Acute Lymphoblastic Leukemia
Acute lymphoblastic leukemia (ALL) is a rapidly progressing cancer of the blood and bone marrow, characterized by the uncontrolled growth of immature white blood cells known as lymphoblasts.[1] While ALL can affect adolescents and young adults [2]it is predominantly recognized as the most common childhood cancer.[3] Understanding the incidence patterns of leukemia subtypes by demographic characteristics is an ongoing area of research. [4]
Biological Basis
Section titled “Biological Basis”The development of ALL is rooted in genetic alterations that affect the normal maturation and proliferation of lymphocytes. [5] These alterations can include mutations, epigenetic changes, and aberrant expression of genes involved in leukemogenesis. [6] Genome-wide profiling has provided significant insights into these genetic changes. [7]
Numerous germline susceptibility loci and genetic polymorphisms have been identified through genome-wide association studies (GWAS) and family-based exome-wide association studies, contributing to the risk of developing ALL. [8] Key genes and chromosomal regions associated with ALL susceptibility include:
- ARID5B: Confirmed as a significant susceptibility gene for childhood B-cell ALL, with intron 3 identified as a hotspot for susceptibility [9], [10]. [11]
- CDKN2A and CDKN2B at 9p21.3: Variants in these loci influence childhood ALL risk, including inherited coding variants and heritable missense polymorphisms [12], [13], [14]. [15]
- Loci on 7p12.2, 10q21.2, and 14q11.2: These regions are associated with an increased risk of childhood ALL [16]. [3]
- 10p12.31-12.2 and 10p14: Novel susceptibility variants in these regions influence risk and phenotype of childhood B-cell ALL [17]. [18]
- 10q26.13 and 12q23.1: Identified as risk loci for childhood ALL. [19]
- ETV6-RUNX1 rearrangement: A common genetic alteration in childhood ALL, with germline susceptibility loci identified. [20]
- IKZF1: Variants in this gene have been confirmed in childhood ALL. [21]
Genetic ancestry also plays a role in ALL susceptibility and treatment response, influencing risk alleles and pharmacogenomics of relapse [22]. [23]
Clinical Relevance
Section titled “Clinical Relevance”ALL is a prototype for a drug-responsive cancer, and significant advancements have been made in its treatment.[24] However, individual treatment responses and prognosis can vary widely. [3]Minimal residual disease (MRD) is a crucial prognostic factor in childhood ALL.[25]
Pharmacogenomics, the study of how genes affect a person’s response to drugs, is increasingly important in ALL management. Genetic variations can influence treatment outcomes, drug efficacy, and the risk of adverse effects, such as glucocorticoid-associated osteonecrosis [26] or elevated hepatic transaminase after therapy linked to a PNPLA3 variant. [27] The integration of genetic and clinical risk factors helps improve prognostication, particularly in relapsed childhood B-cell precursor ALL. [28]Genomic profiling also aids in refining risk assessment and identifying novel therapeutic targets.[6] New therapeutic strategies continue to be developed to improve patient outcomes. [29]
Social Importance
Section titled “Social Importance”The significant impact of ALL on children and their families underscores its social importance. Research has highlighted survival variability by race and ethnicity in childhood ALL, indicating disparities that need to be addressed. [30] Studies involving multi-ethnic samples and ethnically diverse populations are crucial for a comprehensive understanding of ALL risk and to ensure equitable treatment and outcomes [31]. [17] International collaborations, such as the Childhood Leukemia International Consortium, demonstrate a global commitment to advancing research and improving care for ALL patients. [32]
Limitations
Section titled “Limitations”Ancestry and Generalizability Constraints
Section titled “Ancestry and Generalizability Constraints”Many studies on acute lymphoblastic leukemia (ALL) susceptibility have predominantly focused on populations of European descent, which can limit the generalizability of findings to more ethnically diverse groups.[33]Genetic architectures, including allele frequencies and linkage disequilibrium patterns, can vary significantly across ancestries, meaning that risk variants identified in one population may not have the same effect size or even be present in others.[17]For admixed populations, such as Hispanics, the complex interplay of different ancestral contributions necessitates careful consideration to prevent population stratification, a phenomenon where spurious associations can arise due to differences in ancestry between cases and controls rather than true genetic links to the disease.[34] This limitation suggests that risk prediction models and targeted therapies derived from predominantly European cohorts might not be optimally effective or equitable for individuals from other ethnic backgrounds, underscoring the critical need for more inclusive genomic research. [23]
Methodological and Statistical Limitations
Section titled “Methodological and Statistical Limitations”The interpretation of genetic association studies is often constrained by study design and statistical considerations. Sample sizes, while large in some meta-analyses, can still be insufficient to detect variants with small effect sizes, potentially leading to an underestimation of the full genetic contribution to ALL susceptibility. [35] Furthermore, stringent quality control measures, such as exclusions for low genotyping call rates, cryptic relatedness, or deviations from Hardy-Weinberg equilibrium, are essential for data integrity but can inadvertently reduce sample power or introduce subtle biases. [36] The reliance on imputation to infer genotypes for unassayed variants introduces a degree of uncertainty, and while statistical models like logistic regression are widely used, their assumptions about genetic models and potential confounding factors must be carefully considered. [17] Gaps in replication across independent cohorts remain a challenge, as initial findings, especially those with modest effect sizes, may not consistently replicate, highlighting the need for robust validation studies to confirm associations. [36]
Unmeasured Environmental and Complex Etiological Factors
Section titled “Unmeasured Environmental and Complex Etiological Factors”Current genetic studies, while elucidating several susceptibility loci, only partially explain the heritability of ALL, indicating a “missing heritability” that may be attributed to a combination of unmeasured genetic factors, rare variants, and complex gene-environment interactions. [19] Environmental exposures, such as infections or other early-life influences, are recognized as significant contributors to ALL etiology, yet their precise interactions with genetic predispositions are often not comprehensively captured in current study designs. [37]The absence of detailed environmental exposure data can obscure the true impact of genetic variants or lead to confounding, where observed genetic associations might be indirectly influenced by unmeasured environmental factors correlated with specific genotypes.[34] Therefore, a comprehensive understanding of ALL risk requires future research to integrate detailed environmental phenotyping with genomic data, moving beyond purely genetic associations to explore the dynamic interplay between inherited predispositions and external influences.
