Development and validation of a novel survival model for acute myeloid leukemia based on autophagy-related genes

Background Acute myeloid leukemia (AML) is one of the most common blood cancers, and is characterized by impaired hematopoietic function and bone marrow (BM) failure. Under normal circumstances, autophagy may suppress tumorigenesis, however under the stressful conditions of late stage tumor growth autophagy actually protects tumor cells, so inhibiting autophagy in these cases also inhibits tumor growth and promotes tumor cell death. Methods AML gene expression profile data and corresponding clinical data were obtained from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, from which prognostic-related genes were screened to construct a risk score model through LASSO and univariate and multivariate Cox analyses. Then the model was verified in the TCGA cohort and GEO cohorts. In addition, we also analyzed the relationship between autophagy genes and immune infiltrating cells and therapeutic drugs. Results We built a model containing 10 autophagy-related genes to predict the survival of AML patients by dividing them into high- or low-risk subgroups. The high-risk subgroup was prone to a poorer prognosis in both the training TCGA-LAML cohort and the validation GSE37642 cohort. Univariate and multivariate Cox analysis revealed that the risk score of the autophagy model can be used as an independent prognostic factor. The high-risk subgroup had not only higher fractions of CD4 naïve T cell, NK cell activated, and resting mast cells but also higher expression of immune checkpoint genes CTLA4 and CD274. Last, we screened drug sensitivity between high- and low-risk subgroups. Conclusion The risk score model based on 10 autophagy-related genes can serve as an effective prognostic predictor for AML patients and may guide for patient stratification for immunotherapies and drugs.

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A Risk Score Combined Clinical and Molecular Profiles Identifies a High-Risk Subgroup within Intermediate-Risk Acute Myeloid Leukemia

Blood ◽

10.1182/blood-2019-129186 ◽

2019 ◽

Vol 134 (Supplement_1) ◽

pp. 2713-2713

Author(s):

Xiaoxia Hu ◽

Aijie Huang ◽

Qi Chen ◽

Ying Zhang ◽

Lixia Liu ◽

...

Keyword(s):

