scholarly journals Copy Number Alteration Profile Provides Additional Prognostic Value for Acute Lymphoblastic Leukemia Patients Treated on BFM Protocols

Cancers ◽  
2021 ◽  
Vol 13 (13) ◽  
pp. 3289
Author(s):  
Μirella Αmpatzidou ◽  
Lina Florentin ◽  
Vassilios Papadakis ◽  
Georgios Paterakis ◽  
Marianna Tzanoudaki ◽  
...  

We present our data of a novel proposed CNA-profile risk-index, applied on a Greek ALLIC-BFM-treated cohort, aiming at further refining genomic risk-stratification. Eighty-five of 227 consecutively treated ALL patients were analyzed for the copy-number-status of eight genes (IKZF1/CDKN2A/2B/PAR1/BTG1/EBF1/PAX5/ETV6/RB1). Using the MLPA-assay, patients were stratified as: (1) Good-risk(GR)-CNA-profile (n = 51), with no deletion of IKZF1/CDKN2A/B/PAR1/BTG1/EBF1/PAX5/ETV6/RB1 or isolated deletions of ETV6/PAX5/BTG1 or ETV6 deletions with a single additional deletion of BTG1/PAX5/CDKN2A/B. (2) Poor-risk(PR)-CNA-profile (n = 34), with any deletion of ΙΚΖF1/PAR1/EBF1/RB1 or any other CΝΑ. With a median follow-up time of 49.9 months, EFS for GR-CNA-profile and PR-CNA-profile patients was 96.0% vs. 57.6% (p < 0.001). For IR-group and HR-group patients, EFS for the GR-CNA/PR-CNA subgroups was 100.0% vs. 60.0% (p < 0.001) and 88.2% vs. 55.6% (p = 0.047), respectively. Among FC-MRDd15 + patients (MRDd15 ≥ 10−4), EFS rates were 95.3% vs. 51.7% for GR-CNA/PR-CNA subjects (p < 0.001). Similarly, among FC-MRDd33 + patients (MRDd33 ≥ 10−4), EFS was 92.9% vs. 27.3% (p < 0.001) and for patients FC-MRDd33 − (MRDd33 < 10−4), EFS was 97.2% vs. 72.7% (p = 0.004), for GR-CNA/PR-CNA patients, respectively. In a multivariate analysis, the CNA-profile was the most important outcome predictor. In conclusion, the CNA-profile can establish a new genomic risk-index, identifying a distinct subgroup with increased relapse risk among the IR-group, as well as a subgroup of patients with superior prognosis among HR-patients. The CNA-profile is feasible in BFM-based protocols, further refining MRD-based risk-stratification.

2020 ◽  
Vol 14 (4) ◽  
pp. 115
Author(s):  
Adhitya Bayu Perdana ◽  
Fahreza Saputra ◽  
Mururul Aisyi

