WGX50 mitigates doxorubicin-induced cardiotoxicity through inhibition of mitochondrial ROS and ferroptosis.

BACKGROUND: Doxorubicin (DOX)-induced cardiotoxicity (DIC) is a major impediment to its clinical application. It is indispensable to explore alternative treatment molecules or drugs for mitigating DIC. WGX50, an organic extract derived from Zanthoxylum bungeanum Maxim, has anti-inflammatory and antioxidant biological activity, however, its function and mechanism in DIC remain unclear. METHODS: We established DOX-induced cardiotoxicity models both in vitro and in vivo. Echocardiography and histological analyses were used to determine the severity of cardiac injury in mice. The myocardial damage markers cTnT, CK-MB, ANP, BNP, and ferroptosis associated indicators Fe2+, MDA, and GPX4 were measured using ELISA, RT-qPCR, and western blot assays. The morphology of mitochondria was investigated with a transmission electron microscope. The levels of mitochondrial membrane potential, mitochondrial ROS, and lipid ROS were detected using JC-1, MitoSOX™, and C11-BODIPY 581/591 probes. RESULTS: Our findings demonstrate that WGX50 protects DOX-induced cardiotoxicity via restraining mitochondrial ROS and ferroptosis. In vivo, WGX50 effectively relieves doxorubicin-induced cardiac dysfunction, cardiac injury, fibrosis, mitochondrial damage, and redox imbalance. In vitro, WGX50 preserves mitochondrial function by reducing the level of mitochondrial membrane potential and increasing mitochondrial ATP production. Furthermore, WGX50 reduces iron accumulation and mitochondrial ROS, increases GPX4 expression, and regulates lipid metabolism to inhibit DOX-induced ferroptosis. CONCLUSION: Taken together, WGX50 protects DOX-induced cardiotoxicity via mitochondrial ROS and the ferroptosis pathway, which provides novel insights for WGX50 as a promising drug candidate for cardioprotection.

The long noncoding RNA KTN1-AS1 promotes bladder cancer tumorigenesis via KTN1 cis-activation and the consequent initiation of Rho GTPase-mediated signaling.

BACKGROUND: Accumulating evidence support the hypothesis that long noncoding RNAs (lncRNAs) are involved in several physiological and pathological conditions, including cancer. Here, we investigated the potential role of lncRNAs in bladder cancer. METHODS: We first looked at available datasets retrieved from the TCGA database and discovered that the lncRNA KTN 1 antisense RNA 1 (KTN1-AS1) was significantly up-regulated in several cancer types including bladder cancer, but was decreased in some other tumors. Therefore, we focused our attention on KTN1-AS1. Using both in vitro and in vivo systems that allowed the modulation of KTN1-AS1 and expression of other relevant proteins, we investigated in-depth the role of KTN1-AS1 in bladder cancer (and the mechanism behind). We further investigated the potential KTN1-AS1-interacting proteins using RNA immunoprecipitation, and explored the KTN1-AS1-related epigenetic landscape (with a particular emphasis on acetylation) using chromatin immunoprecipitation (ChIP) assays. RESULTS: KTN1-AS1 silencing inhibited the proliferation, invasion, and migration of bladder cancer cells, while KTN1-AS1 overexpression had the obvious opposite effects. Mechanistically, KTN1-AS1 promoted the recruitment of EP300, a histone acetyltransferase that enriched acetylation of histone H3 at lysine 27 (H3K27Ac) in the KTN1 promoter region. This epigenetic modulation contributed to the up-regulation of KTN1, which affected bladder cancer growth and progression via the regulation of Rho GTPase (RAC1, RHOA, and CDC42)-mediated signaling. CONCLUSION: Overall, our data support the idea that the lncRNA KTN1-AS1 promotes bladder cancer tumorigenesis via modulation of the KTN1/Rho GTPase axis and is a promising new therapeutic target for the treatment of bladder cancer.

Effect of up-regulation of circMATR3 on the proliferation, metastasis, progression and survival of hypopharyngeal carcinoma.

