Introduction
leukemia is described as a type of cancer affecting white blood cells. It mainly influences a patient’s bone marrow and lymphatic nodes (Pierro et al. 2017). Healthy people have white blood cells that multiply evenly and in an organized manner to fight infections. However, people who suffer from leukemia experience increased production levels of white blood cells, which affect their normal functioning (George et al. 2016).
This type of condition affects varied groups of patients because some types of leukemia are mostly visible in children while others are commonly reported among adults. Acute Lymphoblastic leukemia (ALL) is mostly known to affect children. It is classified among a broader group of cancers known as pediatric leukemia because of the young age of patients who are affected by it (George et al. 2016).
Characterized by the development of large amounts of immature lymphocytes, ALL often manifests when patients have pale skin, fever, feelings of being tired and easy bleeding (among other symptoms) (George et al. 2016). Sometimes, the condition is associated with enlarged lymph nodes and pain in the bones (Pierro et al. 2017). Based on its acute nature, if left untreated, ALL could cause fatalities in months or even weeks of occurrence (George et al. 2016).
It is estimated that thousands of children suffer from ALL and about 10% of them die because of the disease (Pierro et al. 2017). Children who are between the ages of two and five are the most commonly affected demographic (Boissel & Sender 2015; Lamble, Phelan & Burke 2017). In fact, in the US, ALL is believed to be the most common type of cancer among children within this age group. In the UK, statistics show that about 400 new cases of ALL are diagnosed every year (Boissel & Sender 2015; Lamble, Phelan & Burke 2017).
Like other forms of cancer, ALL has no known cure. However, recent advances in treatment research have improved the efficacy of specific groups of associated therapies. Chemotherapy is one of them and it is the most commonly used. Radiation therapy is another one but it has primarily been adopted in cases where patients are in remission (Lamble, Phelan & Burke 2017). If the disease recurs, stem cell transplantation is often adopted as a viable strategy for managing the disease (Boissel & Sender 2015).
Newer research studies are still being undertaken to improve the efficacy of some of these techniques and significant milestones are yet to be updated. Based on this understanding, this paper investigates the progress that has been made in treating ALL by exploring the advancements made in CAR T-cell therapy, animal modeling techniques, gene fusions, cell therapy, immunotherapy, and next-generation sequencing. However, before delving into the details of this review, it is first important to understand the diagnosis of this type of cancer.
Diagnosis
According to López-Villar et al. (2014), there are two main types of leukemia. The first one is chronic and the second one is acute. Chronic leukemia has a slow progression rate unlike acute leukemia, which spreads quickly and causes fatalities in a short time. ALL is a progressive type of leukemia and can progress fast. It often starts in the bone marrow and can spread quickly to other parts of the body or organs (Leonard & Stock 2017).
An ALL diagnosis often starts with a comprehensive understanding of a patient’s medical history. The process may also involve a physical examination of a child or a blood count analysis. Although most symptoms of ALL can be linked with other diseases, persistent ones increase suspicion of its presence (Li et al. 2015).
Albeit important to undertake a comprehensive medical history of a patient, further testing is often required to ascertain a positive cancer diagnosis. For example, a high number of white blood cells in a patient’s blood could signify determine the presence of the disease. This is because ALL is linked to the rapid production of lymphoid cells (Leonard & Stock 2017). Therefore, the higher the number of white blood cells, the higher the risk of a positive prognosis for ALL.
Although the causes of ALL are not known, it is speculated that genes significantly predict a child’s probability of getting the disease (O’Connor et al. 2018). Particularly, genetic factors that cause diseases, such as Down syndrome, are known to influence the probability of ALL occurring (O’Connor et al. 2018). Significant environmental exposures to cancer-causing agents, such as radiation and chemotherapy treatment, are also known risk factors for the disease (O’Connor et al. 2018).
The treatment of ALL involves different kinds of therapies. The selection of the right therapy method to use is often influenced by several factors such as a patients’ age and progression of the disease. Most therapies used are ineffective. Therefore, researchers have been struggling to make significant progress in improving their efficacy. Some of the recent advances made are discussed below.
