Ganglioside SSEA-4 in Ewing sarcoma marks a tumor cell population with aggressive features and is a potential cell-surface immune target.

Carbohydrate markers of immature cells during prenatal human development can be aberrantly expressed in cancers and deserve evaluation as immune targets. A candidate target in Ewing sarcoma is the globo-series ganglioside stage-specific embryonic antigen-4 (SSEA-4). We detected SSEA-4 expression on the cell surface of all of 14 EwS cell lines and in 21 of 31 (68%) primary EwS tumor biopsies. Among paired subpopulations of tumor cells with low versus high SSEA-4 expression, SSEA-4high expression was significantly and consistently associated with functional characteristics of tumor aggressiveness, including higher cell proliferation, colony formation, chemoresistance and propensity to migrate. SSEA-4low versus SSEA-4high expression was not related to expression levels of the EWSR1-FLI1 fusion transcript or markers of epithelial/mesenchymal plasticity. SSEA-4low cells selected from bulk populations regained higher SSEA-4 expression in vitro and during in vivo tumor growth in a murine xenograft model. T cells engineered to express SSEA-4-specific chimeric antigen receptors (CARs) specifically interacted with SSEA-4 positive EwS cells and exerted effective antigen-specific tumor cell lysis in vitro. In conclusion, with its stable expression and functional significance in EwS, SSEA-4 is an attractive therapeutic immune target in this cancer that deserves further evaluation for clinical translation.

Preclinical Development of CAR T Cells with Antigen-Inducible IL18 Enforcement to Treat GD2-Positive Solid Cancers.

PURPOSE: Cytokine-engineering of chimeric antigen receptor-redirected T cells (CAR T cells) is a promising principle to overcome the limited activity of canonical CAR T cells against solid cancers. EXPERIMENTAL DESIGN: We developed an investigational medicinal product, GD2IL18CART, consisting of CAR T cells directed against ganglioside GD2 with CAR-inducible IL18 to enhance their activation response and cytolytic effector functions in the tumor microenvironment. To allow stratification of patients according to tumor GD2 expression, we established and validated immunofluorescence detection of GD2 on paraffin-embedded tumor tissues. RESULTS: Lentiviral all-in-one vector engineering of human T cells with the GD2-specific CAR with and without inducible IL18 resulted in cell products with comparable proportions of CAR-expressing central memory T cells. Production of IL18 strictly depends on GD2 antigen engagement. GD2IL18CART respond to interaction with GD2-positive tumor cells with higher IFNγ and TNFα cytokine release and more effective target cytolysis compared with CAR T cells without inducible IL18. GD2IL18CART further have superior in vivo antitumor activity, with eradication of GD2-positive tumor xenografts. Finally, we established GMP-compliant manufacturing of GD2IL18CART and found it to be feasible and efficient at clinical scale. CONCLUSIONS: These results pave the way for clinical investigation of GD2IL18CART in pediatric and adult patients with neuroblastoma and other GD2-positive cancers (EU CT 2022-501725-21-00).

Thrombopoietin levels in sepsis and septic shock - a systematic review and meta-analysis.

OBJECTIVES: Sepsis is a life-threatening condition implicating an inadequate activation of the immune system. Platelets act as modulators and contributors to immune processes. Indeed, altered platelet turnover, thrombotic events, and changes in thrombopoietin levels in systemic inflammation have been reported, but thrombopoietin-levels in sepsis and septic-shock have not yet been systematically evaluated. We therefore performed a meta-analysis of thrombopoietin (TPO)-levels in patients with sepsis. METHODS: Two independent reviewers screened records and full-text articles for inclusion. Scientific databases were searched for studies examining thrombopoietin levels in adult sepsis and septic-shock patients until August 1st 2022. RESULTS: Of 95 items screened, six studies met the inclusion criteria, including 598 subjects. Both sepsis and severe sepsis were associated with increased levels of thrombopoietin (sepsis vs. control: standardized mean difference 3.06, 95 % CI 1.35-4.77; Z=3.50, p=0.0005) (sepsis vs. severe sepsis: standardized mean difference -1.67, 95 % CI -2.46 to -0.88; Z=4.14, p<0.0001). TPO-levels did not show significant differences between severe sepsis and septic shock patients but differed between sepsis and inflammation-associated non-septic controls. Overall, high heterogeneity and low sample size could be noted. CONCLUSIONS: Concluding, increased levels of thrombopoietin appear to be present both in sepsis and severe sepsis with high heterogeneity but thrombopoietin does not allow to differentiate between severe sepsis and septic-shock. TPO may potentially serve to differentiate sepsis from non-septic trauma and/or tissue damage related (systemic) inflammation. Usage of different assays and high heterogeneity demand standardization of methods and further large multicenter trials.

