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.

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.

Outcome prediction by the 2022 European LeukemiaNet genetic-risk classification for adults with acute myeloid leukemia: an Alliance study.

Recently, the European LeukemiaNet (ELN) revised its genetic-risk classification of acute myeloid leukemia (AML). We categorized 1637 adults with AML treated with cytarabine/anthracycline regimens according to the 2022 and 2017 ELN classifications. Compared with the 2017 ELN classification, 2022 favorable group decreased from 40% to 35% and adverse group increased from 37% to 41% of patients. The 2022 genetic-risk groups seemed to accurately reflect treatment outcomes in all patients and patients aged <60 years, but in patients aged ≥60 years, relapse rates, disease-free (DFS) and overall (OS) survival were not significantly different between intermediate and adverse groups. In younger African-American patients, DFS and OS did not differ between intermediate-risk and adverse-risk patients nor did DFS between favorable and intermediate groups. In Hispanic patients, DFS and OS did not differ between favorable and intermediate groups. Outcome prediction abilities of 2022 and 2017 ELN classifications were similar. Among favorable-risk patients, myelodysplasia-related mutations did not affect patients with CEBPAbZIP mutations or core-binding factor AML, but changed risk assignment of NPM1-mutated/FLT3-ITD-negative patients to intermediate. NPM1-mutated patients with adverse-risk cytogenetic abnormalities were closer prognostically to the intermediate than adverse group. Our analyses both confirm and challenge prognostic significance of some of the newly added markers.

The impact of early PEG-asparaginase discontinuation in young adults with ALL: a post hoc analysis of the CALGB 10403 study.

Asparaginase is a key component of pediatric-inspired regimens in young adults with acute lymphoblastic leukemia (ALL). Truncation of asparaginase therapy is linked to inferior outcomes in children with ALL. However, a similar correlation in adults is lacking. Here, we studied the prevalence and risk factors associated with pegylated (PEG)-asparaginase discontinuation in young adults with ALL treated on the US intergroup Cancer and Leukemia Group B (CALGB) 10403 study and examined the prognostic impact of early discontinuation (ED) (defined as <4 of 5 or 6 planned doses) on survival outcomes. The analysis included 176 patients who achieved complete remission and initiated the delayed intensification (DI) cycle. The median number of PEG-asparaginase doses administered before DI was 5 (range, 1-6), with 57 (32%) patients with ED. The ED patients were older (median, 26 vs 23 years; P = .023). Survival was apparently lower for ED patients compared with those receiving ≥4 doses, but this finding was not statistically significant (hazard ratio [HR], 1.82; 95% confidence interval [CI], 0.97-3.43; P = .06), with corresponding 5-year overall survival (OS) rates of 66% and 80%, respectively. In patients with standard-risk ALL, the ED of PEG-asparaginase adversely influenced OS (HR, 2.3; 95% CI, 1.02-5.22; P = .04) with a trend toward inferior event-free survival (EFS) (HR, 1.84; 95% CI, 0.92-3.67; P = .08). In contrast, there was no impact of early PEG-asparaginase discontinuation on OS (P = .64) or EFS (P = .32) in patients with high-risk disease based on the presence of high-risk cytogenetics, Ph-like genotype, and/or high white blood cell count at presentation. In conclusion, early PEG-asparaginase discontinuation is common in young adults with ALL and may adversely impact survival of patients with standard-risk ALL.

High-dimensional genomic feature selection with the ordered stereotype logit model.

For many high-dimensional genomic and epigenomic datasets, the outcome of interest is ordinal. While these ordinal outcomes are often thought of as the observed cutpoints of some latent continuous variable, some ordinal outcomes are truly discrete and are comprised of the subjective combination of several factors. The nonlinear stereotype logistic model, which does not assume proportional odds, was developed for these 'assessed' ordinal variables. It has previously been extended to the frequentist high-dimensional feature selection setting, but the Bayesian framework provides some distinct advantages in terms of simultaneous uncertainty quantification and variable selection. Here, we review the stereotype model and Bayesian variable selection methods and demonstrate how to combine them to select genomic features associated with discrete ordinal outcomes. We compared the Bayesian and frequentist methods in terms of variable selection performance. We additionally applied the Bayesian stereotype method to an acute myeloid leukemia RNA-sequencing dataset to further demonstrate its variable selection abilities by identifying features associated with the European LeukemiaNet prognostic risk score.

