Identify Gene Markers Research Articles

Excavation of gene markers associated with pancreatic ductal adenocarcinoma based on interrelationships of gene expression.

Pancreatic ductal adenocarcinoma (PDAC) accounts for 95% of all pancreatic cancer cases, posing grave challenges to its diagnosis and treatment. Timely diagnosis is pivotal for improving patient survival, necessitating the discovery of precise biomarkers. An innovative approach was introduced to identify gene markers for precision PDAC detection. The core idea of our method is to discover gene pairs that display consistent opposite relative expression and differential co-expression patterns between PDAC and normal samples. Reversal gene pair analysis and differential partial correlation analysis were performed to determine reversal differential partial correlation (RDC) gene pairs. Using incremental feature selection, the authors refined the selected gene set and constructed a machine-learning model for PDAC recognition. As a result, the approach identified 10 RDC gene pairs. And the model could achieve a remarkable accuracy of 96.1% during cross-validation, surpassing gene expression-based models. The experiment on independent validation data confirmed the model's performance. Enrichment analysis revealed the involvement of these genes in essential biological processes and shed light on their potential roles in PDAC pathogenesis. Overall, the findings highlight the potential of these 10 RDC gene pairs as effective diagnostic markers for early PDAC detection, bringing hope for improving patient prognosis and survival.

Using transcriptomics to identify gene markers for flower longevity in dahlias

Using transcriptomics to identify gene markers for flower longevity in dahlias

Abstract P1051: Minimally Invasive Delivery Of Synthetic Cardiac Stromal Cells In A Large Animal Model Of Myocardial Infarction

Cell therapies for cardiac tissue regeneration are commonly used for tissue remolding post-MI, however, due to viability, retention, and cost, acellular therapeutic components are being explored. Synthetic cardiac stromal cells (synCSCs) generated by encapsulating secreted factors from isolated human cardiac stromal cells were shown to promote cardiac repair after MI. Previously, synCSCs implantation required surgy. Reducing the risks of surgical complications is essential for translational research. It is beneficial to develop a minimally invasive approach such as intrapericardial cavity (iPC) injections. This pre-clinical study aims to elucidate the therapeutic effects of synCSC embedded in hyaluronic acid (HA) hydrogel on a large animal model of MI through iPC injection. HA hydrogel and synCSCs are fabricated according to previous studies. Video-assisted thoracoscopic surgery is performed for iPC injections in Yorkshire male pigs. Magnetic resonance imaging (MRI) and immunohistochemistry (IHC) data were collected for cardiac function analyses. This pre-clinical study aims to bridge the gap between the bench and bedside by using a minimally invasive approach of iPC injection of synCSCs embedded in the hydrogel. Figure 1 shows iPC injection of synCSCs in HA improved cardiac function and cardiomyocyte proliferation in the pig MI model. Single-cell RNA sequencing data is being analyzed to identify gene markers elevated by synCSC treatment and further uncover the molecular pathways activated by synCSC. iPC injection of synCSC provides a unique dataset in the field of cardiac tissue regeneration and offers another therapeutic option for patients suffering from MI.

Significance of PPARA as a Treatment Target for Chronic Lymphocytic Leukemia.

Peroxisome proliferator-activated receptor alpha (PPARA) has been suggested as a therapeutic target for chronic lymphocytic leukemia (CLL). However, the underlying molecular mechanism remains largely unclear. In this study, we analyzed DNA next-generation sequencing (NGS) data and clinical information from 86 CLL patients to identify gene markers related to treatment-free survival (TFS) length. We then constructed a genetic network that includes CLL promoters, treatment targets, and TFS-related marker genes. To assess the significance of PPARA within the network, we utilized degree centrality (DC) and pathway enrichment score (EScore). Clinical and NGS data revealed 10 TFS length-related gene markers, including RPS15, FOXO1, FBXW7, KMT2A, NOTCH1, GNA12, EGR2, GNA13, KDM6A, and ATM. Through literature data mining, 83 genes were identified as CLL upstream promoters and treatment targets. Among them, PPARA exhibited a stronger connection to CLL and TFS-related gene markers, as evidenced by its ranking at No. 13 based on DC, compared to most of the other promoters (>84%). Additionally, PPARA co-functions with 70 out of 92 in-network genes in various functional pathways/gene groups related to CLL pathology, such as regulation of cell adhesion, inflammation, reactive oxygen species, and cell differentiation. Based on our findings, PPARA is considered one of the critical genes within a large genetic network that influences the prognosis and TFS of CLL through multiple pathogenic pathways.

