Clinical interpretation of cell-based non-invasive prenatal testing for monogenic disorders including repeat expansion disorders: potentials and pitfalls.

Introduction: Circulating fetal cells isolated from maternal blood can be used for prenatal testing, representing a safe alternative to invasive testing. The present study investigated the potential of cell-based noninvasive prenatal testing (NIPT) for diagnosing monogenic disorders dependent on the mode of inheritance. Methods: Maternal blood samples were collected from women opting for prenatal diagnostics for specific monogenic disorders (N = 7). Fetal trophoblasts were enriched and stained using magnetic activated cell sorting and isolated by fluorescens activated single-cell sorting. Individual cells were subject to whole genome amplification, and cells of fetal origin were identified by DNA-profiling using short tandem repeat markers. The amplified fetal DNA was input for genetic testing for autosomal dominant-, autosomal recessive-, X-linked and repeat expansion disorders by direct variant analysis and haplotyping. The cell-based NIPT results were compared with those of invasive testing. Results: In two cases at risk of skeletal dysplasia, caused by variants in the FGFR3 gene (autosomal dominant disorders), cell-based NIPT correctly stated an affected fetus, but allelic dropout of the normal alleles were observed in both cases. Cell-based NIPT gave an accurate result in two cases at risk of autosomal recessive disorders, where the parents carried either different diastrophic dysplasia causing variants in the SLC26A2 gene or the same cystic fibrosis disease-causing variant in the CFTR gene. Cell-based NIPT accurately identified an affected male fetus in a pregnancy at risk of Duchenne muscular dystrophy (DMD gene, X-linked recessive disorders). In two cases at risk of the myotonic dystrophy type 1 (DMPK gene, repeat expansion disorder), cell-based NIPT correctly detected an affected and an unaffected fetus, respectively. Discussion: Circulating fetal cells can be used to detect both maternally- and paternally inherited monogenic disorders irrespective of the type of variant, however, the risk of allelic dropout must be considered. We conclude that the clinical interpretation of the cell-based NIPT result thus varies depending on the disorders' mode of inheritance.

Validation of computational determination of microsatellite status using whole exome sequencing data from colorectal cancer patients.

BACKGROUND: Microsatellite instability (MSI), resulting from a defective mismatch repair system, occurs in approximately 15% of sporadic colorectal cancers (CRC). Since MSI is associated with a poor response to 5-fluorouracile based chemotherapy and is a positive predictive marker of immunotherapy, it is routine practice to evaluate the MSI status of resected tumors in CRC patients. MSIsensor is a novel computational tool for determining MSI status using Next Generation Sequencing. However, it is not widely used in the clinic and has not been independently validated in exome data from CRC. To facilitate clinical implementation of computational determination of MSI status, we compared MSIsensor to current gold standard methods for MSI testing. METHODS: MSI status was determined for 130 CRC patients (UICC stage I-IV) using immunohistochemistry, PCR based microsatellite stability testing and by applying MSIsensor to exome sequenced tumors and paired germline DNA. Furthermore, we investigated correlation between MSI status, mutational load and mutational signatures. RESULTS: Eighteen out of 130 (13.8%) patients were microsatellite instable. We found a 100% agreement between MSIsensor and gold standard methods for MSI testing. All MSI tumors were hypermutated. In addition, two microsatellite stable (MSS) tumors were hypermutated, which was explained by a dominant POLE signature and pathogenic POLE mutations (p.Pro286Arg and p.Ser459Phe). CONCLUSION: MSIsensor is a robust tool, which can be used to determine MSI status of tumor samples from exome sequenced CRC patients.

High CXCR4 expression impairs rituximab response and the prognosis of R-CHOP-treated diffuse large B-cell lymphoma patients.

