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Tolerance associated gene expression following allogeneic hematopoietic cell transplantation

ABSTRACT: Biologic markers of immune tolerance may facilitate tailoring of immune suppression duration after allogeneic hematopoietic cell transplantation (HCT). In a cross-sectional study, peripheral blood samples were obtained from tolerant (n=15, median 38.5 months post-HCT) and non-tolerant (n=17, median 39.5 post-HCT) HCT recipients and healthy control subjects (n=10) for analysis of immune cell subsets and differential gene expression. There were no significant differences in immune subsets across groups. We identified 281 probe sets unique to the tolerant (TOL) group and 122 for non-tolerant (non-TOL). These were enriched for process networks including NK cell cytotoxicity, antigen presentation, lymphocyte proliferation, and cell cycle and apoptosis. Differential gene expression was enriched for CD56, CD66, and CD14 human lineage-specific gene expression. Differential expression of 20 probe sets between groups was sufficient to develop a classifier with > 90% accuracy, correctly classifying 14/15 TOL cases and 15/17 non-TOL cases. These data suggest that differential gene expression can be utilized to accurately classify tolerant patients following HCT. Prospective investigation of immune tolerance biologic markers is warranted.

ORGANISM(S): Homo sapiens

PROVIDER: GSE64300 | GEO | 2015/05/25

SECONDARY ACCESSION(S): PRJNA270685

REPOSITORIES: GEO

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Project description:Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to compare NGS-derived HCT-116 cell transcriptome profiling (RNA-seq) to microarray and quantitative reverse transcription polymerase chain reaction (qRT–PCR) methods and to evaluate protocols for optimal high-throughput data analysis. Methods: HCT-116 cell mRNA profiles of HCT-116-GOLPH3-Vector and HCT-116-GOLPH3-Overepression were generated by deep sequencing, in triplicate, using Illumina GAIIx. The sequence reads that passed quality filters were analyzed at the transcript isoform level with two methods: Burrows–Wheeler Aligner (BWA) followed by ANOVA (ANOVA) and TopHat followed by Cufflinks. qRT–PCR validation was performed using TaqMan and SYBR Green assays. Results: RNA sequencing (RNA-seq) was used to investigate gene expression in HCT-116-PMSCV-Vector and HCT-116-PMSCV GOLPH3 cells, while Gene Ontology (GO) was used to annotate the various functional genes. By comparing the differentially expressed genes, we noticed that GOLPH3 was associated with EMT. Gene set enrichment analysis (GSEA) analysis of the RNA-seq results based on the GSE77953 dataset was performed to investigate the biological functions of HCT-116-PMSCV-Vector and HCT-116-PMSCV-GOLPH3 cells. The findings suggested that GOLPH3 expression was positively associated with colon cancer cell autophagy. Signal pathway enrichment was next analyzed based on the differential expression of genes between HCT-116-PMSCV-Vector and HCT-116-PMSCV-GOLPH3 cells, as examined by RNA-seq. Notably, GOLPH3 has correlated with the PI3K/Akt signaling pathway. Conclusions: Our study represents the first detailed analysis of HCT-116 cell transcriptomes, with biologic replicates, generated by RNA-seq technology. The optimized data analysis workflows reported here should provide a framework for comparative investigations of expression profiles. Our results show that NGS offers a comprehensive and more accurate quantitative and qualitative evaluation of mRNA content within a cell or tissue. We conclude that RNA-seq based transcriptome characterization would expedite genetic network analyses and permit the dissection of complex biologic functions.

Project description:This study corresponds to a re-analysis and meta-analysis of the five transcriptomic studies related to spontaneous tolerance to renal allograft in human. It examines the transcriptome of peripheral blood samples from six distinct clinical groups: healthy volunteers (HV); tolerant patients (TOL); stable patients on minimal immunosuppression (MIS) or maintained on classical immunosuppressive therapy (STA); patients showing either signs of chronic rejection (CR) or acute rejection (AR). The initial studies are the following: -Study 1 from Braud C. et al. (J Cell Biochem., 2008) published under GEO accession number GSE47755 and comprising 250 unique samples (8 HV; 21 TOL; 190 STA; 31 CR). -Study 2 from Brouard S. et al. (Proc Natl Acad Sci U S A., 2007) published under GEO accession number GSE47683 and comprising 67 unique samples (8 HV; 12 TOL; 10 MIS; 12 STA; 11 CR; 14 AR). - Study 3 from Lozano JJ. et al. (Am J Transplant., 2011) published under GEO accession number GSE22707 and comprising 42 unique samples (6 HV; 12 TOL; 12 STA; 12 CR). - Study 4 from Newell KA. et al. (J Clin Invest., 2010) published under GEO accession number GSE22229 and comprising 58 unique samples (12 HV; 19 TOL; 27 STA). - Study 5 from Sagoo P. et al. (J Clin Invest. 2010) published under GEO accession number GSE14655 and comprising two distinct cohorts of patients. The IOT (“Indices of Tolerance”) cohort (5a) corresponds to a European group of patients and totalizes 74 unique samples (8 HV; 10 TOL; 11 MIS; 36 STA; 9 CR). The ITN (“Immune Tolerance in Transplantation”) cohort (5b) corresponds to an American group of patients and totalizes 105 unique samples (20 HV; 22 TOL; 11 MIS; 34 STA; 18 CR). The final data matrix corresponds to the combination of the data from the five independent studies and examines the expression of 1846 meta-genes (MG) across 596 unique blood samples. The 1846 meta-genes correspond to the genes being measured across the five datasets and form a virtual microarray platform (TOL-HUMAN-G1846). The 596 examined samples can be divided into 62 HV, 96 TOL, 32 MIS, 311 STA, 81 CR, and 14 AR.

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Tolerance associated gene expression following allogeneic hematopoietic cell transplantation

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