Next Article in Journal
Arterial Calcification as a Pseudoxanthoma Elasticum-like Manifestation in Beta-Thalassemia: Molecular Mechanisms and Significance
Previous Article in Journal
Effect of Omega-3 in Patients Undergoing Bone Marrow Transplantation: A Narrative Review
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Review

Beyond TKIs: Advancing Therapeutic Frontiers with Immunotherapy, Targeted Agents, and Combination Strategies in Resistant Chronic Myeloid Leukemia

1
Department of Internal Medicine, College of Medicine, RAK Medical and Health Science University, Ras al Khaimah 11172, United Arab Emirates
2
College of Pharmacy, RAK Medical and Health Science University, Ras al Khaimah 11172, United Arab Emirates
3
Promise Department, School of Medicine, University of Palermo, 90127 Palermo, Italy
*
Author to whom correspondence should be addressed.
Submission received: 8 November 2024 / Revised: 19 February 2025 / Accepted: 7 March 2025 / Published: 11 March 2025

Abstract

:
Background: Chronic myeloid leukemia (CML) relates to the abnormal presence of the Philadelphia chromosome, which originates the production of the BCR-ABL1 fusion protein and therefore leads to neoplastic transformation and unregulated cell growth. The advent of tyrosine kinase inhibitors (TKIs) has resulted in tremendous improvements in CML scenarios; however, there are practical difficulties, especially considering the late stages of the disease. This review examines recently developed strategies that are intended to increase the efficiency of treatment by overcoming TKI resistance. Methods: We performed a literature review of such databases as PubMed, Scopus, Web of Science, and Embase for the last ten years. The following keywords were used in the studies: ‘CML’, ‘TKI resistance’, ‘novel therapies’, ‘immunotherapy’, ‘targeted agents’, and ‘combination therapies’. Only those studies were included that were clinical trials and preclinical across-the-board developmental programs that attempt to target the tumor at multiple levels and not just focus on basic first-line TKIs. Results: In CML patients who do not respond to TKIs, novel therapeutics encompass ponatinib, asciminib, CAR-T immunotherapy, and BCL-2 and mTOR inhibition in conjunction with TKI therapy. This addresses both BCR-ABL1-dependent and independent resistance mechanisms, increasing the chance of achieving deeper molecular response and reduced toxicity. Nonetheless, they exhibit diverse characteristics regarding efficacy, safety, cost, and quality of life effects. Discussion: Nonetheless, numerous challenges remain regarding the understanding of the mechanisms of resistance, the long-term efficacy of novel medicines, and the ideal combinations to attain optimal outcomes. Areas of future research include the search for other patterns of molecular resistance, tailoring specific treatments to patients, and incorporating AI to improve diagnosis and monitoring. Conclusion: The introduction of novel therapeutic techniques into clinical practice needs a collaborative approach and persistent dynamism to new findings from research. Our analysis indicates that the challenges posed by resistant CML disease are complex and require further improvements in therapeutic and clinical protocol development.

1. Introduction

1.1. Background of Chronic Myeloid Leukemia (CML)

Chronic myeloid leukemia, or CML, is a clonal myeloproliferative condition that has its origin in hematopoietic stem cells found in the bone marrow. The fusion of chromosomes 22 and 9, which are translocated, is mostly associated with this kind of leukemia, known as the Philadelphia chromosome [1]. As a result of the BCR-ABL1 gene fusing, leukemic cells begin to proliferate uncontrollably as they code for a permanently active tyrosine kinase. In summary, excessive cell division is accompanied by inhibition of cellular apoptosis [2]. The disease progresses from the chronic phase to the accelerated phase and then the blast crisis phase. Often patients who are asymptomatic during the chronic phase are diagnosed when the condition is close to or has evolved into a more severe form, which closely resembles an acute form of leukemia [3,4].

1.2. Historical Impact of Tyrosine Kinase Inhibitors (TKIs) on CML Treatment and Outcomes

The management of chronic myeloid leukemia was transformed with the commercialization of imatinib mesylate in the early 2000s, followed by other third-generation tyrosine kinase inhibitors (TKIs). Chronic myeloid leukemia has drastically evolved. It is no longer seen as a condition requiring only end-of-life care, as its effective pharmaceutical treatment has become possible [5]. This class of tyrosine kinase inhibitors completely changed the face of the disease, converting it from an uncontrolled process to one that is chronic and manageable. Dasatinib and nilotinib emerged as second-generation TKIs after imatinib, and they were more potent than the first-generation drug [6]. The advancement of third-generation TKIs, like ponatinib, facilitated the creation of treatments for more intricate mutations, such as T315I, thereby broadening the therapeutic repertoire [7,8]. The development of third-generation TKIs, such as ponatinib, allowed drugs with more complex mutations, like T315I, to be developed, expanding the therapeutic arsenal even further [7,8]. These advancements have not only improved survival rates but have also made treatment-free remission a possibility for some patients, signaling unprecedented success in the treatment of CML.

1.3. Limitations of Current TKI Therapies

The use of TKIs has proven effective; however, several side effects have arisen in this instance that affect their long-term benefits. Firstly, resistance development owing to mutations in the BCR-ABL1 gene remains a major barrier, most notably the T315I mutation [9,10]. Moreover, the adverse effects of TKI therapy, ranging from mild to severe, such as cardiovascular hazards, hepatic toxicity, and bone marrow suppression, complicate clinical management. More so, TKI resistance could also be developed by means other than BCR-ABL1, such as triggering other signaling pathways and epigenetic alterations, causing a complex therapeutic environment [11,12]. It has been established that leukemic stem cells are present in patients who achieve remission with TKIs, and this supports the call for new treatment modalities that would eliminate these cells and avoid disease progression [13].
The present review will address the concept of the next-generation CML therapeutic regimen with emphasis on the recent progress in the fields of immunotherapy, targeting agents, and combination approaches, aimed at the TKI-resistant CML population and improvement of the disease burden. These novel therapies are expected to provide more sustained responses with reduced toxicity, which are the key unmet needs of patients with resistant or refractory CML.

1.4. Objective and Scope of the Review

Given the challenges associated with current therapies, there is a clear need to explore novel therapeutic strategies for CML, particularly for patients who do not respond adequately to existing TKIs.
This review critically assesses recent advancements in the treatment of chronic myeloid leukemia (CML), with a particular focus on three key areas. First, it explores combination therapies that involve tyrosine kinase inhibitors (TKIs) used alongside other drugs targeting various cellular pathways and mechanisms. Secondly, the review evaluates the role of immunotherapy in CML treatment, including the application of CAR-T cell therapies and immune checkpoint inhibitors. Lastly, it investigates next-generation targeted agents that address resistance mechanisms or introduce novel modes of action against CML cells.
This comprehensive review will delve into emerging research and clinical developments to provide insights into potential new directions in CML treatment, with the goal of overcoming resistance and improving patient outcomes.

2. Search Databases and Inclusion/Exclusion Criteria

The literature review focuses on the most recent scientific evidence. A comprehensive search was conducted using the PubMed, Scopus, Web of Science, and Embase databases.

2.1. Inclusion Criteria

The inclusion criteria for the study were studies published within the last ten years, encompassing both clinical trials and preclinical studies, and focusing on novel therapeutic strategies beyond first-line TKIs.

2.2. Exclusion Criteria

The exclusion criteria for the study were studies focusing exclusively on first-line TKI treatments and duplicate articles or studies with incomplete clinical data.
This search strategy ensures a focused and relevant selection of high-quality literature, aligning with the review’s objective of evaluating emerging therapies for resistant CML.

3. Results and Discussion

3.1. Mechanisms of Resistance in CML Patients

The management of chronic myeloid leukemia (CML) faces significant hurdles due to the development of resistance to tyrosine kinase inhibitors (TKIs), which are the cornerstone of treatment. This resistance can be categorized into BCR-ABL-dependent and independent mechanisms, each contributing to disease progression and impacting therapeutic strategies.

3.1.1. BCR-ABL-Dependent Mechanisms

1.
Mutations:
The T315I mutation remains one of the most challenging resistance factors, as it renders almost all first- and second-generation TKIs ineffective. This mutation changes the amino acid threonine to isoleucine at position 315, thereby altering the TKI binding site and reducing drug binding affinity. Ponatinib and asciminib are specifically designed to target and inhibit the activity of this mutant form of BCR-ABL [14,15]. Ponatinib targets multiple kinases, offering efficacy against a range of mutations, including T315I. Asciminib, on the other hand, binds to a myristoyl site of BCR-ABL, providing an alternative inhibition mechanism that remains effective even with the presence of the T315I mutation.
2.
Overexpression of the BCR-ABL Gene:
Overexpression of the BCR-ABL gene leads to increased tyrosine kinase activity, which can overwhelm the inhibitory effects of TKIs. This overexpression may result from gene amplification or enhanced promoter activity and has been associated with accelerated disease progression and poor responses to standard doses of TKIs [16].

