LAT, HOXD3 and NFE2L3 identified as novel DNA methylation-driven genes and prognostic markers in human clear cell renal cell carcinoma by integrative bioinformatics approaches

The CNC-family transcription factor NRF3: A crucial therapeutic target for cancer treatment

The CNC-bZIP family member NRF3 (NFE2L3) has received limited attention since its discovery. However, recent research has gradually revealed its biological functions, such as involvement in the regulation of cell differentiation, lipid metabolism, and malignant cell proliferation. Under physiological conditions, NRF3 is anchored to the endoplasmic reticulum within the cytoplasm and is biologically inactive. Upon cellular exposure to microenvironmental stresses such as oxidative stress, NRF3 translocates to the nucleus, binds to DNA, and acts as a transcription factor by inducing or repressing the expression of various genes. In terms of tumor regulation, NRF3 exhibits a dual role. It can function as a tumor suppressor to prevent the malignant progression of tumor tissues, protecting the organism from harm. Conversely, current research indicates that NRF3 plays a tumor-promoting role in most tumor tissues. NRF3 enhances the proliferation, migration and invasion of tumor cells by regulating cell cycle-related proteins and enhancing proteasome assembly to degrade tumor suppressors. Studies correlating NRF3 expression with clinical tumor features have found that elevated NRF3 expression is often associated with poor prognoses in various cancers, with patients exhibiting higher NRF3 expression typically having lower survival rates. Several studies suggest that NRF3 could serve as a clinical diagnostic and prognostic marker for tumors. Finally, from the clinical perspective, exploring the feasibility of inhibiting NRF3 activity in tumor treatment provides new insights for the development of NRF3-targeted oncological therapies.

Bioinformatics screening of prognostic immune-related genes in renal clear cell carcinoma

This study aims to harness bioinformatics to identify prognostic immune-related genes in clear cell renal cell carcinoma (ccRCC), focusing particularly on LILRB3. It evaluates LILRB3's expression in ccRCC, its association with patient prognosis, and its potential as a biomarker for predicting survival, thereby providing a preliminary basis for the diagnosis of ccRCC. Utilizing The Cancer Genome Atlas (TCGA) datasets and an immune gene set, we sought immune-related genes with elevated expression in ccRCC. Seventy-two normal tissue samples and 531 ccRCC samples were analyzed, and differential genes were identified with a screening criterion of fold change (FC) > 2 and P value < 0.01. Survival analysis and receiver operating characteristic (ROC) curve analysis were employed to discover genes of prognostic and diagnostic relevance to ccRCC. Pearson correlation analysis with a cutoff of |r|≥ 0.5, facilitated by cBioPortal, assessed genes co-expressed with LILRB3. The DAVID online tool conducted functional and pathway enrichment analyses for LILRB3-coexpressed genes. The TIMER and TCIA databases were utilized to explore LILRB3's influence on immune infiltration in the tumor microenvironment and its relation to key immunological checkpoints. Screening the TCGA database revealed 3719 up-regulated differential genes in ccRCC, with 355 overlapping immune-related genes. Survival analysis of these 355 genes revealed 100 with significant survival impact. ROC curve analysis pinpointed the top 10 genes, including LILRB3, with the highest diagnostic efficiency. LILRB3 emerged as an independent risk factor from the Cox risk regression model. GO and KEGG analyses linked LILRB3 to various biological processes, including chemokine signaling pathways, immunological response, antigen processing and presentation, inflammatory response, T cell co-stimulation, and signal transduction. LILRB3 significantly affected ccRCC immune infiltration and correlated positively with several immunological checkpoints, such as PD-1, LAG3, IDO1, PD-L1, CTLA4, TIM3, TIGIT, and VISTA. LILRB3 shows higher expression levels in ccRCC than in normal tissues and correlates with poor patient prognosis. Its impactful role in the immune infiltration of the RCC microenvironment suggests that LILRB3 could serve as a novel target for ccRCC treatment and prognosis, underlining its diagnostic and prognostic significance.

New insight into the CNC-bZIP member, NFE2L3, in human diseases

Nuclear factor erythroid 2 (NF-E2)-related factor 3 (NFE2L3), a member of the CNC-bZIP subfamily and widely found in a variety of tissues, is an endoplasmic reticulum (ER) membrane-anchored transcription factor that can be released from the ER and moved into the nucleus to bind the promoter region to regulate a series of target genes involved in antioxidant, inflammatory responses, and cell cycle regulation in response to extracellular or intracellular stress. Recent research, particularly in the past 5 years, has shed light on NFE2L3's participation in diverse biological processes, including cell differentiation, inflammatory responses, lipid homeostasis, immune responses, and tumor growth. Notably, NFE2L3 has been identified as a key player in the development and prognosis of multiple cancers including colorectal cancer, thyroid cancer, breast cancer, hepatocellular carcinoma, gastric cancer, renal cancer, bladder cancer, esophageal squamous cell carcinoma, T cell lymphoblastic lymphoma, pancreatic cancer, and squamous cell carcinoma. Furthermore, research has linked NFE2L3 to other cancers such as lung adenocarcinoma, malignant pleural mesothelioma, ovarian cancer, glioblastoma multiforme, and laryngeal carcinoma, indicating its potential as a target for innovative cancer treatment approaches. Therefore, to gain a better understanding of the role of NFE2L3 in disease, this review offers insights into the discovery, structure, function, and recent advancements in the study of NFE2L3 to lay the groundwork for the development of NFE2L3-targeted cancer therapies.

