Clinical Significance of the Thioredoxin System and Thioredoxin-Domain-Containing Protein Family in Hepatocellular Carcinoma

Deciphering the underlying mechanisms of the oxidative perturbations and impaired meat quality in Wooden breast myopathy by label-free quantitative MS-based proteomics

The study aimed to investigate biochemical mechanisms occurred in Wooden breast (WB) chicken meat, with attention to the impact on meat quality. Commercial chicken breasts were classified as Normal (N, n = 12), WB-M (moderate degree; focal hardness on cranial region, n = 12) and WB-S (severe degree; extreme and diffused hardness over the entire surface, n = 12). Samples were analyzed for physico-chemical properties, oxidative damage to lipids and proteins, and discriminating sarcoplasmic proteins by using a Q-Exactive mass spectrometer. WB meat presented impaired composition and functionality and higher levels of lipid and protein oxidation markers than N meat. The proteomic profile of WB-S presents a dynamic regulation of the relevant proteins involved in redox homeostasis, carbohydrate, protein and lipid metabolisms. Proteomics results demonstrate that the physiological and metabolic processes of muscles affected by WB myopathy are involved in combating the inflammatory process and in repairing the damaged tissue by oxidative stress.

A novel inflammasome-related gene nomogram predicts survival in hepatocellular carcinoma

Inflammasomes are closely associated with the progression of multiple cancers. We established an inflammasome-related gene (IRG)-based model to predict the survival of patients with hepatocellular carcinoma (HCC). The RNA-sequencing data and clinical information of HCC patients were downloaded from the cancer genome atlas-liver hepatocellular carcinoma database, and the differentially expressed inflammasome-related gene were screened. Seven prognostic differentially expressed inflammasome-related genes were identified by univariate Cox analysis and incorporated into the risk model using least absolute shrinkage and selection operator-Cox algorithm. The predictive accuracy of the risk model was evaluated through the Kaplan-Meier, receiver operating characteristic and Cox regression analyses. The performance of the model was verified in the International Cancer Genome Consortium-Liver Cancer - RIKEN, JP cohort. A nomogram was constructed to predict the 1-, 2-, 3- ,and 5-year survival of HCC patients, and its performance was evaluated using calibration curves. The significantly enriched gene ontology terms, Kyoto encyclopedia of genes and genomes pathways and infiltrating immune cell populations associated with the IRG model were also analyzed to explore of the potential molecular mechanisms and immunotherapeutic targets. An independent and highly accurate prognostic model consisting of 7 IRGs was established and verified in 2 independent HCC cohorts. The IRG model was significantly associated with cell division and cell cycle. In addition, the high-risk group was more likely to have greater infiltration of immune cells and higher expression of immune checkpoint-related genes compared to the low-risk group. An IRG-based model was established to predict 1-, 2-, 3-, and 5-year survival rate in individual HCC patients, which provides new insights into the role of inflammasomes in HCC.

Identification of thioredoxin domain containing family members' expression pattern and prognostic value in diffuse gliomas via in silico analysis

BACKGROUND

Gliomas are the most prevalent primary tumors of the central nervous system. Their aggressive nature and the obstacles arising during therapy highlights the importance of finding new prognostic markers and therapy targets for gliomas. TXNDC genes are members of the thioredoxin superfamily and were shown to play a role in redox homeostasis, protein folding, electron transfer and also acting as cellular adapters. The well known contribution of these processes in cancer progression prompted us to investigate if TXNDC family members may also play a role in carcinogenesis, in particular diffuse gliomas.

METHODS

The present study used in silico analysis tools GEPIA, UCSC Xena, Gliovis, cBioPortal, and Ivy GAP to evaluate the expression pattern, prognostic value and clinical significance of TXNDC family members in diffuse gliomas.

RESULTS

Our analysis showed that TXNDC family members' expression pattern differ between tumors and healthy tissues and among tumors with different grades. The detailed analysis of TXNDC5 in glioma pathogenesis revealed that TXNDC5 expression is associated with more aggressive clinical and molecular features and poor therapy success both in LGG and GBM samples. Kaplan-Meier survival curves represented a worse prognosis for patients with leveated TXNDC5 levels in LGG and all grade glioma patients. The levels of TXNDC5 was shown to be possibly regulated by hypoxia-ER stress axis and a potential mechanism for TXNDC5-driven glioma progression was found to be extracellular matrix (ECM) production which is known to promote tumor aggressiveness.

