Identification of Key Biomarkers and Potential Molecular Mechanisms in Renal Cell Carcinoma by Bioinformatics Analysis

Long Non-Coding RNA TPTEP1 Exerts Tumor Suppressive Functions via Sequestering miR-4295 to Regulate Growth Arrest and DNA Damage-Inducible 45α Expression in Acute Myeloid Leukemia

Introduction

Recent evidences show that long non-coding RNA (lncRNA) plays an essential role in physiology and pathophysiology. The purpose of this study was to determine the role and its potential underlying mechanisms of the lncRNA transmembrane phosphatase with tensin homology pseudogene 1 (TPTEP1) in acute myeloid leukemia (AML).

Methods

We detected the TPTEP1 and miR-4295 expression levels in AML cells. The vitro effects of TPTEP1 and miR-4295 on AML cells were analyzed. The correlation between miR-4295 and TPTEP1 or Growth arrest and DNA damage-inducible 45α (GADD45α) was confirmed by a luciferase reporter assay and RNA immunoprecipitation. The expression of GADD45α was investigated by Western blotting.

Results

TPTEP1 was down-regulated in AML cell lines and AML patients. Ectopic expression of TPTEP1 inhibited AML cells proliferation while promoted cells apoptosis. And we found that silencing miR-4295 produced the similar effect of TPTEP1 overexpression. TPTEP1 regulated the malignant behavior of AML cells by binding to miR-4295. In addition, overexpression of TPTEP up-regulated GADD45α, a direct target of miR-4295 which play a suppressive role in AML cells. Moreover, when AML cell lines were treated with a DNA methylation inhibitor, TPTEP1 expression was up-regulated.

Conclusion

This study reveals that the lncRNA TPTEP1 regulates the expression of GADD45α by sponging miR-4295 in AML cells, which may represent a novel therapeutic target for AML.

Identification of key biomarker genes in liver hepatocellular carcinoma and kidney renal clear cell carcinoma progression: A shared high-throughput screening and molecular docking method with potentials for targeted therapeutic interventions

BACKGROUND AND OBJECTIVES

Liver Hepatocellular Carcinoma (LIHC) and Kidney Renal Clear Cell Carcinoma (KIRC) are leading causes of cancer death worldwide, but their early detections remain hindered by a lack of genetic markers. Our study aims to find prospective biomarkers that could serve as prognostic indicators for efficient drug candidates for KIRC and LIHC treatment.

METHODS

To detect differentially expressed genes (DEGs), four datasets were used: GSE66271 and GSE213324 for KIRC, and GSE135631 and GSE202853 for LIHC. Visualization of DEGs was done using heatmaps, volcano plots, and Venn diagrams. Hub genes were identified via PPI analysis and the cytoHubba plugin in Cytoscape. Their expression was evaluated using box plots, stage plots, and survival plots for prognostic assessment via GEPIA2. Molecular docking with PyRx's AutoDock Vina identified optimal binding interactions between compounds and proteins. Pharmacokinetic and toxicity analyses reinforced the drug-likeness and safety of these compounds.

RESULTS

In this study, 47 DEGs were identified, with the top 10 hub genes being TOP2A, BUB1, PTTG1, CCNB2, NUSAP1, KIF20A, BIRC5, RRM2, NDC80 and CDC45, chosen for their high MCC scores. Data mining revealed a correlation between TOP2A expression and clinical survival outcomes in KIRC and LIHC patients. Docking studies of the TOP2A structure identified a promising compound from Andrographis paniculata with high binding energy and interactions with TOP2A. Pharmacokinetic and toxicity assessments support its potential as a drug candidate.

CONCLUSION

Our study emphasizes TOP2A's prognostic significance in KIRC and LIHC and recognizes Andrographis paniculata compound as potential therapeutics, offering prospective for enhanced treatment and patient outcomes in these cancers.