Increasing number of circular RNAs (circRNAs) have been reported to play important role in gene regulation, carcinogenesis and pathogenesis in various cancers. However, the biological functions and underlying molecular mechanisms of circRNAs in hypopharyngeal squamous cell carcinoma (HSCC) remain elusive. Thus, secondary circRNA-seq profiling was performed to identify the differentially expressed circRNAs between HSCC tissues and adjacent normal tissues, and the expression level of circMATR3 (derived from human gene matrin3 (MATR3), has_circRNA_0008922) was confirmed by qRT-PCR. Proliferation of HSCC cells was detected by cell counting kit-8 (CCK8) assay, apoptosis and the cell cycle were analysed by flow cytometry, and the migration and invasion of HSCC cells was determined by transwell assay. Bioinformatics analysis was conducted to predict possible pathways and potential miRNA targets of circMATR3. We found that circMATR3 was up-regulated in HSCC tissues, and abundant circMATR3 expression was markedly correlated with late T classification, advanced clinical stage, greater lymph node metastasis, and poor prognosis. Furthermore, knock-down of circMATR3 significantly inhibited proliferation, migration and invasion of HSCC cells, whereas silencing of circMATR3 induced cell apoptosis. Our analysis predicted that circMATR3 may participate in cancer-related pathways by serving as miRNA sponges. In conclusion, our findings first identified the oncogenic roles of circMATR3 in promoting the progression of HSCC and demonstrated that circMATR3 may be a novel prognostic marker and therapeutic target for HSCC.

The Long Noncoding RNA TUG1 Promotes Laryngeal Cancer Proliferation and Migration.

BACKGROUND/AIMS: Researchers have shown that long noncoding RNAs are closely associated with the pathogenesis of laryngeal squamous cell carcinoma (LSCC). However, the role of the long noncoding RNA taurine-upregulated gene 1 (TUG1) in the pathogenesis of LSCC remains unclear, although it is recognized as an oncogenic regulator for several types of squamous cell carcinoma. METHODS: qRT-PCR was performed to measure the expression of TUG1 in LSCC tissues and cell lines. 3-(4,5-dimethyl-2-thiazolyl)-2,5-diphenyl-2-H-tetrazolium bromide (MTT) was used to measure the effect of TUG1 on cell proliferation. Transwell assay and flow cytometry were employed to determine the effect of TUG1 on cell migration and invasion. Western-blot were performed to explore the relation of TUG1 and p53 mRNA. RESULTS: Higher TUG1 expression in LSCC than in paired normal tumor-adjacent tissue specimens (N = 64) was observed using quantitative real-time polymerase chain reaction. Also, high TUG1 expression was positively associated with advanced T category, worse lymph node metastasis and late clinical stage. Furthermore, in vitro experiments demonstrated that silencing of TUG1 markedly inhibited proliferation, cell-cycle progression, migration, and invasion of LSCC cells, whereas depletion of TUG1 led to increased apoptosis. CONCLUSION: These findings demonstrated that upregulated TUG1 expression exerted oncogenic effects by promoting proliferation, migration, and invasion, and inhibiting apoptosis in LSCC cells.

Multi-omics comprehensive analyses of programmed cell death patterns to regulate the immune characteristics of head and neck squamous cell carcinoma.

Head and neck squamous cell carcinoma (HNSCC) is a heterogeneous cancer with high morbidity and mortality. Triggering the programmed cell death (PCD) to enhance the anti-tumor therapies is being applied in multiple cancers. However, the limited understanding of genetic heterogeneity in HNSCC severely hampers the clinical efficacy. We systematically analyzed 14 types of PCD in HNSCC from The Cancer Genome Atlas (TCGA). We utilized ssGSEA to calculate the PCD scores and classify patients into two clusters. Subsequently, we displayed the genomic alteration landscape to unravel the significant differences in copy number alterations and gene mutations. Furthermore, we calculated the IC50 values of targeted drugs to predict the differences in sensitivity. To identify the immune-related prognostic types, we comprehensively estimated the relationship between immune indicators and all prognostic PCD in three datasets (TCGA, GSE65858, GSE41613). Finally, 7 regulators were filtered. Subsequently, we integrated 10 machine learning algorithms and 101 algorithm combinations to test the clinical predictive efficacy. Using WGCNA as a basis, we built a weighted co-expression network to identify modules involved in the immune landscape with different colors. Meanwhile, our results indicated that blue and red modules containing crucial regulators closely related to the CD4+, CD8+ T cells, TMB or PD-L1. FCGR2A from blue module, CSF2, INHBA, and THBS1 from the red module were determined. After verifying in vivo experiments, FCGR2A was identified as hub gene. In conclusion, our findings suggest a potential role of PCD in HNSCC, offering new insights into effective immunotherapy and anti-tumor therapies in HNSCC.