A Prognostic Methylation-Driven Two-Gene Signature in Medulloblastoma

Medulloblastoma (MB) is one of the most common pediatric brain tumors and it is estimated that one-third of patients will not achieve long-term survival. Conventional prognostic parameters have limited and unreliable correlations with MB outcome, presenting a major challenge for patients' clinical improvement. Acknowledging this issue, our aim was to build a gene signature and evaluate its potential as a new prognostic model for patients with the disease. In this study, we used six datasets totaling 1679 samples including RNA gene expression and DNA methylation data from primary MB as well as control samples from healthy cerebellum. We identified methylation-driven genes (MDGs) in MB, genes whose expression is correlated with their methylation. We employed LASSO regression, incorporating the MDGs as a parameter to develop the prognostic model. Through this approach, we derived a two-gene signature (GS-2) of candidate prognostic biomarkers for MB (CEMIP and NCBP3). Using a risk score model, we confirmed the GS-2 impact on overall survival (OS) with Kaplan-Meier analysis. We evaluated its robustness and accuracy with receiver operating characteristic curves predicting OS at 1, 3, and 5 years in multiple independent datasets. The GS-2 showed highly significant results as an independent prognostic biomarker compared to traditional MB markers. The methylation-regulated GS-2 risk score model can effectively classify patients with MB into high and low-risk, reinforcing the importance of this epigenetic modification in the disease. Such genes stand out as promising prognostic biomarkers with potential application for MB treatment.

Hypomethylation-Mediated Upregulation of NFE2L3 Promotes Malignant Phenotypes of Clear Cell Renal Cell Carcinoma Cells

This work aimed to study the effect of NFE2 like bZIP transcription factor 3 (NFE2L3) on clear cell renal cell carcinoma (ccRCC) cells and whether NFE2L3 expression was mediated by DNA methylation. Twenty-one ccRCC patients were collected. The gene methylation and expression data of TCGA-KIRC were accessed from TCGA. Candidate methylation driver genes were identified by "MethylMix" package, and finally, NFE2L3 was selected as the target gene. The methylation of NFE2L3 was assayed by Ms PCR and QMSP. mRNA level of NFE2L3 was analyzed by qRT-PCR. Protein level of NFE2L3 was measured by Western blot. Demethylation was performed with methylation inhibitor 5-Aza-2'-deoxycytidine (5-Aza-CdR). Proliferative, migratory, and invasive abilities of ccRCC cells were assayed via cell colony formation assay, scratch healing assay, and transwell assay, respectively. Analysis of TCGA database presented that DNA hypomethylation occurred in the NFE2L3 promoter region in ccRCC tissues. NFE2L3 was significantly upregulated in ccRCC tissues and cells. Its expression in cells treated with 5-Aza-CdR was proportional to the concentration of methylation inhibitor. In cell function experiments, overexpressing NFE2L3 or demethylation could stimulate proliferation, migration, and invasion abilities of ccRCC and normal cells. 5-Aza-CdR treatment rescued repressive impact of knockdown NFE2L3 on malignant phenotypes of ccRCC and normal cells. DNA hypomethylation could induce high expression of NFE2L3 and facilitate malignant phenotypes of ccRCC cells. These results may generate insights into ccRCC therapy.

Comprehensive analysis of single-cell and bulk RNA-sequencing data identifies B cell marker genes signature that predicts prognosis and analysis of immune checkpoints expression in head and neck squamous cell carcinoma

Recent studies have shown that B cells and the associated tertiary lymphoid structures (TLS) correlate with the response of patients to immune checkpoint inhibitors (ICIs) and predict overall survival (OS) in cancer patients. We screened 145 B cell marker genes (BCMG) by a comprehensive analysis of single-cell RNA-sequencing (scRNA-seq) data of head and neck squamous cell carcinoma (HNSC) from the Gene Expression Omnibus (GEO) database. The BCMG signature (BCMGS) was established using The Cancer Genome Atlas (TCGA) dataset of HNSC and verified in four independent datasets. The multivariate Cox regression analysis identified the signature as an independent prognostic factor. A prognostic nomogram was constructed with independent prognostic factors using the TCGA dataset. GO and KEGG analysis revealed the underlying signaling pathways related to this signature. Study of immune profiles showed that patients in the low-risk group presented discriminative immune-cell infiltrations. Furthermore, the low-risk group was featured by higher TCR and BCR diversity, which suggested that low-risk patients may be more sensitive to ICIs. Immunohistochemistry was performed, and we found that high expression of FTH1 was significantly correlated with poor OS (P = 0.025). The expression of TIM-3, LAG-3 and PD-1 was positively correlated and associated with better OS in HNSC. However, there was no statistically significant difference between PD-L1, PD-L2, CTLA-4, TIGIT and prognosis. The BCMGS was a promising prognostic biomarker in HNSC, which may help to interpret the responses to immunotherapy and provide a new perspective for future research on the treatment in HNSC.