Variants
Section titled “Variants”Genetic variations play a significant role in an individual’s susceptibility to acute lymphoblastic leukemia (ALL), particularly in childhood cases. These variants often occur in genes crucial for lymphocyte development and regulation, influencing cellular pathways that can lead to uncontrolled cell proliferation. Genome-wide association studies (GWAS) have consistently identified several key genetic loci linked to ALL risk, with some variants demonstrating stronger associations with specific ALL subtypes, such as B-cell ALL.
Variants within the ARID5B gene, including rs7089424 , rs10821936 , and rs4245595 , are strongly associated with an increased risk of childhood ALL. ARID5B (AT-rich interactive domain 5b) encodes a transcription factor involved in embryogenesis, growth regulation, and the definition of B-cell lineage, with its expression known to be upregulated in certain leukemias. [16] For instance, the rs7089424 variant at 10q21.2 has been associated with a combined odds ratio of 1.65 for ALL and 1.70 for B-cell ALL. [16] Similarly, rs10821936 has shown a significant association with ALL, demonstrating an odds ratio of 1.91 in pediatric ALL populations. [38] These intronic variants, such as rs4245595 , are believed to alter ARID5B function, thereby increasing susceptibility to this B-lineage leukemia. [34]
Another critical gene implicated in ALL susceptibility is IKZF1, which encodes Ikaros, a transcription factor essential for normal lymphoid development in both mice and humans. Deletions or variations within IKZF1 are known to contribute to the pathogenesis of aggressive forms of childhood ALL. [38] Variants like rs11978267 , rs4132601 , rs6964969 (located in the IKZF1 - RNU6-1091P region), and rs1110701 have been identified as risk loci for ALL. Specifically, the rs1110701 variant is significantly associated with ALL, showing an odds ratio of 1.69 for all ALL cases and a higher odds ratio of 1.91 when analysis is confined to the B-cell subtype. [21] The rs4132601 variant also demonstrates a significant increase in ALL risk, particularly with homozygosity for its minor allele. [21]
Further genetic contributions to ALL risk involve variants in genes such as CEBPE and PIP4K2A. The CEBPE (CCAAT/enhancer-binding protein epsilon) gene is a transcription factor vital for the differentiation of myeloid and lymphoid cells, and its dysregulation can impact immune cell development. Variants including rs2239633 and rs4982731 (located in the CIROP - CEBPE intergenic region) are linked to ALL susceptibility. [17] Additionally, the rs4748813 variant in the PIP4K2Agene, which encodes Phosphatidylinositol-5-Phosphate 4-Kinase Type II Alpha, also contributes to the cumulative genetic risk of ALL.[17] PIP4K2A is involved in crucial lipid signaling pathways, and alterations may affect cellular growth and survival relevant to leukemia development.
Other notable variants associated with childhood ALL susceptibility include rs4617118 in CCDC26, rs11155133 in the RPS3AP24 - RN7SKP106 region, rs7142143 in PYGL, and rs17079534 in the NFU1P1 - MYRIP region. While the precise mechanisms by which these variants contribute to ALL risk are complex and continue to be elucidated, CCDC26 (Coiled-Coil Domain Containing 26) is a gene associated with various cancers, and PYGL (Glycogen Phosphorylase Liver) plays a role in glycogen metabolism. [16] These genetic markers, identified through comprehensive genomic studies, collectively highlight the multifaceted genetic landscape underlying ALL predisposition.
Key Variants
Section titled “Key Variants”| RS ID | Gene | Related Traits |
|---|---|---|
| rs7089424 rs10821936 rs4245595 | ARID5B | acute lymphoblastic leukemia B-cell acute lymphoblastic leukemia |
| rs11978267 rs4132601 | IKZF1 | acute lymphoblastic leukemia type 1 diabetes mellitus |
| rs6964969 rs1110701 | IKZF1 - RNU6-1091P | acute lymphoblastic leukemia |
| rs4748813 | PIP4K2A | acute lymphoblastic leukemia |
| rs2239633 | CEBPE | B-cell acute lymphoblastic leukemia eosinophil percentage of leukocytes eosinophil count eosinophil percentage of granulocytes acute lymphoblastic leukemia |
| rs4617118 | CCDC26 | acute lymphoblastic leukemia |
| rs11155133 | RPS3AP24 - RN7SKP106 | acute lymphoblastic leukemia |
| rs7142143 | PYGL | acute lymphoblastic leukemia |
| rs4982731 | CIROP - CEBPE | acute lymphoblastic leukemia basophil percentage of leukocytes basophil percentage of granulocytes basophil measurement |
| rs17079534 | NFU1P1 - MYRIP | acute lymphoblastic leukemia |
Classification, Definition, and Terminology
Section titled “Classification, Definition, and Terminology”Defining Acute Lymphoblastic Leukemia (ALL)
Section titled “Defining Acute Lymphoblastic Leukemia (ALL)”Acute lymphoblastic leukemia (ALL) is a malignant disorder characterized by the uncontrolled proliferation of immature lymphocytes, known as lymphoblasts, within the bone marrow, peripheral blood, and other tissues.[39] This rapid and unregulated growth of abnormal white blood cells impairs the production of healthy blood cells, leading to various clinical manifestations. [1]The term “acute” signifies the swift onset and aggressive progression of the disease, demanding immediate diagnostic confirmation and therapeutic intervention. While ALL is predominantly recognized as a childhood cancer, it can manifest across all age groups, necessitating age-specific diagnostic considerations and treatment protocols.[40]
Classification and Subtypes
Section titled “Classification and Subtypes”The classification of lymphoid neoplasms, including ALL, relies on comprehensive systems developed for both clinical management and epidemiological research. Notable frameworks include those from the International Lymphoma Epidemiology Consortium (InterLymph) and the World Health Organization (WHO), which provide a hierarchical structure for disease categorization.[41]A primary classification distinguishes ALL based on the lineage of the malignant lymphoblasts, with B-cell precursor acute lymphoblastic leukemia (B-ALL) being a common and extensively studied subtype.[40] Further refinement involves the identification of specific cytogenetic and molecular characteristics, such as the presence of the ETV6-RUNX1 gene rearrangement in childhood ALL [42] or the absence of the Philadelphia chromosome (Ph-), which are critical for accurate diagnosis and prognostic assessment. [40]
Risk stratification in ALL is significantly informed by the evaluation of minimal residual disease (MRD), which refers to the detectable leukemia cells remaining after initial treatment that are below the threshold of conventional microscopic detection.[25] MRD assessment, often performed using highly sensitive techniques like real-time quantitative PCR analysis of immunoglobulin and T-cell receptor gene rearrangements, plays a pivotal role in guiding risk-adapted therapy in international clinical trials for childhood ALL. [43] This response-based stratification, integrated with other factors such as specific cytogenetic subgroups like hyperdiploid negative (<51 chromosomes), allows for tailored treatment plans to optimize patient outcomes. [40]
