The aim of this study was to evaluate how comorbidities and molecular landscape relate to outcome in patients with acute myeloid leukemia (AML) aged 60 years or older who received intensive induction therapy. In 91 patients, 323 mutations were identified in 77 genes by next-generation sequencing, with a median of four mutations per patient, with NPM1, FLT3, TET2, and DNMT3A being the most frequently mutated genes. A multistate model identified FLT3, IDH2, RUNX1, and TET2 mutations as associated with a higher likelihood of achieving complete remission while STAG2 mutations were associated with primary refractory disease, and DNMT3A, FLT3, IDH2, and TP53 mutations with mortality after relapse. Ferrara unfitness criteria and performance status were the best predictors of short-term outcome (area under the curve = 82 for 2-month survival for both parameters), whereas genomic classifications better predicted long-term outcome, with the Patel risk stratification performing the best over the 5-year follow-up period (C-index = 0.63 for event-free and overall survival). We show that most genomic prognostic classifications, mainly used in younger patients, are useful for classifying older patients, but to a lesser extent, because of different mutational profiles. Specific prognostic classifications, incorporating performance status, comorbidities, and cytogenetic/molecular data, should be specifically designed for patients over 60 years.
<p>supplementary data Figure S1. Gene expression signatures define distinct molecular groups of T-ALL. Figure S2. Global flow chart of the patients Figure S3. Comparison of outcomes between LALA94 patients with central lab onco-genetic study performed (dotted line) and patients without (full line). Figure S4. Epigenetic histone marks. Figure S5. Kaplan-Meier graph for OS is shown for TAL1+ patients treated on LALA-94 vs. GRAALL-2003/2005 trials. Figure S6. TAL1 expression normalised to GAPDH by RTQ-PCR in 8 PDX treated with L-asparaginase (Rf. Figure 4H). Figure S7. (A) Correlation analysis between ASNS expression and ASNS promoter methylation ratio. (B) ASNS transcriptional expression normalized to GAPDH in T-ALL, in normal Bone Marrow (BM) (100%, 50%, 10% and 1%) and in normal Peripheral Blood Cells (PBL) (100%, 50%, 10% and 1. (C) comparison of ASNS transcriptional expression in non-sorted diagnostic sample, blast and non-blast sorted cells in two patients with a hypermethylated ASNS promoter (UPNT-573 and UPNT-498) and high ASNS expression (T3 tertile) (left) and, in primary samples and PDX (Primary Derived Xenograft) using a human specific Taqman system for two hypermethylated cases (UPNT-485 and UPNT-419) and two hypomethylated cases (UPNT-615 and UPNT-241) (right). (D) Correlation analysis between ASNS expression and ASNS promoter methylation ratio in purified blasts cells (PDX n=8 )and sorted primary samples (n=3). (E) Correlation analysis between ASNS expression (RNA-seq) and ASNS promoter methylation ratio in a series of 13 T-ALL cell lines (LOUCY, DND41, RPMI8402, HPB-ALL, ALL-SIL, TALL1, MOLT3, PEER, SUPT1, PF382, MOLT3, MOLT16, JURKAT). Table S1. Clinico-biological characteristics of patients included in the LALA94 trial according to their inclusion in the present study. Table S2. GRAALL03, 05 and LALA94 trials overview and drug administration schedule. Table S3. SiRNA sequences Table S4. Probes sequences for ASNS MS-MLPA analysis Table S5. DNA Global Methylation study Table S6. Characteristics of TLX1+, TLX3+ and TLX neg patients Table S7. Clinico-biological characteristics of T1 (lower ASNS methylation tertile) and T2+T3 (higher methylation tertiles) adult T-ALL. Table S8. Univariate and multivariate analysis for EFS and OS</p>
In total, 279 patients with hairy-cell leukemia (HCL) were analyzed, with a median follow-up of 10 years. Data were collected up to June 2018. We analyzed responses to treatment, relapses, survival, and the occurrence of second malignancies during follow-up. The median age was 59 years. In total, 208 patients (75%) were treated with purine analogs (PNAs), either cladribine (159) or pentosatin (49), as the first-line therapy. After a median follow-up of 127 months, the median overall survival was 27 years, and the median relapse-free survival (RFS) was 11 years. The cumulative 10-year relapse incidence was 39%. In patients receiving second-line therapy, the median RFS was 7 years. For the second-line therapy, using the same or another PNA was equivalent. We identified 68 second malignancies in 59 patients: 49 solid cancers and 19 hematological malignancies. The 10-year cumulative incidences of cancers, solid tumors, and hematological malignancies were 15%, 11%, and 5.0%, respectively, and the standardized incidence ratios were 2.22, 1.81, and 6.67, respectively. In multivariate analysis, PNA was not a risk factor for second malignancies. HCL patients have a good long-term prognosis. PNAs are the first-line treatment. HCL patients require long-term follow-up because of their relatively increased risk of second malignancies.