Genetic Modelling
Medical research on the treatment of ALL has been associated with high rates of success when curing this type of cancer (Terwilliger & Abdul-Hay 2017). Reports show that in the 1990s, patients only had about a 10% chance of recovering from the disease, but because of improvements in medical research, this number increased to about 90%. Most of the scientific advances made to find out the best treatment methods for ALL stem from attempts to address six key issues influencing how these tumors are developed. They include “sustaining proliferative signaling, evading growth suppressors, resisting cell death, enabling replicative immortality, inducing angiogenesis, and activating invasion and metastasis” (Hanahan & Weinberg 2011, p. 646).
These six hallmarks represent the organizing principle surrounding the rationalization of the complexities influencing the growth and development of the neoplastic disease (Luan, Yang & Chen 2015). Here, it should be understood that although cancer-related tumors may contain cancerous cells, these cells are not entirely “bad” because they also contain normal cells. Cancerous cells only thrive if there is a tumor microenvironment (van Dongen et al. 2015).
The widespread application of the six concepts of cancer discussed above is likely to be influenced by future research advances in cancer treatment. Underlying the effects of these six tenets of cancer management on the development of ALL is the effect of genetic pre-disposure on the disease. In other words, research has shown that genetic diversity expedites the acquisition of ALL (van Dongen et al. 2015). Genetics also affect a patient’s rate of inflammation after disease occurrence, thereby fostering multiple hallmark functions (van Dongen et al. 2015).
In a study to understand the role of the TEL-AMLI fusion gene in predicting the outcome of clinical trials for the management of ALL, it was established that chromosomal translocations play a vital role in the efficacy of ALL treatments (Zelent, Greaves & Enver 2004). Particularly, researchers established that these translocations influenced the efficacy of hematopoietic neoplasm. Genes that have transcription factors often moderate this relationship. Overall, they play a critical role in normal hematopoiesis (Zelent, Greaves & Enver 2004).
Chromosomal translocations are also known to generate chimeric genes. In turn, chimeric genes promote oncoprotein fusion. These processes are part of a larger leukemogenic process development associated with translocation genes, which are usually stable and consistent (Zelent, Greaves & Enver 2004). At the same time, they provide consistent molecular markers for a specific type of disease, which later adds to leukemogenic processes (Zelent, Greaves & Enver 2004). The most common gene recombination is the chromosomal translocation. It is often reported in cases involving pediatric cancers because it occurs in about 25% of Leukemic cases (Zelent, Greaves & Enver 2004).
Advances in research, which have been reported within the last decade have also highlighted the pivotal role played by reprogramming of energy metabolism in influencing the growth and spread of ALL. At the same time, the role of a patient’s immunity in influencing disease outcomes is also known to affect the treatment and management of ALL (Sun, Chang & Zhu 2017).
In a study conducted by O’Connor et al. (2018) to find out the Minimal Residual Disease (MRD) interpretation for classifying Leukemic diseases in pediatric patients, it was established that MRD was also an important risk factor in the determination of ALL. The same relationship is true for genetic abnormalities because they affected ALL rates as well (Malouf & Ottersbach 2017). At present, researchers have identified inconsistencies in assessing the MRD risk as a potential problem affecting the outcomes of ALL management (Yokota & Kanakura 2016).
Relative to this assertion, it is established that current risk algorithms used in ALL treatment often create a dichotomy of MRD data without assimilating genetic information to assess MRD and ALL risks (O’Connor et al. 2018). These problems are known to minimize the predictive accuracy of ALL risk factors (O’Connor et al. 2018).
Although scientific advances in research have made it possible to effectively categorize MRD risk groups, there is a challenge in their inability to determine the response kinetics of specific genetic subtypes. In line with this recommendation, future researchers are encouraged to consider integrating MRD with genetic information to identify patients who have a high risk of relapse (O’Connor et al. 2018).