Multi-omics reveals the impact of cancer-associated fibroblasts on the prognosis and treatment response of adult diffuse highest-grade gliomas.

Background: Cancer associated fibroblasts (CAF), an important cancer-promoting and immunosuppressive component of the tumor immune microenvironment (TIME), have recently been found to infiltrate adult diffuse highest-grade gliomas (ADHGG) (gliomas of grade IV). Methods: Gene expression and clinical data of ADHGG patients were obtained from the CGGA and TCGA databases. Consensus clustering was used to identify CAF subtypes based on CAF key genes acquired from single-cell omics and spatial transcriptomomics. CIBERSORT, ssGSEA, MCPcounter, and ESTIMATE analyses were used to assess the TIME of GBM. Survival analysis, drug sensitivity analysis, TCIA database, TIDE and cMap algorithms were used to compare the prognosis and treatment response between patients with different CAF subtypes. An artificial neural network (ANN) model based on random forest was constructed to exactly identify CAF subtypes, which was validated in a real-world patient cohort of ADHGG. Results: Consensus clustering classified ADHGG into two CAF subtypes. Compared with subtype B, patients with ADHGG subtype A had a poorer prognosis, worse responsiveness to immunotherapy and radiotherapy, higher CAF infiltration in TIME, but higher sensitivity to temozolomide. Furthermore, patients with subtype A had a much lower proportion of IDH mutations. Finally, the ANN model based on five genes (COL3A1, COL1A2, CD248, FN1, and COL1A1) could exactly discriminate CAF subtypes, and the validation of the real-world cohort indicated consistent results with the bioinformatics analyses. Conclusion: This study revealed a novel CAF subtype to distinguish ADHGG patients with different prognosis and treatment responsiveness, which may be helpful for accurate clinical decision-making of ADHGG.

Identify and validate RUNX2 and LAMA2 as novel prognostic signatures and correlate with immune infiltrates in bladder cancer.

Background: Muscle-invasive bladder cancer (MIBC) develops lymph node (LN) metastasis or distant metastasis, leading to recurrence and poor prognosis. The five-year survival rate of MIBC with LN or distant metastasis is only 8.1%; therefore, there is an urgent need to identify reliable biomarkers for prognosis and treatment regimen for patients with bladder cancer (BLCA). Methods: SEER database was used to select important clinical characteristics for MIBC. Then, weighted gene co-expression network analysis (WGCNA) was employed to identify differentially expressed genes (DEGs) to recognize significant co-expression modules by calculating the correlation between the modules and clinical data. Furthermore, Cox regression and lasso analysis were applied to screen prognostic hub genes and establish the risk predictive model. Bladder cancer cell lines (UMUC3 and 5637) were used for experimental validation in vitro. Results: Cox analysis of 122,600 MIBC patients showed that the N stage was the most important clinical factor. A total of 4,597 DEGs were calculated between N0 and N+ patients, and WGCNA with these DEGs in 368 samples revealed that expression of turquoise was positively and strongly correlated with the N stage. Eight genes were identified as important prognostic candidates using lasso regression based on Cox analysis and STRING database. Combining GEO datasets, literature, and clinical factors, we identified LAMA2 and RUNX2 as novel prognostic biomarkers. CCK8 assay showed that depletion of LAMA2 or RUNX2 significantly inhibited the proliferation of BLCA cells, and flow cytometry indicated that knockdown of LAMA2 or RUNX2 induced the apoptosis of BLCA cells. Transwell assay also showed that silencing of LAMA2 or RUNX2 weakened the migration and invasiveness of BLCA cells. Conclusions: We constructed a new eight-gene risk model to provide novel prognostic biomarkers and therapeutic targets for BLCA.

Identify and validate circadian regulators as potential prognostic markers and immune infiltrates in head and neck squamous cell carcinoma.

