ABAT and ALDH6A1, regulated by transcription factor HNF4A, suppress tumorigenic capability in clear cell renal cell carcinoma

Inhibition of citrate transport reduces HIF-1α/GABA-T-mediated succinate accumulation in macrophages: The role of astragaloside IV in ischemic stroke

BACKGROUND

The occurrence of ischemic stroke is closely associated with the inflammatory infiltration of peripheral monocytes/macrophages, and the inflammatory activation of macrophages is often affected by metabolic reprogramming. The Slc25a1 regulates mitochondrial citrate transport and has been shown to affect cell proliferation and migration in cancer. Astragaloside IV exhibits significant anti-inflammatory activity and improves ischemic stroke, but its regulatory effect on macrophage metabolic reprogramming has not been elucidated.

OBJECTIVES

This study aims to explore the effect of astragaloside IV on ischemic stroke injury from the perspective of Slc25a1-mediated cellular metabolic reprogramming.

METHODS

A total of 170 mice were used to establish the middle cerebral artery occlusion (MCAO) model. The therapeutic effect of astragaloside IV was evaluated by neurobehavioral scores and infarct volume, with its impact further verified through the depletion of peripheral macrophages. The modulation of Slc25a1 by astragaloside IV and its influence on macrophages were investigated in mouse bone marrow-derived macrophages (BMDMs) and peripheral blood mononuclear cell-derived macrophages (PBMC-derived macrophages).

RESULTS

Astragaloside IV significantly mitigated neurological impairment and reduced cerebral infarction volume in MCAO mice by inhibition of peripheral monocytes/macrophage inflammatory infiltration. In activated BMDMs and PBMC-derived macrophages, astragaloside IV interacted with Slc25a1, attenuated citrate transport, maintained mitochondrial function, therefore enhancing the shift from the M1- to M2-like macrophages. Mechanistically, astragaloside IV inhibited the transcriptional regulation of HIF-1α on GABA-T via citate-mediated histone H3 and H4 deacetylation and promoted the resumption of the broken TCA cycle and mitochondrial OXPHOS in macrophages.

CONCLUSIONS

Our study unveiled a therapeutic strategy for ischemic stroke by intervening in the inflammatory infiltration of peripheral monocytes/macrophages. Astragaloside IV, by binding to the mitochondrial citrate transporter Slc25a1, maintained the homeostasis of the TCA cycle and mitochondrial function, ultimately blocking the inflammation of peripheral macrophages to ameliorate ischemic stroke damage. This discovery provides data support for expanding the clinical application of astragaloside IV and offers research insights into the external treatment of encephalopathy.

GABA regulates metabolic reprogramming to mediate the development of brain metastasis in non-small cell lung cancer

BACKGROUND

Brain metastasis (BrM) poses a significant challenge to the prognosis and quality of life for patients with non-small cell lung cancer (NSCLC). Gamma-aminobutyric acid (GABA), an inhibitory neurotransmitter in the central nervous system (CNS), has been implicated in the progression of various tumors. However, its potential role in BrM of NSCLC and the underlying mechanisms remain largely unexplored.

METHODS

A multi-omics approach combined with in vivo and in vitro experiments identified GABA as a key target in BrM of NSCLC. Functional and mechanistic studies were conducted to investigate how GABA mediates brain metastasis through the activation of the NF-κB pathway.

RESULTS

GABA levels were significantly elevated in both cells and serum of patients with NSCLC who had BrM. GABA markedly enhanced the brain metastatic capabilities and malignancy of NSCLC cells. Mechanistically, tumor cells with a tendency for brain metastasis can inhibit 4-aminobutyrate aminotransferase (ABAT) by downregulating forkhead box A2 (FOXA2) expression, leading to increased GABA accumulation. GABA subsequently activates the NF-κB pathway and the astrocytes, thus facilitating the brain metastasis of NSCLC.

CONCLUSIONS

Our findings indicate that GABA plays a crucial role in the development of NSCLC brain metastasis by activating the NF-κB pathway through the FOXA2/ABAT/GABA axis. Additionally, the interaction between NSCLC and astrocytes creates an inhibitory microenvironment that promotes tumor colonization.

Glutathiones' life in multi-cancers: especially their potential micropetides in liver hepatocellular carcinoma

BACKGROUND

Glutathione plays critical roles in detoxifying xenobiotics, cell signaling, cell death and the antioxidant defence in an emerging body of evidence, the most abundant intracellular low molecular weight thiol in tissues. However, all glutathione metabolism pertinent genes (GMPGs) expression and their diagnostic/prognostic/micropeptide potential analyses have not been investigated to perform in pan-cancers.

METHODS

We gained GMPGs from the MsigDB 7.2, 12,123 samples were used to reveal the differentially expressed genes (DEGs) and the survival analysis in 32 types of cancers from TCGA, GTEx, and GEO datasets for the first time. All statistical analyses were performed by R for bioinformatics, such as DEGs, prognostic, diagnostic analysis, ceRNA, micropeptide prediction and immune infiltration. In addition, we utilized siRNA technology to target knockdown the expression of the G6PD gene in Huh7 hepatocellular carcinoma cells.

RESULTS

G6PD was significantly expressed and poor prognosis in liver hepatocellular carcinoma (LIHC) and predicted RBM26-AS1 encoded micropeptide might target G6PD in LIHC. In vitro experiments show that G6PD knockout in Huh7 cells reduces their proliferation, migration, and invasion capabilities.

CONCLUSIONS

We confirmed that G6PD played a crucial role in the occurrence and progression of LIHC. G6PD is positively associated with Th2 cells in LIHC, regulating immune responses in the immune system. We considered that micropeptide RBM26-AS1 might be a new player involved in LIHC by interacting with G6PD, might perform a key function in liver cancer.

Identifying ADME-related gene signature for immune landscape and prognosis in KIRC by single-cell and spatial transcriptome analysis

Kidney renal clear cell carcinoma (KIRC) is the most prevalent subtype of kidney cancer. Although multiple therapeutic agents have been proven effective in KIRC, their clinical application has been hindered by a lack of reliable biomarkers. This study focused on the prognostic value and function of drug absorption, distribution, metabolism, and excretion- (ADME-) related genes (ARGs) in KIRC to enhance personalized therapy. The critical role of ARGs in KIRC microenvironment was confirmed by single cell RNA-seq analysis and spatial transcriptome sequencing analysis for the first time. Then, an ADME-related prognostic signature (ARPS) was developed by the bulk RNA-seq analysis. The ARPS, created through Cox regression, LASSO, and stepAIC analyses, identified eight ARGs that stratified patients into high-risk and low-risk groups. High-risk patients had significantly poorer overall survival. Multivariate analysis confirmed the independent predictive ability of ARPS, and an ARPS-based nomogram was constructed for clinical application. Gene ontology and KEGG pathway analyses revealed immune-related functions and pathways enriched in these groups, with low-risk patients showing better responses to immunotherapy. Finally, the expression of ARGs was validated by qRT-PCR and Western blotting experiments. These findings underscore the prognostic significance of ARPS in KIRC and its potential application in guiding personalized treatment strategies.