Childhood cancer has been a global public health scourge with considerably escalating incidence each year [1]. Although the incidence is relatively lower compared to adult malignancies, it remains the leading cause of disease-related death in children. The most frequent childhood cancer is acute lymphoblastic leukemia (ALL) with an annual incidence of 3.5 per 100,000 children in the United States [2]. Similarly, in Indonesia, ALL has the highest number of cancer cases in children [3]. The total incidence of ALL in Indonesia reaches 2.5-4.0 per 100,000 children with an estimated 2,000-3,200 annually [4]. Because of its high incidence and curability, ALL is a logical initial objective for childhood cancer program developments in Indonesia. As an indicator of successful treatment of childhood ALL, the 5-year survival rate shows contrasting figures between high-income (HIC) and lower-middle-income countries (LMIC). In the United States and most European countries, the survival rates are approximately 90% and 85% respectively. However, in Southeast Asian countries, the highest 5-year survival rate for children aged 0 to 14 was reported in Malaysia (69.4%), followed by Thailand (55.1%) [5]. Furthermore, more unfavorable results were reported in Indonesia. Studies from Dharmais Cancer Hospital and Dr. Sardjito Hospital reported the 5-year survival rate of 28.9% and 31.8% respectively [6,7]. The outcome difference between Indonesia and other countries is probably due to the high rate of relapse occurrence and toxic death during the treatment. Some studies revealed the factors that affecting the worst outcome of childhood ALL in LMIC include inadequate and delayed diagnosis, limited healthcare access, treatment abandonment, and suboptimal supportive care [8]. As pediatric oncologists in HIC have become more effective at treating childhood ALL, much of the research attempts concentrated on the risk stratification of the patients. The term “risk stratification” is used to allocate the patients into various risk groups based on the notable prognostic features for specific treatment administration. Patients with a high-risk assessment could be targeted for more aggressive treatments, while patients with lower risk could be treated less intensively to avoid the side effects and toxicities [9]. In Indonesia, risk stratification strategy encompasses clinical-hematologic parameters (age, leukocyte count, extramedullary involvement), and conventional morphological examination. These assessments represent the first step in the diagnostic pathway of ALL. Though helpful, in certain cases, the residual leukemic cells might be undetectable under bone marrow morphology examination. This led to more underdiagnosed cases, thus more patients were subjected to inadequate treatment. Fortunately, immunophenotyping is currently applied to improve the diagnosis of childhood ALL by grouping the patients based on the aberrant expression of leukemic cell antigen, even though its application is only available in several centers including Dharmais Cancer Hospital. The BCR-ABL1 fusion gene examination by PCR-based techniques has also routinely been implemented to predict the poor outcome since it was detected in 12% of childhood ALL patients [10]. However, the current above-mentioned strategy is insufficient to solve the accuracy of risk stratification of childhood ALL. In HIC, childhood ALL are classified by more comprehensive examination involving morphology, immunophenotyping, cytogenetics, and molecular techniques. The approach to classifying prognosis and to personalize treatment based on the underlying genetic biology has already implemented for understanding the pathogenesis of childhood ALL. According to studies, the molecular features of childhood ALL have been shown to have a significant prognostic value [11], and the survival rate was improved when genetic examinations are applied [12]. In recent years, high-resolution array-based genomic technologies have revolutionized the understanding of the genetic basis of childhood ALL. Several biomarkers have successfully been identified that are provenly associated with poor prognosis in childhood ALL, including the deletion/mutation of IKZF1 (IKAROS), CDKN2A, ETV6, EBF1, JAK2, and many more [13]. The majority of these genetic changes were originally identified by sophisticated methods such as single nucleotide polymorphism (SNP) arrays, gene expression profiling (GEP), array-based comparative genomic hybridization (aCGH), and more recently next-generation sequencing (NGS) [14]. Despite being highly sensitive for detection of multiple copy number changes, these approaches are not feasible for routine diagnostic use in LMIC which requires significant EDITORIAL Indonesian Journal of Cancer, Vol 14(4), 115–116, December 2020 DOI: http://dx.doi.org/10.33371/ijoc.v14i4.818 www.indonesianjournalofcancer.or.id P-ISSN: 1978-3744 E-ISSN: 2355-6811 116 | financial investment. Therefore, molecular techniques that suit available resources and infrastructure should be developed in LMIC, and most importantly the cost should be affordable for patients. One feasible method is Multiplex Ligation-dependent Probe Amplification (MLPA). MLPA is a rapid multiplex PCR-based technique that enables the comparative analysis of multiple mutation spots [15]. MLPA provides a low-cost, simple alternative to array-based techniques for much routine clinical practice, even though it is unsuitable for whole-genome analysis. Furthermore, one benefit compared to other quantitative PCR-based techniques is that MLPA allows 50 or more different genomic DNA to be analyzed in a single tube reaction. Several studies have demonstrated the implementation of specific MLPA probe mixes for hematological malignancies, including ALL, chronic lymphocytic leukemia (CLL), and myelodysplastic syndrome (MDS). These studies have also shown the sensitive and accurate identification of clinically significant diseasespecific copy number changes [16]. Currently, MLPA has been established as a routine diagnostic of childhood ALL patients in Dharmais Cancer Hospital by a research-based service setting. It reliably detects small focal deletions, even from the low amount of specimens. In general, the results demonstrated the concordance between mutated genes reported in highrisk patients (deletion of IKZF1, CDKN2A, CDKN2B, PAX5). These findings surely can guide the doctors in Dharmais Cancer Hospital to assign the specific patients for the intensive treatment protocol, which is expected to increase the patient’s survival. Therefore, concerning the future clinical application, the inclusion of mutation status by MLPA for childhood ALL risk stratification should be widely promoted to a large health community, especially the Indonesian Pediatric Society, which views this as a consideration for refinement of standard diagnosis protocol for childhood ALL in Indonesia.