A pan-cancer analysis of the role of HOXD1, HOXD3, and HOXD4 and validation in renal cell carcinoma

HOXD1, HOXD3, and HOXD4 are members of the HOXD genes family and are related to tumorigenesis of the tumor. However, whether HOXDs (1, 3, 4) have a crucial role across pan-cancer is still unknown. HOXD1, HOXD3, and HOXD4 expressions were analyzed using public databases in 33 types of tumors. The UCSC Xena website was carried out to investigate the relationship between the expression of genes and the progress of cancers. The biological functions of HOXD3 were tested by colony forming, transwell, wound healing, and xenograft assay in vitro and in vivo. GSEA was used to identify the associated cancer hallmarks with HOXDs expression. Immune cell infiltration analysis was applied to verify the immune cell infiltrations related to genes. The results showed HOXD1, HOXD3, and HOXD4 co-low expressed in BRCA, COAD, KICH, KIRC, KIRP, READ, and TGCT. In the KIRC, all of HOXDs expression was connected with tumor stage and histological grade. Upregulation of HOXDs was associated with improved OS, DSS, and PFI. Down-expression of HOXD3 induced cell proliferation, migration, and invasion in vivo and in vitro. In addition, HOXDs were connected with immune-activated hallmarks and cancer immune cell infiltrations. These findings demonstrated that HOXDs may be indicative biomarkers for the prognosis and immunotherapy in pan-cancer.

Identification and validation of a DNA methylation-driven gene-based prognostic model for clear cell renal cell carcinoma

BACKGROUND

Clear cell renal cell carcinoma (ccRCC) is a malignant tumor with heterogeneous morphology and poor prognosis. This study aimed to establish a DNA methylation (DNAm)-driven gene-based prognostic model for ccRCC.

METHODS

Reduced representation bisulfite sequencing (RRBS) was performed on the DNA extracts from ccRCC patients. We analyzed the RRBS data from 10 pairs of patient samples to screen the candidate CpG sites, then trained and validated an 18-CpG site model, and integrated the clinical characters to establish a Nomogram model for the prognosis or risk evaluation of ccRCC.

RESULTS

We identified 2261 DMRs in the promoter region. After DMR selection, 578 candidates were screened, and was correspondence with 408 CpG dinucleotides in the 450 K array. We collected the DNAm profiles of 478 ccRCC samples from TCGA dataset. Using the training set with 319 samples, a prognostic panel of 18 CpGs was determined by univariate Cox regression, LASSO regression, and multivariate Cox proportional hazards regression analyses. We constructed a prognostic model by combining the clinical signatures. In the test set (159 samples) and whole set (478 samples), the Kaplan-Meier plot showed significant differences; and the ROC curve and survival analyses showed AUC greater than 0.7. The Nomogram integrated with clinicopathological characters and methylation risk score had better performance, and the decision curve analyses also showed a beneficial effect.

CONCLUSIONS

This work provides insight into the role of hypermethylation in ccRCC. The targets identified might serve as biomarkers for early ccRCC diagnosis and prognosis biomarkers for ccRCC. We believe our findings have implications for better risk stratification and personalized management of this disease.

DNA methylation and cancer: transcriptional regulation, prognostic, and therapeutic perspective

DNA methylation is one among the major grounds of cancer progression which is characterized by the addition of a methyl group to the promoter region of the gene thereby causing gene silencing or increasing the probability of mutations; however, in bacteria, methylation is used as a defense mechanism where DNA protection is by addition of methyl groups making restriction enzymes unable to cleave. Hypermethylation and hypomethylation both pose as leading causes of oncogenesis; the former being more frequent which occurs at the CpG islands present in the promoter region of the genes, whereas the latter occurs globally in various genomic sequences. Reviewing methylation profiles would help in the detection and treatment of cancers. Demethylation is defined as preventing methyl group addition to the cytosine DNA base which could cause cancers in case of global hypomethylation, however, upon further investigation; it could be used as a therapeutic tool as well as for drug design in cancer treatment. In this review, we have studied the molecules that induce and enzymes (DNMTs) that bring about methylation as well as comprehend the correlation between methylation with transcription factors and various signaling pathways. DNA methylation has also been reviewed in terms of how it could serve as a prognostic marker and the various therapeutic drugs that have come into the market for reversing methylation opening an avenue toward curing cancers.