Acute Myeloid Leukemia ◽

Prognostic Factors ◽

High Risk ◽

Signaling Pathway ◽

Risk Score ◽

Myeloid Leukemia ◽

Intermediate Risk ◽

Concordance Index ◽

Scoring Model ◽

Acute Myeloid

Introduction Acute myeloid leukemia (AML) is categorized into favorable-, intermediate- and adverse-risk groups according to European LeukemiaNet (ELN) risk stratification. The intermediate-risk AML comprises a substantial proportion of AML, and even within the intermediate-risk AML, the biology and prognosis are highly different, which suggests that more prognostic factors are needed to be identified. Method A total of 265 newly diagnosed AML patients treated between January 2010 and January 2019 who had cryopreserved DNA for mutational analyses diagnosed and treated in Changhai Hospital were included. 121 patients were aged ≤ 65y, and classified as intermediate-risk (IR)-AML. A Custom Amplicon panel targeting exons of 210 genes was used for deep sequencing at diagnosis. We used a LASSO Cox regression model to achieve shrinkage and variable selection from prognostic factors (P<0.1 in log-rank tests) to build risk score for predicting overall survival. A nomogram was constructed to display the risk of death in individuals. The discrimination of the risk score was measured by the concordance index (C-index) and areas under time-dependent receiver-operating characteristics (ROC) curves (AUCs), and the calibration of the risk score was explored graphically by calibration plots. Patients with IR-AML and aged ≤ 65y in The Cancer Genome Atlas (TCGA) data (n= 41) was used as a validation cohort. Results The median age was 44 (11-75) years, and 54% had normal karyotype. NRAS and CEBPA were the most recurrently mutated genes (both 26%), followed by KIT (24%), DNMT3A (23%), ARID1B (20%), FLT3-ITD (19%), PCLO (17%), and TET2 (17%). In univariate analyses, age ≥ 55 years, WBC ≥ 10×109/L , PLT > 40×109/L, high LDH counts at diagnosis, DNMT3A and Signaling Pathway genes mutations and the number of mutated genes ≥ 8 were significantly associated with poor OS (P < 0.05), and age ≥ 55 years, WBC≥ 10×109/L, DNMT3A and FLT3-ITD mutations were associated with worse relapse free survival(RFS, P < 0.05). Three variables were incorporated in our scoring model by LASSO, including Signaling Pathway genes mutations (including NRAS, KIT, FLT3, KRAS etc), DNMT3A mutation and WBC≥ 10×109/L. A risk scoring model was developed incorporating the weighted coefficients of these variables:0.6749 × Signaling Pathway + 1.1147 × DNMT3A + 0.7829 × WBC. The risk score grouped IR-AML patients into two subgroups: intermediate-low risk (ILR, score < 1, n= 48) and intermediate-high risk (IHR, score ≥ 1, n= 62) groups (Table1). Concordance index[OS: 0.703, 95% CI (0.643, 0.763); RFS: 0.681, 95%CI (0.620, 0.741)] demonstrated well discrimination power and calibration plots showed that the nomograms did well compared with an ideal model. The 3-year OS for ILR and IHR groups were 72.3% and 29.4% (P < 0.0001), and 3-year RFS were 63.9% and 19.4% (P < 0.0001), respectively (Figure 1A-B). The similar results were also observed in TCGA cohort (3-year OS 57.7% vs. 26.2%, P= 0.019; Figure 1C). The survival was equivalent for patients with ILR when treated with chemotherapy and allogeneic hematopoietic stem cell transplantation (alloHSCT, 3-year OS: 74.7% vs. 70.8%, P= 0.936, RFS: 76.4% vs. 55.0%, P= 0.225; Figure 2A-B). However, alloHSCT benefited patients with IHR. Patients who received alloHSCT had survival advantages over those who treated with chemotherapy only (3-year OS: 51.6% vs. 20.7%, P= 0.022; 3-year RFS: 38.1% vs. 7.8%, P= 0.008; Figure 2C-D). The prognosis of patients with IHR was as poor as those with adverse-risk AML (n=65 , 3-year OS: 29.5% vs. 33.3%, P= 0.794; 3-year RFS: 19.4% vs. 39.1, P= 0.294). Conclusions In this study, we developed and validated a novel scoring model that incorporated molecular and clinical profiles. According to our score model, IR-AML patients could be further stratified into two subgroups with distinct clinical outcomes. And the prognosis of patients with IHR was similar with patients with adverse-risk. Moreover, alloHSCT would override the poor outcome of patients with IHR. In summary, our scoring model might help identify patients with IR-AML who are most likely to benefit from alloHSCT. The results are needed to be validated in other independent cohorts and prospective studies before implementation into clinics. Disclosures No relevant conflicts of interest to declare.

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A Risk Score Combined Clinical and Molecular Profiles Identifies a High-Risk Subgroup within AML1-ETO-Positive Acute Myeloid Leukemia

Blood ◽

10.1182/blood-2020-142100 ◽

2020 ◽

Vol 136 (Supplement 1) ◽

pp. 19-19

Author(s):

Min Yang ◽

Yi Zhang ◽

Jinghan Wang ◽

Lixia Liu ◽

Chengcheng Wang ◽

...

Keyword(s):

