Genomics

Dataset Information

0

Integrated microRNA-mRNA transcript analysis reveals microRNAs regulating therapy resistant diffuse large B-cell lymphoma


ABSTRACT: Diffuse large B-cell lymphoma (DLBCL) is the most common lymphoma in adults. Although 60-70% of the patients can be cured with standard chemoimmunotherapy, a substantial number of patients die from the disease due to relapse or primary refractory disease. To better understand the biological processes behind the treatment resistance, we characterized the microRNA (miRNA) expression profiles of matched primary and relapsed DLBCL by next-generation sequencing. A total of 492 known miRNAs were expressed in the DLBCL samples (n=7 pairs). A majority of these showed similar expression at diagnosis and relapse; we identified 24 highly expressed and 177 lowly expressed miRNAs in the DLBCL samples as compared to a control set of non-malignant cells. Interestingly, only 13 miRNAs had differential expression between the primary–relapse pairs. MiRNA-mRNA target pair analysis combined with pathway enrichment analysis revealed the putative targets of differentially expressed miRNAs to be significantly enriched for several cancer-associated pathways that included phosphatidylinositol, MAPK and B-cell receptor signaling, suggesting activation of these pathways during progression. Additionally, Kaplan-Meier survival analyses indicated higher expression of genes from these pathways to be associated with shorter survival in immunochemotherapy-treated patients (n=92). Taken together, our data demonstrate that the miRNA expression profile remains relatively constant during the disease progression, but a small set of differentially expressed miRNAs may contribute to the relapse by regulating key cell survival pathways, thus representing potential novel therapeutic targets.

ORGANISM(S): Homo sapiens

PROVIDER: GSE69810 | GEO | 2018/02/23

REPOSITORIES: GEO

Dataset's files

Source:
Action DRS
Other
Items per page:
1 - 1 of 1

Similar Datasets

2023-03-10 | PXD037148 | Pride
2015-04-14 | E-GEOD-66329 | biostudies-arrayexpress
2015-04-14 | GSE66329 | GEO
2011-07-18 | GSE22420 | GEO
2022-05-09 | GSE202370 | GEO
2021-12-06 | GSE171272 | GEO
2024-09-02 | BIOMD0000000530 | BioModels
2011-07-17 | E-GEOD-22420 | biostudies-arrayexpress
2023-09-21 | GSE233648 | GEO
2023-09-21 | GSE229787 | GEO