Adjusting Acute Kidney Injury Kidney Disease: Improving Global Outcomes Urine Output Criterion for Predicted Body Weight Improves Prediction of Hospital Mortality.

BACKGROUND: Based on the Kidney Disease: Improving Global Outcomes (KDIGO) definitions, urine output, serum creatinine, and need for kidney replacement therapy are used for staging acute kidney injury (AKI). Currently, AKI staging correlates strongly with mortality and can be used as a predictive tool. However, factors associated with the development of AKI may affect its predictive ability. We tested whether adjustment for predicted (versus actual) body weight improved the ability of AKI staging to predict hospital mortality. METHODS: A total of 3279 patients who had undergone cardiac surgery in a university hospital were retrospectively analyzed. AKI was staged according to KDIGO criteria (standard staging) and after adjustment for hourly urine output adjusted by predicted body weight for each patient and each day of their hospital stay. RESULTS: The incidence of AKI (all stages) was 43% (predicted body weight adjusted) and 50% (standard staging), respectively ( P < .001). In sensitivity-specificity analyses for predicting hospital mortality, the area under the curve was significantly higher after adjustment for predicted body weight than with standard staging ( P = .002). CONCLUSIONS: Compared to standard staging, adjustment of urine output for predicted body weight increases the specificity and improves prediction of hospital mortality in patients undergoing cardiac surgery.

Sex-associated differences in frequencies and prognostic impact of recurrent genetic alterations in adult acute myeloid leukemia (Alliance, AMLCG).

Clinical outcome of patients with acute myeloid leukemia (AML) is associated with demographic and genetic features. Although the associations of acquired genetic alterations with patients' sex have been recently analyzed, their impact on outcome of female and male patients has not yet been comprehensively assessed. We performed mutational profiling, cytogenetic and outcome analyses in 1726 adults with AML (749 female and 977 male) treated on frontline Alliance for Clinical Trials in Oncology protocols. A validation cohort comprised 465 women and 489 men treated on frontline protocols of the German AML Cooperative Group. Compared with men, women more often had normal karyotype, FLT3-ITD, DNMT3A, NPM1 and WT1 mutations and less often complex karyotype, ASXL1, SRSF2, U2AF1, RUNX1, or KIT mutations. More women were in the 2022 European LeukemiaNet intermediate-risk group and more men in adverse-risk group. We found sex differences in co-occurring mutation patterns and prognostic impact of select genetic alterations. The mutation-associated splicing events and gene-expression profiles also differed between sexes. In patients aged <60 years, SF3B1 mutations were male-specific adverse outcome prognosticators. We conclude that sex differences in AML-associated genetic alterations and mutation-specific differential splicing events highlight the importance of patients' sex in analyses of AML biology and prognostication.

Diffusion-Weighted MRI for Treatment Response Assessment in Osteoblastic Metastases-A Repeatability Study.

