UD-GenoMed (Hungary)

Background: Leukemic B-cell precursor (BCP) lymphoblasts were identified as a novel expression site for coagulation factor XIII subunit A (FXIII-A). Flow cytometry (FC) revealed three distinct expression patterns, i.e., FXIII-A negative, FXIII-A dim, and FXIII-A bright subgroups. The FXIII-A negative subgroup was significantly associated with the “B-other” genetic category and had an unfavorable disease outcome.Methods: RNA was extracted from bone marrow lymphoblasts of 42 pediatric patients with BCP-acute lymphoblastic leukemia (ALL). FXIII-A expression was determined by multiparameter FC. Genetic diagnosis was based on conventional cytogenetic method and fluorescence in situ hybridization. Affymetrix GeneChip Human Primeview array was used to analyze global expression pattern of 28,869 well-annotated genes. Microarray data were analyzed by Genespring GX14.9.1 software. Gene Ontology analysis was performed using Cytoscape 3.4.0 software with ClueGO application. Selected differentially expressed genes were validated by RT-Q-PCR.Results: We demonstrated, for the first time, the general expression of F13A1 gene in pediatric BCP-ALL samples. The intensity of F13A1 expression corresponded to the FXIII-A protein expression subgroups which defined three characteristic and distinct gene expression signatures detected by Affymetrix oligonucleotide microarrays. Relative gene expression intensity of ANGPTL2, EHMT1 FOXO1, HAP1, NUCKS1, NUP43, PIK3CG, RAPGEF5, SEMA6A, SPIN1, TRH, and WASF2 followed the pattern of change in the intensity of the expression of the F13A1 gene. Common enhancer elements of these genes revealed by in silico analysis suggest that common transcription factors may regulate the expression of these genes in a similar fashion. PLAC8 was downregulated in the FXIII-A bright subgroup. Gene expression signature of the FXIII-A negative subgroup showed an overlap with the signature of “B-other” samples. DFFA, GIGYF1, GIGYF2, and INTS3 were upregulated and CD3G was downregulated in the “B-other” subgroup. Validated genes proved biologically and clinically relevant. We described differential expression of genes not shown previously to be associated with pediatric BCP-ALL.Conclusions: Gene expression signature according to FXIII-A protein expression status defined three novel subgroups of pediatric BCP-ALL. Multiparameter FC appears to be an easy-to-use and affordable method to help in selecting FXIII-A negative patients who require a more elaborate and expensive molecular genetic investigation to design precision treatment.

The most common malignant primary brain tumor is glioblastoma which infiltrates the peritumoral brain, while secondary brain metastases are well demarcated malignancies. Previous research has proved the pivotal role of the changes in the extracellular matrix (ECM) in cancer cell invasion. The mRNA expression of 40 ECM molecules was determined using qRT-PCR in 54 fresh-frozen glioblastoma and brain metastasis samples. Seventy-two samples were used to determine the levels of 20 ECM proteins. The mRNA and protein expression pattern of the studied tumors differs greatly. Linear discriminant analysis of mRNA expression identified samples based on their mRNA expression profile with 92.3% probability and highlighted the role of some molecules as their level greatly influenced sample identification. Different tumor types with different invasiveness differ in the composition of their ECM and this can be used to identify samples. Furthermore, some ECM molecules greatly contribute to tumor invasiveness and could be targets of anti-invasive oncotherapy.

BackgroundAccelerated atherosclerosis and cardiovascular (CV) disease have been associated with rheumatoid arthritis (RA). Many genes have been implicated in atherosclerosis, RA or both. However, most of these studies described SNPs in CD40, SMAD3, HLADR, CTLA4 and other alleles. Very few studies on genetic signatures have been performed that would link RA and CV pathology. We have previously associated some genomic profiles with pathological carotid atherosclerosis (ccIMT), arterial stiffness (PWV) and brachial artery flow-mediated vasodilation (FMD). In other studies we have also found 165 genes that separated anti-TNF responder patients from non-responders.ObjectivesHere we looked for associations between clinical and “vascular” response to biologics and vascular pathology in RA patients.MethodsIn this study, 19 RA patients were treated with either etanercept (ETN) or certolizumab pegol (CZP) for one year. We separated responders (R) and non-responders (NR) according to EULAR response criteria. Microarray gene expression study was performed (Affymetrix) followed by analysis using the GeneSpring software, hierarchy clustering and principal component analysis (PCA). “Vascular response” (VR) to biologics was defined as an at least 20% improvement in FMD, ccIMT or PWV. Good Vascular Response (GVR) was defined as an at least 20% improvement in two or three of these variables.ResultsAmong the 19 patients, 13 were R and 6 were NR. With respect to VR, FMD, ccIMT and PWV responded to anti-TNF treatment in 10, 9 and 8 patients, respectively. GVR was observed in 8 patients and 5 patients had VR in all 3 parameters. When comparing clinical response and VR, 7 out of 8 patients showing GVR also had good clinical response to biologics. Up-regulation of 99 and down-regulation of 67 genes separated clinical R and NR patients. Significant correlation was found between ccIMT improvement upon biological therapy and clinical response (R=0.418, p=0.04).ConclusionsGenomic signature analysis may be able to separate clinical responders and non-responders to biologics, as well as patients that show or do not show imporvement of vascular pathology.Disclosure of InterestNone declared