Evaluation of TP53 Codon 72, P21 Codon 31, and MDM2 SNP309 Polymorphisms in Iranian Patients with Acute Lymphocytic Leukemia

Contribution of Cyclin Dependent Kinase Inhibitor 1A Genotypes to Childhood Acute Lymphocytic Leukemia Risk in Taiwan

BACKGROUND/AIM

The disruption of cell-cycle control can lead to an imbalance in cell proliferation, often accompanied by genomic instability, which in turn can facilitate carcinogenesis. This study aimed to examine the impact of CDKN1A rs1801270 and rs1059234 polymorphisms on the risk of childhood acute lymphocytic leukemia (ALL) in Taiwan.

MATERIALS AND METHODS

The genotypes of CDKN1A rs1801270 and rs1059234 in 266 childhood ALL cases and 266 controls were determined using PCR-RFLP techniques.

RESULTS

The genotypic and allelic frequencies for CDKN1A rs1801270 and rs1059234 did not significantly differ between childhood ALL cases and controls (all p>0.05). However, stratified analysis revealed that the CDKN1A rs1801270 AA variant was associated with a reduced risk of childhood ALL in males (OR=0.40, 95%CI=0.20-0.82, p=0.0178). Additionally, the AC and AA genotypes of rs1801270 were linked to a lower risk classification for childhood ALL and longer survival times (OR=0.57 and 0.31, 95%CI=0.33-0.97 and 0.18-0.56, p=0.0538 and 0.0001, respectively). No significant associations were found for rs1059234 in the stratified analyses (p>0.05 for all).

CONCLUSION

Although CDKN rs1801270 and rs1059234 genotypes were not associated with an overall risk of childhood ALL, CDKN1A rs1801270 polymorphism may serve as a protective predictor in males and as a potential marker for better prognosis of childhood ALL. Validation in larger and more diverse populations is necessary to confirm the feasibility of this predictor.

The Diversity of Methylation Patterns in Serous Borderline Ovarian Tumors and Serous Ovarian Carcinomas

Background: Changes in DNA methylation patterns are a pivotal mechanism of carcinogenesis. In some tumors, aberrant methylation precedes genetic changes, while gene expression may be more frequently modified due to methylation alterations than by mutations. Methods: Herein, 128 serous ovarian tumors were analyzed, including borderline ovarian tumors (BOTS) with (BOT.V600E) and without (BOT) the BRAF V600E mutation, low-grade (lg), and high-grade (hg) ovarian cancers (OvCa). The methylome of the samples was profiled with Infinium MethylationEPIC microarrays. Results: The biggest number of differentially methylated (DM) CpGs and regions (DMRs) was found between lgOvCa and hgOvCa. By contrast, the BOT.V600E tumors had the lowest number of DM CpGs and DMRs compared to all other groups and, in relation to BOT, their genome was strongly downmethylated. Remarkably, the ten most significant DMRs, discriminating BOT from lgOvCa, encompassed the MHC region on chromosome 6. We also identified hundreds of DMRs, being of potential use as predictive biomarkers in BOTS and hgOvCa. DMRs with the best discriminative capabilities overlapped the following genes: BAIAP3, IL34, WNT10A, NEU1, SLC44A4, and HMOX1, TCN2, PES1, RP1-56J10.8, ABR, NCAM1, RP11-629G13.1, AC006372.4, NPTXR in BOTS and hgOvCa, respectively. Conclusions: The global genome-wide hypomethylation positively correlates with the increasing aggressiveness of ovarian tumors. We also assume that the immune system may play a pivotal role in the transition from BOTS to lgOvCa. Given that the BOT.V600E tumors had the lowest number of DM CpGs and DMRs compared to all other groups, when methylome is considered, such tumors might be placed in-between BOT and OvCa.