Aldehyde dehydrogenases as drug targets for cancer: SAR and structural biology aspects for inhibitor design

Aldehydes are organic compounds containing a carbonyl group found exogenously or produced by normal metabolic processes and their accumulation can lead to toxicity if not cleared. Aldehyde dehydrogenases (ALDHs) are NAD(P)+-dependent enzymes that catalyze the oxidation of such aldehydes and prevent their accumulation. Along with this primary detoxification function, the known 19 human isoforms of ALDHs, which act on different substrates, are also involved in various physiological and developmental processes. Functional alterations of ALDHs via mutations or expression levels cause various disease conditions, including many different cancer types like lung, ovarian, etc. These properties make this family of enzymes an ideal therapeutic and prognostic target for drug development. However, sequence similarities between the ALDH isoforms force the need to design inhibitors for a specific isoform using the differences in the substrate-binding sites of each protein. This has resulted in developing isoform-specific inhibitors, especially for ALDH1A1, ALDH2, and ALDH3A1, which are implicated in various cancers. In this review, we briefly outline the functional roles of the different isoforms of the ALDH family members, their role in cancer and discuss the various selective inhibitors that have been developed for the ALDH1A1 and ALDH3A1 enzymes, along with a detailed examination of the respective structure-activity relationship (SAR) studies available. From the available SAR and structural biology data, insights into the functional groups and interactions necessary to develop selective inhibitors for ALDH1A1 and ALDH3A1 are highlighted, which can act as a guide for developing more potent and selective inhibitors of ALDH isoforms.

Modal-nexus auto-encoder for multi-modality cellular data integration and imputation

Heterogeneous feature spaces and technical noise hinder the cellular data integration and imputation. The high cost of obtaining matched data across modalities further restricts analysis. Thus, there's a critical need for deep learning approaches to effectively integrate and impute unpaired multi-modality single-cell data, enabling deeper insights into cellular behaviors. To address these issues, we introduce the Modal-Nexus Auto-Encoder (Monae). Leveraging regulatory relationships between modalities and employing contrastive learning within modality-specific auto-encoders, Monae enhances cell representations in the unified space. The integration capability of Monae furnishes it with modality-complementary cellular representations, enabling the generation of precise intra-modal and cross-modal imputation counts for extensive and complex downstream tasks. In addition, we develop Monae-E (Monae-Extension), a variant of Monae that can converge rapidly and support biological discoveries. Evaluations on various datasets have validated Monae and Monae-E's accuracy and robustness in multi-modality cellular data integration and imputation.

Targeting the peripheral neural-tumour microenvironment for cancer therapy

As the field of cancer neuroscience expands, the strategic targeting of interactions between neurons, cancer cells and other elements in the tumour microenvironment represents a potential paradigm shift in cancer treatment, comparable to the advent of our current understanding of tumour immunology. Cancer cells actively release growth factors that stimulate tumour neo-neurogenesis, and accumulating evidence indicates that tumour neo-innervation propels tumour progression, inhibits tumour-related pro-inflammatory cytokines, promotes neovascularization, facilitates metastasis and regulates immune exhaustion and evasion. In this Review, we give an up-to-date overview of the dynamics of the tumour microenvironment with an emphasis on tumour innervation by the peripheral nervous system, as well as current preclinical and clinical evidence of the benefits of targeting the nervous system in cancer, laying a scientific foundation for further clinical trials. Combining empirical data with a biomarker-driven approach to identify and hone neuronal targets implicated in cancer and its spread can pave the way for swift clinical integration.

Research on molecular characteristics of ADME-related genes in kidney renal clear cell carcinoma

Genes involved in drug absorption, distribution, metabolism, and excretion (ADME) are named ADME genes. However, the comprehensive role of ADME genes in kidney renal clear cell carcinoma (KIRC) remains unclear. Using the clinical and gene expression data of KIRC patients downloaded from The Cancer Genome Atlas (TCGA), ArrayExpress, and the Gene Expression Omnibus (GEO) databases, we cluster patients into two patterns, and the population with a relatively poor prognosis demonstrated higher level of immunosuppressive cell infiltration and higher proportion of glycolytic subtypes. Then, 17 ADME genes combination identified through the least absolute shrinkage and selection operator algorithm (LASSO, 1000 times) was utilized to calculate the ADME score. The ADME score was found to be an independent predictor of prognosis in KIRC and to be tightly associated with the infiltration level of immune cells, metabolic properties, tumor-related signaling pathways, genetic variation, and responses to chemotherapeutics. Our work revealed the characteristics of ADME in KIRC. Assessing the ADME profiles of individual patients can deepen our comprehension of tumor microenvironment (TME) features in KIRC and can aid in developing more personalized and effective therapeutic strategies.

Decoding sunitinib resistance in ccRCC: Metabolic-reprogramming-induced ABAT and GABAergic system shifts

Sunitinib, a primary treatment for clear cell renal cell carcinoma (ccRCC), frequently encounters the challenge of resistance development. Metabolic reprogramming, a characteristic change in ccRCC, is likely linked to this resistance. Our research revealed a notable decrease in the expression of the key metabolic gene ABAT in ccRCC, which contributed to diminished sensitivity to sunitinib. Downregulation of ABAT led to an increase in the intracellular level of gamma-aminobutyric acid (GABA), triggering abnormal activation of the G-protein-coupled receptor GABA-B. This activation resulted in increased transactivation of the tyrosine kinase receptors SYK and LYN, thereby reducing the antitumor and antiangiogenic properties of sunitinib. However, the application of SYK and LYN inhibitors successfully inhibited this effect. The transactivation of SYK and LYN caused resistance to the antiangiogenic effects of sunitinib through the upregulation of PGF protein levels. Furthermore, the combined application of an LYN inhibitor with sunitinib has been shown to enhance therapeutic efficacy.

Therapeutic insight into the role of nuclear protein HNF4α in liver carcinogenesis

Hepatocyte nuclear factor 4-alpha (HNF4α), a well-preserved member of the nuclear receptor superfamily of transcription factors, is found in the liver. It is recognized as a central controller of gene expression specific to the liver and plays a key role in preserving the liver's homeostasis. Irregular expression of HNF4α is increasingly recognized as a crucial factor in the proliferation, cell death, invasiveness, loss of specialized functions, and metastasis of cancer cells. An increasing number of studies are pointing to abnormal HNF4α expression as a key component of cancer cell invasion, apoptosis, proliferation, dedifferentiation, and metastasis. Understanding HNF4α's intricate involvement in liver carcinogenesis provides a promising avenue for therapeutic intervention. This chapter attempts to shed light on the diverse aspects of HNF4's role in liver carcinogenesis and demonstrate how this knowledge can be harnessed for approaches to prevent and treat liver cancer. This comprehensive chapter will offer an elaborate perspective on HNF4's function in liver cancer, delineating its molecular mechanisms that aid in the emergence of liver cancer. Furthermore, it will highlight the potential to help create more effective and precisely targeted therapeutic strategies, rekindling fresh optimism in the fight against this formidable condition.