Blood ◽  
2019 ◽  
Vol 134 (Supplement_1) ◽  
pp. 1473-1473
Author(s):  
Thomas Creasey ◽  
Amir Enshaei ◽  
Kathryn Watts ◽  
Gavin Cuthbert ◽  
Claire Schwab ◽  
...  

Acute lymphoblastic leukemia (ALL) is characterised by a number of recurrent chromosomal abnormalities which inform prognosis. Low hypodiploidy (HoTr) and high hyperdiploidy (HeH) are genetic subgroups associated with large non-random ploidy shifts, specifically 30-39 chromosomes and 51-65 chromosomes respectively. HoTr ALL often presents with a near triploid karyotype of 60-78 chromosomes through chromosomal endoreduplication without cytokinesis. This presents a diagnostic challenge in distinguishing this poor risk entity from good risk HeH ALL. To date, classification of such challenging cases has been based on the modal chromosome number, the pattern of specific gains, and identification of loss of heterozygosity (LOH) using single nucleotide polymorphism (SNP) arrays where possible. However, loss of cellular context and mixed cell populations (normal diploid, low hypodiploid and near-triploid) when analysing SNP arrays can pose additional analytical difficulty. The aim of this SNP array study was to (1) determine the level of inaccurate genetic subgrouping when cytogenetics only was used to distinguish HeH from doubled up HoTr and (2) develop a diagnostic algorithm to reliably call HeH and HoTr without supporting cytogenetic analysis. SNP arrays were performed on diagnostic ALL samples of 85 patients (46 HoTr, 39 HeH) using Illumina CytoSNP 850k (n=80) or Affymetrix Cytoscan HD (n=5) arrays. Probe level data were uploaded to Nexus Copy Number 10 (BioDiscovery) and manual segments spanning the length of each chromosome were created. No further data pre-processing was carried out and log2 ratio of 0 was automatically assigned to the median log2 ratio of the sample. Chromosomal log2 ratios were normalized within each sample and a variety of machine-learning techniques used to cluster the samples independently of assigned diagnosis. Cases residing in the incorrect cluster based on initial diagnosis were examined in detail using information from cytogenetics and SNP array interpretation. SNP arrays were analysed from 46 HoTr (median age 50.5 years (range 7-87), 43% male) and 39 HeH (median age 7 years (range 1-58), 56% male) patients. Unsupervised clustering of log2 ratios showed a clear distinction between HeH and HoTr patients (figure (A)). Six cases clustered incorrectly based on cytogenetic diagnosis. After detailed interpretation of all cases, including identifying LOH affecting chromosomes 3, 7, 15, 16 and 17, 3/6 cases initially classified as HeH were highly suggestive of HoTr ALL despite having &lt;60 chromosomes. Similarly, 1/6 cases was cytogenetically diagnosed with HoTr but had a SNP array pattern typical of HeH ALL. We identified chromosomes 1, 4, 11, 17, 19, and 21 as those contributing most to the distinction in the HoTr and HeH signatures with the log2 ratio of chromosome 1 the most highly discriminatory in this cohort. Using whole chromosome log2 ratios, HoTr and HeH ALL have distinct profiles. SNP array analysis highlighted at least 4 patients whose ploidy subgroups appeared incorrectly called by cytogenetics, which can affect risk stratification. Crucially, these data call into question the accepted modal chromosome numbers for HeH and HoTr in the near triploid phase and suggest this alone cannot be used to classify patients into these ploidy groups. All samples incorrectly classified as HeH ALL were from adults aged &gt;40 years, suggesting this good risk subgroup is even rarer than previously thought in older adults. After re-classification, our cohort only contained 5/41 adults &gt;40 years with HeH ALL, signifying that HoTr ALL is the commonest genetic ploidy group in older adults with ALL and must still be considered in cases with 50-60 chromosomes. Copy number analysis from SNP arrays is challenging in samples with marked ploidy shift and mixed cell populations. Importantly, a number of our samples had significant contaminating normal DNA and LOH could not be confirmed visually (figure (B)), underlying the need for additional factors to aid classification. Our analysis only takes into account log2 ratio of entire chromosomes, thus permitting a measure of the relative over and under-representation of specific chromosomes within the sample. This method accurately clusters patients even when LOH cannot be clearly visualized from B-allele frequency due to contaminating non-leukemic DNA and supports the development of a diagnostic classifier based on chromosomal log2 ratios. Disclosures Fielding: Amgen: Consultancy; Novartis: Consultancy; Pfizer: Consultancy; Incyte: Consultancy.


