Validation of mutated CEBPA bZIP as a distinct prognosis entity in acute myeloid leukemia: a study by the Spanish PETHEMA registry.

Not available.

CALR but Not JAK2 Mutations Are Associated with an Overexpression of Retinoid X Receptor Alpha in Essential Thrombocythemia.

Essential thrombocythemia (ET) is a blood cancer caused by mutations in JAK2 and CALR. It is widely recognized that both mutations lead to the constitutive activation of JAK2/STAT signaling, although other JAK/STAT-independent pathogenic mechanisms triggered by these alterations have also been described in ET. In an attempt to study JAK2/STAT-independent mechanisms derived from CALR mutations, our research group created a C. elegans model with patient-like mutations in calreticulin that lacks JAK counterparts. The introduction of patient-like mutations in the calreticulin of C. elegans leads to an increase in the transcriptional expression of nhr-2, independently of JAK2/STAT activation. In the present study, we aim to verify if this mechanism is conserved in patients with ET harboring CALR mutations. To do so, we evaluated the expression of potential orthologs of nhr-2 in human cell lines of interest for the study, as well as in bone marrow (BM) or peripheral blood (PB) mononuclear cells from patients with CALR or JAK2 mutations. The results revealed that this mechanism is conserved in CALR-mutated ET patients, since CALR, but not JAK2 mutations, were associated with an overexpression of RXRA in patients with ET. The use of drugs targeting the activation or blockade of this target in the analyzed cell lines did not result in changes in cell viability. However, RXRA might be relevant in the disease, pointing to the need for future research testing retinoids and other drugs targeting RXRα for the treatment of ET patients.

Quantification of cyclin D1 and D2 proteins in multiple myeloma identifies different expression patterns from those revealed by gene expression profiling.

Upregulation of a cyclin D gene determined by expression microarrays is an almost universal event in multiple myeloma (MM), but this finding has not been properly confirmed at the protein level. For this reason, we carried out a quantitative analysis of cyclin D proteins using a capillary electrophoresis nanoimmunoassay in newly diagnosed MM patients. Exclusive expression of cyclin D1 and D2 proteins was detected in 54 of 165 (33%) and 30 of 165 (18%) of the MM patients, respectively. Of note, cyclin D1 or D2 proteins were undetectable in 41% of the samples. High levels of cyclin D1 protein were strongly associated with the presence of t(11;14) or 11q gains. Cyclin D2 protein was detected in all the cases bearing t(14;16), but in only 24% of patients with t(4;14). The presence of cyclin D2 was associated with shorter overall survival (hazard ratio =2.14; P=0.017), although patients expressing cyclin D2 protein, but without 1q gains, had a favorable prognosis. In conclusion, although one of the cyclins D is overexpressed at the mRNA level in almost all MM patients, in approximately half of the patients this does not translate into detectable protein. This suggests that cyclins D could not play an oncogenic role in a proportion of patients with MM (clinicaltrials gov. identifier: NCT01916252).

Predictors of unsustained measurable residual disease negativity in transplant-eligible patients with multiple myeloma.

ABSTRACT: The role of measurable residual disease (MRD) negativity as a biomarker to stop treatment is being investigated in transplant-eligible patients with multiple myeloma (MM). Thus, it is important to identify risk factors of MRD resurgence and/or progressive disease (PD) among patients achieving undetectable MRD to avoid undertreating them. Here, we studied 267 newly diagnosed transplant-eligible patients with MM enrolled in the GEM2012MENOS65 and GEM2014MAIN clinical trials who achieved MRD negativity by next-generation flow cytometry. After a median follow-up of 73 months since the first MRD negative assessment, 111 of the 267 (42%) patients showed MRD resurgence and/or PD. The only prognostic factors at diagnosis that predicted MRD resurgence and/or PD were an International Staging System (ISS) 3 and the presence of ≥0.01% circulating tumor cells (CTCs). Failure to achieve MRD negativity after induction also predicted higher risk of MRD resurgence and/or PD. Patients having 0 vs 1 vs ≥2 risk factors (ISS 3, ≥0.01% CTCs, and late MRD negativity) showed 5-year rates of MRD resurgence and/or PD of 16%, 33%, and 57%, respectively (P < .001). Thus, these easily measurable risk factors could help refine the selection of patients for whom treatment cessation after MRD negativity is being investigated in clinical trials. This trial was registered at www.clinicaltrials.gov as NCT01916252 and NCT02406144.