Navigating the blurred path of mixed neuroimmune signaling

Evolution has created complex mechanisms to sense environmental danger and protect tissues, with the nervous and immune systems playing pivotal roles. These systems work together, coordinating local and systemic reflexes to restore homeostasis in response to tissue injury and infection. By sharing receptors and ligands, they influence the pathogenesis of various diseases. Recently, a less-explored aspect of neuroimmune communication has emerged: the release of neuropeptides from immune cells and cytokines/chemokines from sensory neurons. This article reviews evidence of this unique neuroimmune interplay and its impact on the development of allergy, inflammation, itch, and pain. We highlight the effects of this neuroimmune signaling on vital processes such as host defense, tissue repair, and inflammation resolution, providing avenues for exploration of the underlying mechanisms and therapeutic potential of this signaling.

Chromosome-level Asian elephant genome assembly and comparative genomics of long-lived mammals reveal the common substitutions for cancer resistance

The naked mole rat (Heterocephalus glaber), bats (e.g., genus Myotis), and elephants (family Elephantidae) are known as long-lived mammals and are assumed to be excellent cancer antagonists. However, whether there are common genetic changes underpinning cancer resistance in these long-lived species is yet to be fully established. Here, we newly generated a high-quality chromosome-level Asian elephant (Elephas maximus) genome and identified that the expanded gene families in elephants are involved in Ras-associated and base excision repair pathways. Moreover, we performed comparative genomic analyses of 12 mammals and examined genes with signatures of positive selection in elephants, naked mole rat, and greater horseshoe bat. Residues at positively selected sites of CDR2L and ALDH6A1 in these long-lived mammals enhanced the inhibition of tumor cell migration compared to those in short-lived relatives. Overall, our study provides a new genome resource and a preliminary survey of common genetic changes in long-lived mammals.

Integrative analysis developing and validating potential candidate biomarkers for cancer stemness features of pan-renal cell carcinoma

In our study, 49 key genes significantly associated with renal cell carcinoma (RCC) stemness were obtained. Next, we developed a molecular prognostic signature associated with stemness features of pan-RCC. The difference in OS between high-risk and low-risk group was statistically significant (P < 0.05). The area under ROC curve for 1-years OS, 5-years OS and 10-years OS was 0.759, 0.712 and 0.918, respectively. The results of validation in TCGA cohort and ICGC cohort revealed the predictive capability of this signature. Further, we selected three genes and further validation showed that these three hub genes were potential hub biomarkers for pan-RCC stemness features.

GABAergic signaling beyond synapses: an emerging target for cancer therapy

Traditionally, γ-aminobutyric acid (GABA) is best known for its role as a primary inhibitory neurotransmitter reducing neuronal excitability in the mammalian central nervous system (CNS), thereby producing calming effects. However, an emerging body of data now supports a function for GABA beyond neurotransmission as a potent factor regulating cancer cell growth and metastasis, as well as the antitumor immune response, by shaping the tumor microenvironment (TME). Here, we review the current knowledge on GABA's effects on the function of tumor cells, tumor-immune interactions, and the underlying molecular mechanisms. Since altered GABAergic signaling is now recognized as a feature of certain types of solid tumors, we also discuss the potential of repurposing existing GABAergic agents as a new class of anticancer therapy.

Identification and validation of NFIA as a novel prognostic marker in renal cell carcinoma

Prognostic tools are an essential component of the clinical management of patients with renal cell carcinoma (RCC). Although tumour stage and grade can provide important information, they fail to consider patient- and tumour-specific biology. In this study, we set out to find a novel molecular marker of RCC by using hepatocyte nuclear factor 4A (HNF4A), a transcription factor implicated in RCC progression and malignancy, as a blueprint. Through transcriptomic analyses, we show that the nuclear factor I A (NFIA)-driven transcription network is active in primary RCC and that higher levels of NFIA confer a survival benefit. We validate our findings using immunohistochemical staining and analysis of a 363-patient tissue microarray (TMA), showing for the first time that NFIA can independently predict poor cancer-specific survival in clear cell RCC (ccRCC) patients (hazard ratio = 0.46, 95% CI = 0.24-0.85, p value = 0.014). Furthermore, we confirm the association of HNF4A with higher grades and stages in ccRCC in our TMA cohort. We present novel data that show HNF4A protein expression does not confer favourable prognosis in papillary RCC, confirming our survival analysis with publicly available HNF4A RNA expression data. Further work is required to elucidate the functional role of NFIA in RCC as well as the testing of these markers on patient material from diverse multi-centre cohorts, to establish their value for the prognostication of RCC.

Aldehyde dehydrogenase in solid tumors and other diseases: Potential biomarkers and therapeutic targets

The family of aldehyde dehydrogenases (ALDHs) contains 19 isozymes and is involved in the oxidation of endogenous and exogenous aldehydes to carboxylic acids, which contributes to cellular and tissue homeostasis. ALDHs play essential parts in detoxification, biosynthesis, and antioxidants, which are of important value for cell proliferation, differentiation, and survival in normal body tissues. However, ALDHs are frequently dysregulated and associated with various diseases like Alzheimer's disease, Parkinson's disease, and especially solid tumors. Notably, the involvement of the ALDHs in tumor progression is responsible for the maintenance of the stem-cell-like phenotype, triggering rapid and aggressive clinical progressions. ALDHs have captured increasing attention as biomarkers for disease diagnosis and prognosis. Nevertheless, these require further longitudinal clinical studies in large populations for broad application. This review summarizes our current knowledge regarding ALDHs as potential biomarkers in tumors and several non-tumor diseases, as well as recent advances in our understanding of the functions and underlying molecular mechanisms of ALDHs in disease development. Finally, we discuss the therapeutic potential of ALDHs in diseases, especially in tumor therapy with an emphasis on their clinical implications.

An immune infiltration-related prognostic model of kidney renal clear cell carcinoma with two valuable markers: CAPN12 and MSC

Background

Since its discovery, clear cell renal cell carcinoma (ccRCC) has been the most prevalent and lethal kidney malignancy. Our research aims to identify possible prognostic genes of ccRCC and to develop efficient prognostic models for ccRCC patients based on multi-omics investigations to shed light on the treatment and prognosis of ccRCC.

