Oncotarget


Automated, Accurate Reporting for NGS-Based Clonality Testing


FOR IMMEDIATE RELEASE
2023-05-16

“[...] we have developed a fully automated calling algorithm for determining B and T cell clonality from NGS [next-generation sequencing] data, with greater sensitivity than previously developed models.”


 

BUFFALO, NY- May 16, 2023 – A new research paper was published in Oncotarget's Volume 14 on May 12, 2023, entitled, “Development and implementation of an automated and highly accurate reporting process for NGS-based clonality testing.”

 

B and T cells undergo random recombination of the VH/DH/JH portions of the immunoglobulin loci (B cell) and T-cell receptors before becoming functional cells. When one V-J rearrangement is over-represented in a population of B or T cells indicating an origin from a single cell, this indicates a clonal process. Clonality aids in the diagnosis and monitoring of lymphoproliferative disorders and evaluation of disease recurrence. 

 

In a new study, researchers Sean T. Glenn, Phillip M. Galbo Jr., Jesse D. Luce, Kiersten Marie Miles, Prashant K. Singh, Manuel J. Glynias, and Carl Morrison from Roswell Park Comprehensive Cancer Center aimed to develop objective criteria, which can be automated, to classify B and T cell clonality results as positive (clonal), No evidence of clonality, or invalid (failed). 

 

“Using clinical samples with 'gold standard' clonality data obtained using PCR/CE testing, we ran NGS-based amplicon clonality assays and developed our own model for clonality reporting.”

 

To assess the performance of their model, the researchers analyzed the NGS results across other published models. Their model for clonality calling using NGS-based technology increases the assay’s sensitivity, more accurately detecting clonality. In addition, they built a computational pipeline to use their model to objectively call clonality in an automated fashion. 

 

“Collectively the results outlined below will have a direct clinical impact by expediting the review and sign-out process for concise clonality reporting.”

 

Read the full paper: DOI: https://doi.org/10.18632/oncotarget.28429 

 

Correspondence to: Sean T. Glenn

 

Email: [email protected] 

 

Keywords: clonality, NGS, bioinformatics, molecular diagnostics, leukemia


 

About Oncotarget: Oncotarget (a primarily oncology-focused, peer-reviewed, open access journal) aims to maximize research impact through insightful peer-review; eliminate borders between specialties by linking different fields of oncology, cancer research and biomedical sciences; and foster application of basic and clinical science.

 

To learn more about Oncotarget, visit Oncotarget.com and connect with us on social media:

Twitter
Facebook
YouTube
Instagram

LinkedIn

Pinterest

LabTube

SoundCloud

 

Click here to subscribe to Oncotarget publication updates.

For media inquiries, please contact: [email protected].

 

Oncotarget Journal Office

6666 East Quaker Str., Suite 1A

Orchard Park, NY 14127

Phone: 1-800-922-0957 (option 2)



Copyright © 2024 Impact Journals, LLC
Impact Journals is a registered trademark of Impact Journals, LLC