Abstract
Inherited polymorphic sequence variations in drug transport genes like ABCB1 impact a portion of patients with hematologic malignancies that show intrinsic or acquire resistance to treatment. Keeping in view inter-individual sensitivities for such drugs, we through this case–control study tested whether ABCB1 C3435T and G2677T polymorphisms have any influence on the risk and treatment response in patients with chronic myeloid leukemia (CML) and B-acute lymphoblastic leukemia (B-ALL). Genotyping for ABCB1 polymorphisms was performed by polymerase chain reaction-restriction fragment length polymorphism in 100 CML and 80 B-ALL patients along with 100 age and gender matched healthy controls. ABCB1 C3435T and G2677T polymorphism showed no association with CML. Genotype distribution revealed significant higher frequency of TT genotype for both SNPs in B-ALL cases and associated with increased B-ALL risk (OR 2.5, p = 0.04 for 3435TT; OR 2.4, p = 0.04 for 2677TT). There was no significant difference in genotype frequency of 3435C > T and 2677G > T among resistant and responsive groups for the two leukemia types. Kaplan–Meier survival plots revealed significantly lower event free survival in CML and B-ALL patients that were carriers of 3435TT genotype (p < 0.05). Multivariate analysis considered 3435TT genotype as independent risk factor for imatinib resistance in CML cases (HR 6.24, p = 0.002) and increased relapse risk in B-ALL patients (HR 4.51, p = 0.03). The current study provides preliminary evidence of a significant association between variant TT genotype and increased B-ALL risk. Also, results suggest that ABCB1 3435TT genotype increases imatinib resistance in CML and influence therapeutic outcome in B-ALL.
Keywords: Chronic myeloid leukemia, Kashmir, ABCB1, RFLP, BCR-ABL1, Acute lymphoblastic leukemia
Introduction
Leukemia is a heterogeneous disease and its treatment regimen ranges from common drugs such as alkylating agents to specialized target therapy like Tyrosine Kinase Inhibitors (TKIs), besides these other regimes have been reported to be promising [1]. Substantial advancement in the management of hematological malignancies in the past decade has made it possible to cure patients with Acute Lymphoblastic Leukemia (ALL) as well as Chronic Myeloid Leukemia (CML). However, a fraction of patients with different leukemias are intrinsically resistant or in later stages of treatment acquire resistance to various anti-cancer drugs and succumb from the underlying disease within one decade after diagnosis [2]. Failure to respond to the different anti-leukemic drugs reflects not only the patient’s sensitivity to the drugs but may also be determined by inherited polymorphic sequence variations in various genes most notably ATP-binding cassette transporter B1 (ABCB1) gene [3–6].
P-glycoprotein (P-gp) commonly known as ABCB1 is encoded by the multidrug resistance 1 (MDR1) gene [7]. P-gp is a membrane transporter protein that works both as a functional barrier and as an efflux transporter in different tissues and influences the pharmacokinetics of several anti-cancer drugs [8–11]. Polymorphic variants of the ABCB1 gene have been shown to alter function and/or expression of P-gp and its over expression in tumor cells leads to multidrug resistance [12]. Among 50 single nucleotide polymorphisms in the ABCB1 gene, G2677T SNP at exon 21 and C3435T SNP at exon 26 that has been associated with the function of P-gp [12–14]. Previous studies have reported a significant impact of ABCB1 C3435T and G2677T polymorphic sequence variants on clinical outcomes of patients with hematologic malignancies such as CML and ALL [15–17]. Therefore, in order to promote effective therapeutic response and increased survival rates, it is important to understand the critical role of polymorphisms in ABCB1 drug transporters on the outcome of hematological malignancies.
Keeping in view the plausible role of ABCB1 gene sequence variations, we hypothesized that genotypic variation of ABCB1 gene may provide us insight into the molecular differences between patients in terms of their disease susceptibility and response to chemotherapy regimens. In this first of its kind hospital-based case–control study, we tested whether ABCB1 C3435T (rs1045642) and G2677T (rs2032582) polymorphic variants have any influence on the etiology and therapeutic outcome of CML and B-ALL patients of Kashmir (North India).
