S. K., Elliott, B. E., Madarnas, Y., Ghaffari, A., Day, A., Nicol, C. J. B. Novel prognostic and predictive microRNA targets for triple-negative breast cancer. FASEB J. 32, 5937–5954 (2018). www.fasebj.org
SUMMARY The development of targeted therapy for patients with Multiple Myeloma (MM) is hampered by the low frequency of actionable genetic abnormalities. Gain or amplification of chr1q (Amp1q) is the most frequent arm-level copy number gain in patients with MM, and it is associated with higher risk of progression and death despite recent advances in therapeutics. Thus, developing targeted therapy for patients with MM and Amp1q stands to benefit a large portion of patients in need of more effective management. Here, we employed large-scale dependency screens and drug screens to systematically characterize the therapeutic vulnerabilities of MM with Amp1q and showed increased sensitivity to the combination of MCL1 and PI3K inhibitors. Using single-cell RNA sequencing, we compared subclones with and without Amp1q within the same patient tumors and showed that Amp1q is associated with higher levels of MCL1 and the PI3K pathway. Furthermore, by isolating isogenic clones with different copy number for part of the chr1q arm, we showed increased sensitivity to MCL1 and PI3K inhibitors with arm-level gain. Lastly, we demonstrated synergy between MCL1 and PI3K inhibitors and dissected their mechanism of action in MM with Amp1q.
Abstract Detecting cancer at early stages or upon recurrence is critical to decreasing cancer morbidity and mortality. We developed TuFEst (Tumor Fraction Estimator), a cost-effective computational approach for pan-cancer detection and tumor burden estimation from ultra-low coverage whole genome sequencing (~0.1x, ULP-WGS) of minimally invasive cell-free DNA (cfDNA). Current state-of-the-art methods estimate tumor fraction (TF) from ULP-WGS depending exclusively on total copy number variation, which loses tumor signal in either copy number-quiet tumors or tumors with copy-neutral loss-of-heterozygosity. Additionally, it is difficult in many cases to distinguish clonal from sub-clonal copy-number events, therefore complicating the ability to estimate tumor fraction. On the other hand, fragments shed into the blood from cancer cells, i.e., circulating tumor DNA (ctDNA), of various cancer types show significantly different length distribution than that from normal cells in healthy donors. By synergistically integrating both (i) copy number variation and (ii) altered fragment length signals, TuFEst successfully achieved higher sensitivity and more accurate TF estimation than current methods in >200 cfDNA samples across different cancer types, even in low tumor-fraction cases (TF < 0.1%). Application of TuFEst to serial cfDNA samples from blood biopsies demonstrate its utility in accurately estimating TF in ~100 cfDNAs, suggesting that TuFEst can be used to detect early cancer recurrence during different treatments. In one breast cancer patient receiving CDK4/6 therapy, TuFEst indicated disease progression 262 days earlier than routine imaging. Altogether, our work suggests that accurate TF estimation from cfDNA can not only aid in detecting cancer at early stages but also provide evidence of disease progression during treatment. We believe that such a non-invasive, cost-effective, pan-cancer detection method will benefit both initial cancer screening and monitoring of resistance to therapy in clinical applications. Citation Format: Ziao Lin, Chip Stewart, Elizabeth E. Martin, Brian P. Danysh, Raquel A. Jacobs, Kara Slowik, Lee Lawton, Elizabeth Lightbody, Kahn Rhrissorrakrai, Filippo Utro, Chaya Levovitz, Carrie Cibulskis, Irene M. Ghobrial, Margaret Shipp, Ryan B. Corcoran, Dejan Juric, Laxmi Parida, Heather A. Parsons, Gad Getz. TuFEst: a sensitive and cost-effective pan-cancer detection approach with accurate tumor fraction estimation [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5162.
Abstract Breast tumors that overexpress human epidermal growth factor receptor 2 (HER2+) grow and spread faster than HER2-negative tumors, resulting in poor patient prognosis. Peroxisome proliferator-activated receptor (PPAR)γ is a nuclear transcription factor that controls the expression of genes essential for normal metabolism of fats and sugars in the body. Our laboratory previously showed that PPARγ expression suppresses environmental carcinogen DMBA-mediated breast tumor progression in vivo, and PPARγ-activating drugs further enhance this effect. However, the role of PPARγ and PPARγ agonists on HER2+ breast tumorigenesis and patient survival is unclear. We hypothesized that PPARγ loss enhances HER2+ breast tumor progression. To test this, this study generated a novel mouse model referred to as NIC:PPARγ-KO, which has targeted PPARγ deletion in the same HER2+ transformed mammary epithelial cells that drive breast tumorigenesis. Compared to NIC:PPARγ-WT mice, NIC:PPARγ-KO mice have increased mammary tumor incidences and lung metastases. Protein analysis of NIC:PPARγ-KO tumors shows PPARγ loss is inversely correlated with increased HER2 phosphorylation at tyrosine 877 (pY877HER2) in primary and metastatic tumorigenic tissue. Immunofluorescence also showed HER2 H-scores were significantly highest among tumors from NIC:PPARγ-KO mice, but also correlated with targeted PPARγ loss in DMBA-induced primary and metastatic mammary tumors among PPARγ-WT and PPARγ-KO mice (p<0.05). To further investigate the role of PPARγ in the metastatic process, we established cell lines from the freshly isolated lung metastatic tumors harvested from the NIC:PPARγ-KO model (NIC:PPARγ-KO-lmet). In vitro analysis of several human HER2+ breast cancer cells lines and our NIC:PPARγ-KO-lmet cells shows migration, invasion and tumorsphere-forming potential were significantly increased after epidermal growth factor (EGF, 20ng/mL) treatment and, more interestingly, that co-treatment with a PPARγ-activating drug (rosiglitazone, 10μM) significantly abrogated these effects (p<0.05). Together, these data provide the first evidence that PPARγ may be a useful prognostic/predictive biomarker for HER2+ breast tumors, and suggest that the novel inclusion of PPARγ-activating drugs may benefit a subset of HER2+ breast cancer patients. Citation Format: Elizabeth D. Lightbody, Kathleen MJ O'Connell, Hailey T. Newton, Rachel R. Rubino, Anthony J. Apostoli, Kevin Ren, Sandip K. SenGupta, Christopher J. Nicol. PPARγ loss increases the metastatic potential of HER2+ breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 110.
