Evaluation of cytogenetic and molecular markers with MTX-mediated toxicity in pediatric acute lymphoblastic leukemia patients

Association of SLC19A1 Gene Polymorphisms and Its Regulatory miRNAs with Methotrexate Toxicity in Children with Acute Lymphoblastic Leukemia

Methotrexate (MTX) is an anti-folate chemotherapeutic agent that is considered to be a gold standard in Acute Lymphoblastic Leukemia (ALL) therapy. Nevertheless, toxicities induced mainly due to high doses of MTX are still a challenge for clinical practice. MTX pharmacogenetics implicate various genes as predictors of MTX toxicity, especially those that participate in MTX intake like solute carrier family 19 member 1 (SLC19A1). The aim of the present study was to evaluate the association between SLC19A1 polymorphisms and its regulatory miRNAs with MTX toxicity in children with ALL. A total of 86 children with ALL were included in this study and were all genotyped for rs2838958, rs1051266 and rs1131596 SLC19A1 polymorphisms as well as the rs56292801 polymorphism of miR-5189. Patients were followed up (48, 72 and 96 h) after treatment with MTX in order to evaluate the presence of MTX-associated adverse events. Our results indicate that there is a statistically significant correlation between the rs1131596 SLC19A1 polymorphism and the development of MTX-induced hepatotoxicity (p = 0.03), but there is no significant association between any of the studied polymorphisms and mucositis or other side effects, such as nausea, emesis, diarrhea, neutropenia, skin rash and infections. In addition, when genotype TT of rs1131596 and genotype AA of rs56292801 are both present in a patient then there is a higher risk of developing severe hepatotoxicity (p = 0.0104).

Machine learning in paediatric haematological malignancies: a systematic review of prognosis, toxicity and treatment response models

BACKGROUND

Machine Learning (ML) has demonstrated potential in enhancing care in adult oncology. However, its application in paediatric haematological malignancies is still emerging, necessitating a comprehensive review of its capabilities and limitations in this area.

METHODS

A literature search was conducted through Ovid. Studies included focused on ML models in paediatric patients with haematological malignancies. Studies were categorised into thematic groups for analysis.

RESULTS

Twenty studies, primarily on leukaemia, were included in this review. Studies were organised into thematic categories such as prognoses, treatment responses and toxicity predictions. Prognostic studies showed AUC scores between 0.685 and 0.929, indicating moderate-high predictive accuracy. Treatment response studies demonstrated AUC scores between 0.840 and 0.875, reflecting moderate accuracy. Toxicity prediction studies reported high accuracy with AUC scores from 0.870 to 0.927. Only five studies (25%) performed external validation. Significant heterogeneity was noted in ML tasks, reporting formats, and effect measures across studies, highlighting a lack of standardised reporting and challenges in data comparability.

CONCLUSION

The clinical applicability of these ML models remains limited by the lack of external validation and methodological heterogeneity. Addressing these challenges through standardised reporting and rigorous external validation is needed to translate ML from a promising research tool into a reliable clinical practice component.

IMPACT

Key message: Machine Learning (ML) significantly enhances predictive models in paediatric haematological cancers, offering new avenues for personalised treatment strategies. Future research should focus on developing ML models that can integrate with real-time clinical workflows. Addition to literature: Provides a comprehensive overview of current ML applications and trends. It identifies limitations to its applicability, including the limited diversity in datasets, which may affect the generalisability of ML models across different populations.

IMPACT

Encourages standardisation and external validation in ML studies, aiming to improve patient outcomes through precision medicine in paediatric haematological oncology.

GENETIC PREDICTORS OF TOXIC EFFECTS OF METHOTREXATE IN CANCER PATIENTS

Today, methotrexate (MTX) is used in combination with other medicines to treat a wide range of malignancies. Despite its proven high efficacy, MTX often causes serious side effects, which may result in the need to reduce the dose of MTX or discontinue the drug altogether. This, in turn, can provoke the development of MTX resistance and cancer progression. Predicting the risk of MTX-induced toxicity is currently difficult due to the variability of pharmacokinetics and pharmacodynamics in different patients, so the scientific literature is intensively searching for potential biomarkers. Based on the data available in the current literature, we analyzed the relationship between variants in the genes encoding the key components of MTX intracellular metabolism and the MTX-induced side effects and drug response. According to the results of our work, the most studied variants are those of the SLC19A1 gene, which encodes the reduced folate carrier protein 1, and the MTHFR gene, which encodes the enzyme methylenetetrahydrofolate reductase. Studies of the effect of methylation of the promoter regions of genes on the therapeutic effect of MTX are also very promising. In conclusion, the study of molecular genetic markers of MTX toxicity is extremely relevant and necessary because it can help to avoid the effect of multidrug resistance and improve the quality of life and survival of patients.