Molecular Landscape and Validation of New Genomic Classification in 2668 Adult AML Patients: Real Life Data from the PETHEMA Registry.

Next-Generation Sequencing (NGS) implementation to perform accurate diagnosis in acute myeloid leukemia (AML) represents a major challenge for molecular laboratories in terms of specialization, standardization, costs and logistical support. In this context, the PETHEMA cooperative group has established the first nationwide diagnostic network of seven reference laboratories to provide standardized NGS studies for AML patients. Cross-validation (CV) rounds are regularly performed to ensure the quality of NGS studies and to keep updated clinically relevant genes recommended for NGS study. The molecular characterization of 2856 samples (1631 derived from the NGS-AML project; NCT03311815) with standardized NGS of consensus genes (ABL1, ASXL1, BRAF, CALR, CBL, CEBPA, CSF3R, DNMT3A, ETV6, EZH2, FLT3, GATA2, HRAS, IDH1, IDH2, JAK2, KIT, KRAS, MPL, NPM1, NRAS, PTPN11, RUNX1, SETBP1, SF3B1, SRSF2, TET2, TP53, U2AF1 and WT1) showed 97% of patients having at least one mutation. The mutational profile was highly variable according to moment of disease, age and sex, and several co-occurring and exclusion relations were detected. Molecular testing based on NGS allowed accurate diagnosis and reliable prognosis stratification of 954 AML patients according to new genomic classification proposed by Tazi et al. Novel molecular subgroups, such as mutated WT1 and mutations in at least two myelodysplasia-related genes, have been associated with an adverse prognosis in our cohort. In this way, the PETHEMA cooperative group efficiently provides an extensive molecular characterization for AML diagnosis and risk stratification, ensuring technical quality and equity in access to NGS studies.

Different prognostic impact of recurrent gene mutations in chronic lymphocytic leukemia depending on IGHV gene somatic hypermutation status: a study by ERIC in HARMONY.

Recent evidence suggests that the prognostic impact of gene mutations in patients with chronic lymphocytic leukemia (CLL) may differ depending on the immunoglobulin heavy variable (IGHV) gene somatic hypermutation (SHM) status. In this study, we assessed the impact of nine recurrently mutated genes (BIRC3, EGR2, MYD88, NFKBIE, NOTCH1, POT1, SF3B1, TP53, and XPO1) in pre-treatment samples from 4580 patients with CLL, using time-to-first-treatment (TTFT) as the primary end-point in relation to IGHV gene SHM status. Mutations were detected in 1588 (34.7%) patients at frequencies ranging from 2.3-9.8% with mutations in NOTCH1 being the most frequent. In both univariate and multivariate analyses, mutations in all genes except MYD88 were associated with a significantly shorter TTFT. In multivariate analysis of Binet stage A patients, performed separately for IGHV-mutated (M-CLL) and unmutated CLL (U-CLL), a different spectrum of gene alterations independently predicted short TTFT within the two subgroups. While SF3B1 and XPO1 mutations were independent prognostic variables in both U-CLL and M-CLL, TP53, BIRC3 and EGR2 aberrations were significant predictors only in U-CLL, and NOTCH1 and NFKBIE only in M-CLL. Our findings underscore the need for a compartmentalized approach to identify high-risk patients, particularly among M-CLL patients, with potential implications for stratified management.

Integrated flow cytometry and sequencing to reconstruct evolutionary patterns from dysplasia to acute myeloid leukemia.

Clonal evolution in acute myeloid leukemia (AML) originates long before diagnosis and is a dynamic process that may affect survival. However, it remains uninvestigated during routine diagnostic workups. We hypothesized that the mutational status of bone marrow dysplastic cells and leukemic blasts, analyzed at the onset of AML using integrated multidimensional flow cytometry (MFC) immunophenotyping and fluorescence-activated cell sorting (FACS) with next-generation sequencing (NGS), could reconstruct leukemogenesis. Dysplastic cells were detected by MFC in 285 of 348 (82%) newly diagnosed patients with AML. Presence of dysplasia according to MFC and World Health Organization criteria had no prognostic value in older adults. NGS of dysplastic cells and blasts isolated at diagnosis identified 3 evolutionary patterns: stable (n = 12 of 21), branching (n = 4 of 21), and clonal evolution (n = 5 of 21). In patients achieving complete response (CR), integrated MFC and FACS with NGS showed persistent measurable residual disease (MRD) in phenotypically normal cell types, as well as the acquisition of genetic traits associated with treatment resistance. Furthermore, whole-exome sequencing of dysplastic and leukemic cells at diagnosis and of MRD uncovered different clonal involvement in dysplastic myelo-erythropoiesis, leukemic transformation, and chemoresistance. Altogether, we showed that it is possible to reconstruct leukemogenesis in ∼80% of patients with newly diagnosed AML, using techniques other than single-cell multiomics.