Diagnostic and Prognostic Markers
Section titled “Diagnostic and Prognostic Markers”The diagnostic and prognostic evaluation of acute lymphoblastic leukemia incorporates a range of clinical, biochemical, and genetic markers. For instance, the monitoring of liver function, specifically through alanine aminotransferase (ALT) values, is a crucial measurement during treatment, with severity graded according to established criteria like the Common Terminology Criteria for Adverse Events (CTCAE) version 3.0.[44]These criteria define thresholds for ALT elevations, such as 1.0 to 2.5-fold above the normal upper limit for Grade 1, and greater than 20.0-fold for Grade 4. Additionally, operational definitions like body mass index (BMI) percentile, where obesity is defined as ≥ 95th percentile, are used in patient assessment.[44]
Genetic analysis is integral for identifying susceptibility and predicting treatment response in ALL. Several germline susceptibility loci have been identified, including variants in the ARID5B and IKZF1 genes, which are recognized risk alleles for childhood ALL. [34] Furthermore, variations within the CDKN2A locus at 9p21.3 and the CDKN2B gene are known to influence the risk and etiology of childhood ALL. [13] Specific risk loci for childhood B-cell precursor ALL have been identified at rs35837782 (10q26.13, associated with LHPP) and rs4762284 (12q23.1, associated with ELK3), providing valuable insights into inherited predisposition and molecular pathogenesis. [19]
Signs and Symptoms
Section titled “Signs and Symptoms”Hepatic Markers at Diagnosis
Section titled “Hepatic Markers at Diagnosis”At the time of acute lymphoblastic leukemia diagnosis, prior to the initiation of induction therapy, specific biochemical markers related to liver function are assessed. Alanine aminotransferase (ALT) and total bilirubin levels are routinely measured as part of the initial diagnostic workup. These objective measurements provide a baseline status of hepatic health before patients are exposed to therapeutic agents such as methotrexate or asparaginase.[27]The assessment of ALT and total bilirubin at diagnosis is crucial for establishing pre-treatment liver function. These markers serve as diagnostic indicators for potential underlying hepatic involvement by the leukemia or pre-existing conditions, and their baseline values are important for subsequent monitoring of treatment-induced hepatotoxicity, allowing clinicians to differentiate between disease-related effects and adverse drug reactions during the course of therapy.
Treatment-Related Clinical Manifestations
Section titled “Treatment-Related Clinical Manifestations”During the therapeutic course for acute lymphoblastic leukemia, patients can develop clinical manifestations primarily linked to the treatment regimen. Common toxicities observed during consolidation therapy, particularly when methotrexate and 6-mercaptopurine are administered, include gastrointestinal issues, specifically mucositis, and increased susceptibility to infection.[38]These toxicities are prospectively scored using standardized criteria, such as the National Cancer Institute (NCI) Cancer Therapy Evaluation Program (CTEP) toxicity criteria, which define grade 3 and 4 toxicities for mucositis and infection.[38]Objective measurement of alanine aminotransferase (ALT) levels is a required observation at specific points, such as day 1 of induction and the start of consolidation therapy, with reporting mandatory for grade 3 and higher elevations.[27]Such elevations in ALT indicate hepatic toxicity, which can be a significant adverse effect of treatments like asparaginase. These measurements, alongside clinical assessment of symptoms like mucositis and signs of infection, are critical for monitoring patient safety, guiding treatment adjustments, and understanding the overall clinical phenotype and severity ranges experienced during ALL therapy.
Genetic and Individual Variability in Clinical Course
Section titled “Genetic and Individual Variability in Clinical Course”The clinical course of acute lymphoblastic leukemia, particularly regarding treatment-related manifestations, exhibits significant inter-individual variability. Genetic factors play a crucial role in shaping these diverse clinical phenotypes. For instance, specific germline genetic variations, such as those inGRIA1 on chromosome 5q33, are associated with hypersensitivity reactions to asparaginase, a common therapeutic agent. [45] Similarly, a variant in PNPLA3 has been linked to elevated hepatic transaminase levels following ALL therapy, demonstrating a genetic predisposition to certain adverse effects. [27]This genetic heterogeneity influences how individuals experience the disease and respond to treatment, leading to variations in the severity and pattern of toxicities like mucositis, infection, and hepatic dysfunction. Measurement approaches involving genetic testing can identify patients at higher risk for these specific adverse reactions, informing personalized treatment strategies. For example, genetic variation in an organic anion transporter polypeptide is associated with methotrexate pharmacokinetics and clinical effects, influencing drug clearance and the likelihood of developing toxicities.[38] Understanding these genetic predispositions helps in predicting the clinical course and managing potential complications, thereby impacting overall patient outcomes and defining aspects of prognostic indicators.
Causes
Section titled “Causes”Genetic Factors Influencing Disease Characteristics
Section titled “Genetic Factors Influencing Disease Characteristics”Genetic variations contribute to the diverse presentation and clinical course of acute lymphoblastic leukemia (ALL). Key among these are inherited variants in genes such asTPMT (thiopurine methyltransferase), which is recognized as a monogenic pharmacogenomic trait. [44] Polymorphisms in TPMT affect the enzyme’s activity, which is crucial for metabolizing thiopurine drugs used in ALL treatment. [46] Individuals with certain TPMT genotypes may exhibit reduced enzyme activity, leading to intolerance to medications like azathioprine and mercaptopurine and necessitating altered treatment regimens. [47]These genetic predispositions influence the efficacy and toxicity of chemotherapy, thereby shaping the overall disease management and patient outcomes.
Beyond specific gene variants, broader ancestral genetic backgrounds are associated with distinct pharmacogenomic profiles and can influence the likelihood of relapse in ALL. [23] Population-specific differences in TPMTallele frequencies, observed in diverse groups such as British, Ghanaian, and Italian-Caucasian populations, highlight how inherited genetic makeup can contribute to varying drug responses and, consequently, impact the trajectory of the disease.[48] These genetic factors, while not necessarily initiating the leukemia, are integral to its manifestation, progression, and response to therapeutic interventions.