Effects of gene polymorphisms on delayed MTX clearance, toxicity, and metabolomic changes after HD-MTX treatment in children with acute lymphoblastic leukemia

This study aims to assess the role of methotrexate-related gene polymorphisms in children with acute lymphoblastic leukemia (ALL) during high-dose methotrexate (HD-MTX) therapy and to explore their effects on serum metabolites before and after HD-MTX treatment. The MTHFR 677C>T, MTHFR 1298A>C, ABCB1 3435C>T, and GSTP1 313A>G genotypes of 189 children with ALL who received chemotherapy with the CCCG-ALL-2020 regimen from January 2020 to April 2023 were analyzed, and toxic effects were reported according to the Common Terminology Criteria for Adverse Events (CTCAE, version 5.0). Fasting peripheral blood serum samples were collected from 27 children before and after HD-MTX treatment, and plasma metabolites were analyzed by liquid chromatography-tandem mass spectrometry (LC-MS). The results of univariate and multivariate analyses showed that MTHFR 677C>T and ABCB1 3435 C>T gene polymorphisms were associated with the delayed MTX clearance (P < 0.05) and lower platelet count after treatment in children with MTHFR 677 mutation compared with wild-type ones (P < 0.05), and pure mutations in ABCB1 3435 were associated with higher serum creatinine levels (P < 0.05). No significant association was identified between MTHFR 677C>T, MTHFR 1298A>C, ABCB1 3435 C>T, and GSTP1 313A>G genes and hepatotoxicity or nephrotoxicity (P > 0.05). However, the serum metabolomic analysis indicated that the presence of the MTHFR 677C > T gene polymorphism could potentially contribute to delayed MTX clearance by influencing L-phenylalanine metabolism, leading to the occurrence of related toxic side effects.

CONCLUSION

MTHFR 677C>T and ABCB1 3435 C>T predicted the risk of delayed MTX clearance during HD-MTX treatment in children with ALL. Serum L-phenylalanine levels were significantly elevated after HD-MTX treatment in children with the MTHFR 677C>T mutation gene.

TRIAL REGISTRATION

This study was registered at the Chinese Clinical Trial Registry (registration number: ChiCTR2000035264; registration: 2020/08/05; https://www.chictr.org.cn/ ).

WHAT IS KNOWN

• MTX-related genes play an important role in MTX pharmacokinetics and toxicity, but results from different studies are inconsistent and the mechanisms involved are not clear.

WHAT IS NEW

• Characteristics, prognosis, polymorphisms of MTX-related genes, and metabolite changes were comprehensively evaluated in children treated with HD-MTX chemotherapy. • Analysis revealed that both heterozygous and pure mutations in MTHFR 677C>T resulted in a significantly increased risk of delayed MTX clearance, and that L-phenylalanine has the potential to serve as a predictive marker for the metabolic effects of the MTHFR 677C>T polymorphism.

Comprehensive scientometrics and visualization study profiles lymphoma metabolism and identifies its significant research signatures

Background

There is a wealth of poorly utilized unstructured data on lymphoma metabolism, and scientometrics and visualization study could serve as a robust tool to address this issue. Hence, it was implemented.

Methods

After strict quality control, numerous data regarding the lymphoma metabolism were mined, quantified, cleaned, fused, and visualized from documents (n = 2925) limited from 2013 to 2022 using R packages, VOSviewer, and GraphPad Prism.

