Application of NanoString technologies in angioimmunoblastic T cell lymphoma

Genes Genomics. 2020 Apr;42(4):485-494. doi: 10.1007/s13258-020-00919-7. Epub 2020 Mar 7.

Abstract

Background: Angioimmunoblastic T-cell lymphoma (AITL) is an aggressive disease. Most cancer diagnoses are determined by anatomical histology. Therefore, many samples are stored in FFPE blocks for H&E staining. However, RNAs extracted from the FFPE block have a high level of fragmentation, making it difficult to perform accurate DEG analysis using RNA sequencing.

Objective: To overcome fragmented RNA's drawback in NGS application, we applied the NanoString nCounter® technique of hybridization method that can be used for DEG analysis without PCR amplification.

Methods: We characterized the gene expression profiling of AITLs though transcriptome analysis based on the nCounter® PanCancer IO 360™ Panel and NanoString platform. To perform the analysis of differential expression gene (DEG) profiles in AITLs, we compared the NanoString data from eight AITL patients with a healthy control donor.

Results: Ninety-one genes were up-regulated and six genes were down-regulated in AITLs compared to control. The Gene Ontology (GO) analysis of 97-DEGs revealed that they were closely related to cytokine, MAPK cascade, leukocyte differentiation, and immune response, suggesting that this affect the immune system. In addition, KEGG analysis revealed that AITL DEGs were found to be highly involved in cytokine-cytokine receptor interaction and PI3K-Akt signaling pathway.

Conclusion: We believe that comprehensive multiplex studies, along with NanoString analysis, may be helpful to understand the molecular mechanisms of AITL, including mutations, gene expression, and protein expression studies.

Keywords: AITL; Angioimmunoblastic T-cell lymphoma; DEG; Differentially expressed genes; NanoString.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Gene Expression Profiling / methods*
  • Gene Expression Profiling / standards
  • Humans
  • Immunoblastic Lymphadenopathy / genetics*
  • Lymphoma, T-Cell / genetics*
  • Tissue Embedding / methods
  • Transcriptome