Differential Expression Analysis of Single-Cell RNA-Seq Data: Current Statistical Approaches and Outstanding Challenges.

With the advent of single-cell RNA-sequencing (scRNA-seq), it is possible to measure the expression dynamics of genes at the single-cell level. Through scRNA-seq, a huge amount of expression data for several thousand(s) of genes over million(s) of cells are generated in a single experiment. Differential expression analysis is the primary downstream analysis of such data to identify gene markers for cell type detection and also provide inputs to other secondary analyses. Many statistical approaches for differential expression analysis have been reported in the literature. Therefore, we critically discuss the underlying statistical principles of the approaches and distinctly divide them into six major classes, i.e., generalized linear, generalized additive, Hurdle, mixture models, two-class parametric, and non-parametric approaches. We also succinctly discuss the limitations that are specific to each class of approaches, and how they are addressed by other subsequent classes of approach. A number of challenges are identified in this study that must be addressed to develop the next class of innovative approaches. Furthermore, we also emphasize the methodological challenges involved in differential expression analysis of scRNA-seq data that researchers must address to draw maximum benefit from this recent single-cell technology. This study will serve as a guide to genome researchers and experimental biologists to objectively select options for their analysis.

Transcriptomic Analysis of the Spleen of Different Chicken Breeds Revealed the Differential Resistance of Salmonella Typhimurium.

Salmonella Typhimurium (ST) is a foodborne pathogen that adversely affects the health of both animals and humans. Since poultry is a common source and carrier of the disease, controlling ST infection in chickens will have a protective impact on human health. In the current study, Beijing-You (BY) and Cobb chicks (5-day-old specific-pathogen-free) were orally challenged by 2.4 × 1012 CFU ST, spleen transcriptome was conducted 1 day post-infection (DPI) to identify gene markers and pathways related to the immune system. A total of 775 significant differentially expressed genes (DEGs) in comparisons between BY and Cobb were identified, including 498 upregulated and 277 downregulated genes (fold change ≥2.0, p < 0.05). Several immune response pathways against Salmonella were enriched, including natural killer-cell-mediated-cytotoxicity, cytokine–cytokine receptor interaction, antigen processing and presentation, phagosomes, and intestinal immune network for IgA production, for both BY and Cobb chickens. The BY chicks showed a robust response for clearance of bacterial load, immune response, and robust activation of phagosomes, resulting in ST resistance. These results confirmed that BY breed more resistance to ST challenge and will provide a better understanding of BY and Cobb chickens’ susceptibility and resistance to ST infection at the early stages of host immune response, which could expand the known intricacies of molecular mechanisms in chicken immunological responses against ST. Pathways induced by Salmonella infection may provide a novel approach to developing preventive and curative strategies for ST, and increase inherent resistance in animals through genetic selection.

Seasonal and sexual variation in mRNA expression of selected adipokine genes affecting fat deposition and metabolism of the emu (Dromaius novaehollandiae)

Emus are farmed for fat production. Oil rendered from their back and abdominal fat pads has good anti-oxidant and anti-inflammatory properties and has ingredients that promote cell growth. Our objective is to examine the mRNA expression of 7 emu adipokine genes (eFABP4, eSCD1, eAdipoQ, eAdipoR1, eAdipoR2, eLEP and eLepR) to identify gene markers that may help improve emu fat production. Back and abdominal fat tissues from 11 adult emus were biopsied at four time points (April, June, August and November). Total RNA was isolated and cDNA was synthesized. Gene specific primers were designed for partial cloning fragments to amplify the open reading frame of the 7 genes. eLEP was not expressed in emu fat tissue. Nucleotides and amino acids sequences of the 6 expressed gene were compared with homologs from other species and phylogenetic relationships established. Seasonal mRNA expression of each gene was assessed by quantitative RT-PCR and differential expression analysed by the 2−ΔΔCT method. The 6 expressed genes showed seasonal variation in expression and showed association of expression level with back fat adiposity. More whole-genome scanning studies are needed to develop novel molecular markers that can be applied to improve fat production in emus.