3.1.2. BCR-ABL-Independent Mechanisms

1.
Activation of Alternative Signaling Pathways:
CML cells can activate other proliferative and survival pathways, such as the JAK-STAT, MAPK, and PI3K-AKT pathways, which can support the survival of leukemic cells independent of BCR-ABL kinase activity (Figure 1). These pathways might be upregulated due to genetic or epigenetic alterations in their components, contributing to resistance even in the presence of effective BCR-ABL inhibition [5,17].
In addition to the classical signaling pathways, resistance in CML may also involve the overexpression or activation of various growth factor receptors like PDGFR or FGFR, which can activate similar downstream signaling cascades as BCR-ABL, promoting cell survival and proliferation.
Furthermore, the bone marrow stromal environment can contribute to resistance by providing protective signals that promote the survival of leukemic cells independent of BCR-ABL activity. These signals might be mediated through cytokines or direct cell-to-cell contact.
2.
Epigenetic Modifications:
Epigenetic changes such as DNA methylation and histone modifications can lead to the activation of oncogenes or the suppression of tumor suppressor genes, facilitating resistance. These modifications can confer a survival advantage to leukemic cells under the selective pressure of therapy [18,19].
Ongoing research is important not only for elucidating the molecular basis of TKI resistance but also for monitoring the development of novel agents capable of tackling these issues.

3.2. Emerging Therapies for Resistant Chronic Myeloid Leukemia

3.2.1. Clinical Trials

Chronic myeloid leukemia (CML) is still an obstinate disease, more so when standard tyrosine kinase inhibitor (TKI) treatment is met with resistance. This section highlights advancements in addressing resistant forms of disease by introducing innovative agents and strategic therapeutic combinations. These approaches specifically target the molecular mechanisms responsible for resistance, aiming to enhance treatment effectiveness while reducing associated adverse effects. (Figure 2) Even though T315I is an important mutation involved in resistance, great strides have been made in CML management with the use of TKIs (Table 1).

3.2.2. Real-World Evidence

With the continuing advancement in the management of chronic myeloid leukemia (CML), the role of strong clinical data to support the therapy in resistant cases becomes crucial. Table 2 outlines the filed clinical studies as well as real-life cases that provide some insights into the use of new therapies for resistant CML.

3.2.3. Comparative Analysis of Emerging Therapies for Resistant Chronic Myeloid Leukemia (CML)

As the treatment options for chronic myeloid leukemia (CML) continue to expand, it is crucial to understand not only the efficacy of new therapies but also their safety profiles, costs, and impacts on patient quality of life. This comparative analysis seeks to elucidate the distinctions among these emerging therapies by evaluating their efficacy, safety profiles, associated costs, and their impacts on patient quality of life.
Table 3 below consolidates the most recent information obtained from clinical trials and other studies, enabling straightforward comparison of various therapies. This comparative method aims to assist healthcare professionals, researchers, and other stakeholders in evaluating the feasibility of integrating new therapies into standard clinical practice.

3.3. Challenges and Future Directions for Resistant CML Therapies

Treatment-resistant chronic myeloid leukemia (CML) presents critical challenges that limit the efficacy of traditional therapies, necessitating research into novel approaches. This section focuses on the different issues related to and possible future directions for the management of resistant CML, detailing the diversity of the resistance mechanisms that are an inherent problem, the side effects of the novel therapies, the politics regarding money, and the important issue of affordability of therapies. In the case of each of these concerns, the varying forms of resistance, the long-term effects of newer modalities, etc.
We also consider potential solutions such as personalized approaches, sophisticated molecular assays, and better methodologies for patient selection and grouping to increase the efficacy and safety of therapy.
In addition, Table 4 outlines the strategies that would fill the gaps in knowledge so far available, particularly emphasizing advanced clinical trials and the development of new predictive biomarkers, making treatments more cost-effective. This study aims to alleviate the challenges associated with treating resistant CML while simultaneously developing attributes that enhance patient management.

3.4. Clinical Implications for Practice in Resistant Chronic Myeloid Leukemia

The most critical aspect of the CML patient care is the management of chronic myeloid leukemia. This disease is relatively easy to treat with conventional imatinib, but still, a considerable number of individuals will develop diseases that are resistant to TKI therapy. These considerations vary from patient to patient and from one type of disease to another.

3.4.1. Clinical Factors That Affect the Treatment Choices of Patients with Resistant Chronic Myeloid Leukemia

About managing individual patients suffering from chronic myeloid leukemia (CML), towards the second objective, including where there is a failure of first-line tyrosine kinase inhibitors (TKIs), a range of clinical and patient-related factors cumulatively affect the decision-making. This multifactorial decision-making structure forms the basis on which resistant CML treatment approaches are constructed (Figure 3).

3.4.2. Criteria for Switching from TKIs to New Therapies

Molecular Response:
  • Major Molecular Response (MMR): Achieving and maintaining MMR is a critical factor. Patients who do not achieve MMR within a specific timeframe may need to switch therapies. For instance, patients who do not achieve MMR within 12 months of treatment may experience shorter cytogenetic remission and poorer outcomes, suggesting the need for alternative therapies [71].
  • Molecular Recurrence (MRec): Discontinuation of TKIs can be considered if patients achieve a deep molecular response, such as undetectable BCR-ABL1 levels. However, detectable BCR-ABL1 by real-time quantitative PCR (RQ-PCR) or droplet digital PCR (ddPCR) at the time of TKI discontinuation is associated with a higher risk of MRec, indicating that these patients might need to continue or switch therapies [72].
  • Treatment-Free Remission (TFR): Successful TFR is another criterion. Patients who maintain TFR without molecular recurrence may not need to switch therapies, but those who relapse may require re-initiation or switching of TKIs.
Health risks and Adverse Effects:
Hematological Toxicity: Severe hematological toxicity (grade 3–4) is a significant adverse effect associated with TKIs. Patients experiencing severe hematological toxicity have lower rates of complete cytogenetic response (CCyR) and MMR, and poorer progression-free survival (PFS) and overall survival (OS), suggesting the need for alternative therapies [73].
Cardiovascular Toxicities: TKIs, especially second and third-generation ones, are associated with serious cardiovascular adverse effects, including reduced left ventricular ejection fraction and symptomatic heart failure. Monitoring and managing these toxicities are crucial, and persistent cardiovascular issues may necessitate switching therapies [74].
Thyroid Dysfunction: Thyroid abnormalities, including hypothyroidism and hyperthyroidism, are common with second-generation TKIs. Persistent or severe thyroid dysfunction, particularly autoimmune thyroiditis, may require switching therapies [75].
Other Adverse Effects: Fatigue, diarrhea, and other patient-reported outcomes (PROs) significantly impact the quality of life. Discontinuation of TKIs has been associated with improvements in these symptoms, and persistent adverse effects may warrant switching therapies [76].

3.4.3. Managing Treatment-Related Toxicity and Maintaining Quality of Life

Toxicity Management: Given the numerous difficulties associated with these leukemias, the treatment is likely to entail significant adverse effects; therefore, prioritizing the control of these toxicities is essential. This may involve dosage adjustments, temporarily halting the therapy, or considering alternative treatment options [77].
Life Quality: Clinical decisions should be informed by the ongoing assessment of quality of life, aligning with treatment goals and the individual’s health status and life aspirations. Psychological therapy and additional supporting interventions should be provided [78].

3.5. Personalized Treatment Approaches

Pharmacogenetics and patient-specific phenotyping have been substantially utilized in the advancement of personalized medicine in the management of chronic myeloid leukemia (CML). These strategies facilitate the customization of drug regimens by enabling the strategic combination of innovative treatments such as CAR-T cells and immune checkpoint inhibitors with diverse therapeutic agents, such as TKIs, and the adjustment of doses. This method is especially beneficial for patients who are resistant to conventional therapies. In addition, the real-time adjustment of treatment plans is facilitated by ongoing quantitative molecular assessments, which offer a dynamic response to the evolution of the disease or emergent drug resistance.
The optimization of clinical outcomes in a personalized manner is guaranteed by this proactive strategy, which ensures that treatment remains ahead of disease progression and is continuously aligned with the individual’s changing health requirements.

3.6. Limitations of the Review

3.6.1. Limitations Due to the Availability of Literature and Clinical Trials

This literature review is equally constrained by clinical trials published literature and global clinical trials conducted before the year 2024. Since the review of the more recent medical literature and emerging data by the last half of the current year are not included, it would alter the understanding of the treatment strategies for resistant CML. Recent advances might not be well represented in relation to this time frame set forth policy, especially gene editing and molecular authority, which are fast-developing subjects.

3.6.2. Possible Publication Bias

The publication of effective studies is more prevalent than those that produce negative or inconclusive results. This, in turn, increases the effectiveness and perceived efficacy of the therapies discussed, resulting in the overestimation of benefits associated with novel treatment for CML or the underestimation of risks. It is crucial to underscore that in order to accurately represent the treatment landscape, unpublished data and negative outcome studies must also be incorporated.

3.6.3. Identifying Research Gaps

Progress has been made in the management of CML; however, there are a few crucial gaps that can still be solved to improve the health of the patients even further:
  • Leukemic stem cells are enduring and can be eradicated; however, current medicines can only mature leukemic cells without eliminating leukemic stem cells. This gap results in the persistence of the disease and recurrence. Subsequent research should develop techniques that specifically target these stem cells.
  • Understanding inhibition mechanisms related to drug resistance: Despite the availability of third-generation TKIs, resistance remains a significant concern. Increased emphasis is necessary on the source of resistance mechanisms, especially concerning recent mutations that existing medicines do not address.
  • Significant impact and danger for the duration of emerging medicines: There is a lack of long-term data on the safety and efficacy of numerous novel TKI therapies and immunotherapies. Conducting longitudinal studies on their impact is essential.
  • The ambit of combination therapy addresses challenges: Although combination therapy offers advantages, there is no unequivocally established ideal treatment strategy. It is essential to examine several drug combinations that may synergize effectively to identify the optimal procedures.
  • Performance Predictors for Treatment: Identifying biomarkers that can forecast a patient’s treatment response signifies a transition towards a more personalized therapeutic approach. This necessitates extensive biomarker discovery and validation research.

