Redox Metabolism-Associated Molecular Classification of Clear Cell Renal Cell Carcinoma

One-carbon metabolism shapes T cell immunity in cancer

One-carbon metabolism (1CM), comprising folate metabolism and methionine metabolism, serves as an important mechanism for cellular energy provision and the production of vital signaling molecules, including single-carbon moieties. Its regulation is instrumental in sustaining the proliferation of cancer cells and facilitating metastasis; in addition, recent research has shed light on its impact on the efficacy of T cell-mediated immunotherapy. In this review, we consolidate current insights into how 1CM affects T cell activation, differentiation, and functionality. Furthermore, we delve into the strategies for modulating 1CM in both T cells and tumor cells to enhance the efficacy of adoptively transferred T cells, overcome metabolic challenges in the tumor microenvironment (TME), and maximize the benefits of T cell-mediated immunotherapy.

Identification of key ferroptosis genes and subtypes in kidney renal clear cell carcinoma

Tumour immunity is highly important for the occurrence and development of tumours, and many cancers are resistant to ferroptosis. This study aims to explore the relationship between ferroptosis-related genes (FRGs) and the immunological characteristics of kidney renal clear cell carcinoma (KIRC). We obtained RNA-seq profiles and clinical data of KIRC patients from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases and identified CD44 and GLRX5 as the key FRGs involved in KIRC immune infiltration through Spearman's correlation analysis. Based on the expression of CD44 and GLRX5, the consensus clustering algorithm was used to classify the TCGA-KIRC samples into two clusters. A nomogram was constructed to evaluate the prognosis of KIRC patients. ESTIMATE, CIBERSORT, and single-sample gene set enrichment analysis (ssGSEA) were performed to evaluate immune infiltration between the two clusters. A weighted gene co-expression network analysis (WGCNA) was used to identify the most relevant genes to the clusters and immunity. Then, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed. The external dataset GSE53757 was used to validate the immunological features between the two clusters. Cluster 2 patients had more active immune infiltration and might be more sensitive to immunotherapy; Cluster 2 patients also had a worse prognosis and might be at a more advanced stage of KIRC. We identified key ferroptosis-related genes and subgroups involved in the immune infiltration of KIRC, which is highly important for exploring the molecular mechanisms and treatments of KIRC.

Comprehensive analysis of the prognostic value of glutathione S-transferases Mu family members in breast cancer

Breast cancer (BC) remains a significant public health concern globally, with a high number of reported cases and a substantial number of deaths every year. Accumulating reactive oxygen species (ROS) and oxidative stress are related to BC and the Glutathione S-transferases Mu (GSTM) family is one of the most important enzymatic detoxifiers associated with many cancers. In this study, UALCAN, Kaplan-Meier plotter, bc-GenExMiner, cBioPortal, STRING, Enrichr, and TIMER databases were employed to carry out a comprehensive bioinformatic analysis and provide new insight into the prognostic value of GSTMs in BC. GSTM2-5 genes in mRNA and protein levels were found to be expressed at lower levels in breast tumors compared to normal tissues, and reduction in mRNA levels is linked to shorter overall survival (OS) and relapse-free survival (RFS). The lower mRNA levels of GSTMs were strongly associated with the worse Scarff-Bloom-Richardson (SBR) grades (p < 0.0001). The mRNA levels of all five GSTMs were substantially higher in estrogen receptor (ER)-positive and progesterone receptor (PR)-positive compared to ER-negative and PR-negative BC patients. As well, when nodal status was compared, GSTM1, GSTM3, and GSTM5 were significantly higher in nodal-positive BC patients (p < .01). Furthermore, GSTM4 had the most gene alteration (4%) among other family members, and GSTM5 showed the strongest correlation with CD4+ T cells (Cor= .234, p = 2.22e-13). In conclusion, our results suggest that GSTM family members may be helpful as biomarkers for prognosis and as therapeutic targets in BC.

A New Vista of Aldehyde Dehydrogenase 1A3 (ALDH1A3): New Specific Inhibitors and Activity-Based Probes Targeting ALDH1A3 Dependent Pathways in Glioblastoma, Mesothelioma and Other Cancers

Aldehyde dehydrogenases of the subfamily 1A (ALDH1A) are enzymes necessary for the oxidation of all-trans or 9-cis retinal to retinoic acid (RA). Retinoic acid and its derivatives are important for normal development and maintenance of epithelia, reproduction, memory, and immune function in adults. Moreover, in recent years, it has been demonstrated that ALDH1A members are also expressed and functional in several human cancers where their role is not limited to the synthesis of RA. Here, we review the current knowledge about ALDH1A3, one of the 1A isoforms, in cancers with an emphasis on two of the deadliest tumors that affect humans: glioblastoma multiforme and mesothelioma. In both tumors, ALDH1A3 is considered a negative prognostic factor, and its level correlates with excessive proliferation, chemoresistance, and invasiveness. We also review the recent attempts to develop both ALDH1A3-selective inhibitors for cancer therapy and ALDH1A3-specific fluorescent substrates for fluorescence-guided tumor resection.

