Understanding the molecular underpinnings of cancer is of critical importance to developing targeted intervention strategies. Identification of such targets, however, is notoriously difficult and unpredictable. Malignant cell transformation requires the cooperation of a few oncogenic mutations that cause substantial reorganization of many cell features 1 and induce complex changes in gene expression patterns 2-6 . Genes critical to this multi-faceted cellular phenotype thus only have been identified following signaling pathway analysis 7-10 or on an ad hoc basis 4, 11-14 . Our observations that cell transformation by cooperating oncogenic lesions depends on synergistic modulation of downstream signaling circuitry 15-17 suggest that malignant transformation is a highly cooperative process, involving synergy at multiple levels of regulation, including gene expression. Here we show that a large proportion of genes controlled synergistically by loss-of-function p53 and Ras activation are critical to the malignant state. Remarkably, 14 among 24 such 'cooperation response genes' (CRGs) were found to contribute to tumor formation in gene perturbation experiments. In contrast, only one in 14 perturbations of genes responding in a non-synergistic manner had a similar effect. Synergistic control of gene expression by oncogenic mutations thus emerges as an underlying key to malignancy and provides an attractive rationale for identifying intervention targets in gene networks downstream of oncogenic gain and loss-of-function mutations.To identify genes regulated synergistically by cooperating oncogenic mutations at genomic scale, we compared mRNA expression profiles of young adult murine colon (YAMC) cells

Motivation: Quantitative real-time PCR (qPCR) is one of the most widely used methods to measure gene expression. Despite extensive research in qPCR laboratory protocols, normalization and statistical analysis, little attention has been given to qPCR non-detects—those reactions failing to produce a minimum amount of signal.Results: We show that the common methods of handling qPCR non-detects lead to biased inference. Furthermore, we show that non-detects do not represent data missing completely at random and likely represent missing data occurring not at random. We propose a model of the missing data mechanism and develop a method to directly model non-detects as missing data. Finally, we show that our approach results in a sizeable reduction in bias when estimating both absolute and differential gene expression.Availability and implementation: The proposed algorithm is implemented in the R package, . This package also contains the raw data for the three example datasets used in this manuscript. The package is freely available at http://mnmccall.com/software and as part of the Bioconductor project.Contact: mccallm@gmail.com

Human papillomaviruses (HPVs) cause squamous cancers of epithelial surfaces, of which genital cancers are the most common. In this article we have attempted to describe the properties and functions of the viral proteins of HPV type 16, a common cause of genital cancers, and have tried to suggest how their expression may lead to a dysregulated cell which may become malignant. These viruses are attempting to replicate in terminally differentiating keratinocytes and must stimulate G1 to S-phase progression for the replication of their genome. As part of the successful completion of replication and assembly of infectious virus particles, the virus needs at least partial differentiation to occur. Therefore, at the same time as differentiation is occurring, the nuclei of infected cells are in S-phase. While the mechanisms of action of the viral proteins are not completely understood, researchers are making progress and this article strives to bring together the conclusions from some of this work.

Human papillomavirus type 16 (HPV-16), a DNA tumor virus, has a causal role in cervical cancer, and the viral oncoproteins E6 and E7 contribute to oncogenesis in multiple ways. E6 increases telomerase activity in keratinocytes through increased transcription of the telomerase catalytic subunit gene (TERT), but the factors involved in this have been elusive. We have found that mutation of the proximal E box in the TERT promoter has an activating effect in luciferase assays. This suggested that a repressive complex might be present at this site. HPV-16 E6 activated the TERT promoter predominantly through the proximal E box, and thus, might be acting on this repressive complex. This site is specific for the Myc/Mad/Max transcription factors as well as USF1 and USF2. Addition of exogenous USF1 or USF2 repressed activation of the TERT promoter by E6, dependent on the proximal E box. Using siRNA against USF1 or USF2 allowed for greater activation of the TERT promoter by E6. Conversely, loss of c-Myc function, through a dominant-negative Myc molecule, reduced activation by E6. Chromatin immunoprecipitations showed that in the presence of E6, there was a reduction in binding of USF1 and USF2 at the TERT promoter proximal E box, and a concomitant increase in c-Myc bound to this site. This shows that a repressive complex containing USF1 and USF2 is present in normal cells with little or no telomerase activity. In E6 keratinocytes, this repressive complex is replaced by c-Myc, which corresponds to higher levels of TERT transcription and consequently, telomerase activity.

Bone marrow mesenchymal stromal cells (MSCs) constitute one of the important components of the hematopoietic microenvironmental niche. In vivo studies have shown that depletion of marrow MSCs resulted in reduction of hematopoietic stem cell content, and there is in vitro evidence that marrow MSCs are able to support leukemia progenitor cell proliferation and survival and provide resistance to cytotoxic therapies. How MSCs from leukemia marrow differ from normal counterparts and how they are influenced by the presence of leukemia stem and progenitor cells are still incompletely understood. In this work, we compared normal donor (ND) and acute myelogenous leukemia (AML) derived MSCs and found that AML-MSCs had increased adipogenic potential with improved ability to support survival of leukemia progenitor cells. To identify underlying changes, RNA-Seq analysis was performed. Gene ontology and pathway analysis revealed adipogenesis to be among the set of altered biological pathways dysregulated in AML-MSCs as compared with ND-MSCs. Expression of both SOX9 and EGR2 was decreased in AML-MSCs as compared with ND-MSCs. Increasing expression of SOX9 decreased adipogenic potential of AML-MSCs and decreased their ability to support AML progenitor cells. These findings suggest that AML-MSCs possess adipogenic potential which may enhance support of leukemia progenitor cells.