Systematic Evaluation of the Prognostic Impact and Intratumour Heterogeneity of Clear Cell Renal Cell Carcinoma Biomarkers

AbstractBackgroundCandidate biomarkers have been identified for clear cell renal cell carcinoma (ccRCC) patients, but most have not been validated.ObjectiveTo validate published ccRCC prognostic biomarkers in an independent patient cohort and to assess intratumour heterogeneity (ITH) of the most promising markers to guide biomarker optimisation.Design, setting, and participantsCancer-specific survival (CSS) for each of 28 identified genetic or transcriptomic biomarkers was assessed in 350 ccRCC patients. ITH was interrogated in a multiregion biopsy data set of 10 ccRCCs.Outcome measurements and statistical analysisBiomarker association with CSS was analysed by univariate and multivariate analyses.Results and limitationsA total of 17 of 28 biomarkers (TP53 mutations; amplifications of chromosomes 8q, 12, 20q11.21q13.32, and 20 and deletions of 4p, 9p, 9p21.3p24.1, and 22q; low EDNRB and TSPAN7 expression and six gene expression signatures) were validated as predictors of poor CSS in univariate analysis. Tumour stage and the ccB expression signature were the only independent predictors in multivariate analysis. ITH of the ccB signature was identified in 8 of 10 tumours. Several genetic alterations that were significant in univariate analysis were enriched, and chromosomal instability indices were increased in samples expressing the ccB signature. The study may be underpowered to validate low-prevalence biomarkers.ConclusionsThe ccB signature was the only independent prognostic biomarker. Enrichment of multiple poor prognosis genetic alterations in ccB samples indicated that several events may be required to establish this aggressive phenotype, catalysed in some tumours by chromosomal instability. Multiregion assessment may improve the precision of this biomarker.Patient summaryWe evaluated the ability of published biomarkers to predict the survival of patients with clear cell kidney cancer in an independent patient cohort. Only one molecular test adds prognostic information to routine clinical assessments. This marker showed good and poor prognosis results within most individual cancers. Future biomarkers need to consider variation within tumours to improve accuracy

Hormone-sensing cells require Wip1 for paracrine stimulation in normal and premalignant mammary epithelium

10.1186/bcr3381Breast Cancer Research15

Pubertal high fat diet: effects on mammary cancer development

INTRODUCTION: Epidemiological studies linking dietary fat intake and obesity to breast cancer risk have produced inconsistent results. This may be due to the difficulty of dissociating fat intake from obesity, and/or the lack of defined periods of exposure in these studies. The pubertal mammary gland is highly sensitive to cancer-causing agents. We assessed how high fat diet (HFD) affects inflammation, proliferative, and developmental events in the pubertal gland, since dysregulation of these can promote mammary tumorigenesis. To test the effect of HFD initiated during puberty on tumorigenesis, we utilized BALB/c mice, for which HFD neither induces obesity nor metabolic syndrome, allowing dissociation of HFD effects from other conditions associated with HFD. METHODS: Pubertal BALB/c mice were fed a low fat diet (12% kcal fat) or a HFD (60% kcal fat), and subjected to carcinogen 7,12-dimethylbenz[a]anthracene (DMBA)-induced tumorigenesis. RESULTS: HFD elevated mammary gland expression of inflammatory and growth factor genes at 3 and 4 weeks of diet. Receptor activator of nuclear factor kappa-B ligand (RANKL), robustly induced at 4 weeks, has direct mitogenic activity in mammary epithelial cells and, as a potent inducer of NF-κB activity, may induce inflammatory genes. Three weeks of HFD induced a transient influx of eosinophils into the mammary gland, consistent with elevated inflammatory factors. At 10 weeks, prior to the appearance of palpable tumors, there were increased numbers of abnormal mammary epithelial lesions, enhanced cellular proliferation, increased growth factors, chemokines associated with immune-suppressive regulatory T cells, increased vascularization, and elevated M2 macrophages. HFD dramatically reduced tumor latency. Early developing tumors were more proliferative and were associated with increased levels of tumor-related growth factors, including increased plasma levels of HGF in tumor-bearing animals. Early HFD tumors also had increased vascularization, and more intra-tumor and stromal M2 macrophages. CONCLUSIONS: Taken together in this non-obesogenic context, HFD promotion of inflammatory processes, as well as local and systemically increased growth factor expression, are likely responsible for the enhanced tumorigenesis. It is noteworthy that although DMBA mutagenesis is virtually random in its targeting of genes in tumorigenesis, the short latency tumors arising in animals on HFD showed a unique gene expression profile, highlighting the potent overarching influence of HFD

