MAGE I Transcription Factors Regulate KAP1 and KRAB Domain Zinc Finger Transcription Factor Mediated Gene Repression

Class I MAGE proteins (MAGE I) are normally expressed only in developing germ cells but are aberrantly expressed in many cancers. They have been shown to promote tumor survival, aggressive growth, and chemoresistance but the underlying mechanisms and MAGE I functions have not been fully elucidated. KRAB domain zinc finger transcription factors (KZNFs) are the largest group of vertebrate transcription factors and regulate neoplastic transformation, tumor suppression, cellular proliferation, and apoptosis. KZNFs bind the KAP1 protein and direct KAP1 to specific DNA sequences where it suppresses gene expression by inducing localized heterochromatin characterized by histone 3 lysine 9 trimethylation (H3me3K9). Discovery that MAGE I proteins also bind to KAP1 prompted us to investigate whether MAGE I can affect KZNF and KAP1 mediated gene regulation. We found that expression of MAGE I proteins, MAGE-A3 or MAGE-C2, relieved repression of a reporter gene by ZNF382, a KZNF with tumor suppressor activity. ChIP of MAGE I (-) HEK293T cells showed KAP1 and H3me3K9 are normally bound to the ID1 gene, a target of ZNF382, but that binding is greatly reduced in the presence of MAGE I proteins. MAGE I expression relieved KAP1 mediated ID1 repression, causing increased expression of ID1 mRNA and ID1 chromatin relaxation characterized by loss of H3me3K9. MAGE I binding to KAP1 also induced ZNF382 poly-ubiquitination and degradation, consistent with loss of ZNF382 leading to decreased KAP1 binding to ID1. In contrast, MAGE I expression caused increased KAP1 binding to Ki67, another KAP1 target gene, with increased H3me3K9 and decreased Ki67 mRNA expression. Since KZNFs are required to direct KAP1 to specific genes, these results show that MAGE I proteins can differentially regulate members of the KZNF family and KAP1 mediated gene repression

An overview of cancer/testis antigens expression in classical Hodgkin's lymphoma (cHL) identifies MAGE-A family and MAGE-C1 as the most frequently expressed antigens in a set of Brazilian cHL patients

<p>Abstract</p> <p>Background</p> <p>Cancer/testis antigens are considered potential targets for immunotherapy due to their tumor-associated expression pattern. Although recent studies have demonstrated high expression of CT45 in classical Hodgkin's lymphomas (cHL), less is known about the expression pattern of other families of CTAs in cHL. We aim to evaluate the expression of MAGE-A family, MAGE-C1/CT7, MAGE-C2/CT10, NY-ESO1 and GAGE family in cHL and to correlate their expression with clinical and prognostic factors in cHL.</p> <p>Methods</p> <p>Tissue microarray was generated from 38 cHL archival cases from Pathology Department of Universidade Federal de Sao Paulo. Immunohistochemistry (IHC) was done using the following panel of antibodies: MAGE-A family (MA454, M3H67, 57B and 6C1), GAGE (#26), NY-ESO-1 (E978), MAGE-C1/CT7 (CT7-33) and MAGE-C2/CT10 (CT10#5).</p> <p>Results</p> <p>We found CTA expression in 21.1% of our cHL series. Among the tested CTAs, only MAGE-A family 7/38 (18.4%) and MAGE-C1/CT7 5/38 (13.2%) were positive in our cHL samples. We found higher CTA positivity in advanced stage (28.6%) compared to early stage (11.8%) disease, but this difference was not statistically significant. Analysis of other clinicopathological subgroups of cHL including histological subtypes, EBV status and response to treatment also did not demonstrate statistical significant differences in CTA expression.</p> <p>Conclusion</p> <p>We found CTA expression in 21.1% of cHL samples using our panel. Our preliminary findings suggest that from all CTAs included in this study, MAGE-A family and MAGE-C1/CT7 are the most interesting ones to be explored in further studies.</p

Errors in RNA-Seq quantification affect genes of relevance to human disease

BACKGROUND: RNA-Seq has emerged as the standard for measuring gene expression and is an important technique often used in studies of human disease. Gene expression quantification involves comparison of the sequenced reads to a known genomic or transcriptomic reference. The accuracy of that quantification relies on there being enough unique information in the reads to enable bioinformatics tools to accurately assign the reads to the correct gene. RESULTS: We apply 12 common methods to estimate gene expression from RNA-Seq data and show that there are hundreds of genes whose expression is underestimated by one or more of those methods. Many of these genes have been implicated in human disease, and we describe their roles. We go on to propose a two-stage analysis of RNA-Seq data in which multi-mapped or ambiguous reads can instead be uniquely assigned to groups of genes. We apply this method to a recently published mouse cancer study, and demonstrate that we can extract relevant biological signal from data that would otherwise have been discarded. CONCLUSIONS: For hundreds of genes in the human genome, RNA-Seq is unable to measure expression accurately. These genes are enriched for gene families, and many of them have been implicated in human disease. We show that it is possible to use data that may otherwise have been discarded to measure group-level expression, and that such data contains biologically relevant information. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13059-015-0734-x) contains supplementary material, which is available to authorized users