PCNA in Cervical Intraepithelial Neoplasia and Cervical Cancer: An Interaction Network Analysis of Differentially Expressed Genes

The investigation of differentially expressed genes (DEGs) and their interactome could provide valuable insights for the development of markers to optimize cervical intraepithelial neoplasia (CIN) screening and treatment. This study investigated patients with cervical disease to identify gene markers whose dysregulated expression and protein interaction interface were linked with CIN and cervical cancer (CC). Literature search of microarray datasets containing cervical epithelial samples was conducted in Gene Expression Omnibus and Pubmed/Medline from inception until March 2021. Retrieved DEGs were used to construct two protein-protein interaction (PPI) networks. Module DEGs that overlapped between CIN and CC samples, were ranked based on 11 topological algorithms. The highest-ranked hub gene was retrieved and its correlation with prognosis, tissue expression and tumor purity in patients with CC, was evaluated. Screening of the literature yielded 9 microarray datasets (GSE7803, GSE27678, GSE63514, GSE6791, GSE9750, GSE29570, GSE39001, GSE63678, GSE67522). Two PPI networks from CIN and CC samples were constructed and consisted of 1704 and 3748 DEGs along 21393 and 79828 interactions, respectively. Two gene clusters were retrieved in the CIN network and three in the CC network. Multi-algorithmic topological analysis revealed PCNA as the highest ranked hub gene between the two networks, both in terms of expression and interactions. Further analysis revealed that while PCNA was overexpressed in CC tissues, it was correlated with favorable prognosis (log-rank P=0.022, HR=0.58) and tumor purity (P=9.86 × 10-4, partial rho=0.197) in CC patients. This study identified that cervical PCNA exhibited multi-algorithmic topological significance among DEGs from CIN and CC samples. Overall, PCNA may serve as a potential gene marker of CIN progression. Experimental validation is necessary to examine its value in patients with cervical disease.

DNA microarray analysis of Staphylococcus aureus from Nigeria and South Africa.

Staphylococcus aureus is an important human pathogen with an arsenal of virulence factors and a propensity to acquire antibiotic resistance genes. The understanding of the global epidemiology of S. aureus through the use of various typing methods is important in the detection and tracking of novel and epidemic clones in countries and regions. However, detailed information on antibiotic resistance and virulence genes of S. aureus, and its population structure is still limited in Africa. In this study, S. aureus isolates collected in South Africa (n = 38) and Nigeria (n = 2) from 2001-2004 were characterized by spa typing and DNA microarray. The combination of these two methods classified the isolates into seven spa types and three clonal complexes (CCs) i.e. t064-CC8 (n = 17), t037-CC8 (n = 8), t1257-CC8 (n = 6), t045-CC5 (n = 5), t951-CC8 (n = 1), t2723-CC88 (n = 1), t6238-CC8 (n = 1), and untypeable-CC8 (n = 1). A high percentage agreement (>95%) and kappa coefficient (>0.60) was largely observed with antibiotic susceptibility testing and DNA microarray, indicating substantial agreement. Some antibiotic and virulence gene markers were associated with specific clones. The detection of the collagen-binding adhesion (cna) gene was unique for t037-CC8-MRSA while the enterotoxin gene cluster (egc) and staphylococcal complement inhibitor (scn) gene were identified with t045-CC5-MRSA. Moreover, the combination of genes encoding enterotoxins (entA, entB, entK, entQ) was noted with most of the CC8 isolates. The t045-CC5-MRSA clone was positive for the mercury resistance (mer) operon. DNA microarray provides information on antibiotic resistance and virulence gene determinants and can be a useful tool to identify gene markers for specific S. aureus clones in Africa.

Role of MdERF3 and MdERF118 natural variations in apple flesh firmness/crispness retainability and development of QTL-based genomics-assisted prediction.