The apparent diffusion coefficient (ADC) is a candidate marker of treatment response in osteoblastic metastases that are not evaluable by morphologic imaging. However, it is unclear whether the ADC meets the basic requirement for reliable treatment response evaluation, namely a low variance of repeated measurements in relation to the differences found between viable and nonviable metastases. The present study addresses this question by analyzing repeated in vivo ADCmedian measurements of 65 osteoblastic metastases in nine patients, as well as phantom measurements. PSMA-PET served as a surrogate for bone metastasis viability. Measures quantifying repeatability were calculated and differences in mean ADC values according to PSMA-PET status were examined. The relative repeatability coefficient %RC of ADCmedian measurements was 5.8% and 12.9% for phantom and in vivo measurements, respectively. ADCmedian values of bone metastases ranged from 595×10-6mm2/s to 2090×10-6mm2/s with an average of 63% higher values in nonviable metastases compared with viable metastases (p < 0.001). ADC shows a small repeatability coefficient in relation to the difference in ADC values between viable and nonviable metastases. Therefore, ADC measurements fulfill the technical prerequisite for reliable treatment response evaluation in osteoblastic metastases.

Which risk factors significantly influence the outcome of traumatic brain injured patients with alcohol use disorder?

PURPOSE: Every year, approximately 10 million people worldwide suffer a traumatic brain injury that leads to hospitalization or mortality. Chronic and acute alcohol intoxication increase the risk of developing traumatic brain injury. Alcohol use disorder (AUD) as a predictor of outcome in neurosurgical patients and the definition of risk factors have been sparsely addressed so far. This study aims to improve the understanding of the effects of alcohol use disorder in the context of neurosurgical therapy. METHODS: This study included patients admitted to Münster University Hospital with a traumatic brain injury and alcohol use disorder from January 1, 2010, to December 31, 2018. Univariate and multivariate analyses were performed to identify risk factors for a poorer outcome, assessed by the Glasgow Outcome Score. RESULTS: Of the 197 patients included, 156 (79%) were male, and 41 (21%) were female, with a median age of 49 years (IQR 38-58 years). In multivariate analyses, age (p < 0.001), the occurrence of a new neurologic deficit (p < 0.001), the development of hydrocephalus (p = 0.005), and CT-graphic midline shift due to intracerebral hemorrhage (p = 0.008) emerged as significant predictors of a worse outcome (GOS 1-3). In addition, the level of blood alcohol concentration correlated significantly with the occurrence of seizures (p = 0.009). CONCLUSIONS: Early identification of risk factors in patients with alcohol use disorder and traumatic brain injury is crucial to improve the outcome. In this regard, the occurrence of hydrocephalus or seizures during the inpatient stay should be considered as cause of neurological deterioration in this patient group.

Acute megakaryoblastic leukaemia shows high frequency of chromosome 1q aberrations and dismal outcome.

Acute megakaryoblastic leukaemia (AMKL) is associated with poor prognosis. Limited information is available on its cytogenetics, molecular genetics and clinical outcome. We performed genetic analyses, evaluated prognostic factors and the value of allogeneic haematopoietic stem cell transplantation (allo-HSCT) in a homogenous adult AMKL patient cohort. We retrospectively analysed 38 adult patients with AMKL (median age: 58 years, range: 21-80). Most received intensive treatment in AML Cooperative Group (AMLCG) trials between 2001 and 2016. Cytogenetic data showed an accumulation of adverse risk markers according to ELN 2017 and an unexpected high frequency of structural aberrations on chromosome arm 1q (33%). Most frequently, mutations occurred in TET2 (23%), TP53 (23%), JAK2 (19%), PTPN11 (19%) and RUNX1 (15%). Complete remission rate in 33 patients receiving intensive chemotherapy was 33% and median overall survival (OS) was 33 weeks (95% CI: 21-45). Patients undergoing allo-HSCT (n = 14) had a superior median OS (68 weeks; 95% CI: 11-126) and relapse-free survival (RFS) of 27 weeks (95% CI: 4-50), although cumulative incidence of relapse after allo-HSCT was high (62%). The prognosis of AMKL is determined by adverse genetic risk factors and therapy resistance. So far allo-HSCT is the only potentially curative treatment option in this dismal AML subgroup.

CAR T cells as micropharmacies against solid cancers: Combining effector T-cell mediated cell death with vascular targeting in a one-step engineering process.