2019 ◽  
Vol 3 (2) ◽  
pp. 148-157 ◽  
Author(s):  
Lina Hamadeh ◽  
Amir Enshaei ◽  
Claire Schwab ◽  
Cristina N. Alonso ◽  
Andishe Attarbaschi ◽  
...  

Abstract Genetic abnormalities provide vital diagnostic and prognostic information in pediatric acute lymphoblastic leukemia (ALL) and are increasingly used to assign patients to risk groups. We recently proposed a novel classifier based on the copy-number alteration (CNA) profile of the 8 most commonly deleted genes in B-cell precursor ALL. This classifier defined 3 CNA subgroups in consecutive UK trials and was able to discriminate patients with intermediate-risk cytogenetics. In this study, we sought to validate the United Kingdom ALL (UKALL)–CNA classifier and reevaluate the interaction with cytogenetic risk groups using individual patient data from 3239 cases collected from 12 groups within the International BFM Study Group. The classifier was validated and defined 3 risk groups with distinct event-free survival (EFS) rates: good (88%), intermediate (76%), and poor (68%) (P &lt; .001). There was no evidence of heterogeneity, even within trials that used minimal residual disease to guide therapy. By integrating CNA and cytogenetic data, we replicated our original key observation that patients with intermediate-risk cytogenetics can be stratified into 2 prognostic subgroups. Group A had an EFS rate of 86% (similar to patients with good-risk cytogenetics), while group B patients had a significantly inferior rate (73%, P &lt; .001). Finally, we revised the overall genetic classification by defining 4 risk groups with distinct EFS rates: very good (91%), good (81%), intermediate (73%), and poor (54%), P &lt; .001. In conclusion, the UKALL-CNA classifier is a robust prognostic tool that can be deployed in different trial settings and used to refine established cytogenetic risk groups.


Blood ◽  
2014 ◽  
Vol 124 (9) ◽  
pp. 1434-1444 ◽  
Author(s):  
Anthony V. Moorman ◽  
Amir Enshaei ◽  
Claire Schwab ◽  
Rachel Wade ◽  
Lucy Chilton ◽  
...  

Key Points Integrating cytogenetic and genomic data in pediatric ALL reveals 2 subgroups with different outcomes independent of other risk factors. A total of 75% of children on UKALL2003 had a good-risk genetic profile, which predicted an EFS and OS of 94% and 97% at 5 years.


Blood ◽  
2007 ◽  
Vol 110 (11) ◽  
pp. 4228-4228
Author(s):  
Murtadha Al-Khabori ◽  
Samira Samiee ◽  
Sharon Fung ◽  
Wei Xu ◽  
Joseph Brandwein ◽  
...  

Abstract We retrospectively reviewed our experience of 63 adult T-ALL patients to identify clinical and pathologic prognostic factors and build a risk-stratification model for induction chemotherapy. At presentation, the patients’ median age was 30, 49 were male and 14 female, 69% had lymphadenopathy, 38% a mediastinal mass, 24% CNS involvement and 21% splenomegaly. The median initial WBC was 17.9 x 109/L (range 0.10–510.0). Blasts expressed CD34 in 42% of cases, CD10 in 33% and at least one myeloid-associated antigen (CD13 or CD33) in 27%. Karyotypes were abnormal in 34% of cases. Fifty-three of 61 patients (87%) who underwent induction chemotherapy achieved complete remission (CR) on protocols including vinca alkaloids, anthracyclines and corticosteroids. On univariate analysis; age, gender, initial WBC, CD10, CD34 and abnormal karyotype did not predict CR but patients expressing at least one myeloid-associated antigen had a CR of 71% compared to 93% (P=0.03) for patients not expressing myeloid antigens. The median follow-up was 19.2 months (95% CI: 0.1–172.8). Twenty-three patients relapsed with a median relapse-free survival (RFS) of 41.6 months (95%CI: 21.6–55.9). The RFS was longer for patients with an initial WBC of 3–50 x 109 and for cases expressing CD10 but neither was statistically significant (P=0.19, P=0.14). On follow-up, 34 patients died with a median overall survival (OS) of 31.3 months (95%CI: 16.8–56.8). Patients with CD10 expression had a longer median OS at 44.7 months (versus 19.2 months for CD10 negative patients) but again, the difference was not statistically significant (P=0.11). Age, gender, CD34, myeloid-associated antigen expression and karyotype did not influence RFS or OS. Our study indicates that expression of myeloid-associated antigens is an adverse prognostic factor for complete remission of adult T-ALL and should be considered for induction chemotherapy risk-stratification.