Molecular cytogenetics in acute myeloid leukemia in adult patients: practical implications.

Throughout the last 50 years, cytogenetic analyses of pretreatment bone marrow and / or blood samples from patients diagnosed with acute myeloid leukemia (AML) revealed a large number of recurring chromosome aberrations, both structural and numerical. Using standard banding methods and, more recently, molecular cytogenetic techniques, such as fluorescence in situ hybridization, spectral karyotyping, multiplex fluorescence in situ hybridization and comparative genomic hybridization, cytogenetic investigations detect acquired abnormalities that, together with submicroscopic gene mutations and changes in gene expression, strongly influence the clinical features and prognosis of patients with AML. Selected reciprocal translocations and inversions and their molecular counterparts, as well as a number of unbalanced chromosome abnormalities are used, together with bone marrow morphology, immunophenotype, and clinical characteristics, to define separate AML entities in the World Health Organization Classification of Haematolymphoid Tumours. Moreover, cytogenetic findings (and specific gene mutations) are being used in geneticrisk classifications, such as the 2022 European LeukemiaNet classification. Such classifications divide patients into broad prognostic categories: favorable, intermediate, and adverse, which are useful in the management of adults with AML. In this article, I review the present data on recurrent chromosome rearrangements in AML and on correlations between cytogenetic findings and clinical features and treatment outcomes of adult patients diagnosed with AML.

High early death rates, treatment resistance, and short survival of Black adolescents and young adults with AML.

Survival of patients with acute myeloid leukemia (AML) is inversely associated with age, but the impact of race on outcomes of adolescent and young adult (AYA; range, 18-39 years) patients is unknown. We compared survival of 89 non-Hispanic Black and 566 non-Hispanic White AYA patients with AML treated on frontline Cancer and Leukemia Group B/Alliance for Clinical Trials in Oncology protocols. Samples of 327 patients (50 Black and 277 White) were analyzed via targeted sequencing. Integrated genomic profiling was performed on select longitudinal samples. Black patients had worse outcomes, especially those aged 18 to 29 years, who had a higher early death rate (16% vs 3%; P=.002), lower complete remission rate (66% vs 83%; P=.01), and decreased overall survival (OS; 5-year rates: 22% vs 51%; P<.001) compared with White patients. Survival disparities persisted across cytogenetic groups: Black patients aged 18 to 29 years with non-core-binding factor (CBF)-AML had worse OS than White patients (5-year rates: 12% vs 44%; P<.001), including patients with cytogenetically normal AML (13% vs 50%; P<.003). Genetic features differed, including lower frequencies of normal karyotypes and NPM1 and biallelic CEBPA mutations, and higher frequencies of CBF rearrangements and ASXL1, BCOR, and KRAS mutations in Black patients. Integrated genomic analysis identified both known and novel somatic variants, and relative clonal stability at relapse. Reduced response rates to induction chemotherapy and leukemic clone persistence suggest a need for different treatment intensities and/or modalities in Black AYA patients with AML. Higher early death rates suggest a delay in diagnosis and treatment, calling for systematic changes to patient care.

Controlled variable selection in Weibull mixture cure models for high-dimensional data.

Medical breakthroughs in recent years have led to cures for many diseases. The mixture cure model (MCM) is a type of survival model that is often used when a cured fraction exists. Many have sought to identify genomic features associated with a time-to-event outcome which requires variable selection strategies for high-dimensional spaces. Unfortunately, currently few variable selection methods exist for MCMs especially when there are more predictors than samples. This study develops high-dimensional penalized Weibull MCMs, which allow for identification of prognostic factors associated with both cure status and/or survival. We demonstrated how such models may be estimated using two different iterative algorithms. The model-X knockoffs method was combined with these algorithms to control the false discovery rate (FDR) in variable selection. Through extensive simulation studies, our penalized MCMs have been shown to outperform alternative methods on multiple metrics and achieve high statistical power with FDR being controlled. In an acute myeloid leukemia (AML) application with gene expression data, our proposed approach identified 14 genes associated with potential cure and 12 genes with time-to-relapse, which may help inform treatment decisions for AML patients.

Effect of additional cytogenetic abnormalities on survival in arsenic trioxide-treated acute promyelocytic leukemia.