The transcriptomic landscape of elderly acute myeloid leukemia identifies B7H3 and BANP as a favorable signature in high-risk patients.

Acute myeloid leukemia (AML) in the elderly remains a clinical challenge, with a five-year overall survival rate below 10%. The current ELN 2017 genetic risk classification considers cytogenetic and mutational characteristics to stratify fit AML patients into different prognostic groups. However, this classification is not validated for elderly patients treated with a non-intensive approach, and its performance may be suboptimal in this context. Indeed, the transcriptomic landscape of AML in the elderly has been less explored and it might help stratify this group of patients. In the current study, we analyzed the transcriptome of 224 AML patients > 65 years-old at diagnosis treated in the Spanish PETHEMA-FLUGAZA clinical trial in order to identify new prognostic biomarkers in this population. We identified a specific transcriptomic signature for high-risk patients with mutated TP53 or complex karyotype, revealing that low expression of B7H3 gene with high expression of BANP gene identifies a subset of high-risk AML patients surviving more than 12 months. This result was further validated in the BEAT AML cohort. This unique signature highlights the potential of transcriptomics to identify prognostic biomarkers in in elderly AML.

NGS-Based Molecular Karyotyping of Multiple Myeloma: Results from the GEM12 Clinical Trial.

Next-generation sequencing (NGS) has greatly improved our ability to detect the genomic aberrations occurring in multiple myeloma (MM); however, its transfer to routine clinical labs and its validation in clinical trials remains to be established. We designed a capture-based NGS targeted panel to identify, in a single assay, known genetic alterations for the prognostic stratification of MM. The NGS panel was designed for the simultaneous study of single nucleotide and copy number variations, insertions and deletions, chromosomal translocations and V(D)J rearrangements. The panel was validated using a cohort of 149 MM patients enrolled in the GEM2012MENOS65 clinical trial. The results showed great global accuracy, with positive and negative predictive values close to 90% when compared with available data from fluorescence in situ hybridization and whole-exome sequencing. While the treatments used in the clinical trial showed high efficacy, patients defined as high-risk by the panel had shorter progression-free survival (p = 0.0015). As expected, the mutational status of TP53 was significant in predicting patient outcomes (p = 0.021). The NGS panel also efficiently detected clonal IGH rearrangements in 81% of patients. In conclusion, molecular karyotyping using a targeted NGS panel can identify relevant prognostic chromosomal abnormalities and translocations for the clinical management of MM patients.

TP53 Abnormalities Are Underlying the Poor Outcome Associated with Chromothripsis in Chronic Lymphocytic Leukemia Patients with Complex Karyotype.

Chromothripsis (cth) has been associated with a dismal outcome and poor prognosis factors in patients with chronic lymphocytic leukemia (CLL). Despite being correlated with high genome instability, previous studies have not assessed the role of cth in the context of genomic complexity. Herein, we analyzed a cohort of 33 CLL patients with cth and compared them against a cohort of 129 non-cth cases with complex karyotypes. Nine cth cases were analyzed using optical genome mapping (OGM). Patterns detected by genomic microarrays were compared and the prognostic value of cth was analyzed. Cth was distributed throughout the genome, with chromosomes 3, 6 and 13 being those most frequently affected. OGM detected 88.1% of the previously known copy number alterations and several additional cth-related rearrangements (median: 9, range: 3-26). Two patterns were identified: one with rearrangements clustered in the region with cth (3/9) and the other involving both chromothriptic and non-chromothriptic chromosomes (6/9). Cases with cth showed a shorter time to first treatment (TTFT) than non-cth patients (median TTFT: 2 m vs. 15 m; p = 0.013). However, when stratifying patients based on TP53 status, cth did not affect TTFT. Only TP53 maintained its significance in the multivariate analysis for TTFT, including cth and genome complexity defined by genomic microarrays (HR: 1.60; p = 0.029). Our findings suggest that TP53 abnormalities, rather than cth itself, underlie the poor prognosis observed in this subset.