Head and neck squamous cell carcinoma (HNSCC) is a heterogeneity pathological malignant cancer with leading causes of morbidity and mortality. EGFR inhibitors, immune checkpoint inhibitors have become novel treatments. However, the mechanism still remained uncertain. Several studies have confirmed that the circadian rhythms induce multiple malignancies developing. We utilized multi-omics analysis to demonstrate the crosstalk between circadian clock genes and tumor microenvironment in HNSCC. Firstly, we performed the LASSO Cox regression analysis based on the 16 important clock genes. A 7-gene risk model was successfully established in TCGA and validated in GEO datasets. Next, CIBERSORT and ESTIMATE methods were performed to display the immune landscape of high risk and low risk groups, and the results showed that high abundance of mast cells activated, dendritic cells activated and neutrophils were positively correlated with poor OS. To further identify hub genes, Kaplan Meier plot was applied in all TCGA and GEO datasets and two hub genes (PER2, and PER3) were identified, especially PER3, which was found strongly associated with immune score, PDCD1, CD4 + and CD8 + T cells in HNSCCC. Moreover, to explore the innate mechanism of circadian-induced pathway, we constructed a circadian-related ceRNA regulatory network containing 34 lncRNAs, 3 miRNAs and 4 core circadian genes. In-vitro experiments also verified that Per2 or Per3 could suppressed the proliferation, migration and invasion of HNSC. This study unraveled the association between PER3 and prognosis in patients with HNSC and the innate mechanism remains to be elucidated.

circRNA_0067717 promotes paclitaxel resistance in nasopharyngeal carcinoma by acting as a scaffold for TRIM41 and p53.

PURPOSE: Circular RNAs (circRNAs) play important roles in tumour progression. This study aimed to explore the mechanism of hsa_circ_0067717 (termed circRNA_0067717) promoting paclitaxel resistance in nasopharyngeal carcinoma (NPC). METHODS: We assayed CNE-1 and HNE-2 parental cell lines and the corresponding paclitaxel-resistant NPC cell lines using circRNA microarrays. RNA pull-down assay, RNA immunoprecipitation, and RNA fluorescence in situ hybridization were used to identify the molecular mechanisms. RESULTS: Here, we confirm that circRNA_0067717 is significantly upregulated in NPC paclitaxel-resistant cells and is associated with paclitaxel resistance in NPC. Mechanistically, circRNA_0067717 functions as a scaffold for TRIM41 protein (a ubiquitin E3 ligase) and p53 protein. In nasopharyngeal carcinoma paclitaxel-resistant cells, the highly expressed circRNA_0067717 can bind to more TRIM41 and p53 protein, promoting TRIM41-induced p53 ubiquitination and degradation, resulting in a decrease in p53 protein level. Moreover, the 1-176 nt area of circRNA_0067717 and the 301-425 nt region of circRNA_0067717 are the binding sites for p53 and TRIM41, respectively. The resistance of NPC cells to paclitaxel can be reduced by blocking these binding regions of circRNA_0067717. CONCLUSION: We demonstrate that circRNA_0067717 acts as a scaffold for TRIM41 and p53, enhancing paclitaxel chemoresistance in NPC by promoting TRIM41-induced p53 degradation via ubiquitination.

Multi-omics analysis of the oncogenic value of copper Metabolism-Related protein COMMD2 in human cancers.

BACKGROUND: The copper metabolism MURR1 domain (COMMD) protein family is involved in tumorigenicity of malignant tumors. However, as the member of COMMD, the role of COMMD2 in human tumors remains unknown. METHODS: We used The Cancer Genome Atlas (TCGA), Genotype Tissue Expression (GTEx), Human Protein Atlas (HPA) database, Cancer Cell Line Encyclopedia (CCLE) platform, univariate Cox regression analysis, Kaplan-Meier curve, cBioPortal, UALCAN database, Sangerbox online platform, GSCA database gene set enrichment analysis (GSEA), and GeneMANIA to analyze the expression of COMMD2, its prognostic values, genomic alteration patterns, and the correlation with tumor stemness, tumor mutational burden (TMB), microsatellite instability (MSI), and immune infiltrates, drug sensitivity, and gene function enrichment in pan-cancer. qRT-PCR, CCK-8, EdU, wound healing, and transwell migration assays were performed to confirm the function of COMMD2. RESULTS: COMMD2 was strongly expressed in most cancer types. Elevated COMMD2 expression affects the prognosis, clinicopathological stage, and molecular or immune subtypes of various tumors. Moreover, promoter hypomethylation and mutations in the COMMD2 gene may be associated with its high expression and poor survival. Additionally, we discovered that COMMD2 expression was linked to tumor stemness, TMB, MSI, immune cell infiltration, immune-checkpoint inhibitors, and drug sensitivity in pan-cancer. Furthermore, the COMMD2 gene co-expression network is constructed with GSEA analysis, displaying significant interaction of COMMD2 with E2F targets, G2-M checkpoint, and mitotic spindle in bladder cancer (BLCA). Finally, RNA interference data showed suppression of COMMD2 prevented proliferation and migration of BLCA and uterine corpus endometrial carcinoma (UCEC) cells. CONCLUSION: Our findings shed light on the COMMD2 functions in human cancers and demonstrate that it is a promising prognostic biomarker and therapeutic target in pan-cancer.