Survival of diffuse large B-cell lymphoma (DLBCL) patients has improved by inclusion of rituximab. Refractory/recurrent disease caused by treatment resistance is, however, a major problem. Determinants of rituximab sensitivity are not fully understood, but effect of rituximab are enhanced by antagonizing cell surface receptor CXCR4. In a two-step strategy, we tested the hypothesis that prognostic value of CXCR4 in DLBCL relates to rituximab treatment, due to a hampering effect of CXCR4 on the response of DLBCL cells to rituximab. First, by investigating the prognostic impact of CXCR4 mRNA expression separately for CHOP (n=181) and R-CHOP (n=233) cohorts and, second, by assessing the interaction between CXCR4 and rituximab in DLBCL cell lines. High CXCR4 expression level was significantly associated with poor outcome only for R-CHOP-treated patients, independent of IPI score, CD20 expression, ABC/GCB and B-cell-associated gene signature (BAGS) classifications. s. For responsive cell lines, inverse correlation was observed between rituximab sensitivity and CXCR4 surface expression, rituximab induced upregulation of surface-expressed CXCR4, and growth-inhibitory effect of rituximab increased by plerixafor, supporting negative impact of CXCR4 on rituximab function. In conclusion, CXCR4 is a promising independent prognostic marker for R-CHOP-treated DLBCL patients, possibly due to inverse correlation between CXCR4 expression and rituximab sensitivity.

Molecular classification of tissue from a transformed non-Hogkin's lymphoma case with unexpected long-time remission.

BACKGROUND: The concept of precision medicine in cancer includes individual molecular studies to predict clinical outcomes. In the present N = 1 case we retrospectively have analysed lymphoma tissue by exome sequencing and global gene expression in a patient with unexpected long-term remission following relaps. The goals were to phenotype the diagnostic and relapsed lymphoma tissue and evaluate its pattern. Furthermore, to identify mutations available for targeted therapy and expression of genes to predict specific drug effects by resistance gene signatures (REGS) for R-CHOP as described at http://www.hemaclass.org. We expected that such a study could generate therapeutic information and a frame for future individual evaluation of molecular resistance detected at clinical relapse. CASE PRESENTATION: The patient was diagnosed with a transformed high-grade non-Hodgkin lymphoma stage III and treated with conventional R-CHOP [rituximab (R), cyclophosphamide (C), doxorubicin (H), vincristine (O) and prednisone (P)]. Unfortunately, she suffered from severe toxicity but recovered during the following 6 months' remission until biopsy-verified relapse. The patient refused second-line combination chemotherapy, but accepted 3 months' palliation with R and chlorambucil. Unexpectedly, she obtained continuous complete remission and is at present >9 years after primary diagnosis. Molecular studies and data evaluation by principal component analysis, mutation screening and copy number variations of the primary and relapsed tumor, identified a pattern of branched lymphoma evolution, most likely diverging from an in situ follicular lymphoma. Accordingly, the primary diagnosed transformed lymphoma was classified as a diffuse large B cell lymphoma (DLBCL) of the GCB/centrocytic subtype by "cell of origin BAGS" assignment and R sensitive and C, H, O and P resistant by "drug specific REGS" assignment. The relapsed DLBCL was classified as NC/memory subtype and R, C, H sensitive but O and P resistant. CONCLUSIONS: Thorough analysis of the tumor DNA and RNA documented a branched evolution of the two clinical diagnosed tFL, most likely transformed from an unknown in situ lymphoma. Classification of the malignant tissue for drug-specific resistance did not explain the unexpected long-term remission and potential cure. However, it is tempting to consider the anti-CD20 immunotherapy as the curative intervention in the two independent tumors of this case.

The CXCR4 antagonist plerixafor enhances the effect of rituximab in diffuse large B-cell lymphoma cell lines.