Overall Survival ◽

Acute Myeloid Leukemia ◽

High Risk ◽

Risk Score ◽

Myeloid Leukemia ◽

Validation Cohort ◽

Concordance Index ◽

Scoring Model ◽

Mutation Burden ◽

Acute Myeloid

Background: AML1-ETO-positive acute myeloid leukemia, is classified as a favorable leukemia subtype according to the European Leukemia Net (ELN) risk stratification. Nevertheless, studies show the biology and prognosis within the AML1-ETO-positive AML are highly different, which suggests that more prognostic factors are needed to be identified. Aims: This study mainly revealed the genomic mutation characteristics and explored more factors which affect the prognosis of Chinese AML1-ETO-positive AML patients. Methods: A total of 167 AML1-ETO-positive patients who diagnosed and treated in Zhejiang Institute of Hematology had cryopreserved DNA for deep target 185-gene regional sequencing. Variants were detected with a variant allele frequency (VAF) cutoff of 0.5%. We used a LASSO Cox regression model to build risk score for predicting overall survival. A nomogram was constructed to display the risk of death in individuals. The discrimination of the risk score was measured by the concordance index (C-index) and areas under time-dependent receiver-operating characteristics (ROC) curves (AUCs), and the calibration of the risk score was explored graphically by calibration plots. Patients (n=75) from other hospital were used as a validation cohort. Results: The median age in analyzed patients was 42(6-78) years. The most common recurrent mutations occurred in KIT(n=84,50%), ASXL2(n=46,28%), NRAS(n=37,22%), FLT3-ITD(n=35,21%) and TET2(n=30,18%). We observed that high KIT mutant allele burden predicts for poor outcome in t(8:21) AML. High KIT VAF(≥15%) correlated with shortened overall survival compared to the other KIT mutated cases including low VAF and wild-type KIT (3-year OS 26.6% vs 59.0% vs 69.6%, HR 1.50, 95%CI 0.78-2.89, P=0.0005). In addition, we also identified some other mutated genes influence the prognosis of patients with t (8;21), such as FLT3-ITD high mutation burden(VAF≥44% vs other cases, 3-year OS 30.0% vs 56.2%, HR 2.94, 95%CI 0.43-20.18, P=0.056), TET2 high mutation burden (VAF≥43% vs other cases, 3-year OS 33.3% vs 56.5%, HR 2.87, 95%CI 0.66-12.46, P=0.018) and DHX15 high mutation burden (VAF≥22% vs other cases, 3-year OS 15.0% vs 58.3%, HR 2.65, 95%CI 0.81-8.73, P=0.011). In univariate analyses for OS, age>42 (3-year OS 46.3% vs 64.4%, HR 1.91, 95%CI 1.14-3.14, P=0.012), WBC>27.1×109/L(3-year OS 34.3% vs 60.0%, HR 2.59, 95%CI 1.13-5.9, P=0.001), BM blast>20% (3-year OS 52.2% vs 92.8%, HR 6.36, 95%CI 2.7-14.97, P =0.035), LDH > 504U/L (3-year OS 44.1% vs 67.1%, HR 2.62, 95%CI 1.50-4.59, P=0.0007), PLT≤28×109/L (3-year OS 47.1% vs 66.9%, HR 1.89, 95%CI 1.13-3.17, P=0.019), HB≤87g/L (3-year OS 49.4% vs 73.8%, HR 2.20, 95%CI 1.27-3.84, P=0.019) were significantly associated with poor OS. Six variables were incorporated in our scoring model by LASSO, including age, WBC, PLT, KIT mutation, FLT3-ITD mutation and TET2 mutation. A risk scoring model was developed incorporating the weighted coefficients of these variables. The risk score grouped AML1-ETO AML patients into two subgroup: low risk (LR, n=68) and high risk (HR, n=86) groups. The 3-year OS for LR and HR groups were 72.7% and 43.0% (P<0.0001, Figure A). The similar results were also observed in validation cohort (3-year OS 79.1% vs 49.5%, P= 0.01; Figure B). Concordance index [train: 0.708, 95% CI (0.680, 0.736), validation: 0.722, 95% CI (0.666, 0.778)] demonstrated well discrimination power and calibration plots showed that the nomograms did well compared with an ideal model. Conclusion: In this study, our findings indicate that the prognostic effect of gene mutation in de novo t(8:21) AML may be influenced by the relative abundance of the mutated allele. A novel scoring model was developed and validated that incorporated molecular and clinical profiles. According to our score model, AML1-ETO AML patients could be further stratified into two subgroups with distinct clinical outcomes. Our data can serve as a basis for guided and risk-adapted treatment strategies for CBF-AML patients. The results are needed to be validated in other independent cohorts and prospective studies before implementation into clinics. Disclosures No relevant conflicts of interest to declare.

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Elderly Patients with Acute Myeloid Leukemia Are Not All the Same: Results of the Prospective DSIL AML96 Trial.

Blood ◽

10.1182/blood.v110.11.1840.1840 ◽

2007 ◽

Vol 110 (11) ◽

pp. 1840-1840

Author(s):

Markus Andreas Schaich ◽

Walter E. Aulitzky ◽

Heinrich Bodenstein ◽

Martin Bornhaeuser ◽

Thomas Illmer ◽

...

