Exploring a specialized programmed-cell death patterns to predict the prognosis and sensitivity of immunotherapy in cutaneous melanoma via machine learning.

The mortality and therapeutic failure in cutaneous melanoma (CM) are mainly caused by wide metastasis and chemotherapy resistance. Meanwhile, immunotherapy is considered a crucial therapy strategy for CM patients. However, the efficiency of currently available methods and biomarkers in predicting the response of immunotherapy and prognosis of CM is limited. Programmed cell death (PCD) plays a significant role in the occurrence, development, and therapy of various malignant tumors. In this research, we integrated fourteen types of PCD, multi-omics data from TCGA-SKCM and other cohorts in GEO, and clinical CM patients to develop our analysis. Based on significant PCD patterns, two PCD-related CM clusters with different prognosis, tumor microenvironment (TME), and response to immunotherapy were identified. Subsequently, seven PCD-related features, especially CD28, CYP1B1, JAK3, LAMP3, SFN, STAT4, and TRAF1, were utilized to establish the prognostic signature, namely cell death index (CDI). CDI accurately predicted the response to immunotherapy in both CM and other cancers. A nomogram with potential superior predictive ability was constructed, and potential drugs targeting CM patients with specific CDI have also been identified. Given all the above, a novel CDI gene signature was indicated to predict the prognosis and exploit precision therapeutic strategies of CM patients, providing unique opportunities for clinical intelligence and new management methods for the therapy of CM.

ZNF765 is a prognostic biomarker of hepatocellular carcinoma associated with cell cycle, immune infiltration, m6A modification, and drug susceptibility.

Hepatocellular carcinoma (HCC) is an ongoing challenge worldwide. Zinc finger protein 765 (ZNF765) is an important zinc finger protein that is related to the permeability of the blood-tumor barrier. However, the role of ZNF765 in HCC is unclear. This study evaluated the expression of ZNF765 in hepatocellular carcinoma and the impact of its expression on patient prognosis based on The Cancer Genome Atlas (TCGA). Immunohistochemical assays (IHC) were used to examine protein expression. Besides, a colony formation assay was used to examine cell viability. We also explored the relationship between ZNF765 and chemokines in the HCCLM3 cells by qRT-PCR. Moreover, we examined the effect of ZNF765 on cell resistance by measurement of the maximum half-inhibitory concentration. Our research revealed that ZNF765 expression in HCC samples was higher than that in normal samples, whose upregulation was not conducive to the prognosis. The results of GO, KEGG, and GSEA showed that ZNF765 was associated with the cell cycle and immune infiltration. Furthermore, we confirmed that the expression of ZNF765 had a strong connection with the infiltration level of various immune cells, such as B cells, CD4+ T cells, macrophages, and neutrophils. In addition, we found that ZNF765 was associated with m6A modification, which may affect the progression of HCC. Finally, drug sensitivity testing found that patients with HCC were sensitive to 20 drugs when they expressed high levels of ZNF765. In conclusion, ZNF765 may be a prognostic biomarker related to cell cycle, immune infiltration, m6A modification, and drug sensitivity for hepatocellular carcinoma.

Comprehensive analysis reveals TSEN54 as a robust prognosis biomarker and promising immune-related therapeutic target for hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma represents the most common primary malignancy of all liver cancer types and its prognosis is usually unsatisfactory. TSEN54 encodes a protein constituting a subunit of the tRNA splicing endonuclease heterotetramer. Previous researches concentrated on the contribution of TSEN54 in pontocerebellar hypoplasia, but no studies have yet reported its role in HCC. METHODS: TIMER, HCCDB, GEPIA, HPA, UALCAN, MEXPRESS, SMART, TargetScan, RNAinter, miRNet, starBase, Kaplan-Meier Plotter, cBioPortal, LinkedOmics, GSEA, TISCH, TISIDB, GeneMANIA, PDB, GSCALite were applied in this research. RESULTS: We identified the upregulation of TSEN54 expression in HCC and related it to multiple clinicopathological features. Hypomethylation of TSEN54 was closely associated with its high expression. HCC sufferers who held high TSEN54 expression typically had shorter survival expectations. Enrichment analysis showed the involvement of TSEN54 in the cell cycle and metabolic processes. Afterward, we observed that TSEN54 expression level had a positive relationship to the infiltration level of multiple immune cells and the expression of several chemokines. We additionally identified that TSEN54 was related to the expression level of several immune checkpoints and TSEN54 was linked to several m6A-related regulators. CONCLUSIONS: TSEN54 is a prognostic marker of HCC. TSEN54 could become a prospective candidate for HCC diagnosis and therapy.

