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Introduction The hallmark of CML is BCR-ABL1 (breakpoint cluster region gene-Abelson murine leukemia viral oncogene homolog 1) on Philadelphia chromosome, which is the result of a reciprocal translocation between the long arms of chromosomes 9 and 22 (t[9;22][q34;q11]) [1]. Chromosome 22 breakpoints influence the BCR portions preserved in the BCL-ABL1 fusion mRNA and protein and are mainly localized to one of three BCRs, namely major-BCR (M-BCR), minor BCR (m-BCR) and micro-BCR (µ-BCR). In comparison, breaks in chromosome 9 arise most frequently by alternative splicing of the two first ABL1 exons, and can also be generated in a large genetic region, upstream of exon Ib at the 5' end, or downstream of exon Ia at the 3' end. In the majority of CML cases, the breakpoint lies within the M-BCR and gives rise to e13a2 or e14a2 fusion mRNAs (previously denoted as b2a2 and b3a2) and a p210BCR-ABL fusion protein [2]. [3] Methodology We conducted a retrospective analysis of the files of 79 patients being treated in our center for CML with known BCR-ABL1 breakpoints; there were few more patients with known transcript type but excluded because either travelled immediately on diagnosis or had a failure due to confirmed compliance issues. Patients' management and response assessment was done based on ELN 2013 guidelines. The analysis is done based on two main groups, obese versus normal BMI, and then based on BCR-ABL1 transcripts: e13a2 versus e14a2. Ethical approval was obtained from Medical Research Center for Hamad Medical Corporation (MRC-01-18-337). Results Patients included 62 males (78.5%) and 17 females (21.5%) with the mean age at diagnosis 38.8±11.8 years (median, 38; range 21 to 69 years). The characteristics (demographics, anthropometric, hematological and clinico-pathological) of the patients and their association with transcript types and obesity are summarized in Table 1. Patient outcomes, cytogenetic and molecular responses The median follow-up was 30 months (range 6 to 196 months) and 38 months (range 3 to 192 months) in normal weight and obesity groups, respectively. The median follow-up was 28 months (range 3 to 196 months) and 39 months (range 10 to 192 months) in e14a2 and e13a2 patients, respectively. A total of 22 patients distributed among different groups ended up leaving the country (censored) after a variable duration of follow-up (6 - 196 months), 18 of them CML-CP, and 4 CML-AP. 3 patients died in our cohort, all of them had e14a2 transcript, one of them was in the normal weight/BMI group, two were in the obesity group. In e14a2 group, more patients were on imatinib at the time of analysis (15 (39.5%) vs 7 (17.1%) in e13a2 group, p = 0.026). The percentage of patients of had to switch TKI was similar in both groups (47.4% vs 53.7%, p = 0.576). However, less patients in e14a2 group had to switch TKI because of failure/progression (10 (55.6%) vs 17 (77.3%), p = 0.145); however, this didn't translate into a significant difference of achieving MMR at 1 year, where in e14a2 group, 10 patients achieved MMR at 1 year (31.3%), same as in e13a2 group (10 patients = 29.3%) p 0.331 (all shown in table 1). When comparing long-term outcomes, there was also no significant difference between groups based on transcript type with regards to MMR (44.7% vs 46.3% in e14a2 vs e13a2 respectively) or DMR (26.3% vs 22% respectively) as shown in figure. In the obesity group, there were 2 patients using ponatinib due to T315I mutation, compared to none in normal weight group. However, there were no significant differences in TKI used, switch of TKI, or reason for switch. Same applies for achieving MMR at 1 year, as 11 patients in the obesity group achieved MMR (28.2%) compared to 9 patients in normal weight group (33.3%), p = 0.778 (as shown in table 1). Regarding the long-term outcomes, more patients in the obesity group achieved MMR (53.2%) compared to normal weight group (34.3%), and this response was faster, but not statistically significant. This difference was less clear with regards to DMR (25.5% in the obesity group compared to 21.9% in normal weight group) as shown in figure. Conclusion In the patient-cohort studied there were no significant differences in molecular response based on transcript type or body weight/BMI. Figure 1 Figure 1. Disclosures No relevant conflicts of interest to declare.