CONCLUSIONS

Our results uncovered the previously unknown role of TXNDC family members in glioma pathogenesis and showed that TXNDC5 levels could serve as a predictor of clinical outcome and therapy success and may very well be used for targeted therapy.

Deciphering a mitochondria-related signature to supervise prognosis and immunotherapy in hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC) is a major public health problem in humans. The imbalance of mitochondrial function has been discovered to be closely related to the development of cancer recently. However, the role of mitochondrial-related genes in HCC remains unclear.

Methods

The RNA-sequencing profiles and patient information of 365 samples were derived from the Cancer Genome Atlas (TCGA) dataset. The mitochondria-related prognostic model was established by univariate Cox regression analysis and LASSO Cox regression analysis. We further determined the differences in immunity and drug sensitivity between low- and high-risk groups. Validation data were obtained from the International Cancer Genome Consortium (ICGC) dataset of patients with HCC. The protein and mRNA expression of six mitochondria-related genes in tissues and cell lines was verified by immunohistochemistry and qRT-PCR.

Results

The six mitochondria-related gene signature was constructed for better prognosis forecasting and immunity, based on which patients were divided into high-risk and low-risk groups. The ROC curve, nomogram, and calibration curve exhibited admirable clinical predictive performance of the model. The risk score was associated with clinicopathological characteristics and proved to be an independent prognostic factor in patients with HCC. The above results were verified in the ICGC validation cohort. Compared with normal tissues and cell lines, the protein and mRNA expression of six mitochondria-related genes was upregulated in HCC tissues and cell lines.

Conclusion

The signature could be an independent factor that supervises the immunotherapy response of HCC patients and possess vital guidance value for clinical diagnosis and treatment.

USF2-mediated upregulation of TXNRD1 contributes to hepatocellular carcinoma progression by activating Akt/mTOR signaling

Thioredoxin reductase 1 (TXNRD1) is one of the major redox regulators in mammalian cells, which has been reported to be involved in tumorigenesis. However, its roles and regulatory mechanism underlying the progression of HCC remains poorly understood. In this study, we demonstrated that TXNRD1 was significantly upregulated in HCC tumor tissues and correlated with poor survival in HCC patients. Functional studies indicated TXNRD1 knockdown substantially suppressed HCC cell proliferation and metastasis both in vitro and in vivo, and its overexpression showed opposite effects. Mechanistically, TXNRD1 attenuated the interaction between Trx1 and PTEN which resulting in acceleration of PTEN degradation, thereby activated Akt/mTOR signaling and its target genes which conferred to elevated HCC cell mobility and metastasis. Moreover, USF2 was identified as a transcriptional suppressor of TXNRD1, which directly interacted with two E-box sites in TXNRD1 promoter. USF2 functioned as tumor suppressor through the downstream repression of TXNRD1. Further clinical data revealed negative co-expression correlations between USF2 and TXNRD1. In conclusion, our findings reveal that USF2-mediated upregulation of TXNRD1 contributes to hepatocellular carcinoma progression by activating Akt/mTOR signaling.

High expression of TXNDC11 indicated unfavorable prognosis of glioma

Background

Thioredoxin domain containing 11 (TXNDC11) has been implicated in numerous cancers. Nevertheless, the function of TXNDC11 in glioma is not well described. This study aimed to assess clinical significance of TXNDC11 in glioma based on bioinformatics analysis and immunohistochemical (IHC) staining.

Methods

GEPIA2, The Cancer Genome Atlas (TCGA), and Gene Expression Omnibus (GEO) databases were employed to detect the levels of TXNDC11 transcript in glioma. Gene expression profiles and data from the methylation chip with clinical details from TCGA and Chinese Glioma Genome Atlas (CGGA) of glioma samples were examined. The methylation of TXNDC11 in glioma was evaluated by 450K methylation chip data analysis. The pathways involved in TXNDC11 expression were screened by gene set enrichment analysis (GSEA). The correlation between TXNDC11 and immune cells was analyzed. Protein level of TXNDC11 was detected by IHC staining in glioma specimens.

