Using Genomic and Transcriptome Analyses to Identify the Role of the Oxidative Stress Pathway in Renal Clear Cell Carcinoma and Its Potential Therapeutic Significance

A state-of-the-art review on the NRF2 in Hepatitis virus-associated liver cancer

According to a paper released and submitted to WHO by IARC scientists, there would be 905,700 new cases of liver cancer diagnosed globally in 2020, with 830,200 deaths expected as a direct result. Hepatitis B virus (HBV) hepatitis C virus (HCV), and hepatitis D virus (HDV) all play critical roles in the pathogenesis of hepatocellular carcinoma (HCC), despite the rising prevalence of HCC due to non-infectious causes. Liver cirrhosis and HCC are devastating consequences of HBV and HCV infections, which are widespread worldwide. Associated with a high mortality rate, these infections cause about 1.3 million deaths annually and are the primary cause of HCC globally. In addition to causing insertional mutations due to viral gene integration, epigenetic alterations and inducing chronic immunological dysfunction are all methods by which these viruses turn hepatocytes into cancerous ones. While expanding our knowledge of the illness, identifying these pathways also give possibilities for novel diagnostic and treatment methods. Nuclear factor erythroid 2-related factor 2 (NRF2) activation is gaining popularity as a treatment option for oxidative stress (OS), inflammation, and metabolic abnormalities. Numerous studies have shown that elevated Nrf2 expression is linked to HCC, providing more evidence that Nrf2 is a critical factor in HCC. This aberrant Nrf2 signaling drives cell proliferation, initiates angiogenesis and invasion, and imparts drug resistance. As a result, this master regulator may be a promising treatment target for HCC. In addition, the activation of Nrf2 is a common viral effect that contributes to the pathogenesis, development, and chronicity of virus infection. However, certain viruses suppress Nrf2 activity, which is helpful to the virus in maintaining cellular homeostasis. In this paper, we discussed the influence of Nrf2 deregulation on the viral life cycle and the pathogenesis associated with HBV and HCV. We summed up the mechanisms for the modulation of Nrf2 that are deregulated by these viruses. Moreover, we describe the molecular mechanism by which Nrf2 is modulated in liver cancer, liver cancer stem cells (LCSCs), and liver cancer caused by HBV and HCV. Video Abstract.

Cuproptosis associated genes affect prognosis and tumor microenvironment infiltration characterization in lung adenocarcinoma

Cuproptosis, a newly discovered mechanism of programmed cell death, is important for detailing the metabolic aspects of cancer progression and thereby guiding cancer therapy. An exciting era of translational medicine has led to the rapid development of countless immunotherapeutic strategies. The existing successful cancer immunotherapies have sparked new hope for patients with solid and hematologic malignancies. Hence, it is important to characterize the link between the cuproptosis process and the immunity status in the tumor microenvironment (TME) in Lung Adenocarcinoma (LUAD), which may be able to predict patient's prognosis. In this study, we systematically assessed 10 cuproptosis-associated genes (CAGs) and comprehensively characterized the relationship between cuproptosis and the molecular characteristics and immune cell infiltration of tumor tissue, prognosis and clinical treatment of patients. Subsequently, the CAG_score for predicting overall survival (OS) was established and its reliable predictive ability in LUAD patients was confirmed. Next, we created a highly reliable nomogram to facilitate the clinical viability of the CAG_score. The low CAG_score group, with lower immune cell infiltration, and mutation burden, had a significantly superior OS, which was associated with a better response to immunotherapy. The present study revealed that cuproptosis play a significant role in TME regulation in LUAD. Collectively, we identified a prognostic CAGs-related signature for LUAD patients. This signature may contribute to clarifying the characteristics of TME and enable the exploration of more potent immunotherapy strategies.

