CDKN2A Polymorphism in Melanoma Patients in Colombian Population: A Case-Control Study

Polygenic Risk Score Analysis of 37 SNPs Associated with Melanoma Risk in Colombian Population

Melanoma incidence is increasing, with distinct genetic and clinical patterns observed in the Latin American population. This study aimed to evaluate melanoma risk in a Colombian cohort through polygenic risk analysis using 37 variants across nine genes previously associated with melanoma. We performed polygenic risk score (PRS) analysis on 85 melanoma patients and 165 controls. Genotyping was performed for 37 melanoma-associated SNPs, and on the basis of previous GWAS reports, individual PRSs were calculated for each participant. The participants were then stratified into quartiles to examine risk gradients. In addition, phenotypic features such as eye and hair color were evaluated, and genetic models and haplotype analyses were performed, adjusting for sex and family history of cancer. PRS quartile stratification revealed a clear risk gradient. Notably, 31.8% of the melanoma cases were clustered in the highest-risk quartile (Q4), with a maximum PRS of 1.04. Variants in TYR, TYRP1, CDKN2A, and HERC2 significantly contributed to risk, and light brown eye and hair colors were strongly associated with increased melanoma risk. Moreover, a protective haplotype in the OCA2-HERC2 region was identified among males. The integration of the PRS with clinical and phenotypic factors has potential for improving melanoma risk stratification in the Colombian population, warranting further investigation in larger, diverse cohorts.

The Prognostic Value of the 31-Gene Expression Profile Test in Cutaneous Melanoma: A Systematic Review and Meta-Analysis

BACKGROUND

Cutaneous melanoma is an increasingly common and potentially lethal form of skin cancer. Current staging systems based on clinical and pathological features have limitations in accurately predicting outcomes, particularly for early-stage disease. The 31-gene expression profile (31-GEP) test has emerged as a promising tool for improving risk stratification in melanoma patients.

METHODS

We conducted a systematic review and meta-analysis of studies evaluating the prognostic performance of the 31-GEP test in cutaneous melanoma. A comprehensive literature search was performed in multiple databases. Studies reporting survival outcomes stratified by 31-GEP class were included. Random-effects models were used to determine survival estimates across studies.

RESULTS

Thirteen studies comprising 14,760 patients were included in the meta-analysis. The 31-GEP test consistently stratified patients into risk groups with significantly different outcomes. The 5-year melanoma-specific survival rates were 99.8% (95% CI: 98-100%) for Class 1A, 97.6% (95% CI: 92.4-99.3%) for Class 1B/2A, and 83.4% (95% CI: 66.5-92.7%) for Class 2B. Similar trends were observed for recurrence-free and distant metastasis-free survival.

CONCLUSIONS

This meta-analysis supports the prognostic utility of the 31-GEP test in cutaneous melanoma prognostication. The test consistently stratified patients into clinically meaningful risk groups across multiple survival metrics. These findings support the potential clinical utility of the 31-GEP test in enhancing current staging systems and informing personalized management strategies for melanoma patients.

Comparative Analysis of the Effect of the BRAF Inhibitor Dabrafenib in 2D and 3D Cell Culture Models of Human Metastatic Melanoma Cells

BACKGROUND/AIM

Melanoma, a variant of skin cancer, presents the highest mortality rates among all skin cancers. Despite advancements in targeted therapies, immunotherapies, and tissue culture techniques, the absence of an effective early treatment model remains a challenge. This study investigated the impact of dabrafenib on both 2D and 3D cell culture models with distinct molecular profiles.

MATERIALS AND METHODS

We developed a high-throughput workflow enabling drug screening on spheroids. Our approach involved cultivating 2D and 3D cultures derived from normal melanocytes and metastatic melanoma cells, treating them with dabrafenib and conducting viability, aggregation, migration, cell cycle, and apoptosis assays.

RESULTS

Dabrafenib exerted multifaceted influences, particularly on migration at concentrations of 10 and 25 μM. It induced a decrease in cell viability, impeded cellular adhesion to the matrix, inhibited cellular aggregation and spheroid formation, arrested the cell cycle in the G1 phase, and induced apoptosis.

CONCLUSION

These results confirm the therapeutic potential of dabrafenib in treating melanoma with the BRAF V600E mutation and that 3D models are validated models to study the potential of new molecules for therapeutic purposes. Furthermore, our study underscores the relevance of 3D models in simulating physiological in vivo microenvironments, providing insights into varied treatment responses between normal and tumor cells.

