P121 Increased gene expression levels of CXCL9, CXCL10 and CXCL11 in renal allograft biopsies with an early acute t cell-mediated rejection

2019 ◽  
Vol 80 ◽  
pp. 145
Author(s):  
Marieke van der Zwan ◽  
Carla Baan ◽  
Robert Colvin ◽  
Rex Smith ◽  
Rebecca White ◽  
...  
Blood ◽  
2016 ◽  
Vol 128 (22) ◽  
pp. 1042-1042
Author(s):  
Kohei Hosokawa ◽  
Sachiko Kajigaya ◽  
Keyvan Keyvanfar ◽  
Qiao Wangmin ◽  
Yanling Xie ◽  
...  

Abstract Background. Paroxysmal nocturnal hemoglobinuria (PNH) is a rare acquired blood disease, characterized by hemolytic anemia, bone marrow (BM) failure, and venous thrombosis. The etiology of PNH is a somatic mutation in the phosphatidylinositol glycan class A gene (PIG-A) on the X chromosome, which causes deficiency in glycosyl phosphatidylinositol-anchored proteins (GPI-APs). The involvement of T cells in PNH is strongly supported by clinical overlap between PNH and aplastic anemia (AA); the presence of GPI-AP deficient cells in AA associated with favorable response to immunosuppressive therapy; and an oligoclonal T cell repertoire in PNH patients. However, the molecular mechanisms responsible for the aberrant immune responses in PNH patients are not well understood. To identify aberrant molecular mechanisms involved in immune targeting of hematopoietic stem cells in BM, RNA sequencing (RNA-seq) was applied to examine the transcriptome of T cell subsets from PNH patients and healthy controls. Method. Blood samples were obtained after informed consent from 15 PNH patients and 15 age-matched healthy controls. For RNA extraction, freshly isolated peripheral blood mononuclear cells were sorted on the same day of blood draw to obtain four different T cell (CD3+ CD14- CD19- ViViD-) populations [CD4+ naïve (CD45RA+ CD45RO-), CD4+ memory (CD45RA- CD45RO+), CD8+ naïve (CD45RA+ CD45RO-), and CD8+ memory (CD45RA- CD45RO+) T cells] by fluorescence-activated cell sorter . RNA-Seq analysis from three PNH and three healthy controls was performed using the Illumina HiSeq™ 2000 platform. The Ingenuity® Pathway Analysis and Gene set enrichment analysis (GSEA) were employed to elucidate transcriptional pathways. RNA-seq data were validated by flow cytometry and quantitative real-time RT-PCR (RT-qPCR). Results and Discussion . Differentially expressed gene analysis of four T cell subsets showed distinct gene expression signatures in individual T cell subsets. In CD4+ naïve T cells, 11 gene expression levels were significantly different: five upregulated (including SRRM2 and TNFSF8) and six downregulated genes (including GIMAP6) (> 2 fold change, false discovery rate [FDR] < 0.05). In CD4+ memory T cells, 25 gene expression levels were significantly different: 15 upregulated (including JUND and TOB1) and 10 downregulated genes (including GIMAP4). In CD8+ naive T cells, only two gene expression levels were significantly different: upregulated CTSW and downregulated RPL9. In CD8+ memory T cells, seven gene expression levels were significantly different: two upregulated (CTSW and DPP4) and five downregulated genes (including SLC12A7). Further, differentially expressed gene analysis was performed by combining CD4+ naïve, CD4+ memory, CD8+ naïve, and CD8+ memory T cells from PNH or healthy controls, respectively. Out of 55 gene expression levels that were significantly different, 41 were upregulated (including TNFAIP3, JUN, JUND, TOB1, TNFSF8, and CD69) and 14 downregulated (including GIMAP4). By canonical pathways analysis, putative gene network interactions of differentially expressed genes were significantly enriched for canonical pathways of TNFR1, TNFR2, IL-17A, and CD27 signaling. By GSEA, the most significantly upregulated gene sets in CD4+ naïve, CD4+ memory, CD8+ naïve, and CD8+ memory T cells from PNH patients displayed gene signatures related to the "IGF1 pathway", "Pre-NOTCH expression and processing", "AP-1 pathway", and "ATF2 pathway", respectively. For validation of the RNA-seq data, we chose seven genes (TNFAIP3, JUN, JUND, TOB1, TNFSF8, CD69, and CTSW) because these are important mediators involved in regulation for T cells and dysregulation of these genes is associated with autoimmune diseases. Differential expression levels of TNFAIP3, JUN, and TOB1 were validated by RT-qPCR. By flow cytometry, higher expression of CD69 and TNFSF8 was confirmed in CD4+ and CD8+T cells from PNH compared to healthy controls. Conclusion. Using RNA-seq, we identified novel molecular mechanisms and pathways which may underlie the aberrant T cell immune status in PNH. Specific dysregulation of T cell intracellular signaling may contribute to BM failure and the inflammatory environment in PNH. Understanding these pathways may provide new therapeutic strategies to modulate T cell immune responses in BM failure. Disclosures Hosokawa: Aplastic Anemia and MDS International Foundation: Research Funding. Rios:GSK/Novartis: Research Funding. Weinstein:GSK/Novartis: Research Funding. Townsley:GSK/Novartis: Research Funding.