NFE2L3 as a Potential Functional Gene Regulating Immune Microenvironment in Human Kidney Cancer

With the increasing incidence and mortality of renal cancer, it is pressing to find new biomarkers and drug targets for diagnosis and treatment. However, as one negative upstream regulator of p53, the prognostic and immunological role of NFE2L3 in renal cancer is still barely known. We investigated the expression, prognostic value, and relevant pathways of NFE2L3 using the datasets from public databases, including The Cancer Genome Atlas Program (TCGA), Genotype-Tissue Expression (GTEx), Cancer Cell Line Encyclopedia (CCLE), and UALCAN. Furthermore, we analyzed the relationship between NFE2L3 expression and the immune microenvironment using distinct methods. We found that NFE2L3 was higher expressed in kidney renal clear cell carcinoma (KIRC) and kidney renal papillary cell carcinoma (KIRP) tissues than adjacent normal tissues. Additionally, we identified NFE2L3 as one survival-related factor for KIRC and KIRP. The enrichment analyses revealed that NFE2L3 was associated with a variety of immune-relevant pathways in KIRC and related to the infiltration ratios of 17 types of immune cells in KIRC patients. Ultimately, we demonstrated nine significantly enriched mutations, such as TP53 and MET, in NFE2L3-expression-changing groups. The elevated expression of NFE2L3 in renal cancerous tissues versus normal tissues is associated with poor outcomes in patients. Besides, NFE2L3 has a role in the regulation of the immune microenvironment in renal cancer patients. The findings of our study provide a potential prognostic biomarker and a new drug target for renal cancer.

Significance of HOXD transcription factors family in progression, migration and angiogenesis of cancer

The transcription factors (TFs) of the HOX family play significant roles during early embryonic development and cellular processes. They also play a key role in tumorigenesis as tumor oncogenes or suppressors. Furthermore, TFs of the HOXD geFIne cluster affect proliferation, migration, and invasion of tumors. Consequently, dysregulated activity of HOXD TFs has been linked to clinicopathological characteristics of cancer. HOXD TFs are regulated by non-coding RNAs and methylation of DNA on promoter and enhancer regions. In addition, HOXD genes modulate the biological function of cancer cells via the MEK and AKT signaling pathways, thus, making HOXD TFs, a suitable molecular marker for cancer prognosis and therapy. In this review, we summarized the roles of HOXD TFs in different cancers and highlighted its potential as a diagnostic and therapeutic target.

Multi-Omics Analysis of Molecular Characteristics and Carcinogenic Effect of NFE2L3 in Pan-Cancer

NFE2L3, also known as NFE2L3, is a nuclear transcription factor associated with the pathogenesis and progression of human tumors. To systematically and comprehensively investigate the role of NFE2L3 in tumors, a pan-cancer analysis was performed using multi-omics data, including gene expression analysis, diagnostic and prognostic analysis, epigenetic methylation analysis, gene alteration analysis, immune feature analysis, functional enrichment analysis, and tumor cell functional status analysis. Furthermore, the molecular mechanism of NFE2L3 in liver hepatocellular carcinoma (LIHC) was explored. The relationship between NFE2L3 expression and survival prognosis of patients with LIHC was analyzed and a nomogram prediction model was constructed. Our study showed that NFE2L3 expression was upregulated in most cancers, suggesting that NFE2L3 may play an important role in promoting cancer progression. NFE2L3 expression is closely related to DNA methylation, genetic alteration, immune signature, and tumor cell functional status in pan-cancers. Furthermore, NFE2L3 was demonstrated to be an independent risk factor for LIHC, and the nomogram model based on NFE2L3 expression had good prediction efficiency for the overall survival of patients with LIHC. In summary, our study indicated that NFE2L3 may be an important molecular biomarker for the diagnosis and prognosis of pan-cancer. NFE2L3 is expected to be a potential molecular target for the treatment of tumors.

A methylation-driven genes prognostic signature and the immune microenvironment in epithelial ovarian cancer

Aberrant gene methylation has been implicated in the development and progression of tumors. In this study, we aimed to identity methylation driven genes involved in epithelial ovarian cancer (EOC) to establish a prognostic signature for patients with EOC. We identified and verified 6 MDGs that are closely related to the prognosis of ovarian cancer. A prognostic risk score model and nomogram for predicting the prognosis of ovarian cancer were constructed based on the six MDGs. It can also effectively reflect the immune environment and immunotherapy response of ovarian cancer. These MDGs have great significance to the implementation of individualized treatment and disease monitoring of ovarian cancer patients.

NRF3 Decreases during Melanoma Carcinogenesis and Is an Independent Prognostic Marker in Melanoma

The prognostic significance of the major redox regulator, nuclear factor erythroid-2-related factor 2 (NRF2), is recognized in many cancers, but the role of NRF3 is not studied. Analysis from the Gene Expression Omnibus datasets showed that NRF3 mRNA levels increased from benign to dysplastic naevi (p = 0.04). We characterized the immunohistochemical expression of NRF3 in 81 naevi, 67 primary skin melanomas, and 51 lymph node metastases. The immunohistochemical expression of cytoplasmic NRF3 decreased from benign to dysplastic naevi (p < 0.001) and further to primary melanomas (p < 0.001). High cytoplasmic NRF3 protein expression in pigment cells of the primary melanomas associated with worse melanoma-specific survival in multivariate analysis, specifically in the subgroup of patients with the lymph node metastases at the time of diagnosis (hazard ratio 3.179; 95% confidence interval 1.065-9.493; p = 0.038). Intriguingly, we did not observe associations between NRF3 and the traditional prognostic factors such as Breslow thickness, ulceration, or stage. Together, this data represents the primary description about the role of NRF3 in pigment tumours that is worthy of further explorations.