Introduction Chronic myeloid leukemia (CML) is a myeloproliferative neoplasm characterized by the dysregulated production and uncontrolled proliferation of mature and maturing granulocytes with fairly normal differentiation. The hallmark of CML is BCR-ABL1 (breakpoint cluster region gene-Abelson murine leukemia viral oncogene homolog 1) on Philadelphia chromosome, which is the result of a reciprocal translocation between the long arms of chromosomes 9 and 22 (t[9;22][q34;q11]). With rare exceptions, breaks in chromosome 22 localize to one of three BCRs and determine the portions of BCR retained in the BCR-ABL1 fusion mRNA and protein. In contrast, the chromosome 9 breaks can occur over a large genetic region, 5′ of ABL1 exon Ib, 3′ of ABL1 exon Ia, or most commonly between the two alternative first ABL1 exons. In an overwhelming majority of CML patients, the break occurs in the major BCR (M-BCR), generating e13a2 or e14a2 fusion mRNAs and a p210BCR-ABL fusion protein. p230BCR-ABL, the largest of the fusion proteins, corresponds to a break in the micro BCR (μ-BCR), an e19a2 fusion mRNA, and is associated with neutrophilic predominance and possibly less aggressive disease. Molecular monitoring of BCR-ABL1 transcript levels following treatment with tyrosine kinase inhibitors (TKIs) is central to the effective clinical management of patients with CML. BCR-ABL1 transcripts measured at standardized time points is used to define responses at key milestones in treatment allowing early signs of poor adherence or resistance to treatment to be detected and allow for early, effective clinical intervention. Objective The aim of this study is to evaluate response to treatment with standard dose TKI in obese and non-obese CML patients together with BCR-ABL1 transcript type Methodology A retrospective analysis of clinicopathological variables and response to treatment was performed for 37 chronic phase CMLs to compare, obese vs normal weight, and BCR-ABL1 transcript type determined at diagnosis. Patients' management and response assessment was done based on ELN 2013 guidelines. Response to treatment was assessed using RT-qPCR analysis of blood calculated on the International Scale (IS). Various statistical methods used, all Statistical analyses were done using statistical packages SPSS 22.0 (SPSS Inc. Chicago, IL) and Epi-info (Centers for Disease Control and Prevention, Atlanta, GA) software. Results The study cohort included 26 males (70.3%) and 11 females (29.7%) with mean age at diagnosis 36.8 years. 59.5% (n=22) expressed an e14a2 transcript, and 40.5% (n=15) an e13a2 transcript, most patients were started on imatinib, then switched either due to toxicity or failure. Median follow-up was 18 months for both transcript types. WBC, platelet counts, spleen size and Sokal scores at diagnosis, both median and Inter-quartile range (IQR) were observed to be higher in e14a2 compared to e13a2 transcript group, and, lower in obese patients compared patients with normal weight. At one year, patients with e13a2 transcript had higher percentage of CCyR (or better) 60% (95% CI 36.6, 80.3%) compared to e14a2 group 46.7% (95% CI 24.8, 69.9%), however this difference was statistically insignificant (odds ratio =1.71, 95% CI 0.40, 7.29; P=0.464) Overall, there was higher and faster achievement of CCyR and MMR in patients with e13a2 transcript compared to e14a2 transcript, and in the obese vs normal-weight patients. Patients in e13a2 group and obesity group had a lower rate of treatment failure and fewer indications to switch TKI. Of note MMR was observed to be significantly higher in patients of African origin (n=10) compared to patients with Asian ethnicity (50% vs 16%; P=0.038), which could be reflect differences in disease biology. Conclusion In the patient cohort studied an e14a2 BCR-ABL1 transcript type / normal body weight was associated with an inferior outcome when compared to e13a2 transcript / obesity groups Disclosures No relevant conflicts of interest to declare.

Chronic lymphocytic leukemia (CLL) is the most common adult leukemia. It is characterized by the accumulation of CD19+/CD5+ lymphocytes and can have variable outcomes. Richter syndrome (RS) is a lethal complication in CLL patients that results in aggressive B-cell lymphomas, and there are no tests to predict its occurrence. Because alterations in microRNA expression can predict the development and progression of several cancers, we investigated whether dysregulation of specific microRNAs can predict RS in CLL patients. Thus, we compared microRNA expression levels in samples from 49 CLL patients who later developed RS with samples from 59 CLL patients who did not. We found that high expression of miR-125a-5p or low expression of miR-34a-5p can predict ∼50% of RS with a false positive rate of ∼9%. We found that CLL patients predicted to develop RS show either an increase of miR-125a-5p expression (∼20-fold) or a decrease of miR-34a-5p expression (∼21-fold) compared with CLL patients that are not predicted to develop RS. Thus, miR-125a-5p and miR-34a-5p can be valuable predictor markers of RS and have the potential to provide physicians with information that can indicate the best therapeutic strategy for CLL patients.