SummaryRetention of flesh texture attributes during cold storage is critical for the long‐term maintenance of fruit quality. The genetic variations determining flesh firmness and crispness retainability are not well understood. The objectives of this study are to identify gene markers based on quantitative trait loci (QTLs) and to develop genomics‐assisted prediction (GAP) models for apple flesh firmness and crispness retainability. Phenotype data of 2664 hybrids derived from three Malus domestica cultivars and a M. asiatica cultivar were collected in 2016 and 2017. The phenotype segregated considerably with high broad‐sense heritability of 83.85% and 83.64% for flesh firmness and crispness retainability, respectively. Fifty‐six candidate genes were predicted from the 62 QTLs identified using bulked segregant analysis and RNA‐seq. The genotype effects of the markers designed on each candidate gene were estimated. The genomics‐predicted values were obtained using pyramiding marker genotype effects and overall mean phenotype values. Fivefold cross‐validation revealed that the prediction accuracy was 0.5541 and 0.6018 for retainability of flesh firmness and crispness, respectively. An 8‐bp deletion in the MdERF3 promoter disrupted MdDOF5.3 binding, reduced MdERF3 expression, relieved the inhibition on MdPGLR3, MdPME2, and MdACO4 expression, and ultimately decreased flesh firmness and crispness retainability. A 3‐bp deletion in the MdERF118 promoter decreased its expression by disrupting the binding of MdRAVL1, which increased MdPGLR3 and MdACO4 expression and reduced flesh firmness and crispness retainability. These results provide insights regarding the genetic variation network regulating flesh firmness and crispness retainability, and the GAP models can assist in apple breeding.

Genetic Aspects of Myoma: From Somatic Mutations to the Markers of Development

Study Objective to identify gene markers that influence the development of uterine myoma in patients with family history of this disease and multiple forms of myoma. Design Canadian Task Force: Level II-2. Setting V.I. Kulakov National Medical Research Center of Obstetrics, Gynecology and Perinatology. Patients or Participants 215 patients scheduled for hysterectomy or myomectomy were organized into 3 groups: group 1 with family history of myoma, group 2 without such family history, group 3 – patients with noinformation about their anamnesis. 30 women were included in the control group. Interventions Collection of blood samples and tissue of the myomatous nodules in studied patients was undertaken. DNA isolation was carried out; genotyping of the obtained material was conducted at six loci (rs3020434, rs11742635, rs124577644, rs12637801, rs2861221, rs17677069) of the ESR1, FBN2, CELF4, KCWMB2 genes. Measurements and Main Results Rare alleles of polymorphisms rs3020434 (TT), rs11742635 (TT), rs2861221 (GG) and rs17677069 (GG) were not found in the group of women with a family history. These women, however, had common forms of the following polymorphisms: CC allele of rs3020434 polymorphism, seen in 73 % of patients, GG variant of rs11742635 observed in 82 %, CC allele of rs2861221,and AA allele of rs17677069 identified in 82 % of women with familial predisposition of uterine myoma. Interestingly, homozygosity in CC allele of rs12637801 was observed in 83.5% of women with multiple myoma and may potentially become a marker for this form of the disease. Conclusion Rare alleles of rs3020434, rs11742635, rs2861221 and rs17677069 polymorphisms can be protective variants against the development of familial forms of uterine myoma. The homozygous variant of СС of rs12637801 can be a predictor of the development of multiple uterine fibroids in a single patient.

An ANN model for the differential diagnosis of tuberculosis and sarcoidosis.

Sarcoidosis is often misdiagnosed as tuberculosis and consequently mistreated owing to inherent limitations in histopathological and radiological presentations. It is known that the differential diagnosis of Tuberculosis and Sarcoidosis is often non-trivial and requires expertise and experience from clinicians. Therefore, it is of interest to describe a multilayer neural network model to differentiate pulmonary tuberculosis from Sarcoidosis using signal intensity data from blood transcriptional microarray. Genes that are significantly upregulated in Pulmonary Tuberculosis and Sarcoidosis in comparison with healthy controls were used in the model. The model classified Pulmonary Tuberculosis and Sarcoidosis with 95.8% accuracy. The model also helps to identify gene markers that are differentially upregulated in the two clinical conditions.

Studying human reproductive biology through single-cell analysis and in vitro differentiation of stem cells into germ cell-like cells.