Socioeconomic and Geographic Influences
Section titled “Socioeconomic and Geographic Influences”Socioeconomic and geographic factors play a role in the overall impact and outcomes of acute lymphoblastic leukemia. Significant variability in survival rates among children with ALL has been observed across different racial and ethnic groups.[30]These disparities may reflect a complex interplay of genetic predispositions, environmental exposures, and access to quality healthcare, which are often correlated with socioeconomic status and geographic location. Such external factors contribute to the heterogeneous experience of ALL, influencing how the disease progresses and how effectively it can be managed within different populations.
Biological Background
Section titled “Biological Background”Pathogenesis and Cellular Origins of Acute Lymphoblastic Leukemia
Section titled “Pathogenesis and Cellular Origins of Acute Lymphoblastic Leukemia”Acute lymphoblastic leukemia (ALL) is a type of cancer that originates from lymphoid precursor cells, which are immature white blood cells. This disease is characterized by the uncontrolled proliferation of these abnormal cells, leading to a disruption in the normal development and function of the lymphatic system. The accumulation of these leukemic cells impairs the production of healthy blood cells, a process known as hematopoiesis, and can spread throughout the body.[1] A common subtype, B-cell precursor ALL, involves specific abnormalities in B-lymphocyte development. The oncogenic JAK1gene, which encodes a cytoplasmic tyrosine kinase, plays a role in lymphoid cell precursor proliferation and differentiation, and its dysregulation contributes to the development of hematological malignancies, including pediatric B progenitor ALL.[6] Similarly, ERP, a member of the ETS transcription factor family, exhibits differential expression during B-lymphocyte development, suggesting its involvement in the cellular processes that can be perturbed in ALL. [19]
Genetic and Epigenetic Drivers of ALL Susceptibility
Section titled “Genetic and Epigenetic Drivers of ALL Susceptibility”The development of ALL is significantly influenced by germline genomic variants, which are inherited genetic differences that can increase an individual’s susceptibility to the disease.[38] Multiple risk loci have been identified across the genome, including those on chromosomes 7p12.2, 10q21.2, and 14q11.2. [16] Key susceptibility genes include ARID5B, where variants like rs10821936 and a “hot spot” in intron 3 are strongly associated with childhood B-cell ALL risk. [34] Another significant risk allele is IKZF1 (rs11978267 ), which, along with ARID5B, has been consistently confirmed in various studies. [21] Other germline susceptibility loci have been identified at 10p12.31-12.2, 10q26.13, and 12q23.1, further highlighting the complex genetic architecture of ALL. [19] Additionally, variants in CDKN2A at 9p21.3, PIP4K2A (rs7088318 ), and CEBPE (rs4982731 ) also contribute to the risk of childhood ALL. [34]
Beyond germline variants, the molecular genetic landscape of ALL involves somatic alterations, including chromosomal and genomic abnormalities, such as the ETV6-RUNX1 rearrangement frequently seen in childhood ALL. [42] Recurrent IGH translocations can target members of the CEBP transcription factor family in B-cell precursor ALL, leading to aberrant gene regulation. [16] Furthermore, epigenetic changes, which are heritable modifications in gene expression without altering the underlying DNA sequence, and aberrant expression levels of both protein-coding and noncoding genes, are critical mechanisms involved in leukemogenesis. [6] The presence of multiple risk alleles can have a cumulative effect, further increasing an individual’s susceptibility to developing ALL. [14]
Molecular Pathways and Cellular Functions in ALL
Section titled “Molecular Pathways and Cellular Functions in ALL”The pathogenesis of ALL involves the dysregulation of crucial molecular and cellular pathways that normally control cell growth, survival, and differentiation. Signaling pathways, such as the JAK-STAT pathway, are frequently implicated, with their aberrant activation being a key event in various hematological malignancies.[6] The JAK1 gene, for example, encodes a cytoplasmic tyrosine kinase whose dysregulation can drive uncontrolled lymphoid cell proliferation. [6] Critical proteins and enzymes involved in these pathways become altered, contributing to the malignant phenotype. Transcription factors, like ARID5B, play a significant role as variants in this gene can influence the expression patterns of numerous genes within leukemia cells, affecting their biological behavior and contributing to disease progression.[38]
Cellular functions such as apoptosis (programmed cell death) are often compromised in ALL, allowing leukemic cells to evade normal cellular surveillance mechanisms and persist. [23] The expression of apoptosis-related genes, alongside genes involved in metabolic processes, contributes to the overall cellular function and drug resistance of leukemic cells. [23] Understanding these regulatory networks and the specific biomolecules involved is crucial for identifying therapeutic targets.
Systemic Consequences and Treatment Response in ALL
Section titled “Systemic Consequences and Treatment Response in ALL”Acute lymphoblastic leukemia, while originating in the bone marrow, has systemic consequences that affect various tissues and organs throughout the body. The uncontrolled proliferation of leukemic cells in the bone marrow leads to a decline in the production of normal blood cells, causing anemia, thrombocytopenia, and immunodeficiency.[1] These malignant cells can infiltrate other organs, including the liver, spleen, lymph nodes, central nervous system, and testes, leading to organ-specific effects and broader systemic disruptions. [1]
Treatment response in childhood ALL is a complex trait influenced by the genetic makeup of both the leukemic cells and the individual’s germline. [23] Genes associated with chemotherapy cross-resistance, for instance, impact how effectively patients respond to various therapeutic agents. [23] Similarly, the identification of glucocorticoid-response genes and prednisolone-responsive genes in leukemic cells is vital, as glucocorticoids are a cornerstone of ALL treatment, and variations in these genes can dictate treatment efficacy and patient outcome. [23]Monitoring minimal residual disease (MRD) after treatment is a critical prognostic factor, reflecting the persistence of small numbers of leukemic cells and guiding further therapeutic strategies.[23]
Pathways and Mechanisms
Section titled “Pathways and Mechanisms”Acute lymphoblastic leukemia (ALL) arises from a complex interplay of genetic and epigenetic alterations that disrupt normal hematopoietic development and cellular functions. These dysregulations affect critical signaling networks, metabolic processes, and regulatory mechanisms, leading to uncontrolled proliferation and impaired differentiation of immature lymphoid cells. Understanding these pathways is crucial for identifying the molecular basis of ALL and developing targeted therapies.