Comprehensive characterisation of immunogenic cell death in melanoma revealing the association with prognosis and tumor immune microenvironment

Increasing evidence has highlighted the critical functions of immunogenic cell death (ICD) within many tumors. However, the therapeutic possibilities and mechanism of utilizing ICD in melanoma are still not well investigated. Melanoma samples involved in our study were acquired from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. First, pan-cancer analysis of ICD systematically revealed its expression characteristics, prognostic values, mutation information, methylation level, pathway regulation relationship in multiple human cancers. The non-negative matrix factorization clustering was utilized to separate the TCGA-melanoma samples into two subtypes (i.e. C1 and C2) with different prognosis and immune microenvironment based on the expression traits of ICD. Then, LASSO-Cox regression analysis was utilized to determine an ICD-dependent risk signature (ICDRS) based on the differentially expressed genes (DEGs) between the two subtypes. Principal component analysis and t-distributed stochastic neighbor embedding analysis of ICDRS showed that high- and low-risk subpopulations could be clearly distinguished. Survival analysis and ROC curves in the training, internal validation, and external validation cohorts highlighted the accurate prognosis evaluation of ICDRS. The obvious discrepancies of immune microenvironment between the different risk populations might be responsible for the different prognoses of patients with melanoma. These findings revealed the close association of ICD with prognosis and tumor immune microenvironment. More importantly, ICDRS-based immunotherapy response and targeted drug prediction might be beneficial to different risk subpopulations of patients with melanoma. The innotative ICDRS could function as a marker to determine the prognosis and tumor immune microenvironment in melanoma. This will aid in patient classification for individualized melanoma treatment.

Integration of transcriptomics, proteomics, and metabolomics data to reveal HER2-associated metabolic heterogeneity in gastric cancer with response to immunotherapy and neoadjuvant chemotherapy

Background

Currently available prognostic tools and focused therapeutic methods result in unsatisfactory treatment of gastric cancer (GC). A deeper understanding of human epidermal growth factor receptor 2 (HER2)-coexpressed metabolic pathways may offer novel insights into tumour-intrinsic precision medicine.

Methods

The integrated multi-omics strategies (including transcriptomics, proteomics and metabolomics) were applied to develop a novel metabolic classifier for gastric cancer. We integrated TCGA-STAD cohort (375 GC samples and 56753 genes) and TCPA-STAD cohort (392 GC samples and 218 proteins), and rated them as transcriptomics and proteomics data, resepectively. 224 matched blood samples of GC patients and healthy individuals were collected to carry out untargeted metabolomics analysis.

Results

In this study, pan-cancer analysis highlighted the crucial role of ERBB2 in the immune microenvironment and metabolic remodelling. In addition, the metabolic landscape of GC indicated that alanine, aspartate and glutamate (AAG) metabolism was significantly associated with the prevalence and progression of GC. Weighted metabolite correlation network analysis revealed that glycolysis/gluconeogenesis (GG) and AAG metabolism served as HER2-coexpressed metabolic pathways. Consensus clustering was used to stratify patients with GC into four subtypes with different metabolic characteristics (i.e. quiescent, GG, AAG and mixed subtypes). The GG subtype was characterised by a lower level of ERBB2 expression, a higher proportion of the inflammatory phenotype and the worst prognosis. However, contradictory features were found in the mixed subtype with the best prognosis. The GG and mixed subtypes were found to be highly sensitive to chemotherapy, whereas the quiescent and AAG subtypes were more likely to benefit from immunotherapy.

Conclusions

Transcriptomic and proteomic analyses highlighted the close association of HER-2 level with the immune status and metabolic features of patients with GC. Metabolomics analysis highlighted the co-expressed relationship between alanine, aspartate and glutamate and glycolysis/gluconeogenesis metabolisms and HER2 level in GC. The novel integrated multi-omics strategy used in this study may facilitate the development of a more tailored approach to GC therapy.

FMR1 is identified as an immune-related novel prognostic biomarker for renal clear cell carcinoma: A bioinformatics analysis of TAZ/YAP