To enhance the potency of chimeric antigen receptor (CAR) engineered T cells in solid cancers, we designed a novel cell-based combination strategy with an additional therapeutic mode of action. CAR T cells are used as micropharmacies to produce a targeted pro-coagulatory fusion protein, truncated tissue factor (tTF)-NGR, which exerts pro-coagulatory activity and hypoxia upon relocalization to the vascular endothelial cells that invade tumor tissues. Delivery by CAR T cells aimed to induce locoregional tumor vascular infarction for combined immune-mediated and hypoxic tumor cell death. Human T cells that were one-vector gene-modified to express a GD2-specific CAR along with CAR-inducible tTF-NGR exerted potent GD2-specific effector functions while secreting tTF-NGR that activates the extrinsic coagulation pathway in a strictly GD2-dependent manner. In murine models, the CAR T cells infiltrated GD2-positive tumor xenografts, secreted tTF-NGR into the tumor microenvironment and showed a trend towards superior therapeutic activity compared with control cells producing functionally inactive tTF-NGR. In vitro evidence supports a mechanism of hypoxia-mediated enhancement of T cell cytolytic activity. We conclude that combined CAR T cell targeting with an additional mechanism of antitumor action in a one-vector engineering strategy is a promising approach to be further developed for targeted treatment of solid cancers.

Radiomics of Tumor Heterogeneity in 18F-FDG-PET-CT for Predicting Response to Immune Checkpoint Inhibition in Therapy-Naïve Patients with Advanced Non-Small-Cell Lung Cancer.

We aimed to evaluate the predictive and prognostic value of baseline 18F-FDG-PET-CT (PET-CT) radiomic features (RFs) for immune checkpoint-inhibitor (CKI)-based first-line therapy in advanced non-small-cell lung cancer (NSCLC) patients. In this retrospective study 44 patients were included. Patients were treated with either CKI-monotherapy or combined CKI-based immunotherapy-chemotherapy as first-line treatment. Treatment response was assessed by the Response Evaluation Criteria in Solid Tumors (RECIST). After a median follow-up of 6.4 months patients were stratified into "responder" (n = 33) and "non-responder" (n = 11). RFs were extracted from baseline PET and CT data after segmenting PET-positive tumor volume of all lesions. A Radiomics-based model was developed based on a Radiomics signature consisting of reliable RFs that allow classification of response and overall progression using multivariate logistic regression. These RF were additionally tested for their prognostic value in all patients by applying a model-derived threshold. Two independent PET-based RFs differentiated well between responders and non-responders. For predicting response, the area under the curve (AUC) was 0.69 for "PET-Skewness" and 0.75 predicting overall progression for "PET-Median". In terms of progression-free survival analysis, patients with a lower value of PET-Skewness (threshold < 0.2014; hazard ratio (HR) 0.17, 95% CI 0.06-0.46; p < 0.001) and higher value of PET-Median (threshold > 0.5233; HR 0.23, 95% CI 0.11-0.49; p < 0.001) had a significantly lower probability of disease progression or death. Our Radiomics-based model might be able to predict response in advanced NSCLC patients treated with CKI-based first-line therapy.

Unsupervised meta-clustering identifies risk clusters in acute myeloid leukemia based on clinical and genetic profiles.

BACKGROUND: Increasingly large and complex biomedical data sets challenge conventional hypothesis-driven analytical approaches, however, data-driven unsupervised learning can detect inherent patterns in such data sets. METHODS: While unsupervised analysis in the medical literature commonly only utilizes a single clustering algorithm for a given data set, we developed a large-scale model with 605 different combinations of target dimensionalities as well as transformation and clustering algorithms and subsequent meta-clustering of individual results. With this model, we investigated a large cohort of 1383 patients from 59 centers in Germany with newly diagnosed acute myeloid leukemia for whom 212 clinical, laboratory, cytogenetic and molecular genetic parameters were available. RESULTS: Unsupervised learning identifies four distinct patient clusters, and statistical analysis shows significant differences in rate of complete remissions, event-free, relapse-free and overall survival between the four clusters. In comparison to the standard-of-care hypothesis-driven European Leukemia Net (ELN2017) risk stratification model, we find all three ELN2017 risk categories being represented in all four clusters in varying proportions indicating unappreciated complexity of AML biology in current established risk stratification models. Further, by using assigned clusters as labels we subsequently train a supervised model to validate cluster assignments on a large external multicenter cohort of 664 intensively treated AML patients. CONCLUSIONS: Dynamic data-driven models are likely more suitable for risk stratification in the context of increasingly complex medical data than rigid hypothesis-driven models to allow for a more personalized treatment allocation and gain novel insights into disease biology.