Immunotherapy
Few immunotherapy techniques have been used to treat pediatric cancers such as ALL. Despite their limitations, immunotherapy has shown promising results in creating antitumor effects (Mackall, Merchant & Fry 2014). For example, Monoclonal antibodies targeting cell-mediated cytotoxicity have shown a high rate of success in improving the survival rates for patients who suffer from neuroblastoma (Mackall, Merchant & Fry 2014). Additional research has shown the power of immunotherapy in increasing remission rates for cancers, as was seen in the high remission rates among patients who have acute B-cell lymphoblastic leukemia (B-ALL) (Mackall, Merchant & Fry 2014).
The risk of relapse is often associated with MRD (Vora et al. 2013). Here, MRD risk stratification is often used to assess whether the treatment of ALL could be moderated, or not (Vora et al. 2013). This view is supported by a research study conducted by Vora et al. (2013) which investigated whether treatment intensity for ALL could be moderated using MRD stratification. The researchers established that treatment reduction could be achieved among patients who had a rapid clearance of MRD (Vora et al. 2013). Nonetheless, no randomized study has shown that treatment by MRD improves the health condition for patients who are suffering from ALL.
The successes of immunotherapies are associated with increased accuracy levels of amplifying existent antitumor immunity (Mackall, Merchant & Fry 2014). The potential for immunotherapy to induce durable antitumor immune responses in ALL (among other types of cancers) is also another basis for its success.
Here, it should be understood that immunotherapy is not part of a small contingent of treatment techniques because it represents a wide spectrum of therapeutic approaches, which include monoclonal antibodies, tumor vaccines, and adoptive therapies (among other techniques) (Mackall, Merchant & Fry 2014). Most immunotherapy approaches rely on T-cells and natural killer cells to realize the best outcomes (Mackall, Merchant & Fry 2014).
Relative to the above views, T-Cell therapy has been identified to improve the management and treatment of ALL because of its potential to improve immune system functions (Milne 2019). In some quarters, the therapy has been linked with a paradigm shift in medical research surrounding the treatment of ALL because of its potential to expand and improve the specificity of disease management techniques (Milne 2019). CD19CAR transfer is a related treatment method.
Its main advantages include the improved targeting of ALL, a broader spectrum of applications, and decreased toxicity (Milne 2019). At the same time, this treatment method is regarded as having a high potential for success because it redirects the specificity of T-cells (Milne 2019). This process is associated with viral gene transfers, which are used to stabilize patients’ health. In line with this view, the potential for improved success is enhanced because the CD19CAR is rewired to recognize leukemia cells. The outcome is an expression of CD 19 surface antigen (Milne 2019).
Animal Modelling
Based on the above-mentioned developments, researchers and medics have attempted to introduce new and effective drugs to treat ALL through animal modeling. Although most of them have failed in the earlier stages of a trial, this area of research still shows a lot of promise (Zelent, Greaves & Enver 2004). As Milne (2019) contends, animal modeling is not a new area of research because it has been successfully used to improve research test outcomes in cancer research. Studies that have focused on the treatment of ALL are largely associated with chromosome translocations (Zelent, Greaves & Enver 2004).
Particularly, the evidence used to support such a claim has been partly focused on mixed-lineage leukemia through gene fusion analysis. Fusions have been conducted in a frame with multiple partner genes to create novel fusion proteins using mixed-lineage leukemia (Zelent, Greaves & Enver 2004). The by-product is mixed lineage leukemia and novel fusion proteins (MLL-FPS) (Zelent, Greaves & Enver 2004).
The MLL-FPS is commonly associated with the treatment of aggressive acute leukemia. Advancements in ALL treatment are also based on animal modeling. This technique has been used to understand underlying disease mechanisms and to review the efficacy of novel therapeutic approaches (Zelent, Greaves & Enver 2004). Research has also shown that patients who have MLL-FPs have few cooperating mutations, thereby justifying undertaking animal modeling (Zelent, Greaves & Enver 2004).