Circulating Tumor Cells for the Staging of Patients With Newly Diagnosed Transplant-Eligible Multiple Myeloma.

PURPOSE: Patients with multiple myeloma (MM) may show patchy bone marrow (BM) infiltration and extramedullary disease. Notwithstanding, quantification of plasma cells (PCs) continues to be performed in BM since the clinical translation of circulating tumor cells (CTCs) remains undefined. PATIENTS AND METHODS: CTCs were measured in peripheral blood (PB) of 374 patients with newly diagnosed MM enrolled in the GEM2012MENOS65 and GEM2014MAIN trials. Treatment included bortezomib, lenalidomide, and dexamethasone induction followed by autologous transplant, consolidation, and maintenance. Next-generation flow cytometry was used to evaluate CTCs in PB at diagnosis and measurable residual disease (MRD) in BM throughout treatment. RESULTS: CTCs were detected in 92% (344 of 374) of patients with newly diagnosed MM. The correlation between the percentages of CTCs and BM PCs was modest. Increasing logarithmic percentages of CTCs were associated with inferior progression-free survival (PFS). A cutoff of 0.01% CTCs showed an independent prognostic value (hazard ratio: 2.02; 95% CI, 1.3 to 3.1; P = .001) in multivariable PFS analysis including the International Staging System, lactate dehydrogenase levels, and cytogenetics. The combination of the four prognostic factors significantly improved risk stratification. Outcomes according to the percentage of CTCs and depth of response to treatment showed that patients with undetectable CTCs had exceptional PFS regardless of complete remission and MRD status. In all other cases with detectable CTCs, only achieving MRD negativity (and not complete remission) demonstrated a statistically significant increase in PFS. CONCLUSION: Evaluation of CTCs in PB outperformed quantification of BM PCs. The detection of ≥ 0.01% CTCs could be a new risk factor in novel staging systems for patients with transplant-eligible MM.

Unsupervised machine learning improves risk stratification in newly diagnosed multiple myeloma: an analysis of the Spanish Myeloma Group.

The International Staging System (ISS) and the Revised International Staging System (R-ISS) are commonly used prognostic scores in multiple myeloma (MM). These methods have significant gaps, particularly among intermediate-risk groups. The aim of this study was to improve risk stratification in newly diagnosed MM patients using data from three different trials developed by the Spanish Myeloma Group. For this, we applied an unsupervised machine learning clusterization technique on a set of clinical, biochemical and cytogenetic variables, and we identified two novel clusters of patients with significantly different survival. The prognostic precision of this clusterization was superior to those of ISS and R-ISS scores, and appeared to be particularly useful to improve risk stratification among R-ISS 2 patients. Additionally, patients assigned to the low-risk cluster in the GEM05 over 65 years trial had a significant survival benefit when treated with VMP as compared with VTD. In conclusion, we describe a simple prognostic model for newly diagnosed MM whose predictions are independent of the ISS and R-ISS scores. Notably, the model is particularly useful in order to re-classify R-ISS score 2 patients in 2 different prognostic subgroups. The combination of ISS, R-ISS and unsupervised machine learning clusterization brings a promising approximation to improve MM risk stratification.

Preneoplastic somatic mutations including MYD88L265P in lymphoplasmacytic lymphoma.

Normal cell counterparts of solid and myeloid tumors accumulate mutations years before disease onset; whether this occurs in B lymphocytes before lymphoma remains uncertain. We sequenced multiple stages of the B lineage in elderly individuals and patients with lymphoplasmacytic lymphoma, a singular disease for studying lymphomagenesis because of the high prevalence of mutated MYD88. We observed similar accumulation of random mutations in B lineages from both cohorts and unexpectedly found MYD88L265P in normal precursor and mature B lymphocytes from patients with lymphoma. We uncovered genetic and transcriptional pathways driving malignant transformation and leveraged these to model lymphoplasmacytic lymphoma in mice, based on mutated MYD88 in B cell precursors and BCL2 overexpression. Thus, MYD88L265P is a preneoplastic event, which challenges the current understanding of lymphomagenesis and may have implications for early detection of B cell lymphomas.

A Machine Learning Model Based on Tumor and Immune Biomarkers to Predict Undetectable MRD and Survival Outcomes in Multiple Myeloma.