Loss of NFE2L3 protects against inflammation-induced colorectal cancer through modulation of the tumor microenvironment

We investigated the role of the NFE2L3 transcription factor in inflammation-induced colorectal cancer. Our studies revealed that Nfe2l3^−/− mice exhibit significantly less inflammation in the colon, reduced tumor size and numbers, and skewed localization of tumors with a more pronounced decrease of tumors in the distal colon. CIBERSORT analysis of RNA-seq data from normal and tumor tissue predicted a reduction in mast cells in Nfe2l3^−/− animals, which was confirmed by toluidine blue staining. Concomitantly, the transcript levels of Il33 and Rab27a, both important regulators of mast cells, were reduced and increased, respectively, in the colorectal tumors of Nfe2l3^−/− mice. Furthermore, we validated NFE2L3 binding to the regulatory sequences of the IL33 and RAB27A loci in human colorectal carcinoma cells. Using digital spatial profiling, we found that Nfe2l3^−/− mice presented elevated FOXP3 and immune checkpoint markers CTLA4, TIM3, and LAG3, suggesting an increase in Treg counts. Staining for CD3 and FOXP3 confirmed a significant increase in immunosuppressive Tregs in the colon of Nfe2l3^−/− animals. Also, Human Microbiome Project (HMP2) data showed that NFE2L3 transcript levels are higher in the rectum of ulcerative colitis patients. The observed changes in the tumor microenvironment provide new insights into the molecular differences regarding colon cancer sidedness. This may be exploited for the treatment of early-onset colorectal cancer as this emerging subtype primarily displays distal/left-sided tumors.

Identification and Verification of Tumor Immune Microenvironment-Related Prognostic Genes in Kidney Renal Clear Cell Carcinoma

Background

The tumor immune microenvironment is vital to kidney renal clear cell carcinoma (KIRC) progression, and immunotherapies have been shown to be effective in the management of KIRC. However, the prognostic genes associated with the tumor immune microenvironment in KIRC have not been fully identified. We obtained the KIRC RNA sequencing data and the clinical characteristics from The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) database. We screened the gene modules associated with the tumor immune microenvironment based on the ESTIMATE algorithm and weighted gene coexpression network analysis (WGCNA). Univariate Cox analysis and the LASSO method were used to construct a prognostic model. Receiver Operating Characteristic (ROC) curve analysis was performed to evaluate the accuracy of our risk model. TIMER and Single-Sample Gene Set Enrichment Analysis (ssGSEA) were used to explore the correlation between prognostic genes and immune cell infiltration.

Results

Fifty-four genes in modules were significantly associated with the overall survival (OS) time of patients with KIRC. Furthermore, 12 hub genes were selected to construct the prognostic model. The prognostic model showed superior accuracy in both TCGA and ICGC cohorts using ROC curve analysis. Systematic analysis of immune cell infiltration revealed that nine genes were significantly correlated with levels of tumor-infiltrating immune cells.

Conclusions

Our findings indicated that the tumor immune microenvironment was an important determinant of KIRC outcomes and revealed potential biomarkers for predicting patient OS and for targeted immunotherapies.

NFE2L3 promotes tumor progression and predicts a poor prognosis of bladder cancer

The high incidence and vulnerability to recurrence of bladder urothelial carcinoma (BLCA) is a challenge in the clinical. Recent studies have revealed that NFE2L3 plays a vital role in the carcinogenesis and progression of different human tumors. However, the role of NFE2L3 in bladder cancer has not been elucidated. In this study, NFE2L3 expression was significantly increased in bladder cancer samples. Its high expression was associated with advanced clinicopathological characteristics and was an independent prognostic factor for overall survival (OS) and metastasis-free survival (MFS) in 106 patients with BLCA. In vitro and in vivo experiments demonstrated that NFE2L3 knockdown inhibited bladder cancer cells proliferation by inducing the cell cycle arrest and cell apoptosis. Meanwhile, NFE2L3 overexpression promotes BLCA cell migration and invasion in vitro cell lines and in vivo xenografts. Moreover, we identified many genes and pathway alterations associated with tumor progression and metastasis by performing RNA-Seq analysis and functional enrichment of NFE2L3 overexpressing BLCA cells. Mechanistic investigation reveals that overexpression of NFE2L3 promoted epithelial-mesenchymal transition (EMT) in bladder cancer cells with decreased expression of gap junction-associated protein ZO-1 and epithelial marker E-cadherin with the elevation of transcription factors Snail1 and Snail2. Finally, we performed a comprehensive proteomics analysis to explore more potential molecular mechanisms. Our findings revealed that NFE2L3 might serve as a valuable clinical prognostic biomarker and therapeutic target in BLCA.

