Novel oxidative stress-related prognostic biomarkers for melanoma associated with tumor metastasis

Proteomic Analysis Highlights the Impact of the Sphingolipid Metabolizing Enzyme β-Galactosylceramidase on Mitochondrial Plasticity in Human Melanoma

Mitochondrial plasticity, marked by a dynamism between glycolysis and oxidative phosphorylation due to adaptation to genetic and microenvironmental alterations, represents a characteristic feature of melanoma progression. Sphingolipids play a significant role in various aspects of cancer cell biology, including metabolic reprogramming. Previous observations have shown that the lysosomal sphingolipid-metabolizing enzyme β-galactosylceramidase (GALC) exerts pro-oncogenic functions in melanoma. Here, mining the cBioPortal for a Cancer Genomics data base identified the top 200 nuclear-encoded genes whose expression is negatively correlated with GALC expression in human melanoma. Their categorization indicated a significant enrichment in Gene Ontology terms and KEGG pathways related to mitochondrial proteins and function. In parallel, proteomic analysis by LC-MS/MS of two GALC overexpressing human melanoma cell lines identified 98 downregulated proteins when compared to control mock cells. Such downregulation was confirmed at a transcriptional level by a Gene Set Enrichment Analysis of the genome-wide expression profiling data obtained from the same cells. Among the GALC downregulated proteins, we identified a cluster of 42 proteins significantly associated with GO and KEGG categorizations related to mitochondrion and energetic metabolism. Overall, our data indicate that changes in GALC expression may exert a significant impact on mitochondrial plasticity in human melanoma cells.

Emerging prognostic biomarkers in advanced cutaneous melanoma: a literature update

INTRODUCTION

Over the past two years, the scientific community has witnessed an exponential growth in research focused on identifying prognostic biomarkers for melanoma, both in pre-clinical and clinical settings. This surge in studies reflects the need of developing effective prognostic indicators in the field of melanoma.

AREAS COVERED

The aim of this work is to review the scientific literature on the most recent findings on the development or validation of prognostic biomarkers in melanoma, in the attempt of providing both clinicians and researchers with an updated broad synopsis of prognostic biomarkers in cutaneous melanoma.

EXPERT OPINION

While the field of prognostic biomarkers in melanoma appears promising, there are several complexities and limitations to address. The interdependence of clinical, histological, and molecular features requires accurate classification of different biomarker families. Correlation does not imply causation, and adjustments for confounding factors are often overlooked. In this scenario, large-scale studies based on high-quality clinical trial data can provide more reliable evidence. It is essential to avoid oversimplification by focusing on a single biomarker, as the interactions among multiple factors contribute to define the disease course and patient's outcome. Furthermore, implementing well-supported evidence in real-life settings can help advance prognostic biomarker research in melanoma.

Integrative analysis of the prognostic value and immune microenvironment of mitophagy-related signature for multiple myeloma

BACKGROUND

Multiple myeloma (MM) is a fatal malignant tumor in hematology. Mitophagy plays vital roles in the pathogenesis and drug sensitivity of MM.

METHODS

We acquired transcriptomic expression data and clinical index of MM patients from NCI public database, and 36 genes involved in mitophagy from the gene set enrichment analysis (GSEA) database. Least absolute shrinkage and selection operator (LASSO) Cox regression analysis was conducted to construct a risk score prognostic model. Kaplan-Meier survival analysis and receiver operation characteristic curves (ROC) were conducted to identify the efficiency of prognosis and diagnosis. ESTIMATE algorithm and immune-related single-sample gene set enrichment analysis (ssGSEA) was performed to uncover the level of immune infiltration. QRT-PCR was performed to verify gene expression in clinical samples of MM patients. The sensitivity to chemotherapy drugs was evaluated upon the database of the genomics of drug sensitivity in cancer (GDSC).

RESULTS

Fifty mitophagy-related genes were differently expressed in two independent cohorts. Ten out of these genes were identified to be related to MM overall survival (OS) rate. A prognostic risk signature model was built upon on these genes: VDAC1, PINK1, VPS13C, ATG13, and HUWE1, which predicted the survival of MM accurately and stably both in training and validation cohorts. MM patients suffered more adverse prognosis showed more higher risk core. In addition, the risk score was considered as an independent prognostic element for OS of MM patients by multivariate cox regression analysis. Functional pathway enrichment analysis of differentially expressed genes (DEGs) based on risk score showed terms of cell cycle, immune response, mTOR pathway, and MYC targets were obviously enriched. Furthermore, MM patients with higher risk score were observed lower immune scores and lower immune infiltration levels. The results of qRT-PCR verified VDAC1, PINK1, and HUWE1 were dysregulated in new diagnosed MM patients. Finally, further analysis indicated MM patients showed more susceptive to bortezomib, lenalidomide and rapamycin in high-risk group.

CONCLUSION

Our research provided a neoteric prognostic model of MM based on mitophagy genes. The immune infiltration level based on risk score paved a better understanding of the participation of mitophagy in MM.

