Analysis of Drug Metabolizing Gene Panel in Osteosarcoma Patients Identifies Association Between Variants in SULT1E1, CYP2B6 and CYP4F8 and Methotrexate Levels and Toxicities

Advances in drug resistance of osteosarcoma caused by pregnane X receptor

Osteosarcoma (OS) is a prevalent malignancy among adolescents, commonly manifesting during childhood and adolescence. It exhibits a high degree of malignancy, propensity for metastasis, rapid progression, and poses challenges in clinical management. Chemotherapy represents an efficacious therapeutic modality for OS treatment. However, chemotherapy resistance of OS is a major problem in clinical treatment. In order to treat OS effectively, it is particularly important to explore the mechanism of chemotherapy resistance in OS.The Pregnane X receptor (PXR) is a nuclear receptor primarily involved in the metabolism, transport, and elimination of xenobiotics, including chemotherapeutic agents. PXR involves three stages of drug metabolism: stage I: drug metabolism enzymes; stage II: drug binding enzyme; stage III: drug transporter.PXR has been confirmed to be involved in the process of chemotherapy resistance in malignant tumors. The expression of PXR is increased in OS, which may be related to drug resistance of OS. Therefore, wereviewed in detail the role of PXR in chemotherapy drug resistance in OS.

Genetic polymorphisms in CYP2B6 may be associated with lung cancer risk in the Chinese Han population

BACKGROUND

Our study aimed to elucidate the association between single nucleotide polymorphisms (SNPs) in CYP2B6 gene and susceptibility to lung cancer (LC).

METHODS

Five SNPs in CYP2B6 were genotyped in Chinese Han population (507 cases and 505 controls) utilizing Agena MassARRAY. The relationship between these SNPs and LC susceptibility was assessed using odds ratios, 95% confidence intervals, and χ2 tests. Additionally, multifactor dimensionality reduction was employed to analyze SNP-SNP interactions. Bioinformatics methods were applied to investigate the function of these SNPs.

RESULTS

We found that rs2099361 was associated with an increased susceptibility to LC in the codominant model (OR = 1.31, p = 0.045). Stratification analysis revealed the allele G at rs4803418 and the allele T at rs4803420 of CYP2B6 (BMI >24 kg/m2) were significantly linked to decreased susceptibility of LC. Conversely, the allele C at rs12979270 (BMI >24 kg/m2) showed increased susceptibility to LC. Moreover, a robust redundant relationship between rs12979270 and rs4803420 was identified in the study. According to the VannoPortal database, we found that rs4803420, rs12979270 and rs2099361 may modulate the binding affinity of LMNB1, SP1 and HDAC2, respectively.

CONCLUSIONS

Our results suggest that SNPs in the CYP2B6 gene play crucial roles in LC susceptibility.

An Investigation of the Prognostic Role of Genes Related to Lipid Metabolism in Head and Neck Squamous Cell Carcinoma

Head and neck squamous cell carcinoma (HNSCC) has become a prevalent malignancy, and its incidence and mortality rate are increasing worldwide. Accumulating evidence has indicated that lipid metabolism-related genes (LMRGs) are involved in the occurrence and development of HNSCC. This study investigated the latent association of lipid metabolism with HNSCC and established a prognostic signature based on LMRGs. A prognostic risk model composed of eight differentially expressed LMRGs (PHYH, CYP4F8, INMT, ELOVL6, PLPP3, BCHE, TPTE, and STAR) was constructed through The Cancer Genome Atlas database. Then, ELOVL6 expression was validated in oral squamous cell carcinoma (OSCC), which is a common type of HNSCC, by immunohistochemical analysis. ELOVL6 expression in the OSCC II/III group was significantly higher than that in the other three groups (normal, dysplasia, and OSCC I), and OSCC patients with high ELOVL6 expression had poorer survival than those with low ELOVL6 expression. In summary, the LMRG-based prognostic feature had prognostic predictive capacity. ELOVL6 may be a potential prognostic factor for HNSCC patients.

Pharmacogenetics of chemotherapy treatment response and -toxicities in patients with osteosarcoma: a systematic review

BACKGROUND

Osteosarcoma is the most common bone tumor in children and adolescents. Despite multiagent chemotherapy, only 71% of patients survives and these survivors often experience long-term toxicities. The main objective of this systematic review is to provide an overview of the discovery of novel associations of germline polymorphisms with treatment response and/or chemotherapy-induced toxicities in osteosarcoma.  METHODS: MEDLINE and Embase were systematically searched (2010-July 2022). Genetic association studies were included if they assessed > 10 germline genetic variants in > 5 genes in relevant drug pathways or if they used a genotyping array or other large-scale genetic analysis. Quality was assessed using adjusted STrengthening the REporting of Genetic Association studies (STREGA)-guidelines. To find additional evidence for the identified associations, literature was searched to identify replication studies.