The Role of Arginine Metabolism in Oral Tongue Squamous Cell Carcinoma

Simple Summary

Cancers that are ‘arginine auxotrophic’ rely on extracellular arginine as a crucial substrate for proliferation and growth. Capitalizing on this vulnerability, there are numerous clinical trials evaluating the therapeutic benefits of depleting arginine in multiple types of cancer, including those occurring in the head and neck. However, head and neck cancers are different and are nonauxotrophic for arginine. Here, we explored the intricacies of arginine metabolism in tongue cancer in order to better understand the therapeutic potential of this biological vulnerability. We showed that reprogramming arginase 1 (ARG1) expression in tongue cancer cells inhibits growth compared with controls. Further, RNA-sequencing showed that HIFα, natural killer cell and interferon signaling were concordantly deregulated.

Abstract

Early diagnosis and treatment do not prevent the high morbidity and poor prognosis of oral tongue squamous cell carcinoma (TSCC). Earlier studies have shown that ARG1 signaling is deregulated in TSCC. Here, we investigated the complexity of ARG1 metabolism in this cancer subsite to appreciate the therapeutic potential of this potential biological vulnerability. Various functional studies show that ARG1 overexpression in oral cancer cells inhibits cell proliferation and invasion compared with controls. Further, RNA-sequencing revealed numerous differentially expressed genes (DEGs) and associated networks were dysregulated by ARG1 overexpression, including hypoxia-inducible factor (HIFα) signaling, the natural killer cell signaling pathway and interferon signaling. Our work provides a foundation for understanding the mechanism of action of disrupted arginine metabolism in oral tongue squamous cell carcinoma. This may impact the community for developing further therapeutic approaches.

Construction of a novel methylation-related prognostic model for colorectal cancer based on microsatellite status

The present study aimed to construct a novel methylation-related prognostic model based on microsatellite status that may enhance the prognosis of colorectal cancer (CRC) from methylation and microsatellite status perspective. DNA methylation and mRNA expression data with clinical information were downloaded from The Cancer Genome Atlas (TCGA) data set. The samples were divided into microsatellite stability and microsatellite instability group, and CIBERSORT was used to assess the immune cell infiltration characteristics. After identifying the differentially methylated genes and differentially expression genes using R packages, the methylation-driven genes were further identified. Prognostic genes that were used to establish the methylation-related risk score model were generated by the univariate and multivariate Cox regression model. Finally, we established and evaluated the methylation-related prognostic model for CRC patients. A total of 69 MDGs were obtained and three of these genes (MIOX, TH, DKFZP434K028) were selected to construct the prognostic model. Patients in the low-risk score group had a conspicuously better overall survival than those in the high-risk score group (p < .0001). The area under the receiver operating characteristic curve for this model was 0.689 at 3 years, 0.674 at 4 years, and 0.658 at 5 years. The Wilcoxon test showed that higher risk score was associated with higher T stage (p = .01), N stages (p = .0028), metastasis (p = .013), and advanced pathological stage (p = .0013). However, the more instability of microsatellite status, the lower risk score of CRC patients (p = .0048). Our constructed methylation-related prognostic model based on microsatellite status presents potential significance in assessing recurrence risk stratification, tumor staging, and immunotherapy for CRC patients.

A ceRNA-associated risk model predicts the poor prognosis for head and neck squamous cell carcinoma patients

Head and neck squamous cell carcinoma (HNSCC) is one of the most malignant cancers with poor prognosis worldwide. Emerging evidence indicates that competing endogenous RNAs (ceRNAs) are involved in various diseases, however, the regulatory mechanisms of ceRNAs underlying HNSCC remain unclear. In this study, we retrieved differentially expressed long non-coding RNAs (DElncRNAs), messenger RNAs (DEmRNAs) and microRANs (DEmiRNAs) from The Cancer Genome Atlas database and constructed a ceRNA-based risk model in HNSCC by integrated bioinformatics approaches. Functional enrichment analyses showed that DEmRNAs might be involved in extracellular matrix related biological processes, and protein–protein interaction network further selected out prognostic genes, including MYL1 and ACTN2. Importantly, co-expressed RNAs identified by weighted co-expression gene network analysis constructed the ceRNA networks. Moreover, AC114730.3, AC136375.3, LAT and RYR3 were highly correlated to overall survival of HNSCC by Kaplan–Meier method and univariate Cox regression analysis, which were subsequently implemented multivariate Cox regression analysis to build the risk model. Our study provides a deeper understanding of ceRNAs on the regulatory mechanisms, which will facilitate the expansion of the roles on the ceRNAs in the tumorigenesis, development and treatment of HNSCC.