Understanding the molecular and cellular mechanisms of human reproductive development has been limited by the scarcity of human samples and ethical constraints. Recently, in vitro differentiation of human pluripotent stem cells into germ cells and single-cell analyses have opened new avenues to directly study human germ cells and identify unique mechanisms in human reproductive development. The goal of this review is to collate novel findings and insightful discoveries with these new methodologies, aiming at introducing researchers and clinicians to the use of these tools to study human reproductive biology and develop treatments for infertility. PubMed was used to search articles and reviews with the following main keywords: in vitro differentiation, human stem cells, single-cell analysis, spermatogenesis, oogenesis, germ cells and other key terms related to these subjects. The search period included all publications from 2000 until now. Single-cell analyses of human gonads have identified many important gene markers at different developmental stages and in subpopulations of cells. To validate the functional roles of these gene markers, researchers have used the in vitro differentiation of human pluripotent cells into germ cells and confirmed that some genetic requirements are unique in human germ cells and are not conserved in mouse models. Moreover, transcriptional regulatory networks and the interaction of germ and somatic cells in gonads were elucidated in these studies. Single-cell analyses allow researchers to identify gene markers and potential regulatory networks using limited clinical samples. On the other hand, in vitro differentiation methods provide clinical researchers with tools to examine these newly identify gene markers and study the causative effects of mutations previously associated with infertility. Combining these two methodologies, researchers can identify gene markers and networks which are essential and unique in human reproductive development, thereby producing more accurate diagnostic tools for assessing reproductive disorders and developing treatments for infertility.

Identification of lung cancer gene markers through kernel maximum mean discrepancy and information entropy

BackgroundThe early diagnosis of lung cancer has been a critical problem in clinical practice for a long time and identifying differentially expressed gene as disease marker is a promising solution. However, the most existing gene differential expression analysis (DEA) methods have two main drawbacks: First, these methods are based on fixed statistical hypotheses and not always effective; Second, these methods can not identify a certain expression level boundary when there is no obvious expression level gap between control and experiment groups.MethodsThis paper proposed a novel approach to identify marker genes and gene expression level boundary for lung cancer. By calculating a kernel maximum mean discrepancy, our method can evaluate the expression differences between normal, normal adjacent to tumor (NAT) and tumor samples. For the potential marker genes, the expression level boundaries among different groups are defined with the information entropy method.ResultsCompared with two conventional methods t-test and fold change, the top average ranked genes selected by our method can achieve better performance under all metrics in the 10-fold cross-validation. Then GO and KEGG enrichment analysis are conducted to explore the biological function of the top 100 ranked genes. At last, we choose the top 10 average ranked genes as lung cancer markers and their expression boundaries are calculated and reported.ConclusionThe proposed approach is effective to identify gene markers for lung cancer diagnosis. It is not only more accurate than conventional DEA methods but also provides a reliable method to identify the gene expression level boundaries.

Inferring Genes and Biological Functions That Are Sensitive to the Severity of Toxicity Symptoms.

The effective development of new drugs relies on the identification of genes that are related to the symptoms of toxicity. Although many researchers have inferred toxicity markers, most have focused on discovering toxicity occurrence markers rather than toxicity severity markers. In this study, we aimed to identify gene markers that are relevant to both the occurrence and severity of toxicity symptoms. To identify gene markers for each of four targeted liver toxicity symptoms, we used microarray expression profiles and pathology data from 14,143 in vivo rat samples. The gene markers were found using sparse linear discriminant analysis (sLDA) in which symptom severity is used as a class label. To evaluate the inferred gene markers, we constructed regression models that predicted the severity of toxicity symptoms from gene expression profiles. Our cross-validated results revealed that our approach was more successful at finding gene markers sensitive to the aggravation of toxicity symptoms than conventional methods. Moreover, these markers were closely involved in some of the biological functions significantly related to toxicity severity in the four targeted symptoms.

