Add like
Add dislike
Add to saved papers

The application of targeted RNA sequencing for the analysis of fusion genes, gene mutations, IKZF1 intragenic deletion, and CRLF2 overexpression in acute lymphoblastic leukemia.

INTRODUCTION: Acute lymphoblastic leukemia (ALL) is characterized by highly genetic heterogeneity, owing to recurrent fusion genes, gene mutations, intragenic deletion, and gene overexpression, which poses significant challenges in clinical detection. RNA sequencing (RNA-seq) is a powerful tool for detecting multiple genetic abnormalities, especially cryptic gene rearrangements, in a single test.

METHODS: Sixty samples (B-ALL, n = 49; T-ALL, n = 9; mixed phenotype acute leukemia (MPAL), n = 2) and 20 controls were analyzed by targeted RNA-seq panel of 507 genes developed by our lab. Of these, 16 patients were simultaneously analyzed for gene mutations at the DNA level using a next-generation sequencing panel of 51 genes. Fusion genes, CRLF2 expression, and IKZF1 intragenic deletion were also detected by reverse transcription-polymerase chain reaction (RT-PCR). Karyotype analysis was performed using the R-banding and G-banding technique on bone marrow cells after 24 hours of culture. Partial fusion genes were analyzed using fluorescence in situ hybridization (FISH).

RESULTS: Compared with the results of Karyotype analysis, FISH, and RT-PCR, the detection rate of fusion genes by targeted RNA-seq increased from 48.3% to 58.3%, and six unexpected fusion genes were discovered, along with one rare isoform of IKZF1 intragenic deletion (IK10). The DNA sequencing analysis of 16 ALL patients revealed that 96.2% (25/26) of gene mutations identified at the DNA level were also detectable at the RNA level, except for one mutation with a low variant allele fraction. The detection of CRLF2 overexpression exhibited complete concordance between RT-PCR and RNA-seq.

CONCLUSION: The utilization of RNA-seq enables the identification of clinically significant genetic abnormalities that may go undetected through conventional detection methods. Its robust analytical performance might bring great application value for clinical diagnosis, prognosis, and therapy in ALL.

Full text links

We have located links that may give you full text access.
Can't access the paper?
Try logging in through your university/institutional subscription. For a smoother one-click institutional access experience, please use our mobile app.

Related Resources

For the best experience, use the Read mobile app

Mobile app image

Get seemless 1-tap access through your institution/university

For the best experience, use the Read mobile app

All material on this website is protected by copyright, Copyright © 1994-2024 by WebMD LLC.
This website also contains material copyrighted by 3rd parties.

By using this service, you agree to our terms of use and privacy policy.

Your Privacy Choices Toggle icon

You can now claim free CME credits for this literature searchClaim now

Get seemless 1-tap access through your institution/university

For the best experience, use the Read mobile app