N7-methylguanosine methylation-related regulator genes as biological markers in predicting prognosis for melanoma

Identification and validation of N7 -methylguanosine-associated gene NCBP1 as prognostic and immune-associated biomarkers in breast cancer patients

We intend to evaluate the importance of N7 -methylguanosine (m7G) for the prognosis of breast cancer (BC). We gained 29 m7G-related genes from the published literature and among them, 16 m7G-related genes were found to have differential expression. Five differentially expressed genes (CYFIP1, EIF4E, EIF4E3, NCBP1 and WDR4) were linked to overall survival. This suggests that m7G-related genes might be prognostic or therapeutic targets for BC patients. We put the five genes to LASSO regression analysis to create a four-gene signature, including EIF4E, EIF4E3, WDR4 and NCBP1, that divides samples into two risky groups. Survival was drastically worsened in a high-risk group (p < 0.001). The signature's predictive capacity was demonstrated using ROC (10-year AUC 0.689; 10-year AUC 0.615; 3-year AUC 0.602). We found that immune status was significantly different between the two risk groups. In particular, NCBP1 also has a poor prognosis, with higher diagnostic value in ROC. NCBP1 also has different immune states according to its high or low expression. Meanwhile, knockdown of NCBP1 suppresses BC malignancy in vitro. Therefore, m7G RNA regulators are crucial participants in BC and four-gene mRNA levels are important predictors of prognosis. NCBP1 plays a critical target of m7G mechanism in BC.

Integrative lactylation and tumor microenvironment signature as prognostic and therapeutic biomarkers in skin cutaneous melanoma

BACKGROUND

The incidence of skin cutaneous melanoma (SKCM), one of the most aggressive and lethal skin tumors, is increasing worldwide. However, for advanced SKCM, we still lack an accurate and valid way to predict its prognosis, as well as novel theories to guide the planning of treatment options for SKCM patients. Lactylation (LAC), a novel post-translational modification of histones, has been shown to promote tumor growth and inhibit the antitumor response of the tumor microenvironment (TME) in a variety of ways. We hope that this study will provide new ideas for treatment options for SKCM patients, as well as research on the molecular mechanisms of SKCM pathogenesis and development.

METHODS

At the level of the RNA sequencing set (TCGA, GTEx), we used differential expression analysis, LASSO regression analysis, and multifactor Cox regression analysis to screen for prognosis-related genes and calculate the corresponding LAC scores. The content of TME cells in the tumor tissue was calculated using the CIBERSORT algorithm, and the TME score was calculated based on its results. Finally, the LAC-TME classifier was established and further analyzed based on the two scores, including the construction of a prognostic model, analysis of clinicopathological characteristics, and correlation analysis of tumor mutation burden (TMB) and immunotherapy. Based on single-cell RNA sequencing data, this study analyzed the cellular composition in SKCM tissues and explored the role of LAC scores in intercellular communication. To validate the functionality of the pivotal gene CLPB in the model, cellular experiments were ultimately executed.

RESULTS

We screened a total of six prognosis-related genes (NDUFA10, NDUFA13, CLPB, RRM2B, HPDL, NARS2) and 7 TME cells with good prognosis. According to Kaplan-Meier survival analysis, we found that the LAClow/TMEhigh group had the highest overall survival (OS) and the LAChigh/TMElow group had the lowest OS (p value < 0.05). In further analysis of immune infiltration, tumor microenvironment (TME), functional enrichment, tumor mutational load and immunotherapy, we found that immunotherapy was more appropriate in the LAClow/TMEhigh group. Moreover, the cellular assays exhibited substantial reductions in proliferation, migration, and invasive potentials of melanoma cells in both A375 and A2058 cell lines upon CLPB knockdown.

CONCLUSIONS

The prognostic model using the combined LAC score and TME score was able to predict the prognosis of SKCM patients more consistently, and the LAC-TME classifier was able to significantly differentiate the prognosis of SKCM patients across multiple clinicopathological features. The LAC-TME classifier has an important role in the development of immunotherapy regimens for SKCM patients.

Multiple epigenetic modification profiles reveal the tumor immune microenvironment and clinical outcomes of uveal melanoma

Uveal melanoma (UM) is an aggressive intraocular cancer that, in 50% of cases, spreads to the patient's other systems. The exact cause of the increased metastatic rate is still unknown. Methylation and immune response, metastasis, and the expansion of cancer cells are closely related. Additionally, proteins linked to RNA methylation have come to light as possible cancer treatment targets. However, the relationship between methylation-related genes (MRGs) and the tumor microenvironment (TME) is still not understood. The goal of this work was to discover important MRGs and create a signature for UM patients' prognosis prediction. Using two different data sets, we examined the MRG expression patterns in the transcriptional and genomic regions of 106 UM samples. We discovered a connection between the clinicopathological traits of the patients, their prognosis, the capability of TME cells to infiltrate, and various MRG changes. Following that, we developed an MRGs signature to forecast prognosis, and we evaluated the model's precision in patients with UM. We grouped the patients into multiple categories based on their clinical traits, looked at the survival rates for various groups within various groupings, and tested their accuracy. Additionally, to increase the practical usability of the MRGs model, we created a very accurate nomogram. TIDE scores were higher in the low-risk group. We go over how MGRs could impact UM's TME, immunotherapy responsiveness, prognosis, and clinically significant features. We looked for different chemotherapeutic drugs and cutting-edge targeted agents for patients in diverse subgroups in order to better understand MRGs in UM. This helped in the creation of customized therapy to open new doors. We could also further research the prognosis and develop more efficient immunotherapy regimens.