Key signaling nodes in mammary gland development and cancer: β-catenin

β-Catenin plays important roles in mammary development and tumorigenesis through its functions in cell adhesion, signal transduction and regulation of cell-context-specific gene expression. Studies in mice have highlighted the critical role of β-catenin signaling for stem cell biology at multiple stages of mammary development. Deregulated β-catenin signaling disturbs stem and progenitor cell dynamics and induces mammary tumors in mice. Recent data showing deregulated β-catenin signaling in metaplastic and basal-type tumors suggest a similar link to reactivated developmental pathways and human breast cancer. The present review will discuss β-catenin as a central transducer of numerous signaling pathways and its role in mammary development and breast cancer

Integrative genome-wide expression profiling identifies three distinct molecular subgroups of renal cell carcinoma with different patient outcome

ABSTRACT: BACKGROUND: Renal cell carcinoma (RCC) is characterized by a number of diverse molecular aberrations that differ among individuals. Recent approaches to molecularly classify RCC were based on clinical, pathological as well as on single molecular parameters. As a consequence, gene expression patterns reflecting the sum of genetic aberrations in individual tumors may not have been recognized. In an attempt to uncover such molecular features in RCC, we used a novel, unbiased and integrative approach. METHODS: We integrated gene expression data from 97 primary RCCs of different pathologic parameters, 15 RCC metastases as well as 34 cancer cell lines for two-way nonsupervised hierarchical clustering using gene groups suggested by the PANTHER Classification System. We depicted the genomic landscape of the resulted tumor groups by means of Single Nuclear Polymorphism (SNP) technology. Finally, the achieved results were immunohistochemically analyzed using a tissue microarray (TMA) composed of 254 RCC. Results: We found robust, genome wide expression signatures, which split RCC into three distinct molecular subgroups. These groups remained stable even if randomly selected gene sets were clustered. Notably, the pattern obtained from RCC cell lines was clearly distinguishable from that of primary tumors. SNP array analysis demonstrated differing frequencies of chromosomal copy number alterations among RCC subgroups. TMA analysis with group-specific markers showed a prognostic significance of the different groups. Conclusion: We propose the existence of characteristic and histologically independent genome-wide expression outputs in RCC with potential biological and clinical relevance

ERrrr…Where are the Progenitors? Hormone Receptors and Mammary Cell Heterogeneity

The mammary epithelium is a highly heterogenous and dynamic tissue that includes a range of cell types with varying levels of proliferative capacity and differentiation potential, from stem to committed progenitor and mature cells. Generation of mature cells through expansion and specification of immature precursors is driven by hormonal and local stimuli. Intriguingly, although circulating hormones can be directly sensed only by a subset of mammary cells, they also regulate the behaviour of cells lacking their cognate receptors through paracrine mechanisms. Thus, mapping the hormonal signalling network on to the emerging mammary cell hierarchy appears to be a difficult task. Nevertheless, a first step towards a better understanding is the characterization of the hormone receptor expression pattern across individual cell types in the mammary epithelium. Here we review the most relevant findings on the cellular distribution of hormone receptors in the mammary gland, taking into account differences between mice and humans, the methods employed to assess receptor expression as well as the variety of approaches used to resolve the mammary cell heterogeneity