Results

TXNDC11 was highly expressed in glioma, and high TXNDC11 expression was associated with poor overall survival (OS) and worse clinical prognostic variables. The methylation of cg04399632 was statistically different between glioma samples and normal samples, and was negatively correlated with TXNDC11 expression in glioma patients. Survival analysis demonstrated a poorer prognosis in glioma patients with cg04399632 hypomethylation. TXNDC11-high phenotype was associated with certain immune-related pathways and other signaling pathways in glioma. The expression of TXNDC11 was correlated positively with M2 macrophage infiltration and negatively with M0 and M1 macrophage infiltration. IHC staining confirmed that TXNDC11 expression increased in higher-grade glioma.

Conclusions

High expression of TXNDC11 may predict unfavorable prognosis of glioma patients.

AccPDIA6 from Apis cerana cerana plays important roles in antioxidation

PDIA6 is a member of the protein disulfide isomerase (PDI) family, shows disulfide isomerase activity and oxidoreductase activity, and can act as a molecular chaperone. Its biological functions include modulating apoptosis, regulating the proliferation and invasion of cancer cells, supporting thrombosis and modulating insulin secretion. However, the roles of PDIA6 in Apis cerana cerana are poorly understood. Herein, we obtained the PDIA6 gene from A. cerana cerana (AccPDIA6). We investigated the expression patterns of AccPDIA6 in response to oxidative stress induced by H₂O₂, UV, HgCl₂, extreme temperatures (4 °C, 42 °C) and pesticides (thiamethoxam and hexythiazox) and found that AccPDIA6 was upregulated by these treatments. Western blot analysis indicated that AccPDIA6 was also upregulated by oxidative stress at the protein level. In addition, a survival test demonstrated that the survival rate of E. coli cells expressing AccPDIA6 increased under oxidative stress, suggesting a possible antioxidant function of AccPDIA6. In addition, we tested the transcripts of other antioxidant genes and found that some of them were downregulated in AccPDIA6 knockdown samples. It was also discovered that the antioxidant enzymatic activity of superoxide dismutase (SOD) decreased in AccPDIA6-silenced bees. Moreover, the survival rate of AccPDIA6 knockdown bees decreased under oxidative stress, implying that AccPDIA6 may function in the oxidative stress response by enhancing the viability of honeybees. Taken together, these results indicated that AccPDIA6 may play an essential role in counteracting oxidative stress.

Development and Validation of a Metabolic-related Prognostic Model for Hepatocellular Carcinoma

BACKGROUND AND AIMS

Growing evidence suggests that metabolic-related genes have a significant impact on the occurrence and development of hepatocellular carcinoma (HCC). However, the prognostic value of metabolic-related genes for HCC has not been fully revealed.

METHODS

mRNA sequencing and clinical data were obtained from The Cancer Genome Atlas and the GTEx Genotype-Tissue Expression comprehensive database. Differentially expressed metabolic-related genes in tumor tissues (n=374) and normal tissues (n=160) were identified by the Wilcoxon test. Time-dependent receiver operating characteristic curve analysis, univariate multivariate Cox regression analysis and Kaplan-Meier survival analysis were used to evaluate the predictive effectiveness and independence of the prognostic model. Two independent cohorts (International Cancer Genome Consortiums and GSE14520) were applied to verify the prognostic model.

RESULTS

Our study included a total of 793 patients with HCC. We constructed a risk score consisting of five metabolic-genes (BDH1, RRM2, CYP2C9, PLA2G7, and TXNRD1). For the overall survival rate, the low-risk group had a considerably higher rate than the high-risk group. Univariate and multivariate Cox regression analyses indicated that the risk score was an independent predictor for the prognosis of HCC.

CONCLUSIONS

We constructed and validated a novel prognostic model, which may provide support for the precise treatment of HCC.

The role of functional polymorphisms in oxidative stress-related genes on early-stage breast cancer survival

BACKGROUND

Genetic variations in oxidative stress-related genes may alter the coded protein level and impact the pathogenesis of breast cancer.

