Optimization of Preanalytical Variables for cfDNA Processing and Detection of ctDNA in Archival Plasma Samples.

DNA released from cells into the peripheral blood is known as cell-free DNA (cfDNA), representing a promising noninvasive source of biomarkers that could be utilized to manage Diffuse Large B-Cell Lymphoma (DLBCL), among other diseases. The procedure for purification and handling of cfDNA is not yet standardized, and various preanalytical variables may affect the yield and analysis of cfDNA, including the purification kits, blood collection tubes, and centrifugation regime. Therefore, we aimed to investigate the impact of these preanalytical variables on the yield of cfDNA by comparing three different purification kits DNeasy Blood & Tissue Kit (Qiagen), QIAamp Circulating Nucleic Acid Kit (Qiagen), and Quick-cfDNA Serum & Plasma Kit (Zymo Research). Two blood collection tubes (BCTs), EDTA-K2 and Cell-Free DNA (Streck), stored at four different time points before plasma was separated and cfDNA purified, were compared, and for EDTA tubes, two centrifugation regimes at 2000 × g and 3000 × g were tested. Additionally, we have tested the utility of long-term archival blood samples from DLBCL patients to detect circulating tumor DNA (ctDNA). We observed a higher cfDNA yield using the QIAamp Circulating Nucleic Acid Kit (Qiagen) purification kit, as well as a higher cfDNA yield when blood samples were collected in EDTA BCTs, with a centrifuge regime at 2000 × g. Moreover, ctDNA detection was feasible from archival plasma samples with a median storage time of nine years.

Development of a Precision Medicine Workflow in Hematological Cancers, Aalborg University Hospital, Denmark.

Within recent years, many precision cancer medicine initiatives have been developed. Most of these have focused on solid cancers, while the potential of precision medicine for patients with hematological malignancies, especially in the relapse situation, are less elucidated. Here, we present a demographic unbiased and observational prospective study at Aalborg University Hospital Denmark, referral site for 10% of the Danish population. We developed a hematological precision medicine workflow based on sequencing analysis of whole exome tumor DNA and RNA. All steps involved are outlined in detail, illustrating how the developed workflow can provide relevant molecular information to multidisciplinary teams. A group of 174 hematological patients with progressive disease or relapse was included in a non-interventional and population-based study, of which 92 patient samples were sequenced. Based on analysis of small nucleotide variants, copy number variants, and fusion transcripts, we found variants with potential and strong clinical relevance in 62% and 9.5% of the patients, respectively. The most frequently mutated genes in individual disease entities were in concordance with previous studies. We did not find tumor mutational burden or micro satellite instability to be informative in our hematologic patient cohort.

Unaccounted uncertainty from qPCR efficiency estimates entails uncontrolled false positive rates.

BACKGROUND: Accurate adjustment for the amplification efficiency (AE) is an important part of real-time quantitative polymerase chain reaction (qPCR) experiments. The most commonly used correction strategy is to estimate the AE by dilution experiments and use this as a plug-in when efficiency correcting the Δ Δ C q . Currently, it is recommended to determine the AE with high precision as this plug-in approach does not account for the AE uncertainty, implicitly assuming an infinitely precise AE estimate. Determining the AE with such precision, however, requires tedious laboratory work and vast amounts of biological material. Violation of the assumption leads to overly optimistic standard errors of the Δ Δ C q , confidence intervals, and p-values which ultimately increase the type I error rate beyond the expected significance level. As qPCR is often used for validation it should be a high priority to account for the uncertainty of the AE estimate and thereby properly bounding the type I error rate and achieve the desired significance level. RESULTS: We suggest and benchmark different methods to obtain the standard error of the efficiency adjusted Δ Δ C q using the statistical delta method, Monte Carlo integration, or bootstrapping. Our suggested methods are founded in a linear mixed effects model (LMM) framework, but the problem and ideas apply in all qPCR experiments. The methods and impact of the AE uncertainty are illustrated in three qPCR applications and a simulation study. In addition, we validate findings suggesting that MGST1 is differentially expressed between high and low abundance culture initiating cells in multiple myeloma and that microRNA-127 is differentially expressed between testicular and nodal lymphomas. CONCLUSIONS: We conclude, that the commonly used efficiency corrected quantities disregard the uncertainty of the AE, which can drastically impact the standard error and lead to increased false positive rates. Our suggestions show that it is possible to easily perform statistical inference of Δ Δ C q , whilst properly accounting for the AE uncertainty and better controlling the false positive rate.