The importance of protein domain mutations in cancer therapy

Cancer is a complex disease that is caused by multiple genetic factors. Researchers have been studying protein domain mutations to understand how they affect the progression and treatment of cancer. These mutations can significantly impact the development and spread of cancer by changing the protein structure, function, and signalling pathways. As a result, there is a growing interest in how these mutations can be used as prognostic indicators for cancer prognosis. Recent studies have shown that protein domain mutations can provide valuable information about the severity of the disease and the patient's response to treatment. They may also be used to predict the response and resistance to targeted therapy in cancer treatment. The clinical implications of protein domain mutations in cancer are significant, and they are regarded as essential biomarkers in oncology. However, additional techniques and approaches are required to characterize changes in protein domains and predict their functional effects. Machine learning and other computational tools offer promising solutions to this challenge, enabling the prediction of the impact of mutations on protein structure and function. Such predictions can aid in the clinical interpretation of genetic information. Furthermore, the development of genome editing tools like CRISPR/Cas9 has made it possible to validate the functional significance of mutants more efficiently and accurately. In conclusion, protein domain mutations hold great promise as prognostic and predictive biomarkers in cancer. Overall, considerable research is still needed to better define genetic and molecular heterogeneity and to resolve the challenges that remain, so that their full potential can be realized.

METTL14-Mediated m6a Modification of CDKN2A Promotes the Development of Retinoblastoma by Inhibiting the p53 Pathway

The methyltransferase 14, N6-adenosine-methyltransferase subunit (METTL14) and Cyclin-dependent kinase inhibitor 2A (CDKN2A) have been identified as involved in the regulation of various cancer progression, while their mechanism and regulatory effect in retinoblastoma (RB) is still unclear. Cell colony formation, CCK-8 as well as Western blotting were used to evaluate the proliferation, apoptosis as well as p53 protein level of RB cell line. The METTL14 and CDKN2A levels were detected by qRT-PCR or Western blotting when METTL14 was up-regulated or CDKN2A was down-regulated. MeRIP and Pearson analysis were performed to confirm the regulatory relationship between METTL14 among CDKN2A. We found that the levels of CDKN2A and METTL14 were abundant in RB samples, as well as RB cells. METTL14 enhances N6-methyladenosine (m6A) modification of CDKN2A to upregulate its mRNA and protein levels. The proliferation of RB cells can be inhibited by silencing CDKN2A, which promotes apoptosis and p53 protein level. Furthermore, high-expression of METTL14 eliminated the anti-tumor effect of CDKN2A silencing in RB progression in vitro. CDKN2A is mediated by METTL14-m6A modified and restrains p53 pathway activation to accelerate the malignancy of RB. This points to the METTL14-m6A-CDKN2A-p53 pathway axis as a possible prospective target for the future RB treatment.

The relationship between single nucleotide polymorphisms and skin cancer susceptibility: A systematic review and network meta-analysis

Background

Single nucleotide polymorphisms (SNPs) interfere with the function of certain genes and thus may influence the probability of skin cancer. The correlation between SNPs and skin cancer (SC) lacks statistical power, however. Therefore, the purpose of this study was to identify the gene polymorphisms involved in skin cancer susceptibility using network meta-analysis and to determine the relationship between SNPs and SC risk.

Methods

PubMed, Embase, and Web of Science were searched for articles including "SNP" and different types of SC as keywords between January 2005 and May 2022. The Newcastle-Ottawa Scale was used to assess bias judgments. The odds ratio (ORs) and their 95% confidence intervals (CIs) were determined to estimate heterogeneity within and between studies. Meta-analysis and network meta-analysis were carried out to identify the SNPs associated with SC. The P-score of each SNP was compared to obtain the rank of probability. Subgroup analyses were performed by cancer type.

Results

A total of 275 SNPs from 59 studies were included in the study. Two subgroup SNP networks using the allele model and dominant model were analyzed. The alternative alleles of rs2228570 (FokI) and rs13181 (ERCC2) were the first-ranking SNPs in both subgroups one and two of the allele model, respectively. The homozygous dominant genotype and heterozygous genotype of rs475007 in subgroup one and the homozygous recessive genotype of rs238406 in subgroup two were most likely to be associated with skin cancer based on the dominant model.

Conclusions

According to the allele model, SNPs FokI rs2228570 and ERCC2 rs13181 and, according to the dominant model, SNPs MMP1 rs475007 and ERCC2 rs238406 are closely linked to SC risk.

3'UTR-CDKN2A and CDK4 Germline Variants Are Associated With Susceptibility to Cutaneous Melanoma

BACKGROUND/AIM

Genetic variations of the CDKN2A and CDK4 gene have been associated to melanoma development. In the present study we investigated the potential associations of CDKN2A and CDK4 gene variants in a colombian population diagnosed with melanoma.

MATERIALS AND METHODS

DNA was extracted from whole blood samples from 85 patients diagnosed with cutaneous melanoma and 166 healthy controls. CDKN2A and CDK4 genes were genotyped using a high-resolution melting assay.

RESULTS

A similar distribution of CDKN2A variants 500C>G and 540C>T was found among cases (12% and 31% respectively) and controls (15% and 31% respectively). The CDKN2A variants were present in 36% of acral lentiginous melanoma and 39.47% of lentigo maligna. The haplotype analysis showed an association with susceptibility in the development of melanoma.

CONCLUSION

The presence of haplotype 500G/540C in males is associated with an increased risk of melanoma in a colombian population, especially in subjects with a family history of cancer.