ZNF320 is a hypomethylated prognostic biomarker involved in immune infiltration of hepatocellular carcinoma and associated with cell cycle.

Hepatocellular carcinoma (HCC) is one of the most deadly and common malignant cancers around the world, and the prognosis of HCC patients is not optimistic. ZNF320 belongs to Krüppel like zinc finger gene family. However, no studies have focused on the influence of ZNF320 in HCC. We first analyzed ZNF320 expression in HCC by using data from TCGA and ICGC, then conducted a joint analysis with TIMER and UALCAN, and validated by immunohistochemistry in clinical HCC samples. Then we applied UALCAN to explore the correlation between ZNF320 expression and clinicopathological characteristics. Consequently, using Kaplan-Meier Plotter analysis and the Cox regression, we can predict the prognostic value of ZNF320 for HCC patients. Next, the analysis by GO, KEGG, and GSEA revealed that ZNF320 was significantly correlated to cell cycle and immunity. Finally, TIMER and GEPIA analysis verified that ZNF320 expression is closely related to tumor infiltrating immune cells (TIIC), including B cells, CD8+ T cells, CD4+ T cells, macrophages, neutrophils, and dendritic cells. The analysis of the TCGA and ICGC data sets revealed that ZNF320 expression was significantly correlated with m6A related genes (RBMX, YTHDF1, and METTL3). In conclusion, ZNF320 may be a prognostic biomarker related to immunity as a candidate for liver cancer.

Identification of KRBA1 as a Potential Prognostic Biomarker Associated with Immune Infiltration and m6A Modification in Hepatocellular Carcinoma.

Purpose: Hepatocellular carcinoma (HCC) is a malignancy with high incidence, but its prognosis is not optimistic. KRBA1 is a member of the KRAB family and participates in the regulation of gene transcription. However, no studies have focused on the role of KRBA1 in HCC. Patients and Methods: In this study, we first analyzed the expression of KRBA1 in HCC using TCGA and ICGC databases and validated by Immunohistochemistry in clinical HCC samples. The Wilcoxon rank-sum test was used to determine the relationship between KRBA1 expression and clinicopathological features. Subsequently, we used Kaplan-Meier online website analysis and Cox regression model to predict the prognostic value of KRBA1 in HCC patients. Furthermore, the functions of KRBA1 were identified by enrichment analysis. TIMER and GSCALite were used to investigate the relationship between KRBA1 expression in HCC and immune infiltration and drug targets, respectively. Finally, the relationship between KRBA1 expression and m6A modification in HCC was analyzed using the TCGA and ICGA datasets. Results: The results showed that KRBA1 was upregulated in HCC and was associated with many clinicopathological features. High KRBA1 causes poor overall survival and may be an independent risk factor for HCC. KRBA1 tends to be hypermethylated and associated with poor prognosis in HCC compared with normal tissues. Enrichment analysis indicates that KRBA1 is associated with cell cycle and immune processes, and TIMER analysis shows that KRBA1 expression is associated with infiltration levels and immune characteristics of various immune cells. Silenced KRBA1 evidently reduced three chemokine expression in HCC cells. Drug sensitivity analysis showed that KRBA1 was sensitive to 39 drug small molecules. KRBA1 showed a strong positive correlation with five m6A related genes. Conclusion: KRBA1 is a prognostic biomarker associated with HCC immunity and m6a modification, serving as an effective target for the diagnosis and treatment of HCC.