Methods

To determine a risk score for each patient, we screened out differentially expressed genes using data from tumor samples, and control samples mined from The Cancer Genome Atlas (TCGA) and GTEx datasets. Somatic mutation and copy number variation profiles were analyzed to look for specific genomic changes connected to risk scores. To investigate potential functional relationships of prognostic genes, gene set variation analysis (GSVA) and gene set enrichment analysis (GSEA) were carried out. We created a prognostic model by fusing risk ratings with other clinical variables. For validation, the 786-O cell line was used to carry out the dual-gRNA approach to knock down CAPN12 and MSC. This was followed by qRT-PCR to verify the knockdown of CAPN12 and MSC.

Results

For ccRCC, seven predictive genes were discovered: PVT1, MSC, ALDH6A1, TRIB3, QRFPR, CYS1, and CAPN12. The most enriched pathways in the GSVA study and GSEA analysis promote tumorigenesis and immune system modulation. The risk score derived from prognostic genes corresponds with immune infiltration cells and helps predict how well a medicine will work. The mutation of numerous oncogenes was also linked to a high-risk score. A prognostic model with a high ROC value was created for the risk score. An in vitro study demonstrates that the suppression of CAPN12 and MSC dramatically reduced the ability of 786-O cells to proliferate in the CCK-8 proliferation assay and plate clonality assays.

Conclusions

A thorough prognostic model with good performance has been developed for ccRCC patients using seven prognostic genes that were discovered to be related to ccRCC prognosis. In ccRCC, CAPN12 and MSC were significant indicators and would make good therapeutic targets.

The role of hepatocyte nuclear factor 4α (HNF4α) in tumorigenesis

Hepatocyte Nuclear Factor 4 Alpha (HNF4α) is a master transcription factor mainly expressed in the liver, kidney, intestine and endocrine pancreas. It regulates multiple target genes involved in embryonic development and metabolism. HNF4α-related diseases include non-alcoholic fatty liver disease (NAFLD), obesity, hypertension, hyperlipidemia, metabolic syndrome and diabetes mellitus. Recently, HNF4α has been emerging as a key player in a variety of cancers. In this review, we summarized the role and mechanism of HNF4α in different types of cancers, especially in liver and colorectal cancer, aiming to provide additional guidance for intervention of these diseases.

Nonsense-Mediated Decay Targeted RNA (ntRNA): Proposal of a ntRNA–miRNA–lncRNA Triple Regulatory Network Usable as Biomarker of Prognostic Risk in Patients with Kidney Cancer

The most prevalent subtype of renal cell carcinoma (RCC), kidney renal clear cell carcinoma (KIRC) may be associated with a poor prognosis in a high number of cases, with a stage-specific prognostic stratification currently in use. No reliable biomarkers have been utilized so far in clinical practice despite the efforts in biomarker research in the last years. Nonsense-mediated mRNA decay (NMD) is a critical safeguard against erroneous transcripts, particularly mRNA transcripts containing premature termination codons (called nonsense-mediated decay targeted RNA, ntRNA). In this study, we first characterized 296 differentially expressed ntRNAs that were independent of the corresponding gene, 261 differentially expressed miRNAs, and 4653 differentially expressed lncRNAs. Then, we constructed a hub ntRNA–miRNA–lncRNA triple regulatory network associated with the prognosis of KIRC. Moreover, the results of immune infiltration analysis indicated that this network may influence the changes of the tumor immune microenvironment. A prognostic model derived from the genes and immune cells associated with the network was developed to distinguish between high- and low-risk patients, which was a better prognostic than other models, constructed using different biomarkers. Additionally, correlation of methylation and ntRNAs in the network suggested that some ntRNAs were regulated by methylation, which is helpful to further study the causes of abnormal expression of ntRNAs. In conclusion, this study highlighted the possible clinical implications of ntRNA functions in KIRC, proposing potential significant biomarkers that could be utilized to define the prognosis and design personalized treatment plans in kidney cancer management in the next future.

A metabolic reprogramming-related prognostic risk model for clear cell renal cell carcinoma: From construction to preliminary application

Metabolic reprogramming is one of the characteristics of clear cell renal cell carcinoma (ccRCC). Although some treatments associated with the metabolic reprogramming for ccRCC have been identified, remain still lacking. In this study, we identified the differentially expressed genes (DEGs) associated with clinical traits with a total of 965 samples via DEG analysis and weighted correlation network analysis (WGCNA), screened the prognostic metabolism-related genes, and constructed the risk score prognostic models. We took the intersection of DEGs with significant difference coexpression modules and received two groups of intersection genes that were connected with metabolism via functional enrichment analysis. Then we respectively screened prognostic metabolic-related genes from the genes of the two intersection groups and constructed the risk score prognostic models. Compared with the predicted effect of clinical grade and stage for ccRCC patients, finally, we selected the model constructed with genes of ABAT, ALDH6A1, CHDH, EPHX2, ETNK2, and FBP1. The risk scores of the prognostic model were significantly related to overall survival (OS) and could serve as an independent prognostic factor. The Kaplan-Meier analysis and ROC curves revealed that the model efficiently predicts prognosis in the TCGA-KIRC cohort and the validation cohort. Then we investigated the potential underlying mechanism and sensitive drugs between high- and low-risk groups. The six key genes were significantly linked with worse OS and were downregulated in ccRCC, we confirmed the results in clinical samples. These results demonstrated the efficacy and robustness of the risk score prognostic model, based on the characteristics of metabolic reprogramming in ccRCC, and the key genes used in constructing the model also could develop into targets of molecular therapy for ccRCC.

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

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

ALDH6A1 weakens the progression of colon cancer via modulating the RAS/RAF/MEK/ERK pathway in cancer cell lines

BACKGROUND

Aldehyde dehydrogenase 6 family member A1 (ALDH6A1) is associated with multiple diseases, but its pathogenesis in colon cancer (CC) is ambiguous and needs further study so that this research explores the function of ALDH6A1 in CC.

METHODS

The level of ALDH6A1 in colon adenocarcinoma (COAD), CC tissues, and cells was measured by starBase v2.0, quantitative real-time polymerase chain reaction (qRT-PCR), and western blot. Post transfection with overexpressed (oe)-ALDH6A1, cell biological behaviors, as well as apoptosis-, matrix metalloproteinase (MMP)-, and rat sarcoma virus (RAS)/rapidly accelerated fibrosarcoma (RAF)/mitogen-activated protein kinase (MEK)/extracellular signal-regulated kinase (ERK) pathway-related markers were measured by cell function experiments, qRT-PCR, and western blot. Next, the effects of small interfering RNA targeting ALDH6A1 (si-ALDH6A1) and RAS/RAF inhibitor (MCP110) on cell biological behaviors, as well as apoptosis-, MMP-, and RAS/RAF/MEK/ERK pathway-related markers were detected again.

