Maciej Kaźmierczak

Cancer procoagulant in patients with adenocarcinomas.

Cancer procoagulant (CP) is a cysteine proteinase that may be produced by malignant and foetal tissue. The possible role of CP in the pathogenesis of cancer-related thrombosis has been suggested recently. The purpose of the study was to evaluate coagulation prothrombotic markers and their relation to CP concentration in the blood of patients with gastrointestinal adenocarcinomas (GIAC). The study group consisted of 45 patients with confirmed diagnosis of adenocarcinoma (stomach, 18 patients; colon, 27 patients) and without evident metastatic disease. In 24 patients further observation showed metastases. The control group for CP was composed of 10 healthy subjects. Blood samples were drawn on the admission day, before any treatment. Among 45 patients with GIAC, deep venous thrombosis was observed in two (4.4%). In all patients the CP activity in the serum was found, and the mean CP activity shortened the coagulation time almost three times compared with the healthy control group. Also, the mean thrombin–antithrombin complex concentration was above the normal range. A significant elevation of the mean prothrombin fragment 1+2 plasma content in this group of patients was noticed. Despite these observations, CP remained within the normal range and did not correlate with thrombin–antithrombin complex or prothrombin fragment 1+2 plasma concentrations. A positive correlation was observed between serum CP and fibrinogen concentration, and a negative correlation between CP and free protein S plasma content (P = 0.04 and P = 0.025, respectively). A negative correlation between activated protein C resistance ratio and protein C activity in the plasma was confirmed. Protein C activity in the plasma showed a correlation with free protein S plasma content. Analysis of factors influencing the activated partial thromboplastin time revealed the presence of antiphospholipid antibodies in seven persons from the study group (in three cases of IgG and in four cases of IgM class). Our data suggest that CP is a minor risk factor for deep venous thrombosis in GIAC patients. To confirm this, however, the number of patients and controls should be larger. After 3 years of observation, the follow-up in 10 living GIAC patients showed nobody with thromboembolic disease.

Comparative proteome analysis of acute myeloid leukemia with and without maturation.

Acute myeloid leukemia (AML) is a severe, rapidly progressing disease triggered by blocking granulocyte or monocyte differentiation and maturation. Because of its heterogeneity, AML is divided into a number of subtypes. Unfortunately, so far very few correlations have been found between AML classification and its clinical course or patient response to treatment. In addition, as yet only a few subtype-specific AML biomarkers have been discovered. To solve these problems here, we focused on two AML subtypes M1 and M2 that are especially difficult to differentiate. Using 2D electrophoresis and mass spectrometry, we analyzed the protein profiles of peripheral blood (PB) and/or bone marrow (BM) samples collected from 38 AML-M1/M2 patients and 17 healthy volunteers. Comparative analysis of AML-M1/M2 and control PB/BM cells revealed 25 proteins that accumulated differentially. Hierarchical clustering of proteomic results clearly divided the AML samples into 2 groups (M1 and M2). Annexin III, L-plastin and 6-phosphogluconate dehydrogenase were found only in the M2 group. We also observed that the levels of annexin I and actin gamma 1 were correlated with resistance to treatment and the time of relapse. It appears that these five proteins can serve as potential AML biomarkers.

Comparative proteomics in acute myeloid leukemia

The term proteomics was used for the first time in 1995 to describe large-scale protein analyses. At the same time proteomics was distinguished as a new domain of the life sciences. The major object of proteomic studies is the proteome, i.e. the set of all proteins accumulating in a given cell, tissue or organ. During the last years several new methods and techniques have been developed to increase the fidelity and efficacy of proteomic analyses. The most widely used are two-dimensional electrophoresis (2DE) and mass spectrometry (MS). In the past decade proteomic analyses have also been successfully applied in biomedical research. They allow one to determine how various diseases affect the pattern of protein accumulation. In this paper, we attempt to summarize the results of the proteomic analyses of acute myeloid leukemia (AML) cells. They have increased our knowledge on the mechanisms underlying AML development and contributed to progress in AML diagnostics and treatment.