Hypoxia is correlated with the tumor immune microenvironment: Potential application of immunotherapy in bladder cancer.

OBJECTIVE: Hypoxia, which can considerably affect the tumor microenvironment, hinders the use of immunotherapy in bladder cancer (BLCA). Therefore, we aimed to identify reliable hypoxia-related biomarkers to guide clinical immunotherapy in BLCA. METHODS: Using data downloaded from TCGA-BLCA cohort, we determined BLCA subtypes which divide 408 samples into different subtypes. Tumor immune infiltration levels of two clusters were quantified using ssGSEA, MCPcounter, EPIC, ESTIMATE, and TIMER algorithms. Next, we constructed a hypoxia score based on the expression of hypoxia-related genes. The IMvigor210 cohort and SubMap analysis were used to predict immunotherapeutic responses in patients with different hypoxia scores. Hub genes were screened using cytoscape, immunohistochemistry (IHC), and multispectral immunofluorescence were used to detect the spatial distribution of immune markers. RESULTS: Patients with BLCA were categorized into cluster1 (n = 227) and Cluster2 (n = 181). Immune infiltration and expression of immune markers were higher in Cluster1. Immune infiltration was also more obvious in the high-hypoxia score group which related to a better predicted response to immunotherapy. IHC, and multispectral immunofluorescence confirmed the importance of TLR8 in immune infiltration and immune phenotype. CONCLUSIONS: BLCA subtype can evaluate the infiltration of immune cells in the tumor microenvironment of different patients. Hypoxia score in this study could effectively predict immunotherapeutic responses in patients with BLCA. TLR8 may be a potential target for clinical immunotherapy.

Multi-Omics Analysis and Verification of the Oncogenic Value of CCT8 in Pan-Cancers.

Background: Chaperonin-containing TCP1 subunit 8 (CCT8) has been proved to be involved in the occurrence and development of some cancers. However, no study has reported the potential role of CCT8 in a pan-cancer manner. Methods: TIMER2.0, GEPIA2, UALCAN and Sangerbox were used to explore the expression, prognosis and methylation of CCT8. We used cBioPortal, TISIDB, SangerBox, TIMER2.0 and TISMO to investigate the genetic alteration of CCT8 and the relationship of CCT8 with molecular subtype, immune subtype, immune infiltration and immunotherapy response. CCT8-related genes were screened out through GEPIA and STRING for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. CCK-8, the colony formation assay, the wound healing assay and the Transwell assay were performed to explore the influence of CCT8 on proliferation and migration. Results: CCT8 was highly expressed in most cancers with a poor prognosis. The expression level of CCT8, which was affected by the promoter region methylation and genetic alteration, was related to the molecular and immune subtype of cancers. Interestingly, CCT8 was positively associated with the activated CD4 T cells and type 2 T-helper cells. CCT8 played a vital role in the cell cycle and RNA transport of cancers, and it significantly inhibited the proliferation and migration of lung adenocarcinoma cells when it was knocked down. Conclusion: CCT8 plays an indispensable role in promoting the proliferation and migration of many cancers. CCT8 might be a biomarker of T-helper type 2 (Th2) cell infiltration and a promising therapeutic target for T-helper type 1(Th1)/Th2 imbalance.

An Integrated Analysis of Prognostic Signature and Immune Microenvironment in Tongue Squamous Cell Carcinoma.

