Cell cycle and immune-related processes are significantly altered in chronic GVHD

Prognostic value of lipid metabolism-related genes in head and neck squamous cell carcinoma

BACKGROUND

Altered lipid metabolism is involved in the development of many tumors. However, the role of dissimilar lipid metabolism in head and neck squamous cell carcinoma (HNSCC) is not fully established.

AIMS

Here, we sought to determine the prognostic value of lipid metabolism-related genes in HNSCC.

METHODS

RNA-seq data and clinical features of 545 HNSCC cases were obtained from The Cancer Genome Atlas database. A regulatory network of transcription factors-lipid metabolism genes and a risk prognostic model of lipid metabolism-related genes was developed using bioinformatics and Cox regression modeling. We used tumor immune estimation resource to analyze immune cell infiltration in patients with HNSCC based on the prognostic index (PI) of lipid metabolism-related genes.

RESULTS

A total of 136 differentially expressed lipid metabolism genes were identified. Of these, 23 are related to prognosis. In addition to predicting HNSCC prognosis, 11 lipid metabolism-related genes (ARSI, CYP27B1, CYP2D6, DGKG, DHCR7, LPIN1, PHYH, PIP5K1B, PLA2G2D, RDH16, and TRIB3) also affect HNSCC clinical features (stage, gender, and pathological stage). The PI of lipid metabolism-related genes embodied the state of HNSCC tumor immune microenvironment.

MicroRNAs as Potential Diagnostic, Prognostic, and Predictive Biomarkers for Acute Graft-versus-Host Disease

Successful treatment of various hematologic diseases with allogeneic hematopoietic stem cell transplantation is often limited due to the occurrence of acute graft-versus-host disease (aGVHD). So far, there are no approved molecular biomarkers for the diagnosis and prediction of aGVHD at the clinical level due to our incomplete understanding of the molecular biology of the disease. Various studies have been conducted on animal models and humans to investigate the role of microRNAs in aGVHD pathogenesis to implicate them as biomarkers and therapeutic targets. Because of their high stability, tissue specificity, ease of measurement, low cost, and simplicity, they are excellent targets for biomarkers. In this review, we focused on microRNA expression profiling studies that were performed recently in both animal models and human cases of aGVHD to identify diagnostic and predictive biomarkers for this disease. The expression pattern of microRNAs can be specific to cells and tissues. Because aGVHD affects several organs, microRNA signatures in target tissues may help to understand the molecular pathology of the disease. Identification of organ-specific microRNAs in aGVHD can be promising to categorize patients for organ-specific therapies. Thus, microRNAs can be used as noninvasive diagnostic tests in clinic to improve prophylaxis, predict incidence and severity, and reduce morbidity.

Serum and Extracellular Vesicle MicroRNAs miR-423, miR-199, and miR-93* As Biomarkers for Acute Graft-versus-Host Disease

Acute graft-versus-host disease (aGvHD) is a major cause of adverse outcome in hematopoietic stem cell transplantation (HSCT), with a high incidence (20–50%). A novel, non-invasive diagnostic test to predict for prevalence and severity would enable improved prophylaxis and reduce morbidity. Circulatory microRNAs (miRNAs) miR-423, miR-199, miR-93*, and miR-377 have previously been associated with aGvHD in post-HSCT patient plasma, but validation is lacking and their expression within extracellular vesicles (EVs) has not been explored. This study replicated elevated serum expression of miR-423 (p < 0.001), miR-199 (p = 0.04), miR-93* (p < 0.001), and miR-377 (p = 0.03) in aGvHD, using a prognostic cohort of day 14 (D14) post-HSCT patient samples (n = 81). Expression also associated with disease severity. Further analysis at aGvHD diagnosis in an independent cohort (n = 65) confirmed high miR-423 (p = 0.02), miR-199 (p = 0.007), and miR-93* (p = 0.004) expression at disease onset. Investigation of expression patterns during early HSCT sequential timepoints (pre-HSCT to D28) identified elevated miRNAs at D7 post-HSCT in all transplant patients. In a novel investigation of miRNA expression in serum EVs (n = 15), miR-423 (p = 0.09), miR-199 (p = 0.008), and miR-93* (p = 0.001) levels were lower at D14 in patients who later developed aGvHD, and this was replicated for miR-423 (p = 0.02) and miR-199 (p = 0.04) (n = 47). Comparing serum to circulating EVs, at D14 patients remaining aGvHD-free had higher expression of miR-423 (p = 0.03), miR-199 (p = 0.009), and miR-93* (p = 0.002) in the EV fraction. Results verify the capacity for circulating miR-423, miR-199, and miR-93* as diagnostic and prognostic aGvHD biomarkers. The novel finding of their differential expression in EVs suggests a potential role in aGvHD etiology.

Integrating and mining diverse data in human immunological studies

Bioanalysts and immunologists can interrogate the immune system with a variety of high-throughput technologies such as gene expression, multiplex bead arrays and flow cytometry. Conceptually, these assays support systems immunology studies, in which phenomena can be measured and correlated across biological compartments. First, however, the resulting high-dimensional data must be combined in a consistent fashion that supports analysis of the data as an integrated whole. Next, analytical methods must be applied to the hundreds or thousands of readouts. We recommend the use of a four-part analytical pipeline, consisting of data integration, hypothesis generation, prediction and hypothesis testing, and validation. We describe a variety of established methods appropriate for these integrated datasets, and highlight their application to human immunological studies. Our goal is to provide bioanalysts, immunologists and data analysts with a valuable perspective with which to approach the multiassay high-dimensional datasets generated by contemporary immunological studies.