Altered Expression of Oligodendrocyte and Neuronal Marker Genes Predicts the Clinical Onset of Autoimmune Encephalomyelitis and Indicates the Effectiveness of Multiple Sclerosis–Directed Therapeutics

Experimental autoimmune encephalomyelitis (EAE) is a valuable model for studying immunopathology in multiple sclerosis (MS) and for exploring the interface between autoimmune responses and CNS tissue that ultimately leads to lesion development. In this study, we measured gene expression in mouse spinal cord during myelin oligodendrocyte gp35-55 peptide-induced EAE, using quantitative RT-PCR, to identify gene markers that monitor individual hallmark pathological processes. We defined a small panel of genes whose longitudinal expression patterns provided insight into the timing, interrelationships, and mechanisms of individual disease processes and the efficacy of therapeutics for the treatment of MS. Earliest transcriptional changes were upregulation of Il17a and sharp downregulation of neuronal and oligodendrocyte marker genes preceding clinical disease onset, whereas neuroinflammatory markers progressively increased as symptoms and tissue lesions developed. EAE-induced gene-expression changes were not altered in mice deficient in IKKβ in cells of the myeloid lineage compared with controls, but the administration of a selective inhibitor of soluble TNF to mice from the day of immunization delayed changes in the expression of innate inflammation, myelin, and neuron markers from the presymptomatic phase. Proof of principle that the gene panel shows drug screening potential was obtained using a well-established MS therapeutic, glatiramer acetate. Prophylactic treatment of mice with glatiramer acetate normalized gene marker expression, and this correlated with the level of therapeutic success. These results show that neurons and oligodendrocytes are highly sensitive to CNS-directed autoimmunity before the development of clinical symptoms and immunopathology and reveal a role for soluble TNF in mediating the earliest changes in gene expression.

Gene expression markers in circulating tumor cells may predict bone metastasis and response to hormonal treatment in breast cancer

Circulating tumor cells (CTCs) have recently attracted attention due to their potential as prognostic and predictive markers for the clinical management of metastatic breast cancer patients. The isolation of CTCs from patients may enable the molecular characterization of these cells, which may help establish a minimally invasive assay for the prediction of metastasis and further optimization of treatment. Molecular markers of proven clinical value may therefore be useful in predicting disease aggressiveness and response to treatment. In our earlier study, we identified a gene signature in breast cancer that appears to be significantly associated with bone metastasis. Among the genes that constitute this signature, trefoil factor 1 (TFF1) was identified as the most differentially expressed gene associated with bone metastasis. In this study, we investigated 25 candidate gene markers in the CTCs of metastatic breast cancer patients with different metastatic sites. The panel of the 25 markers was investigated in 80 baseline samples (first blood draw of CTCs) and 30 follow-up samples. In addition, 40 healthy blood donors (HBDs) were analyzed as controls. The assay was performed using quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) with RNA extracted from CTCs captured by the CellSearch system. Our study indicated that 12 of the genes were uniquely expressed in CTCs and 10 were highly expressed in the CTCs obtained from patients compared to those obtained from HBDs. Among these genes, the expression of keratin 19 was highly correlated with the CTC count. The TFF1 expression in CTCs was a strong predictor of bone metastasis and the patients with a high expression of estrogen receptor β in CTCs exhibited a better response to hormonal treatment. Molecular characterization of these genes in CTCs may provide a better understanding of the mechanism underlying tumor metastasis and identify gene markers in CTCs for predicting disease progression and response to treatment.

Comparative Gene Expression Profiling of In Vivo-Derived Expanded and Hatched Porcine Blastocyst-Stage Embryos.

During the pre-implantation period of embryonic development, the mammalian embryo exhibits dramatic changes and many key events take place. The developmental stage at which porcine embryos are most commonly manipulated is the blastocyst, and the quality of the embryos used is critical to the success of reproductive technologies such as embryo transfer. Despite the importance of this critical period, our ability to determine early embryonic quality based on morphological criteria is limited. As an alternative, characterization of the gene expression profile of the early porcine embryo could identify gene markers of embryonic quality. The objective of this study was to perform comparative gene expression profiling analysis of in vivo-derived expanded and hatched porcine blastocysts using two-colored microarray (Pig-Oligo Array, USDA Pig Genome Consortium). Microarray data were interpreted using WebArray and DAVID functional annotation tools. The microarray results identified 1783 genes that were commonly expressed in both expanded and hatched porcine blastocysts. A further 148 genes were differentially expressed (p<0.05) and in comparison to expanded blastocysts, 35 genes were down-regulated and 113 genes were up-regulated after hatching. Many of the differentially expressed genes are related to important molecular mechanisms, such as macromolecule metabolism and energy related pathways. A total of 14 genes of interest (LDHA, LDHB, SLC16A7 (previously known as MCT2), BSG, SLC2A1, SLC2A3, SLC2A5, POU5F1 (previously known as OCT4), ACTB, GAPDH, GRB2, SETX, SPG7, and YWHAZ) were selected from the gene list generated by the microarray analysis, and their expressions were verified using SYBR Green-based real-time PCR. For the genes tested, the real-time PCR results were consistent with the microarray results. The differences detected in the gene expression profiles between in vivo-derived expanded and hatched porcine blastocysts increases our understanding of the molecular mechanisms involved in the hatching process and identifies potential candidate gene markers of porcine embryo quality. This research was supported by the Natural Sciences and Engineering Research Council (NSERC) and is a part of the activities of the EmbryoGENE NSERC Strategic Research Network. (poster)