Long Noncoding RNA E2F1 Messenger RNA Stabilizing Factor (EMS) Promotes Sorafenib Resistance in Renal Cell Carcinoma by Regulating miR-363-3p and Dual-Specificity Phosphatase 10 Expression

Renal cell carcinoma (RCC) is a common kidney disease associated with high mortality. Sorafenib is a protein kinase inhibitor that targets multiple kinases and is used for treating different cancers, including RCC. However, sorafenib resistance in patients with RCC hampers its use. Therefore, elucidating the molecular mechanisms underlying sorafenib resistance in RCC and developing novel therapeutic strategies to overcome drug resistance are vital. In this study, we found that the expression level of the long noncoding RNA (lncRNA) E2F1 messenger RNA stabilizing factor (EMS) was significantly higher in sorafenib-resistant RCC tissues and cell lines than in sorafenib-sensitive RCC tissues and cell lines. lncRNA EMS knockdown improved the sensitivity of sorafenib-resistant RCC cells to sorafenib treatment, as evidenced by decreased cell proliferation and increased apoptosis. Additionally, lncRNA EMS silencing combined with sorafenib treatment markedly inhibited RCC tumor development in vivo. Moreover, it was systematically shown that lncRNA EMS sponged miR-363-3p, whose expression was decreased in sorafenib-resistant RCC. Notably, miR-363-3p negatively regulated the expression of dual-specificity phosphatase 10 (DUSP10) by targeting its 3'-UTR. Furthermore, miR-363-3p overexpression restored sorafenib sensitivity, whereas upregulated DUSP10 expression promoted sorafenib resistance in sorafenib-resistant cell lines. In conclusion, the lncRNA EMS/miR-363-3p/DUSP10 axis regulates sorafenib resistance in RCC, and these molecules are promising biomarkers and therapeutic targets for patients with sorafenib-resistant RCC.

Assessing Creatine-Related Gene Expression in Kidney Disease: Can Available Data Give Insights into an Old Discussion?

The impact of creatine supplementation on individuals with kidney disease or pathological conditions with an increased risk of developing kidney dysfunction remains an active discussion. However, the literature on gene expression related to cellular creatine uptake and metabolism under altered renal function is scarce. Therefore, the present study utilized comprehensive bioinformatics analysis to evaluate the expression of creatine-related genes and to establish their relationships to normal and disturbed renal conditions. We identified 44 genes modulated explicitly in response to creatine exposure from a gene enrichment analysis, including IGF1, SLC2A4, and various creatine kinase genes. The analysis revealed associations with metabolic processes such as amino acid metabolism, indicating a connection between creatine and tissue physiology. Using the Genotype-Tissue Expression Portal, we evaluated their basal tissue-specific expression patterns in kidney and pancreas tissues. Then, we selected several pieces of Gene Expression Omnibus (GEO) transcriptomic data, estimated their expression values, and established relationships to the creatine metabolism pathways and regulation, shedding light on the potential regulatory roles of creatine in cellular processes during kidney diseases. These observations also highlight the connection between creatine and tissue physiology, emphasizing the importance of understanding the balance between endogenous creatine synthesis and creatine uptake, particularly the roles of genes such as GATM, GAMT, SLC6A8, and IGF1, under several kidney dysfunction conditions. Overall, the available data in the biological databases can provide new insights and directions into creatine's effects and role in renal function.

Pan-cancer analysis reveals the prognostic gene CASR suppresses tumor progression and epithelial-mesenchymal transition in renal clear cell carcinoma

Calcium-sensing receptor (CASR), primarily found in the parathyroid gland and other tissues, plays a crucial role in sensing and regulating extracellular calcium, which was also aberrantly expressed in human tumors. Nevertheless, a comprehensive analysis of CASR in pan-cancer has yet to be conducted. To gain a better understanding of CASR in pan-cancer, data profiles on CASR cancers were collected from TCGA database. The expression level, clinical significance, prognostic value, and potential mechanisms of CASR in pan-cancer were analyzed via multiple public databases. The functional assays were conducted using human kidney renal clear cell carcinoma (KIRC) cell lines, clinical samples, and nude mice. Our research revealed that the abnormal expression of CASR was found in a variety of tumors. The expression and mutation of CASR were significantly associated with tumor prognosis and stage. Pathway analyses suggested that CASR was involved in the epithelial-mesenchymal transition (EMT) progress. Besides, CASR expression was correlated with immune inhibitory genes and immunotherapy in cancers. Particularly in KIRC, we established that CASR mRNA and protein levels were downregulated in clinical samples and cell lines. Moreover, a Cox regression analysis revealed that CASR was an independent prognostic factor in both TCGA-KIRC samples and clinical samples from our center. In vitro and in vivo experiments revealed that blocking CASR with lentivirus could suppress tumor growth and invasion, and EMT progress in KIRC cells. In summary, our study provides a comprehensive bioinformatic analysis of CASR in pan-cancer, offering deeper insights into its function and the EMT mechanism in KIRC, warranting further investigation.