Keyword(s):

Acute Myeloid Leukemia ◽

Prognostic Factors ◽

High Risk ◽

Elderly Patients ◽

Induction Therapy ◽

Myeloid Leukemia ◽

Low Risk ◽

Severe Toxicity ◽

Elderly Aml ◽

Acute Myeloid

Abstract The majority of patients with acute myeloid leukemia (AML) are older than 60 years at diagnosis. However, treatment results for these elderly patients are still unsatisfactory. This is thought to be due to a more aggressive disease, preexisting co-morbidities or a decreased tolerance for intensive treatment approaches. As for younger patients there is growing evidence that elderly AML patients may be divided into prognostic subgroups. So far data on prognostic factors in this group of patients are still sketchy. Between February 1996 and March 2005 a total of 827 elderly AML patients with a median age of 67 (61–87) years were treated within the prospective AML96 trial of the German Study Initiative Leukemia (DSIL). 643 patients had de novo and 184 patients secondary disease. All patients were scheduled to receive a double induction therapy with Daunorubicin and Ara-C (DA3+7). The consolidation therapy consisted of one course of m-Amsacrine and intermediate-dose (10g/m2) Ara-C. 265 (32%) patients reached CR criteria after double induction therapy. Forty-two patients (5%) had only a PR, 307(37%) displayed refractory disease, 126(15%) died during induction therapy and 77(10%) received only one course of induction therapy due to severe toxicity. Out of the 265 patients in CR 120 (45%) patients received the consolidation course. The strongest independent prognostic factors for achieving a CR were less than 10% blasts in the day 15 bone marrow, the presence of a NPM mutation or a low-risk karyotype (p<0.0001 each). The 3-year overall (OS) and relapse-free survival (RFS) rates were 18% for all patients and 17% for all patients in CR, respectively. In the multivariate analysis the strongest prognostic factors for survival were age, LDH and cytogenetics (p<0.0001 each). Using these three parameters a prognostic model for survival was established. Patients older than 70 years with intermediate- or high-risk cytogenetics and a high LDH level at diagnosis (n=213) had a 3-year OS of only 9%, whereas patients with low-risk cytogenetics or patients with intermediate-risk cytogenetics, younger than 70 years and a low LDH level (n=237) had a 3-year OS of 32%. All other patients (n=377) had an intermediate 3-year OS of 15% (p<0.0001). In conclusion, elderly AML patients can be stratified into prognostic groups. AML patients older than 70 years with high LDH levels and intermediate- or high-risk cytogenetics at diagnosis do not profit from conventional chemotherapy.

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A three-gene signature might predict prognosis in patients with acute myeloid leukemia

Bioscience Reports ◽

10.1042/bsr20193808 ◽

2020 ◽

Vol 40 (6) ◽

Author(s):

Xin Zhu ◽

Qian Zhao ◽

Xiaoyu Su ◽

Jinming Ke ◽

Yunyun Yi ◽

...

Keyword(s):

Acute Myeloid Leukemia ◽

Transcription Factor ◽

High Risk ◽

Myeloid Leukemia ◽

Cox Regression ◽

Risk Group ◽

White Blood Cells ◽

Gene Signature ◽

Low Risk ◽

Acute Myeloid

Abstract The identification of effective signatures is crucial to predict the prognosis of acute myeloid leukemia (AML). The investigation aimed to identify a new signature for AML prognostic prediction by using the three-gene expression (octamer-binding transcription factor 4 (OCT4), POU domain type 5 transcription factor 1B (POU5F1B) and B-cell-specific Moloney murine leukemia virus integration site-1 pseudogene 1 (BMI1P1). The expressions of genes were obtained from our previous study. Only the specimens in which three genes were all expressed were included in this research. A three-gene signature was constructed by the multivariate Cox regression analyses to divide patients into high-risk and low-risk groups. Receiver operating characteristic (ROC) analysis of the three-gene signature (area under ROC curve (AUC) = 0.901, 95% CI: 0.821–0.981, P<0.001) indicated that it was a more valuable signature for distinguishing between patients and controls than any of the three genes. Moreover, white blood cells (WBCs, P=0.004), platelets (PLTs, P=0.017), percentage of blasts in bone marrow (BM) (P=0.011) and complete remission (CR, P=0.027) had significant differences between two groups. Furthermore, high-risk group had shorter leukemia-free survival (LFS) and overall survival (OS) than low-risk group (P=0.026; P=0.006), and the three-gene signature was a prognostic factor. Our three-gene signature for prognosis prediction in AML may serve as a prognostic biomarker.