BACKGROUND: Diffuse large B-cell lymphoma (DLBCL) is an aggressive disease with variable clinical outcome, accounting for at least 25-30 % of adult non-Hodgkin lymphomas. Approximately one third of DLBCL patients are not cured by the currently used treatment regimen, R-CHOP. Hence, new treatment strategies are needed. Antagonizing the CXCR4 receptor might be promising since the CXCR4-CXCL12 axis is implicated in several aspects of tumor pathogenesis as well as in protection from chemotherapeutic response. In Burkitt lymphoma, the CXCR4 antagonist plerixafor has already been shown to enhance the therapeutic effect of rituximab, the immunotherapeutic agent of R-CHOP; but this is yet to be confirmed for DLBCL. We, therefore, investigated the effect of plerixafor on DLBCL cellular response to rituximab. METHODS: In this in vitro study, human DLBCL cell lines were treated with rituximab and/or plerixafor, concomitantly or in sequence. The trypan blue exclusion method and MTS-based assays were used to evaluate cellular proliferation, whereas flow cytometry was used for assessment of apoptosis status and CXCR4 surface expression level. Linear mixed effects models were used to assess statistical significance. RESULTS: We observed that simultaneous addition of plerixafor and rituximab resulted in a significant decrease in DLBCL cellular proliferation, compared to monotherapeutic response. The effect was dose-dependent, and concomitant administration was observed to be superior to sequential drug administration. Accordingly, the fraction of apoptotic/dead cells significantly increased following addition of plerixafor to rituximab treatment. Furthermore, exposure of DLBCL cells to plerixafor resulted in a significant decrease in CXCR4 fluorescence intensity. CONCLUSIONS: Based on our results, implying that the anti-proliferative/pro-apoptotic effect of rituximab on DLBCL cells can be synergistically enhanced by the CXCR4 antagonist plerixafor, addition of plerixafor to the R-CHOP regimen can be suggested to improve treatment outcome for DLBCL patients.

Anti-Apoptotic Effects of Lentiviral Vector Transduction Promote Increased Rituximab Tolerance in Cancerous B-Cells.

Diffuse large B-cell lymphoma (DLBCL) is characterized by great genetic and clinical heterogeneity which complicates prognostic prediction and influences treatment efficacy. The most common regimen, R-CHOP, consists of a combination of anthracycline- and immuno-based drugs including Rituximab. It remains elusive how and to which extent genetic variability impacts the response and potential tolerance to R-CHOP. Hence, an improved understanding of mechanisms leading to drug tolerance in B-cells is crucial, and modelling by genetic intervention directly in B-cells is fundamental in such investigations. Lentivirus-based gene vectors are widely used gene vehicles, which in B-cells are an attractive alternative to potentially toxic transfection-based methodologies. Here, we investigate the use of VSV-G-pseudotyped lentiviral vectors in B-cells for exploring the impact of microRNAs on tolerance to Rituximab. Notably, we find that robust lentiviral transduction of cancerous B-cell lines markedly and specifically enhances the resistance of transduced germinal center B-cells (GCBs) to Rituximab. Although Rituximab works partially through complement-mediated cell lysis, increased tolerance is not achieved through effects of lentiviral transduction on cell death mediated by complement. Rather, reduced levels of PARP1 and persistent high levels of CD43 in Rituximab-treated GCBs demonstrate anti-apoptotic effects of lentiviral transduction that may interfere with the outcome and interpretation of Rituximab tolerance studies. Our findings stress that caution should be exercised exploiting lentiviral vectors in studies of tolerance to therapeutics in DLBCL. Importantly, however, we demonstrate the feasibility of using the lentiviral gene delivery platform in studies addressing the impact of specific microRNAs on Rituximab responsiveness.

High miR-34a expression improves response to doxorubicin in diffuse large B-cell lymphoma.