WW domain-containing transcription regulator 1 (TAZ, or WWTR1) and Yes-associated protein 1 (YAP) are both important effectors of the Hippo pathway and exhibit different functions. However, few studies have explored their co-regulatory mechanisms in kidney renal clear cell carcinoma (KIRC). Here, we used bioinformatics approaches to evaluate the co-regulatory roles of TAZ/YAP and screen novel biomarkers in KIRC. GSE121689 and GSE146354 were downloaded from the GEO. The limma was applied to identify the differential expression genes (DEGs) and the Venn diagram was utilized to screen co-expressed DEGs. Co-expressed DEGs obtained the corresponding pathways through GO and KEGG analysis. The protein-protein interaction (PPI) network was constructed using STRING. The hub genes were selected applying MCODE and CytoHubba. GSEA was further applied to identify the hub gene-related signaling pathways. The expression, survival, receiver operating character (ROC), and immune infiltration of the hub genes were analyzed by HPA, UALCAN, GEPIA, pROC, and TIMER. A total of 51 DEGs were co-expressed in the two datasets. The KEGG results showed that the enriched pathways were concentrated in the TGF-β signaling pathway and endocytosis. In the PPI network, the hub genes (STAU2, AGO2, FMR1) were identified by the MCODE and CytoHubba. The GSEA results revealed that the hub genes were correlated with the signaling pathways of metabolism and immunomodulation. We found that STAU2 and FMR1 were weakly expressed in tumors and were negatively associated with the tumor stages. The overall survival (OS) and disease-free survival (DFS) rate of the high-expressed group of FMR1 was greater than that of the low-expressed group. The ROC result exhibited that FMR1 had certainly a predictive ability. The TIMER results indicated that FMR1 was positively correlated to immune cell infiltration. The abovementioned results indicated that TAZ/YAP was involved in the TGF-β signaling pathway and endocytosis. FMR1 possibly served as an immune-related novel prognostic gene in KIRC.

Construction and Validation of Angiogenesis-Related Prognostic Risk Signature to Facilitate Survival Prediction and Biomarker Excavation of Breast Cancer Patients

This study is aimed at exploring the potential mechanism of angiogenesis, a biological process-related gene in breast cancer (BRCA), and constructing a risk model related to the prognosis of BRCA patients. We used multiple bioinformatics databases and multiple bioinformatics analysis methods to complete our exploration in this research. First, we use the RNA-seq transcriptome data in the TCGA database to conduct a preliminary screening of angiogenesis-related genes through univariate Cox curve analysis and then use LASSO regression curve analysis for secondary screening. We successfully established a risk model consisting of seven angiogenesis-related genes in BRCA. The results of ROC curve analysis show that the risk model has good prediction accuracy. We can successfully divide BRCA patients into the high-risk and low-risk groups with significant prognostic differences based on this risk model. In addition, we used angiogenesis-related genes to perform cluster analysis in BRCA patients and successfully divided BRCA patients into three clusters with significant prognostic differences, namely, cluster 1, cluster 2, and cluster 3. Subsequently, we combined the clinical-pathological data for correlation analysis, and there is a significant correlation between the risk model and the patient’s T and stage. Multivariate Cox regression curve analysis showed that the age of BRCA patients and the risk score of the risk model could be used as independent risk factors in the progression of BRCA. In particular, based on this angiogenesis-related risk model, we have drawn a matching nomogram that can predict the 5-, 7-, and 10-year overall survival rates of BRCA patients. Subsequently, we performed a series of pan-cancer analyses of CNV, SNV, OS, methylation, and immune infiltration for this risk model gene and used GDSC data to explore drug sensitivity. Subsequently, to gain insight into the protein expression of these risk model genes in BRCA, we used the immunohistochemical data in the THPA database for verification. The results showed that the protein expressions of IL18, RUNX1, SCG2, and THY1 molecules in BRCA tissues were significantly higher than those in normal breast tissues, while the protein expressions of PF4 and TNFSF12 molecules in BRCA tissues were significantly lower than those in normal breast tissues. Finally, we conducted multiple GSEA analyses to explore the biological pathways these risk model genes can cross in cancer progression. In summary, we believe that this study can provide valuable data and clues for future studies on angiogenesis in BRCA.

Application of Regulatory Cell Death in Cancer: Based on Targeted Therapy and Immunotherapy

The development of cancer treatment methods is constantly changing. For common cancers, our treatment methods are still based on conventional treatment methods, such as chemotherapy, radiotherapy, and targeted drug therapy. Nevertheless, the emergence of tumor resistance has a negative impact on treatment. Regulated cell death is a gene-regulated mode of programmed cell death. After receiving specific signal transduction, cells change their physical and chemical properties and the extracellular microenvironment, resulting in structural destruction and decomposition. As research accumulates, we now know that by precisely inducing specific cell death patterns, we can treat cancer with less collateral damage than other treatments. Many newly discovered types of RCD are thought to be useful for cancer treatment. However, some experimental results suggest that some RCDs are not sensitive to cancer cell death, and some may even promote cancer progression. This review summarizes the discovered types of RCDs, reviews their clinical efficacy in cancer treatment, explores their anticancer mechanisms, and discusses the feasibility of some newly discovered RCDs for cancer treatment in combination with the immune and tumor microenvironment.