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A Four-Gene-Based Prognostic Model Predicts Overall Survival in Patients With Cutaneous Melanoma

Frontiers in Oncology ◽

10.3389/fonc.2021.639874 ◽

2021 ◽

Vol 11 ◽

Author(s):

Xiaoxia Tong ◽

Xiaofei Qu ◽

Mengyun Wang

Keyword(s):

Gene Expression ◽

High Risk ◽

Risk Score ◽

Cutaneous Melanoma ◽

Cox Regression ◽

Risk Group ◽

High Risk Group ◽

Low Risk ◽

Rank Test ◽

Score Model

BackgroundCutaneous melanoma (CM) is one of the most aggressive cancers with highly metastatic ability. To make things worse, there are limited effective therapies to treat advanced CM. Our study aimed to investigate new biomarkers for CM prognosis and establish a novel risk score system in CM.MethodsGene expression data of CM from Gene Expression Omnibus (GEO) datasets were downloaded and analyzed to identify differentially expressed genes (DEGs). The overlapped DEGs were then verified for prognosis analysis by univariate and multivariate COX regression in The Cancer Genome Atlas (TCGA) datasets. Based on the gene signature of multiple survival associated DEGs, a risk score model was established, and its prognostic and predictive role was estimated through Kaplan-Meier (K-M) analysis and log-rank test. Furthermore, the correlations between prognosis related genes expression and immune infiltrates were analyzed via Tumor Immune Estimation Resource (TIMER) site.ResultsA total of 103 DEGs were obtained based on GEO cohorts, and four genes were verified in TCGA datasets. Subsequently, four genes (ADAMDEC1, GNLY, HSPA13, and TRIM29) model was developed by univariate and multivariate Cox regression analyses. The K-M plots showed that the high-risk group was associated with shortened survival than that in the low-risk group (P < 0.0001). Multivariate analysis suggested that the model was an independent prognostic factor (high-risk vs. low-risk, HR= 2.06, P < 0.001). Meanwhile, the high-risk group was prone to have larger breslow depth (P< 0.001) and ulceration (P< 0.001).ConclusionsThe four-gene risk score model functions well in predicting the prognosis and treatment response in CM and will be useful for guiding therapeutic strategies for CM patients. Additional clinical trials are needed to verify our findings.

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Impact of allogeneic hematopoietic stem cell transplantation on pediatric acute myeloid leukemia of FAB subtypes M4 and M5

10.21203/rs.3.rs-30250/v1 ◽

2020 ◽

Author(s):

Yu-juan Xue ◽

Pan Suo ◽

Yi-fei Cheng ◽

Ai-dong Lu ◽

Yu Wang ◽

...

Keyword(s):