A novel immune-related gene signature for predicting immunotherapy outcomes and survival in clear cell renal cell carcinoma

Clear cell renal carcinoma (ccRCC) is one of the most common cancers worldwide. In this study, a new model of immune-related genes was developed to predict the overall survival and immunotherapy efficacy in patients with ccRCC. Immune-related genes were obtained from the ImmPort database. Clinical data and transcriptomics of ccRCC samples were downloaded from GSE29609 and The Cancer Genome Atlas. An immune-related gene-based prognostic model (IRGPM) was developed using the least absolute shrinkage and selection operator regression algorithm and multivariate Cox regression. The reliability of the developed models was evaluated by Kaplan-Meier survival curves and time-dependent receiver operating characteristic curves. Furthermore, we constructed a nomogram based on the IRGPM and multiple clinicopathological factors, along with a calibration curve to examine the predictive power of the nomogram. Overall, this study investigated the association of IRGPM with immunotherapeutic efficacy, immune checkpoints, and immune cell infiltration. Eleven IRGs based on 528 ccRCC samples significantly associated with survival were used to construct the IRGPM. Remarkably, the IRGPM, which consists of 11 hub genes (SAA1, IL4, PLAUR, PLXNB3, ANGPTL3, AMH, KLRC2, NR3C2, KL, CSF2, and SEMA3G), was found to predict the survival of ccRCC patients accurately. The calibration curve revealed that the nomogram developed with the IRGPM showed high predictive performance for the survival probability of ccRCC patients. Moreover, the IRGPM subgroups showed different levels of immune checkpoints and immune cell infiltration in patients with ccRCC. IRGPM might be a promising biomarker of immunotherapeutic responses in patients with ccRCC. Overall, the established IRGPM was valuable for predicting survival, reflecting the immunotherapy response and immune microenvironment in patients with ccRCC.

Identification of novel biomarkers linking depressive disorder and Alzheimer's disease based on an integrative bioinformatics analysis

BACKGROUND

Previous reports revealed that a history of major depressive disorder (MDD) increased the risk of Alzheimer's disease (AD). The immune disorder is associated with MDD and AD pathophysiology. We aimed to identify differentially expressed immune-related genes (DEIRGs) that are involved in the pathogenesis of MDD and AD.

METHODS

We downloaded mRNA expression profiles (GSE76826 and GSE5281) from the Gene Expression Omnibus (GEO) database. The R software was used to identify DEIRGs for the two diseases separately. Functional enrichment analysis and PPI network of DEIRGs were performed. Finally, the relationship between shared DEIRGs and immune infiltrates of AD and MDD were analyzed, respectively.

RESULTS

A total of 121 DEIRGs linking AD and MDD were identified. These genes were significantly enriched in immune-related pathways, such as the JAK-STAT signaling pathway, regulation of chemotaxis, chemotaxis, cytokine-cytokine receptor interaction, and primary immunodeficiency. Furthermore, three shared DEIRGs (IL1R1, CHGB, and NRG1) were identified. Correlation analysis between DEIRGs and immune cells revealed that IL1R1 and NRG1 had a negative or positive correlation with some immune cells both in AD and MDD.

CONCLUSION

Both DEIRGs and immune cell infiltrations play a vital role in the pathogenesis of AD and MDD. Our findings indicated that there are common genes and biological processes between MDD and AD, which provides a theoretical basis for the study of the comorbidity of MDD and AD.

Higher TYROBP and lower SOX6 as predictive biomarkers for poor prognosis of clear cell renal cell carcinoma: A pilot study

BACKGROUND

Clear cell renal carcinoma (ccRCC) is the most common subtype of renal cancer, accounting for approximately 75% of all histological types of renal cancer, and is the leading cause of death from renal cancer. However, the molecular mechanism of tyrosine kinase binding protein (TYROBP) and sex-determining region Y Box-6 (SOX6) in the ccRCC was not precise.