3.7. Future Directions and Use of Available Resources and New Technologies

AI and machine learning (ML) technology has brought a revolution in CML diagnosis, monitoring, and treatment.
  • AI in Diagnosis:
AI algorithms have demonstrated remarkable potential in enhancing the diagnosis and management of chronic myeloid leukemia (CML) through the analysis of extensive datasets, encompassing genetic, phenotypic, and clinical information. Notably, AI models such as hybrid convolutional neural network with interactive autodidactic school (HCNN-IAS) and MayGAN have achieved up to 100% accuracy in diagnosing CML from blood smear images, utilizing advanced image processing techniques for segmentation and feature extraction. Similarly, AI systems like support vector machine (SVM), eXtreme gradient boosting (XGBoost), and artificial neural networks (ANN) are employed to analyze gene profiles and clinical parameters, with specific algorithms such as Bi-LSTM integrated with CNN, enhancing the prediction accuracy of CML by processing and normalizing datasets. The capability of AI to amalgamate diverse data types—including biochemical, biomolecular, imaging, and clinical data—further augments the precision of CML diagnosis and prognosis, notably in the analysis of flow cytometry data, which have shown promising results in diagnosing and predicting outcomes for hematological malignancies [79,80,81,82]. AI’s impact extends to early detection, where subtle changes in blood smears and genetic profiles can lead to earlier diagnosis and intervention, thereby significantly enhancing treatment accuracy and reducing the potential for human error. Additionally, AI facilitates the personalization of treatment by identifying molecular subtypes and predicting responses, enabling more tailored and effective therapeutic strategies. However, challenges such as integrating diverse data types and fostering human-AI collaboration remain, with advancements in explainable AI models crucial for building trust and enhancing synergies between clinicians and AI systems. Overall, AI is revolutionizing the approach to CML, offering tools for early detection, high accuracy, and personalized treatment strategies, with the integration of genetic, phenotypic, and clinical data through AI models holding immense promise for improving patient outcomes in CML.
2.
ML in Treatment personalization:
Machine learning (ML) is increasingly critical in personalizing treatment by predicting individual responses to therapies. Trained on diverse therapeutic approaches and continually updated through clinical trial data reviews, ML models enhance treatment strategies by analyzing patient characteristics and predicted outcomes. These models address challenges like data imbalance in treated/control distributions, using techniques like active learning to improve treatment effect estimation reliability. ML supports pharmacogenomics to tailor chemotherapy based on genomic and proteomic data, enhancing treatment efficacy and reducing toxicity [83].
ML model performance is validated using metrics such as discrimination for benefit and calibration, which help evaluate model efficacy in personalized medicine. Integration of ML with electronic health records refines treatment recommendations, considering complex patient factors for tailored treatments [84].
However, implementing ML in treatment personalization faces hurdles such as model interpretability, data quality, and ethical concerns regarding data privacy. Collaborative efforts among clinicians, statisticians, and computer scientists are essential to overcome these challenges and maximize the benefits of ML in healthcare [85].
3.
AI-based Monitoring Accessories:
AI-based monitoring tools are revolutionizing healthcare by enabling real-time tracking of disease progression and treatment responses, enhancing patient outcomes, and optimizing care delivery. These tools use AI-integrated remote patient monitoring (RPM) systems and wearable devices to continuously collect and analyze health data, facilitating quick and informed clinical decisions. They are particularly valuable in managing chronic diseases like heart failure and diabetes by creating personalized treatment plans and adjusting to changes in a patient’s condition. Additionally, AI tools aid in the early detection and proactive management of diseases, integrating with the Internet of Medical Things (IoMT) to handle large datasets and provide actionable insights. However, challenges such as data privacy, security, and the need for robust regulatory frameworks persist. Future technological advancements in AI are expected to further enhance the efficiency and personalization of healthcare [86,87].
4.
Robotic—robotics:
The integration of robotics and automation in laboratory practices significantly enhances the efficiency and accuracy of chronic myeloid leukemia (CML) monitoring. These technologies increase throughput, reduce human error, and ensure precise and consistent sample analysis, making them cost-effective for high-volume testing. In CML monitoring, automated systems like the Xpert BCR-ABL Monitor™ accurately quantify crucial genetic markers, while robotic liquid handlers streamline PCR sample preparations. Compared to manual methods, automation offers superior performance in terms of error rates, reproducibility, and operational efficiency, proving essential for effective CML management and patient care [88,89].
5.
Virtual Reality (VR) and Augmented Reality:
Virtual reality (VR) and augmented reality (AR) are revolutionizing medical education, particularly in teaching complex diseases like chronic myeloid leukemia (CML) at the molecular level. These technologies enhance learning by creating immersive, interactive environments that make complex medical information more accessible and engaging. For example, applications such as MycoAR and VR Baby help students visualize intricate subjects, while tools like ChimeraX facilitate the exploration of molecular structures essential for understanding CML [90,91,92,93,94].
VR and AR are especially beneficial in CML education, where they can construct detailed 3D models of the disease, improving understanding, patient engagement, and treatment compliance. These tools also simulate treatment effects, aiding both patients and healthcare professionals in making informed decisions. Moreover, VR and AR are invaluable for training healthcare professionals on the latest CML research and treatment protocols, ensuring they are well-equipped to manage the disease effectively [95].
Integrating the new therapeutic approaches with advanced technologies will advance the future of CML treatment. Closing the noted research gaps with specific studies and applying AI and ML for diagnostic–procedural augmentations will be paramount in addressing the present gaps in the control of CML diseases. This amalgam approach will not only improve the management of CML on a molecular basis but also assist in converting the understanding into patient management approaches that are more appropriate and effective.

4. Conclusions

There is an apparent growth in the understanding of the disease and hence a shift from the long-standing paradigm of treatment that solely relied on allogeneic HSCT and TKIs for CML patients to a more comprehensive treatment model that utilizes hematopoietic stem cell transplant as part of combination therapy with targeted agents, advanced immunotherapies, and next-generation therapies.
With the recent emergence of novel B cell therapies such as CAR-T cell therapy, host T cells become reprogrammed to attack the leukemic cells and therefore provide additional benefit for patients suffering from chronic myeloid leukemia (CML) resistant to other treatments.
The utilization of combining targeted agents with other therapies has proven to be fundamental in treating CML due to their having the ability to efficiently target multiple areas, which can allow the overcoming of advanced CML and other cancer treatments by using a synergistic approach. Additionally, the novel targeted agents, such as asciminib, allow for high specificity targeting of varying molecular areas of the BCR-ABL protein complex, guiding targeted treatments to patients with specific mutations.
Notably, with these promising alternatives come a number of challenges that are yet to be resolved. The introduction of further new treatments into clinical practice has a certain lag that is the result of the need for education among healthcare providers to develop an understanding of how the new therapies are meant to be used and at what point in the progression of the disease. In addition to that, active efforts still need to be made to fill in this knowledge deficit, which is predominantly about the effectiveness of these treatment methods and their safety profile over a period of time. Wider and more heterogeneous datasets need to be able to confirm findings that have not been conclusively demonstrated in previous studies, thus expanding the scope of the use of these new approaches.
At the same time, there is also an equally strong demand for the development of new biomarkers that can assist in the prescription and prediction of suitable treatment for the specific condition, which further enhances the practical application of personalized medicine within the CML space. Such tools are essential to improve patient care and optimize the treatment regimen offered to match their requirements.

Author Contributions

Conceptualization, I.R. and M.E.-T.; methodology, A.F.W. and I.R.; data curation, I.R.; writing—original draft preparation, I.R., A.F.W. and M.E.-T.; writing—review and editing, I.R., A.F.W. and M.E.-T.; visualization, A.F.W.; supervision, M.R. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Data Availability Statement

No new data were created.

Acknowledgments

We would like to extend our deepest gratitude to Ismail Matalka and Ali Hajeer, for their cooperation and support.