Materials and Methods
Study Population
The cases enrolled for the study conducted at Department of Immunology and Molecular Medicine include patients diagnosed with CML and B-ALL from Kashmir who visited the outpatient clinic or inpatient wards of departments of Medical Oncology and Clinical Hematology, Sher-i-Kashmir Institute of Medical Sciences (SKIMS), J&K (North India) from November 2014 to May 2019. The patient group comprised of 100 newly diagnosed CML patients [46 males and 54 females; median age 41.6 ± 1.41 years (range 10–81 years)] and 80 B-ALL patients [(49 males and 31 females; median age 14 ± 1.13 years (range 2–58 years)]. All patients were assessed clinically and diagnosed by standard methods like Giemsa stained peripheral blood picture, bone marrow analysis, peripheral blood/bone marrow cytogenetic detection of t (9;22) in CML cases and hallmark translocations/other chromosomal changes in ALL patients. Diagnosis in CML patients was confirmed by molecular detection of BCR-ABL1 fusion gene transcripts from peripheral blood/bone marrow by reverse transcriptase polymerase chain reaction standard protocol [18]. The corresponding BCR-ABL1 transcripts were quantified by real-time quantitative PCR (Rq-PCR) using Genosen’s BCR-ABL1 quantitative kits (Genome Diagnostics, India) according to international log reduction scale. For ALL patients, diagnosis was confirmed by determining B-cell subtypes of ALL by Immunophenotyping. Patient details were collected by personal interaction with the patients and laboratory parameters like total leukocyte count (TLC), differential leukocyte count (DLC), Platelet counts and blast cell counts were recorded from the routine complete blood cell (CBC)/bone marrow reports.
Out of the 100 CML cases, 90 patients presented with chronic phase (CP) CML, 08 were in accelerated phase (AP) and 02 progressed to blast crisis (BC). Patients were treated with different imatinib concentrations (400 mg for CP and 600–800 mg for AP/BC patients). Response to imatinib was assessed as per the standard protocol by Rq-PCR at 3, 6, 12 months and thereafter every 6 months. In our study, 74 patients responded to imatinib treatment and 26 were resistant. Patients with CML were categorized as being imatinib responders or resistant according to the European Leukemia Recommendations of 2013 according to which BCR-ABL1 transcript levels ≤ 10% at 3 months, < 1% at 6 months, and ≤ 0.1% from 12 months onward define optimal response, whereas > 10% at 6 months and > 1% from 12 months onward was considered as being resistant to imatinib, mandating a change in treatment [19]. Patients with B-ALL were risk stratified into low, medium and high risk groups and treated according to modified BFM-95 protocol [20, 21]. All the patients were evaluated at baseline, after consolidation and during as well as after maintenance stage of treatment for their response to chemotherapy. The evaluation of the response was based on bone marrow/peripheral blood blast cell counts. Generally, bone marrow leukemic blasts < 5% with restoration of normal hematopoiesis was predictive of the attainment of complete molecular remission. Re-emergence of leukemic blasts in the marrow and deranged hematopoiesis during or after treatment was indicative of leukemic relapse [21, 22]. Out of the 80 patients, 69 achieved remission and 11 patients relapsed at different stages of treatment.
The control group comprised of age and gender matched 100 healthy volunteers having no medical history of any leukemia, with same ethnicity and living in the same geographical area as the patients. This study was conducted only after taking informed consent from all participants and sanction by the institutional Ethics committee of Sher-i-Kashmir Institute of Medical Sciences.
DNA Extraction
Genomic DNA from the peripheral blood/bone marrow of CML cases and peripheral blood of control subjects was extracted using QIAamp DNA Blood Mini Kit (Cat No. 51104), Qiagen (Germany) and its concentration and purity was analyzed by Bio spectrophotometer (Eppendorf AG; Serial No: 6137EQ 102539; Germany).
Genotyping
Genotyping of the two SNPs was performed as previously described [23]. RFLP analysis was done using restriction endonuclease MobI (Fermentas, Germany) for C3435T and BanI (Fermentas, Germany) for G2677T SNPs according to the manufacturer’s instructions. 4% agarose gel was used to resolve the digested products and visualized on Flourchem HD2 gel doc (USA).