There are various ways in which clinicians can predict the risk of disease progression in patients with leukemia, helping them to treat the patients accordingly. However, these approaches are usually designed by human experts and might not fully capture the complexity of a patient's disease. Here, with a large cohort of patients with acute myeloid leukemia, we design an unsupervised machine learning model ­ a type of computer model that learns from patterns in data without human input­to separate these patients into subgroups according to risk. We identify four distinct groups which differ with regards to patient genetics, laboratory values, and clinical characteristics. These groups have differences in response to treatment and patient survival, and we validate our findings in another dataset. Our approach might help clinicians to better predict outcomes in patients with leukemia and make decisions on treatment.

Validation and refinement of the 2022 European LeukemiaNet genetic risk stratification of acute myeloid leukemia.

The revised 2022 European LeukemiaNet (ELN) AML risk stratification system requires validation in large, homogeneously treated cohorts. We studied 1118 newly diagnosed AML patients (median age, 58 years; range, 18-86 years) who received cytarabine-based induction chemotherapy between 1999 and 2012 and compared ELN-2022 to the previous ELN-2017 risk classification. Key findings were validated in a cohort of 1160 mostly younger patients. ELN-2022 reclassified 15% of patients, 3% into more favorable, and 12% into more adverse risk groups. This was mainly driven by patients reclassified from intermediate- to adverse-risk based on additional myelodysplasia-related mutations being included as adverse-risk markers. These patients (n = 79) had significantly better outcomes than patients with other adverse-risk genotypes (5-year OS, 26% vs. 12%) and resembled the remaining intermediate-risk group. Overall, time-dependent ROC curves and Harrel's C-index controlling for age, sex, and AML type (de novo vs. sAML/tAML) show slightly worse prognostic discrimination of ELN-2022 compared to ELN-2017 for OS. Further refinement of ELN-2022 without including additional genetic markers is possible, in particular by recognizing TP53-mutated patients with complex karyotypes as "very adverse". In summary, the ELN-2022 risk classification identifies a larger group of adverse-risk patients at the cost of slightly reduced prognostic accuracy compared to ELN-2017.

Behavioral Voluntary and Social Bioassays Enabling Identification of Complex and Sex-Dependent Pain-(-Related) Phenotypes in Rats with Bone Cancer.

Cancer-induced bone pain (CIBP) is a common and devastating symptom with limited treatment options in patients, significantly affecting their quality of life. The use of rodent models is the most common approach to uncovering the mechanisms underlying CIBP; however, the translation of results to the clinic may be hindered because the assessment of pain-related behavior is often based exclusively on reflexive-based methods, which are only partially indicative of relevant pain in patients. To improve the accuracy and strength of the preclinical, experimental model of CIBP in rodents, we used a battery of multimodal behavioral tests that were also aimed at identifying rodent-specific behavioral components by using a home-cage monitoring assay (HCM). Rats of all sexes received an injection with either heat-deactivated (sham-group) or potent mammary gland carcinoma Walker 256 cells into the tibia. By integrating multimodal datasets, we assessed pain-related behavioral trajectories of the CIBP-phenotype, including evoked and non-evoked based assays and HCM. Using principal component analysis (PCA), we discovered sex-specific differences in establishing the CIBP-phenotype, which occurred earlier (and differently) in males. Additionally, HCM phenotyping revealed the occurrence of sensory-affective states manifested by mechanical hypersensitivity in sham when housed with a tumor-bearing cagemate (CIBP) of the same sex. This multimodal battery allows for an in-depth characterization of the CIBP-phenotype under social aspects in rats. The detailed, sex-specific, and rat-specific social phenotyping of CIBP enabled by PCA provides the basis for mechanism-driven studies to ensure robustness and generalizability of results and provide information for targeted drug development in the future.