RESULTS

ALDH6A1 was low-expressed in COAD, CC tissues, and cells . Oe-ALDH6A1 weakened cell vitality, migration and invasionbut facilitated apoptosis; while it reduced expression levels of Bcl-2, MMP-2, MMP-9 and the RAS/RAF/MEK/ERK pathway-related markers but promoted Bax level. However, the regulation of si-ALDH6A1 on cell biological behaviors and related genes was opposite to that of oe-ALDH6A1. Moreover, MCP110 rescued the regulation of si-ALDH6A1 on cell biological behaviors, expressions of apoptosis- MMP- as well as RAS/RAF/MEK/ERK pathway-related markers. To sum up, ALDH6A1 attenuated CC progression by down-regulating the expressions of RAS/RAF/MEK/ERK pathway-related markers.

Identification of Survival Risk and Immune-Related Characteristics of Kidney Renal Clear Cell Carcinoma

Background

Immunity exerts momentous functions in the progression and treatment of kidney renal clear cell carcinoma (KIRC). A better understanding of the relationship between KIRC and immunity may make a great contribution to evaluating the prognosis and immune-related therapeutic response of KIRC.

Methods

A series of information such as RNA sequence, clinical data, and tumor mutation burden (TMB) of KIRC patients were downloaded through The Cancer Genome Atlas (TCGA). Next, combining the survival information and gene expression data of TCGA and Gene Expression Omnibus (GEO), we established an immune gene-related prognosis model (IGRPM) and analyzed it. Then we constructed a nomogram which was convenient for clinicians to judge the prognosis of KIRC. Last but not the least, the expressions of some genes used to construct IGRPM in early KIRC, and adjacent normal tissues were verified through real-time fluorescence quantitative polymerase chain reaction (RT-qPCR). Perl (strawberry-perl-5.30.0.1-64bit), R software (4.0.3), and GraphPad Prism 7 were used to process the relevant data.

Results

The single-sample gene set enrichment analysis (ssGSEA) showed that there were significant differences in StromalScore, ImmuneScore, ESTIMATEScore, TumorPurity, 22 kinds of human immune cells infiltration, and HLA genes expression between high immunity group (Immunity_H) and low immunity group (Immunity_L). The Immunity_H expressed more immune-related genes and enriched more immune-related functions than the Immunity_L. In addition, compared with the low-risk group, the high-risk group had worse survival outcome and higher TMB. Combining IGRPM-based risk characteristic and TMB, we found that low-TMB + low-risk was the most beneficial to the survival outcome of KIRC patients. The risk characteristic based on IGRPM could be used as an independent prognostic factor for KIRC, and the nomogram constructed for evaluating the prognosis of KIRC showed excellent predictive potential. The RT-qPCR results suggested that not all the genes used to construct IGRPM showed differential expression in early KIRC compared with adjacent normal tissues, but all these genes had significant influence on the prognosis of KIRC.

Conclusion

These comprehensive immune assessments and survival predictions, integrating multiple aspects of data and clinical information, can provide additional value to the current Tumor Node Metastasis staging system for risk stratification of KIRC and may facilitate the development of KIRC immunotherapy.

Regulation of Gamma-Aminobutyric Acid Transaminase Expression and Its Clinical Significance in Hepatocellular Carcinoma

Background

Gamma-aminobutyric acid transaminase (ABAT) catalyzes the conversion of gamma-aminobutyric acid (GABA) into succinic semialdehyde. Although some evidence supports a key role of ABAT in the progression of hepatocellular carcinoma (HCC), no systematic analysis is available. Thus, this study aimed to investigate the possible mechanisms related to low ABAT expression and the prognostic value and potential functions of ABAT in HCC.

Methods

We obtained relevant datasets from the Encyclopedia of RNA Interactomes, MethSurv, cBioPortal, TISIDB and The Cancer Genome Atlas and used bioinformatic methods to analyze DNA methylation, copy number variation, gene mutation, and upstream microRNAs (miRNAs) of ABAT, exploring the potential relationship between ABAT expression and the prognosis, glycolysis, and immune infiltration in HCC.

Results

The results indicated that ABAT expression was lower in HCC tumor tissues than in normal tissues or adjacent tissues. Low ABAT expression was related to patient age, T stage classification, pathologic stage, histological grade, and alpha-fetoprotein level of HCC. Kaplan-Meier survival analyses indicated that low ABAT expression was correlated with poor HCC prognosis. ABAT was also verified as an independent risk factor in HCC via Cox multivariate analysis. Gene set enrichment analysis showed enrichment in various signaling pathways. Furthermore, DNA methylation, copy number variation, and gene mutation potentially induced low ABAT expression; miR-135a-5p was a potential upstream miRNA of ABAT. Additionally, ABAT expression was associated with glycolysis-related genes, infiltrated immune cells, immunoinhibitors, and immunostimulators in HCC.

Conclusions

Our study reveals that deficient ABAT expression is correlated with disease progression and poor prognosis in HCC because of its role in tumorigenesis and tumor immunity.

A Deep Insight Into Regulatory T Cell Metabolism in Renal Disease: Facts and Perspectives

Kidney disease encompasses a complex set of diseases that can aggravate or start systemic pathophysiological processes through their complex metabolic mechanisms and effects on body homoeostasis. The prevalence of kidney disease has increased dramatically over the last two decades. CD4⁺CD25⁺ regulatory T (Treg) cells that express the transcription factor forkhead box protein 3 (Foxp3) are critical for maintaining immune homeostasis and preventing autoimmune disease and tissue damage caused by excessive or unnecessary immune activation, including autoimmune kidney diseases. Recent studies have highlighted the critical role of metabolic reprogramming in controlling the plasticity, stability, and function of Treg cells. They are also likely to play a vital role in limiting kidney transplant rejection and potentially promoting transplant tolerance. Metabolic pathways, such as mitochondrial function, glycolysis, lipid synthesis, glutaminolysis, and mammalian target of rapamycin (mTOR) activation, are involved in the development of renal diseases by modulating the function and proliferation of Treg cells. Targeting metabolic pathways to alter Treg cells can offer a promising method for renal disease therapy. In this review, we provide a new perspective on the role of Treg cell metabolism in renal diseases by presenting the renal microenvironment、relevant metabolites of Treg cell metabolism, and the role of Treg cell metabolism in various kidney diseases.

Aldehyde dehydrogenase 6 family member A1 negatively regulates cell growth and to cisplatin sensitivity in bladder cancer

Aldehyde dehydrogenase 6 family member A1 (ALDH6A1) is a highly conserved member of aldehyde dehydrogenase (ALDHs) family. Recent studies reveal that it broadly involved in tumorigenesis and drug metabolism in kinds of cancer. However, the critical role of ALDH6A1 in bladder cancer progression and cisplatin resistance of cancer cells are still poorly understood. In this study, we researched the significant function of ALDH6A1 in bladder cancer. Our results showed that ALDH6A1 exhibited a decreased expression in clinical bladder cancer tissues and bladder cancer cell lines. Stable ALDH6A1 knockdown not only could promote cell growth and colony formation in bladder cancer cells, but also enhance drug resistance to cisplatin treatment. On the contrary, we found the active transcript factor hepatocyte nuclear factor 4α (HNF4α, NR2A1) by alveriene could upregulate ALDH6A1 expression, significantly inhibit the cell growth and colony formation of bladder cancer cells, and improve cisplatin sensitivity of bladder cancer cells. Together, our results show that ALDH6A1 plays as a tumor suppressor in bladder cancer, which regulated by HNF4a. ALDH6A1 could be a promising diagnostic marker and treatment target in bladder cancer.