For C3435T SNP, an uncut 193 bp band depicted homozygous variant (TT) whereas electrophoretic pattern displayed two digested bands (144 and 49 bp) for wild type genotype (CC) and three bands (193, 144, and 49 bp) for heterozygous (CT) genotype. For G2677T SNP, the enzyme BanI yielded two bands of (198 and 26 bp) for wild type genotype (GG), three bands of (224,198 and 26 bp) for heterozygous genotype (GT) and a single uncut band of (224 bp) for homozygous mutant genotype (TT).
Statistics
Difference in frequencies of ABCB1-C3435T and ABCB1-G2677T among cases and controls was evaluated by Chi-square test. Odds ratio (OR) as an estimate of relative risk at the 95% confidence interval (CI) was calculated using SPSS data analysis software. Univariate and multivariate Cox proportional hazard model was used to evaluate the risk factors of all events. Survival analysis of patients was estimated by Kaplan–Meier method. The Overall Survival (OS) is the time duration from commence of treatment until death or last follow-up whereas Event-free survival (EFS) is from the time of diagnosis until the date of relapse or last known follow-up for event-free survivors. For all analysis, p values < 0.05 were taken as statistically significant.
Results
Frequency Distribution of ABCB1 C3435T and G2677T Genotypes in CML and B-ALL Patients
The genotype distribution of ABCB1 C3435T and G2677T SNPs in cases and controls are shown in (Table 1). Distribution of genotypes in cases was not related to clinical characteristics like gender, age, dwelling, disease phase and laboratory parameters (Data not shown). No significant correlation between the genotype frequencies of either ABCB1 C3435T or G2677T polymorphism and CML susceptibility was reported in this study (p > 0.05) (Table 1). For B-ALL cases, the frequency of ABCB1 3435 CC, CT and TT genotypes was 12.5%, 43.7% and 43.8% and in controls the respective frequencies were 20%, 52% and 28%. There was a significant difference in the frequency distribution of TT genotype between patients and controls (OR 2.5, 95% CI 1.4–5.9, p = 0.04). Similarly for ABCB1 G2677T SNP, the frequencies of 2677 GG, GT and TT genotypes were 20%, 35% and 45% in ALL patients and 25%, 52% and 23% in the control group respectively. We observed a significant difference in frequency of homozygous variant genotype 2677-TT between cases and controls (OR 2.4, 95% CI 1.0–5.5, p = 0.04).
Table 1.
Genotypic distribution and allelic frequencies of the ABCB1 SNPs in CML and B-ALL patients in comparison to controls
| SNP | Controls (n = 100) (%) | CML cases (n = 100) (%) | OR (95% CI) | p value | ALL cases (n = 80) (%) | OR (95% CI) | p value |
|---|---|---|---|---|---|---|---|
| ABCB1 C3435T | |||||||
| CC | 20 (20) | 33 (33) | Ref | 10 (12.5) | Ref | ||
| CT | 52 (52) | 45 (45) | 1.9 (0.9–3.7) | 0.08 | 35 (43.7) | 1.3 (0.6–3.2) | 0.52 |
| TT | 28 (28) | 22 (22) | 2.1 (0.9–4.6) | 0.07 | 35 (43.8) | 2.5 (1.4–5.9) | 0.04** |
| CT +TT | 80 (80) | 67 (67) | 1.9 (1.0–3.7) | 0.05 | 70 (87.5) | 1.7 (0.8–3.9) | 0.22 |
| Allele frequency | |||||||
| 3435 C | 92 (46) | 111 (55.5) | 55 (34.4) | 1.4 (0.9–2.2) | 0.1 | ||
| 3435 T | 108 (54) | 89 (44.5) | 0.6 (0.4–1.0) | 0.07 | 105 (65.6) | ||
| ABCB1 G2677T | |||||||
| GG | 25 (25) | 23 (23) | Ref | 16 (20) | Ref | ||
| GT | 52 (52) | 50 (50) | 1.0 (0.5–2.0) | 1.0 | 28 (35) | 0.8 (0.3–1.8) | 0.6 |
| TT | 23 (23) | 27 (27) | 1.2 (0.5–2.8) | 0.6 | 36 (45) | 2.4 (1.0–5.5) | 0.04** |
| GT + TT | 75 (75) | 77 (77) | 1.1 (0.5–2.1) | 0.8 | 64 (80) | 1.3 (0.6–2.7) | 0.4 |
| Allele frequency | |||||||
| 2677 G | 102 (51) | 96 (48) | 0.6 | 60 (37.5) | |||
| 2677 T | 98 (49) | 104 (52) | 1.1 (0.7–1.6) | 100 (62.5) | 1.7 (1.1–2.6) | 0.01** |
**Bold values indicate that the statistically significant values
Among 100 CML patients, 74 (74%) were responsive and 26 (26%) were resistant to Imatinib. The distribution of 3435C > T and 2677 G > T genotypes among these groups revealed no significant difference. Similarly, the genotypic distribution of the respective SNPs showed no significant difference between 69 (86.2%) ALL patients in remission against 11 (13.4%) relapsed ones (Table 2).