The standard treatment for patients with diffuse large B-cell lymphoma (DLBCL) is the immunochemotherapy-based R-CHOP regimen (rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisolone). Resistance to treatment, intrinsic or acquired, is observed in approximately 40% of patients with DLBCL, who thus require novel interventions to survive. To identify biomarkers for cytotoxic response assessment, microRNAs (miRNAs) associated with doxorubicin sensitivity were determined by combining global miRNA expression profiling with systematic dose-response screens in 15 human DLBCL cell lines. One candidate, miR-34a, was tested in functional in vitro studies and in vivo in a retrospective clinical cohort. High expression of miR-34a was observed in cell lines sensitive to doxorubicin, and upregulation of miR-34a is documented here to increase doxorubicin sensitivity in in vitro lentiviral transduction assays. High expression of miR-34a had a prognostic impact using overall survival as outcome. With risk stratification of DLBCL samples based on resistance gene signatures (REGS), doxorubicin-responsive samples had statistically significant upregulated miR-34a expression. Classification of the DLBCL samples into subset-specific B cell-associated gene signatures (BAGS) revealed differentiation-specific expression of miR-34a. Our data further support FOXP1 as a target of miR-34a, suggesting that downregulation of FOXP1 may sensitize DLBCL cells to doxorubicin. We conclude that miRNAs, in particular miR-34a, may have clinical utility in DLBCL patients as both predictive and prognostic biomarkers.

MicroRNAs as novel biomarkers in diffuse large B-cell lymphoma--a systematic review.

INTRODUCTION: MicroRNAs (miRNAs) are short non-coding RNAs that have the ability to regulate gene expression at the post-transcriptional level. MiRNAs are deregulated in many cancer types, and several miRNAs have been suggested as novel diagnostic and prognostic biomarkers in diffuse large B-cell lymphoma (DLBCL). The objective of this study was to systematically collect and evaluate current knowledge of miRNAs functioning as diagnostic and prognostic biomarkers within DLBCL. METHODS: This review was conducted according to the Preferred Reporting for Systematic Reviews and Meta-analyses guidelines. A systematic search of literature in PubMed and Embase was made and supplemented by screening of reference lists. Only original peer-reviewed studies written in English were included and screened based on miRNA expression, molecular subtypes of DLBCL and patient outcome. RESULTS: Out of 277 candidate records, a total of 20 studies qualified for inclusion in this review. In all, 11 studies reported a total of 48 miRNAs with expression patterns associated with specific molecular DLBCL subtypes, and 14 studies reported a total of 30 miRNAs associated with patient outcome. However, only few miRNAs showed significant results in more than one study. CONCLUSION: MiRNAs qualify as potential diagnostic and prognostic biomarkers in DLBCL. However, more clinical validation including prospective and cross-centre studies are required before specific miRNAs can be integrated into the daily practice as biomarkers in DLBCL, which would contribute to an era of more personalised medicine.

Predicting response to multidrug regimens in cancer patients using cell line experiments and regularised regression models.

BACKGROUND: 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. METHODS: First, B-cell cancer cell lines were tested successively for resistance towards the chemotherapeutic components of R-CHOP: cyclophosphamide (C), doxorubicin (H), and vincristine (O). Second, baseline gene expression data were obtained for each cell line before treatment. Third, regularised multivariate regression models with cross-validated tuning parameters were used to generate classifier and predictor based resistance gene signatures (REGS) for the combination and individual chemotherapeutic drugs C, H, and O. Fourth, each developed REGS was used to assign resistance levels to individual patients in three clinical cohorts. RESULTS: Both classifier and predictor based REGS, for the combination CHO, were of prognostic value. For patients classified as resistant towards CHO the risk of progression was 2.33 (95% CI: 1.6, 3.3) times greater than for those classified as sensitive. Similarly, an increase in the predicted CHO resistance index of 10 was related to a 22% (9%, 36%) increased risk of progression. Furthermore, the REGS classifier performed significantly better than the REGS predictor. CONCLUSIONS: The regularised multivariate regression models provide a flexible workflow for drug resistance studies with promising potential. However, the gene expressions defining the REGSs should be functionally validated and correlated to known biomarkers to improve understanding of molecular mechanisms of drug resistance.

MicroRNAs in B-cells: from normal differentiation to treatment of malignancies.