Protective Mechanism of Leucine and Isoleucine against H2O2-Induced Oxidative Damage in Bovine Mammary Epithelial Cells

Leucine and isoleucine possess antioxidative and anti-inflammatory properties. However, their underlying protective mechanisms against oxidative damage remain unknown. Therefore, in this study, the protective mechanism of leucine and isoleucine against H₂O₂-induced oxidative damage in a bovine mammary epithelial cell lines (MAC-T cells) were investigated. Briefly, MAC-T cells exposed or free to H₂O₂ were incubated with different combinations of leucine and isoleucine. The cellular relative proliferation rate and viability, oxidative stress indicators, and inflammatory factors were determined by specific commercial kits. The genes related to barrier functions was measured by real-time quantitative PCR. The protein expression differences were explored by 4D label-free quantitative proteomic analyses and validated by parallel reaction monitoring. The results revealed that leucine and isoleucine increased cell proliferation, total antioxidant status (TAS), and the relative mRNA expression of occludin, as well as decreased malondialdehyde (MDA), total oxidant status (TOS)/TAS, IL-6, IL-1β, and TOS. When leucine and isoleucine were combined, MDA, TOS/TAS, and the relative mRNA expression levels of claudin-1, occludin, and zonula occludens-1 increased when compared to leucine or isoleucine alone. Proteomics analyses revealed that leucine significantly upregulated the propanoate metabolism; valine, leucine, and isoleucine degradation; and thermogenesis pathways, whereas isoleucine significantly upregulated the peroxisome and propanoate metabolism pathways. In conclusion, leucine protected MAC-T cells from H₂O₂-induced oxidative stress by generating more ATP to supplement energy demands, and isoleucine improved the deficit in peroxisome transport and promoted acetyl-CoA production. The findings of this study enhance our understanding of the protective mechanisms of leucine and isoleucine against oxidative damage.

Gamma-Aminobutyrate Transaminase Protects against Lipid Overload-Triggered Cardiac Injury in Mice

Lipid overload contributes to cardiac complications of diabetes and obesity. However, the underlying mechanisms remain obscure. This study investigates the role of gamma-aminobutyrate transaminase (ABAT), the key enzyme involved in the catabolism of γ-aminobutyric acid (GABA), in lipid overload-induced cardiac injury. Microarray revealed a down-regulation of ABAT mRNA expression in high fat diet (HFD)-fed mouse hearts, which correlated with a reduction in ABAT protein level and its GABA catabolic activity. Transgenic mice with cardiomyocyte-specific ABAT over-expression (Tg-ABAT/tTA) were generated to determine the role of ABAT in lipid overload-induced cardiac injury. Feeding with a HFD to control mice for 4 months reduced ATP production and the mitochondrial DNA copy number, and induced myocardial oxidative stress, hypertrophy, fibrosis and dysfunction. Such pathological effects of HFD were mitigated by ABAT over-expression in Tg-ABAT/tTA mice. In cultured cardiomyocytes, palmitate increased mitochondrial ROS production, depleted ATP production and promoted apoptosis, all of which were attenuated by ABAT over-expression. With the inhibition of ABAT’s GABA catabolic activity, the protective effects of ABAT remained unchanged in palmitate-induced cardiomyocytes. Thus, ABAT protects the mitochondrial function in defending the heart against lipid overload-induced injury through mechanisms independent of its GABA catabolic activity, and may represent a new therapeutic target for lipid overload-induced cardiac injury.

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

Clear cell renal cell carcinoma (ccRCC) is the most common subtype of renal cell carcinoma. Redox metabolism has been recognized as the hallmark of cancer. But the concrete role of redox-related genes in patient stratification of ccRCC remains unknown. Herein, we aimed to characterize the molecular features of ccRCC based on the redox gene expression profiles from The Cancer Genome Atlas. Differentially expressed redox genes (DERGs) and vital genes in metabolism regulation were identified and analyzed in the ccRCC. Consensus clustering was performed to divide patients into three clusters (C1, C2, and C3) based on 139 redox genes with median FPKM value > 1. We analyzed the correlation of clusters with clinicopathological characteristics, immune infiltration, gene mutation, and response to immunotherapy. Subclass C1 was metabolic active with moderate prognosis and associated with glucose, lipid, and protein metabolism. C2 had intermediate metabolic activity with worse prognosis and correlated with more tumor mutation burden, neoantigen, and aneuploidy, indicating possible drug sensitivities towards immune checkpoint inhibitors. Metabolic exhausted subtype C3 showed high cytolytic activity score, suggesting better prognosis than C1 and C2. Moreover, the qRT-PCR was performed to verify the expression of downregulated DERGs including ALDH6A1, ALDH1L1, GLRX5, ALDH1A3, and GSTM3, and upregulated SHMT1 in ccRCC. Overall, our study provides an insight into the characteristics of molecular classification of ccRCC patients based on redox genes, thereby deepening the understanding of heterogeneity of ccRCC and allowing prediction of prognosis of ccRCC patients.

Long Non-coding RNA DANCR in Cancer: Roles, Mechanisms, and Implications

Long non-coding RNA (lncRNA) DANCR (also known as ANCR)—differentiation antagonizing non-protein coding RNA, was first reported in 2012 to suppress differentiation of epithelial cells. Emerging evidence demonstrates that DANCR is a cancer-associated lncRNA abnormally expressed in many cancers (e.g., lung cancer, gastric cancer, breast cancer, hepatocellular carcinoma). Increasing studies suggest that the dysregulation of DANCR plays critical roles in cancer cell proliferation, apoptosis, migration, invasion, and chemoresistance in vitro and tumor growth and metastasis in vivo. Mechanistic analyses show that DANCR can serve as miRNA sponges, stabilize mRNAs, and interact with proteins. Recent research reveals that DANCR can be detected in many body fluids such as serum, plasma, and exosomes, providing a quick and convenient method for cancer monitor. Thus DANCR can be used as a promising diagnostic and prognostic biomarker and therapeutic target for various types of cancer. This review focuses on the role and mechanism of DANCR in cancer progression with an emphasis on the clinical significance of DANCR in human cancers.

