Herpesvirus Screening in Childhood Hematopoietic Transplant Reveals High Systemic Inflammation in Episodes of Multiple Viral Detection and an EBV Association with Elevated IL-1ß, IL-8 and Graft-Versus-Host Disease.

Infections remain a major cause of morbidity and mortality among hematopoietic stem cell transplant (HSCT) recipients. Unlike Epstein-Barr Virus (EBV) and Human Cytomegalovirus (HCMV), Human Herpesvirus (HHV) 6, HHV7 and HHV8 are not routinely monitored in many centers, especially in the pediatric population of low-medium income countries. We screened EBV, HCMV, HHV6, HHV7 and HHV8 in 412 leukocytes-plasma paired samples from 40 pediatric patients assisted in a tertiary hospital in Mexico. Thirty-two underwent allo-HSCT, whereas eight received auto-HSCT. Overall viral detection frequencies in allo- and auto-HSCT were: EBV = 43.7% and 30.0%, HCMV = 5.0% and 6.7%, HHV6 = 7.9% and 20.0% and HHV7 = 9.7% and 23.3%. HHV8 was not detected in any sample. Interestingly, HHV6 and HHV7 were more frequent in auto-HSCT, and HHV6 was observed in all episodes of multiple detection in auto-HSCT patients. We found EBV DNA in plasma samples, whereas HCMV, HHV6 and HHV7 DNA were predominantly observed in leukocytes, indicative of their expansion in cellular compartments. We also found that IL-1ß, IL-2, IL-6 and IL-8 were significantly increased in episodes in which multiple viruses were simultaneously detected, and samples positive for EBV DNA and graft-versus-host disease had a further increase of IL-1ß and IL-8. In conclusion, the EBV, HCMV, HHV6 and HHV7 burdens were frequently detected in allo- and auto-HSCT, and their presence associated with systemic inflammation.

Transcriptional Regulation of Yin-Yang 1 Expression through the Hypoxia Inducible Factor-1 in Pediatric Acute Lymphoblastic Leukemia.

Yin-Yang transcription factor 1 (YY1) is involved in tumor progression, metastasis and has been shown to be elevated in different cancers, including leukemia. The regulatory mechanism underlying YY1 expression in leukemia is still not understood. Bioinformatics analysis reveal three Hypoxia-inducible factor 1-alpha (HIF-1α) putative binding sites in the YY1 promoter region. The regulation of YY1 by HIF-1α in leukemia was analyzed. Mutation of the putative YY1 binding sites in a reporter system containing the HIF-1α promoter region and CHIP analysis confirmed that these sites are important for YY1 regulation. Leukemia cell lines showed that both proteins HIF-1α and YY1 are co-expressed under hypoxia. In addition, the expression of mRNA of YY1 was increased after 3 h of hypoxia conditions and affect several target genes expression. In contrast, chemical inhibition of HIF-1α induces downregulation of YY1 and sensitizes cells to chemotherapeutic drugs. The clinical implications of HIF-1α in the regulation of YY1 were investigated by evaluation of expression of HIF-1α and YY1 in 108 peripheral blood samples and by RT-PCR in 46 bone marrow samples of patients with pediatric acute lymphoblastic leukemia (ALL). We found that the expression of HIF-1α positively correlates with YY1 expression in those patients. This is consistent with bioinformatic analyses of several databases. Our findings demonstrate for the first time that YY1 can be transcriptionally regulated by HIF-1α, and a correlation between HIF-1α expression and YY1 was found in ALL clinical samples. Hence, HIF-1α and YY1 may be possible therapeutic target and/or biomarkers of ALL.

Automatic discovery of 100-miRNA signature for cancer classification using ensemble feature selection.

BACKGROUND: MicroRNAs (miRNAs) are noncoding RNA molecules heavily involved in human tumors, in which few of them circulating the human body. Finding a tumor-associated signature of miRNA, that is, the minimum miRNA entities to be measured for discriminating both different types of cancer and normal tissues, is of utmost importance. Feature selection techniques applied in machine learning can help however they often provide naive or biased results. RESULTS: An ensemble feature selection strategy for miRNA signatures is proposed. miRNAs are chosen based on consensus on feature relevance from high-accuracy classifiers of different typologies. This methodology aims to identify signatures that are considerably more robust and reliable when used in clinically relevant prediction tasks. Using the proposed method, a 100-miRNA signature is identified in a dataset of 8023 samples, extracted from TCGA. When running eight-state-of-the-art classifiers along with the 100-miRNA signature against the original 1046 features, it could be detected that global accuracy differs only by 1.4%. Importantly, this 100-miRNA signature is sufficient to distinguish between tumor and normal tissues. The approach is then compared against other feature selection methods, such as UFS, RFE, EN, LASSO, Genetic Algorithms, and EFS-CLA. The proposed approach provides better accuracy when tested on a 10-fold cross-validation with different classifiers and it is applied to several GEO datasets across different platforms with some classifiers showing more than 90% classification accuracy, which proves its cross-platform applicability. CONCLUSIONS: The 100-miRNA signature is sufficiently stable to provide almost the same classification accuracy as the complete TCGA dataset, and it is further validated on several GEO datasets, across different types of cancer and platforms. Furthermore, a bibliographic analysis confirms that 77 out of the 100 miRNAs in the signature appear in lists of circulating miRNAs used in cancer studies, in stem-loop or mature-sequence form. The remaining 23 miRNAs offer potentially promising avenues for future research.

Role of Yin Yang-1 (YY1) in the transcription regulation of the multi-drug resistance (MDR1) gene.

Resistance to chemotherapy hinders the successful treatment of acute lymphoblastic leukemia (ALL). The multi-drug resistance-1 (MDR1/ABCB1) gene encodes P-glycoprotein (P-gp), which plays an important role in chemoresistance; however, its transcriptional regulation remains unclear. We investigated the role of YY1 in the regulation of MDR1 and its relation to ALL outcomes. Analysis of the MDR1 promoter revealed four putative YY1-binding sites, which we analyzed using a reporter system and ChIP analysis. YY1 silencing resulted in the inhibition of MDR1 expression and function. The clinical roles of YY1 and MDR1 expression were evaluated in children with ALL. Expression of both proteins was increased in ALL patients compared to controls. We identified a positive correlation between YY1 and MDR1 expression. High levels of YY1 were associated with decreased overall survival. Our results demonstrated that YY1 regulates the transcription of MDR1. Therefore, YY1 may serve as a useful prognostic and/or therapeutic target.

Ectopic expression of new alternative splice variant of Smac/DIABLO increases mammospheres formation.

Smac-α is a mitochondrial protein that, during apoptosis, is translocated to the cytoplasm, where it negatively regulates members of the inhibitor of apoptosis (IAP) family via the IAP-binding motif (IBM) contained within its amino-terminus. Here, we describe a new alternative splice variant from Smac gene, which we have named Smac-ε. Smac-ε lacks both an IBM and a mitochondrial-targeting signal (MTS) element. Smac-ε mRNA exhibits a tissue-specific expression pattern in healthy human tissues as well as in several cancer cell lines. The steady-state levels of endogenous Smac-ε protein is regulated by the proteasomal pathway. When ectopically expressed, this isoform presents a cytosolic localization and is unable to associate with or to regulate the expression of X-linked Inhibitor of apoptosis protein, the best-studied member of IAP family. Nevertheless, over-expression of Smac-ε increases mammosphere formation. Whole genome expression analyses from these mammospheres show activation of several pro-survival and growth pathways, including Estrogen-Receptor signaling. In conclusion, our results support the functionality of this new Smac isoform.