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.

Diffuse large B-cell lymphoma classification system that associates normal B-cell subset phenotypes with prognosis.

PURPOSE: Current diagnostic tests for diffuse large B-cell lymphoma use the updated WHO criteria based on biologic, morphologic, and clinical heterogeneity. We propose a refined classification system based on subset-specific B-cell-associated gene signatures (BAGS) in the normal B-cell hierarchy, hypothesizing that it can provide new biologic insight and diagnostic and prognostic value. PATIENTS AND METHODS: We combined fluorescence-activated cell sorting, gene expression profiling, and statistical modeling to generate BAGS for naive, centrocyte, centroblast, memory, and plasmablast B cells from normal human tonsils. The impact of BAGS-assigned subtyping was analyzed using five clinical cohorts (treated with cyclophosphamide, doxorubicin, vincristine, and prednisone [CHOP], n = 270; treated with rituximab plus CHOP [R-CHOP], n = 869) gathered across geographic regions, time eras, and sampling methods. The analysis estimated subtype frequencies and drug-specific resistance and included a prognostic meta-analysis of patients treated with first-line R-CHOP therapy. RESULTS: Similar BAGS subtype frequencies were assigned across 1,139 samples from five different cohorts. Among R-CHOP-treated patients, BAGS assignment was significantly associated with overall survival and progression-free survival within the germinal center B-cell-like subclass; the centrocyte subtype had a superior prognosis compared with the centroblast subtype. In agreement with the observed therapeutic outcome, centrocyte subtypes were estimated as being less resistant than the centroblast subtype to doxorubicin and vincristine. The centroblast subtype had a complex genotype, whereas the centrocyte subtype had high TP53 mutation and insertion/deletion frequencies and expressed LMO2, CD58, and stromal-1-signature and major histocompatibility complex class II-signature genes, which are known to have a positive impact on prognosis. CONCLUSION: Further development of a diagnostic platform using BAGS-assigned subtypes may allow pathogenetic studies to improve disease management.

Proof of the concept to use a malignant B cell line drug screen strategy for identification and weight of melphalan resistance genes in multiple myeloma.

In a conceptual study of drug resistance we have used a preclinical model of malignant B-cell lines by combining drug induced growth inhibition and gene expression profiling. In the current report a melphalan resistance profile of 19 genes were weighted by microarray data from the MRC Myeloma IX trial and time to progression following high dose melphalan, to generate an individual melphalan resistance index. The resistance index was subsequently validated in the HOVON65/GMMG-HD4 trial data set to prove the concept. Biologically, the assigned resistance indices were differentially distributed among translocations and cyclin D expression classes. Clinically, the 25% most melphalan resistant, the intermediate 50% and the 25% most sensitive patients had a median progression free survival of 18, 32 and 28 months, respectively (log-rank P-value  = 0.05). Furthermore, the median overall survival was 45 months for the resistant group and not reached for the intermediate and sensitive groups (log-rank P-value  = 0.003) following 38 months median observation. In a multivariate analysis, correcting for age, sex and ISS-staging, we found a high resistance index to be an independent variable associated with inferior progression free survival and overall survival. This study provides clinical proof of concept to use in vitro drug screen for identification of melphalan resistance gene signatures for future functional analysis.

Increased expression of transcription factor TFAP2α correlates with chemosensitivity in advanced bladder cancer.