Dysregulation of Transcriptional and Epigenetic Control
Section titled “Dysregulation of Transcriptional and Epigenetic Control”The development of ALL is frequently driven by disruptions in gene regulation, often involving transcription factors and epigenetic modifiers. Recurrent chromosomal translocations, such as the IGH translocations, can aberrantly target members of the CEBP transcription factor family in B-cell precursor ALL, leading to altered gene expression essential for normal lymphocyte development. [49] Similarly, the ETV6-RUNX1 fusion gene, a hallmark of a common ALL subtype, results in a chimeric transcription factor that interferes with normal hematopoietic differentiation programs. [42] Germline variants in genes like ARID5B and IKZF1further modulate susceptibility and disease progression by influencing chromatin remodeling and the function of key transcriptional regulators critical for B-cell development.[34] Moreover, the NF-kappaB family of transcription factors plays a significant role in regulating gene expression related to cell survival and inflammation, and its dysregulation contributes to leukemogenesis. [40]The interplay between genetic and epigenetic variations, including allele-specific chromatin remodeling, defines gene expression patterns that contribute to the disease phenotype.[36]
Aberrant Growth and Survival Signaling
Section titled “Aberrant Growth and Survival Signaling”Uncontrolled cell proliferation and resistance to apoptosis in ALL are often driven by dysregulated signaling pathways that promote cell growth and survival. Activating mutations in receptor tyrosine kinases such as KIT and FLT3, or downstream signaling molecules like JAK2, NRAS, and KRAS, can lead to constitutive activation of proliferative pathways. [6] These mutations bypass normal regulatory mechanisms, causing cells to divide continuously without external stimuli. Furthermore, the cell cycle regulators CDKN2A and CDKN2B (located at 9p21.3) are frequently affected by genetic variations, impacting cell cycle progression and increasing ALL risk. [13] The loss of function in these tumor suppressor genes removes critical checkpoints, allowing cells to proliferate uncontrollably. The MYConcogene, a powerful driver of cell growth and division, also plays a significant role, with its dysregulation contributing to cancer risk through altered gene repression.[36]
Metabolic Reprogramming and Therapeutic Vulnerabilities
Section titled “Metabolic Reprogramming and Therapeutic Vulnerabilities”Leukemic cells often exhibit altered metabolic pathways to support their rapid proliferation and survival, creating unique therapeutic vulnerabilities. One critical example is asparagine metabolism, where leukemic cells may become dependent on exogenous asparagine due to insufficient asparagine synthetase activity.[50]This dependency forms the basis for asparaginase therapy, which depletes circulating asparagine and induces cell death in susceptible leukemic cells. Additionally, antimetabolite drugs like thiopurines, used in ALL treatment, disrupt nucleotide biosynthesis pathways, hindering DNA and RNA synthesis essential for cell division.[44] Genetic variants in genes such as HLA-DQA1-HLA-DRB1 can influence the susceptibility to side effects like pancreatitis induced by these thiopurine immunosuppressants, highlighting the genetic basis of drug metabolism and individual responses. [44] The modulation of metabolic flux through these pathways represents a key target for therapeutic intervention in ALL.
Network Perturbations and Systems-Level Integration
Section titled “Network Perturbations and Systems-Level Integration”ALL pathogenesis involves a complex network of interacting pathways rather than isolated defects, necessitating a systems-level understanding. Computational approaches have been employed to identify perturbed genetic networks, revealing the extensive network interactions involved in leukemogenesis. [16] Pathway crosstalk, where different signaling pathways influence each other, contributes to the robustness and adaptability of leukemic cells. For instance, the dysregulation of multiple transcription factors and signaling cascades collectively drives the emergent properties of ALL cells, such as heightened proliferative capacity and resistance to therapy. The hierarchical regulation within these networks means that specific key genetic alterations, such as variants in CDKN2A, can confer strong risk and are preferentially selected during clonal evolution, shaping the disease’s trajectory and influencing treatment response.[19]Understanding this integrated network of dysregulated pathways and their compensatory mechanisms is essential for identifying novel therapeutic targets and predicting treatment outcomes, including minimal residual disease response.[44]
Pharmacogenetics in Acute Lymphoblastic Leukemia
Section titled “Pharmacogenetics in Acute Lymphoblastic Leukemia”Pharmacogenetics plays an increasingly vital role in optimizing therapy for acute lymphoblastic leukemia (ALL) by identifying inherited genetic variations that influence drug metabolism, efficacy, and toxicity. Understanding a patient’s genetic profile can enable personalized treatment strategies, leading to improved outcomes and reduced adverse events. This section explores key pharmacogenetic aspects relevant to ALL treatment, from drug disposition to predicting therapeutic response and mitigating toxicity.
Genetic Influence on Drug Pharmacokinetics and Efficacy
Section titled “Genetic Influence on Drug Pharmacokinetics and Efficacy”Germline genetic variations significantly impact the pharmacokinetics and pharmacodynamics of several drugs crucial in ALL therapy. Thiopurine methyltransferase (TPMT) activity, for instance, is a well-established monogenic pharmacogenomic trait that dictates the metabolism of thiopurine drugs. [44] Individuals with genetic variants leading to reduced TPMT enzyme activity experience decreased drug metabolism, resulting in higher systemic exposure to thiopurines and an increased risk of severe myelosuppression if standard doses are administered.