Table 2.
Genotypes distribution and allelic frequencies of the ABCB1 SNPs between remission and relapse groups of CML and B-ALL patients
| SNP | CML | ALL | ||||
|---|---|---|---|---|---|---|
| Response (n = 74) (%) | Resistance (n = 26) (%) | p value | Remission (n = 69) (%) | Relapse (n = 11) (%) | p value | |
| ABCB1 C3435T | ||||||
| CC | 26 (35.1%) | 7 (26.9%) | Ref | 8 (11.6%) | 2 (18.2%) | |
| CT | 31 (41.9%) | 14 (53.8%) | 0.4 | 31 (44.9%) | 4 (36.4%) | 0.6 |
| TT | 17 (23.0%) | 5 (19.3%) | 1.0 | 30 (43.5%) | 5 (45.4%) | 0 |
| CT +TT | 48 (63.5%) | 19 (76.9%) | 0.4 | 61 (88.4%) | 9 (81.8%) | 0.6 |
| Allele frequency | ||||||
| 3435 C | 83 (56.1%) | 28 (53.8%) | Ref | 47 (34.1%) | 8 (36.4%) | 1 |
| 3435 T | 65 (43.9%) | 24 (46.2%) | 0.8 | 91 (65.9%) | 14 (63.6%) | |
| ABCB1 G2677T | ||||||
| GG | 15 (20.3%) | 8 (30.8%) | Ref | 14 (20.3%) | 2 (18.2%) | Ref |
| GT | 38 (51.3%) | 12 (46.1%) | 0.4 | 25 (36.2%) | 3 (27.3%) | 1 |
| TT | 21 (28.4%) | 6 (23.1%) | 0.3 | 30 (43.5%) | 6 (54.5%) | 1 |
| GT + TT | 59 (79.7%) | 18 (69.2%) | 0.2 | 55 (79.7%) | 9 (81.8%) | 1 |
| Allele frequency | ||||||
| 2677 G | 68 (45.9%) | 28 (53.8%) | Ref | 53 (38.4%) | 7 (31.8%) | |
| 2677 T | 80 (54.1%) | 24 (46.2%) | 0.3 | 85 (61.6%) | 15 (68.2%) | 0.6 |
Haplotype analysis was performed to estimate the cumulative effect of the two SNPs on the risk for the two leukemia types. No significant differences in distribution of haplotypes were observed between controls and two patients groups (Table 3).
Table 3.
