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Time to Treatment Prediction in Chronic Lymphocytic Leukemia Based on New Transcriptional Patterns.

ABSTRACT: Chronic lymphocytic leukemia (CLL) is the most frequent lymphoproliferative syndrome in western countries. CLL evolution is frequently indolent, and treatment is mostly reserved for those patients with signs or symptoms of disease progression. In this work, we used RNA sequencing data from the International Cancer Genome Consortium CLL cohort to determine new gene expression patterns that correlate with clinical evolution.We determined that a 290-gene expression signature, in addition to immunoglobulin heavy chain variable region (IGHV) mutation status, stratifies patients into four groups with notably different time to first treatment. This finding was confirmed in an independent cohort. Similarly, we present a machine learning algorithm that predicts the need for treatment within the first 5 years following diagnosis using expression data from 2,198 genes. This predictor achieved 90% precision and 89% accuracy when classifying independent CLL cases. Our findings indicate that CLL progression risk largely correlates with particular transcriptomic patterns and paves the way for the identification of high-risk patients who might benefit from prompt therapy following diagnosis.

SUBMITTER: Mosquera Orgueira A

PROVIDER: S-EPMC6384245 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Time to Treatment Prediction in Chronic Lymphocytic Leukemia Based on New Transcriptional Patterns.

Mosquera Orgueira Adrián A Antelo Rodríguez Beatriz B Alonso Vence Natalia N Bendaña López Ángeles Á Díaz Arias José Ángel JÁ Díaz Varela Nicolás N González Pérez Marta Sonia MS Pérez Encinas Manuel Mateo MM Bello López José Luis JL

Frontiers in oncology 20190215

Chronic lymphocytic leukemia (CLL) is the most frequent lymphoproliferative syndrome in western countries. CLL evolution is frequently indolent, and treatment is mostly reserved for those patients with signs or symptoms of disease progression. In this work, we used RNA sequencing data from the International Cancer Genome Consortium CLL cohort to determine new gene expression patterns that correlate with clinical evolution.We determined that a 290-gene expression signature, in addition to immunog ...[more]

PMID: 30828568

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Project description:BackgroundThe established clinical staging systems (Rai/Binet) of chronic lymphocytic leukemia (CLL) cannot accurately predict the appropriate treatment of patients in the earlier stages. In the past two decades, several prognostic factors have been identified to predict the outcome of patients with CLL, but only a few studies investigated more markers together. To predict the time to first treatment (TTFT) in patients of early stages, we evaluated the prognostic role of conventional markers as well as cytogenetic abnormalities and combined them together in a new prognostic scoring system, the CLL prognostic index (CLL-PI).MethodsTaking advantage of a population of 406 untreated Chinese patients with CLL at early and advanced stage of disease, we identified the strongest prognostic markers of TTFT and, subsequently, in a cohort of 173 patients who had complete data for all 3 variables, we integrated the data of traditional staging system, cytogenetic aberrations, and mutational status of immunoglobulin heavy chain variable region (IGHV) in CLL-PI. The median follow-up time was 45 months and the end point was TTFT.ResultsThe median TTFT was 38 months and the 5-year overall survival was 80%. According to univariate analysis, patients of advanced Rai stages (P < 0.001) or with 11q- (P = 0.002), 17p- (P < 0.001), unmutated IGHV (P < 0.001), negative 13q- (P = 0.007) and elevated lactate dehydrogenase levels (P = 0.001) tended to have a significantly shorter TTFT. And subsequently, based on multivariate Cox regression analysis, three independent factors for TTFT were identified: advanced clinical stage (P = 0.002), 17p- (P = 0.050) and unmutated IGHV (P = 0.049). Applying weighted grading of these independent factors, a CLL-PI was constructed based on regression parameters, which could categorize four different risk groups (low risk [score 0], intermediate low [score 1], intermediate high [score 2] and high risk [score 3-6]) with significantly different TTFT (median TTFT of not reached (NR), 65.0 months, 36.0 months and 19.0 months, respectively, P < 0.001).ConclusionsThis study developed a weighted, integrated CLL-PI prognostic system of CLL patients which combines the critical genetic prognostic markers with traditional clinical stage. This novel modified PI system could be used to discriminate among groups and may help predict the TTFT and prognosis of patients with CLL.

Dataset Information

Time to Treatment Prediction in Chronic Lymphocytic Leukemia Based on New Transcriptional Patterns.

Publications

Time to Treatment Prediction in Chronic Lymphocytic Leukemia Based on New Transcriptional Patterns.

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