Acute Myeloid Leukemia ◽

Stem Cell ◽

High Risk ◽

Myeloid Leukemia ◽

Risk Groups ◽

Low Risk ◽

Intermediate Risk ◽

Hematopoietic Stem ◽

Pediatric Acute Myeloid Leukemia ◽

Acute Myeloid

Abstract Background: FAB-M4 and M5 are unique subgroups of pediatric acute myeloid leukemia. However, for these patients, few studies have demonstrated the clinical and biological characteristics and efficacy of hematopoietic stem cell transplantation (HSCT), and especially haplo-HSCT. Procedure: We retrospectively evaluated the outcomes of 70 children with FAB-M4/M5 enrolled in our center from January 2013 to December 2017. Results: Of the patients, 32, 23, and 15 were in low-risk, intermediate-risk, and high-risk groups, respectively. T(16;16), inv16/CBFB-MYH11 was the most frequent cytogenetic abnormality. Among detected genetic alterations, WT1 was mutated at the highest frequency, followed by FLT3-ITD, NPM1, and CEBPA. Thirty-three patients received HSCT (haplo-HSCT = 30), of which four, 18, and 11 were in low-risk, intermediate-risk, and high-risk groups, respectively. For all patients, the 3-year overall survival (OS), event-free survival (EFS), and cumulative incidence of relapse (CIR) were 85.3 ± 4.3%, 69.0 ± 5.7%, and 27.9 ± 5.2%, respectively. By multivariate analysis, low-risk stratification predicted superior OS, EFS, and PLT ≤ 50 × 109/L at diagnosis, with FLT3-ITD mutations predicting higher CIR and poorer EFS. In intermediate- and high-risk groups, HSCT was independently associated with higher EFS and lower CIR. With a median post-transplant observation time of 30.0 months, the 3-year OS, EFS, CIR, and non-relapse mortality in the haplo-HSCT group were 74.2 ± 8.6%, 68.3 ± 8.9, 24.6 ± 7.6%, and 6.6 ± 4.1%, respectively. Conclusions: Risk-oriented treatment is important for pediatric FAB-M4/M5. For intermediate- and high-risk groups, HSCT significantly improved survival and haplo-HSCT might be a viable alternative approach.

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Reduced TET2 expression in Patients with Myelodysplastic Syndromes and Acute Myeloid Leukemia.

Blood ◽

10.1182/blood.v120.21.2822.2822 ◽

2012 ◽

Vol 120 (21) ◽

pp. 2822-2822

Author(s):

Renata Scopim-Ribeiro ◽

Joao Machado-Neto ◽

Paula de Melo Campos ◽

Patricia Favaro ◽

Adriana S. S. Duarte ◽

...

Keyword(s):

Gene Expression ◽

Overall Survival ◽

High Risk ◽

Myeloid Leukemia ◽

Research Funding ◽

Erythroid Differentiation ◽

Low Risk ◽

High Risk Disease ◽

Cd34 Cells ◽

Acute Myeloid

Abstract Abstract 2822 Introduction: Acquired mutations in TET2 and DNMT3A have been found in myelodysplastic syndromes (MDS) and acute myeloid leukemia (AML), and may predict a worse survival in these diseases. TET2 mutations are considered to be a loss-of-function mutation and results in decreased 5-hydroxymethylcitosine (5-hmc) levels. In normal CD34+ cells, TET2 silencing skews progenitor differentiation towards the granulomonocytic lineage at the expense of lymphoid and erythroid lineages. Dnmt3a participates in the epigenetic silencing of hematopoietic stem cell regulatory genes, enabling efficient differentiation. Here, we attempted to evaluate the expression of TET2 and DNMT3A in total bone marrow cells from normal donors, patients with MDS and AML, and in CD34+ cells from MDS and normal controls during erythroid differentiation. Materials and Methods: The study included normal donors (n = 21), patients with MDS (n = 43) and AML (n = 42) at diagnosis. All normal donors and patients provided informed written consent and the study was approved by the ethics committee of the Institution. MDS patients were stratified into low and high-risk according to WHO classification (RCUD/RCMD/RARS=31 and RAEB1/RAEB2=12). TET2 and DNMT3A mRNA expression was assessed by quantitative PCR. CD34+ cells from normal donors (n = 9) and low-risk MDS patients (n = 7) were submitted to erythroid differentiation. Cells were collected and submitted to immunophenotyping for GPA and CD71 (days 6 and 12) and q-PCR for TET2 and DNMT3A expression (days 6, 8 and 12). Results of gene expression in normal donors and patients are presented as median, minimum-maximum, and were compared using Mann-Whitney test. Student t test was used for comparison of gene expression during CD34+ erythroid diferentiation. Overall survival was defined from the time of sampling to the date of death or last seen. Univariate analysis for overall survival was conducted with the Cox proportional hazards model. Results: TET2 expression was significantly reduced in both AML (0.62; 0.01–32.69) and MDS (1.46; 0.17–21.30) compared to normal donors (2.72; 0.43–31.49); P<0.0001 and P=0.01, respectively. TET2 expression was also significantly reduced in AML compared to MDS (P=0.0007). MDS patients were stratified into low and high-risk disease, and we still observed a significant reduction in TET2 expression in high-risk (0.73, 0.17–7.25) when compared to low-risk (1.58; 0.48–21.30; P=0.02) patients, but no difference was noted between normal donors vs. low-risk MDS, and high-risk MDS vs. AML. In MDS cohort, the median overall survival was 14 months (range 1–83), increased TET2 expression was associated with a longer survival (HR, 0.44; 95% CI, 0.21–0.91, P=0.03), and, as expected, WHO high-risk disease was associated with a shorter survival (HR, 10.16; 95% CI, 3.06–33.72, P<0.001), even though the confidence interval (CI) was large. TET2 expression did not impact survival in our cohort of AML patients. The erythroid differentiation was effective in cells from normal donors and MDS patients, as demonstrated by the flow cytometry analyses of GPA and CD71. TET2 expression was significantly increased on day 12 of erythroid differentiation, P<0.05. On the other hand, DNMT3A expression was similar between normal donors (0.74; 0.22–1.53), MDS (0.78; 0.26–3.46) and AML (0.95, 0.15–6.46), and during erythroid differentiation, with no impact on survival. Conclusion: These data suggest that decreased TET2 expression may participate in leukemogenesis, and supports the participation of TET2 in the erythroid differentiation of MDS. DNMT3A was not differentially expressed in AML and MDS, indicating that the presence of mutations in this gene may be the predominant mechanism of changes in protein function. We thus suggest that decreased TET2 expression may explain the reduced levels of 5-hmc found in TET2 wild type patients, and may become a predictive marker for outcomes in MDS and other myeloid diseases. Further studies would be necessary to better elucidate the clinical relevance and biologic significance of our findings, and whether the decreased TET2 expression results in hypermethylation in these diseases. Disclosures: Maciejewski: NIH: Research Funding; Aplastic Anemia&MDS International Foundation: Research Funding.