Frontline arsenic trioxide (ATO)-based treatment regimens achieve high rates of long-term relapse-free survival in treating acute promyelocytic leukemia (APL) and form the current standard of care. Refining prognostic estimates for newly diagnosed patients treated with ATO-containing regimens remains important in continuing to improve outcomes and identify patients who achieve suboptimal outcomes. We performed a pooled analysis of exclusively ATO-treated patients at a single academic institution and from the ALLG APML4 and Alliance C9710 studies to determine the prognostic importance of additional cytogenetic abnormalities and/or complex karyotype. We demonstrated inferior event-free survival for patients harboring complex karyotype (hazard ratio [HR], 3.74; 95% confidence interval [CI], 1.63-8.56; P = .002), but not for patients harboring additional cytogenetic abnormalities (HR, 2.13; 95% CI, 0.78-5.82; P = .142). These data support a role for full karyotypic analysis of all patients with APL and indicate a need for novel treatment strategies to overcome the adverse effect of APL harboring complex karyotype.

Clinical and molecular relevance of genetic variants in the non-coding transcriptome of patients with cytogenetically normal acute myeloid leukemia.

Expression levels of long non-coding RNA (lncRNA) have been shown to associate with clinical outcome of patients with cytogenetically normal acute myeloid leukemia (CN-AML). However, the frequency and clinical significance of genetic variants in the nucleotide sequences of lncRNA in AML patients is unknown. Herein, we analyzed total RNA sequencing data of 377 younger adults (aged <60 years) with CN-AML, who were comprehensively characterized with regard to clinical outcome. We used available genomic databases and stringent filters to annotate genetic variants unequivocally located in the non-coding transcriptome of AML patients. We detected 981 variants, which are recurrently present in lncRNA that are expressed in leukemic blasts. Among these variants, we identified a cytosine-to-thymidine variant in the lncRNA RP5-1074L1.4 and a cytosine-to-thymidine variant in the lncRNA SNHG15, which independently associated with longer survival of CN-AML patients. The presence of the SNHG15 cytosine-to-thymidine variant was also found to associate with better outcome in an independent dataset of CN-AML patients, despite differences in treatment protocols and RNA sequencing techniques. In order to gain biological insights, we cloned and overexpressed both wild-type and variant versions of the SNHG15 lncRNA. In keeping with its negative prognostic impact, overexpression of the wild-type SNHG15 associated with higher proliferation rate of leukemic blasts when compared with the cytosine-to-thymidine variant. We conclude that recurrent genetic variants of lncRNA that are expressed in the leukemic blasts of CN-AML patients have prognostic and potential biological significance.

Molecular, clinical, and prognostic implications of PTPN11 mutations in acute myeloid leukemia.

Prognostic factors associated with chemotherapy outcomes in patients with acute myeloid leukemia (AML) are extensively reported, and one gene whose mutation is recognized as conferring resistance to several newer targeted therapies is protein tyrosine phosphatase non-receptor type 11 (PTPN11). The broader clinical implications of PTPN11 mutations in AML are still not well understood. The objective of this study was to determine which cytogenetic abnormalities and gene mutations co-occur with PTPN11 mutations and how PTPN11 mutations affect outcomes of patients treated with intensive chemotherapy. We studied 1725 patients newly diagnosed with AML (excluding acute promyelocytic leukemia) enrolled onto the Cancer and Leukemia Group B/Alliance for Clinical Trials in Oncology trials. In 140 PTPN11-mutated patient samples, PTPN11 most commonly co-occurred with mutations in NPM1, DNMT3A, and TET2. PTPN11 mutations were relatively common in patients with an inv(3)(q21q26)/t(3;3)(q21;q26) and a normal karyotype but were very rare in patients with typical complex karyotype and core-binding factor AML. Mutations in the N-terminal SH2 domain of PTPN11 were associated with a higher early death rate than those in the phosphatase domain. PTPN11 mutations did not affect outcomes of NPM1-mutated patients, but these patients were less likely to have co-occurring kinase mutations (ie, FLT3-ITD), suggesting activation of overlapping signaling pathways. However, in AML patients with wild-type NPM1, PTPN11 mutations were associated with adverse patient outcomes, providing a rationale to study the biology and treatment approaches in this molecular group. This trial was registered at www.clinicaltrials.gov as #NCT00048958 (CALGB 8461), #NCT00899223 (CALGB 9665), and #NCT00900224 (CALGB 20202).

Discovery of clinically relevant fusions in pediatric cancer.