Background: Chronic Myelocytic Leukemia (CML) is a clonal myeloproliferative disorder characterized by constitutive phosphorylation of Protein Tyrosine kinases (PTKS) that continuously activates multiple proliferative and antiapoptotic signaling pathways. Protein Tyrosine Phosphatases (PTPs) on the other hand is potential natural inhibitory mechanism for regulating the tyrosine kinase activities in which phosphorylation is reciprocally controlled and maintained in equilibrium state by PTKs and PTPs. As a member of PTPs family, Protein Tyrosine Phosphatase Receptor Gamma (PTPRG) was found to act as a tumor suppressor gene. This negative regulatory mechanism of PTPRG was observed to be down-regulated and disabled in CML and one of the possible mechanisms that alter the negative regulatory effect of PTPs is mutations. Several mutations have been identified in PTPs in many different leukemias such as Acute Myeloid Leukemia (AML), Juvenile MyeloMonocytic Leukemia (JMML), Myelodysplasic Syndrome (MDS), B-cell Acute Lymphoblastic Leukemia (B-ALL) and these mutations are associated with hyper-cellular proliferation, disease progression and poor outcome. However, relatively little is known about PTPRG mutations and no studies on CML are available in the literature while mutations inBCR-ABL1tyrosine kinase have been extensively characterized. Thus, understanding the role of PTPRG in antagonizing the PTK phosphorylation of BCR-ABL1 will be important to determine its role in CML development and progression. Aim: 1) To identify potential genetic alterations causing inactivation of PTPRG and 2) correlate the PTPRG findings with patients' response to the Tyrosine kinase Inhibitors. Methods: 16 CML patients, 9 from Qatar and 7 from Italy respectively, were studied for PTPRG mutations by exome sequencing. Custom primers were designed for Human PTPRG gene (5 Kb of exonic region of interest) using Ion AmpliSeq Designer. Target regions were enriched and amplified for the 16 DNA samples using Ion AmpliSeq Library kit 2.0. The amplicons were partially digested with FuPa reagent and phosphorylated prior to ligation of Ion Xpress Barcode Adapters followed by cleanup using HighPrep reagent. The adapter ligated molecules were enriched with adapter specific primers using a limited cycle PCR followed by a cleanup using HighPrep reagent. The final libraries were quantified on Qubit Flurometer using Qubit dsDNA HS Assay Kit and Agilent Bioanalyzer using Agilent High Sensitivity DNA Kit. All samples were pooled according to the concentrations on the Bioanalyzer and loaded on Ion 318TM Chip kit V2 to be sequenced on Ion Personal Genome Machine (PGM) system. European Leukemia Net (ELN) 2013 criteria were employed to assess the response/resistance of patients to treatment. Responses are defined at the hematological, cytogenetic and molecular levels. Patients response was classified into optimal and failure Results: Four mutations/variants were identified in PTPRG genes, three were missense Y92H, G574S, S561Y and 1 was frameshift Y285fs in the 16 CML patients. PTPRG Y92H was identified in 5 (1 Homozygous and 4 heterozygous alleles) patients and the 5 patient failed the Imatinib Mesylate (IM) treatment. On the other hand, The PTPRG G574S was identified in 6 (2 homozygous and 4 heterozygous alleles) patients. Out of the 6 patients, 4 were classified as failure to the treatment and 2 responded optimally. In addition, the PTPRG S561Y and Y285fs were identified on 1 and 3 patients respectively and these patients responded optimally to IM treatment. Discussion and Conclusions: This is the first prospective pilot study to investigate PTPRG gene mutations as underlying mechanism to explain treatment failure. Our preliminary data showed that the identified variant PTPRG Y92H might be associated with IM failure although it has been reported as Single Nucleotide Polymorphisms (SNPs) (rs62620047) and this could be attributed that some polymorphisms might behave like a mutation. On the other hand, PTPRG G574S variant (rs2292245) showed various clinical outcomes regardless to its allele zygosity as 67% (4/6) of patients failed the TKIs treatment. From the results of our pilot study we recommend carrying out PTPRG sequencing in a significantly larger cohort of patients to further explore and pinpoint the crucial mutations that can be correlated with CML resistance/response to treatment. Disclosures No relevant conflicts of interest to declare.