BACKGROUND: The standard treatment for patients with advanced transitional cell carcinoma of the bladder is platin based chemotherapy. Only approximately 50% of the patients respond to chemotherapy. Therefore, molecular predictive markers for identification of chemotherapy sensitive subgroups of patients are highly needed. We selected the transcription factor TFAP2α from a previously identified gene expression signature for chemotherapy response. METHODS: TFAP2α expression and localization was assessed by immunohistochemistry using a tissue microarray (TMA) containing 282 bladder cancer tumors from patients with locally advanced (pT2-T4(b) and N(1-3)) or metastatic (M(1)) disease. All patients had received cisplatin containing chemotherapy. Furthermore, QPCR analysis of three TFAP2α isoforms was performed on tumor specimens of advanced muscle invasive bladder cancers (T2-4). Using the bladder cell lines T24 and SW780 the relation of TFAP2α and cisplatin and gemcitabine sensitivity as well as cell proliferation was examined using siRNA directed TFAP2α knockdown. RESULTS: TFAP2α protein expression was analyzed on a TMA with cores from 282 advanced bladder cancer tumors from patients treated with cisplatin based combinational chemotherapy. TFAP2α was identified as a strong independent predictive marker for a good response and survival after cisplatin-containing chemotherapy in patients with advanced bladder cancer. Strong TFAP2α nuclear and cytoplasmic staining predicted good response to chemotherapy in patients with lymph node metastasis, whereas weak TFAP2α nuclear staining predicted good response in patients without lymph node metastasis. In vitro studies showed that siRNA mediated knockdown of TFAP2α increased the proliferation of SW780 cells and rendered the cells less sensitive to cisplatin and gemcitabine. In contrast to that T24 bladder cells with mutated p53 showed to be more drug sensitive upon TFAP2α depletion. CONCLUSIONS: High levels of nuclear and cytoplasmic TFAP2α protein were a predictor of increased overall survival and progression free survival in patients with advanced bladder cancer treated with cisplatin based chemotherapy. TFAP2α knockdown increased the proliferation of the SW780 bladder cells and reduced cisplatin and gemcitabine induced cell death. The inverse effect was observed in the TP53 mutated T24 cell line where TFAP2α silencing augmented cisplatin and gemcitabine sensitivity and did not stimulate proliferation.

Additivity in effects of vitronectin and monoclonal antibodies against alpha-helix F of plasminogen activator inhibitor-1 on its reactions with target proteinases.

The serpin plasminogen activator inhibitor-1 (PAI-1) is a potential therapeutic target in cardiovascular and cancerous diseases. PAI-1 circulates in blood as a complex with vitronectin. A PAI-1 variant (N-((2-(iodoacetoxy)ethyl)-N-methyl)amino-7-nitrobenz-2-oxa-3-diazole (NBD) P9 PAI-1) with a fluorescent tag at the reactive center loop (RCL) was used to study the effects of vitronectin and monoclonal antibodies (mAbs) directed against alpha-helix F (Mab-2 and MA-55F4C12) on the reactions of PAI-1 with tissue-type and urokinase-type plasminogen activators. Both mAbs delay the RCL insertion and induce an increase in the stoichiometry of inhibition (SI) to 1.4-9.5. Binding of vitronectin to NBD P9 PAI-1 does not affect SI but results in a 2.0-6.5-fold decrease in the limiting rate constant (klim) of RCL insertion for urokinase-type plasminogen activator at pH 6.2-8.0 and for tissue-type plasminogen activator at pH 6.2. Binding of vitronectin to the complexes of NBD P9 PAI-1 with mAbs results in a decrease in klim and in a 1.5-22-fold increase in SI. Thus, vitronectin and mAbs demonstrated additivity in the effects on the reaction with target proteinases. The same step in the reaction mechanism remains limiting for the rate of RCL insertion in the absence and presence of Vn and mAbs. We hypothesize that vitronectin, bound to alpha-helix F on the side opposite to the epitopes of the mAbs, potentiates the mAb-induced delay in RCL insertion and the associated substrate behavior by selectively decreasing the rate constant for the inhibitory branch of PAI-1 reaction (ki). These results demonstrate that mAbs represent a valid approach for inactivation of vitronectin-bound PAI-1 in vivo.

Plasminogen activator inhibitor-I and tumour growth, invasion, and metastasis.