Conflicts of Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

References

  1. Chereda, B.; Melo, J.V. Natural course and biology of CML. Ann. Hematol. 2015, 94, 107–121. [Google Scholar] [CrossRef] [PubMed]
  2. Wolfe, H.R.; Rein, L.A. The evolving landscape of frontline therapy in chronic phase chronic myeloid leukemia (CML). Curr. Hematol. Malig. Rep. 2021, 16, 448–454. [Google Scholar] [CrossRef]
  3. Hochhaus, A.; Wang, J.; Kim, D.D.H.; Mayer, J.; Goh, Y.-T.; le Coutre, P.; Takahashi, N.; Kim, I.; Etienne, G.; Andorsky, D.; et al. Asciminib in Newly Diagnosed Chronic Myeloid Leukemia. New Engl. J. Med. 2024, 391, 885–898. [Google Scholar] [CrossRef] [PubMed]
  4. Towachiraporn, S.; Punnachet, T.; Hantrakun, N.; Piriyakhuntorn, P.; Rattanathammethee, T.; Hantrakool, S.; Chai-Adisaksopha, C.; Rattarittamrong, E.; Norasetthada, L.; Tantiworawit, A. Long-Term Outcomes with Sequential Tyrosine Kinase Inhibitors Treatment in Chronic Myeloid Leukemia Patients. Asian Pac. J. Cancer Prev. APJCP 2023, 24, 1513. [Google Scholar] [CrossRef] [PubMed]
  5. Alves, R.; Gonçalves, A.C.; Rutella, S.; Almeida, A.M.; Rivas, J.D.L.; Trougakos, I.P.; Ribeiro, A.B.S. Resistance to tyrosine kinase inhibitors in chronic myeloid leukemia—From molecular mechanisms to clinical relevance. Cancers 2021, 13, 4820. [Google Scholar] [CrossRef]
  6. Sundaram, D.N.M.; Jiang, X.; Brandwein, J.M.; Valencia-Serna, J.; Remant, K.; Uludağ, H. Current outlook on drug resistance in chronic myeloid leukemia (CML) and potential therapeutic options. Drug Discov. Today 2019, 24, 1355–1369. [Google Scholar] [CrossRef]
  7. Massaro, F.; Molica, M.; Breccia, M. Ponatinib: A review of efficacy and safety. Curr. Cancer Drug Targets 2018, 18, 847–856. [Google Scholar] [CrossRef]
  8. Kantarjian, H.M.; Jabbour, E.; Deininger, M.; Abruzzese, E.; Apperley, J.; Cortes, J.; Chuah, C.; DeAngelo, D.J.; DiPersio, J.; Hochhaus, A.; et al. Ponatinib after failure of second-generation tyrosine kinase inhibitor in resistant chronic-phase chronic myeloid leukemia. Am. J. Hematol. 2022, 97, 1419–1426. [Google Scholar] [CrossRef]
  9. Abasian, Z.; Rostamzadeh, A.; Mohammadi, M.; Hosseini, M.; Rafieian-Kopaei, M. A review on role of medicinal plants in polycystic ovarian syndrome: Pathophysiology, neuroendocrine signaling, therapeutic status and future prospects. Middle East Fertil. Soc. J. 2018, 23, 255–262. [Google Scholar] [CrossRef]
  10. Cuellar, S.; Vozniak, M.; Rhodes, J.; Forcello, N.; Olszta, D. BCR-ABL1 tyrosine kinase inhibitors for the treatment of chronic myeloid leukemia. J. Oncol. Pharm. Pract. 2018, 24, 433–452. [Google Scholar] [CrossRef]
  11. Shyam Sunder, S.; Sharma, U.C.; Pokharel, S. Adverse effects of tyrosine kinase inhibitors in cancer therapy: Pathophysiology, mechanisms and clinical management. Signal Transduct. Target. Ther. 2023, 8, 262. [Google Scholar] [CrossRef] [PubMed]
  12. Cortes, J.E.; Sasaki, K.; Kim, D.-W.; Hughes, T.P.; Etienne, G.; Mauro, M.J.; Hochhaus, A.; Lang, F.; Heinrich, M.C.; Breccia, M.; et al. Asciminib monotherapy in patients with chronic-phase chronic myeloid leukemia with the T315I mutation after ≥1 prior tyrosine kinase inhibitor: 2-year follow-up results. Leukemia 2024, 38, 1–12. [Google Scholar] [CrossRef] [PubMed]
  13. Yeung, D.T.; Shanmuganathan, N.; Hughes, T.P. Asciminib: A new therapeutic option in chronic-phase CML with treatment failure. Blood J. Am. Soc. Hematol. 2022, 139, 3474–3479. [Google Scholar] [CrossRef]
  14. Tomassetti, S.; Lee, J.; Qing, X. A case of chronic myelogenous leukemia with the T315I mutation who progressed to myeloid blast phase and was successfully treated with asciminib. Clin. Case Rep. 2022, 10, e6478. [Google Scholar] [CrossRef]
  15. Miller, G.D.; Bruno, B.J.; Lim, C.S. Resistant mutations in CML and Ph+ ALL–role of ponatinib. Biol. Targets Ther. 2014, 8, 243–254. [Google Scholar]
  16. Chandran, R.K.; Geetha, N.; Sakthivel, K.M.; Aswathy, C.G.; Gopinath, P.; Raj, T.V.A.; Priya, G.; Nair, J.K.K.M.; Sreedharan, H. Genomic amplification of BCR-ABL1 fusion gene and its impact on the disease progression mechanism in patients with chronic myelogenous leukemia. Gene 2019, 686, 85–91. [Google Scholar] [CrossRef] [PubMed]
  17. Valent, P. Targeting the JAK2-STAT5 pathway in CML. Blood J. Am. Soc. Hematol. 2014, 124, 1386–1388. [Google Scholar] [CrossRef]
  18. Awad, S.A.; Brück, O.; Shanmuganathan, N.; Jarvinen, T.; Lähteenmäki, H.; Klievink, J.; Ibrahim, H.; Kytölä, S.; Koskenvesa, P.; Hughes, T.P.; et al. Epigenetic modifier gene mutations in chronic myeloid leukemia (CML) at diagnosis are associated with risk of relapse upon treatment discontinuation. Blood Cancer J. 2022, 12, 69. [Google Scholar] [CrossRef] [PubMed]
  19. Machova Polakova, K.; Koblihova, J.; Stopka, T. Role of epigenetics in chronic myeloid leukemia. Curr. Hematol. Malig. Rep. 2013, 8, 28–36. [Google Scholar] [CrossRef]
  20. Lipton, J.H.; Chuah, C.; Guerci-Bresler, A.; Rosti, G.; Simpson, D.; Assouline, S.; Etienne, G.; Nicolini, F.E.; Le Coutre, P.; Clark, R.; et al. Epic: A phase 3 trial of ponatinib compared with imatinib in patients with newly diagnosed chronic myeloid leukemia in chronic phase (CP-CML). Blood 2014, 124, 519. [Google Scholar] [CrossRef]
  21. Jiang, Q.; Li, Z.; Qin, Y.; Li, W.; Xu, N.; Liu, B.; Zhang, Y.; Meng, L.; Zhu, H.; Du, X.; et al. Correction: Olverembatinib (HQP1351), a well-tolerated and effective tyrosine kinase inhibitor for patients with T315I-mutated chronic myeloid leukemia: Results of an open-label, multicenter phase 1/2 trial. J. Hematol. Oncol. 2023, 16. [Google Scholar] [CrossRef] [PubMed]
  22. Rea, D.; Mauro, M.J.; Boquimpani, C.; Minami, Y.; Lomaia, E.; Voloshin, S.; Turkina, A.; Kim, D.W.; Apperley, J.F.; Abdo, A.; et al. A phase 3, open-label, randomized study of asciminib, a STAMP inhibitor, vs bosutinib in CML after 2 or more prior TKIs. Blood J. Am. Soc. Hematol. 2021, 138, 2031–2041. [Google Scholar]
  23. Zou, J.-Y.; Huang, S.-M.; Zhoub, H.-X.; Xu, M.-Z.; Sun, A.-N.; Wu, D.-P.; Xue, S.-L.; Zhang, T.-T. Combination of venetoclax with BCR-ABL tyrosine kinase inhibitor as a therapeutic strategy for Philadelphia chromosome-positive leukemias. Hematology 2023, 28, 2237790. [Google Scholar] [CrossRef]
  24. Maiti, A.; Franquiz, M.J.; Ravandi, F.; Cortes, J.E.; Jabbour, E.J.; Sasaki, K.; Marx, K.; Daver, N.G.; Kadia, T.M.; Konopleva, M.Y.; et al. Venetoclax and BCR-ABL tyrosine kinase inhibitor combinations: Outcome in patients with philadelphia chromosome-positive advanced myeloid leukemias. Acta Haematol. 2021, 143, 567–573. [Google Scholar] [CrossRef] [PubMed]
  25. Beagle, B.R.; Nguyen, D.M.; Mallya, S.; Tang, S.S.; Lu, M.; Zeng, Z.; Konopleva, M.; Vo, T.T.; Fruman, D.A. mTOR kinase inhibitors synergize with histone deacetylase inhibitors to kill B-cell acute lymphoblastic leukemia cells. Oncotarget 2014, 6, 2088. [Google Scholar] [CrossRef]
  26. Mitchell, R.; Hopcroft, L.E.; Baquero, P.; Allan, E.K.; Hewit, K.; James, D.; Hamilton, G.; Mukhopadhyay, A.; O’prey, J.; Hair, A.; et al. Targeting BCR-ABL-independent TKI resistance in chronic myeloid leukemia by mTOR and autophagy inhibition. JNCI J. Natl. Cancer Inst. 2018, 110, 467–478. [Google Scholar] [CrossRef]
  27. Hofmann, S.; Schubert, M.-L.; Wang, L.; He, B.; Neuber, B.; Dreger, P.; Müller-Tidow, C.; Schmitt, M. Chimeric antigen receptor (CAR) T cell therapy in acute myeloid leukemia (AML). J. Clin. Med. 2019, 8, 200. [Google Scholar] [CrossRef]
  28. Fiorenza, S.; Turtle, C.J. CAR-T cell therapy for acute myeloid leukemia: Preclinical rationale, current clinical progress, and barriers to success. BioDrugs 2021, 35, 281–302. [Google Scholar] [CrossRef]
  29. Xu, X.; Huang, S.; Xiao, X.; Sun, Q.; Liang, X.; Chen, S.; Zhao, Z.; Huo, Z.; Tu, S.; Li, Y. Challenges and clinical strategies of CAR T-cell therapy for acute lymphoblastic leukemia: Overview and developments. Front. Immunol. 2021, 11, 569117. [Google Scholar] [CrossRef]
  30. Champlin, R.; Jabbour, E.; Kebriaei, P.; Anderlini, P.; Andersson, B.; de Lima, M. Allogeneic stem cell transplantation for chronic myeloid leukemia resistant to tyrosine kinase inhibitors. Clin. Lymphoma Myeloma Leuk. 2011, 11, S96–S100. [Google Scholar] [CrossRef]
