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MicroRNAs associated to single drug components of R-CHOP identifies diffuse large B-cell lymphoma patients with poor outcome and adds prognostic value to the international prognostic index.

ABSTRACT: BACKGROUND: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. METHODS:Fifteen DLBCL cell lines were tested for sensitivity towards single drug compounds of the standard treatment R-CHOP: rituximab (R), cyclophosphamide (C), doxorubicin (H), and vincristine (O). For each drug, cell lines were ranked using the area under the dose-response curve and grouped as either sensitive, intermediate or resistant. Baseline miRNA expression data were obtained for each cell line in untreated condition, and differential miRNA expression analysis between sensitive and resistant cell lines identified 43 miRNAs associated to growth response after exposure towards single drugs of R-CHOP. Using the Affymetrix HG-U133 platform, expression levels of miRNA precursors were assessed in 701 diagnostic DLBCL biopsies, and miRNA-panel classifiers predicting disease progression were build using multiple Cox regression or random survival forest. Classifiers were validated and ranked by repeated cross-validation. RESULTS:Prognostic accuracies were assessed by Brier Scores and time-varying area under the ROC curves, which revealed better performance of multivariate Cox models compared to random survival forest models. The Cox model including miR-146a, miR-155, miR-21, miR-34a, and miR-23a~miR-27a~miR-24-2 cluster performed the best and successfully stratified GCB-DLBCL patients into high- and low-risk of disease progression. In addition, combination of the Cox miRNA-panel and IPI substantially increased prognostic performance in GCB classified patients. CONCLUSION:As a proof of concept, we found that expression data of drug associated miRNAs display prognostic utility and adding these to IPI improves prognostic stratification of GCB-DLBCL patients treated with R-CHOP.

SUBMITTER: Due H

PROVIDER: S-EPMC7082970 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

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MicroRNAs associated to single drug components of R-CHOP identifies diffuse large B-cell lymphoma patients with poor outcome and adds prognostic value to the international prognostic index.

Due Hanne H Brøndum Rasmus Froberg RF Young Ken H KH Bøgsted Martin M Dybkær Karen K

BMC cancer 20200320 1

<h4>Background</h4>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.<h4>Methods</h4>Fifteen DLBCL cell lines ...[more]

PMID: 32192453

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Project description:BACKGROUND:The introduction of rituximab (R) to conventional CHOP chemotherapy for newly diagnosed diffuse large B-cell lymphoma (DLBCL) led to an unequivocal improvement in survival, establishing RCHOP as the standard of care. Still, nearly 40% of DLBCL patients will eventually die of relapsed disease. Efforts to improve outcomes by addition of new biologic agents (X) to the RCHOP backbone are underway. In this era of R(X)CHOP, it is imperative to develop prognostic and predictive markers, not only to identify patients who will suffer a particularly aggressive course, but also to accurately select patients for clinical trials from which they will most benefit. DESIGN:The following review was undertaken to describe prognostic factors in DLBCL, with emphasis on markers that are accurate, relatively available, and clinically applicable in 2014. RESULTS:The International Prognostic Index retains its validity in the era of RCHOP, although with limited ability to predict those with <50% chance of long-term survival. Gene expression profiling has provided novel insights into the biology of DLBCL and led to the development of immunohistochemistry (IHC) algorithms that are in routine practice. Identification of a 'double-hit' (DH) lymphoma by fluorescent in situ hybridization with aberrations involving MYC and/or BCL2 and BCL6 genes has important implications due to its extremely dismal prognosis with RCHOP. Other markers such as the absolute lymphocyte count (ALC), serum immunoglobulin free light chains, vitamin D levels, serum cytokines/chemokines, and imaging with positron emission tomography (PET) have all shown promise as future predictive/prognostic tests. CONCLUSIONS:The future for new treatment options in DLBCL is promising with current clinical trials testing novel targeted agents such as bortezomib, lenalidomide, and ibrutinib as the 'X' in R(X)CHOP. Predictive factors are required to select and randomize patients appropriately for these trials. We envision the day when 'X' will be chosen based on the biological characteristics of the tumor.

Project description:PurposeAlthough the role of tumor-infiltrating T cells in follicular lymphoma (FL) has been reported previously, the prognostic value of peripheral blood T lymphocyte subsets has not been systematically assessed. Thus, we aim to incorporate T-cell subsets with clinical features to develop a predictive model of clinical outcome.MethodsWe retrospectively screened a total of 1,008 patients, including 252 newly diagnosed de novo FL patients with available peripheral blood T lymphocyte subsets who were randomized to different sets (177 in the training set and 75 in the internal validation set). A nomogram and a novel immune-clinical prognostic index (ICPI) were established according to multivariate Cox regression analysis for progression-free survival (PFS). The concordance index (C-index), Akaike's information criterion (AIC), and likelihood ratio chi-square were employed to compare the ICPI's discriminatory capability and homogeneity to that of FLIPI, FLIPI2, and PRIMA-PI. Additional external validation was performed using a dataset (n = 157) from other four centers.ResultsIn the training set, multivariate analysis identified five independent prognostic factors (Stage III/IV disease, elevated lactate dehydrogenase (LDH), Hb <120g/L, CD4+ <30.7% and CD8+ >36.6%) for PFS. A novel ICPI was established according to the number of risk factors and stratify patients into 3 risk groups: high, intermediate, and low-risk with 4-5, 2-3, 0-1 risk factors respectively. The hazard ratios for patients in the high and intermediate-risk groups than those in the low-risk were 27.640 and 2.758. The ICPI could stratify patients into different risk groups both in the training set (P < 0.0001), internal validation set (P = 0.0039) and external validation set (P = 0.04). Moreover, in patients treated with RCHOP-like therapy, the ICPI was also predictive (P < 0.0001). In comparison to FLIPI, FLIPI2, and PRIMA-PI (C-index, 0.613-0.647), the ICPI offered adequate discrimination capability with C-index values of 0.679. Additionally, it exhibits good performance based on the lowest AIC and highest likelihood ratio chi-square score.ConclusionsThe ICPI is a novel predictive model with improved prognostic performance for patients with de novo FL treated with R-CHOP/CHOP chemotherapy. It is capable to be used in routine practice and guides individualized precision therapy.

Dataset Information

MicroRNAs associated to single drug components of R-CHOP identifies diffuse large B-cell lymphoma patients with poor outcome and adds prognostic value to the international prognostic index.

Publications

MicroRNAs associated to single drug components of R-CHOP identifies diffuse large B-cell lymphoma patients with poor outcome and adds prognostic value to the international prognostic index.

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