Computational Screening of Anti-Cancer Drugs Identifies a New BRCA Independent Gene Expression Signature to Predict Breast Cancer Sensitivity to Cisplatin.

The development of therapies that target specific disease subtypes has dramatically improved outcomes for patients with breast cancer. However, survival gains have not been uniform across patients, even within a given molecular subtype. Large collections of publicly available drug screening data matched with transcriptomic measurements have facilitated the development of computational models that predict response to therapy. Here, we generated a series of predictive gene signatures to estimate the sensitivity of breast cancer samples to 90 drugs, comprising FDA-approved drugs or compounds in early development. To achieve this, we used a cell line-based drug screen with matched transcriptomic data to derive in silico models that we validated in large independent datasets obtained from cell lines and patient-derived xenograft (PDX) models. Robust computational signatures were obtained for 28 drugs and used to predict drug efficacy in a set of PDX models. We found that our signature for cisplatin can be used to identify tumors that are likely to respond to this drug, even in absence of the BRCA-1 mutation routinely used to select patients for platinum-based therapies. This clinically relevant observation was confirmed in multiple PDXs. Our study foreshadows an effective delivery approach for precision medicine.

The site of breast cancer metastases dictates their clonal composition and reversible transcriptomic profile.

Intratumoral heterogeneity is a driver of breast cancer progression, but the nature of the clonal interactive network involved in this process remains unclear. Here, we optimized the use of optical barcoding to visualize and characterize 31 cancer subclones in vivo. By mapping the clonal composition of thousands of metastases in two clinically relevant sites, the lungs and liver, we found that metastases were highly polyclonal in lungs but not in the liver. Furthermore, the transcriptome of the subclones varied according to their metastatic niche. We also identified a reversible niche-driven signature that was conserved in lung and liver metastases collected during patient autopsies. Among this signature, we found that the tumor necrosis factor-α pathway was up-regulated in lung compared to liver metastases, and inhibition of this pathway affected metastasis diversity. These results highlight that the cellular and molecular heterogeneity observed in metastases is largely dictated by the tumor microenvironment.

Changes in MiRNA-5196 Expression as a Potential Biomarker of Anti-TNF-α Therapy in Rheumatoid Arthritis and Ankylosing Spondylitis Patients.

In this study, we analysed the expression level of sera circulating miRNA-5196 in rheumatoid arthritis (RA) and ankylosing spondylitis (AS) patients before and after tumor necrosis factor (TNF)-α therapy as biomarkers predicting positive treatment outcome. We enrolled 10 RA patients, 13 AS patients, and 12 healthy individuals in the study. The expression of miRNA-5196 was measured by real-time polymerase chain reaction before and after anti-TNF-α therapy. Disease activity of RA patients was assessed using disease activity score 28 (DAS28), whereas ankylosing spondylitis DAS (ASDAS) was used in AS patients. MiRNA-5196 expression was significantly higher in patients with RA and AS before TNF-α therapy than in those following anti-TNF-α therapy and healthy controls. Changes in miRNA-5196 expression positively correlated with delta DAS28 or delta ASDAS, respectively, following TNF-α therapy. In contrast, changes in C-reactive protein (CRP) levels in RA and AS patients did not positively correlate with DAS28 or ASDAS changes. Receiver-operating characteristic analysis showed better diagnostic accuracy of miRNA-5196 expression both in RA (area under curve (AUC) = 0.87, p = 0.055) and AS patients (AUC = 0.90, p = 0.050) compared to CRP levels in RA (AUC = 0.75, p = 0.201) and AS patients (AUC = 0.85, p = 0.086) upon biologic therapy treatment. Finding novel biomarkers, including miRNA-5196 which allow to predict and monitor anti-TNF-α response, would be of clinical value especially during the early phase of RA or AS development.

The role of microRNA-5196 in the pathogenesis of systemic sclerosis.

BACKGROUND: Systemic sclerosis (SSc) is a chronic autoimmune disease characterised by tissue fibrosis and immune abnormalities. Recent evidence suggests that activated circulating monocytes from patients with SSc play an important role in early stages of SSc pathogenesis due to enhanced expression of tissue inhibitor of metalloproteinases 1 (TIMP-1), IL-8 and reactive oxygen species (ROS) induction. However, the exact factors that contribute to chronic inflammation and subsequently fibrosis progression are still unknown. MATERIALS AND METHODS: The expression pattern of IL-8, TIMP-1, AP-1 transcription factor-Fra2 and ROS induction in peripheral blood monocytes following DZNep (histone methyltransferase inhibitor) and TLR8 agonist stimulation was investigated. Exogenous microRNA-5196, which is predicted to bind 3'UTR of Fra2 gene, was delivered to reverse profibrotic phenotype in monocytes. Expression of circulating microRNA-5196 was correlated with SSc parameters. RESULTS: DZNep + TLR8 agonist stimulation enhanced profibrotic TIMP-1, IL-8 and ROS generation in HC and SSc monocytes. As opposed by the decrease of miRNA-5196 and antioxidant SOD1 expression in SSc monocytes. Exogenous delivery of microRNA-5196 reduced Fra2 and TIMP-1 expression suggesting that it may be used as a potential modulator of fibrogenesis in SSc. Circulating microRNA-5196 was significantly increased in SSc and positively correlated with CRP level but not with Rodnan skin score or ESR. CONCLUSIONS: These results suggest that microRNA-5196 can be used as a potential biomarker characterising SSc. Overall, this study may open new possibilities for the development of microRNA-5196-based diagnostics and therapy in early phases of SSc.