METHODS

Bioinformatics analysis was performed to explore the hub role of TYROBP and SOX6 on the ccRCC. A total of 6 patients with clear cell renal cell carcinoma (ccRCC) were recruited. HE staining was performed to observe the pathology result of ccRCC. Immunohistochemistry and Immunofluorescence assay was made to detect the protein expression of TYROBP. Total RNA was extracted using TRIzol to examine the mRNA expression of TYROBP via the Real time quantitative polymerase chain reaction. The strong correlation between the expression of TYROBP and the survival time of ccRCC patients was performed by the BP neural network and support vector machine.

RESULTS

Compared with the control group, the expression of SOX6 was downregulated in the samples with ccRCC. However, the expression of TYROBP was higher in the samples with ccRCC than in the control group. Compared with the patients with high SOX6 expression, the patients with low SOX6 expression have a poor survival prognosis (HR=0.39, P < .05). However, the patients with high TYROBP expression have a shorter survival time than the patients with low TYROBP expression (HR=1.66, P < .05). The genes related with TYROBP and SOX6 are mainly enriched in the regulation of cell activation, leukocyte activation, negative regulation of cell activation, myeloid leukocyte activation, positive regulation of response to external stimulus, immune response-regulating signaling pathway. The interaction between TYROBP, SOX6, and kidney neoplasms was drawn, and the inference score of TYROBP and SOX6 on the kidney neoplasms was high.

CONCLUSION

In conclusion, TYROBP is highly expressed in renal clear cell carcinoma, and when this molecule is highly expressed, the survival prognosis of renal carcinoma is poor. TYROBP and SOX6 may be potential targets for diagnosing and treating renal clear cell carcinoma.

High-dimension to high-dimension screening for detecting genome-wide epigenetic and noncoding RNA regulators of gene expression

MOTIVATION

The advancement of high-throughput technology characterizes a wide variety of epigenetic modifications and noncoding RNAs across the genome involved in disease pathogenesis via regulating gene expression. The high dimensionality of both epigenetic/noncoding RNA and gene expression data make it challenging to identify the important regulators of genes. Conducting univariate test for each possible regulator-gene pair is subject to serious multiple comparison burden, and direct application of regularization methods to select regulator-gene pairs is computationally infeasible. Applying fast screening to reduce dimension first before regularization is more efficient and stable than applying regularization methods alone.

RESULTS

We propose a novel screening method based on robust partial correlation to detect epigenetic and noncoding RNA regulators of gene expression over the whole genome, a problem that includes both high-dimensional predictors and high-dimensional responses. Compared to existing screening methods, our method is conceptually innovative that it reduces the dimension of both predictor and response, and screens at both node (regulators or genes) and edge (regulator-gene pairs) levels. We develop data-driven procedures to determine the conditional sets and the optimal screening threshold, and implement a fast iterative algorithm. Simulations and applications to long noncoding RNA and microRNA regulation in Kidney cancer and DNA methylation regulation in Glioblastoma Multiforme illustrate the validity and advantage of our method.

AVAILABILITY AND IMPLEMENTATION

The R package, related source codes and real datasets used in this article are provided at https://github.com/kehongjie/rPCor.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Linking Late Endosomal Cholesterol with Cancer Progression and Anticancer Drug Resistance

Cancer cells undergo drastic metabolic adaptions to cover increased bioenergetic needs, contributing to resistance to therapies. This includes a higher demand for cholesterol, which often coincides with elevated cholesterol uptake from low-density lipoproteins (LDL) and overexpression of the LDL receptor in many cancers. This implies the need for cancer cells to accommodate an increased delivery of LDL along the endocytic pathway to late endosomes/lysosomes (LE/Lys), providing a rapid and effective distribution of LDL-derived cholesterol from LE/Lys to other organelles for cholesterol to foster cancer growth and spread. LDL-cholesterol exported from LE/Lys is facilitated by Niemann–Pick Type C1/2 (NPC1/2) proteins, members of the steroidogenic acute regulatory-related lipid transfer domain (StARD) and oxysterol-binding protein (OSBP) families. In addition, lysosomal membrane proteins, small Rab GTPases as well as scaffolding proteins, including annexin A6 (AnxA6), contribute to regulating cholesterol egress from LE/Lys. Here, we summarize current knowledge that links upregulated activity and expression of cholesterol transporters and related proteins in LE/Lys with cancer growth, progression and treatment outcomes. Several mechanisms on how cellular distribution of LDL-derived cholesterol from LE/Lys influences cancer cell behavior are reviewed, some of those providing opportunities for treatment strategies to reduce cancer progression and anticancer drug resistance.