The Role of Artificial Intelligence in the Diagnosis and Prognosis of Renal Cell Tumors

The increasing availability of molecular data provided by next-generation sequencing (NGS) techniques is allowing improvement in the possibilities of diagnosis and prognosis in renal cancer. Reliable and accurate predictors based on selected gene panels are urgently needed for better stratification of renal cell carcinoma (RCC) patients in order to define a personalized treatment plan. Artificial intelligence (AI) algorithms are currently in development for this purpose. Here, we reviewed studies that developed predictors based on AI algorithms for diagnosis and prognosis in renal cancer and we compared them with non-AI-based predictors. Comparing study results, it emerges that the AI prediction performance is good and slightly better than non-AI-based ones. However, there have been only minor improvements in AI predictors in terms of accuracy and the area under the receiver operating curve (AUC) over the last decade and the number of genes used had little influence on these indices. Furthermore, we highlight that different studies having the same goal obtain similar performance despite the fact they use different discriminating genes. This is surprising because genes related to the diagnosis or prognosis are expected to be tumor-specific and independent of selection methods and algorithms. The performance of these predictors will be better with the improvement in the learning methods, as the number of cases increases and by using different types of input data (e.g., non-coding RNAs, proteomic and metabolic). This will allow for more precise identification, classification and staging of cancerous lesions which will be less affected by interpathologist variability.

Roles of NRF3 in the Hallmarks of Cancer: Proteasomal Inactivation of Tumor Suppressors

Simple Summary

This review summarizes recent advances in our understanding of the physiological roles of the NFE2-related factor 2 (NRF2)-related transcription factor NRF3 in cancer. NRF3 confers cells with six so-called “hallmarks of cancer” through upregulating gene expression of specific target genes, leading to tumorigenesis and cancer malignancy. These driver gene-like functions of NRF3 in cancer are distinct from those of NRF2.

Abstract

The physiological roles of the NRF2-related transcription factor NRF3 (NFE2L3) have remained unknown for decades. The remarkable development of human cancer genome databases has led to strong suggestions that NRF3 has functional significance in cancer; specifically, high NRF3 mRNA levels are induced in many cancer types, such as colorectal cancer and pancreatic adenocarcinoma, and are associated with poor prognosis. On the basis of this information, the involvement of NRF3 in tumorigenesis and cancer malignancy has been recently proposed. NRF3 confers cancer cells with selective growth advantages by enhancing 20S proteasome assembly through induction of the chaperone gene proteasome maturation protein (POMP) and consequently promoting degradation of the tumor suppressors p53 and retinoblastoma (Rb) in a ubiquitin-independent manner. This new finding offers insight into the proteasomal but not the genetic inactivation mechanism of tumor suppressors. Moreover, NRF3 promotes cancer malignancy-related processes, including metastasis and angiogenesis. Finally, the molecular mechanisms underlying NRF3 activation have been elucidated, and this knowledge is expected to provide many insights that are useful for the development of anticancer drugs that attenuate NRF3 transcriptional activity. Collectively, the evidence indicates that NRF3 confers cells with six so-called “hallmarks of cancer”, implying that it exhibits cancer driver gene-like function. This review describes recent research advances regarding the newly discovered addiction of cancer cells to NRF3 compared to NRF2.

Transcription factor NFYA promotes G1/S cell cycle transition and cell proliferation by transactivating cyclin D1 and CDK4 in clear cell renal cell carcinoma

NFYA (nuclear transcription factor Y, subunit A) is a CCAAT-binding transcription factor. Accumulating evidence suggests that NFYA plays an important role in breast, ovarian, lung and gastric cancer. However, the role of NFYA in clear cell renal cell carcinoma (ccRCC) remains unclear. In this study, it was discovered that the expression of NFYA is elevated in tissues of ccRCC patient and high NFYA expression is linked to poor overall survival in ccRCC patient. Inhibition of G1/S cell cycle transition and decreased cell proliferation were observed upon NFYA knockdown in ccRCC cells. Moreover, further investigation revealed that NFYA binds directly to the promoter region of both CDK4 and cyclin D1 (CCND1) thus transactivating their expression, resulting in RB phosphorylation and the activation of subsequent E2F pathway activation. Taken together, these findings imply the oncogenic role of NFYA in ccRCC progression and its potential as a target for ccRCC therapy.

In Vitro to In Vivo Concordance of Toxicity Using the Human Proximal Tubule Cell Line HK-2

The renal proximal tubule cell line, human kidney 2 (HK-2), recapitulates many of the functional cellular and molecular characteristics of differentiated primary proximal tubule cells. These features include anchorage dependence, gluconeogenesis capability, and sodium-dependent sugar transport. In order to ascertain how well HK-2 cells can reliably reveal the toxicological profile of compounds having a potential to cause proximal tubule injury in vivo, we sought to evaluate the effects of known proximal tubule toxicants using the HK-2 cell line. We selected 20 pure nephrotoxic compounds that included chemotherapeutic drugs, antibiotics, and heavy metal-containing compounds and evaluated their ability to induce HK-2 cell injury relative to 10 innocuous pure compounds or cell culture media alone. We performed a comprehensive set of in vitro cellular toxicological assays to evaluate cell viability, oxidative stress, mitochondrial integrity, and a specific biomarker of renal injury, Kidney Injury Molecule 1. For each of our selected compounds, we were able to establish a reproducible profile of toxicological outcomes. We compared our results to those described in peer-reviewed publications to understand how well the HK-2 cellular model agrees with overall in vivo rat or human toxicological outcomes. This study begins to address the question of how well in vitro data generated with HK-2 cells can mirror in vivo animal and human outcomes.

