Identifying long-term survivors and those at higher or lower risk of relapse among patients with cytogenetically normal acute myeloid leukemia using a high-dimensional mixture cure model.

Patients with cytogenetically normal acute myeloid leukemia (CN-AML) may harbor prognostically relevant gene mutations and thus be categorized into one of the three 2022 European LeukemiaNet (ELN) genetic-risk groups. Nevertheless, there remains heterogeneity with respect to relapse-free survival (RFS) within these genetic-risk groups. Our training set included 306 adults on Alliance for Clinical Trials in Oncology studies with de novo CN-AML aged < 60 years who achieved a complete remission and for whom centrally reviewed cytogenetics, RNA-sequencing, and gene mutation data from diagnostic samples were available (Alliance trial A152010). To overcome deficiencies of the Cox proportional hazards model when long-term survivors are present, we developed a penalized semi-parametric mixture cure model (MCM) to predict RFS where RNA-sequencing data comprised the predictor space. To validate model performance, we employed an independent test set from the German Acute Myeloid Leukemia Cooperative Group (AMLCG) consisting of 40 de novo CN-AML patients aged < 60 years who achieved a complete remission and had RNA-sequencing of their pre-treatment sample. For the training set, there was a significant non-zero cure fraction (p = 0.019) with 28.5% of patients estimated to be cured. Our MCM included 112 genes associated with cure, or long-term RFS, and 87 genes associated with latency, or shorter-term time-to-relapse. The area under the curve and C-statistic were respectively, 0.947 and 0.783 for our training set and 0.837 and 0.718 for our test set. We identified a novel, prognostically relevant molecular signature in CN-AML, which allows identification of patient subgroups independent of 2022 ELN genetic-risk groups.Trial registration Data from companion studies CALGB 8461, 9665 and 20202 (trials registered at www.clinicaltrials.gov as, respectively, NCT00048958, NCT00899223, and NCT00900224) were obtained from Alliance for Clinical Trials in Oncology under data sharing study A152010. Data from the AMLCG 2008 trial was registered at www.clinicaltrials.gov as NCT01382147.

Identification of a gene expression signature associated with brain metastasis in colorectal cancer.

PURPOSE: Brain metastasis (BM) in colorectal cancer (CRC) is a rare event with poor prognosis. Apart from (K)RAS status and lung and bone metastasis no biomarkers exist to identify patients at risk. This study aimed to identify a gene expression signature associated with colorectal BM. METHODS: Three patient groups were formed: 1. CRC with brain metastasis (BRA), 2. exclusive liver metastasis (HEP) and, 3. non-metastatic disease (M0). RNA was extracted from primary tumors and mRNA expression was measured using a NanoString Panel (770 genes). Expression was confirmed by qPCR in a validation cohort. Statistical analyses including multivariate logistic regression followed by receiver operating characteristic (ROC) analysis were performed. RESULTS: EMILIN3, MTA1, SV2B, TMPRSS6, ACVR1C, NFAT5 and SMC3 were differentially expressed in BRA and HEP/M0 groups. In the validation cohort, differential NFAT5, ACVR1C and SMC3 expressions were confirmed. BRA patients showed highest NFAT5 levels compared to HEP/M0 groups (global p = 0.02). High ACVR1C expression was observed more frequently in the BRA group (42.9%) than in HEP (0%) and M0 (7.1%) groups (global p = 0.01). High SMC3 expressions were only detectable in the BRA group (global p = 0.003). Only patients with BM showed a combined high expression of NFAT5, ACVR1C or SMC3 as well as of all three genes. ROC analysis revealed a good prediction of brain metastasis by the three genes (area under the curve (AUC) = 0.78). CONCLUSIONS: The NFAT5, ACVR1C and SMC3 gene expression signature is associated with colorectal BM. Future studies should further investigate the importance of this biomarker signature.

Prognostic impact of CEBPA mutational subgroups in adult AML.

Despite recent refinements in the diagnostic and prognostic assessment of CEBPA mutations in AML, several questions remain open, i.e. implications of different types of basic region leucin zipper (bZIP) mutations, the role of co-mutations and the allelic state. Using pooled primary data analysis on 1010 CEBPA-mutant adult AML patients, a comparison was performed taking into account the type of mutation (bZIP: either typical in-frame insertion/deletion (InDel) mutations (bZIPInDel), frameshift InDel or nonsense mutations inducing translational stop (bZIPSTOP) or single base-pair missense alterations (bZIPms), and transcription activation domain (TAD) mutations) and the allelic state (single (smCEBPA) vs. double mutant (dmCEBPA)). Only bZIPInDel patients had significantly higher rates of complete remission and longer relapse free and overall survival (OS) compared with all other CEBPA-mutant subgroups. Moreover, co-mutations in bZIPInDel patients (e.g. GATA2, FLT3, WT1 as well as ELN2022 adverse risk aberrations) had no independent impact on OS, whereas in non-bZIPInDel patients, grouping according to ELN2022 recommendations added significant prognostic information. In conclusion, these results demonstrate bZIPInDel mutations to be the major independent determinant of outcome in CEBPA-mutant AML, thereby refining current classifications according to WHO (including all dmCEBPA and smCEBPA bZIP) as well as ELN2022 and ICC recommendations (including CEBPA bZIPms).