  31. Radich, J. Stem Cell Transplant for Chronic Myeloid Leukemia in the Imatinib Era. In Seminars in Hematology; Elsevier: Amsterdam, The Netherlands, 2010. [Google Scholar]
  32. Wang, Z.-Q.; Zhang, Z.-C.; Wu, Y.-Y.; Pi, Y.-N.; Lou, S.-H.; Liu, T.-B.; Lou, G.; Yang, C. Bromodomain and extraterminal (BET) proteins: Biological functions, diseases, and targeted therapy. Signal Transduct. Target. Ther. 2023, 8, 420. [Google Scholar] [CrossRef] [PubMed]
  33. Alqahtani, A.; Choucair, K.; Ashraf, M.; Hammouda, D.M.; Alloghbi, A.; Khan, T.; Senzer, N.; Nemunaitis, J. Bromodomain and extra-terminal motif inhibitors: A review of preclinical and clinical advances in cancer therapy. Future Sci. OA 2019, 5, FSO372. [Google Scholar] [CrossRef] [PubMed]
  34. Cortes, J.; Apperley Elza Lomaia, J.; Moiraghi, B.; Undurraga Sutton, M.; Pavlovsky, C.; Chuah, C.; Sacha, T.; Lipton, J.H.; Schiffer, C.A.; McCloskey, J.; et al. Ponatinib dose-ranging study in chronic-phase chronic myeloid leukemia: A randomized, open-label phase 2 clinical trial. Blood J. Am. Soc. Hematol. 2021, 138, 2042–2050. [Google Scholar] [CrossRef] [PubMed]
  35. Sanford, D.; Kantarjian, H.; Skinner, J.; Jabbour, E.; Cortes Sanford, J. Phase II trial of ponatinib in patients with chronic myeloid leukemia resistant to one previous tyrosine kinase inhibitor. Haematologica 2015, 100, e494. [Google Scholar] [CrossRef]
  36. Hochhaus, A.; Réa, D.; Boquimpani, C.; Minami, Y.; Cortes, J.E.; Hughes, T.P.; Apperley, J.F.; Lomaia, E.; Voloshin, S.; Turkina, A. Asciminib vs bosutinib in chronic-phase chronic myeloid leukemia previously treated with at least two tyrosine kinase inhibitors: Longer-term follow-up of ASCEMBL. Leukemia 2023, 37, 617–626. [Google Scholar] [CrossRef]
  37. Réa, D.; Mauro, M.J.; Boquimpani, C.; Minami, Y.; Lomaia, E.; Voloshin, S.; Turkina, A.; Kim, D.W.; Apperley, J.F.; Abdo, A.; et al. CML-395 Efficacy and Safety Results From ASCEMBL, a Phase III Study of Asciminib vs. Bosutinib in Patients with Chronic Myeloid Leukemia in Chronic Phase (CML-CP) After ≥2 Prior Tyrosine Kinase Inhibitors (TKIs): Week 96 Update. Clin. Lymphoma Myeloma Leuk. 2022, 22, S295–S296. [Google Scholar] [CrossRef]
  38. Daver, N.; Perl, A.E.; Maly, J.; Levis, M.; Ritchie, E.; Litzow, M.; McCloskey, J.; Smith, C.C.; Schiller, G.; Bradley, T.; et al. Venetoclax in combination with gilteritinib in patients with relapsed/refractory acute myeloid leukemia: A phase 1b study. Blood 2019, 134, 3910. [Google Scholar]
  39. Lap, C.J.; Nassereddine, S.; Liu, M.L.; Nava, V.E.; Aggarwal, A. Combined ruxolitinib and venetoclax treatment in a patient with a BCR-JAK2 rearranged myeloid neoplasm. Case Rep. Hematol. 2021, 2021, 2348977. [Google Scholar] [CrossRef]
  40. Pullarkat, V.A.; Lacayo, N.J.; Jabbour, E.; Rubnitz, J.E.; Bajel, A.; Laetsch, T.W.; Leonard, J.; Colace, S.I.; Khaw, S.L.; Fleming, S.A.; et al. Venetoclax and navitoclax in combination with chemotherapy in patients with relapsed or refractory acute lymphoblastic leukemia and lymphoblastic lymphoma. Cancer Discov. 2021, 11, 1440–1453. [Google Scholar] [CrossRef]
  41. Eghtedar, A.; Verstovsek, S.; Estrov, Z.; Burger, J.; Cortes, J.; Bivins, C.; Faderl, S.; Ferrajoli, A.; Borthakur, G.; George, S.; et al. Phase 2 study of the JAK kinase inhibitor ruxolitinib in patients with refractory leukemias, including postmyeloproliferative neoplasm acute myeloid leukemia. Blood J. Am. Soc. Hematol. 2012, 119, 4614–4618. [Google Scholar] [CrossRef]
  42. Nicolini, F.E.; Khoury, H.J.; Akard, L.; Rea, D.; Kantarjian, H.; Baccarani, M.; Leonoudakis, J.; Craig, A.; Benichou, A.C.; Cortes, J. Omacetaxine mepesuccinate for patients with accelerated phase chronic myeloid leukemia with resistance or intolerance to two or more tyrosine kinase inhibitors. Haematologica 2013, 98, e78. [Google Scholar] [CrossRef]
  43. Gandhi, V.; Plunkett, W.; Cortes, J.E. Omacetaxine: A protein translation inhibitor for treatment of chronic myelogenous leukemia. Clin. Cancer Res. 2014, 20, 1735–1740. [Google Scholar] [CrossRef]
  44. Zhao, J.; Song, Y.; Liu, D. Clinical trials of dual-target CAR T cells, donor-derived CAR T cells, and universal CAR T cells for acute lymphoid leukemia. J. Hematol. Oncol. 2019, 12, 17. [Google Scholar] [CrossRef] [PubMed]
  45. Das, D.K. Olverembatinib Demonstrates Promising Results in T315I-Mutant CML. Oncol. Times 2023, 45, 1–15. [Google Scholar]
  46. Scalzulli, E.; Carmosino, I.; Costa, A.; Bisegna, M.L.; Martelli, M.; Breccia, M. Management of Chronic Myeloid Leukemia Patients in Later Lines: The Role of Ponatinib and New Compounds. Clin. Lymphoma Myeloma Leuk. 2023, 23, 420–425. [Google Scholar] [CrossRef] [PubMed]
  47. Haddad, F.G.; Issa, G.C.; Jabbour, E.; Yilmaz, M. Ponatinib for the treatment of adult patients with resistant or intolerant chronic-phase chronic myeloid leukemia. Expert Opin. Pharmacother. 2022, 23, 751–758. [Google Scholar] [CrossRef]
  48. Cortes, J.E.; Hochhaus, A.; Takahashi, N.; Larson, R.A.; Issa, G.C.; Bombaci, F.; Ramscar, N.; Ifrah, S.; Hughes, T.P. Asciminib monotherapy for newly diagnosed chronic myeloid leukemia in chronic phase: The ASC4FIRST phase III trial. Future Oncol. 2022, 18, 4161–4170. [Google Scholar] [CrossRef]
  49. Mauro, M.; Minami, Y.; Hochhaus, A.; Lomaia, E.; Voloshin, S.; Turkina, A.; Kim, D.-W.; Apperley, J.F.; Cortes, J.; Andre, N.R.; et al. Sustained efficacy and safety with asciminib (ASC) after almost 4 years of median follow-up from ascembl, a phase 3 study of ASC Vs bosutinib (BOS) in patients (pts) with chronic myeloid leukemia in chronic phase (CML-CP) after ≥2 prior tyrosine kinase inhibitors (TKIs): An end of study treatment (EOS Tx) update, including results from switch population. Blood 2023, 142, 4536. [Google Scholar]
  50. Roberts, A.W.; Ma, S.; Kipps, T.J.; Coutre, S.E.; Davids, M.S.; Eichhorst, B.; Hallek, M.; Byrd, J.C.; Humphrey, K.; Zhou, L.; et al. Efficacy of venetoclax in relapsed chronic lymphocytic leukemia is influenced by disease and response variables. Blood J. Am. Soc. Hematol. 2019, 134, 111–122. [Google Scholar] [CrossRef]
  51. Rogers, K.A.; Huang, Y.; Ruppert, A.S.; Abruzzo, L.V.; Andersen, B.L.; Awan, F.T.; Bhat, S.A.; Dean, A.; Lucas, M.; Banks, C.; et al. Phase II study of combination obinutuzumab, ibrutinib, and venetoclax in treatment-naïve and relapsed or refractory chronic lymphocytic leukemia. J. Clin. Oncol. 2020, 38, 3626–3637. [Google Scholar] [CrossRef] [PubMed]
  52. Rambaldi, A.; Biagi, E.; Bonini, C.; Biondi, A.; Introna, M. Cell-based strategies to manage leukemia relapse: Efficacy and feasibility of immunotherapy approaches. Leukemia 2015, 29, 1–10. [Google Scholar] [CrossRef]
  53. Khair, D.O.; Bax, H.J.; Mele, S.; Crescioli, S.; Pellizzari, G.; Khiabany, A.; Nakamura, M.; Harris, R.J.; French, E.; Hoffmann, R.M.; et al. Combining immune checkpoint inhibitors: Established and emerging targets and strategies to improve outcomes in melanoma. Front. Immunol. 2019, 10, 453. [Google Scholar] [CrossRef]
  54. Petrazzuolo, A.; Maiuri, M.C.; Zitvogel, L.; Kroemer, G.; Kepp, O. Trial Watch: Combination of tyrosine kinase inhibitors (TKIs) and immunotherapy. Oncoimmunology 2022, 11, 2077898. [Google Scholar] [CrossRef] [PubMed]
  55. Odenike, O.; Onida, F.; Padron, E. Myelodysplastic syndromes and myelodysplastic/myeloproliferative neoplasms: An update on risk stratification, molecular genetics, and therapeutic approaches including allogeneic hematopoietic stem cell transplantation. Am. Soc. Clin. Oncol. Educ. Book 2015, 35, e398–e412. [Google Scholar] [CrossRef] [PubMed]
  56. Yassine, F.; Reljic, T.; Moustafa, M.A.; Iqbal, M.; Murthy, H.S.; Kumar, A.; Kharfan-Dabaja, M.A. Efficacy of allogeneic hematopoietic cell transplantation in patients with chronic phase CML resistant or intolerant to tyrosine kinase inhibitors. Hematol. Oncol. Stem Cell Ther. 2022, 15, 36–43. [Google Scholar] [CrossRef]