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Early immunophenotypical evaluation of minimal residual disease in acute myeloid leukemia identifies different patient risk groups and may contribute to postinduction treatment stratification

Blood ◽

10.1182/blood.v98.6.1746 ◽

2001 ◽

Vol 98 (6) ◽

pp. 1746-1751 ◽

Cited By ~ 225

Author(s):

Jesús F. San Miguel ◽

Marı́a B. Vidriales ◽

Consuelo López-Berges ◽

Joaquı́n Dı́az-Mediavilla ◽

Norma Gutiérrez ◽

...

Keyword(s):

Acute Myeloid Leukemia ◽

High Risk ◽

Minimal Residual Disease ◽

Myeloid Leukemia ◽

Residual Disease ◽

Response To Therapy ◽

Low Risk ◽

Prognostic Impact ◽

Minimal Residual ◽

Acute Myeloid

Abstract Early response to therapy is one of the most important prognostic factors in acute leukemia. It is hypothesized that early immunophenotypical evaluation may help identify patients at high risk for relapse from those who may remain in complete remission (CR). Using multiparametric flow cytometry, the level of minimal residual disease (MRD) was evaluated in the first bone marrow (BM) in morphologic CR obtained after induction treatment from 126 patients with acute myeloid leukemia (AML) who displayed aberrant phenotypes at diagnosis. Based on MRD level, 4 different risk categories were identified: 8 patients were at very low risk (fewer than 10−4 cells), and none have relapsed thus far; 37 were at low risk (10−4 to 10−3 cells); and 64 were at intermediate risk (fewer than 10−3 to 10−2 cells), with 3-year cumulative relapse rates of 14% and 50%, respectively. The remaining 17 patients were in the high-risk group (more than 10−2 residual aberrant cells) and had a 3-year relapse rate of 84% (P = .0001). MRD level not only influences relapse-free survival but also overall survival (P = .003). The adverse prognostic impact was also observed when M3 and non-M3 patients with AML were separately analyzed, and was associated with adverse cytogenetic subtypes, 2 or more cycles to achieve CR, and high white blood cell counts. Multivariate analysis showed that MRD level was the most powerful independent prognostic factor, followed by cytogenetics and number of cycles to achieve CR. In conclusion, immunophenotypical investigation of MRD in the first BM in mCR obtained after AML induction therapy provides important information for risk assessment in patients with AML.