METHODS

The current study investigated the associations of functional single nucleotide polymorphisms in the NFE2L2, HMOX1, P21, TXNRD2, and ATF3 genes with the early-stage breast cancer clinicopathological characteristics and disease-free survival, metastasis-free survival, and overall survival. A total of 202 Eastern European (Lithuanian) women with primary I-II stage breast cancer were involved. Genotyping of the single nucleotide polymorphisms was performed using TaqMan single nucleotide polymorphisms genotyping assays.

RESULTS

The CA+AA genotypes of P21 rs1801270 were significantly less frequent in patients with lymph node metastasis and larger tumor size (P=0.041 and P=0.022, respectively). The TT genotype in ATF3 rs3125289 had significantly lower risk of estrogen receptor (ER), progesterone receptor (PR) negative, and human epidermal growth factor receptor 2 (HER2) positive status (P=0.023, P=0.046, and P=0.040, respectively). In both, univariate and multivariate Cox analysis, TXNRD2 rs1139793 GG genotype vs. GA+AA was a negative prognostic factor for disease-free survival (multivariate hazard ratio (HR) 2.248; P=0.025) and overall survival (multivariate HR 2.248; P=0.029). The ATF3 rs11119982 CC genotype in the genotype model was a negative prognostic factor for disease-free survival (multivariate HR 5.878; P=0.006), metastasis-free survival (multivariate HR 4.759; P=0.018), and overall survival (multivariate HR 3.280; P=0.048).

CONCLUSION

Our findings suggest that P21 rs1801270 is associated with lymph node metastasis and larger tumor size, and ATF3 rs3125289 is associated with ER, PR, and HER2 status. Two potential, novel, early-stage breast cancer survival biomarkers, TXNRD2 rs1139793 and ATF3 rs11119982, were detected. Further investigations are needed to confirm the results of the current study.

Establishment of a Genomic-Clinicopathologic Nomogram for Predicting Early Recurrence of Hepatocellular Carcinoma After R0 Resection

BACKGROUND

A high rate of postoperative recurrence, especially early recurrence (ER) occurring within 1 year, seriously impedes patients with hepatocellular carcinoma (HCC) from achieving long-term survival. This study aimed to establish a genomic-clinicopathologic nomogram for precisely predicting ER in HCC patients after R0 resection.

METHODS

Two reliable datasets from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases were selected as the training and validation cohorts, respectively. The prognostic genes related to ER were screened out by univariate Cox regression analysis and differential expression analysis. The gene-based prognostic index was constructed using LASSO and Cox regression analyses, and its independent prognostic value was assessed by Kaplan-Meier and multivariate Cox analyses. Gene set enrichment analysis (GSEA) was performed to explore the biological pathways related to the prognostic index. Finally, the nomogram integrating all the independent prognostic factors was established and comprehensively evaluated by calibration plots, the C-index, receiver operating characteristic curves, and decision curve analysis.

RESULTS

Nine dysregulated and prognostic genes related to ER (ZNF131, TATDN2, TXN, DDX55, KPNA2, ZNF30, TIMELESS, SFRP1, and COLEC11) were identified (all P < 0.05). The prognostic index model based on the 9 genes was successfully constructed using the TCGA cohort and showed a certain capability to discriminate the ER group from the non-ER group (P < 0.05) and good independent prognostic value in terms of predicting poor early recurrence-free survival (P < 0.05). Eight biological pathways significantly related to ER were identified by GSEA, such as "cell cycle", "homologous recombination" and "p53 signaling pathway." The genomic-clinicopathologic nomogram integrating the 9-gene-based prognostic index and TNM stage displayed significantly higher predictive accuracy and clinical application value than that of TNM stage model both in the training and validation cohorts (all P < 0.05).

CONCLUSIONS

The novel genomic-clinicopathologic nomogram may be a convenient and powerful tool for accurately predicting ER in HCC patients after R0 resection.