  57. Stelljes, M.; Middeke, J.M.; Bug, G.; Wagner-Drouet, E.M.; Müller, L.P.; Schmid, C.; Krause, S.W.; Bethge, W.; Jost, E.; Platzbecker, U.; et al. Remission induction versus immediate allogeneic haematopoietic stem cell transplantation for patients with relapsed or poor responsive acute myeloid leukaemia (ASAP): A randomised, open-label, phase 3, non-inferiority trial. Lancet Haematol. 2024, 11, e324–e335. [Google Scholar] [CrossRef]
  58. Jermakowicz, A.M.; Kurimchak, A.M.; Johnson, K.J.; Bourgain-Guglielmetti, F.; Kaeppeli, S.; Affer, M.; Pradhyumnan, H.; Suter, R.K.; Walters, W.; Cepero, M.; et al. RAPID resistance to BET inhibitors is mediated by FGFR1 in glioblastoma. Sci. Rep. 2024, 14, 9284. [Google Scholar] [CrossRef]
  59. Osman, A.E.; Deininger, M.W. Chronic Myeloid Leukemia: Modern therapies, current challenges and future directions. Blood Rev. 2021, 49, 100825. [Google Scholar] [CrossRef]
  60. Seiwerth, R.S.; Mrsić, M.; Nemet, D.; Bogdanić, V.; Mikulić, M.; Sertić, D.; Grković, L.; Cecuk, E.; Bojanić, I.; Batinić, D.; et al. Treatment of acute leukemia with allogeneic stem cell transplantation. Acta Medica Croat. Cas. Hravatske Akad. Med. Znanosti. 2009, 63, 205–208. [Google Scholar]
  61. Majhail, N.S.; Farnia, S.H.; Carpenter, P.A.; Champlin, R.E.; Crawford, S.; Marks, D.I.; Omel, J.L.; Orchard, P.J.; Palmer, J.; Saber, W.; et al. Indications for autologous and allogeneic hematopoietic cell transplantation: Guidelines from the American Society for Blood and Marrow Transplantation. Biol. Blood Marrow Transplant. 2015, 21, 1863–1869. [Google Scholar] [CrossRef] [PubMed]
  62. Maziarz, R.T.; Devine, S.; Garrison, L.P.; Agodoa, I.; Badaracco, J.; Gitlin, M.; Perales, M.A. Estimating the lifetime medical cost burden of an allogeneic hematopoietic cell transplantation patient. Transplant. Cell. Ther. 2023, 29, 637-e1. [Google Scholar] [CrossRef] [PubMed]
  63. Pidala, J.; Anasetti, C.; Jim, H. Quality of life after allogeneic hematopoietic cell transplantation. Blood J. Am. Soc. Hematol. 2009, 114, 7–19. [Google Scholar] [CrossRef]
  64. Sun, J.; Hu, R.; Han, M.; Tan, Y.; Xie, M.; Gao, S.; Hu, J.F. Mechanisms underlying therapeutic resistance of tyrosine kinase inhibitors in chronic myeloid leukemia. Int. J. Biol. Sci. 2024, 20, 175. [Google Scholar] [CrossRef]
  65. Javidi-Sharifi, N.; Hobbs, G. Future directions in chronic phase CML treatment. Curr. Hematol. Malig. Rep. 2021, 16, 1–9. [Google Scholar] [CrossRef]
  66. Jabbour, E.; Cortes, J.; Kantarjian, H. Long-term outcomes in the second-line treatment of chronic myeloid leukemia: A review of tyrosine kinase inhibitors. Cancer 2011, 117, 897–906. [Google Scholar] [CrossRef]
  67. Flis, S.; Chojnacki, T. Chronic myelogenous leukemia, a still unsolved problem: Pitfalls and new therapeutic possibilities. Drug Des. Dev. Ther. 2019, 13, 825–843. [Google Scholar] [CrossRef] [PubMed]
  68. Silbermann, M.; Pitsillides, B.; Al-Alfi, N.; Omran, S.; Al-Jabri, K.; Elshamy, K.; Ghrayeb, I.; Livneh, J.; Daher, M.; Charalambous, H.; et al. Multidisciplinary care team for cancer patients and its implementation in several Middle Eastern countries. Ann. Oncol. 2013, 24, vii41–vii47. [Google Scholar] [CrossRef]
  69. Trivedi, D.; Landsman-Blumberg, P.; Darkow, T.; Smith, D.; McMorrow, D.; Mullins, C.D. Adherence and persistence among chronic myeloid leukemia patients during second-line tyrosine kinase inhibitor treatment. J. Manag. Care Pharm. 2014, 20, 1006–1015. [Google Scholar] [CrossRef]
  70. Lustberg, M.B.; Kuderer, N.M.; Desai, A.; Bergerot, C.; Lyman, G.H. Mitigating long-term and delayed adverse events associated with cancer treatment: Implications for survivorship. Nat. Rev. Clin. Oncol. 2023, 20, 527–542. [Google Scholar] [CrossRef]
  71. Fava, C.; Kantarjian, H.; Cortes, J. Molecular resistance: An early indicator for treatment change? Clin. Lymphoma Myeloma Leukemia. 2012, 12, 79–87. [Google Scholar] [CrossRef]
  72. Atallah, E.; Schiffer, C.A.; Radich, J.P.; Weinfurt, K.P.; Zhang, M.J.; Pinilla-Ibarz, J.; Kota, V.; Larson, R.A.; Moore, J.O.; Mauro, M.J.; et al. Assessment of outcomes after stopping tyrosine kinase inhibitors among patients with chronic myeloid leukemia: A nonrandomized clinical trial. JAMA Oncol. 2021, 7, 42–50. [Google Scholar] [CrossRef]
  73. Gustafson, D.; Fish, J.E.; Lipton, J.H.; Aghel, N. Mechanisms of cardiovascular toxicity of BCR-ABL1 tyrosine kinase inhibitors in chronic myelogenous leukemia. Curr. Hematol. Malig. Rep. 2020, 15, 20–30. [Google Scholar] [CrossRef] [PubMed]
  74. Karakulak, U.N.; Aladag, E.; Hekimsoy, V.; Sahiner, M.L.; Kaya, E.B.; Ozer, N.; Aksu, S.; Demiroglu, H.; Goker, H.; Buyukasik, Y.; et al. Four-dimensional echocardiographic evaluation of left ventricular systolic functions in patients with chronic myeloid leukaemia receiving tyrosine kinase inhibitors. Cardiovasc. Toxicol. 2021, 21, 216–223. [Google Scholar] [CrossRef] [PubMed]
  75. Rodia, R.; Pani, F.; Caocci, G.; La Nasa, G.; Simula, M.P.; Mulas, O.; Velluzzi, F.; Loviselli, A.; Mariotti, S.; Boi, F. Thyroid autoimmunity and hypothyroidism are associated with deep molecular response in patients with chronic myeloid leukemia on tyrosine kinase inhibitors. J. Endocrinol. Investig. 2022, 45, 291–300. [Google Scholar] [CrossRef]
  76. Kim, T.D.; Schwarz, M.; Nogai, H.; Grille, P.; Westermann, J.; Plöckinger, U.; Braun, D.; Schweizer, U.; Arnold, R.; Dörken, B.; et al. Thyroid dysfunction caused by second-generation tyrosine kinase inhibitors in Philadelphia chromosome-positive chronic myeloid leukemia. Thyroid 2010, 20, 1209–1214. [Google Scholar] [CrossRef] [PubMed]
  77. Roshanaei, M.; Khan, M.R.; Sylvester, N.N. Enhancing Cybersecurity through AI and ML: Strategies, Challenges, and Future Directions. J. Inf. Secur. 2024, 15, 320–339. [Google Scholar] [CrossRef]
  78. Alsadie, D. A Comprehensive Review of AI Techniques for Resource Management in Fog Computing: Trends, Challenges and Future Directions. IEEE Access 2024, 12, 118007–118059. [Google Scholar] [CrossRef]
  79. Mojtahedi, H.; Yazdanpanah, N.; Rezaei, N. Chronic myeloid leukemia stem cells: Targeting therapeutic implications. Stem Cell Res. Ther. 2021, 12, 603. [Google Scholar] [CrossRef]
  80. Malik, V.; Mittal, R.; Rana, A. BiCNN-CML: Hybrid Deep Learning Approach for Chronic Myeloid Leukemia. In Proceedings of the 2022 5th International Conference on Contemporary Computing and Informatics (IC3I), Uttar Pradesh, India, 14 December 2022; IEEE: Piscataway, NJ, USA; pp. 1771–1777. [Google Scholar]
  81. Bernardi, S.; Vallati, M.; Gatta, R. Artificial Intelligence-Based Management of Adult Chronic Myeloid Leukemia: Where Are We and Where Are We Going? Cancers 2024, 16, 848. [Google Scholar] [CrossRef]
  82. Ghane, N.; Vard, A.; Talebi, A.; Nematollahy, P. Classification of effective cells in diagnosis of chronic myeloid leukemia (CML) using semi-automatic image processing of microscopic images. J. Isfahan Med. School. 2016, 34, 1304–1310. [Google Scholar]
  83. Ko, B.S.; Wang, Y.F.; Li, J.L.; Li, C.C.; Weng, P.F.; Hsu, S.C.; Hou, H.A.; Huang, H.H.; Yao, M.; Lin, C.T.; et al. Clinically validated machine learning algorithm for detecting residual diseases with multicolor flow cytometry analysis in acute myeloid leukemia and myelodysplastic syndrome. EBioMedicine 2018, 37, 91–100. [Google Scholar] [CrossRef] [PubMed]
  84. Efthimiou, O.; Hoogland, J.; Debray, T.P.; Seo, M.; Furukawa, T.A.; Egger, M.; White, I.R. Measuring the performance of prediction models to personalize treatment choice. Stat. Med. 2023, 42, 1188–1206. [Google Scholar] [CrossRef]
  85. Berchialla, P.; Lanera, C.; Sciannameo, V.; Gregori, D.; Baldi, I. Prediction of treatment outcome in clinical trials under a personalized medicine perspective. Sci. Rep. 2022, 12, 4115. [Google Scholar] [CrossRef]
  86. Agarwal, S. Machine Learning Based Personalized Treatment Plans for Chronic Conditions. In Proceedings of the 2024 2nd International Conference on Intelligent Data Communication Technologies and Internet of Things (IDCIoT), Bengaluru, India, 4 January 2024; IEEE: Piscataway, NJ, USA; pp. 1127–1132. [Google Scholar]