Tongue squamous cell carcinoma (TSCC) is a prevalent cancer of the oral cavity. Survival metrics are usually unsatisfactory, even using combined treatment with surgery, radiation, and chemotherapy. Immune checkpoint inhibitors can prolong survival, especially in patients with recurrent or metastatic disease. However, there are few effective biomarkers to provide prognosis and guide immunotherapy. Here, we utilized weighted gene co-expression network analysis to identify the co-expression module and selected the turquoise module for further scrutiny. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses revealed the innate pathways. The findings indicated that cell junction organization, response to topologically incorrect protein, and regulation of cell adhesion pathways may be essential. Eleven crucial predictive genes (PLXNB1, N4BP3, KDELR2, INTS8, PLAU, PPFIBP2, OAF, LMF1, IL34, ZFP3, and MAP7D3) were used to establish a risk model based on Cox and LASSO analyses of The Cancer Genome Atlas and GSE65858 databases (regarding overall survival). Kaplan-Meier analysis and receiver operating characteristic curve suggested that the risk model had better prognostic effectiveness than other clinical traits. Consensus clustering was used to classify TSCC samples into two groups with significantly different survival rates. ESTIMATE and CIBERSORT were used to display the immune landscape of TSCC and indicate the stromal score; specific types of immune cells, including naïve B cells, plasma cells, CD8 T cells, CD4 memory resting and memory activated T cells, follicular helper T cells, and T regulatory cells, may influence the heterogeneous immune microenvironment in TSCC. To further identify hub genes, we downloaded GEO datasets (GSE41613 and GSE31056) and successfully validated the risk model. Two hub genes (PLAU and PPFIBP2) were strongly associated with CD4+ and CD8+ T cells and programmed cell death protein 1 (PD1) and PD-ligand 1.

Comprehensive development and validation of gene signature for predicting survival in patients with glioblastoma.

Glioblastoma (GBM) is the most common brain tumor, with rapid proliferation and fatal invasiveness. Large-scale genetic and epigenetic profiling studies have identified targets among molecular subgroups, yet agents developed against these targets have failed in late clinical development. We obtained the genomic and clinical data of GBM patients from the Chinese Glioma Genome Atlas (CGGA) and performed the least absolute shrinkage and selection operator (LASSO) Cox analysis to establish a risk model incorporating 17 genes in the CGGA693 RNA-seq cohort. This risk model was successfully validated using the CGGA325 validation set. Based on Cox regression analysis, this risk model may be an independent indicator of clinical efficacy. We also developed a survival nomogram prediction model that combines the clinical features of OS. To determine the novel classification based on the risk model, we classified the patients into two clusters using ConsensusClusterPlus, and evaluated the tumor immune environment with ESTIMATE and CIBERSORT. We also constructed clinical traits-related and co-expression modules through WGCNA analysis. We identified eight genes (ANKRD20A4, CLOCK, CNTRL, ICA1, LARP4B, RASA2, RPS6, and SET) in the blue module and three genes (MSH2, ZBTB34, and DDX31) in the turquoise module. Based on the public website TCGA, two biomarkers were significantly associated with poorer OS. Finally, through GSCALite, we re-evaluated the prognostic value of the essential biomarkers and verified MSH2 as a hub biomarker.

Identification of novel subtypes based on ssGSEA in immune-related prognostic signature for tongue squamous cell carcinoma.

BACKGROUND: Tongue squamous cell carcinoma (TSCC) is characterized by aggressive invasion and poor prognosis. Currently, immune checkpoint inhibitors may prolong overall survival compared with conventional treatments. However, PD1/PDL1 remain inapplicable in predicting the prognosis of TSCC; thus, it is urgent to explore the genetic characteristics of TSCC. MATERIALS AND METHODS: We utilized single-sample gene set enrichment analysis (ssGSEA) to classify TSCC patients from the TCGA database into clusters with different immune cell infiltrations. ESTIMATE (immune-related scores) and CIBERSORT (immune cell distribution) analyses were used to evaluate the immune landscape among clusters. GO, KEGG, and GSEA analyses were performed to analyze the different underlying molecular mechanisms in the clusters. Based on the immune characteristics, we applied the LASSO Cox regression to select hub genes and construct a prognostic risk model. Finally, we established an interactive network among these hub genes by using Cytoscape, and a pan-cancer analysis to further verify and decipher the innate function of these genes. RESULTS: Using ssGSEA, we constructed three functional clusters with different overall survival and immune-cell infiltration. ESTIMATE and CIBERSORT analyses revealed the different distributions of immune cells (T cells, B cells, and macrophages) with diverse immune-related scores (ESTIMATE, immune, stromal, and tumor purity scores). Moreover, pathways including those of the interferon-gamma response, hypoxia, and glycolysis of the different subtypes were investigated to elucidate their involvement in mediating the heterogeneous immune characteristics. Subsequently, after LASSO Cox regression, a signature of 15 immune-related genes was established that is more prognostically effective than the TNM stage. Furthermore, three hub genes-PGK1, GPI, and RPE-were selected using Cytoscape evaluation and verified by immunohistochemistry. PGK1, the foremost regulator, was a comprehensively profiled pan-cancer, and a PGK1-based interactive network was established. CONCLUSION: Our results suggest that immune-related genes and clusters in TSCC have the potential to guide individualized treatments.