TP53 Gene 72 Arg/Pro (rs1042522) single nucleotide polymorphism increases the risk and the severity of chronic lymphocytic leukemia

Background

Genetic variations in TP53 gene are known to be important in chronic lymphocytic leukemia (CLL) and may cause its inactivation which is associated with an aggressive form of the disease. Single nucleotide polymorphism (rs1042522:G>C) in TP53 gene at codon 72 encodes for arginine (Arg) or proline (Pro) variant which results in amino acid substitution affecting the apoptotic potential of TP53 protein. The aim of this study was to assess the correlation between TP53 codon 72 polymorphism and risk susceptibility as well as severity of CLL among Tunisian patients.

Materials and methods

A case-control study was conducted in Tunisia from February 2019 to November 2021, 160 de novo CLL patients and 160 healthy volunteers matched in age and gender were involved. DNA was extracted from peripheral blood mononuclear cells and the rs1042522 was analyzed using PCR-RFLP.

Results

Pro variant was associated with higher susceptibility to CLL than Arg variant (p= 0.023). A significant association was found between Pro variant and prognostic classification of Binet stage C (p= 0.001), low hemoglobin level (p= 0.003) and low platelet count (p= 0.016).

Conclusion

We suggest that Pro variant may increase the risk of developing CLL in our population and could be associated with the severity of the disease.

Association between CDKN1A gene rs1801270 polymorphisms and susceptibility to colorectal cancser in an Iranian population

CDKN1A gene is implicated in cell differentiation, development process, repair, apoptosis, senescence, migration, and tumorigenesis. Somatic alterations and polymorphisms may interfere in the function of CDKN1A, and this could affect the individual susceptibility to colorectal cancer (CRC). Here in, we evaluated the importance of single nucleotide polymorphic variants in codon 31 of CDKN1A (rs1801270: C > A) for the development of colorectal cancer in an Iranian population. A total of 150 CRC patients and 150 healthy controls were enrolled in this study. Genomic DNA was extracted from peripheral blood specimens. Genotypes were determined using Polymerase Chain Reaction-Restriction Fragment Length Polymorphism (PCR-RFLP) assay. In CRC patients, the genotype frequencies detected were 90%, 8.0% and 2.0%2 for CC, AC and AA genotypes while the genotype frequencies in control group were 78%, 20.7% and 1.35% 1.35% for CC, AC and AA genotype, respectively. There were statistically significant differences in the distribution of CDKN1A rs1801270 genotypes and allele frequencies between colorectal cancer patients and healthy controls (p value = 0.021). Also, results indicated a significant negative association between AC genotype and risk of colorectal cancer occurrence. (Odds ratio (OR)=0.357; 95% confidence interval (CI)=0.168-0.760, p = 0.007). Our data suggest that the AC genotype may have a protective role in the development of CRC in an Iranian population.

EBNA1 Upregulates P53-Inhibiting Genes in Burkitt's Lymphoma Cell Line

Background

Suppression of p53 is an important mechanism in Epstein-Barr virus associate-tumors and described as EBNA1-USP7 which is a key axis in p53 suppression. Thus, in this study, we aimed to evaluate the function of EBNA1 on the expression of p53-inhibiting genes including HDAC-1, MDM2, MDM4, Sirt-3, and PSMD10 and the influence of USP7 inhibition using GNE-6776 on p53 at protein/mRNA level.

Methods

The electroporation method was used to transfect the BL28 cell line with EBNA1. Cells with stable EBNA1 expression were selected by Hygromycin B treatment. The expression of seven genes, including PSMD10, HDAC-1, USP7, MDM2, P53, Sirt-3, and MDM4, was evaluated using a real-time PCR assay. For evaluating the effects of USP7 inhibition, the cells were treated with GNE-6776; after 24 hours and 4 days, the cells were collected and again expression of interest genes was evaluated.

