• The C/EBPdelta protein is stabilized by estrogen receptor α activity, inhibits SNAI2 expression and associates with good prognosis in breast cancer.

      Mendoza-Villanueva, D; Balamurugan, K; Ali, H; Kim, S; Sharan, S; Johnson, R; Merchant, A; Caldas, C; Landberg, Göran; Sterneck, E; et al. (2016-05-16)
      Hypoxia and inflammatory cytokines like interleukin-6 (IL-6, IL6) are strongly linked to cancer progression, and signal in part through the transcription factor Ccaat/enhancer-binding protein δ (C/EBPδ, CEBPD), which has been shown to promote mesenchymal features and malignant progression of glioblastoma. Here we report a different role for C/EBPδ in breast cancer. We found that the C/EBPδ protein is expressed in normal breast epithelial cells and in low-grade cancers. C/EBPδ protein (but not mRNA) expression correlates with estrogen receptor (ER+) and progesterone receptor (PGR) expression and longer progression-free survival of breast cancer patients. Specifically in ER+ breast cancers, CEBPD-but not the related CEBPB-mRNA in combination with IL6 correlated with lower risk of progression. Functional studies in cell lines showed that ERα promotes C/EBPδ expression at the level of protein stability by inhibition of the FBXW7 pathway. Furthermore, we found that C/EBPδ attenuates cell growth, motility and invasiveness by inhibiting expression of the SNAI2 (Slug) transcriptional repressor, which leads to expression of the cyclin-dependent kinase inhibitor CDKN1A (p21(CIP1/WAF1)). These findings identify a molecular mechanism by which ERα signaling reduces the aggressiveness of cancer cells, and demonstrate that C/EBPδ can have different functions in different types of cancer. Furthermore, our results support a potentially beneficial role for the IL-6 pathway specifically in ER+ breast cancer and call for further evaluation of the role of intra-tumoral IL-6 expression and of which cancers might benefit from current attempts to target the IL-6 pathway as a therapeutic strategy.Oncogene advance online publication, 16 May 2016; doi:10.1038/onc.2016.156.
    • Consensus on precision medicine for metastatic cancers: A report from the MAP conference.

      Swanton, C; Soria, J; Bardelli, A; Biankin, A; Caldas, C; Chandarlapaty, S; de Koning, L; Dive, Caroline; Feunteun, J; Leung, S; et al. (2016-05-03)
      Recent advances in biotechnologies have led to the development of multiplex genomic and proteomic analyses for clinical use. Nevertheless, guidelines are currently lacking to determine which molecular assays should be implemented in metastatic cancers. The 1(st) MAP conference was dedicated to exploring the use of genomics to better select therapies in the treatment of metastatic cancers. 16 consensus items were covered. While there was a consensus that new technologies like next-generation sequencing (NGS) of tumors and of ddPCR on circulating free DNA have convincing analytical validity, further work needs to be undertaken to establish both the clinical utility of liquid biopsies and the added clinical value of expanding from individual gene tests into large gene panels. Experts agreed that standardized bioinformatics methods for biological interpretation of genomic data are needed and that Precision Medicine trials should be stratified based on the level of evidence available for the genomic alterations identified.
    • Interrogating open issues in cancer precision medicine with patient-derived xenografts.

      Byrne, A; Alférez, Denis G; Amant, F; Annibali, D; Arribas, J; Biankin, A; Bruna, A; Budinská, E; Caldas, C; Chang, D; et al. (2017-01-20)
      Patient-derived xenografts (PDXs) have emerged as an important platform to elucidate new treatments and biomarkers in oncology. PDX models are used to address clinically relevant questions, including the contribution of tumour heterogeneity to therapeutic responsiveness, the patterns of cancer evolutionary dynamics during tumour progression and under drug pressure, and the mechanisms of resistance to treatment. The ability of PDX models to predict clinical outcomes is being improved through mouse humanization strategies and the implementation of co-clinical trials, within which patients and PDXs reciprocally inform therapeutic decisions. This Opinion article discusses aspects of PDX modelling that are relevant to these questions and highlights the merits of shared PDX resources to advance cancer medicine from the perspective of EurOPDX, an international initiative devoted to PDX-based research.
    • PDX-MI: Minimal information for patient-derived tumor Xenograft models.

      Meehan, T; Conte, N; Goldstein, T; Inghirami, G; Murakami, M; Brabetz, S; Gu, Z; Wiser, J; Dunn, P; Begley, D; et al. (2017-11-01)
      Patient-derived tumor xenograft (PDX) mouse models have emerged as an important oncology research platform to study tumor evolution, mechanisms of drug response and resistance, and tailoring chemotherapeutic approaches for individual patients. The lack of robust standards for reporting on PDX models has hampered the ability of researchers to find relevant PDX models and associated data. Here we present the PDX models minimal information standard (PDX-MI) for reporting on the generation, quality assurance, and use of PDX models. PDX-MI defines the minimal information for describing the clinical attributes of a patient's tumor, the processes of implantation and passaging of tumors in a host mouse strain, quality assurance methods, and the use of PDX models in cancer research. Adherence to PDX-MI standards will facilitate accurate search results for oncology models and their associated data across distributed repository databases and promote reproducibility in research studies using these models. Cancer Res; 77(21); e62-66. ©2017 AACR.