  87. Patel, P.M.; Green, M.; Tram, J.; Wang, E.; Murphy, M.Z.; Abd-Elsayed, A.; Chakravarthy, K. Beyond the Pain Management Clinic: The Role of AI-Integrated Remote Patient Monitoring in Chronic Disease Management—A Narrative Review. J. Pain Res. 2024, 4223–4237. [Google Scholar] [CrossRef] [PubMed]
  88. Kanakaprabha, S.; Kumar, G.G.; Reddy, B.P.; Raju, Y.R.; Rai, P.C. Wearable Devices and Health Monitoring: Big Data and AI for Remote Patient Care. Intell. Data Anal. Bioinform. Biomed. Syst. 2024, 291–311. [Google Scholar] [CrossRef]
  89. More, D.; Khan, N.; Tekade, R.K.; Sengupta, P. An update on current trend in sample preparation automation in bioanalysis: Strategies, challenges and future direction. Crit. Rev. Anal. Chem. 2024, 1–25. [Google Scholar] [CrossRef]
  90. Medina, D.A.; Maciel, E.V.; Lanças, F.M. Modern automated sample preparation for the determination of organic compounds: A review on robotic and on-flow systems. TrAC Trends Anal. Chem. 2023, 166, 117171. [Google Scholar] [CrossRef]
  91. Sandu, M.O.; Gruescu, C.M.; Lovasz, E.C.; Ciupe, V. Synthesis of an Automation System for the PCR (Polymerase Chain Reaction) Samples Preparation Process. In Proceedings of the IFToMM International Symposium on Science of Mechanisms and Machines (SYROM), Iasi, Romania, 17 November 2022; Springer International Publishing: Cham, Switzerland, 2022; pp. 389–396. [Google Scholar]
  92. Hutapea, S.A.; Tumilaar, K.Y.; Nugroho, A.; Maulana, F.I. MycoAR: Augmented Reality Mobile Application for Mycology Education. In Proceedings of the 2024 International Conference on Information Management and Technology (ICIMTech), Bali, Indonesia, 28 August 2024; IEEE: Piscataway, NJ, USA; pp. 783–788. [Google Scholar]
  93. Syamsuar, D. The Implementation of Artificial Intelligence for Online Review: A Systematic Literature Review. In Proceedings of the 2024 International Conference on Information Management and Technology (ICIMTech), Bali, Indonesia, 28 August 2024; IEEE: Piscataway, NJ, USA; pp. 588–593. [Google Scholar]
  94. Ryan, G.; Murphy, J.; Higgins, M.; McAuliffe, F.; Mangina, E. Work-in-Progress—Development of a Virtual Reality Learning Environment: VR Baby. In Proceedings of the 2020 6th International Conference of the Immersive Learning Research Network (iLRN), San Luis Obispo, CA, USA, 21 January 2020; IEEE: Piscataway, NJ, USA; pp. 312–315. [Google Scholar]
  95. Goddard, T.D.; Brilliant, A.A.; Skillman, T.L.; Vergenz, S.; Tyrwhitt-Drake, J.; Meng, E.C.; Ferrin, T.E. Molecular visualization on the holodeck. J. Mol. Biology. 2018, 430, 3982–3996. [Google Scholar] [CrossRef]
Figure 1. Schematic representation of the mechanism of action of tyrosine kinase inhibitors (TKIs). MAPK: mitogen-activated protein kinases; JAK/STAT: Janus kinases/signal transducer and activation of transcription proteins; PI3K/AKT: phosphoinositide-3-kinase/protein kinase B.
Figure 1. Schematic representation of the mechanism of action of tyrosine kinase inhibitors (TKIs). MAPK: mitogen-activated protein kinases; JAK/STAT: Janus kinases/signal transducer and activation of transcription proteins; PI3K/AKT: phosphoinositide-3-kinase/protein kinase B.
Hemato 06 00006 g001
Figure 2. Illustrates the binding mechanisms of various TKIs used in CML treatment. Most approved TKIs, including imatinib, dasatinib, nilotinib, bosutinib, and ponatinib, target the ATP-binding site of the BCR-ABL kinase, interfering with its function. Asciminib, in contrast, uniquely binds to the myristoyl pocket of BCR-ABL, offering a novel inhibitory approach. Also highlighted are emerging third- and fourth-generation TKIs, such as olverembatinib (HQP1351), vodobatinib (K0706), and PF-114, which are under investigation for enhanced efficacy and resistance management. It also displays Omacetaxine, an approved non-TKI therapy for CML, which works by blocking protein synthesis, providing an alternative mechanism of action for cases resistant to conventional TKIs.
Figure 2. Illustrates the binding mechanisms of various TKIs used in CML treatment. Most approved TKIs, including imatinib, dasatinib, nilotinib, bosutinib, and ponatinib, target the ATP-binding site of the BCR-ABL kinase, interfering with its function. Asciminib, in contrast, uniquely binds to the myristoyl pocket of BCR-ABL, offering a novel inhibitory approach. Also highlighted are emerging third- and fourth-generation TKIs, such as olverembatinib (HQP1351), vodobatinib (K0706), and PF-114, which are under investigation for enhanced efficacy and resistance management. It also displays Omacetaxine, an approved non-TKI therapy for CML, which works by blocking protein synthesis, providing an alternative mechanism of action for cases resistant to conventional TKIs.
Hemato 06 00006 g002
Figure 3. This figure illustrates the multifaceted factors impacting treatment choices for patients with resistant chronic myeloid leukemia.
Figure 3. This figure illustrates the multifaceted factors impacting treatment choices for patients with resistant chronic myeloid leukemia.
Hemato 06 00006 g003
Table 1. Overview of emerging therapies for resistant chronic myeloid leukemia (CML).
Table 1. Overview of emerging therapies for resistant chronic myeloid leukemia (CML).
Therapy/StrategyDescription and MechanismClinical Trial Phase/FindingsReferences
Ponatinib and
Olverembatinib
(HQP1351)
TKI targets BCR-ABL mutations, including T315I. Known for broad-spectrum efficacy.Phase III trials showed efficacy in T315I-positive patients but with significant vascular risks. Olverembatinib
is a new third-generation TKI, and the drug is approved in China for the treatment of TKI-resistant CML.
[20,21]
AsciminibFirst-in-class STAMP inhibitor targeting the myristoyl pocket of ABL1.Phase III results demonstrate a superior safety profile and efficacy compared to older TKIs.[22]
Combination: TKIs + VenetoclaxCombines BCR-ABL inhibition with apoptosis induction via BCL-2 inhibition.Early clinical trials indicate potent efficacy in reducing residual disease.[23,24]
Combination: TKIs + mTOR InhibitorsAims to inhibit the mTOR pathway alongside BCR-ABL for a synergistic effect.Phase II studies show promise in overcoming resistance, particularly in refractory patients.[25,26]
CAR-T Cell TherapyUses genetically modified T-cells to target and kill CML cells.Phase I/II trials exploring efficacy; some challenges with toxicity observed.[27,28,29]
Allogeneic HSCTCurative approach involving stem cell transplantation from a donor.Remains a standard for patients with advanced or TKI-resistant CML, with evolving protocols to reduce GVHD.[30,31,32]
BET InhibitorsTargets bromodomain and extra-terminal motif (BET) proteins to disrupt CML cell growth.Preclinical and early clinical data suggest potential in combination with TKIs to overcome resistance.[33,34]
These emerging therapies reflect the advancements in understanding the complex nature of CML resistance and illustrate the ongoing efforts to enhance treatment outcomes through innovative approaches.
Table 2. Overview of key clinical trials and real-world evidence on emerging therapies for resistant CML.
Table 2. Overview of key clinical trials and real-world evidence on emerging therapies for resistant CML.
Therapy/Trial NameStudy PhaseKey FindingsLimitations/GapsReal-World Data/Registry InsightsReferences
Ponatinib (OPTIC Trial)Phase II/IIIDemonstrated robust efficacy in T315I mutation carriers; dose adjustment is critical to balance efficacy and cardiovascular risks.Cardiovascular adverse effects remain a concern; limited data on long-term survival beyond 5 years.Registry data show improved molecular response with early intervention; discontinuations due to toxicity were reported in ~30% of cases.[35,36]
Asciminib (ASCEMBL Trial)Phase IIISuperior to bosutinib with better tolerability; achieved higher major molecular response (MMR) rates at 24 weeks.Limited data on use in the blast phase; long-term safety is still under investigation.Real-world outcomes demonstrate sustained response in patients with T315I mutation; lower discontinuation rates compared to ponatinib.[3,22,37,38]