In recent decades, evidence has been accumulating showing the important role of urokinase-type plasminogen activator (uPA) in growth, invasion, and metastasis of malignant tumours. The evidence comes from results with animal tumour models and from the observation that a high level of uPA in human tumours is associated with a poor patient prognosis. It therefore initially came as a surprise that a high tumour level of the uPA inhibitor plasminogen activator inhibitor-I (PAI-I) is also associated with a poor prognosis, the PAI-I level in fact being one of the most informative biochemical prognostic markers. We review here recent investigations into the possible tumour biological role of PAI-I, performed by animal tumour models, histological examination of human tumours, and new knowledge about the molecular interactions of PAI-I possibly underlying its tumour biological functions. The exact tumour biological functions of PAI-I remain uncertain but PAI-I seems to be multifunctional as PAI-I is expressed by multiple cell types and has multiple molecular interactions. The potential utilisation of PAI-I as a target for anti-cancer therapy depends on further mapping of these functions.

Construction of a plasminogen activator inhibitor-1 variant without measurable affinity to vitronectin but otherwise normal.

Vitronectin (VN) and plasminogen activator inhibitor-1 (PAI-1) have important functional interactions: VN stabilises the protease inhibitory activity of PAI-1 and PAI-1 inhibits binding of adhesion receptors to VN. Having previously mapped the PAI-1 binding area for VN, we have now constructed a PAI-1 variant, R103A-M112A-Q125A, without measurable affinity to VN, but with full protease inhibitory activity and endocytosis receptor binding. As a tool for evaluating the physiological and pathophysiological functions of the PAI-1-VN interaction, our new variant is far superior to the previously widely used PAI-1 variant Q125K, which we have found possesses an only about 10-fold reduced affinity to VN.

Biochemical mechanism of action of a diketopiperazine inactivator of plasminogen activator inhibitor-1.

XR5118 [(3 Z,6 Z )-6-benzylidine-3-(5-(2-dimethylaminoethyl-thio-))-2-(thienyl)methylene-2,5-dipiperazinedione hydrochloride] can inactivate the anti-proteolytic activity of the serpin plasminogen activator inhibitor-1 (PAI-1), a potential therapeutic target in cancer and cardiovascular diseases. Serpins inhibit their target proteases by the P(1) residue of their reactive centre loop (RCL) forming an ester bond with the active-site serine residue of the protease, followed by insertion of the RCL into the serpin's large central beta-sheet A. In the present study, we show that the RCL of XR5118-inactivated PAI-1 is inert to reaction with its target proteases and has a decreased susceptibility to non-target proteases, in spite of a generally increased proteolytic susceptibility of specific peptide bonds elsewhere in PAI-1. The properties of XR5118-inactivated PAI-1 were different from those of the so-called latent form of PAI-1. Alanine substitution of several individual residues decreased the susceptibility of PAI-1 to XR5118. The localization of these residues in the three-dimensional structure of PAI-1 suggested that the XR5118-induced inactivating conformational change requires mobility of alpha-helix F, situated above beta-sheet A, and is in agreement with the hypothesis that XR5118 binds laterally to beta-sheet A. These results improve our understanding of the unique conformational flexibility of serpins and the biochemical basis for using PAI-1 as a therapeutic target.

Mapping of the epitope of a monoclonal antibody protecting plasminogen activator inhibitor-1 against inactivating agents.

Plasminogen activator inhibitor-1 (PAI-1) belongs to the serpin family of serine proteinase inhibitors. Serpins inhibit their target proteinases by an ester bond being formed between the active site serine of the proteinase and the P1 residue of the reactive centre loop (RCL) of the serpin, followed by insertion of the RCL into beta-sheet A of the serpin. Concomitantly, there are conformational changes in the flexible joint region lateral to beta-sheet A. We have now, by site-directed mutagenesis, mapped the epitope for a monoclonal antibody, which protects the inhibitory activity of PAI-1 against inactivation by a variety of agents acting on beta-sheet A and the flexible joint region. Curiously, the epitope is localized in alpha-helix C and the loop connecting alpha-helix I and beta-strand 5A, on the side of PAI-1 opposite to beta-sheet A and distantly from the flexible joint region. By a combination of site-directed mutagenesis and antibody protection against an inactivating organochemical ligand, we were able to identify a residue involved in conferring the antibody-induced conformational change from the epitope to the rest of the molecule. We have thus provided evidence for communication between secondary structural elements not previously known to interact in serpins.