Similarly, genetic variants affect the disposition of other essential antileukemic agents, such as methotrexate. Variants in the organic anion transporter polypeptide gene SLCO1B1 have been identified as being associated with methotrexate pharmacokinetics and its clinical effects. [38] These variations can influence methotrexate clearance and the accumulation of its active polyglutamate forms within leukemic blasts, thereby impacting overall drug exposure and antileukemic efficacy. [23]Specific genotypes linked to higher methotrexate clearance or lower methotrexate polyglutamate accumulation have been associated with a higher frequency of minimal residual disease (MRD), indicating a less effective therapeutic response.[23] Host genetic variability can also affect the disposition of drugs like etoposide, where greater clearance has been linked to higher MRD. [23]
Pharmacogenetic Modulators of Treatment Outcomes
Section titled “Pharmacogenetic Modulators of Treatment Outcomes”Host genetic variability critically influences treatment response in childhood ALL, affecting the eradication of minimal residual disease (MRD) and the subsequent risk of relapse.[23]Genome-wide studies have identified numerous single nucleotide polymorphisms (SNPs) associated with MRD, including several within theIL15 gene. [23] A substantial number of these SNPs also predict hematologic relapse, demonstrating a strong link between germline variations and long-term treatment outcomes. [23] These genetic variants may exert their effects on treatment response by influencing leukemic cell biology or by altering the host’s disposition of antileukemic drugs. [23]
The eradication of malignant cells by chemotherapy is a complex process influenced by both the somatically acquired characteristics of the malignant cells and inherent patient characteristics, including host genetics. [23] Early assessments of MRD are recognized as strong predictors of cure rates and are routinely utilized to modify therapeutic strategies. [23] The identification of host genetic factors associated with MRD eradication reinforces the potential for personalized approaches, integrating germline variant information, to further refine risk-adapted therapy and improve cure rates in ALL. [23]
Germline Variants and Adverse Drug Reactions
Section titled “Germline Variants and Adverse Drug Reactions”Beyond influencing drug efficacy, germline genetic variations contribute significantly to the interindividual variability in adverse drug reactions experienced by ALL patients. A notable example is vincristine-related peripheral neuropathy, a common and dose-limiting toxicity in ALL therapy, which has been associated with specific inherited genetic variants.[51]Identifying these variants can help predict a patient’s susceptibility to neuropathy, enabling clinicians to consider alternative dosing strategies or prophylactic measures to mitigate this debilitating side effect.
Another important adverse event modulated by host genetics is drug-induced hepatotoxicity. A genome-wide association study linked a variant in the PNPLA3gene with elevated hepatic transaminase levels following acute lymphoblastic leukemia therapy.[27] This finding suggests that specific genetic predispositions can increase the risk of liver injury from chemotherapy, providing a potential biomarker for identifying patients who may require closer monitoring or modified treatment regimens to prevent severe hepatic complications.
Clinical Utility and Personalized Therapy
Section titled “Clinical Utility and Personalized Therapy”The increasing understanding of pharmacogenetics in ALL underscores its growing utility in guiding personalized treatment strategies. Integrating germline genetic information into clinical decision-making allows for more informed dosing recommendations and drug selection, moving beyond a uniform approach. [38] For instance, knowledge of variants affecting drug metabolism or disposition can lead to preemptive dose adjustments, optimizing drug exposure for maximum efficacy while minimizing toxicity. [44]
The implementation of pharmacogenetic testing in ALL aims to improve therapeutic outcomes by tailoring treatment to an individual’s genetic makeup. This personalized prescribing approach, supported by evolving clinical guidelines, enables clinicians to anticipate potential challenges such as poor response due to rapid drug clearance or severe adverse reactions from impaired metabolism. [51] Ultimately, leveraging pharmacogenetic insights facilitates risk-adapted therapy, enhancing the safety and effectiveness of ALL treatment regimens and contributing to higher cure rates. [23]
Frequently Asked Questions About Acute Lymphoblastic Leukemia
Section titled “Frequently Asked Questions About Acute Lymphoblastic Leukemia”These questions address the most important and specific aspects of acute lymphoblastic leukemia based on current genetic research.
1. My child got ALL. Could it be something they inherited from me?
Section titled “1. My child got ALL. Could it be something they inherited from me?”Yes, in some cases. While ALL isn’t typically passed down directly like a simple genetic disease, certain genetic variations you carry can increase your child’s susceptibility. Studies have identified several “germline” genetic differences, such as variants inARID5B or CDKN2A, that children can inherit, making them more prone to developing ALL.
2. I have a family history of leukemia. Am I more likely to get ALL?
Section titled “2. I have a family history of leukemia. Am I more likely to get ALL?”Having a family history of leukemia can be a consideration. Research shows that specific inherited genetic variations, or “germline susceptibility loci” like those on 7p12.2 or 10q21.2, can increase the risk of developing ALL. This means you might inherit a genetic predisposition, rather than the disease itself.
3. Why do some kids get ALL, but others don’t, even in the same family?
Section titled “3. Why do some kids get ALL, but others don’t, even in the same family?”It’s complex, but even within families, genetic predispositions can vary significantly. While some children might inherit specific risk variants in genes like ARID5B or CDKN2A, the development of ALL is influenced by a combination of many genetic factors. Not every child with a risk variant will develop ALL, highlighting the multifaceted nature of the disease.
4. My doctor mentioned my ancestry. Does where my family came from affect my ALL risk?
Section titled “4. My doctor mentioned my ancestry. Does where my family came from affect my ALL risk?”Yes, genetic ancestry can play a significant role. Different populations may have varying frequencies of specific genetic risk alleles for ALL, as seen in studies involving Native American ancestry. This means your ancestral background can influence your inherited susceptibility and even how you might respond to treatments.
5. Is there a genetic test that can tell me if my child is at risk for ALL?
Section titled “5. Is there a genetic test that can tell me if my child is at risk for ALL?”While there isn’t a single predictive test that tells you definitively if your child will get ALL, genetic research has identified many specific variations linked to increased risk. For children already diagnosed, genomic profiling is a crucial tool for understanding their specific leukemia, refining risk assessment, and guiding personalized treatment.
6. Why do some ALL patients respond well to drugs, but others struggle with side effects?
Section titled “6. Why do some ALL patients respond well to drugs, but others struggle with side effects?”This is often due to pharmacogenomics, which studies how your genes affect drug response. Genetic variations can influence how your body processes medications, leading to differences in treatment efficacy or your likelihood of experiencing adverse effects. For example, some genes might affect how you metabolize chemotherapy drugs.
7. I’m worried about my child’s treatment side effects. Can genetics help predict them?
Section titled “7. I’m worried about my child’s treatment side effects. Can genetics help predict them?”Yes, genetics can offer insights into potential side effects. For instance, a specific variant in the PNPLA3 gene has been linked to an increased risk of elevated liver enzymes during ALL therapy. Genomic profiling helps doctors anticipate these reactions and tailor treatment plans to minimize adverse effects.
8. If my child has ALL, can knowing their genes help their doctors treat them better?
Section titled “8. If my child has ALL, can knowing their genes help their doctors treat them better?”Absolutely. Genomic profiling is a powerful tool in ALL management. It helps refine risk assessment, identify specific genetic alterations in the leukemia cells, and pinpoint novel therapeutic targets. This allows doctors to create more personalized and effective treatment strategies, improving prognostication.