An acceptance of the basic principle that MLL-FP is the preferred type of driver mutation in ALL diagnosis has paved the way for researchers to undertake a series of investigations aimed at understanding different aspects of MLL-FP leukemogenesis. In line with this study focus, an investigation by Milne (2019) shows that mice have been used for animal modeling in the development of treatment methods for myeloid leukemia. The researcher also suggests that the lessons learned in earlier clinical trials aimed at improving the treatment and management of acute lymphoblastic could be used to improve the flexibility and dynamism of future clinical trials so that they have a higher probability of success (Milne 2019).
Next-Generation Sequencing (NGS)
Based on the developments made in the treatment of ALL, some researchers have explored the role of next-generation sequencing in monitoring ALL. Such is the case of Kotrova et al. (2017) who say that MRD is the most important prognostic factor in detecting cancer. Since MRD has been segmented into different treatment groups, there has been an improved level of positive treatment outcomes associated with the process.
In other words, cure rates have dramatically improved across different age groups based on an application of the technique. In light of this progress, it is established that clonal immunoglobulin and T-cell receptor genes are important factors in MRD analysis (Kotrova et al. 2017). Notably clonal immunoglobulin and T-cell receptor genes are regarded as the “gold standard” in ALL research because they have a low sensitivity rate and can be generalized (Kotrova et al. 2017). At the same time, they provide accurate MRD quantification (Kotrova et al. 2017).
Recent advances in next-generation sequencing show that there is a need to develop NGS-based MRD assays. At the same time, a high sensitivity ratio can be achieved using this technique if a large number of cells are used (Kotrova et al. 2017). The same criterion has been used in predicting relapse rates among patients because of its specificity (Kotrova et al. 2017). This technique is unlike the real-time quantitative method, which has a lower specificity rate.
The next-generation sequencing technology is also regarded as a tool for generating information about physiological T-cell receptors. This information is useful before and after the treatment of ALL because it has a significant impact on the outcome of an associated prognosis. Nonetheless, some researchers point to the need to address several issues regarding the use of the NGS-MRD model (Kotrova et al. 2017). For example, they highlight the need to standardize workflows (Kotrova et al. 2017).
This process should not only be limited to the analysis phase but also the pre-analytical stage. The post-analytical phase, which usually includes bioinformatics and guidelines for correcting data interpretation, may also benefit from the same model through enhanced accuracy levels. Currently, a European Network of medical workers called the EuroClonality-NGS Consortium is working on these issues (Kotrova et al. 2017). Broadly, these insights show that NGS is a reliable tool for detecting MRD. Doing so has the potential to overcome the limitations of ALL detection.
Conclusion
This paper has highlighted the progress made in treating ALL by exploring advancements in T-cell, animal modeling, gene fusion, cell therapy, immunotherapy, and next-generation sequencing techniques.
These treatment methods have shown significant progress in improving the efficacy of current therapies. However, it is important to note that they share a strong relationship with MRD, which has been used to classify Leukemic diseases in pediatric patients for a long time. Nonetheless, immunotherapy has shown the most promise in providing reliable ALL treatment techniques, as has been observed in its ability to amplify existent antitumor immunity.
Reference List
Boissel, N & Sender, LS 2015, ‘Best practices in adolescent and young adult patients with acute lymphoblastic leukemia: a focus on Asparaginase’, Journal of Adolescent and Young Adult Oncology, vol. 4, no. 3, pp. 118-28.
George, B, Kantarjian, H, Jabbour, E & Jain, N 2016, ‘Role of inotuzumab ozogamicin in the treatment of relapsed/refractory acute lymphoblastic leukemia’, Immunotherapy, vol. 8, no. 2, pp. 135-43.
Hanahan, D & Weinberg, RA 2011, ‘Hallmarks of cancer: the next generation’, Cell, vol. 144, no. 5, pp. 646-74.
Kotrova, M, Trka, J, Kneba, M & Bru¨ggemann, M 2017, ‘ Is next-generation sequencing the way to go for residual disease monitoring in Acute Lymphoblastic Leukemia?’, Molecular Diagnosis & Therapy, vol. 21, no. 1, pp. 481-492.
Lamble, A, Phelan, R & Burke, M 2017, ‘When less is good, is none better? The prognostic and therapeutic significance of Peri-transplant minimal residual disease assessment in Pediatric Acute Lymphoblastic Leukemia’, Journal of Clinical Medicine, vol. 6, no. 7, pp. 66-68.