Long non-coding RNA Gm15441 attenuates hepatic inflammasome activation in response to PPARA agonism and fasting

Exploring the molecular mechanisms that prevent inflammation during caloric restriction may yield promising therapeutic targets. During fasting, activation of the nuclear receptor peroxisome proliferator-activated receptor α (PPARα) promotes the utilization of lipids as an energy source. Herein, we show that ligand activation of PPARα directly upregulates the long non-coding RNA gene Gm15441 through PPARα binding sites within its promoter. Gm15441 expression suppresses its antisense transcript, encoding thioredoxin interacting protein (TXNIP). This, in turn, decreases TXNIP-stimulated NLR family pyrin domain containing 3 (NLRP3) inflammasome activation, caspase-1 (CASP1) cleavage, and proinflammatory interleukin 1β (IL1B) maturation. Gm15441-null mice were developed and shown to be more susceptible to NLRP3 inflammasome activation and to exhibit elevated CASP1 and IL1B cleavage in response to PPARα agonism and fasting. These findings provide evidence for a mechanism by which PPARα attenuates hepatic inflammasome activation in response to metabolic stress through induction of lncRNA Gm15441.

Comprehensive analysis reveals a metabolic ten-gene signature in hepatocellular carcinoma

Background

Due to the complicated molecular and cellular heterogeneity in hepatocellular carcinoma (HCC), the morbidity and mortality still remains high level in the world. However, the number of novel metabolic biomarkers and prognostic models could be applied to predict the survival of HCC patients is still small. In this study, we constructed a metabolic gene signature by systematically analyzing the data from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO) and International Cancer Genome Consortium (ICGC).

Methods

Differentially expressed genes (DEGs) between tumors and paired non-tumor samples of 50 patients from TCGA dataset were calculated for subsequent analysis. Univariate cox proportional hazard regression and LASSO analysis were performed to construct a gene signature. The Kaplan–Meier analysis, time-dependent receiver operating characteristic (ROC), Univariate and Multivariate Cox regression analysis, stratification analysis were used to assess the prognostic value of the gene signature. Furthermore, the reliability and validity were validated in four types of testing cohorts. Moreover, the diagnostic capability of the gene signature was investigated to further explore the clinical significance. Finally, Go enrichment analysis and Gene Set Enrichment Analysis (GSEA) have been performed to reveal the different biological processes and signaling pathways which were active in high risk or low risk group.

Results

Ten prognostic genes were identified and a gene signature were constructed to predict overall survival (OS). The gene signature has demonstrated an excellent ability for predicting survival prognosis. Univariate and Multivariate analysis revealed the gene signature was an independent prognostic factor. Furthermore, stratification analysis indicated the model was a clinically and statistically significant for all subgroups. Moreover, the gene signature demonstrated a high diagnostic capability in differentiating normal tissue and HCC. Finally, several significant biological processes and pathways have been identified to provide new insights into the development of HCC.

Conclusion

The study have identified ten metabolic prognostic genes and developed a prognostic gene signature to provide more powerful prognostic information and improve the survival prediction for HCC.

Piperlongumine, a Novel TrxR1 Inhibitor, Induces Apoptosis in Hepatocellular Carcinoma Cells by ROS-Mediated ER Stress

Hepatocellular carcinoma (HCC) is the sixth most common cancer and the third leading cause of cancer-related deaths globally. Despite advances in diagnosis and treatment, the incidence and mortality of HCC continue to rise. Piperlongumine (PL), an alkaloid isolated from the fruit of the long pepper, is known to selectively kill tumor tissues while sparing their normal counterparts. However, the killing effects of PL on HCC and the underlying mechanism of PL are not clear. We report that PL may interact with thioredoxin reductase 1 (TrxR1), an important selenocysteine (Sec)-containing antioxidant enzyme, and induce reactive oxygen species (ROS)-mediated apoptosis in HCC cells. Our results suggest that PL induces a lethal endoplasmic reticulum (ER) stress response in HCC cells by targeting TrxR1 and increasing intracellular ROS levels. Notably, PL treatment reduces TrxR1 activity and tumor cell burden in vivo. Additionally, TrxR1 is significantly upregulated in existing HCC databases and available HCC clinical specimens. Taken together, these results suggest PL as a novel anticancer candidate for the treatment of HCC. More importantly, this study reveals that TrxR1 might be an effective target in treating HCC.

Modulation of ERQC and ERAD: A Broad-Spectrum Spanner in the Works of Cancer Cells?