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.

CSF3R T618I Collaborates With RUNX1-RUNX1T1 to Expand Hematopoietic Progenitors and Sensitizes to GLI Inhibition.

Activating colony-stimulating factor-3 receptor gene (CSF3R) mutations are recurrent in acute myeloid leukemia (AML) with t(8;21) translocation. However, the nature of oncogenic collaboration between alterations of CSF3R and the t(8;21) associated RUNX1-RUNX1T1 fusion remains unclear. In CD34+ hematopoietic stem and progenitor cells from healthy donors, double oncogene expression led to a clonal advantage, increased self-renewal potential, and blast-like morphology and distinct immunophenotype. Gene expression profiling revealed hedgehog signaling as a potential mechanism, with upregulation of GLI2 constituting a putative pharmacological target. Both primary hematopoietic cells and the t(8;21) positive AML cell line SKNO-1 showed increased sensitivity to the GLI inhibitor GANT61 when expressing CSF3R T618I. Our findings suggest that during leukemogenesis, the RUNX1-RUNXT1 fusion and CSF3R mutation act in a synergistic manner to alter hedgehog signaling, which can be exploited therapeutically.

The evolving landscape of COVID-19 and post-COVID condition in patients with chronic lymphocytic leukemia: A study by ERIC, the European research initiative on CLL.

In this retrospective international multicenter study, we describe the clinical characteristics and outcomes of patients with chronic lymphocytic leukemia (CLL) and related disorders (small lymphocytic lymphoma and high-count monoclonal B lymphocytosis) infected by SARS-CoV-2, including the development of post-COVID condition. Data from 1540 patients with CLL infected by SARS-CoV-2 from January 2020 to May 2022 were included in the analysis and assigned to four phases based on cases disposition and SARS-CoV-2 variants emergence. Post-COVID condition was defined according to the WHO criteria. Patients infected during the most recent phases of the pandemic, though carrying a higher comorbidity burden, were less often hospitalized, rarely needed intensive care unit admission, or died compared to patients infected during the initial phases. The 4-month overall survival (OS) improved through the phases, from 68% to 83%, p = .0015. Age, comorbidity, CLL-directed treatment, but not vaccination status, emerged as risk factors for mortality. Among survivors, 6.65% patients had a reinfection, usually milder than the initial one, and 16.5% developed post-COVID condition. The latter was characterized by fatigue, dyspnea, lasting cough, and impaired concentration. Infection severity was the only risk factor for developing post-COVID. The median time to resolution of the post-COVID condition was 4.7 months. OS in patients with CLL improved during the different phases of the pandemic, likely due to the improvement of prophylactic and therapeutic measures against SARS-CoV-2 as well as the emergence of milder variants. However, mortality remained relevant and a significant number of patients developed post-COVID conditions, warranting further investigations.

Combined proteomics and CRISPR‒Cas9 screens in PDX identify ADAM10 as essential for leukemia in vivo.

BACKGROUND: Acute leukemias represent deadly malignancies that require better treatment. As a challenge, treatment is counteracted by a microenvironment protecting dormant leukemia stem cells. METHODS: To identify responsible surface proteins, we performed deep proteome profiling on minute numbers of dormant patient-derived xenograft (PDX) leukemia stem cells isolated from mice. Candidates were functionally screened by establishing a comprehensive CRISPR‒Cas9 pipeline in PDX models in vivo. RESULTS: A disintegrin and metalloproteinase domain-containing protein 10 (ADAM10) was identified as an essential vulnerability required for the survival and growth of different types of acute leukemias in vivo, and reconstitution assays in PDX models confirmed the relevance of its sheddase activity. Of translational importance, molecular or pharmacological targeting of ADAM10 reduced PDX leukemia burden, cell homing to the murine bone marrow and stem cell frequency, and increased leukemia response to conventional chemotherapy in vivo. CONCLUSIONS: These findings identify ADAM10 as an attractive therapeutic target for the future treatment of acute leukemias.

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.

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.

Single-cell transcriptomic atlas-guided development of CAR-T cells for the treatment of acute myeloid leukemia.

