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Hypomethylating agents decitabine and azacytidine are regarded as interchangeable in the treatment of acute myeloid leukemia (AML). However, their mechanisms of action remain incompletely understood, and predictive biomarkers for HMA efficacy are lacking. Here, we show that the bioactive metabolite decitabine triphosphate, but not azacytidine triphosphate, functions as activator and substrate of the triphosphohydrolase SAMHD1 and is subject to SAMHD1-mediated inactivation. Retrospective immunohistochemical analysis of bone marrow specimens from AML patients at diagnosis revealed that SAMHD1 expression in leukemic cells inversely correlates with clinical response to decitabine, but not to azacytidine. SAMHD1 ablation increases the antileukemic activity of decitabine in AML cell lines, primary leukemic blasts, and xenograft models. AML cells acquire resistance to decitabine partly by SAMHD1 up-regulation. Together, our data suggest that SAMHD1 is a biomarker for the stratified use of hypomethylating agents in AML patients and a potential target for the treatment of decitabine-resistant leukemia.
Background: Colorectal cancer (CRC) is a leading cause of cancer-related death worldwide. Growing evidence indicates that tumor-initiating cells (TICs) are responsible for tumor growth and progression. Conventional chemotherapeutics do not sufficiently eliminate TICs, leading to tumor relapse. We aimed to gain insight into TIC biology by comparing the transcriptome of primary TIC cultures and their normal stem cell counterparts to uncover expression differences.
Methods: We established colonosphere cultures derived from the resection of paired specimens of primary tumor and normal mucosa in patients with CRC. These colonospheres, enriched for TICs, were used for differential transcriptome analyses to detect new targets for a TIC-directed therapy. Effects of target inhibition on CRC cells were studied in vitro and in vivo.
Results: Pathway analysis of the regulated genes showed enrichment of genes central to PI3K/AKT and Wnt-signaling. We identified CD133 as a marker for a more aggressive CRC subpopulation enriched with TICs in SW480 CRC cells in an in vivo cancer model. Treatment of CRC cells with the selective AKT inhibitor MK-2206 caused a decrease in cell proliferation, particularly in the TIC fraction, resulting in a significant reduction of the stemness capacity to form colonospheres in vitro and to initiate tumor formation in vivo. Consequently, MK-2206 treatment of mice with established xenograft tumors exhibited a significant deceleration of tumor progression. Primary patient-derived tumorsphere growth was significantly inhibited by MK-2206.
Conclusion: This study reveals that AKT signaling is critical for TIC proliferation and can be efficiently targeted by MK-2206 representing a preclinical therapeutic strategy to repress colorectal TICs.
The optimal follow-up care for relapse detection in acute myeloid leukemia (AML) patients in first remission after consolidation therapy with intensive chemotherapy is not established. In this retrospective study, we evaluate the diagnostic value of an intensive relapse surveillance strategy by regular bone marrow aspirations (BMA) in these patients. We identified 86 patients with newly diagnosed non-promyelocytic AML who had reached complete remission (CR) after intensive induction and consolidation chemotherapy between 2007 and 2019. Annual relapse rates were 40%, 17%, and 2% in years 1–3, respectively. Patients in CR were surveilled by BMA scheduled every 3 months for 2 years, followed by BMA every 6 months. This surveillance regimen detected 29 of 55 relapses (53%), 11 of which were molecular relapses (20%). The remaining 26 of 55 relapses (47%) were diagnosed by non-surveillance BMA prompted by specific suspicion of relapse. Most patients showed concurrent morphological abnormalities in peripheral blood (PB) at time of relapse. Seven percent of all morphological relapses occurred without simultaneous PB abnormalities and would have been delayed without surveillance BMA. Intensified monthly PB assessment paired with BMA every 3 months during the first 2 years may be a highly sensitive relapse surveillance strategy.
Background and Objectives: Red blood cell (RBC) transfusions are needed by almost every acute myeloid leukaemia (AML) patient undergoing induction chemotherapy and constitute a cornerstone in supportive measures for cancer patients in general. Randomized controlled trials have shown non‐inferiority or even superiority of restrictive transfusion guidelines over liberal transfusion guidelines in specific clinical situations outside of medical oncology. In this study, we analysed whether more restrictive RBC transfusion reduces blood use without affecting hard outcomes.
Materials and Methods: A total of 352 AML patients diagnosed between 2007 and 2018 and undergoing intensive induction chemotherapy were included in this retrospective analysis. In the less restrictive transfusion group, patients received RBC transfusion for haemoglobin levels below 8 g/dl (2007–2014). In the restrictive transfusion group, patients received RBC transfusion for haemoglobin levels below 7 g/dl (2016–2018). Liberal transfusion triggers were never endorsed.
Results: A total of 268 (76·1%) and 84 (23·9%) AML patients fell into the less restrictive and restrictive transfusion groups, respectively. The less restrictive transfusion group had 1 g/dl higher mean haemoglobin levels, received their first RBC transfusions earlier and needed 1·5 more units of RBC during the hospital stay of induction chemotherapy. Febrile episodes, C‐reactive protein levels, admission to the intensive care unit, length of hospital stay as well as response and survival rates did not differ between the two cohorts.
Conclusion: From our retrospective analysis, we conclude that a more restrictive transfusion trigger does not affect important outcomes of AML patients. The opportunity to test possible effects of the more severe anaemia in the restrictive transfusion group on quality of life was missed.