The Effects of Oncological Treatment on Redox Balance in Patients with Uveal Melanoma

(1) Background: Uveal malignant melanoma is the most common adult eye cancer and presents metabolic reprogramming that affects the tumoral microenvironment by altering the redox balance and producing oncometabolites. (2) Methods: The study prospectively evaluated patients undergoing enucleation surgery or stereotactic radiotherapy for uveal melanoma by following systemic oxidative-stress redox markers serum lipid peroxides, total albumin groups and total antioxidant levels (3) Results: Serum antioxidants and lipid peroxides were elevated from pre-treatment to longer-term follow-up. Antioxidants inversely correlated to lipid peroxides: higher in stereotactic radiosurgery patients pre/6/12/18 months post-treatment (p = 0.001-0.049) versus higher lipid peroxides in enucleation surgery patients pre/after/6 months post-treatment (p = 0.004-0.010). An increased variance in serum antioxidants was observed for enucleation surgery patients (p < 0.001), however enucleation did not increase mean serum antioxidants or albumin thiols; only lipid peroxides were increased post-enucleation (p < 0.001) and at 6-month follow-up (p = 0.029). Mean albumin thiols were increased for 18- and 24-month follow-ups (p = 0.017-0.022). Males who had enucleation surgery presented higher variance in serum determinations and overall higher lipid peroxides values pre/post-treatment and at the 18-month follow-up. (4) Conclusions: Initial oxidative stress-inducing events of surgical enucleation or stereotactic radiotherapy for uveal melanoma are followed by a longer-term inflammatory cascade gradually subsiding at later follow-ups.

Identification of an Oxidative Stress-Related LncRNA Signature for Predicting Prognosis and Chemotherapy in Patients With Hepatocellular Carcinoma

Background: Oxidative stress plays a critical role in oncogenesis and tumor progression. However, the prognostic role of oxidative stress-related lncRNA in hepatocellular carcinomas (HCC) has not been fully explored.

Methods: We used the gene expression data and clinical data from The Cancer Genome Atlas (TCGA) database to identify oxidative stress-related differentially expressed lncRNAs (DElncRNAs) by pearson correlation analysis. A four-oxidative stress-related DElncRNA signature was constructed by LASSO regression and Cox regression analyses. The predictive signature was further validated by Kaplan–Meier (K–M) survival analysis, receiver operating characteristic (ROC) curves, nomogram and calibration plots, and principal component analysis (PCA). Single-sample gene set enrichment analysis (ssGSEA) was used to explore the relationship between the signature and immune status. Finally, the correlation between the signature and chemotherapeutic response of HCC patients was analyzed.

Results: In our study, the four-DElncRNA signature was not only proved to be a robust independent prognostic factor for overall survival (OS) prediction, but also played a crucial role in the regulation of progression and chemotherapeutic response of HCC. ssGSEA showed that the signature was correlated with the infiltration level of immune cells. HCC patients in high-risk group were more sensitive to the conventional chemotherapeutic drugs including Sorafenib, lapatinib, Nilotinib, Gefitinib, Erlotinib and Dasatinib, which pave the way for targeting DElncRNA-associated treatments for HCC patients.

Conclusion: Our study has originated a prognostic signature for HCC based on oxidative stress-related DElncRNAs, deepened the understanding of the biological role of four key DElncRNAs in HCC and laid a theoretical foundation for the choice of chemotherapy.

Next-Generation Sequencing Advances the Genetic Diagnosis of Cerebral Cavernous Malformation (CCM)

Cerebral Cavernous Malformation (CCM) is a cerebrovascular disease of genetic origin that predisposes to seizures, focal neurological deficits and fatal intracerebral hemorrhage. It may occur sporadically or in familial forms, segregating as an autosomal dominant condition with incomplete penetrance and highly variable expressivity. Its pathogenesis has been associated with loss-of-function mutations in three genes, namely KRIT1 (CCM1), CCM2 and PDCD10 (CCM3), which are implicated in defense mechanisms against oxidative stress and inflammation. Herein, we screened 21 Italian CCM cases using clinical exome sequencing and found six cases (~29%) with pathogenic variants in CCM genes, including a large 145−256 kb genomic deletion spanning the KRIT1 gene and flanking regions, and the KRIT1 c.1664C>T variant, which we demonstrated to activate a donor splice site in exon 16. The segregation of this cryptic splicing mutation was studied in a large Italian family (five affected and seven unaffected cases), and showed a largely heterogeneous clinical presentation, suggesting the implication of genetic modifiers. Moreover, by analyzing ad hoc gene panels, including a virtual panel of 23 cerebrovascular disease-related genes (Cerebro panel), we found two variants in NOTCH3 and PTEN genes, which could contribute to the abnormal oxidative stress and inflammatory responses to date implicated in CCM disease pathogenesis.

Identification of m7G-associated lncRNA prognostic signature for predicting the immune status in cutaneous melanoma

RNA modifications, including RNA methylation, are widely existed in cutaneous melanoma (CM). Among epigenetic modifications, N7-methylguanosine (m7G) is a kind of modification at 5' cap of RNA which participate in maintaining the stability of mRNA and various cell biological processes. However, there is still no study concerning the relationship between CM and m7G methylation complexes, METTL1 and WDR4. Here, long non-coding RNA (lncRNAs) and gene expression data of CM from the Cancer Genome Atlas (TCGA) database were retrieved to identify differentially expressed m7G-related lncRNAs connected with overall survival of CM. Then, Cox regression analyses was applied to construct a lncRNA risk signature, the prognostic value of identified signature was further evaluated. As a result, 6 m7G-associated lncRNAs that were significantly related to CM prognosis were incorporated into our prognostic signature. The functional analyses indicated that the prognostic model was correlated with patient survival, cancer metastasis, and growth. Meanwhile, its diagnostic accuracy was better than conventional clinicopathological characteristics. The pathway enrichment analysis showed that the risk model was enriched in several immunity-associated pathways. Moreover, the signature model was significantly connected with the immune subtypes, infiltration of immune cells, immune microenvironment, as well as several m6A-related genes and tumor stem cells. Finally, a nomogram based on the calculated risk score was established. Overall, a risk signature based on 6 m7G-associated lncRNAs was generated which presented predictive value for the prognosis of CM patients and can be further used in the development of novel therapeutic strategies for CM.