Identification of gene microarray expression profiles in patients with chronic graft-versus-host disease following allogeneic hematopoietic cell transplantation

Chronic graft-versus-host disease (GVHD) results in significant morbidity and mortality, limiting the benefit of allogeneic hematopoietic cell transplantation (HCT). Peripheral blood gene expression profiling of the donor immune repertoire following HCT may provide associated genes and pathways thereby improving the pathophysiologic understanding of chronic GVHD. We profiled 70 patients and identified candidate genes that provided mechanistic insight in the biologic pathways that underlie chronic GVHD. Our data revealed that the dominant gene signature in patients with chronic GVHD represented compensatory responses that control inflammation and included the interleukin-1 decoy receptor, IL-1 receptor type II, and genes that were profibrotic and associated with the IL-4, IL-6 and IL-10 signaling pathways. In addition, we identified three genes that were important regulators of extracellular matrix. Validation of this discovery phase study will determine if the identified genes have diagnostic, prognostic or therapeutic implications.

Human regulatory T cells in allogeneic stem cell transplantation

GVHD is still one of the major complications after allogeneic stem cell transplantation. Whereas murine data have clearly shown the beneficial effects of regulatory T cells (Tregs) on the prevention of GVHD, data from the human system are rare. Here, we present a comparative dynamic analysis of CD4+CD25hiCD127lo/− Tregs from patients with and without GVHD analyzing the whole genome profile over the first 6 months after stem cell transplantation, representing the most sensitive time window for tolerance induction. The Treg transcriptome showed a high stability. However, the comparison of Treg transcriptomes from patients with and without GVHD uncovered regulated gene transcripts highly relevant for Treg cell function. The confirmative protein analyses demonstrated a significantly higher expression of granzyme A, CXCR3, and CCR5 in Tregs of immune tolerant patients. These results point to a reduced suppressive function of Tregs from GVHD patients with diminished migration capacity to the target organs.

Expression profiling of major histocompatibility and natural killer complex genes reveals candidates for controlling risk of graft versus host disease

Background

The major histocompatibility complex (MHC) is the most important genomic region that contributes to the risk of graft versus host disease (GVHD) after haematopoietic stem cell transplantation. Matching of MHC class I and II genes is essential for the success of transplantation. However, the MHC contains additional genes that also contribute to the risk of developing acute GVHD. It is difficult to identify these genes by genetic association studies alone due to linkage disequilibrium in this region. Therefore, we aimed to identify MHC genes and other genes involved in the pathophysiology of GVHD by mRNA expression profiling.

Methodology/Principal Findings

To reduce the complexity of the task, we used genetically well-defined rat inbred strains and a rat skin explant assay, an in-vitro-model of the graft versus host reaction (GVHR), to analyze the expression of MHC, natural killer complex (NKC), and other genes in cutaneous GVHR. We observed a statistically significant and strong up or down regulation of 11 MHC, 6 NKC, and 168 genes encoded in other genomic regions, i.e. 4.9%, 14.0%, and 2.6% of the tested genes respectively. The regulation of 7 selected MHC and 3 NKC genes was confirmed by quantitative real-time PCR and in independent skin explant assays. In addition, similar regulations of most of the selected genes were observed in GVHD-affected skin lesions of transplanted rats and in human skin explant assays.

Conclusions/Significance

We identified rat and human MHC and NKC genes that are regulated during GVHR in skin explant assays and could therefore serve as biomarkers for GVHD. Several of the respective human genes, including HLA-DMB, C2, AIF1, SPR1, UBD, and OLR1, are polymorphic. These candidates may therefore contribute to the genetic risk of GVHD in patients.

A transcription factor map as revealed by a genome-wide gene expression analysis of whole-blood mRNA transcriptome in multiple sclerosis

Background

Several lines of evidence suggest that transcription factors are involved in the pathogenesis of Multiple Sclerosis (MS) but complete mapping of the whole network has been elusive. One of the reasons is that there are several clinical subtypes of MS and transcription factors that may be involved in one subtype may not be in others. We investigate the possibility that this network could be mapped using microarray technologies and contemporary bioinformatics methods on a dataset derived from whole blood in 99 untreated MS patients (36 Relapse Remitting MS, 43 Primary Progressive MS, and 20 Secondary Progressive MS) and 45 age-matched healthy controls.

Methodology/Principal Findings

We have used two different analytical methodologies: a non-standard differential expression analysis and a differential co-expression analysis, which have converged on a significant number of regulatory motifs that are statistically overrepresented in genes that are either differentially expressed (or differentially co-expressed) in cases and controls (e.g., V$KROX_Q6, p-value <3.31E-6; V$CREBP1_Q2, p-value <9.93E-6, V$YY1_02, p-value <1.65E-5).

Conclusions/Significance

Our analysis uncovered a network of transcription factors that potentially dysregulate several genes in MS or one or more of its disease subtypes. The most significant transcription factor motifs were for the Early Growth Response EGR/KROX family, ATF2, YY1 (Yin and Yang 1), E2F-1/DP-1 and E2F-4/DP-2 heterodimers, SOX5, and CREB and ATF families. These transcription factors are involved in early T-lymphocyte specification and commitment as well as in oligodendrocyte dedifferentiation and development, both pathways that have significant biological plausibility in MS causation.

Access to immunology through the Gene Ontology

The Gene Ontology (GO) is widely recognized as the premier tool for the organization and functional annotation of molecular aspects of cellular systems. However, for many immunologists the use of GO is a very foreign concept. Indeed, as a controlled vocabulary, GO can almost be considered a new language, and it can be difficult to appreciate the use and value of this approach for understanding the immune system. This review reflects on the application of GO to the field of immunology and explains the process of GO annotation. Finally, this review hopes to inspire immunologists to invest time and energy in improving both the content of the GO and the quality of GO annotations associated with genes of immunological interest.