BACKGROUND: Pediatric cancers typically have a distinct genomic landscape when compared to adult cancers and frequently carry somatic gene fusion events that alter gene expression and drive tumorigenesis. Sensitive and specific detection of gene fusions through the analysis of next-generation-based RNA sequencing (RNA-Seq) data is computationally challenging and may be confounded by low tumor cellularity or underlying genomic complexity. Furthermore, numerous computational tools are available to identify fusions from supporting RNA-Seq reads, yet each algorithm demonstrates unique variability in sensitivity and precision, and no clearly superior approach currently exists. To overcome these challenges, we have developed an ensemble fusion calling approach to increase the accuracy of identifying fusions. RESULTS: Our Ensemble Fusion (EnFusion) approach utilizes seven fusion calling algorithms: Arriba, CICERO, FusionMap, FusionCatcher, JAFFA, MapSplice, and STAR-Fusion, which are packaged as a fully automated pipeline using Docker and Amazon Web Services (AWS) serverless technology. This method uses paired end RNA-Seq sequence reads as input, and the output from each algorithm is examined to identify fusions detected by a consensus of at least three algorithms. These consensus fusion results are filtered by comparison to an internal database to remove likely artifactual fusions occurring at high frequencies in our internal cohort, while a "known fusion list" prevents failure to report known pathogenic events. We have employed the EnFusion pipeline on RNA-Seq data from 229 patients with pediatric cancer or blood disorders studied under an IRB-approved protocol. The samples consist of 138 central nervous system tumors, 73 solid tumors, and 18 hematologic malignancies or disorders. The combination of an ensemble fusion-calling pipeline and a knowledge-based filtering strategy identified 67 clinically relevant fusions among our cohort (diagnostic yield of 29.3%), including RBPMS-MET, BCAN-NTRK1, and TRIM22-BRAF fusions. Following clinical confirmation and reporting in the patient's medical record, both known and novel fusions provided medically meaningful information. CONCLUSIONS: The EnFusion pipeline offers a streamlined approach to discover fusions in cancer, at higher levels of sensitivity and accuracy than single algorithm methods. Furthermore, this method accurately identifies driver fusions in pediatric cancer, providing clinical impact by contributing evidence to diagnosis and, when appropriate, indicating targeted therapies.

Investigation of the Strength of Plastic Parts Improved with Selective Induction Heating.

The use of selective induction heating of molding surfaces allows for better filling of molding cavities and has a positive effect on the properties of molded products. This is particularly important in the production of parts that include flexible hinges, which are thin plastic layers connecting two or more parts of the product. By using hinges, it is possible to expand the use of injection molding products and their capabilities. They are widely used in the production of parts for the electrical engineering industry and for packaging Fast Moving Consumer Goods (FMCG). The use of hinges also entails specific reductions in wall thickness. Increases in the shear rate can be expected, which can lead to the degradation of polymers and deterioration of mechanical properties of materials. This paper investigates injection molded flexible hinge parts manufactured with selective induction heating to improve their properties. To verify the efficiency of reduction of material degradation due to high shear rates, open/close tests of elastic hinges were performed. The linear relation between the number of cycles the hinges can withstand, mold temperature and injection time was identified, where mold temperature was the more significant factor.

Design and Simulation Study of the Induction Heated Injection Mold with Sliders.

In order to increase the quality of the products manufactured by injection molding, RTC technology can be used to achieve higher mold temperatures. As a result, the path of the injected melt can be extended, allowing the production of parts with more complex shapes and greater length. Induction heating allows heating only selected forming surfaces of the mold which increases the speed and efficiency of the process. This paper presents the concept of a detachable inductor integrated with sliders to enable the application of this technology in an injection mold with sliders, along with the theoretical model used to perform the tests. First, the effect of the magnetic concentrator shape on the process was analyzed. This was followed by a simulation study of the influence of process parameters: heating time, frequency, and electric current. An extensive analysis of the test results of the temperature distribution on the insert allowed for the selection of parameter sets that would enable obtaining the desired surface temperature without a major increase in process time. The results of simulation studies confirm the possible applications and present the range of parameters for obtaining the optimal process.

Rare t(X;14)(q28;q32) translocation reveals link between MTCP1 and chronic lymphocytic leukemia.