Combined haplotypes analysis of ABCB1 SNPs in CML and B-ALL patients in comparison to controls
| Haplotype C3435T G2677T | Controls (n = 100) (%) | CML cases (n = 100) (%) | OR (95% CI) | p value | ALL cases (n = 80) (%) | OR (95% CI) | p value | |
|---|---|---|---|---|---|---|---|---|
| CC | GG | 7 (7%) | 10 (10%) | Ref. | 4 (5%) | Ref. | ||
| CC | GT | 10 (10%) | 17 (17%) | 1.1 (0.3–4.1) | 1 | 4 (%) | 0.7 (0.12–3.79) | 1 |
| CC | TT | 3 (3%) | 6 (6%) | 1.4 (0.2–7.5) | 1 | 2 (%) | 1.1 (0.13–10.1) | 1 |
| CT | GG | 13 (13%) | 11 (11%) | 0.5 (0.1–2.0) | 0.5 | 6 (%) | 0.80 (0.16–3.85) | 1 |
| CT | GT | 26 (26%) | 22 (22%) | 0.5 (0.1–1.8) | 0.4 | 15 (%) | 1.00 (0.25–4.02) | 1 |
| CT | TT | 13 (13%) | 12 (12%) | 0.6 (0.1–2.2) | 0.5 | 14 (%) | 1.88 (0.44–7.96) | 0.4 |
| TT | GG | 5 (5%) | 2 (2%) | 0.2 (0.04–1.8) | 0.3 | 6 (%) | 2.1 (0.38–7.92) | 0.6 |
| TT | GT | 16 (16%) | 11 (11%) | 0.4 (0.1–1.6) | 0.3 | 9 (%) | 0.98 (0.22–4.30) | 1 |
| TT | TT | 7 (7%) | 9 (9%) | 0.9 (0.2–3.5) | 1 | 20 (%) | 5.0 (1.11–8.8) | 0.06 |
ABCB1 Genotypes and Outcome for CML and B-ALL Patients
Influence of ABCBI C3435T and G2677T genotypes on disease outcome in CML and B-ALL patients was evaluated by Kaplan–Meier survival plots. The median follow-up time for CML cases from diagnosis was 49.5 months (range 5–120 months). Out of the 100 CML patients, 26 (26%) were resistant to Imatinib and 3 patients died including 2 that were in blast crisis. No effect on the OS was found for the two ABCB1 SNPs. However, Kaplan–Meier survival plots revealed significantly reduced 5-year Event free survival (pEFS5y) of 43.8% for CML patients carrying 3435TT genotype compared to 63.4% and 67.9% in 3435CT and 3435CC carriers (log-rank p = 0.001) (Fig. 1a). Multivariate analysis of survival adjusted for age, gender, baseline TLC, platelet counts and phase of disease confirmed more than 6-fold increased risk of developing resistance to Imatinib in ABCB1 3435TT carriers (HR 6.24, 95% CI 1.94–15.1, p = 0.002) (Table 4). In contrast, G2677T SNP showed no significant influence on Imatinib response in CML patients.
Fig. 1.
Kaplan–Meier plots for event free survival of CML and B-ALL patients. a, b Event free survival of CML and B-ALL patients according to ABCB1 C3435T genotypes
Table 4.
Multivariate analysis of CML and B-ALL patients according to different clinical parameters and ABCB1 genotypes
| Variable | Responders/remission (n = 74) (%) | Resistant/relapse (n = 26) (%) | Hazard ratio Exp (B) | 95% CI for Exp (B) | p value |
|---|---|---|---|---|---|
| CML | |||||
| Gender | |||||
| Male | 35 (47.3%) | 11 (42.3%) | 1.0 (Ref) | 0.73 | |
| Female | 39 (52.7%) | 15 (57.7%) | 1.13 | 0.63–4.31 | |
| Age | |||||
| ≥ 40 | 40 (54.1%) | 17 (65.4%) | 1.0 (Ref) | 0.41 | |
| < 40 | 34 (45.9%) | 9 (34.6%) | 1.42 | 0.92–5.19 | |
| WBC count | |||||
| > 12,000 | 64 (86.5%) | 24 (92.3%) | 1.0 (Ref) | 0.33 | |
| ≤ 12,000 | 10 (13.5%) | 2 (7.7%) | 1.88 | 0.84–5.97 | |
| CML disease phase | |||||
| Chronic phase (CP) | 70 (94.6%) | 20 (76.9%) | 1.0 (Ref) | ||
| Accelerated phase (AP) | 4 (5.4%) | 4 (15.4%) | 0.83 | 0.32–4.78 | 0.82 |
| Blast crisis (BC) | 0 (–) | 2 (7.7%) | 1.24 | 0.76–5.15 | 0.65 |
| C3435T | |||||
| 3435CC | 26 (35.1%) | 7 (26.9%) | 1.0 (Ref) | ||
| 3435CT | 31 (41.9%) | 14 (53.8%) | 0.74 | 0.26–2.10 | 0.52 |
| 3435TT | 17 (23%) | 5 (19.3%) | 6.24 | 1.94–7.20 | 0.002** |
| G2677T | |||||
| 2677GG | 15 (20.3%) | 8 (30.7%) | 1.0 (Ref) | ||
| 2677GT | 38 (51.3%) | 12 (46.2%) | 0.91 | 0.33–2.46 | 0.83 |
