Background: Medulloblastomas (MB) are the most common malignant brain tumors in the pediatric age. In 2021, WHO categorized medulloblastomas into two groups: molecularly defined and histologically defined medulloblastomas. Molecularly defined medulloblastomas are divided into WNTactivated medulloblastoma, SHH-activated and TP53-wildtype medulloblastoma, SHH-activated, and TP53-mutant and non-WNT/non-SHH medulloblastoma, which include Group 3 (MYC) and Group 4 (CDK6 and MYCN). In this paper, we will focus on molecularly defined medulloblastomas. Objective: This paper aims to review the literature in order to describe the molecular structure of the medulloblastoma groups and to emphasize the importance of genetic predictors in medulloblastoma that can be used in clinical practice, either as a prognostic tool or as a therapeutic target in the future. Results: Each molecular subtype of medulloblastoma presents a different prognosis, and the molecular subtype with the best prognosis is medulloblastoma-activated WNT. It has even been observed that a reduction in the intensity of the combined treatment does not modify the prognosis of the patients, resulting in even fewer adverse effects due to the treatment. On the other hand, it was observed that the subtypes with the worst prognosis are medulloblastomas with activated MYC and medulloblastomas with activated SHH and mutated TP53, due to their high capacity to metastasize or to their radio-resistance. However, a new target therapy has emerged that could help improve the prognosis in these patients. Conclusion: The deeper knowledge of the molecular pathways involved in the appearance and progression of medulloblastomas will allow us to offer a prognosis at the time of diagnosis and more specific treatments through the development of the targeted therapy.

Objectives: The variability in outcomes among individuals is caused by multiple factors, including genetic variations in drug transporter genes known as ABCs. This study investigates the clinical impact of single nucleotide variants (SNV) in the ABCC1/MRP1, ABCC2/MRP2, and ABCC4/MRP4 genes on the clinical response and relapse of pediatric patients with central nervous system tumors. Methods: In a study involving 111 cancer patients, genotyping of ABCC1/MRP1, ABCC2/MRP2, and ABCC4/MRP4 was conducted using real-time PCR with TaqMan probes. Treatment response was evaluated using the Response Assessment in Neuro-Oncology (RANO) criteria. Results: Univariate and multivariate analyses using the Cox proportional hazards (adjusted) model. Multivariate analysis adjusted for sex and age showed a significant association between ABCC1 r.5540G>C; rs12921623 in the gene and non-response to treatment in the codominant model HR=2.095 (95% CI 1.202-3.650) p= 0.009 and in the dominant model HR= 2.025 (95% CI 1.199 -3.421), p=0. 008 and an increased risk of relapse in the codominant model HR= 9.09 (95% CI 1.04-78.85) p=0.04 and the dominant model HR= 3.912 (95% CI 1.139-13.436) p= 0.03. Furthermore, a significant association was found between ABCC2 c. 3972C>T; rs3740066 and relapse in the recessive model HR=3.5 (95% CI 1.02-12.17) p= 0.04. Conclusions: Our findings indicate that ABCC1 r.5540 G>C SNV and in the ABCC2 c. 3972C>T SNV are significant predictors of non-response and relapse in this group of pediatric patients with central nervous system tumors.

Multidrug resistance (MDR) commonly leads to cancer treatment failure because cancer cells often expel chemotherapeutic drugs using ATP-binding cassette (ABC) transporters, which reduce drug levels within the cells. This study investigated the clinical characteristics and single nucleotide variant (SNV) in ABCB1, ABCC1, ABCC2, ABCC4, and ABCG2, and their association with mortality in pediatric patients with central nervous system tumors (CNST). Using TaqMan probes, a real-time polymerase chain reaction genotyped 15 SNPs in 111 samples. Patients were followed up until death or the last follow-up day using the Cox proportional hazards model. An association was found between the rs1045642 (ABCB1) in the recessive model (HR = 2.433, 95% CI 1.098–5.392, p = 0.029), and the ICE scheme in the codominant model (HR = 9.810, 95% CI 2.74–35.06, p ≤ 0.001), dominant model (HR = 6.807, 95% CI 2.87–16.103, p ≤ 0.001), and recessive model (HR = 6.903, 95% CI 2.915–16.544, p = 0.038) significantly increased mortality in this cohort of patients. An association was also observed between the variant rs3114020 (ABCG2) and mortality in the codominant model (HR = 5.35, 95% CI 1.83–15.39, p = 0.002) and the dominant model (HR = 4.421, 95% CI 1.747–11.185, p = 0.002). A significant association between the ICE treatment schedule and increased mortality risk in the codominant model (HR = 6.351, 95% CI 1.831–22.02, p = 0.004, HR = 9.571, 95% CI 2.856–32.07, p ≤ 0.001), dominant model (HR = 6.592, 95% CI 2.669–16.280, p ≤ 0.001), and recessive model (HR = 5.798, 95% CI 2.411–13.940, p ≤ 0.001). The genetic variants rs3114020 in the ABCG2 gene and rs1045642 in the ABCB1 gene and the ICE chemotherapy schedule were associated with an increased mortality risk in this cohort of pediatric patients with CNST.

The variability in outcomes among individuals is caused by multiple factors, including genetic variations in drug transporter genes known as ABCs. This study investigates the clinical effect of single-nucleotide variants (SNVs) in the ABCC1/MRP1, ABCC2/MRP2, and ABCC4/MRP4 genes on the clinical response and relapse of pediatric patients with central nervous system tumors. In a cohort-based association study involving 111 cancer patients, genotyping of ABCC1/MRP1, ABCC2/MRP2, and ABCC4/MRP4 was conducted using real-time PCR with TaqMan probes. Treatment response was evaluated using the Response Assessment in Neuro-Oncology (RANO) criteria. Univariate and multivariate analyses were conducted using the Cox proportional hazards (adjusted) model. Multivariate analysis adjusted for sex and age showed a significant association between ABCC1 r.5540out G>C; rs12921623 in the gene and non-response to treatment in the codominant model [HR] 2.095, 95% CI 1.202–3.650, p = 0.009, and in the dominant model [HR] 2.025, 95% CI 1.199–3.421, p = 0.008, and an increased risk of relapse in the codominant model [HR] 9.09, 95% CI 1.04–78.85, p = 0.04, and in the dominant model [HR] 3.912, 95% CI 1.139–13.436, p = 0.03. Furthermore, a significant association was found between ABCC2 c. 3972 C>T; rs3740066 and relapse in the recessive model [HR] 3.5, 95% CI 1.02–12.17, p = 0.04. Our findings indicate that ABCC1 r.5540 G>C SNV and ABCC2 c. 3972 C>T SNV are significant predictors of non-response and relapse in this group of pediatric patients with central nervous system tumors.