Rare, recurrent balanced translocations occur in a variety of cancers but are often not functionally interrogated. Balanced translocations with the immunoglobulin heavy chain locus (IGH; 14q32) in chronic lymphocytic leukemia (CLL) are infrequent but have led to the discovery of pathogenic genes including CCND1, BCL2, and BCL3. Following identification of a t(X;14)(q28;q32) translocation that placed the mature T cell proliferation 1 gene (MTCP1) adjacent to the immunoglobulin locus in a CLL patient, we hypothesized that this gene may have previously unrecognized importance. Indeed, here we report overexpression of human MTCP1 restricted to the B cell compartment in mice produces a clonal CD5+/CD19+ leukemia recapitulating the major characteristics of human CLL and demonstrates favorable response to therapeutic intervention with ibrutinib. We reinforce the importance of genetic interrogation of rare, recurrent balanced translocations to identify cancer driving genes via the story of MTCP1 as a contributor to CLL pathogenesis.

Phase 3 randomized trial of chemotherapy with or without oblimersen in older AML patients: CALGB 10201 (Alliance).

Overexpression of B-cell leukemia/lymphoma 2 (BCL2) renders acute myeloid leukemia (AML) cells resistant to chemotherapy and has been associated with unfavorable outcomes. Oblimersen (G3139) is a phosphorothioate 18-mer antisense oligonucleotide directed against the first 6 BCL2 codons. In a phase 1 study of AML patients treated with G3139, cytarabine, and daunorubicin induction with cytarabine consolidation, no antisense-related toxicity was reported, and BCL2 downregulation occurred in patients achieving complete remission. In this phase 3 trial, untreated older AML patients were randomized to cytarabine (100 mg/m2 per day on days 4-10) and daunorubicin (60 mg/m2 per day on days 4-6) followed by cytarabine consolidation (2000 mg/m2 per day on days 4-8) with (arm A) or without (arm B) G3139 (7 mg/m2 per day on days 1-10 [induction] or days 1-8 [consolidation]). A total of 506 patients were enrolled. No differences in toxicity were observed between arms. Estimated overall survival (OS) at 1 year was 43% for arm A and 40% for arm B (1-sided log rank P = .13), with no differences in disease-free (DFS; P = .26) or event-free survival (P = .80). Subgroup analyses showed patients age <70 years in arm A had improved OS by 1 month vs those in arm B (P = .04), and patients with secondary AML in arm A had better DFS vs those in arm B (P = .04). We conclude that addition of G3139 to chemotherapy failed to improve outcomes of older AML patients. However, more effective means of inhibiting BCL2 are showing promising results in combination with chemotherapy in AML. This trial was registered at www.clinicaltrials.gov as #NCT00085124.

Precision oncology in AML: validation of the prognostic value of the knowledge bank approach and suggestions for improvement.

Recently, a novel knowledge bank (KB) approach to predict outcomes of individual patients with acute myeloid leukemia (AML) was developed using unbiased machine learning. To validate its prognostic value, we analyzed 1612 adults with de novo AML treated on Cancer and Leukemia Group B front-line trials who had pretreatment clinical, cytogenetics, and mutation data on 81 leukemia/cancer-associated genes available. We used receiver operating characteristic (ROC) curves and the area under the curve (AUC) to evaluate the predictive values of the KB algorithm and other risk classifications. The KB algorithm predicted 3-year overall survival (OS) probability in the entire patient cohort (AUCKB = 0.799), and both younger (< 60 years) (AUCKB = 0.747) and older patients (AUCKB = 0.770). The KB algorithm predicted non-remission death (AUCKB = 0.860) well but was less accurate in predicting relapse death (AUCKB = 0.695) and death in first complete remission (AUCKB = 0.603). The KB algorithm's 3-year OS predictive value was higher than that of the 2017 European LeukemiaNet (ELN) classification (AUC2017ELN = 0.707, p < 0.001) and 2010 ELN classification (AUC2010ELN = 0.721, p < 0.001) but did not differ significantly from that of the 17-gene stemness score (AUC17-gene = 0.732, p = 0.10). Analysis of additional cytogenetic and molecular markers not included in the KB algorithm revealed that taking into account atypical complex karyotype, infrequent recurrent balanced chromosome rearrangements and mutational status of the SAMHD1, AXL and NOTCH1 genes may improve the KB algorithm. We conclude that the KB algorithm has a high predictive value that is higher than those of the 2017 and 2010 ELN classifications. Inclusion of additional genetic features might refine the KB algorithm.