Results

MDM2 (P=0.028), MDM4 (P=0.028), USP7 (P=0.028), and HDAC1 (P=0.015) all showed significantly higher expression in EBNA1-harboring cells compared to control plasmid transfected cells, while p53 mRNA expression was only marginally downregulated in EBNA1 harboring cells (P=0.685). Four-day after treatment, none of the studied genes was significantly changed. Also, in the first 24-hour after treatment, mRNA expression of p53 was downregulated (P=0.685), but after 4 days it was upregulated (P=0.7) insignificantly.

Conclusion

It seems that EBNA1 could strongly upregulate p53-inhibiting genes including HDAC1, MDM2, MDM4, and USP7. Moreover, it appears that the effects of USP7 suppression on p53 at protein/mRNA level depend on the cell nature; however, further research is needed.

In silico identification and in vitro expression analysis of breast cancer-related m6A-SNPs

Research on m6A-associated SNPs (m6A-SNPs) has emerged recently due to their possible critical roles in many key biological processes. In this sense, several investigations have identified m6A-SNPs in different diseases. In order to gain a more complete understanding of the role that m6A-SNPs can play in breast cancer, we performed an in silico analysis to identify the m6A-SNPs associated with breast cancer and to evaluate their possible effects. For this purpose, we downloaded SNPs related to breast cancer and a list of m6A-SNPs from public databases in order to identify which ones appear in both. Subsequently, we assessed the identified m6A-SNPs in silico by expression quantitative trait loci (eQTL) analysis and differential gene expression analysis. We genotyped the m6A-SNPs found in the in silico analysis in 35 patients with breast cancer, and we carried out a gene expression analysis experimentally on those that showed differences. Our results identified 981 m6A-SNPs related to breast cancer. Four m6A-SNPs showed an eQTL effect and only three were in genes that presented an altered gene expression. When the three m6A-SNPs were evaluated in the tissue sample of our breast cancer patients, only the m6A-SNP rs76563149 located in ZNF354A gene presented differences in allele frequencies and a low gene expression in breast cancer tissues, especially in luminal B HER2+ subtype. Future investigations of these m6A-SNPs should expand the study in different ethnic groups and increase the sample sizes to test their association with breast cancer and elucidate their molecular function.

An easy-to-use nomogram predicting overall survival of adult acute lymphoblastic leukemia

Adult acute lymphoblastic leukemia (ALL) is heterogeneous both biologically and clinically. The outcomes of ALL have been improved with the application of children-like regimens and novel agents including immune therapy in young adults. The refractory to therapy and relapse of ALL have occurred in most adult cases. Factors affecting the prognosis of ALL include age and white blood cell (WBC) count at diagnosis. The clinical implications of genetic biomarkers, including chromosome translocation and gene mutation, have been explored in ALL. The interactions of these factors on the prediction of prognosis have not been evaluated in adult ALL. A prognostic model based on clinical and genetic abnormalities is necessary for clinical practice in the management of adult ALL. The newly diagnosed adult ALL patients were divided into the training and the validation cohort at 7:3 ratio. Factors associated with overall survival (OS) were assessed by univariate/multivariate Cox regression analyses and a signature score was assigned to each independent factor. A nomogram based on the signature score was developed and validated. The receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA) were used to assess the performance of the nomogram model. This study included a total of 229 newly diagnosed ALL patients. Five independent variables including age, WBC, bone marrow (BM) blasts, MLL rearrangement, and ICT gene mutations (carried any positive mutation of IKZF1, CREBBP and TP53) were identified as independent adverse factors for OS evaluated by the univariate, Kaplan-Meier survival and multivariate Cox regression analyses. A prognostic nomogram was built based on these factors. The areas under the ROC curve and calibration curve showed good accuracy between the predicted and observed values. The DCA curve showed that the performance of our model was superior to current risk factors. A nomogram was developed and validated based on the clinical and laboratory factors in newly diagnosed ALL patients. This model is effective to predict the overall survival of adult ALL. It is a simple and easy-to-use model that could efficiently predict the prognosis of adult ALL and is useful for decision making of treatment.