Background Papillary renal cell carcinoma, accounting for 15% of renal cell carcinoma, is a heterogeneous disease consisting of different types of renal cancer, including tumors with indolent, multifocal presentation and solitary tumors with an aggressive, highly lethal phenotype. Little is known about the genetic basis of sporadic papillary renal cell carcinoma; no effective forms of therapy for advanced disease exist. Methods We performed comprehensive molecular characterization utilizing whole-exome sequencing, copy number, mRNA, microRNA, methylation and proteomic analyses of 161 primary papillary renal cell carcinomas. Results Type 1 and Type 2 papillary renal cell carcinomas were found to be different types of renal cancer characterized by specific genetic alterations, with Type 2 further classified into three individual subgroups based on molecular differences that influenced patient survival. MET alterations were associated with Type 1 tumors, whereas Type 2 tumors were characterized by CDKN2A silencing, SETD2 mutations, TFE3 fusions, and increased expression of the NRF2-ARE pathway. A CpG island methylator phenotype (CIMP) was found in a distinct subset of Type 2 papillary renal cell carcinoma characterized by poor survival and mutation of the fumarate hydratase (FH) gene. Conclusions Type 1 and Type 2 papillary renal cell carcinomas are clinically and biologically distinct. Alterations in the MET pathway are associated with Type 1 and activation of the NRF2-ARE pathway with Type 2; CDKN2A loss and CIMP in Type 2 convey a poor prognosis. Furthermore, Type 2 papillary renal cell carcinoma consists of at least 3 subtypes based upon molecular and phenotypic features.

Background Gene expression signatures have proven to be useful tools in many cancers to identify distinct subtypes of disease based on molecular features that drive pathogenesis, and to aid in predicting clinical outcomes. However, there are no current signatures for kidney cancer that are applicable in a clinical setting. Objective To generate a signature biomarker for the clear cell renal cell carcinoma (ccRCC) good risk (ccA) and poor risk (ccB) subtype classification that could be readily applied to clinical samples to develop an integrated model for biologically defined risk stratification. Design, setting, and participants A set of 72 ccRCC sample standards was used to develop a 34-gene classifier (ClearCode34) for assigning ccRCC tumors to subtypes. The classifier was applied to RNA-sequencing data from 380 nonmetastatic ccRCC samples from the Cancer Genome Atlas (TCGA), and to 157 formalin-fixed clinical samples collected at the University of North Carolina. Outcome measurements and statistical analysis Kaplan-Meier analyses were performed on the individual cohorts to calculate recurrence-free survival (RFS), cancer-specific survival (CSS), and overall survival (OS). Training and test sets were randomly selected from the combined cohorts to assemble a risk prediction model for disease recurrence. Results and limitations The subtypes were significantly associated with RFS (p < 0.01), CSS (p < 0.01), and OS (p < 0.01). Hazard ratios for subtype classification were similar to those of stage and grade in association with recurrence risk, and remained significant in multivariate analyses. An integrated molecular/clinical model for RFS to assign patients to risk groups was able to accurately predict CSS above established, clinical risk-prediction algorithms. Conclusions The ClearCode34-based model provides prognostic stratification that improves upon established algorithms to assess risk for recurrence and death for nonmetastatic ccRCC patients. Patient summary We developed a 34-gene subtype predictor to classify clear cell renal cell carcinoma tumors according to ccA or ccB subtypes and built a subtype-inclusive model to analyze patient survival outcomes.

SummaryLow-dose exposures to common environmental chemicals that are deemed safe individually may be combining to instigate carcinogenesis, thereby contributing to the incidence of cancer. This risk may be overlooked by current regulatory practices and needs to be vigorously investigated.

Preeclampsia (PE) is a pregnancy disorder characterized by high blood pressure and proteinuria that can cause adverse health effects in both mother and fetus. There is no current cure for PE other than delivery of the fetus. While the etiology is unknown, poor placentation of the placenta due to aberrant signaling of growth and angiogenic factors has been postulated as causal factors of PE. In addition, environmental contaminants, such as the metal cadmium (Cd), have been linked to placental toxicity and increased risk of developing PE. Here, we use a translational study design to investigate genomic and epigenomic alterations in both placentas and placental trophoblasts, focused on the angiogenesis-associated transforming growth factor-beta (TGF-β) pathway. Genes within the TGF-β pathway displayed increased expression in both the preeclamptic placenta and Cd-treated trophoblasts. In addition, miRNAs that target the TGF-β pathway were also significantly altered within the preeclamptic placenta and Cd-treated trophoblasts. Integrative analysis resulted in the identification of a subset of Cd-responsive miRNAs, including miR-26a and miR-155, common to preeclamptic placentas and Cd-treated trophoblasts. These miRNAs have previously been linked to PE and are predicted to regulate members of the TGF-β pathway. Results from this study provide future targets for PE treatment.