Identification and Comprehensive Validation of a DNA Methylation-Driven Gene-Based Prognostic Model for Clear Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) is the most prevalent renal malignancy in adults with generally poor prognosis. This study aimed to establish a DNA methylation-driven gene-based prognostic model for ccRCC. We collected DNA methylation and gene expression profiles of over 1500 ccRCC samples from The Cancer Genome Atlas (TCGA) dataset, four Gene Expression Omnibus (GEO) datasets, the Genotype-Tissue Expression (GTEx) dataset, and cancer cell lines from Cancer Cell Line Encyclopedia database and performed comprehensive bioinformatics analysis. As a result, a total of 31 differentially expressed methylation-driven genes (DEMDGs) were identified. After univariate Cox regression, least absolute shrinkage and selection operator, and multivariate Cox regression analyses, four (NFE2L3, HHLA2, IFI16, and ZNF582) were finally selected to construct a risk score prognostic model. The high-risk group demonstrated significantly poor prognosis than the low-risk group did in TCGA training (hazard ratio [HR] = 3.533, p < 0.001), TCGA internal, and GEO external validation datasets. Furthermore, the nomogram, including the prognostic model and clinical factors, showed promising prognostic value (HR = 5.756, p < 0.001, and area under the curve at 1 year = 0.856). In addition, the model was found to be significantly associated with drug sensitivity of eight targeted agents. These findings provided a novel and reliable four DEMDG-based prognostic model for ccRCC.

Methylation-driven genes and their prognostic value in cervical squamous cell carcinoma

Background

Abnormal gene methylation is crucial for tumor progression. This study explored a cluster of methylation-driven genes involved in cervical squamous cell carcinoma (CESC).

Methods

The data on RNA expression, methylation and clinical outcomes of CESC patients were downloaded from The Cancer Genome Atlas (TCGA) database. Protein-protein interaction (PPI) network was constructed. Gene Ontology (GO) and KEGG analyses were performed to identify the biological functions of methylation-driven genes, and univariable and multivariate Cox analyses to screen out the key prognostic genes. A risk signature was established and its predictive value was evaluated with Kaplan-Meier and ROC curves. The key genes were further investigated by Cox regression analyses, gene set enrichment analysis (GSEA), and methylation site analysis. Additionally, "rms" package was used for establishing nomogram and calibrate curve.

Results

We found 144 differentially expressed methylation-driven genes. A risk model was constructed with three key prognostic genes (ITGA5, HHEX and S1PR4). The risk score was an independent risk factor for CESC prognosis. Lowly-expressed and hypermethylated ITGA5, highly-expressed and hypomethylated HHEX and S1PR4 were associated with better CESC prognosis. The methylation sites and biological functions enriched in ITGA5, HHEX and S1PR4 were uncovered. Additionally, the nomogram also validated the performance of risk model.

Conclusions

Methylation-driven ITGA5, HHEX and S1PR4 are associated with CESC development. The three genes might serve as potential targets in the treatment of CESC.

Methylation-Driven Genes Identified as Novel Prognostic Indicators for Thyroid Carcinoma

BACKGROUND

Aberrant DNA methylation plays an crucial role in tumorigenesis through regulating gene expression. Nevertheless, the exact role of methylation in the carcinogenesis of thyroid cancer and its association with prognosis remains unclear. The purpose of this study is to explore the DNA methylation-driven genes in thyroid cancer by integrative bioinformatics analysis.

METHODS

The transcriptome profiling data and DNA methylation data of thyroid cancer were downloaded from The Cancer Genome Atlas (TCGA) database. The methylmix R package was used to screen DNA methylation-driven genes in thyroid cancer. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were conducted to annotate the function of methylation-driven genes. Univariate Cox regression analyses was performed to distinguish prognosis-related methylation-driven genes. Multivariate Cox regression analyses was utilized to build a prognostic multi-gene signature. A survival analysis was carried out to determine the individual prognostic significance of this multi-gene signature.

RESULTS

A total of 51 methylation-driven genes were identified. The functional analysis indicated that these genes were significantly enriched in diverse biological processes (BP) and pathways related to the malignancy processes. Four of these genes (RDH5, TREM1, BIRC7, and SLC26A7) were selected to construct the risk evaluation model. Patients in the low-risk group had an conspicuously better overall survival (OS) than those in high-risk group (p < 0.001). The area under the receiver operating characteristic (ROC) curve for this model was 0.836, suggesting a good specificity and sensitivity. Subsequent survival analysis revealed that this four-gene signature served as an independent indicator for the prognosis of thyroid cancer. Moreover, the prognostic signature was well validated in a external thyroid cancer cohort.

CONCLUSION

We identified methylation-driven genes in thyroid cancer with independent prognostic value, which may offer new insight into molecular mechanisms of thyroid cancer and provide new possibility for individualized treatment of thyroid cancer patients.