2006 ◽  
Vol 92 (2) ◽  
pp. 130-133 ◽  
Author(s):  
Akemi Iwamoto ◽  
Masahide Ikeguchi ◽  
Sachico Matsumoto ◽  
Youji Hukumoto ◽  
Masashi Inoue ◽  
...  

Aims and Background In several neoplastic diseases including hepatocellular carcinoma (HCC) immunosuppression is correlated with disease stage, progression and outcome. Moreover, recent studies have demonstrated that cyclooxygenase-2 (COX-2) enhances tumor growth in HCCs. The present study analyzed the correlation between local immune responses and COX-2 gene expression levels in patients with primary HCCs. Methods Fresh tissues were obtained from 59 patients who underwent resection of an HCC. The COX-2 gene expression levels were quantified by real-time reverse transcriptase-polymerase chain reaction (RT-PCR) and compared with the CD8+ T cell densities detected by immunohistochemistry. Results COX-2 gene expression was detected in 35 of the 59 tumors. The CD8+ T cell density in COX-2-expressing tumors (6.1 cells/high-power field (HPF), x200 magnification) was suppressed compared with that in non-COX-2-expressing tumors (13.6 cells/HPF, P = 0.009). Tumor COX-2 gene expression was associated with a poorer disease-free survival rate. Conclusions Elevation of the tumor COX-2 level is correlated with the suppression of local immune responses in HCCs, suggesting that COX-2 plays a role in early tumor recurrence in the residual liver in patients after HCC resection.


Genes ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 854
Author(s):  
Yishu Wang ◽  
Lingyun Xu ◽  
Dongmei Ai

DNA methylation is an important regulator of gene expression that can influence tumor heterogeneity and shows weak and varying expression levels among different genes. Gastric cancer (GC) is a highly heterogeneous cancer of the digestive system with a high mortality rate worldwide. The heterogeneous subtypes of GC lead to different prognoses. In this study, we explored the relationships between DNA methylation and gene expression levels by introducing a sparse low-rank regression model based on a GC dataset with 375 tumor samples and 32 normal samples from The Cancer Genome Atlas database. Differences in the DNA methylation levels and sites were found to be associated with differences in the expressed genes related to GC development. Overall, 29 methylation-driven genes were found to be related to the GC subtypes, and in the prognostic model, we explored five prognoses related to the methylation sites. Finally, based on a low-rank matrix, seven subgroups were identified with different methylation statuses. These specific classifications based on DNA methylation levels may help to account for heterogeneity and aid in personalized treatments.


2021 ◽  
Vol 15 (1) ◽  
Author(s):  
Weitong Cui ◽  
Huaru Xue ◽  
Lei Wei ◽  
Jinghua Jin ◽  
Xuewen Tian ◽  
...  

Abstract Background RNA sequencing (RNA-Seq) has been widely applied in oncology for monitoring transcriptome changes. However, the emerging problem that high variation of gene expression levels caused by tumor heterogeneity may affect the reproducibility of differential expression (DE) results has rarely been studied. Here, we investigated the reproducibility of DE results for any given number of biological replicates between 3 and 24 and explored why a great many differentially expressed genes (DEGs) were not reproducible. Results Our findings demonstrate that poor reproducibility of DE results exists not only for small sample sizes, but also for relatively large sample sizes. Quite a few of the DEGs detected are specific to the samples in use, rather than genuinely differentially expressed under different conditions. Poor reproducibility of DE results is mainly caused by high variation of gene expression levels for the same gene in different samples. Even though biological variation may account for much of the high variation of gene expression levels, the effect of outlier count data also needs to be treated seriously, as outlier data severely interfere with DE analysis. Conclusions High heterogeneity exists not only in tumor tissue samples of each cancer type studied, but also in normal samples. High heterogeneity leads to poor reproducibility of DEGs, undermining generalization of differential expression results. Therefore, it is necessary to use large sample sizes (at least 10 if possible) in RNA-Seq experimental designs to reduce the impact of biological variability and DE results should be interpreted cautiously unless soundly validated.


Agronomy ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 92
Author(s):  
Joon Seon Lee ◽  
Lexuan Gao ◽  
Laura Melissa Guzman ◽  
Loren H. Rieseberg

Approximately 10% of agricultural land is subject to periodic flooding, which reduces the growth, survivorship, and yield of most crops, reinforcing the need to understand and enhance flooding resistance in our crops. Here, we generated RNA-Seq data from leaf and root tissue of domesticated sunflower to explore differences in gene expression and alternative splicing (AS) between a resistant and susceptible cultivar under both flooding and control conditions and at three time points. Using a combination of mixed model and gene co-expression analyses, we were able to separate general responses of sunflower to flooding stress from those that contribute to the greater tolerance of the resistant line. Both cultivars responded to flooding stress by upregulating expression levels of known submergence responsive genes, such as alcohol dehydrogenases, and slowing metabolism-related activities. Differential AS reinforced expression differences, with reduced AS frequencies typically observed for genes with upregulated expression. Significant differences were found between the genotypes, including earlier and stronger upregulation of the alcohol fermentation pathway and a more rapid return to pre-flooding gene expression levels in the resistant genotype. Our results show how changes in the timing of gene expression following both the induction of flooding and release from flooding stress contribute to increased flooding tolerance.


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