Gene expression profiling of acute myeloid leukemia samples from adult patients with AML-M1 and -M2 through boutique microarrays, real-time PCR and droplet digital PCR

Acute myeloid leukemia (AML) is the most common and severe form of acute leukemia diagnosed in adults. Owing to its heterogeneity, AML is divided into classes associated with different treatment outcomes and specific gene expression profiles. Based on previous studies on AML, in this study, we designed and generated an AML-array containing 900 oligonucleotide probes complementary to human genes implicated in hematopoietic cell differentiation and maturation, proliferation, apoptosis and leukemic transformation. The AML-array was used to hybridize 118 samples from 33 patients with AML of the M1 and M2 subtypes of the French-American-British (FAB) classification and 15 healthy volunteers (HV). Rigorous analysis of the microarray data revealed that 83 genes were differentially expressed between the patients with AML and the HV, including genes not yet discussed in the context of AML pathogenesis. The most overexpressed genes in AML were STMN1, KITLG, CDK6, MCM5, KRAS, CEBPA, MYC, ANGPT1, SRGN, RPLP0, ENO1 and SET, whereas the most underexpressed genes were IFITM1, LTB, FCN1, BIRC3, LYZ, ADD3, S100A9, FCER1G, PTRPE, CD74 and TMSB4X. The overexpression of the CPA3 gene was specific for AML with mutated NPM1 and FLT3. Although the microarray-based method was insufficient to differentiate between any other AML subgroups, quantitative PCR approaches enabled us to identify 3 genes (ANXA3, S100A9 and WT1) whose expression can be used to discriminate between the 2 studied AML FAB subtypes. The expression levels of the ANXA3 and S100A9 genes were increased, whereas those of WT1 were decreased in the AML-M2 compared to the AML-M1 group. We also examined the association between the STMN1, CAT and ABL1 genes, and the FLT3 and NPM1 mutation status. FLT3+/NPM1− AML was associated with the highest expression of STMN1, and ABL1 was upregulated in FLT3+ AML and CAT in FLT3− AML, irrespectively of the NPM1 mutation status. Moreover, our results indicated that CAT and WT1 gene expression levels correlated with the response to therapy. CAT expression was highest in patients who remained longer under complete remission, whereas WT1 expression increased with treatment resistance. On the whole, this study demonstrates that the AML-array can potentially serve as a first-line screening tool, and may be helpful for the diagnosis of AML, whereas the differentiation between AML subgroups can be more successfully performed with PCR-based analysis of a few marker genes.

Inhibitory effects of bortezomib on platelet aggregation in patients with multiple myeloma

INTRODUCTION Multiple myeloma (MM) therapy affects prothrombotic and anticoagulant processes. Patients receiving thalidomide, especially in combination with steroids, are at increased risk of venous thromboembolism (VTE), while the incidence of VTE on bortezomib is low. In vitro studies indicate that bortezomib causes a reduction in ADP-induced platelet aggregation. OBJECTIVES To analyse the influence of bortezomib on platelet aggregation induced by various agonists in patients with MM. PATIENTS AND METHODS A total of 30 patients (median age 57.5years) with relapsed/refractory MM receiving bortezomib-based regimens were analysed. Optical platelet aggregometry was performed with the agonists collagen, ADP and ristocetin and measured over two 21-day cycles. The results from two groups: those treated with bortezomib and thalidomide (BT group, n=11) and those without thalidomide (B group, n=19) were analysed. RESULTS During the second cycle, significantly decreased platelet aggregation was observed in the B group: 5μM ADP (p=0.0285, day 1 versus 8); 3.5μM ADP (p=0.0005, day 1 versus 8 and day 1 versus 11), collagen (p=0.0014, day 4 versus 8, day 4 versus 11), 1.25mg/ml ristocetin (p=0.0017, day 1 versus 8 and day 1 versus 11). Agonist-induced platelet aggregation tended to be reduced over time during the 1st cycle in group B. In the thalidomide group, significant platelet aggregation inhibition by collagen only was found. Transient reduction in platelet count was observed in all patients, but more prominently in group B. CONCLUSION The inhibitory effects of prolonged exposure of bortezomib on platelet aggregation were demonstrated in relapsed/refractory MM patients, but antithrombotic activity of bortezomib should be clarified in further prospective studies.