Prognostic Value of Metabolism-Related Genes and Immune Infiltration in Clear Cell Renal Cell Carcinoma

Background

Clear cell renal cell carcinoma (ccRCC) is one of the most prevalent cancers. Thus, it is warranted to detect the status of metabolism-related genes (MRGs) and infiltrating immune cells in ccRCC progression for the prognosis of ccRCC. This research was designed to establish and verify the prognostic signature of ccRCC using MRGs. In addition, we investigated the potential link between the relative proportion of tumor infiltrated immune cells (TIICs) and ccRCC prognosis.

Methods

Sequencing data of metabolism-related gene sets in ccRCC cases were obtained from The Cancer Genome Atlas database (TCGA) and Gene Expression Omnibus Database (GEO). The R Programming Language software packages were applied for differential analysis of MRGs. First, a univariate Cox regression model was applied to determine the MRGs linked with overall survival (OS). Then, the multivariate Cox regression model was applied to establish the prognostic signature. Finally, the CIBERSORT algorithm was used to determine the proportion of TIICs.

Results

Overall, 286 differentially expressed MRGs were identified in the TCGA dataset. Univariate and multivariate Cox regression models were applied to develop a prognostic signature with six MRGs. The predictive capability of the prognostic signature was further verified by TCGA and GEO database. In addition, RS positively correlated with memory B cells, plasma cells, activated memory CD4+ T cells, follicular helper T cells, regulatory T cells, CD8+ T cells, and M0 macrophages, and were negatively associated with resting memory CD4+ T cells, resting dendritic cells, activated dendritic cells, M2 macrophages, monocytes, resting mast cells, and eosinophils.

Conclusion

Herein, a prognostic signature was developed using MRGs for ccRCC prognosis. The proportion of 22 TIICs in ccRCC and the association between TIICs and clinical outcomes were also determined. The identified genes and cells could guide future targeted therapy and immunotherapy.

A Robust Panel Based on Mitochondrial Localized Proteins for Prognostic Prediction of Lung Adenocarcinoma

Due to high energy and material metabolism requirements, mitochondria are frequently active in tumor cells. Our study found that the high energy metabolism status is positively correlated with the poor prognosis of patients with lung adenocarcinoma. We constructed a scoring system (mitoRiskscore) based on the gene expression of specific mitochondrial localized proteins through univariate and LASSO cox regression. It has been shown that high mitoRiskscore was correlated with a shorter survival time after surgery in patients with lung adenocarcinoma. Compared with the typical TNM grading system, the mitoRiskscore gene panel had higher prediction accuracy. A vast number of external verification results ensured its universality. Additionally, the mitoRiskscore could evaluate the metabolic pattern and chemotherapy sensitivity of the tumor samples. Lung adenocarcinoma with higher mitoRiskscore was more active in glycolysis, and oxidative phosphorylation expression of proliferation-related pathway genes was also significantly upregulated. In contrast, patients with low mitoRiskscore had similar metabolic patterns to normal tissues. In order to improve the accuracy of prediction ability and promote clinical usage, we developed a nomogram that combined mitoRiskscore and clinical prognostic factors to predict the 3-year, 5-year, and 10-year survival rates of patients. We also performed in vitro experiments to verify the function of the key genes in the mitoRiskscore panel. In conclusion, the mitoRiskscore scoring system may assist clinicians to judge the postoperative survival rate and chemotherapy of patients with lung adenocarcinoma.

Pan-cancer Analysis of NEDD4L and Its Tumor Suppressor Effects in Clear Cell Renal Cell Carcinoma

The expression level of NEDD4L, an E3 ubiquitin ligase, has changed significantly in human cancers. In this study, we aimed to study the expression of NEDD4L in pan-carcinoma and its function in malignant tumors. We analyzed the gene expression level of NEDD4L in pan-cancer from The Cancer Genome Atlas (TCGA) microarray data set, the correlation between gene expression and overall survival, disease-specific survival, and tumor immune microenvironment changes. NEDD4L expression changes in half of the cancer types. Low expression of NEDD4L gene predicts poor overall survival and disease-specific survival (DSS) in renal clear cell carcinoma (KIRC) and renal chromophobe cell carcinoma (KIRP). NEDD4L is negatively related to interstitial cell infiltration and immune cell infiltration in most common cancers. Furthermore, the low expression of NEDD4L was verified in our clear cell renal cell carcinoma (ccRCC) clinical tissues. In ccRCC cells, NEDD4L overexpression significantly reduced cell proliferation and migration. In the functional analysis, we proved that NEDD4L could inhibit ERBB3 and MAPK signaling pathways. When cells are deficient in nutrition, NEDD4L promoted the degradation of the autophagy regulatory protein ULK1. Our study provides novel insights into the role of NEDD4L in pan-cancer. NEDD4L may play a tumor suppressor effect in ccRCC, through tumor immune regulation and ubiquitination of key intracellular kinases.

Medulloblastoma uses GABA transaminase to survive in the cerebrospinal fluid microenvironment and promote leptomeningeal dissemination

Medulloblastoma (MB) is a malignant pediatric brain tumor arising in the cerebellum. Although abnormal GABAergic receptor activation has been described in MB, studies have not yet elucidated the contribution of receptor-independent GABA metabolism to MB pathogenesis. We find primary MB tumors globally display decreased expression of GABA transaminase (ABAT), the protein responsible for GABA metabolism, compared with normal cerebellum. However, less aggressive WNT and SHH subtypes express higher ABAT levels compared with metastatic G3 and G4 tumors. We show that elevated ABAT expression results in increased GABA catabolism, decreased tumor cell proliferation, and induction of metabolic and histone characteristics mirroring GABAergic neurons. Our studies suggest ABAT expression fluctuates depending on metabolite changes in the tumor microenvironment, with nutrient-poor conditions upregulating ABAT expression. We find metastatic MB cells require ABAT to maintain viability in the metabolite-scarce cerebrospinal fluid by using GABA as an energy source substitute, thereby facilitating leptomeningeal metastasis formation.

Controversial roles of hepatocyte nuclear receptor 4 α on tumorigenesis

Hepatocyte nuclear receptor 4 α (HNF4α) is known to be a master transcription regulator of gene expression in multiple biological processes, particularly in liver development and liver function. To date, the function of HNF4α in human cancers has been widely investigated; however, the critical roles of HNF4α in tumorigenesis remain unclear. Numerous controversies exist, even in studies from different research groups but on the same type of cancer. In the present review, the critical roles of HNF4α in tumorigenesis will be summarized and discussed. Furthermore, HNF4α expression profile and alterations will be examined by pan-cancer analysis through bioinformatics, in order to provide a better understanding of the functional roles of this gene in human cancers.