MicroRNAs (miRNAs) are small non-coding RNAs that play important post-transcriptional regulatory roles in a wide range of biological processes. They are fundamental to the normal development of cells, and evidence suggests that the deregulation of specific miRNAs is involved in malignant transformation due to their function as oncogenes or tumor suppressors. We know that miRNAs are involved in the development of normal B-cells and that different B-cell subsets express specific miRNA profiles according to their degree of differentiation. B-cell-derived malignancies contain transcription signatures reminiscent of their cell of origin. Therefore, we believe that normal and malignant B-cells share features of regulatory networks controlling differentiation and the ability to respond to treatment. The involvement of miRNAs in these processes makes them good biomarker candidates. B-cell malignancies are highly prevalent, and the poor overall survival of patients with these malignancies demands an improvement in stratification according to prognosis and therapy response, wherein we believe miRNAs may be of great importance. We have critically reviewed the literature, and here we sum up the findings of miRNA studies in hematological cancers, from the development and progression of the disease to the response to treatment, with a particular emphasis on B-cell malignancies.

Human B-cell cancer cell lines as a preclinical model for studies of drug effect in diffuse large B-cell lymphoma and multiple myeloma.

Drug resistance in cancer refers to recurrent or primary refractory disease following drug therapy. At the cellular level, it is a consequence of molecular functions that ultimately enable the cell to resist cell death-one of the classical hallmarks of cancer. Thus, drug resistance is a fundamental aspect of the cancer cell phenotype, in parallel with sustained proliferation, immortality, angiogenesis, invasion, and metastasis. Here we present a preclinical model of human B-cell cancer cell lines used to identify genes involved in specific drug resistance. This process includes a standardized technical setup for specific drug screening, analysis of global gene expression, and the statistical considerations required to develop resistance gene signatures. The state of the art is illustrated by the first-step classical drug screen (including the CD20 antibody rituximab, the DNA intercalating topoisomerase II inhibitor doxorubicin, the mitotic inhibitor vincristine, and the alkylating agents cyclophosphamide and melphalan) along with the generation of gene lists predicting the chemotherapeutic outcome as validated retrospectively in clinical trial datasets. This B-cell lineage-specific preclinical model will allow us to initiate a range of laboratory studies, with focus on specific gene functions involved in molecular resistance mechanisms.

Exposure time independent summary statistics for assessment of drug dependent cell line growth inhibition.

BACKGROUND: In vitro generated dose-response curves of human cancer cell lines are widely used to develop new therapeutics. The curves are summarised by simplified statistics that ignore the conventionally used dose-response curves' dependency on drug exposure time and growth kinetics. This may lead to suboptimal exploitation of data and biased conclusions on the potential of the drug in question. Therefore we set out to improve the dose-response assessments by eliminating the impact of time dependency. RESULTS: First, a mathematical model for drug induced cell growth inhibition was formulated and used to derive novel dose-response curves and improved summary statistics that are independent of time under the proposed model. Next, a statistical analysis workflow for estimating the improved statistics was suggested consisting of 1) nonlinear regression models for estimation of cell counts and doubling times, 2) isotonic regression for modelling the suggested dose-response curves, and 3) resampling based method for assessing variation of the novel summary statistics. We document that conventionally used summary statistics for dose-response experiments depend on time so that fast growing cell lines compared to slowly growing ones are considered overly sensitive. The adequacy of the mathematical model is tested for doxorubicin and found to fit real data to an acceptable degree. Dose-response data from the NCI60 drug screen were used to illustrate the time dependency and demonstrate an adjustment correcting for it. The applicability of the workflow was illustrated by simulation and application on a doxorubicin growth inhibition screen. The simulations show that under the proposed mathematical model the suggested statistical workflow results in unbiased estimates of the time independent summary statistics. Variance estimates of the novel summary statistics are used to conclude that the doxorubicin screen covers a significant diverse range of responses ensuring it is useful for biological interpretations. CONCLUSION: Time independent summary statistics may aid the understanding of drugs' action mechanism on tumour cells and potentially renew previous drug sensitivity evaluation studies.