Studies have shown that tumor angiogenesis is an essential process for tumor growth, proliferation and metastasis. Also, tumor angiogenesis is an important prognostic factor of clear cell renal cell carcinoma (ccRCC), as well as a factor in guiding treatment with antiangiogenic agents. Here, we attempted to find the associations between tumor angiogenesis and radiomic imaging features from PET/MRI. Specifically, sparse canonical correlation analysis was conducted on 3 feature datasets (i.e., radiomic imaging features, tumor microvascular density (MVD), and vascular endothelial growth factor (VEGF) expression) from 9 patients with primary ccRCC. In order to overcome the potential bias of intratumoral heterogeneity of angiogenesis, this study investigated the relationship between regional expressions of angiogenesis and VEGF, and localized radiomic features from different parts within the tumors. Our study highlighted the significant strong correlations between radiomic features and MVD, and also demonstrated that the spatiotemporal features extracted from DCE-MRI provided stronger radiomic correlation to MVD than the textural features extracted from Dixon sequences and FDG PET. Furthermore, PET/MRI, which takes advantage of the combined functional and structural information, had higher radiomics correlation to MVD than solely utilizing PET or MRI alone.

Purpose The 34-gene classifier, ClearCode34, identifies prognostically distinct molecular subtypes of clear cell renal cell carcinoma (ccRCC) termed ccA and ccB. The primary objective of this study was to describe clinical characteristics and comorbidities of relevance in patients stratified by ClearCode34. Patients and Methods In this retrospective analysis, 282 patients from Moffitt Cancer Center with ccRCC with gene expression analyses of the primary tumor were identified and ClearCode34 was applied to identify tumors as ccA or ccB. The medical record and institutional databases were queried to define patient characteristics, comorbidities, and outcomes. Results We validated in this external cohort the superior overall survival (OS), cancer specific survival (CSS), and recurrence-free survival of ccA patients relative to ccB patients (p<0.001). Addressing other clinical characteristics, the ccA patients were more likely to be obese (48% versus 34%, p=0.021) and diabetic (26% versus 13%, p=0.035). The ccA patients also trended towards having been more frequent users of angiotensin system inhibitors (ASIs) (71% versus 52%, p=0.055). In multivariate analyses, ccB status is independently associated with inferior CSS (HR 3.26, 95% CI 1.84–5.79) and OS (HR 2.50, 95% CI 1.53–4.08). Conclusions ClearCode34, after considering distinct patterns of comorbidities in each molecular subtype, remains a strong prognostic tool in ccRCC patients. Obesity and DM emerged as factors that may influence ccRCC phenotypes and further studies investigating the impact of these metabolic conditions functionally onto tumor biology are warranted. Additionally, use of ASI could be studied in the context of ccRCC molecular classification in future studies to better understand its impact on ccRCC outcomes.

Purpose: Clear cell renal cell carcinoma (ccRCC) has recently been redefined as a highly heterogeneous disease. In addition to genetic heterogeneity, the tumor displays risk variability for developing metastatic disease, therefore underscoring the urgent need for tissue-based prognostic strategies applicable to the clinical setting. We have recently employed the novel PET/magnetic resonance (MR) image modality to enrich our understanding of how tumor heterogeneity can relate to gene expression and tumor biology to assist in defining individualized treatment plans.Experimental Design: ccRCC patients underwent PET/MR imaging, and these images subsequently used to identify areas of varied intensity for sampling. Samples from 8 patients were subjected to histologic, immunohistochemical, and microarray analysis.Results: Tumor subsamples displayed a range of heterogeneity for common features of hypoxia-inducible factor expression and microvessel density, as well as for features closely linked to metabolic processes, such as GLUT1 and FBP1. In addition, gene signatures linked with disease risk (ccA and ccB) also demonstrated variable heterogeneity, with most tumors displaying a dominant panel of features across the sampled regions. Intriguingly, the ccA-and ccB-classified samples corresponded with metabolic features and functional imaging levels. These correlations further linked a variety of metabolic pathways (i.e., the pentose phosphate and mTOR pathways) with the more aggressive, and glucose avid ccB subtype.Conclusions: Higher tumor dependency on exogenous glucose accompanies the development of features associated with the poor risk ccB subgroup. Linking these panels of features may provide the opportunity to create functional maps to enable enhanced visualization of the heterogeneous biologic processes of an individual's disease.

One of the important 'hallmarks' of cancer is angiogenesis, which is the process of formation of new blood vessels that are necessary for tumor expansion, invasion and metastasis. Under normal physiological conditions, angiogenesis is well balanced and controlled by endogenous proangiogenic factors and antiangiogenic factors. However, factors produced by cancer cells, cancer stem cells and other cell types in the tumor stroma can disrupt the balance so that the tumor microenvironment favors tumor angiogenesis. These factors include vascular endothelial growth factor, endothelial tissue factor and other membrane bound receptors that mediate multiple intracellular signaling pathways that contribute to tumor angiogenesis. Though environmental exposures to certain chemicals have been found to initiate and promote tumor development, the role of these exposures (particularly to low doses of multiple substances), is largely unknown in relation to tumor angiogenesis. This review summarizes the evidence of the role of environmental chemical bioactivity and exposure in tumor angiogenesis and carcinogenesis. We identify a number of ubiquitous (prototypical) chemicals with disruptive potential that may warrant further investigation given their selectivity for high-throughput screening assay targets associated with proangiogenic pathways. We also consider the cross-hallmark relationships of a number of important angiogenic pathway targets with other cancer hallmarks and we make recommendations for future research. Understanding of the role of low-dose exposure of chemicals with disruptive potential could help us refine our approach to cancer risk assessment, and may ultimately aid in preventing cancer by reducing or eliminating exposures to synergistic mixtures of chemicals with carcinogenic potential.