RNA Sequencing identifies high-risk chronic lymphocytic leukemia

From Healio.com

A 290-gene expression signature and IGHV mutation status stratified patients with chronic lymphocytic leukemia to identify those with high-risk disease who might benefit from prompt initiation of therapy, according to a study published in Frontiers in Oncology.

Although CLL treatment is typically delayed until disease progression, it is uncertain whether patients would benefit from treatment immediately following diagnosis, when they have a smaller tumor mass and are in better physical condition.

Researchers have discovered new drivers of CLL, and RNA sequencing offers an opportunity to identify additional biomarkers that might predict disease progression and treatment benefit in order to better risk-stratify patients, according to the researchers.

“In fact, previous efforts to improve CLL risk stratification based on RNA sequencing data have demonstrated impressive results, but the clinical application is difficult due to the expense of extensive technical and bioinformatics efforts,” Adrián Mosquera Orgueira, MD, hematology resident of cancer genomics research and bioinformatics at Health Research Institute of Santiago de Compostela, and colleagues wrote. “Therefore, there is a need for smaller transcriptomics patterns correlated with disease evolution for medical use.”

Orgueira and colleagues used RNA sequencing data from the International Cancer Genome Consortium CLL cohort to identify gene expression trends that are associated with clinical disease evolution and time to first treatment. The analysis included a test cohort of 196 patients (median age at diagnosis, 63 years; 60.7% men) and a validation cohort of 79 patients (median age at diagnosis, 62 years; 69.62% men).

(read more at Healio.com…)

Mosquera Orgueira A, Antelo Rodríguez B, Alonso Vence N, Bendaña López Á, Díaz Arias JÁ, Díaz Varela N, González Pérez MS, Pérez Encinas MM, Bello López JL, (2019) Time to Treatment Prediction in Chronic Lymphocytic Leukemia Based on New Transcriptional Patterns. Front Oncol 9:79. [article]

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