Endoplasmic reticulum glycoprotein folding quality control (ERQC) and ER-associated degradation (ERAD) preside over cellular glycoprotein secretion and maintain steady glycoproteostasis. When cells turn malignant, cancer cell plasticity is affected and supported either by point mutations, preferential isoform selection, altered expression levels, or shifts to conformational equilibria of a secreted glycoprotein. Such changes are crucial in mediating altered extracellular signalling, metabolic behavior, and adhesion properties of cancer cells. It is therefore conceivable that interference with ERQC and/or ERAD can be used to selectively damage cancers. Indeed, inhibitors of the late stages of ERAD are already in the clinic against cancers such as multiple myeloma. Here, we review recent advances in our understanding of the complex relationship between glycoproteostasis and cancer biology and discuss the potential of ERQC and ERAD modulators for the selective targeting of cancer cell plasticity.

Identification of Prognostic Candidate Genes in Breast Cancer by Integrated Bioinformatic Analysis

Breast cancer is one of the most common malignancies. However, the molecular mechanisms underlying its pathogenesis remain to be elucidated. The present study aimed to identify the potential prognostic marker genes associated with the progression of breast cancer. Weighted gene coexpression network analysis was used to construct free-scale gene coexpression networks, evaluate the associations between the gene sets and clinical features, and identify candidate biomarkers. The gene expression profiles of GSE48213 were selected from the Gene Expression Omnibus database. RNA-seq data and clinical information on breast cancer from The Cancer Genome Atlas were used for validation. Four modules were identified from the gene coexpression network, one of which was found to be significantly associated with patient survival time. The expression status of 28 genes formed the black module (basal); 18 genes, dark red module (claudin-low); nine genes, brown module (luminal), and seven genes, midnight blue module (nonmalignant). These modules were clustered into two groups according to significant difference in survival time between the groups. Therefore, based on betweenness centrality, we identified TXN and ANXA2 in the nonmalignant module, TPM4 and LOXL2 in the luminal module, TPRN and ADCY6 in the claudin-low module, and TUBA1C and CMIP in the basal module as the genes with the highest betweenness, suggesting that they play a central role in information transfer in the network. In the present study, eight candidate biomarkers were identified for further basic and advanced understanding of the molecular pathogenesis of breast cancer by using co-expression network analysis.

miR-125b-5p inhibits cell proliferation, migration, and invasion in hepatocellular carcinoma via targeting TXNRD1

Background

Thioredoxin reductase 1 (TXNRD1) is an antioxidant enzyme reportedly overexpressed in hepatocellular carcinoma (HCC); however, the detailed function and mechanisms of TXNRD1 in HCC remain obscure. In this study, we investigated the miR-125b-5p-specific regulation of TXNRD1 levels and its effect on HCC cells.

Methods

We detected miR-125b-5p levels in human HCC tissue samples through quantitative reverse transcription polymerase chain reaction (qRT-PCR), and in vitro experiments were employed to investigate the effect of miR-125b-5p on HCC cell proliferation, migration, and invasion. Additionally, we examined miR-125b-5p-mediated changes in TXNRD1 levels by qRT-PCR and western blotting, and a dual luciferase-reporter assay was conducted to confirm direct targeting of the 3' untranslated region of TXNRD1 mRNA by miR-125b-5p.

Results

miR-125b-5p expression was reduced in HCC tissues relative to that in matched para-carcinoma tissues; this finding was verified in HCC cohorts from the Gene Expression Omnibus and The Cancer Genome Atlas. Additionally, low miR-125b-5p expression was associated with poor prognosis in HCC patients, and gene-set enrichment analysis indicated that miR-125b-5p levels were associated with HCC proliferation and metastasis. As predicted, overexpressing miR-125b-5p restrained the proliferation, migration, and invasion of Huh7 and SK-Hep-1 cells and forced expression of the miR-125b-5p-downregulated TXNRD1 mRNA and protein levels in HCC cells. Moreover, dual luciferase-reporter assays revealed that miR-125b-5p targets TXNRD1 to directly regulate its expression, whereas TXNRD1 overexpression abolishes the inhibitory effect of miR-125b-5p on HCC cell proliferation, migration, and invasion.

Conclusions

These results demonstrated miR-125b-5p as a tumor suppressor in HCC through its inhibition of TXNRD1, thereby suggesting it as a potential target for the clinical treatment of HCC.