Analysis of Autophagy-Related Signatures Identified Two Distinct Subtypes for Evaluating the Tumor Immune Microenvironment and Predicting Prognosis in Ovarian Cancer.

Ovarian cancer (OC) is one of the most lethal gynecologic malignant tumors. The interaction between autophagy and the tumor immune microenvironment has clinical importance. Hence, it is necessary to explore reliable biomarkers associated with autophagy-related genes (ARGs) for risk stratification in OC. Here, we obtained ARGs from the MSigDB database and downloaded the expression profile of OC from TCGA database. The k-means unsupervised clustering method was used for clustering, and two subclasses of OC (cluster A and cluster B) were identified. SsGSEA method was used to quantify the levels of infiltration of 24 subtypes of immune cells. Metascape and GSEA were performed to reveal the differential gene enrichment in signaling pathways and cellular processes of the subtypes. We found that patients in cluster A were significantly associated with higher immune infiltration and immune-associated signaling pathways. Then, we established a risk model by LASSO Cox regression. ROC analysis and Kaplan-Meier analysis were applied for evaluating the efficiency of the risk signature, patients with low-risk got better outcomes than those with high-risk in overall survival. Finally, ULK2 and GABARAPL1 expression was further validated in clinical samples. In conclusion, Our study constructed an autophagy-related prognostic indicator, and identified two promising targets in OC.

Analysis of Tumor Microenvironment Characteristics in Bladder Cancer: Implications for Immune Checkpoint Inhibitor Therapy.

The tumor microenvironment (TME) plays a crucial role in cancer progression and recent evidence has clarified its clinical significance in predicting outcomes and efficacy. However, there are no studies on the systematic analysis of TME characteristics in bladder cancer. In this study, we comprehensively evaluated the TME invasion pattern of bladder cancer in 1,889 patients, defined three different TME phenotypes, and found that different subtypes were associated with the clinical prognosis and pathological characteristics of bladder cancer. We further explored the signaling pathways, cancer-immunity cycle, copy number, and somatic mutation differences among the different subtypes and used the principal component analysis algorithm to calculate the immune cell (IC) score, a tool for comprehensive evaluation of TME. Univariate and multivariate Cox regression analyses showed that ICscore is a reliable and independent prognostic biomarker. In addition, the use of anti-programmed death-ligand (PD-L1) treatment cohort, receiver operating characteristic (ROC) curve, Tumor Immune Dysfunction and Exclusion (TIDE), Subnetwork Mappings in Alignment of Pathways (SubMAP), and other algorithms confirmed that ICscore is a reliable prognostic biomarker for immune checkpoint inhibitor response. Patients with higher ICscore showed a significant therapeutic advantage in immunotherapy. In conclusion, this study improves our understanding of the characteristics of TME infiltration in bladder cancer and provides guidance for more effective personalized immunotherapy strategies.

LINC00467 Promotes Tumor Progression via Regulation of the NF-kb Signal Axis in Bladder Cancer.