Prediction of complete remission and survival in acute myeloid leukemia using supervised machine learning.

Achievement of complete remission signifies a crucial milestone in the therapy of acute myeloid leukemia (AML) while refractory disease is associated with dismal outcomes. Hence, accurately identifying patients at risk is essential to tailor treatment concepts individually to disease biology. We used nine machine learning (ML) models to predict complete remission and 2-year overall survival in a large multicenter cohort of 1,383 AML patients who received intensive induction therapy. Clinical, laboratory, cytogenetic and molecular genetic data were incorporated and our results were validated on an external multicenter cohort. Our ML models autonomously selected predictive features including established markers of favorable or adverse risk as well as identifying markers of so-far controversial relevance. De novo AML, extramedullary AML, double-mutated CEBPA, mutations of CEBPA-bZIP, NPM1, FLT3-ITD, ASXL1, RUNX1, SF3B1, IKZF1, TP53, and U2AF1, t(8;21), inv(16)/t(16;16), del(5)/del(5q), del(17)/del(17p), normal or complex karyotypes, age and hemoglobin concentration at initial diagnosis were statistically significant markers predictive of complete remission, while t(8;21), del(5)/del(5q), inv(16)/t(16;16), del(17)/del(17p), double-mutated CEBPA, CEBPA-bZIP, NPM1, FLT3-ITD, DNMT3A, SF3B1, U2AF1, and TP53 mutations, age, white blood cell count, peripheral blast count, serum lactate dehydrogenase level and hemoglobin concentration at initial diagnosis as well as extramedullary manifestations were predictive for 2-year overall survival. For prediction of complete remission and 2-year overall survival areas under the receiver operating characteristic curves ranged between 0.77-0.86 and between 0.63-0.74, respectively in our test set, and between 0.71-0.80 and 0.65-0.75 in the external validation cohort. We demonstrated the feasibility of ML for risk stratification in AML as a model disease for hematologic neoplasms, using a scalable and reusable ML framework. Our study illustrates the clinical applicability of ML as a decision support system in hematology.

Virtual reality reduces pain in palliative care-A feasibility trial.

BACKGROUND: Effective symptom control is a stated goal of palliative care (PC) to improve quality of life for terminally ill patients. Virtual reality (VR) provides temporary escapes from pharmacologically resistant pain and allows for experiences and journeys patients may not access in any other way. Enabling wishes through virtual worlds may also offer additional benefits such as controlling psychological and physical symptoms. AIMS: We investigated the feasibility of a single VR experience as a viable, satisfying, and effective tool for end-of-life pain relief for inpatients presenting palliative needs. DESIGN: This is an observational, single-arm and national single-center feasibility trial. METHODS: A one-time VR experience with a selection of several videos and games was offered to 45 inpatients receiving PC at Muenster University Hospital. Patients with brain tumors, brain metastases, seizures, motion sickness, claustrophobia, vertigo, hearing or visual impairment, or unable to consent were excluded. Primary outcome measured patient reported pain on a visual analogue scale (VAS). We also measured Karnofsky performance status, health-related quality of life (HRQOL) using the EQ-5D-5 L questionnaire, and the Pain Out Questionnaire for postoperative pain. RESULTS: We analyzed data from 21 women (52.5%) and 19 men (47.5%) at an average age of 51.9 (SD: 15.81) years. The mean Karnofsky score among the sample was 45.5 (SD: 14.97) and the HRQOL was 41.9 (SD: 23.08). While no serious side effects were reported during the intervention, three patients experienced nausea (7%), two headaches (5%), and three reported dry eyes (7%) afterwards. Significant pain reduction (baseline VAS 2.25 (SD: 0.4399)) was demonstrated during (VAS 0.7 (SD: 0.2983, p < 0.0001)), immediately after (VAS 0.9 (SD: 0.3354, p = 0.0001)) and one hour after the intervention (VAS 1.15 (SD: 0.4163, p = 0.0004)). More than 80% rated the VR experience as very good or good (85%, n = 34) and intended to make use of the device again (82.5%, n = 33). However, two participants (5%) also expressed sadness by becoming aware of old memories and previous opportunities that are gone. DISCUSSION: The present pilot study suggests that VR seems to be a feasible and effective tool for pain relief in PC. Its use encompasses the approach of a total pain and symptom therapy and enhances patients' dignity and autonomy. Future research ought to include if and to what extent VR could reduce the necessity of pharmacological pain relief.