Results

The linear fitting analysis generated functions predicting the annual publication number (y = 31.685x - 63628, R² = 0.93614, Prediction in 2027: 598) and citation number (y = 1363.7x - 2746019, R² = 0.94956, Prediction in 2027: 18201). In the last decade, the most academically performing author, journal, country, and affiliation were Meignan Michel (n = 35), European Journal of Nuclear Medicine and Molecular Imaging (n = 1653), USA (n = 3114), and University of Pennsylvania (n = 86), respectively. The hierarchical clustering based on unsupervised learning further divided research signatures into five clusters, including the basic study cluster (Cluster 1, Total Link Strength [TLS] = 1670, Total Occurrence [TO] = 832) and clinical study cluster (Cluster 3, TLS = 3496, TO = 1328). The timeline distribution indicated that radiomics and artificial intelligence (Cluster 4, Average Publication Year = 2019.39 ± 0.21) is a relatively new research cluster, and more endeavors deserve. Research signature burst and linear regression analysis further confirmed the findings above and revealed additional important results, such as tumor microenvironment (a = 0.6848, R² = 0.5194, p = 0.019) and immunotherapy (a = 1.036, R² = 0.6687, p = 0.004). More interestingly, by performing a "Walktrap" algorithm, the community map indicated that the "apoptosis, metabolism, chemotherapy" (Centrality = 12, Density = 6), "lymphoma, pet/ct, prognosis" (Centrality = 11, Density = 1), and "genotoxicity, mutagenicity" (Centrality = 9, Density = 4) are crucial but still under-explored, illustrating the potentiality of these research signatures in the field of the lymphoma metabolism.

Conclusion

This study comprehensively mines valuable information and offers significant predictions about lymphoma metabolism for its clinical and experimental practice.

Effects of genetic polymorphisms on methotrexate levels and toxicity in Chinese patients with acute lymphoblastic leukemia

Methotrexate (MTX) has an antitumor effect when used for the treatment of acute lymphoblastic leukemia (ALL). This study aims at evaluating the associations between 14 polymorphisms of six genes involved in MTX metabolism with serum MTX concentration and toxicity accompanying high-dose MTX. Polymorphisms in 183 Chinese patients with ALL were analyzed using TaqMan single nucleotide polymorphism genotyping assay. The serum MTX concentration was determined using homogeneous enzyme immunoassay. MTX-related toxicities were also evaluated. Renal toxicity was significantly associated with higher serum MTX concentrations at 24, 48, and 72 hours, and MTX elimination delay (P = 0.001, P < 0.001, P < 0.001, and P < 0.001, respectively), whereas SLCO1B1 rs4149056 was associated with serum MTX concentrations at 48 and 72 hours, and MTX elimination delay in candidate polymorphisms (P = 0.014, P = 0.019, and P = 0.007, respectively). SLC19A1 rs2838958 and rs3788200 were associated with serum MTX concentrations at 24 hours (P = 0.016, P = 0.043, respectively). MTRR rs1801394 was associated with serum MTX concentrations at 72 hours (P = 0.045). Neutropenia was related to SLC19A1 rs4149056 (odds ratio [OR]: 3.172, 95% confidence interval [CI]: 1.310-7.681, P = 0.011). Hepatotoxicity was associated with ABCC2 rs2273697 (OR: 3.494, 95% CI: 1.236-9.873, P = 0.018) and MTRR rs1801394 (OR: 0.231, 95% CI: 0.084-0.632, P = 0.004). Polymorphisms of SLCO1B1, SLC19A1, ABCC2, and MTRR genes help predict higher risk of increased MTX levels or MTX-related toxicities in adult ALL patients.

Neurotoxicity Associated with Treatment of Acute Lymphoblastic Leukemia Chemotherapy and Immunotherapy

Immunotherapy is a milestone in the treatment of poor-prognosis pediatric acute lymphoblastic leukemia (ALL) and is expected to improve treatment outcomes and reduce doses of conventional chemotherapy without compromising the effectiveness of the therapy. However, both chemotherapy and immunotherapy cause side effects, including neurological ones. Acute neurological complications occur in 3.6–11% of children treated for ALL. The most neurotoxical chemotherapeutics are L-asparaginase (L-ASP), methotrexate (MTX), vincristine (VCR), and nelarabine (Ara-G). Neurotoxicity associated with methotrexate (MTX-NT) occurs in 3–7% of children treated for ALL and is characterized by seizures, stroke-like symptoms, speech disturbances, and encephalopathy. Recent studies indicate that specific polymorphisms in genes related to neurogenesis may have a predisposition to MTX toxicity. One of the most common complications associated with CAR T-cell therapy is immune effector cell-associated neurotoxicity syndrome (ICANS). Mechanisms of neurotoxicity in CAR T-cell therapy are still unknown and may be due to disruption of the blood–brain barrier and the effects of elevated cytokine levels on the central nervous system (CNS). In this review, we present an analysis of the current knowledge on the mechanisms of neurotoxicity of standard chemotherapy and the targeted therapy in children with ALL.