TKI + Venetoclax CombinationPhase II (Ongoing)Early-phase trials indicate a synergistic effect in reducing minimal residual disease.Limited data on safety profile in larger populations; optimal dosing strategies are yet to be established.Case reports highlight partial response in patients with molecular relapse.[39,40,41]
JAK Inhibitor + TKI (Ruxolitinib)Phase II (Ongoing)Promising molecular response in TKI-refractory cases by blocking JAK-STAT pathways.No phase III data available; safety concerns with dual inhibition.Registry data suggest high variability in response rates; adherence challenges reported.[41,42]
Omacetaxine (Protien synthesis inhibitor)Phase II/III (Ongoing)Phase II: Omacetaxine was effective in treating CML patients resistant or intolerant to two or more TKIs, especially in those with the T315I mutation.
Phase III: Sustained use of Omacetaxine resulted in ongoing responses in patients with minimal residual disease, establishing its utility in salvage therapy.
Ongoing Research: Studies are exploring the use of Omacetaxine in combination with newer agents like ponatinib to improve outcomes and overcome resistance.
Limited patient population and short follow-up period restrict broader conclusions. Potential side effects include myelosuppression and injection-site reactions.
Lack of long-term safety data. The administration route (subcutaneous injection) may impact patient compliance.
Early results are promising but incomplete. Need for extensive data to validate findings.
Registry data indicate a modest uptake of Omacetaxine, mainly in heavily pre-treated populations or those with specific mutations like T315I.
Reports from treatment registries suggest variable response rates, with some patients achieving significant molecular responses.
Emerging clinical practice is increasingly incorporating Omacetaxine in combination regimens, especially in refractory cases.
[43,44]
CAR-T Cell TherapyPhase I/II (Ongoing)Effective in eliminating leukemic stem cells; potential for durable remission.Toxicity and manufacturing scalability remain major hurdles.Limited case reports show positive response; early termination in some cases due to immune-related adverse events.[27,45]
There are a range of innovative treatments from next-generation tyrosine kinase inhibitors (TKIs) to cutting-edge cellular therapies, highlighting their therapeutic potential, key findings, and the practical challenges they face in clinical settings (Figure 2). This synthesis not only underscores the critical role of ongoing research in overcoming resistance but also provides insights into the real-world application of these therapies, helping to bridge the gap between clinical trial efficacy and everyday clinical practice.
Table 3. Comparative analysis of emerging therapies for resistant chronic myeloid leukemia.
Table 3. Comparative analysis of emerging therapies for resistant chronic myeloid leukemia.
Therapy/StrategyEfficacySafetyCostQuality of Life ImpactReferences
Ponatinib and OlverembatinibHigh efficacy with the T315I mutation; Phase III success for ponatinibSignificant vascular risks; dose-related toxicity for ponatinibHigh; specific data for olverembatinib pendingCardiovascular side effects may significantly impact[46,47,48]
AsciminibSuperior efficacy compared to older TKIs in Phase IIIBetter safety profile than other TKIsLikely highPotentially better due to fewer side effects[22,49,50]
TKIs + VenetoclaxPotent efficacy in reducing residual disease in early trialsIncreased risk of infections and immunosuppressionIncreased due to combination therapyDependent on disease control vs. increased toxicity[51,52]
TKIs + mTOR InhibitorsPromising in overcoming resistance, especially in refractory patientsPotential added toxicities involving mTOR pathway inhibitionIncreased due to combination therapySimilar to TKIs + Venetoclax
CAR-T Cell TherapyEffective in eliminating leukemic stem cells; potential for durable remissionHigh toxicity; significant immune-related adverse eventsVery highSevere side effects may negatively impact despite the potential for remission[45,53]
Immune Checkpoint
Inhibitors
Early trials suggest potential benefits in combination with TKIsConcerns about immune-related toxicityHighDependent on effective management of immune-related side effects[54,55,56,57,58,59]
Allogeneic HSCTAllogeneic HSCT is highly effective in achieving disease-free survival (DFS) and overall survival (OS) in patients with acute leukemia and other hematologic malignancies.
The efficacy is often measured by the rates of DFS and OS, with studies showing significant long-term survival benefits
The major safety concern with allogeneic HSCT is graft-versus-host disease (GVHD), which can be acute or chronic and significantly impacts patient outcomes.
Acute GVHD (aGVHD) and chronic GVHD (cGVHD) are associated with increased morbidity and mortality, and managing these complications is crucial for improving transplant outcomes
The lifetime cost of allogeneic HSCT is substantial, often exceeding USD 1,000,000 per patient.
The majority of these costs are attributed to the treatment of chronic GVHD and the initial transplant procedure
Quality of life (QOL) post-transplant is a significant concern, with many patients experiencing moderate impairments that can persist for years.
While some patients report a return to pre-transplant QOL levels within the first year, others face long-term challenges, including chronic health issues and psychological impacts
Behavioral and rehabilitative interventions are being explored to improve QOL outcomes for long-term survivors
[60,61,62]
BET InhibitorsEarly data suggest potential efficacy in overcoming TKI resistanceSafety profile still under investigationExpected to be highImpact on quality of life uncertain until further data are available[63]
Table 4. Challenges and future directions for resistant CML therapies.
Table 4. Challenges and future directions for resistant CML therapies.
Key ChallengeDetailsReferences
Overcoming the Heterogeneity in Resistance Mechanisms- Personalized medicine: Tailoring treatment based on molecular profiling to optimize patient outcomes.
- Patient stratification strategies: Identifying subgroups to match with appropriate therapies and improve efficacy.
[64,65]
Long-Term Toxicities and Side Effects of New Therapies- Cardiovascular risks: Ponatinib linked with vascular events; dose management essential.
- Immunosuppression: Risks with dual therapies or CAR-T approaches.
- Secondary malignancies: Potential long-term effects of TKIs.
[66,67]
Economic and Accessibility Issues- Cost-effectiveness: The high cost of novel agents like ponatinib and asciminib limits use.
- Access in resource-limited settings: Limited availability and high prices restrict treatment options.
[68]
Future Research Avenues- Head-to-head trials: Comparisons between new therapies and standard TKIs to identify the most effective treatments.
- Development of biomarkers: New biomarkers to predict therapy response and tailor treatments.
[69,70]
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Rangraze, I.; El-Tanani, M.; Wali, A.F.; Rizzo, M. Beyond TKIs: Advancing Therapeutic Frontiers with Immunotherapy, Targeted Agents, and Combination Strategies in Resistant Chronic Myeloid Leukemia. Hemato 2025, 6, 6. https://doi.org/10.3390/hemato6010006

AMA Style

Rangraze I, El-Tanani M, Wali AF, Rizzo M. Beyond TKIs: Advancing Therapeutic Frontiers with Immunotherapy, Targeted Agents, and Combination Strategies in Resistant Chronic Myeloid Leukemia. Hemato. 2025; 6(1):6. https://doi.org/10.3390/hemato6010006

Chicago/Turabian Style

Rangraze, Imran, Mohamed El-Tanani, Adil Farooq Wali, and Manfredi Rizzo. 2025. "Beyond TKIs: Advancing Therapeutic Frontiers with Immunotherapy, Targeted Agents, and Combination Strategies in Resistant Chronic Myeloid Leukemia" Hemato 6, no. 1: 6. https://doi.org/10.3390/hemato6010006

APA Style

Rangraze, I., El-Tanani, M., Wali, A. F., & Rizzo, M. (2025). Beyond TKIs: Advancing Therapeutic Frontiers with Immunotherapy, Targeted Agents, and Combination Strategies in Resistant Chronic Myeloid Leukemia. Hemato, 6(1), 6. https://doi.org/10.3390/hemato6010006

Article Metrics

Back to TopTop