Blood ◽  
2021 ◽  
Vol 138 (Supplement 1) ◽  
pp. 4119-4119
Author(s):  
Rema Ganapathy ◽  
Aswathy Ashok Beenakumari ◽  
Syamaprasad Vinayakumar ◽  
Remya Sudevan ◽  
Renjitha Bhaskaran ◽  
...  

Abstract Background: Children with Acute Lymphoblastic Leukemia (ALL) in Low Middle income countries(LMIC) face major challenges including treatment abandonment and poor overall survival (OS) and event-free survival (EFS).The preliminary data and results of outcome of Pediatric ALL from our pediatric hematology-oncology center which follows BFM based ALLtreatment protocol has been published in 2015 in ASH forum.Due to non availability of Polymerase chain reaction (PCR)based Minimal residual disease(MRD)analysis, we use multiparametric flowcytometry (FCM) based MRD analysis for remission assessment and risk stratification in our patients. Within resource constraints, we present evidence that outcomes comparable with that seen in high income (HIC)and upper middle income countries(UMIC) can be achieved with a post remission therapy guided by a risk stratification incorporating FCM MRD. Methods: Following IRB approval,an ambidirectional cohort study was performed using clinical information and outcomes of all patients aged 1to 14 years treated for newly diagnosed B- or T-ALL between January 1,2015 and December 31, 2020. AIEOP BFM ALL 2009 protocol with modifications was followed as the institutional protocol in all patients.The treatment algorithm is mentioned in Figure 1. Patients who underwent multiparametric FCM MRD analysis at the end of Induction IA and whose 6 months follow up details were available were included in the analysis. Patients with Ph positive ALL and those who died during Induction IA were excluded. FCM MRD analysis was performed after Induction IA on Day 33.MRD level above 0.01% was considered positive.MRD assessment was repeated following Induction IB on Day 74 in patients who had MRD positivity on Day 33. At the end of Induction IB patients were risk stratified into High risk(HR) and non High risk(Non HR).HR features included Hypodiploidy(&lt;45chromosomes), Positivity for MLL/AF4 or t(4:11),poor prednisolone response(absolute blast count in peripheral blood ≥1 x 10^9/l on Day 8 of initiation of prednisolone) and non remission on Day33. Patients who had persistent MRD positive on Day74 were reallocated to high risk. Treatment with HR protocol was initiated for high risk patients whenever financially manageable.Statistical analysis was done using SPSS version 21 OS and EFS were assessed by Kaplan-Meier method Patients were censored at last follow-up. Results: Median follow-up time was 33.5(4-102) months . Study had 102(n=102) consecutive Ph negative patients who underwent induction therapy. Six patients (5.88%) died during induction IA;96(n=96) children who continued treatment were included in further analysis. The mean age at diagnosis was 6(1-14) years .Forty seven (48.95%)patients were male..B-ALL n=84(87.5%) and T ALL n=12.(12.5%). Four patients(4.16%) had CNS disease at diagnosis. Three children (3.13%) had high risk cytogenetics.Ten children (10.42%)in the cohort had poor prednisolone response. Five patients(5.20%) didnot achieve morphological remission on Day33. Fifteen (15.63%) patients were risk stratified as HR during IA. Four more (4.16%) were reallocated to HR in view of persistent MRD positivity after Induction IB. At median follow-up, the OS was 95.35%±2.65(95% CI 90.16-100.54) and the EFS 94.48%±2.74 (95% CI, 89.11%-99.84%).Female gender predicted better EFS (p=0.042).The EFS of patients without CNS disease at presentation was significantly better(93.5% Vs 23.2% p=0.000). The EFS at median follow up of patients in re HR cohort was 64.19% Vs 97.81% in non HR (p=0.010). EFS by risk stratification is shown in Figure II. Conclusion:Our study suggests that FCM MRD can be successfully incorporated into the treatment algorithm in a resource limited setting. With FCM MRD were able to identify an additional subset of HR patients who otherwise would have been stratified into non HR group. In a prospective cohort , FCM MRD could be tested at an earlier time point in IA induction to facilitate identification of early drug responsive patients with lowest risk of relapse. Figure 1 Figure 1. Disclosures No relevant conflicts of interest to declare.


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