Identification and validation of a two-gene metabolic signature for survival prediction in patients with kidney renal clear cell carcinoma

Metabolic reprogramming contributes to the high mortality of advanced stage kidney renal clear cell carcinoma (KIRC), the most common renal cancer subtype. This study aimed to identify a metabolism-related gene (MRG) signature to improve survival prediction in KIRC patients. We downloaded RNA sequencing data and corresponding clinical information for KIRC and control samples from The Cancer Genome Atlas database and identified, based on an MRG dataset in the Molecular Signatures Database, 123 MRGs with differential expression in KIRC. Following Cox regression analysis and least absolute shrinkage and selection operator selection, RRM2 and ALDH6A1 were identified as prognosis-related genes and used to construct a prognostic signature with independent prognostic significance. After risk score-based patient separation, stratified survival analysis indicated that high-risk patients showed poorer overall survival than low-risk patients. We then constructed a clinical nomogram that showed a concordance index of 0.774 and good performance based upon calibration curves. Gene set enrichment analysis revealed several metabolic pathways significantly enriched in the target genes. The two-gene metabolic signature identified herein may represent a highly valuable tool for KIRC prognosis prediction, and might also help identify new metabolism-related biomarkers and therapeutic targets for KIRC.

BART Cancer: a web resource for transcriptional regulators in cancer genomes

Dysregulation of gene expression plays an important role in cancer development. Identifying transcriptional regulators, including transcription factors and chromatin regulators, that drive the oncogenic gene expression program is a critical task in cancer research. Genomic profiles of active transcriptional regulators from primary cancer samples are limited in the public domain. Here we present BART Cancer (bartcancer.org), an interactive web resource database to display the putative transcriptional regulators that are responsible for differentially regulated genes in 15 different cancer types in The Cancer Genome Atlas (TCGA). BART Cancer integrates over 10000 gene expression profiling RNA-seq datasets from TCGA with over 7000 ChIP-seq datasets from the Cistrome Data Browser database and the Gene Expression Omnibus (GEO). BART Cancer uses Binding Analysis for Regulation of Transcription (BART) for predicting the transcriptional regulators from the differentially expressed genes in cancer samples compared to normal samples. BART Cancer also displays the activities of over 900 transcriptional regulators across cancer types, by integrating computational prediction results from BART and the Cistrome Cancer database. Focusing on transcriptional regulator activities in human cancers, BART Cancer can provide unique insights into epigenetics and transcriptional regulation in cancer, and is a useful data resource for genomics and cancer research communities.

Identification of novel prognostic biomarkers in renal cell carcinoma

Objective: To identify novel prognostic biomarkers in renal cell carcinoma (RCC).

Results: 12 coding genes and one miRNA were finally identified as prognostic biomarkers. All of them were related to a poor prognosis. Lower expression levels of the coding genes were observed in higher clinical stages. Prognostic signatures including 7 biomarkers were identified. Patients in the high-risk group had worse survival than those in the low-risk group. The areas under the curves in different years indicated that it was a valuable signature in prognosis. It was found that elevated WDR72 inhibited the survival and invasion of 786-O and 769P cells in vitro.

Conclusions: Thirteen prognostic biomarkers of RCC were identified. Among them, 7 biomarkers comprised a signature to evaluate the RCC prognosis. WDR72 was a cancer suppressor and a potential therapeutic target in RCC.

Methods: Differentially expressed genes/miRNAs (DEGs/DEMs) and prognosis-related genes/miRNAs were acquired from public database. Prognostic biomarkers were identified by overlapping the significant DEGs/DEMs and prognosis-related genes/miRNAs. The associations between these biomarkers and the clinical stages were analyzed. All of these prognostic biomarkers were further investigated with multi-variable Cox regression. Finally, the inhibitory effect of WDR72 on the growth and invasion of RCC cells was studied.

A Targeted Bioinformatics Assessment of Adrenocortical Carcinoma Reveals Prognostic Implications of GABA System Gene Expression

Adrenocortical carcinoma (ACC) is a rare but deadly cancer for which few treatments exist. Here, we have undertaken a targeted bioinformatics study of The Cancer Genome Atlas (TCGA) ACC dataset focusing on the 30 genes encoding the γ-aminobutyric acid (GABA) system—an under-studied, evolutionarily-conserved system that is an emerging potential player in cancer progression. Our analysis identified a subset of ACC patients whose tumors expressed a distinct GABA system transcriptome. Transcript levels of ABAT (encoding a key GABA shunt enzyme), were upregulated in over 40% of tumors, and this correlated with several favorable clinical outcomes including patient survival; while enrichment and ontology analysis implicated two cancer-related biological pathways involved in metastasis and immune response. The phenotype associated with ABAT upregulation revealed a potential metabolic heterogeneity among ACC tumors associated with enhanced mitochondrial metabolism. Furthermore, many GABA_A receptor subunit-encoding transcripts were expressed, including two (GABRB2 and GABRD) prognostic for patient survival. Transcripts encoding GABA_B receptor subunits and GABA transporters were also ubiquitously expressed. The GABA system transcriptome of ACC tumors is largely mirrored in the ACC NCI-H295R cell line, suggesting that this cell line may be appropriate for future functional studies investigating the role of the GABA system in ACC cell growth phenotypes and metabolism.

Identification of Hub Genes Associated With Hepatocellular Carcinoma Using Robust Rank Aggregation Combined With Weighted Gene Co-expression Network Analysis

Background

Bioinformatics provides a valuable tool to explore the molecular mechanisms underlying pathogenesis of hepatocellular carcinoma (HCC). To improve prognosis of patients, identification of robust biomarkers associated with the pathogenic pathways of HCC remains an urgent research priority.

Methods

We employed the Robust Rank Aggregation method to integrate nine qualified HCC datasets from the Gene Expression Omnibus. A robust set of differentially expressed genes (DEGs) between tumor and normal tissue samples were screened. Weighted gene co-expression network analysis was applied to cluster DEGs and the key modules related to clinical traits identified. Based on network topology analysis, novel risk genes derived from key modules were mined and biological verification performed. The potential functions of these risk genes were further explored with the aid of miRNA–mRNA regulatory networks. Finally, the prognostic ability of these genes was assessed by constructing a clinical prediction model.

Results

Two key modules showed significant association with clinical traits. In combination with protein–protein interaction analysis, 29 hub genes were identified. Among these genes, 19 from one module showed a pattern of upregulation in HCC and were associated with the tumor node metastasis stage, and 10 from the other module displayed the opposite trend. Survival analyses indicated that all these genes were significantly related to patient prognosis. Based on the miRNA-mRNA regulatory network, 29 genes strongly linked to tumor activity were identified. Notably, five of the novel risk genes, ABAT, DAO, PCK2, SLC27A2, and HAO1, have rarely been reported in previous studies. Gene set enrichment analysis for each gene revealed regulatory roles in proliferation and prognosis of HCC. Least absolute shrinkage and selection operator regression analysis further validated DAO, PCK2, and HAO1 as prognostic factors in an external HCC dataset.

Conclusion

Analysis of multiple datasets combined with global network information presents a successful approach to uncover the complex biological mechanisms of HCC. More importantly, this novel integrated strategy facilitates identification of risk hub genes as candidate biomarkers for HCC, which could effectively guide clinical treatments.