Integrated analysis revealing a novel stemness-metabolism-related gene signature for predicting prognosis and immunotherapy response in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a malignant lethal tumor and both cancer stem cells (CSCs) and metabolism reprogramming have been proven to play indispensable roles in HCC. This study aimed to reveal the connection between metabolism reprogramming and the stemness characteristics of HCC, established a new gene signature related to stemness and metabolism and utilized it to assess HCC prognosis and immunotherapy response. The clinical information and gene expression profiles (GEPs) of 478 HCC patients came from the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA). The one-class logistic regression (OCLR) algorithm was employed to calculate the messenger ribonucleic acid expression-based stemness index (mRNAsi), a new stemness index quantifying stemness features. Differentially expressed analyses were done between high- and low-mRNAsi groups and 74 differentially expressed metabolism-related genes (DEMRGs) were identified with the help of metabolism-related gene sets from Molecular Signatures Database (MSigDB). After integrated analysis, a risk score model based on the three most efficient prognostic DEMRGs, including Recombinant Phosphofructokinase Platelet (PFKP), phosphodiesterase 2A (PDE2A) and UDP-glucuronosyltransferase 1A5 (UGT1A5) was constructed and HCC patients were divided into high-risk and low-risk groups. Significant differences were found in pathway enrichment, immune cell infiltration patterns, and gene alterations between the two groups. High-risk group patients tended to have worse clinical outcomes and were more likely to respond to immunotherapy. A stemness-metabolism-related model composed of gender, age, the risk score model and tumor-node-metastasis (TNM) staging was generated and showed great discrimination and strong ability in predicting HCC prognosis and immunotherapy response.

Multi-Omics Approach Reveals Redox Homeostasis Reprogramming in Early-Stage Clear Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) is a malignant tumor originating from proximal tubular epithelial cells, and despite extensive research efforts, its redox homeostasis characteristics and protein S-nitrosylation (or S-nitrosation) (SNO) modification remain largely undefined. This serves as a reminder that the aforementioned features demand a comprehensive inspection. We collected tumor samples and paracancerous normal samples from five patients with early-stage ccRCC (T1N0M0) for proteomic, SNO-proteome, and redox-targeted metabolic analyses. The localization and functional properties of SNO proteins in ccRCC tumors and paracancerous normal tissues were elucidated for the first time. Several highly useful ccRCC-associated SNO proteins were further identified. Metabolic reprogramming, redox homeostasis reprogramming, and tumorigenic alterations are the three major characteristics of early-stage ccRCC. Peroxidative damage caused by rapid proliferation coupled with an increased redox buffering capacity and the antioxidant pool is a major mode of redox homeostasis reprogramming. NADPH and NADP⁺, which were identified from redox species, are both effective biomarkers and promising therapeutic targets. According to our findings, SNO protein signatures and redox homeostasis reprogramming are valuable for understanding the pathogenesis of ccRCC and identifying novel topics that should be seriously considered for the diagnosis and precise therapy of ccRCC.

Integration of single-cell RNA sequencing and bulk RNA sequencing to reveal an immunogenic cell death-related 5-gene panel as a prognostic model for osteosarcoma

Background

Despite the comparatively low prevalence of osteosarcoma (OS) compared to other cancer types, metastatic OS has a poor overall survival rate of fewer than 30%. Accumulating data has shown the crucial functions of immunogenic cell death (ICD) in various cancers; nevertheless, the relationship between ICD and OS was not previously well understood. This research aims to determine the function of ICD in OS and construct an ICD-based prognostic panel.

Methods

Single cell RNA sequencing data from GSE162454 dataset distinguished malignant cells from normal cells in OS. The discrepancy in ICD scores and corresponding gene expression was intensively explored between malignant cells and normal cells. Using the RNA sequencing data of the TARGET-OS, GSE16091, GSE21257, and GSE39058 datasets, the molecular subtype of OS was determined by clustering seventeen ICD-related genes obtained from the literature. Differentially expressed genes (DEGs) between different molecular subtypes were identified to develop a novel ICD-associated prognostic panel.

Results

The malignant cells had a remarkable decrease in the ICD scores and corresponding gene expression compared with normal cells. A total of 212 OS patients were successfully stratified into two subtypes: C1 and C2. C1-like OS patients were characterized by better prognostic outcomes, overexpression of ICD genes, activation of the ICD pathway, high inflitration abundance of immunocytes, and low expression levels of immune checkpoint genes (ICGs); however, the reverse is true in C2-like OS patients. Utilizing the limma programme in R, the DEGs between two subtypes were determined, and a 5-gene risk panel consisting of BAMBI, TMCC2, NOX4, DKK1, and CBS was developed through LASSO-Cox regression analysis. The internal- and external-verification cohorts were employed to verify the efficacy and precision of the risk panel. The AUC values of ROC curves indicated excellent prognostic prediction values of our risk panel.

Conclusions

Overall, ICD represented a protective factor against OS, and our 5-gene risk panel serving as a biomarker could effectively evaluate the prognostic risk in patients with OS.

The downregulated drug-metabolism related ALDH6A1 serves as predictor for prognosis and therapeutic immune response in gastric cancer

Drug metabolism-associated genes have been clarified to play a vital role in the process of cancer cell growth and migration. Nevertheless, the correlation between drug metabolism-associated genes and gastric cancer (GC) has not been fully explored and clarified. This paper has focused on the role of aldehyde dehydrogenase 6 family member A1 (ALDH6A1), a drug metabolism-associated gene, in the immune regulation and prognosis of GC patients. Using several bioinformatics platforms and immunohistochemistry (IHC) assay, we found that ALDH6A1 expression was significantly down-regulated in GC tissues. Moreover, higher expression of ALDH6A1 was related to the better prognosis of GC patients. ALDH6A1 was also found to be involved in the regulation of several immune-associated signatures, including immunoinhibitors. In conclusion, the above results have concluded that aberrant expression of ALDH6A1 might be served as the promising predictor for prognosis and clinical immunotherapy response in GC patients.