Functional deficiency of succinate dehydrogenase promotes tumorigenesis and development of clear cell renal cell carcinoma through weakening of ferroptosis

Clear cell renal cell carcinoma (ccRCC) is the most common subtype of renal carcinomas, with high mortality and poor prognoses worldwide. Succinate dehydrogenase (SDH) consists of four nuclear-encoded subunits and it is the only complex involved in both the tricarboxylic acid (TCA) cycle and oxidative phosphorylation (OXPHOS). Previous studies have shown decreased SDH activity in ccRCC. However, the role and underlying molecular mechanisms of SDH in ccRCC initiation and development remain unclear. In the present study, pan-cancer analysis of SDH gene expression was analyzed and the relationship between SDH gene expression and clinicopathological parameters was assessed using different databases. cBioPortal, UACLAN, and Tumor Immune Estimation Resource (TIMER) were subsequently utilized to analyze genetic alterations, methylation, and immune cell infiltration of SDH genes in ccRCC patients. We found SDHs were significantly downregulated in ccRCC tissues and correlated with ccRCC progression. Increased methylation and high SDH promoter mutation rates may be the cause of reduced expression of SDHs in ccRCC. Moreover, the interaction network showed that SDH genes were correlated with ferroptosis-related genes. We further demonstrated that SDH inhibition dampened oxidative phosphorylation, reduced ferroptotic events, and restored ferroptotic cell death, characterized by eliminated mitochondrial ROS levels, decreased cellular ROS and diminished peroxide accumulation. Collectively, this study provides new insights into the regulatory role of SDH in the carcinogenesis and progression of ccRCC, introducing a potential target for advanced antitumor therapy through ferroptosis.

Study on the Multitarget Mechanism and Active Compounds of Essential Oil from Artemisia argyi Treating Pressure Injuries Based on Network Pharmacology

In order to comprehensively explore multitarget mechanism and key active compounds of Artemisia argyi essential oil (AAEO) in the treatment of pressure injuries (PIs), we analyzed the biological functions and pathways involved in the intersection targets of AAEO and PIs based on network pharmacology, and the affinity of AAEO active compounds and core targets was verified by molecular docking finally. In our study, we first screened 54 effective components according to the relative content and biological activity. In total, 103 targets related to active compounds of AAEO and 2760 targets associated with PIs were obtained, respectively, and 50 key targets were overlapped by Venny 2.1.0. The construction of key targets-compounds network was achieved by the STRING database and Cytoscape 3.7.2 software. GO analysis from Matespace shows that GO results are mainly enriched in biological processes, including adrenergic receptor activity, neurotransmitter clearance, and neurotransmitter metabolic process. KEGG analysis by the David and Kobas website shows that the key targets can achieve the treatment on PIs through a pathway in cancer, PI3K-Akt signaling pathway, human immunodeficiency virus 1 infection, MAPK signaling pathway, Wnt signaling pathway, etc. In addition, molecular docking results from the CB-Dock server indicated that active compounds of AAEO had good activity docking with the first 10 key targets. In conclusion, the potential targets and regulatory molecular mechanisms of AAEO in the treatment of PIs were analyzed by network pharmacology and molecular docking. AAEO can cure PIs through the synergistic effect of multicomponent, multitarget, and multipathway, providing a theoretical basis and new direction for further study.

Collagen Family Genes Associated with Risk of Recurrence after Radiation Therapy for Vestibular Schwannoma and Pan-Cancer Analysis

Background

The safety of radiotherapy techniques in the treatment of vestibular schwannoma (VS) shows a high rate of tumor control with few side effects. Neuropeptide Y (NPY) may have a potential relevance to the recurrence of VS. Further research is still needed on the key genes that determine the sensitivity of VS to radiation therapy.

Materials and Methods

Transcriptional microarray data and clinical information data from VS patients were downloaded from GSE141801, and vascular-related genes associated with recurrence after radiation therapy for VS were obtained by combining information from MSigDB. Logistics regression was applied to construct a column line graph prediction model for recurrence status after radiation therapy. Pan-cancer analysis was also performed to investigate the cooccurrence of these genes in tumorigenesis.

