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]
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.
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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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.
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]
Related Posts
Urine test may improve bladder cancer diagnosis and guide treatment decisions
Tracing 700 million years of cell evolution
RNA-Seq reveals a new way the developing heart controls its growth
The Human RNome Project Consortium seeks to publish first-ever complete sequence of the body’s RNA
Unmasking “zombie cells” in aging tissue with an AI-powered barcode
RNA variant imaging for cancer diagnosis
Autism-risk mutations reveal two opposing patterns of brain gene activity
Avoiding a sticky situation: how cells stop messenger RNAs from clumping together
RNA Sequencing identifies new tick-borne virus that causes flu-like illness
Worm’s radical transformation shows metamorphosis can change the functions of cells
RNA sequencing reveals functional chimeric mRNAs in mammalian immunity
Atlas of the brain’s striatum could guide researchers to new drug treatments
Immune cells offer insights on billion-dollar virus
A functionally integrated cross-tissue alternative splicing program during short-term calorie restriction
Dietary oxidized plant sterol shifts macrophage state to fuel aortic inflammation
Unlocking the past – new method helps gain insights into old tissue
Novel AI model trained on RNA-Seq data accurately detects key gene mutations and predicts biomarkers across 32 cancer types
Transcriptomic aging clock reveals age-related molecular patterns in opioid dependence
RNA sequencing helps predict stem cell transplant benefit in pediatric AML
Protein ‘switch’ determines whether liposarcoma cells will become aggressive
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