| 2677TT | 21 (28.4%) | 6 (23.1%) | 2.19 | 0.61–7.85 | 0.29 |
| (n = 69) (%) | (n = 11) (%) | ||||
|---|---|---|---|---|---|
| ALL | |||||
| Gender | |||||
| Female | 41 (59.4%) | 8 (72.7%) | 1.0 (Ref) | ||
| Male | 28 (40.6%) | 3 (27.3%) | 1.56 | 0.47–9.55 | 0.58 |
| Age | |||||
| < 20 | 46 (66.7%) | 5 (45.5%) | 1.0 (Ref) | ||
| ≥ 20 | 23 (33.3%) | 6 (54.5%) | 2.29 | 0.80–6.33 | 0.27 |
| WBC count | |||||
| ≤ 12,000 | 53 (76.8%) | 6 (54.5%) | 1.0 (Ref) | ||
| > 12,000 | 16 (23.2%) | 5 (45.5%) | 2.98 | 1.17–9.61 | 0.76 |
| ALL risk groups | |||||
| Low risk | 26 (37.7%) | 3 (27.3%) | 1.0 (Ref) | ||
| Intermediate risk | 33 (47.8%) | 6 (54.5%) | 1.27 | 0.77–5.19 | 0.44 |
| High risk | 10 (14.5%) | 2 (18.2%) | 1.85 | 0.67–6.11 | 0.23 |
| C3435T | |||||
| 3435CC | 8 (11.6%) | 2 (18.2%) | 1.0 (Ref) | ||
| 3435CT | 31 (44.9%) | 4 (36.4%) | 1.63 | 0.34–7.75 | 0.5 |
| 3435TT | 30 (43.5%) | 5 (45.5%) | 4.51 | 0.81–6.8 | 0.03** |
| G2677T | |||||
| 2677GG | 14 (20.3%) | 2 (18.2%) | 1.0 (Ref) | 0.16–1.98 | 0.3 |
| 2677GT | 25 (36.2%) | 3 (27.3%) | 0.56 | 0.13–9.09 | 0.9 |
| 2677TT | 30 (43.8%) | 6 (54.5%) | 1.10 |
**Bold values indicate that the statistically significant values
For B-ALL patients, the median follow-up time from diagnosis was 38 months (5–62 months). Of the 80 patients, 69 (86.3%) achieved remission and 11 (13.7%) patients relapsed at different stages of treatment out of which 3 patients died. A significantly reduced pEFS5y of 68.4% was reported for patients with 3435TT genotype compared to 77.4% and 86.3% for 3435CT and 3435CC genotype carriers (log-rank p = 0.027) (Fig. 1b). No ABCBI G2677T genotypes had any effect on the EFS of ALL patients. Multivariate analysis confirmed presence of 3435TT genotype associated with more than fourfold increased relapse risk (HR 4.51, 95% CI 0.81–24.8, p = 0.03) (Table 4).
Discussion and Conclusion
It is an established fact that there is an inter-individual variation for the response to the same drug. The ABCB1 polymorphisms influence the therapeutic efficacy of drugs by altering P-gp expression. Association of ABCB1 SNPs and leukemia risk are being investigated extensively but the results have been highly controversial. In this hospital-based case–control study, we determined the association of ABCB1/MDR1 gene 3435C > T and 2677G > T polymorphisms with risk and therapeutic outcome of CML and B-ALL patients in Kashmiri population of North Indian origin.
In this study, ABCB1 C3435T or G2677T polymorphisms were not significantly associated with CML susceptibility in Kashmiri population that substantiates our previous report from the same ethnic and geographical region [23]. This observation is at apparent variance with studies by Elghannam et al. [24] and Sailaja et al. [25] which showed significantly higher frequency of the wild-type genotype 2677GG in chronic phase and variant genotype 2677GT in blast crisis patients.
For B-ALL patients, the frequency of TT variant genotype for both SNPs was significantly higher in ALL cases and conferred > 2.5-fold risk of developing ALL (p < 0.05). Similar to our study, several studies across the globe in different ethnic populations have demonstrated that carriers of the TT genotype for ABCB1 SNPs are more at risk of developing ALL than other individuals [26–29], whereas, many others have reported no such association [17]. This genetic variation in genotypic distribution of ABCB1 SNP’S between different populations may be due to ethnic differences, sample size, and heterogeneity of patients.