Results

We identified eight VS recurrence-related genes from the GSE141801 dataset. All of these genes were highly expressed in the VS recurrence samples. Four collagen family genes (COL5A1, COL3A1, COL4A1, and COL15A1) were further screened, and a model was constructed to predict the risk of recurrence of VS. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses revealed that these four collagen family genes play important roles in a variety of biological functions and cellular pathways. Pan-cancer analysis further revealed that the expression of these genes was significantly heterogeneous across immune phenotypes and significantly associated with immune infiltration. Finally, Neuropeptide Y (NPY) was found to be significantly and negatively correlated with the expression of COL5A1, COL3A1, and COL4A1.

Conclusions

Four collagen family genes have been identified as possible predictors of recurrence after radiation therapy for VS. Pan-cancer analysis reveals potential associations between the pathogenesis of VS and other tumorigenic factors. The relevance of NPY to VS was also revealed for the first time.

Integrated analyses of long noncoding RNAs and mRNAs in the progression of breast cancer

Objective

The objective was to explore the expression and potential functions of long noncoding RNA (lncRNA) and mRNAs in human breast cancer (BC).

Methods

Differentially expressed lncRNAs and mRNAs were identified and annotated in BC tissues by using the Agilent human lncRNA assay (Agilent Technologies, Santa Clara, CA, USA) and RNA sequencing. After identification of lncRNAs and mRNAs through quantitative reverse transcription polymerase chain reaction, we conducted a series of functional experiments to confirm the effects of knockdown of one lncRNA, TCONS_00029809, on the progression of BC.

Results

We discovered 238 lncRNAs and 200 mRNAs that were differentially expressed in BC tissues and para-carcinoma tissue. We showed that differentially expressed mRNAs were related to biological adhesion and biological regulation and mainly enriched in cytokine-cytokine receptor interaction, metabolic pathways, and PI3K-Akt signaling pathway. We created a protein–protein interaction network to analyze the proteins enriched in these pathways. We demonstrated that silencing of TCONS_00029809 remarkably inhibited proliferation, invasion, and migration of BC cells, and accelerated their apoptosis.

Conclusions

We identified a large number of differentially expressed lncRNAs and mRNAs, which provide data useful in understanding BC carcinogenesis. The lncRNA TCONS_00029809 may be involved in the development of BC.

A united risk model of 11 immune‑related gene pairs and clinical stage for prediction of overall survival in clear cell renal cell carcinoma patients

Clear cell renal cell carcinoma (ccRCC) is the most common subtype of renal cancer. Currently, we lack effective risk models for the prognosis of ccRCC patients. Given the significant role of cancer immunity in ccRCC, we aimed to establish a novel united risk model including clinical stage and immune-related gene pairs (IRGPs) to assess the prognosis. The gene expression profile and clinical data of ccRCC patients from The Cancer Genome Atlas and Arrayexpress were divided into training cohort (n = 381), validation cohort 1 (n = 156), and validation cohort 2 (n = 101). Through univariate Cox regression analysis and Least Absolute Shrinkage and Selection Operator analysis, 11 IRGPs were obtained. After further analysis, it was found that clinical stage could be an independent prognostic factor; hence, we used it to construct a united prognostic model with 11 IRGPs. Based on this model, patients were divided into high-risk and low-risk groups. In Kaplan–Meier analysis, a significant difference was observed in overall survival (OS) among all three cohorts (p < 0.001). The calibration curve revealed that the signature model is in high accordance with the observed values of each data cohort. The 1-year, 3-year, and 5-year receiver operating characteristic curves of each data cohort showed better performance than only IRGP signatures. The results of immune infiltration analysis revealed significantly (p < 0.05) higher abundance of macrophages M0, T follicular helper cells, and other tumor infiltrating cells. In summary, we successfully established a united prognostic risk model, which can effectively assess the OS of ccRCC patients.