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Integrative prognostic risk score in acute myeloid leukemia with normal karyotype

Blood ◽

10.1182/blood-2010-08-303479 ◽

2011 ◽

Vol 117 (17) ◽

pp. 4561-4568 ◽

Cited By ~ 71

Author(s):

Frederik Damm ◽

Michael Heuser ◽

Michael Morgan ◽

Katharina Wagner ◽

Kerstin Görlich ◽

...

Keyword(s):

Acute Myeloid Leukemia ◽

High Risk ◽

Risk Score ◽

Myeloid Leukemia ◽

Risk Group ◽

Normal Karyotype ◽

Risk Groups ◽

Risk Of Death ◽

Risk Patients ◽

Acute Myeloid

Abstract To integrate available clinical and molecular information for cytogenetically normal acute myeloid leukemia (CN-AML) patients into one risk score, 275 CN-AML patients from multicenter treatment trials AML SHG Hannover 0199 and 0295 and 131 patients from HOVON/SAKK protocols as external controls were evaluated for mutations/polymorphisms in NPM1, FLT3, CEBPA, MLL, NRAS, IDH1/2, and WT1. Transcript levels were quantified for BAALC, ERG, EVI1, ID1, MN1, PRAME, and WT1. Integrative prognostic risk score (IPRS) was modeled in 181 patients based on age, white blood cell count, mutation status of NPM1, FLT3-ITD, CEBPA, single nucleotide polymorphism rs16754, and expression levels of BAALC, ERG, MN1, and WT1 to represent low, intermediate, and high risk of death. Complete remission (P = .005), relapse-free survival (RFS, P < .001), and overall survival (OS, P < .001) were significantly different for the 3 risk groups. In 2 independent validation cohorts of 94 and 131 patients, the IPRS predicted different OS (P < .001) and RFS (P < .001). High-risk patients with related donors had longer OS (P = .016) and RFS (P = .026) compared with patients without related donors. In contrast, intermediate-risk group patients with related donors had shorter OS (P = .003) and RFS (P = .05). Donor availability had no impact on outcome of patients in the low-risk group. Thus, the IPRS may improve consolidation treatment stratification in CN-AML patients. Study registered at www.clinicaltrials.gov as #NCT00209833.

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Novel prognostic genes and subclasses of acute myeloid leukemia revealed by survival analysis of gene expression data

BMC Medical Genomics ◽

10.1186/s12920-021-00888-0 ◽

2021 ◽

Vol 14 (1) ◽

Author(s):

Yanli Lai ◽

Guifang OuYang ◽

Lixia Sheng ◽

Yanli Zhang ◽

Binbin Lai ◽

...

Keyword(s):

Gene Expression ◽

Overall Survival ◽

Acute Myeloid Leukemia ◽

Network Analysis ◽

Risk Score ◽

Myeloid Leukemia ◽

The Cancer Genome Atlas ◽

Prognostic Biomarkers ◽

High Expression ◽

Acute Myeloid

Abstract Background Acute myeloid leukemia (AML) is biologically heterogeneous diseases with adverse prognosis. This study was conducted to find prognostic biomarkers that could effectively classify AML patients and provide guidance for treatment decision making. Methods Weighted gene co-expression network analysis was applied to detect co-expression modules and analyze their relationship with clinicopathologic characteristics using RNA sequencing data from The Cancer Genome Atlas database. The associations of gene expression with patients’ mortality were investigated by a variety of statistical methods and validated in an independent dataset of 405 AML patients. A risk score formula was created based on a linear combination of five gene expression levels. Results The weighted gene co-expression network analysis detected 63 co-expression modules. The pink and darkred modules were negatively significantly correlated with overall survival of AML patients. High expression of FNDC3B, VSTM1 and CALR was associated with favourable overall survival, while high expression of PLA2G4A was associated with adverse overall survival. Hierarchical clustering analysis of FNDC3B, VSTM1, PLA2G4A, GOLGA3 and CALR uncovered four subgroups of AML patients. The cluster1 AML patients showed younger age, lower cytogenetics risk, higher frequency of NPM1 mutations and more favourable overall survival than cluster3 patients. The risk score was demonstrated to be an indicator of adverse prognosis in AML patients Conclusions The FNDC3B, VSTM1, PLA2G4A, GOLGA3, CALR and risk score may serve as key prognostic biomarkers for the stratification and ultimately guide rational treatment of AML patients.

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