Noise filtering and nonparametric analysis of microarray data underscores discriminating markers of oral, prostate, lung, ovarian and breast cancer

BACKGROUND: A major goal of cancer research is to identify discrete biomarkers that specifically characterize a given malignancy. These markers are useful in diagnosis, may identify potential targets for drug development, and can aid in evaluating treatment efficacy and predicting patient outcome. Microarray technology has enabled marker discovery from human cells by permitting measurement of steady-state mRNA levels derived from thousands of genes. However many challenging and unresolved issues regarding the acquisition and analysis of microarray data remain, such as accounting for both experimental and biological noise, transcripts whose expression profiles are not normally distributed, guidelines for statistical assessment of false positive/negative rates and comparing data derived from different research groups. This study addresses these issues using Affymetrix HG-U95A and HG-U133 GeneChip data derived from different research groups. RESULTS: We present here a simple non parametric approach coupled with noise filtering to identify sets of genes differentially expressed between the normal and cancer states in oral, breast, lung, prostate and ovarian tumors. An important feature of this study is the ability to integrate data from different laboratories, improving the analytical power of the individual results. One of the most interesting findings is the down regulation of genes involved in tissue differentiation. CONCLUSIONS: This study presents the development and application of a noise model that suppresses noise, limits false positives in the results, and allows integration of results from individual studies derived from different research groups

Analysis of Epstein-Barr virus reservoirs in paired blood and breast cancer primary biopsy specimens by real time PCR

INTRODUCTION: Epstein-Barr virus (EBV) is present in over 90% of the world's population. This infection is considered benign, even though in limited cases EBV is associated with infectious and neoplastic conditions. Over the past decade, the EBV association with breast cancer has been constantly debated. Adding to this clinical and biological uncertainty, different techniques gave contradictory results for the presence of EBV in breast carcinoma specimens. In this study, minor groove binding (MGB)-TaqMan real time PCR was used to detect the presence of EBV DNA in both peripheral blood and tumor samples of selected patients. METHODS: Peripheral blood and breast carcinoma specimens from 24 patients were collected. DNA was extracted and then amplified by MGB-TaqMan real time PCR. RESULTS: Of 24 breast tumor specimens, 11 (46%) were positive for EBV DNA. Of these 11 breast tumor specimens, 7 (64%) were also positive for EBV DNA in the peripheral blood, while 4 (36%) were positive for EBV DNA in the tumor, but negative in the blood. CONCLUSION: EBV was found at extremely low levels, with a mean of 0.00004 EBV genomes per cell (range 0.00014 to 0.00001 EBV genomes per cell). Furthermore, our finding of the presence of EBV in the tumor specimens coupled to the absence of detection of EBV genomic DNA in the peripheral blood is consistent with the epithelial nature of the virus. Because of the low levels of viral DNA in tumor tissue, further studies are needed to assess the biological input of EBV in breast cancer

Identification of Direct Transcriptional Targets of the Kaposi's Sarcoma-Associated Herpesvirus Rta Lytic Switch Protein by Conditional Nuclear Localization▿

Lytic reactivation from latency is critical for the pathogenesis of Kaposi's sarcoma-associated herpesvirus (KSHV). We previously demonstrated that the 691-amino-acid (aa) KSHV Rta transcriptional transactivator is necessary and sufficient to reactivate the virus from latency. Viral lytic cycle genes, including those expressing additional transactivators and putative oncogenes, are induced in a cascade fashion following Rta expression. In this study, we sought to define Rta's direct targets during reactivation by generating a conditionally nuclear variant of Rta. Wild-type Rta protein is constitutively localized to cell nuclei and contains two putative nuclear localization signals (NLSs). Only one NLS (NLS2; aa 516 to 530) was required for the nuclear localization of Rta, and it relocalized enhanced green fluorescent protein exclusively to cell nuclei. The results of analyses of Rta NLS mutants demonstrated that proper nuclear localization of Rta was required for transactivation and the stimulation of viral reactivation. RTA with NLS1 and NLS2 deleted was fused to the hormone-binding domain of the murine estrogen receptor to generate an Rta variant whose nuclear localization and ability to transactivate and induce reactivation were tightly controlled posttranslationally by the synthetic hormone tamoxifen. We used this strategy in KSHV-infected cells treated with protein synthesis inhibitors to identify direct transcriptional targets of Rta. Rta activated only eight KSHV genes in the absence of de novo protein synthesis. These direct transcriptional targets of Rta were transactivated to different levels and included the genes nut-1/PAN, ORF57/Mta, ORF56/Primase, K2/viral interleukin-6 (vIL-6), ORF37/SOX, K14/vOX, K9/vIRF1, and ORF52. Our data suggest that the induction of most of the KSHV lytic cycle genes requires additional protein expression after the expression of Rta

Noise filtering and nonparametric analysis of microarray data underscores discriminating markers of oral, prostate, lung, ovarian and breast cancer

Abstract Background A major goal of cancer research is to identify discrete biomarkers that specifically characterize a given malignancy. These markers are useful in diagnosis, may identify potential targets for drug development, and can aid in evaluating treatment efficacy and predicting patient outcome. Microarray technology has enabled marker discovery from human cells by permitting measurement of steady-state mRNA levels derived from thousands of genes. However many challenging and unresolved issues regarding the acquisition and analysis of microarray data remain, such as accounting for both experimental and biological noise, transcripts whose expression profiles are not normally distributed, guidelines for statistical assessment of false positive/negative rates and comparing data derived from different research groups. This study addresses these issues using Affymetrix HG-U95A and HG-U133 GeneChip data derived from different research groups. Results We present here a simple non parametric approach coupled with noise filtering to identify sets of genes differentially expressed between the normal and cancer states in oral, breast, lung, prostate and ovarian tumors. An important feature of this study is the ability to integrate data from different laboratories, improving the analytical power of the individual results. One of the most interesting findings is the down regulation of genes involved in tissue differentiation. Conclusions This study presents the development and application of a noise model that suppresses noise, limits false positives in the results, and allows integration of results from individual studies derived from different research groups.</p

Guidelines for the use and interpretation of assays for monitoring autophagy

In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. A key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process vs. those that measure flux through the autophagy pathway (i.e., the complete process); thus, a block in macroautophagy that results in autophagosome accumulation needs to be differentiated from stimuli that result in increased autophagic activity, defined as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (in most higher eukaryotes and some protists such as Dictyostelium) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the field understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular autophagy assays, we hope to encourage technical innovation in the field

Guidelines for the use and interpretation of assays for monitoring autophagy

In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. A key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process vs. those that measure flux through the autophagy pathway (i.e., the complete process); thus, a block in macroautophagy that results in autophagosome accumulation needs to be differentiated from stimuli that result in increased autophagic activity, defined as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (in most higher eukaryotes and some protists such as Dictyostelium) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the field understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular autophagy assays, we hope to encourage technical innovation in the field