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Treatment resistance is a major clinical challenge of diffuse large B-cell lymphoma (DLBCL) where approximately 40% of the patients have refractory disease or relapse. Since DLBCL is characterized by great clinical and molecular heterogeneity, the purpose of the present study was to investigate whether miRNAs associated to single drug components of R-CHOP can improve robustness of individual markers and serve as a prognostic classifier.
Patients suffering from cancer are often treated with a range of chemotherapeutic agents, but the treatment efficacy varies greatly between patients. Based on recent popularisation of regularised regression models the goal of this study was to establish workflows for pharmacogenomic predictors of response to standard multidrug regimens using baseline gene expression data and origin specific cell lines. The proposed workflows are tested on diffuse large B-cell lymphoma treated with R-CHOP first-line therapy.
Diffuse large B-cell lymphoma (DLBCL) is the most frequent lymphoid neoplasm among adults,and approximately 30-40% of patients will experience relapse while 5-10% will suffer from primary refractory disease caused by different mechanisms, including treatment-induced resistance. For refractory and relapsed DLBCL (rrDLBCL) patients, early detection and understanding of the mechanisms controlling treatment resistance are of great importance to guide therapy decisions. Here, we have focused on genetic variations in immune surveillance genes in diagnostic DLBCL (dDLBCL) and rrDLBCL patients to elaborate on the suitability of new promising immunotherapies.
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