PURPOSE: Long non-coding RNAs (lncRNAs) play an important role in the occurrence and development of bladder cancer, but the underlying molecular mechanisms remain largely unknown. In this study, we found that LINC00467 was significantly highly expressed in bladder cancer through bioinformatic analysis. The present study aimed to explore the role of LINC00467 in bladder cancer and its possible underlying molecular mechanisms. METHODS: The expression of LINC00467 was obtained from GEO (GSE31189), the TCGA database, and qRT-PCR. The role of LINC00467 in bladder cancer was assessed both in vitro and in vivo. RIP, RNA pulldown, and CO-IP were used to demonstrate the potential mechanism by which LINC00467 regulates the progression of bladder cancer. RESULTS: Through the analysis of GEO (GSE133624) and the TCGA database, it was found that LINC00467 was highly expressed in bladder cancer tissues and that the expression of LINC00467 was significantly negatively correlated with patient prognosis. Cell and animal experiments suggest that LINC00467 promotes the proliferation and invasion of bladder cancer cells. On the one hand, LINC00467 can directly bind to NF-kb-p65 mRNA to stabilize its expression. On the other hand, LINC00467 can directly bind to NF-kb-p65 to promote its translocation into the nucleus to activate the NF-κB signaling pathway, which promotes the progression of bladder cancer. CONCLUSIONS: LINC00467 is highly expressed in bladder cancer and can promote the progression of bladder cancer by regulating the NF-κB signaling pathway. Therefore, targeting LINC00467 is very likely to provide a new strategy for the treatment of bladder cancer and for improving patient prognosis.

Analysis of Ferroptosis-Mediated Modification Patterns and Tumor Immune Microenvironment Characterization in Uveal Melanoma.

Uveal melanoma (UVM) is an intraocular malignancy in adults in which approximately 50% of patients develop metastatic disease and have a poor prognosis. The need for immunotherapies has rapidly emerged, and recent research has yielded impressive results. Emerging evidence has implicated ferroptosis as a novel type of cell death that may mediate tumor-infiltrating immune cells to influence anticancer immunity. In this study, we first selected 11 ferroptosis regulators in UVM samples from the training set (TCGA and GSE84976 databases) by Cox analysis. We then divided these molecules into modules A and B based on the STRING database and used consensus clustering analysis to classify genes in both modules. According to the Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA), the results revealed that the clusters in module A were remarkably related to immune-related pathways. Next, we applied the ESTIMATE and CIBERSORT algorithms and found that these ferroptosis-related patterns may affect a proportion of TME infiltrating cells, thereby mediating the tumor immune environment. Additionally, to further develop the prognostic signatures based on the immune landscape, we established a six-gene-regulator prognostic model in the training set and successfully verified it in the validation set (GSE44295 and GSE27831). Subsequently, we identified the key molecules, including ABCC1, CHAC1, and GSS, which were associated with poor overall survival, progression-free survival, disease-specific survival, and progression-free interval. We constructed a competing endogenous RNA network to further elucidate the mechanisms, which consisted of 29 lncRNAs, 12 miRNAs, and 25 ferroptosis-related mRNAs. Our findings indicate that the ferroptosis-related genes may be suitable potential biomarkers to provide novel insights into UVM prognosis and decipher the underlying mechanisms in tumor microenvironment characterization.

Analysis of m6A-Related Signatures in the Tumor Immune Microenvironment and Identification of Clinical Prognostic Regulators in Adrenocortical Carcinoma.

Adrenocortical carcinoma (ACC) is a rare endocrine malignancy with a high rate of mortality and recurrence. N6-methyladenosine methylation (m6A) is the most common modification to affect cancer development, but to date, the potential role of m6A regulators in ACC prognosis is not well understood. In this study, we systematically analyzed 21 m6A regulators in ACC samples from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) database. We identified three m6A modification patterns with different clinical outcomes and discovered a significant relationship between diverse m6A clusters and the tumor immune microenvironment (immune cell types and ESTIMATE algorithm). Additionally, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA) revealed that the m6A clusters were strongly associated with immune infiltration in the ACC. Next, to further explore the m6A prognostic signatures in ACC, we implemented Lasso (Least Absolute Shrinkage and Selection Operator) Cox regression to establish an eight-m6A-regulator prognostic model in the TCGA dataset, and the results showed that the model-based high-risk group was closely correlated with poor overall survival (OS) compared with the low-risk group. Subsequently, we validated the key modifications in the GEO datasets and found that high HNRNPA2B1 expression resulted in poor OS and event-free survival (EFS) in ACC. Moreover, to further decipher the molecular mechanisms, we constructed a competing endogenous RNA (ceRNA) network based on HNRNPA2B1, which consists of 12 long noncoding RNAs (lncRNAs) and 1 microRNA (miRNA). In conclusion, our findings indicate the potential role of m6A modification in ACC, providing novel insights into ACC prognosis and guiding effective immunotherapy.