Second malignancies after autologous haematopoietic stem cell transplantation following modified BEAM conditioning regimen in patients with Hodgkin lymphoma - characteristics and risk factor analysis.

Aim of the study The aim of the study was to determine the incidence of second malignancies among patients with Hodgkin lymphoma (HL) treated with autologous haematopoietic stem cell transplantation (ASCT) following a modified BEAM (BCNU, etoposide, cytarabine, melphalan, dexamethasone) regimen between 1992 and 2012 at our department. We also intended to define the risk factors for the occurrence of second neoplasm after ASCT. Material and methods The long-term outcomes after transplant were evaluated in 170 patients, median age 31 years (range 17–61), who received a median of two pre-transplant chemotherapy lines (range 1–5). Results MOPP (mechlorethamine, vincristine, procarbazine, prednisone) or MOPP-type regimens were given to 12% of patients prior to ASCT. The median follow-up of the survivors was 73 (12–242) months. The 7-year overall survival and progression-free survival were 75% and 64%, respectively. Second malignancies occurred in 7 of the 170 patients, including 5 haematological malignancies, and 2 solid tumors. They developed at a median of 8 years (range 0.4–13.5) from ASCT. The 10-year and 15-year cumulative incidence of developing a second malignancy were 7% and 13%, respectively. In multivariate analysis, age ≥ 40 years at transplant (HR = 8.8; p = 0.008) and pre-transplant MOPP-type chemotherapy (HR = 5.6; p = 0.030) were the only factors significant for developing a second malignancy. Conclusions Our results indicate that age of patient and the type of pre-transplant chemotherapy contribute to the risk of the development of a second neoplasm after ASCT in patients with HL. We believe that better characterization of second malignancies and associated risk factors may be useful for clinicians who care for these patients.

Spontaneous hematological remission of acute myeloid leukemia

Spontaneous remission (SR) of acute myeloid leukemia (AML) in adults is observed very rarely. To date, about 100 cases have been presented in the literature. To our best knowledge, we describe the first adult Polish patient suffering from acute myelomonocytic leukemia (48, XY, +13, +21/46, XY), in whom after supportive therapy, including non-irradiated, non-leukocyte depleted red cell transfusions and low-dose corticosteroid, we observed resolution of the disease without cytogenetic remission. We suggest a potential transfusion-associated graft versus-host-diseases (TA-GVHD) and graft-versus leukemia (GVL) reaction which might lead to spontaneous hematological remission. However, we did not observe clinical symptoms of such reactions apart from a short episode of non-infectious diarrhea. Additionally, steroids were administered but their role in inducing SR, in our opinion, seems less probable. This 77-year-old man remained in SR for 7 months, when repeated analysis showed AML recurrence. He died due to septic shock 2.5 months later. Additionally, we present a review of the literature.

Analysis of boutique arrays: A universal method for the selection of the optimal data normalization procedure

DNA microarrays, which are among the most popular genomic tools, are widely applied in biology and medicine. Boutique arrays, which are small, spotted, dedicated microarrays, constitute an inexpensive alternative to whole-genome screening methods. The data extracted from each microarray-based experiment must be transformed and processed prior to further analysis to eliminate any technical bias. The normalization of the data is the most crucial step of microarray data pre-processing and this process must be carefully considered as it has a profound effect on the results of the analysis. Several normalization algorithms have been developed and implemented in data analysis software packages. However, most of these methods were designed for whole-genome analysis. In this study, we tested 13 normalization strategies (ten for double-channel data and three for single-channel data) available on R Bioconductor and compared their effectiveness in the normalization of four boutique array datasets. The results revealed that boutique arrays can be successfully normalized using standard methods, but not every method is suitable for each dataset. We also suggest a universal seven-step workflow that can be applied for the selection of the optimal normalization procedure for any boutique array dataset. The described workflow enables the evaluation of the investigated normalization methods based on the bias and variance values for the control probes, a differential expression analysis and a receiver operating characteristic curve analysis. The analysis of each component results in a separate ranking of the normalization methods. A combination of the ranks obtained from all the normalization procedures facilitates the selection of the most appropriate normalization method for the studied dataset and determines which methods can be used interchangeably.