In-depth screening of the ABCB1 gene has identified multiple SNPs which influence the disease outcome by altering transporter function and expression of proteins. Studies have revealed a significant difference in the distribution of C3435T and G2677T genotypes among remission and relapse groups of CML and ALL patients [16, 17, 29, 30]. We observed no such difference in genotypic distribution between resistant and responsive groups for the two leukemia types. Consistent with our findings, number of studies has reported similar findings for Imatinib resistant and responders [23, 24]. Also, Gregers et al. [17] reported same scenario for remission and relapse groups in ALL patients.
The impact of ABCB1 polymorphisms on the disease susceptibility and outcome can also be explained by the importance of linkage disequilibrium because the SNPs are commonly inherited as haplotypes [31, 32]. ABCB1 haplotypes have been substantiated to impact the treatment outcome of the anti cancer drugs and tyrosine kinase inhibitors like Imatinib. However, the current study neither revealed any significant association of these haplotypes with susceptibility to CML or B-ALL, nor with CR rate or survival. In accordance with our results, number of studies found the respective haplotypes not influencing the susceptibility or therapeutic outcome in CML and ALL patients [17, 23, 33, 34]. In contrast, Au et al. [35] reported significant association of ‘CGC’ haplotypes in ‘C1236T’, ‘G2677T’ and ‘C3435T’ linked SNPs with Imatinib resistance (p = 0.03). Gregers et al. [17] found that ALL patients with 2677TT/1236TT haplotype had significantly lower platelets and neutrophil counts.
It is well established that SNPs in genes that encode metabolizing enzymes and drug transporters may alter drug efficacy and therefore, can influence response to treatment [16, 17, 36]. The analysis of factors that influence the clinical outcome of CML and ALL patients in our study showed that carriers of 3435TT genotype had significantly lower EFS (log-rank p < 0.05). Also for both disease groups, the study presented here shows an independent impact of the homozygous variant polymorphism in exon 26 on survival by a clearly increased resistance/relapse risk. In agreement with our study, Ni et al. [30] reported significantly increased resistance to Imatinib in 3435T allele carriers whereas Kim et al. [37] reported no association between G2677T polymorphism and MMR. Also, Dulucq et al. [16] reported worse response to Imatinib among 2677G allele carriers. The results of our study are in agreement with meta analysis that showed no significant effect of G2677T on CR in ALL patients [38]. In contrast, Gregers et al. [17] and Rao et al. [39] reported an inferior survival outcome for ALL patients carrying 3435CC Genotype. This finding makes C3435T SNP a plausible factor to predict the response outcome of CML and B-ALL patients but needs authentication on large sample size.
In conclusion, the current study provides preliminary evidence of a significant association between ABCB1 3435TT variant genotype and increased B-ALL risk whereas; ABCB1 C3435T and G2677T polymorphisms had no role in CML pathogenesis. Also, results suggest that 3435TT genotype increases Imatinib resistance in CML and influence therapeutic outcome in B-ALL. The limitations of the present study remain there as the patients and control subjects were from the same hospital. Nonetheless, more studies with increased sample sizes addressing gene–gene and gene–environment interactions are needed to authenticate the results in different ethnicities, so that a final conclusion can be drawn on the association of these ABCB1 SNPs with the treatment outcomes for patients with hematological malignancies.
Acknowledgements
We acknowledge the departments of Clinical Hematology and Medical Oncology, SKIMS for their support. We also acknowledge our patients for their participation in the study.
Author Contributions
SMB Conceptualized, designed and supervised the study. Did lab work and also drafted the manuscript. ZAS Supervised the study, provided the consumables and logistical support and submitted the manuscript. AAP Did proofreading and corrected the manuscript. MMM Did compilation and statistical work. JRB Provided patient samples. SAG Provided patient samples. GMB Provided patient samples.
Funding
No funding was received for this work.
Compliance with Ethical Standards
Conflict of interest
The authors have no conflict of interest.
Ethics Approval
The study was approved by the local Institutional Ethics committee (IEC-SKIMS).
Consent to Participate
This study was conducted only after taking informed consent from all participants.
Consent for Publication
All the authors gave their consent for submission/publication of this manuscript.
Availability of Data and Materials
Data will be made available on request.
Footnotes
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Shahid M. Baba and Arshad A. Pandith have contributed equally to this work.
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Data Availability Statement
Data will be made available on request.