9. I heard ALL is a childhood cancer. Does that mean adults don’t have the same genetic risks?
Section titled “9. I heard ALL is a childhood cancer. Does that mean adults don’t have the same genetic risks?”While ALL is predominantly recognized as a childhood cancer, it can affect adolescents and young adults too. The underlying genetic alterations and susceptibility loci, such as variants at 9p21.3, are a focus of research across different age groups. While some patterns might differ, genetic risk factors are relevant for all affected individuals.
10. Can my daily choices help prevent ALL if my family has a genetic risk?
Section titled “10. Can my daily choices help prevent ALL if my family has a genetic risk?”The article highlights that ALL development is rooted in genetic alterations and germline susceptibility loci. While a healthy lifestyle is always beneficial for overall health, the current research presented doesn’t detail specific daily choices or environmental factors that can directly prevent or “override” an identified genetic predisposition for ALL.
This FAQ was automatically generated based on current genetic research and may be updated as new information becomes available.
Disclaimer: This information is for educational purposes only and should not be used as a substitute for professional medical advice. Always consult with a healthcare provider for personalized medical guidance.
References
Section titled “References”[1] Pui, C.-H., M. V. Relling, and J. R. Downing. “Acute lymphoblastic leukemia.”New England Journal of Medicine, vol. 350, 2004, pp. 1535-48.
[2] Perez-Andreu, V., et al. “A genome-wide association study of susceptibility to acute lymphoblastic leukemia in adolescents and young adults.”Blood, vol. 125, no. 26, 2015, pp. 4032-6.
[3] Yang, J. J., et al. “Genome-wide interrogation of germline genetic variation associated with treatment response in childhood acute lymphoblastic leukemia.”JAMA, vol. 301, 2009, pp. 393–403.
[4] Yamamoto, J. F., and M. T. Goodman. “Patterns of leukemia incidence in the United States by subtype and demographic characteristics, 1997–2002.” Cancer Causes & Control, vol. 19, no. 4, 2008, pp. 379-90.
[5] Mullighan, C. G. “The molecular genetic makeup of acute lymphoblastic leukemia.”Hematology. American Society of Hematology. Education Program, 2012, pp. 389-96.
[6] Lv, H., et al. “Genome-wide haplotype association study identify the FGFR2gene as a risk gene for acute myeloid leukemia.”Oncotarget, vol. 7, 2016, pp. 80564–80572.
[7] Mullighan, C. G., and J. R. Downing. “Genome-wide profiling of genetic alterations in acute lymphoblastic leukemia: recent insights and future directions.”Leukemia, vol. 23, no. 7, 2009, pp. 1209-18.
[8] Orsi, L., et al. “Genetic polymorphisms and childhood acute lymphoblastic leukemia: GWAS of the ESCALE study (SFCE).”Leukemia, vol. 26, no. 12, 2012, pp. 2487-94.
[9] Archer, N. P., et al. “Family-based exome-wide association study of childhood acute lymphoblastic leukemia among Hispanics confirms role of ARID5B in susceptibility.”PLoS One, vol. 13, no. 8, 2018, p. e0202157.
[10] Healy, J., et al. “Replication analysis confirms the association of ARID5B with childhood B-cell acute lymphoblastic leukemia.”Haematologica, vol. 95, no. 9, 2010, pp. 1608-11.
[11] Gutierrez-Camino, A., et al. “Intron 3 of the ARID5B gene: a hot spot for acute lymphoblastic leukemia susceptibility.”Journal of Cancer Research and Clinical Oncology, vol. 139, no. 11, 2013, pp. 1879-86.
[12] Hungate, E. A., et al. “A variant at 9p21.3 functionally implicates CDKN2B in paediatric B-cell precursor acute lymphoblastic leukaemia aetiology.” Nature Communications, vol. 7, 2016, p. 10635.
[13] Sherborne, A. L., et al. “Variation in CDKN2Aat 9p21.3 influences childhood acute lymphoblastic leukemia risk.”Nat Genet, vol. 42, 2010, pp. 492–4.
[14] Xu, H., et al. “Inherited coding variants at the CDKN2A locus influence susceptibility to acute lymphoblastic leukaemia in children.” Nature Communications, vol. 6, 2015, p. 7553.
[15] Walsh, K. M., et al. “A heritable missense polymorphism in CDKN2A confers strong risk of childhood acute lymphoblastic leukemia and is preferentially selected during clonal evolution.”Cancer Research, vol. 75, no. 23, 2015, pp. 4884-94.
[16] Papaemmanuil, E., et al. “Loci on 7p12.2, 10q21.2 and 14q11.2 are associated with risk of childhood acute lymphoblastic leukemia.”Nat Genet, vol. 41, 2009, pp. 1006–10.
[17] Xu H, et al. Novel susceptibility variants at 10p12.31-12.2 for childhood acute lymphoblastic leukemia in ethnically diverse populations. J Natl Cancer Inst. 2013; PMID: 23512250.
[18] Migliorini, G., et al. “Variation at 10p12.2 and 10p14 influences risk of childhood B-cell acute lymphoblastic leukemia and phenotype.”Blood, vol. 122, no. 23, 2013, pp. 3729-37.
[19] Vijayakrishnan J, et al. A genome-wide association study identifies risk loci for childhood acute lymphoblastic leukemia at 10q26.13 and 12q23.1. Leukemia. 2016; PMID: 27694927.
[20] Ellinghaus, E., et al. “Identification of germline susceptibility loci in ETV6-RUNX1-rearranged childhood acute lymphoblastic leukemia.”Leukemia, vol. 25, no. 12, 2011, pp. 1809-15.
[21] Evans TJ, et al. Confirmation of childhood acute lymphoblastic leukemia variants,ARID5B and IKZF1, and interaction with parental environmental exposures. PLoS One. 2014; PMID: 25310577.
[22] Walsh, K. M., et al. “Associations between genome-wide Native American ancestry, known risk alleles and B-cell ALL risk in Hispanic children.” Leukemia Research, vol. 38, no. 12, 2014, pp. 1414-20.
[23] Yang JJ, Cheng C, Devidas M, Cao X, Fan Y, Campana D, et al. Ancestry and pharmacogenomics of relapse in acute lymphoblastic leukemia. Nat Genet. 2011 Mar; 43:237–41.https://doi.org/10.1038/ng.
[24] Pui, C.-H., and W. E. Evans. “Treatment of acute lymphoblastic leukemia.”New England Journal of Medicine, vol. 354, no. 2, 2006, pp. 166-78.