Leonard, J & Stock, W 2017, ‘Progress in adult ALL: incorporation of new agents to frontline treatment’, Hematology. American Society of Hematology. Education Program, vol. 7, no. 1, pp. 28-36.
Li, SY, Ye, JY, Liang, EY, Zhou, LX & Yang, M 2015, ‘Association between MTHFR C677T polymorphism and risk of acute lymphoblastic leukemia: a meta-analysis based on 51 case-control studies’, Medical Science Monitor: International Medical Journal of Experimental and Clinical Research, vol. 21, no. 1, pp. 740-8.
López-Villar, E, Wang, X, Madero, L & Cho, WC 2014, ‘Application of oncoproteomics to aberrant signaling networks in changing the treatment paradigm in acute lymphoblastic leukemia’, Journal of Cellular and Molecular Medicine, vol. 19, no. 1, pp. 46-52.
Luan, C, Yang, Z & Chen, B 2015, ‘The functional role of microRNA in acute lymphoblastic leukemia: relevance for diagnosis, differential diagnosis, prognosis, and therapy’, OncoTargets and Therapy, vol. 8, no. 1, pp. 2903-14.
Mackall, CL, Merchant, MS & Fry, TJ 2014, ‘Immune-based therapies for childhood cancer’, Nature Reviews Clinical Oncology, vol. 11, no. 12, pp. 693-703.
Malouf, C & Ottersbach, K 2017, ‘Molecular processes involved in B cell acute lymphoblastic leukemia’, Cellular and Molecular Life Sciences, vol. 75, no. 3, pp. 417-446.
Milne, TA 2019, ‘Mouse models of MLL leukemia: recapitulating the human disease’, Blood Journal, vol. 129, no. 16, pp. 2217-2223.
O’Connor, D, Enshaei, A, BartramJeremy, J & Hancock, J 2018, ‘Genotype-specific minimal residual disease interpretation improves stratification in Paediatric Acute Lymphoblastic leukemia’, Journal of Clinical Oncology, vol. 36, no. 1, pp. 33-47.
Pierro, J, Hogan, LE, Bhatla, T & Carroll, WL 2017, ‘New targeted therapies for relapsed paediatric acute lymphoblastic leukemia’, Expert Review of Anticancer Therapy, vol. 17, no. 8, pp. 725-736.
Sun, C, Chang, L & Zhu, X 2017, ‘Pathogenesis of ETV6/RUNX1-positive childhood acute lymphoblastic leukemia and mechanisms underlying its relapse’, Oncotarget, vol. 8, no. 21, pp. 35445-35459.
Terwilliger, T & Abdul-Hay, M 2017, ‘Acute lymphoblastic leukemia: a comprehensive review and 2017 update’, Blood Cancer Journal, vol. 7, no. 6, pp. 57-69.
van Dongen, JJ, van der Velden, VH, Brüggemann, M & Orfao, A 2015, ‘Minimal residual disease diagnostics in acute lymphoblastic leukemia: the need for sensitive, fast, and standardized technologies’, Blood, vol. 125, no. 26, pp. 3996-4009.
Vora, A, Goulden, N, Wade, R, Mitchell, C, Hancock, J, Hough, R, Rowntree, C & Richards, S 2013, ‘Treatment reduction for children and young adults with low-risk acute lymphoblastic leukemia defined by minimal residual disease (UKALL 2003): a randomised controlled trial’, Lancet Oncology, vol. 14, no. 1, pp. 199-209.
Yokota, T & Kanakura, Y 2016, ‘Genetic abnormalities associated with acute lymphoblastic leukemia’, Cancer Science, vol. 107, no. 6, pp. 721-5.
Zelent, A, Greaves, M & Enver, T 2004, ‘Role of the TEL-AML1 fusion gene in the molecular pathogenesis of childhood acute lymphoblastic leukemia’, Oncogene, vol. 23, no. 1, pp. 4275-4283.