Molecular profiling of patients with cytogenetically normal acute myeloid leukemia and hyperleukocytosis.

BACKGROUND: Acute myeloid leukemia (AML) with initial hyperleukocytosis is associated with high early mortality and a poor prognosis. The aims of this study were to delineate the underlying molecular landscape in the largest cytogenetic risk group, cytogenetically normal acute myeloid leukemia (CN-AML), and to assess the prognostic relevance of recurrent mutations in the context of hyperleukocytosis and clinical risk factors. METHODS: The authors performed a targeted sequencing of 49 recurrently mutated genes in 56 patients with newly diagnosed CN-AML and initial hyperleukocytosis of ≥100 G/L treated in the AMLCG99 study. The median number of mutated genes per patient was 5. The most common mutations occurred in FLT3 (73%), NPM1 (75%), and TET2 (45%). RESULTS: The predominant pathways affected by mutations were signaling (84% of patients), epigenetic modifiers (75% of patients), and nuclear transport (NPM1; 75%) of patients. AML with hyperleukocytosis was enriched for molecular subtypes that negatively affected the prognosis, including a high percentage of patients presenting with co-occurring mutations in signaling and epigenetic modifiers such as FLT3 internal tandem duplications and TET2 mutations. CONCLUSIONS: Despite these unique molecular features, clinical risk factors, including high white blood count, hemoglobin level, and lactate dehydrogenase level at baseline, remained the predictors for overall survival and relapse-free survival in hyperleukocytotic CN-AML.

Impact of IDH1 and IDH2 mutational subgroups in AML patients after allogeneic stem cell transplantation.

BACKGROUND: The role of allogeneic hematopoietic cell transplantation (alloHCT) in acute myeloid leukemia (AML) with mutated IDH1/2 has not been defined. Therefore, we analyzed a large cohort of 3234 AML patients in first complete remission (CR1) undergoing alloHCT or conventional chemo-consolidation and investigated outcome in respect to IDH1/2 mutational subgroups (IDH1 R132C, R132H and IDH2 R140Q, R172K). METHODS: Genomic DNA was extracted from bone marrow or peripheral blood samples at diagnosis and analyzed for IDH mutations with denaturing high-performance liquid chromatography, Sanger sequencing and targeted myeloid panel next-generation sequencing, respectively. Statistical as-treated analyses were performed using R and standard statistical methods (Kruskal-Wallis test for continuous variables, Chi-square test for categorical variables, Cox regression for univariate and multivariable models), incorporating alloHCT as a time-dependent covariate. RESULTS: Among 3234 patients achieving CR1, 7.8% harbored IDH1 mutations (36% R132C and 47% R132H) and 10.9% carried IDH2 mutations (77% R140Q and 19% R172K). 852 patients underwent alloHCT in CR1. Within the alloHCT group, 6.2% had an IDH1 mutation (43.4% R132C and 41.4% R132H) and 10% were characterized by an IDH2 mutation (71.8% R140Q and 24.7% R172K). Variants IDH1 R132C and IDH2 R172K showed a significant benefit from alloHCT for OS (p = .017 and p = .049) and RFS (HR = 0.42, p = .048 and p = .009) compared with chemotherapy only. AlloHCT in IDH2 R140Q mutated AML resulted in longer RFS (HR = 0.4, p = .002). CONCLUSION: In this large as-treated analysis, we showed that alloHCT is able to overcome the negative prognostic impact of certain IDH mutational subclasses in first-line consolidation treatment and could pending prognostic validation, provide prognostic value for AML risk stratification and therapeutic decision making.