Current metabolomics approaches utilize cellular metabolite extracts, are destructive, and require high cell numbers. We introduce here an approach that enables the monitoring of cellular metabolism at lower cell numbers by observing the consumption/production of different metabolites over several kinetic data points of up to 48 hours. Our approach does not influence cellular viability, as we optimized the cellular matrix in comparison to other materials used in a variety of in‐cell NMR spectroscopy experiments. We are able to monitor real‐time metabolism of primary patient cells, which are extremely sensitive to external stress. Measurements are set up in an interleaved manner with short acquisition times (approximately 7 minutes per sample), which allows the monitoring of up to 15 patient samples simultaneously. Further, we implemented our approach for performing tracer‐based assays. Our approach will be important not only in the metabolomics fields, but also in individualized diagnostics.
Current metabolomics approaches utilize cellular metabolite extracts, are destructive, and require high cell numbers. We introduce here an approach that enables the monitoring of cellular metabolism at lower cell numbers by observing the consumption/production of different metabolites over several kinetic data points of up to 48 hours. Our approach does not influence cellular viability, as we optimized the cellular matrix in comparison to other materials used in a variety of in‐cell NMR spectroscopy experiments. We are able to monitor real‐time metabolism of primary patient cells, which are extremely sensitive to external stress. Measurements are set up in an interleaved manner with short acquisition times (approximately 7 minutes per sample), which allows the monitoring of up to 15 patient samples simultaneously. Further, we implemented our approach for performing tracer‐based assays. Our approach will be important not only in the metabolomics fields, but also in individualized diagnostics.
In-depth analyses of cancer cell proteomes are needed to elucidate oncogenic pathomechanisms, as well as to identify potential drug targets and diagnostic biomarkers. However, methods for quantitative proteomic characterization of patient-derived tumors and in particular their cellular subpopulations are largely lacking. Here we describe an experimental set-up that allows quantitative analysis of proteomes of cancer cell subpopulations derived from either liquid or solid tumors. This is achieved by combining cellular enrichment strategies with quantitative Super-SILAC-based mass spectrometry followed by bioinformatic data analysis. To enrich specific cellular subsets, liquid tumors are first immunophenotyped by flow cytometry followed by FACS-sorting; for solid tumors, laser-capture microdissection is used to purify specific cellular subpopulations. In a second step, proteins are extracted from the purified cells and subsequently combined with a tumor-specific, SILAC-labeled spike-in standard that enables protein quantification. The resulting protein mixture is subjected to either gel electrophoresis or Filter Aided Sample Preparation (FASP) followed by tryptic digestion. Finally, tryptic peptides are analyzed using a hybrid quadrupole-orbitrap mass spectrometer, and the data obtained are processed with bioinformatic software suites including MaxQuant. By means of the workflow presented here, up to 8,000 proteins can be identified and quantified in patient-derived samples, and the resulting protein expression profiles can be compared among patients to identify diagnostic proteomic signatures or potential drug targets.
Malignant germ cell tumors (GCT) are the most common malignant tumors in young men between 18 and 40 years. The correct identification of histological subtypes, in difficult cases supported by immunohistochemistry, is essential for therapeutic management. Furthermore, biomarkers may help to understand pathophysiological processes in these tumor types. Two GCT cell lines, TCam-2 with seminoma-like characteristics, and NTERA-2, an embryonal carcinoma-like cell line, were compared by a quantitative proteomic approach using high-resolution mass spectrometry (MS) in combination with stable isotope labelling by amino acid in cell culture (SILAC). We were able to identify 4856 proteins and quantify the expression of 3936. 347 were significantly differentially expressed between the two cell lines. For further validation, CD81, CBX-3, PHF6, and ENSA were analyzed by western blot analysis. The results confirmed the MS results. Immunohistochemical analysis on 59 formalin-fixed and paraffin-embedded (FFPE) normal and GCT tissue samples (normal testis, GCNIS, seminomas, and embryonal carcinomas) of these proteins demonstrated the ability to distinguish different GCT subtypes, especially seminomas and embryonal carcinomas. In addition, siRNA-mediated knockdown of these proteins resulted in an antiproliferative effect in TCam-2, NTERA-2, and an additional embryonal carcinoma-like cell line, NCCIT. In summary, this study represents a proteomic resource for the discrimination of malignant germ cell tumor subtypes and the observed antiproliferative effect after knockdown of selected proteins paves the way for the identification of new potential drug targets.
Bloodstream infections (BSI) are a frequent complication in patients with hematological and oncological diseases. However, the impact of different bacterial species causing BSI and of multiple BSI remains incompletely understood. We performed a retrospective study profiling 637 bacterial BSI episodes in hematological and oncological patients. Based on the 30-day (30d) overall survival (OS), we analyzed different types of multiple BSI and grouped BSI-associated bacteria into clusters followed by further assessment of clinical and infection-related characteristics. We discovered that polymicrobial BSI (different organisms on the first day of a BSI episode) and sequential BSI (another BSI before the respective BSI episode) were associated with a worse 30d OS. Different bacterial groups could be classified into three BSI outcome clusters based on 30d OS: favorable (FAV) including mainly common skin contaminants, Escherichia spp. and Streptococcus spp.; intermediate (INT) including mainly Enterococcus spp., vancomycin-resistant Enterococcus spp., and multidrug-resistant gram-negative bacteria (MDRGN); and adverse (ADV) including MDRGN with an additional carbapenem-resistance (MDRGN+CR). A polymicrobial or sequential BSI especially influenced the outcome in the combination of two INT cluster BSI. The presence of a polymicrobial BSI and the assignment into the BSI outcome clusters were identified as independent risk factors for 30d mortality in a Cox multivariate regression analysis. The assignment to a BSI outcome cluster and the differentiated perspective of multiple BSI open new insights into the prognosis of patients with BSI and should be further validated in other patient cohorts.