Chimeric antigen receptor T cells (CAR-T cells) have emerged as a powerful treatment option for individuals with B cell malignancies but have yet to achieve success in treating acute myeloid leukemia (AML) due to a lack of safe targets. Here we leveraged an atlas of publicly available RNA-sequencing data of over 500,000 single cells from 15 individuals with AML and tissue from 9 healthy individuals for prediction of target antigens that are expressed on malignant cells but lacking on healthy cells, including T cells. Aided by this high-resolution, single-cell expression approach, we computationally identify colony-stimulating factor 1 receptor and cluster of differentiation 86 as targets for CAR-T cell therapy in AML. Functional validation of these established CAR-T cells shows robust in vitro and in vivo efficacy in cell line- and human-derived AML models with minimal off-target toxicity toward relevant healthy human tissues. This provides a strong rationale for further clinical development.

X-linked inhibitor of apoptosis protein represents a promising therapeutic target for relapsed/refractory ALL.

Acute lymphoblastic leukemia (ALL) represents the most frequent malignancy in children, and relapse/refractory (r/r) disease is difficult to treat, both in children and adults. In search for novel treatment options against r/r ALL, we studied inhibitor of apoptosis proteins (IAP) and Smac mimetics (SM). SM-sensitized r/r ALL cells towards conventional chemotherapy, even upon resistance against SM alone. The combination of SM and chemotherapy-induced cell death via caspases and PARP, but independent from cIAP-1/2, RIPK1, TNFα or NF-κB. Instead, XIAP was identified to mediate SM effects. Molecular manipulation of XIAP in vivo using microRNA-30 flanked shRNA expression in cell lines and patient-derived xenograft (PDX) models of r/r ALL mimicked SM effects and intermediate XIAP knockdown-sensitized r/r ALL cells towards chemotherapy-induced apoptosis. Interestingly, upon strong XIAP knockdown, PDX r/r ALL cells were outcompeted in vivo, even in the absence of chemotherapy. Our results indicate a yet unknown essential function of XIAP in r/r ALL and reveal XIAP as a promising therapeutic target for r/r ALL.

Lessons learned: the first consecutive 1000 patients of the CCCMunichLMU Molecular Tumor Board.

PURPOSE: In 2016, the University of Munich Molecular Tumor Board (MTB) was implemented to initiate a precision oncology program. This review of cases was conducted to assess clinical implications and functionality of the program, to identify current limitations and to inform future directions of these efforts. METHODS: Charts, molecular profiles, and tumor board decisions of the first 1000 consecutive cases (01/2016-03/2020) were reviewed. Descriptive statistics were applied to describe relevant findings. RESULTS: Of the first 1000 patients presented to the MTB; 914 patients received comprehensive genomic profiling. Median age of patients was 56 years and 58% were female. The most prevalent diagnoses were breast (16%) and colorectal cancer (10%). Different types of targeted or genome-wide sequencing assays were used; most of them offered by the local department of pathology. Testing was technically successful in 88%. In 41% of cases, a genomic alteration triggered a therapeutic recommendation. The fraction of patients receiving a tumor board recommendation differed significantly between malignancies ranging from over 50% in breast or biliary tract to less than 30% in pancreatic cancers. Based on a retrospective chart review, 17% of patients with an MTB recommendation received appropriate treatment. CONCLUSION: Based on these retrospective analyses, patients with certain malignancies (breast and biliary tract cancer) tend to be more likely to have actionable variants. The low rate of therapeutic implementation (17% of patients receiving a tumor board recommendation) underscores the importance of meticulous follow-up for these patients and ensuring broad access to innovative therapies for patients receiving molecular tumor profiling.

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.

Targeting FLT3 with a new-generation antibody-drug conjugate in combination with kinase inhibitors for treatment of AML.

Fms-like tyrosine kinase 3 (FLT3) is often overexpressed or constitutively activated by internal tandem duplication (ITD) and tyrosine kinase domain (TKD) mutations in acute myeloid leukemia (AML). Despite the use of receptor tyrosine kinase inhibitors (TKI) in FLT3-ITD-positive AML, the prognosis of patients is still poor, and further improvement of therapy is required. Targeting FLT3 independent of mutations by antibody-drug conjugates (ADCs) is a promising strategy for AML therapy. Here, we report the development and preclinical characterization of a novel FLT3-targeting ADC, 20D9-ADC, which was generated by applying the innovative P5 conjugation technology. In vitro, 20D9-ADC mediated potent cytotoxicity to Ba/F3 cells expressing transgenic FLT3 or FLT3-ITD, to AML cell lines, and to FLT3-ITD-positive patient-derived xenograft AML cells. In vivo, 20D9-ADC treatment led to a significant tumor reduction and even durable complete remission in AML xenograft models. Furthermore, 20D9-ADC demonstrated no severe hematotoxicity in in vitro colony formation assays using concentrations that were cytotoxic in AML cell line treatment. The combination of 20D9-ADC with the TKI midostaurin showed strong synergy in vitro and in vivo, leading to reduction of aggressive AML cells below the detection limit. Our data indicate that targeting FLT3 with an advanced new-generation ADC is a promising and potent antileukemic strategy, especially when combined with FLT3-TKI in FLT3-ITD-positive AML.