PURPOSE: Undetectable measurable residual disease (MRD) is a surrogate of prolonged survival in multiple myeloma. Thus, treatment individualization based on the probability of a patient achieving undetectable MRD with a singular regimen could represent a new concept toward personalized treatment, with fast assessment of its success. This has never been investigated; therefore, we sought to define a machine learning model to predict undetectable MRD at the onset of multiple myeloma. EXPERIMENTAL DESIGN: This study included 487 newly diagnosed patients with multiple myeloma. The training (n = 152) and internal validation cohorts (n = 149) consisted of 301 transplant-eligible patients with active multiple myeloma enrolled in the GEM2012MENOS65 trial. Two external validation cohorts were defined by 76 high-risk transplant-eligible patients with smoldering multiple myeloma enrolled in the Grupo Español de Mieloma(GEM)-CESAR trial, and 110 transplant-ineligible elderly patients enrolled in the GEM-CLARIDEX trial. RESULTS: The most effective model to predict MRD status resulted from integrating cytogenetic [t(4;14) and/or del(17p13)], tumor burden (bone marrow plasma cell clonality and circulating tumor cells), and immune-related biomarkers. Accurate predictions of MRD outcomes were achieved in 71% of cases in the GEM2012MENOS65 trial (n = 214/301) and 72% in the external validation cohorts (n = 134/186). The model also predicted sustained MRD negativity from consolidation onto 2 years maintenance (GEM2014MAIN). High-confidence prediction of undetectable MRD at diagnosis identified a subgroup of patients with active multiple myeloma with 80% and 93% progression-free and overall survival rates at 5 years. CONCLUSIONS: It is possible to accurately predict MRD outcomes using an integrative, weighted model defined by machine learning algorithms. This is a new concept toward individualized treatment in multiple myeloma. See related commentary by Pawlyn and Davies, p. 2482.

Chromosome banding analysis and genomic microarrays are both useful but not equivalent methods for genomic complexity risk stratification in chronic lymphocytic leukemia patients.

Genome complexity has been associated with poor outcome in patients with chronic lymphocytic leukemia (CLL). Previous cooperative studies established five abnormalities as the cut-off that best predicts an adverse evolution by chromosome banding analysis (CBA) and genomic microarrays (GM). However, data comparing risk stratification by both methods are scarce. Herein, we assessed a cohort of 340 untreated CLL patients highly enriched in cases with complex karyotype (CK) (46.5%) with parallel CBA and GM studies. Abnormalities found by both techniques were compared. Prognostic stratification in three risk groups based on genomic complexity (0-2, 3- 4 and ≥5 abnormalities) was also analyzed. No significant differences in the percentage of patients in each group were detected, but only a moderate agreement was observed between methods when focusing on individual cases (κ=0.507; P<0.001). Discordant classification was obtained in 100 patients (29.4%), including 3% classified in opposite risk groups. Most discrepancies were technique-dependent and no greater correlation in the number of abnormalities was achieved when different filtering strategies were applied for GM. Nonetheless, both methods showed a similar concordance index for prediction of time to first treatment (TTFT) (CBA: 0.67 vs. GM: 0.65) and overall survival (CBA: 0.55 vs. GM: 0.57). High complexity maintained its significance in the multivariate analysis for TTFT including TP53 and IGHV status when defined by CBA (hazard ratio [HR] 3.23; P<0.001) and GM (HR 2.74; P<0.001). Our findings suggest that both methods are useful but not equivalent for risk stratification of CLL patients. Validation studies are needed to establish the prognostic value of genome complexity based on GM data in future prospective studies.

Prognostic heterogeneity of adult B-cell precursor acute lymphoblastic leukaemia patients with t(1;19)(q23;p13)/TCF3-PBX1 treated with measurable residual disease-oriented protocols.

The prognosis of t(1;19)(q23;p13)/transcription factor 3-pre-B-cell leukaemia homeobox 1 (TCF3-PBX1) in adolescent and adult patients with acute lymphoblastic leukaemia (ALL) treated with measurable residual disease (MRD)-oriented trials remains controversial. In the present study, we analysed the outcome of adolescent and adult patients with t(1;19)(q23;p13) enrolled in paediatric-inspired trials. The patients with TCF3-PBX1 showed similar MRD clearance and did not have different survival compared with other B-cell precursor ALL patients. However, patients with TCF3-PBX1 had a significantly higher cumulative incidence of relapse, especially among patients aged ≥35 years carrying additional cytogenetic alterations. These patients might benefit from additional/intensified therapy (e.g. immunotherapy in first complete remission with or without subsequent haematopoietic stem cell transplantation).