DPEP1, expressed in the early stages of colon carcinogenesis, affects cancer cell invasiveness

We investigated changes in the gene expression profile in colon cancer in order to identify gene markers that may be useful in the management of this disease. The Cancer Genome Anatomy Project was used to detect differences in gene expression between normal and cancer tissue. The overexpression of dipeptidase-1 (DPEP1) in cancer tissue was confirmed in a sample of 76 patients by real-time PCR. To identify the function of DPEP1, RNA interference (RNAi) was used to inactivate this gene in the colon cancer cell line. Immunohistochemical analysis was performed to characterize the pattern of DPEP1 expression in colon cancer. DPEP1 expression in cancer was significantly higher than that in normal tissue. However, DPEP1 expression decreased with pathological differentiation, lymph-node and distant metastasis. Patients with tumors with decreased DPEP1 expression showed a poorer prognosis, and this was also true of patients with tumors who are treated with curative intent. RNAi-mediated DPEP1 reduction in the colon cancer cell line did not result in cell proliferation or apoptosis, but was associated with an increased invasive ability. DPEP1 protein was observed on the apical side of the cancer cells, and is expressed in the early stages of carcinogenesis, even in adenomas of both sporadic colorectal cancer and familial adenomatous polyposis patients. DPEP1 expression in normal colonic mucosa is very low, but it is highly expressed in colorectal adenoma and cancer specimens and is negatively correlated with parameters of pathological aggressiveness and poor prognosis. DPEP1 is expressed in the early stages of colon carcinogenesis and affects cancer cell invasiveness.

Expression of Tolerance Associated Gene-1, a Mitochondrial Protein Inhibiting T Cell Activation, Can Be Used to Predict Response to Immune Modulating Therapies

Immune modulating therapies gain increasing importance in treatment of patients with autoimmune diseases such as psoriasis. None of the currently applied biologics achieves significant clinical improvement in all treated patients. Because the therapy with biologics is cost intensive and sometimes associated with side effects, noninvasive diagnostic tools for early prediction of responders are of major interest. We studied the effects of Alefacept (LFA3Ig), an approved drug for treatment of psoriasis, on leukocytes in vitro and in vivo to identify gene markers predictive for treatment response and to further investigate its molecular mechanisms of action. In an open-label study, 20 psoriasis patients were treated weekly with 15 mg Alefacept over 12 wk. We demonstrate that transcription of the tolerance-associated gene (TOAG-1) is significantly up-regulated whereas receptor for hyaluronic acid mediated migration (RHAMM) transcription is down-regulated in PBMCs of responding patients before clinical improvement. TOAG-1 is exclusively localized within mitochondria. Overexpression of TOAG-1 in murine T cells leads to increased susceptibility to apoptosis. Addition of Alefacept to stimulated human T cells in vitro resulted in reduced frequencies of activated CD137(+) cells, increased TOAG-1 but reduced RHAMM expression. This was accompanied by reduced proliferation and enhanced apoptosis. Inhibition of proliferation was dependent on enhanced PDL1 expression of APCs. Thus, peripheral changes of TOAG-1 and RHAMM expression can be used to predict clinical response to Alefacept treatment in psoriasis patients. In the presence of APCs Alefacept can inhibit T cell activation and survival by increasing expression of TOAG-1 on T cells and PDL1 on APCs.