[25] van Dongen, J. J., et al. “Prognostic value of minimal residual disease in acute lymphoblastic leukaemia in childhood.”Lancet, vol. 352, no. 9142, 1998, pp. 1731-8.
[26] Karol, S. E., et al. “Genetics of glucocorticoid-associated osteonecrosis in children with acute lymphoblastic leukemia.”Blood, vol. 126, no. 15, 2015, pp. 1770-6.
[27] Liu, Yan, et al. “Genome-Wide Study Links PNPLA3 Variant With Elevated Hepatic Transaminase After Acute Lymphoblastic Leukemia Therapy.”Clinical Pharmacology & Therapeutics, vol. 103, no. 6, 2018, pp. 1025-1033. PMID: 28090653.
[28] Irving, J. A., et al. “Integration of genetic and clinical risk factors improves prognostication in relapsed childhood B-cell precursor acute lymphoblastic leukemia.”Blood, vol. 128, no. 7, 2016, pp. 911-922.
[29] Pui, C.-H., and S. Jeha. “New therapeutic strategies for the treatment of acute lymphoblastic leukaemia.” Nature Reviews Drug Discovery, vol. 6, no. 2, 2007, pp. 149-65.
[30] Kadan-Lottick, N. S. et al. “Survival variability by race and ethnicity in childhood acute lymphoblastic leukemia.” JAMA : the journal of the American Medical Association, vol. 290, no. 15, 2003, pp. 2008–14.
[31] Kennedy, A. E., et al. “Genetic markers in a multi-ethnic sample for childhood acute lymphoblastic leukemia risk.”Leukemia & Lymphoma, vol. 56, no. 1, 2015, pp. 169-74.
[32] Metayer, C., et al. “The Childhood Leukemia International Consortium.” Cancer Epidemiology, vol. 37, no. 3, 2013, pp. 336-347.
[33] Berndt SI, et al. Meta-analysis of genome-wide association studies discovers multiple loci for chronic lymphocytic leukemia. Nat Commun. 2016; PMID: 26956414.
[34] Archer NP, Perez-Andreu V, Scheurer ME, Rabin KR, Peckham-Gregory EC, Plon SE, et al. Family-based exome-wide assessment of maternal genetic effects on susceptibility to childhood B-cell acute lymphoblastic leukemia in Hispanics. Cancer. 2016; 122:3697–704.https://doi.org/10.1002/cncr.
[35] Pe’er I, Yelensky R, Altshuler D, Daly MJ. Estimation of the multiple testing burden for genomewide association studies of nearly all common variants. Genet Epidemiol. 2008; 32:381–385.
[36] Wiemels JL, et al. GWAS in childhood acute lymphoblastic leukemia reveals novel genetic associations at chromosomes 17q12 and 8q24.21. Nat Commun. 2018; PMID: 29348612.
[37] Crouch S, et al. Infectious illness in children subsequently diagnosed with acute lymphoblastic leukemia: modeling the trends from birth to diagnosis. Am. J. Epidemiol. 2012; 176:402–408.
[38] Trevino, L. R., et al. “Germline genetic variation in an organic anion transporter polypeptide associated with methotrexate pharmacokinetics and clinical effects.” J Clin Oncol, vol. 27, no. 33, 2009, pp. 5601-5607.
[39] Inaba, Hiroto, Martin Greaves, and Charles G. Mullighan. “Acute lymphoblastic leukaemia.” Lancet, vol. 381, no. 9881, 2013, pp. 1943-1955.
[40] Clay-Gilmour, A. I., et al. “Genetic association with B-cell acute lymphoblastic leukemia in allogeneic transplant patients differs by age and sex.”Blood Adv, vol. 1, 2017, pp. 2707–15.
[41] Morton, Lindsay M., et al. “Proposed classification of lymphoid neoplasms for epidemiologic research from the Pathology Working Group of the International Lymphoma Epidemiology Consortium (InterLymph).” Blood, vol. 110, no. 2, 2007, pp. 695–708.
[42] Ellinghaus, E., et al. “Identification of germline susceptibility loci in ETV6-RUNX1-rearranged childhood acute lymphoblastic leukemia.”Leukemia, vol. 26, 2012, pp. 1024–30.
[43] Flohr, Thomas, et al. “Minimal residual disease-directed risk stratification using real-time quantitative PCR analysis of immunoglobulin and T-cell receptor gene rearrangements in the international multicenter trial AIEOP-BFM ALL 2000 for childhood acute lymphoblastic leukemia.”Leukemia, vol. 22, no. 8, 2008, pp. 1513–21.
[44] Liu, C. et al. “Genomewide Approach Validates Thiopurine Methyltransferase Activity Is a Monogenic Pharmacogenomic Trait.” Clin Pharmacol Ther, 2016. PMID: 27564568.
[45] Chen, Shih-Hsiang, et al. “Genetic variations in GRIA1 on chromosome 5q33 related to asparaginase hypersensitivity.” Clinical Pharmacology & Therapeutics, vol. 88, no. 1, 2010, pp. 69-76. PMID: 20592726.
[46] Matimba, A. et al. “Thiopurine pharmacogenomics: association of SNPs with clinical response and functional validation of candidate genes.” Pharmacogenomics, vol. 15, no. 4, Mar. 2014, pp. 433–47.
[47] Yates, C. R. et al. “Molecular diagnosis of thiopurine S-methyltransferase deficiency: genetic basis for azathioprine and mercaptopurine intolerance.” Annals of internal medicine, vol. 126, 1997, pp. 608–14.
[48] Ameyaw, M. M. et al. “Thiopurine methyltransferase alleles in British and Ghanaian populations.” Human molecular genetics, vol. 8, no. 2, Feb. 1999, pp. 367–70.
[49] Akasaka, T., et al. “Five members of the CEBP transcription factor family are targeted by recurrent IGHtranslocations in B-cell precursor acute lymphoblastic leukemia (BCP-ALL).”Blood, vol. 109, 2007, pp. 3451–61.
[50] Haskell, C. M., and G. P. Canellos. “l-asparaginase resistance in human leukemia—asparagine synthetase.”Biochem Pharmacol, vol. 18, 1969, pp. 2578–80.
[51] Diouf, B., et al. “Association of an inherited genetic variant with vincristine-related peripheral neuropathy in children with acute lymphoblastic leukemia.”JAMA, vol. 313, no. 8, 2015, pp. 815-823.