RESULTS

After screening 1999 articles, twenty articles met our inclusion criteria. These range from studies focusing on genes in relevant pharmacokinetic pathways to whole genome sequencing. Eleven articles reported on doxorubicin-induced cardiomyopathy. For seven genetic variants in CELF4, GPR35, HAS3, RARG, SLC22A17, SLC22A7 and SLC28A3, replication studies were performed, however without consistent results. Ototoxicity was investigated in one study. Five small studies reported on mucosistis or bone marrow, nephro- and/or hepatotoxicity. Six studies included analysis for treatment efficacy. Genetic variants in ABCC3, ABCC5, FasL, GLDC, GSTP1 were replicated in studies using heterogeneous efficacy outcomes.

CONCLUSIONS

Despite that results are promising, the majority of associations were poorly reproducible due to small patient cohorts. For the future, hypothesis-generating studies in large patient cohorts will be necessary, especially for cisplatin-induced ototoxicity as these are largely lacking. In order to form large patient cohorts, national and international collaboration will be essential.

Thymoquinone Augments Methotrexate-Induced Apoptosis on Osteosarcoma Cells

BACKGROUND

Osteosarcoma (OS) as the most frequent primary bone malignancy in children and adolescents has a short survival rate in advanced stages. Alternative herbal medicines with fewer side effects or the potency to protect common therapy's side effects can be helpful in combinational therapies. Herein, we aim to explore the effects of Thymoquinone (TQ) combined with Methotrexate (MTX) on Saos-2 cells apoptosis.

METHODS

The effects of TQ and MTX alone or in combination on Saos-2 cell viability were measured by MTT assay. Real-time PCR was applied for the measurement of Bax, BCL-2, and caspase-9 mRNA expression. Apoptosis evaluation was conducted by flow cytometry.

RESULTS

TQ improves the cytotoxic effects of MTX on Saos-2 cells proliferation at lower doses. Indeed, the IC50 of MTX decreased from 26 μM to 15 μM when it combined with TQ. TQ and MTX can induce the expression level of pro-apoptotic factors, Bax and caspase-9 while inhibiting anti-apoptotic protein BCL-2. Moreover, the combination of TQ and MTX potentiates apoptosis to 73%, compared to either TQ (48%) or MTX (53%) treated cells.

CONCLUSION

The co-treatment of TQ and MTX is associated with the up-regulation of apoptotic factors and down-regulation of anti-apoptotic factors, conducting apoptosis aggravation and OS cell death.

Risk prediction for delayed clearance of high-dose methotrexate in pediatric hematological malignancies by machine learning

This study aimed to establish a predictive model to identify children with hematologic malignancy at high risk for delayed clearance of high-dose methotrexate (HD-MTX) based on machine learning. A total of 205 patients were recruited. Five variables (hematocrit, risk classification, dose, SLC19A1 rs2838958, sex) and three variables (SLC19A1 rs2838958, sex, dose) were statistically significant in univariable analysis and, separately, multivariate logistic regression. The data was randomly split into a "training cohort" and a "validation cohort". A nomogram for prediction of delayed HD-MTX clearance was constructed using the three variables in the training dataset and validated in the validation dataset. Five machine learning algorithms (cart classification and regression trees, naïve Bayes, support vector machine, random forest, C5.0 decision tree) combined with different resampling methods were used for model building with five or three variables. When developed machine learning models were evaluated in the validation dataset, the C5.0 decision tree combined with the synthetic minority oversampling technique (SMOTE) using five variables had the highest area under the receiver operating characteristic curve (AUC 0.807 [95% CI 0.724-0.889]), a better performance than the nomogram (AUC 0.69 [95% CI 0.594-0.787]). The results support potential clinical application of machine learning for patient risk classification.

Systematic Review of Pharmacogenetic Factors That Influence High-Dose Methotrexate Pharmacokinetics in Pediatric Malignancies

Methotrexate (MTX) is a mainstay therapeutic agent administered at high doses for the treatment of pediatric and adult malignancies, such as acute lymphoblastic leukemia, osteosarcoma, and lymphoma. Despite the vast evidence for clinical efficacy, high-dose MTX displays significant inter-individual pharmacokinetic variability. Delayed MTX clearance can lead to prolonged, elevated exposure, causing increased risks for nephrotoxicity, mucositis, seizures, and neutropenia. Numerous pharmacogenetic studies have investigated the effects of several genes and polymorphisms on MTX clearance in an attempt to better understand the pharmacokinetic variability and improve patient outcomes. To date, several genes and polymorphisms that affect MTX clearance have been identified. However, evidence for select genes have conflicting results or lack the necessary replication and validation needed to confirm their effects on MTX clearance. Therefore, we performed a systematic review to identify and then summarize the pharmacogenetic factors that influence high-dose MTX pharmacokinetics in pediatric malignancies. Using the PRISMA guidelines, we analyzed 58 articles and 24 different genes that were associated with transporter pharmacology or the folate transport pathway. We conclude that there is only one gene that reliably demonstrates an effect on MTX pharmacokinetics: SLCO1B1.