SREBP1 site 1 protease inhibitor PF-429242 suppresses renal cell carcinoma cell growth

Renal cell carcinoma (RCC) cells have increased lipogenesis and cholesterol synthesis. Sterol regulatory element-binding protein-1 (SREBP1) is cleaved by site 1 protease (S1P) to release the transcriptionally active amino-terminal domain. PF-429242 is a potent and competitive S1P inhibitor. We here tested its activity in RCC cells. In established and primary human RCC cells, PF-429242 potently inhibited cell proliferation, migration, and invasion. The S1P inhibitor provoked apoptosis activation in RCC cells. Furthermore, shRNA-mediated S1P silencing or CRISPR/Cas9-induced S1P knockout led to RCC cell growth inhibition and apoptosis activation. Conversely, ectopic overexpression of SREBP1 or S1P augmented RCC cell proliferation and migration. Daily i.v. injection of a single dose of PF-429242 robustly inhibited RCC xenograft growth in severe combined immunodeficiency mice. Additionally, intratumoral injection of S1P shRNA lentivirus inhibited RCC xenograft growth in mice. SREBP1, S1P, and its target gene low density lipoprotein receptor (LDLR) were significantly elevated in human RCC tissues. These results suggest that targeting S1P by PF-429242 inhibited RCC cell growth in vitro and in vivo.

Bioinformatics analysis of C3 and CXCR4 demonstrates their potential as prognostic biomarkers in clear cell renal cell carcinoma (ccRCC)

Background

The molecular prognostic biomarkers of clear cell renal cell carcinoma (ccRCC) are still unknown. We aimed at researching the candidate biomarkers and potential therapeutic targets of ccRCC.

Methods

Three ccRCC expression microarray datasets (include GSE14762, GSE66270 and GSE53757) were downloaded from the gene expression omnibus (GEO) database. The differentially expressed genes (DEGs) between ccRCC and normal tissues were explored. The potential functions of identified DEGs were analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). And then the protein - protein interaction network (PPI) was established to screen the hub genes. After that, the expressions of hub genes were identified by the oncomine database. The hub genes’ prognostic values of patients with ccRCC were analyzed by GEPIA database.

Results

A total of 137 DEGs were identified by utilizing the limma package and RRA method, including 63 upregulated genes and 74 downregulated genes. It is found that 137 DEGs were mainly enriched in 82 functional terms and 24 pathways in accordance with the research results. Thirteen highest-scoring genes were screened as hub genes (include 10 upregulated genes and 3 downregulated candidate genes) by utilizing the PPI network and module analysis. Through integrating the oncoming database and GEPIA database, the author found that C3 and CXCR4 are not only overexpressed in ccRCC, but also associated with the prognosis of ccRCC. Further results could reveal that patients with high C3 expression had a poor overall survival (OS), while patients with high CTSS and TLR3 expressions had a good OS; patients with high C3 and CXCR4 expressions had a poor disease-free survival (DFS), while ccRCC patients with high TLR3 expression had a good DFS.

Conclusion

These findings suggested that C3 and CXCR4 were the candidate biomarkers and potential therapeutic targets of ccRCC patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08525-w.

Diagnostic and Prognostic Significance of Keap1 mRNA Expression for Lung Cancer Based on Microarray and Clinical Information from Oncomine Database

We performed a bioinformatics analysis with validation by multiple databases, aiming to evaluate the diagnostic and prognostic value of Kelch-like ECH-associated protein 1 (Keap1) mRNA for lung cancer, and to explore possible mechanisms. Diagnostic performance of Keap1 mRNA was determined by receiver operating characteristic (ROC) curve analysis. Prognostic implication of Keap1 mRNA was estimated by Kaplan-Meier survival analysis. Co-expressed genes with both Keap1 and Nfe2L2 were identified by LinkedOmics. Mechanisms of Keap1-Nfe2L2-co-expressed genes underlying the pathogenesis of lung cancer were explored by function enrichment and pathway analysis. The ROC curve analysis determined a good diagnostic performance of Keap1 mRNA for lung squamous cell carcinoma (LUSC), with an area under the ROC curve (AUC) of 0.833, sensitivity of 72.7%, and specificity of 90.6% (P<0.001). Multivariate Cox regression recognized high Keap1 mRNA to be an independent risk factor of mortality for overall lung cancer [hazard ratio (HR): 11.034, P=0.044], but an independent antagonistic factor for lung adenocarcinoma (LUAD) (HR: 0.404, P<0.001). Validation by UALCAN and GEPIA supported Oncomine findings regarding the diagnostic value of Keap1 mRNA for LUSC, but denied its prognostic value. After screening, we identified 17 co-expressed genes with both Keap1 and Nfe2L2 for LUAD, and 22 for LUSC, mainly enriched in signaling pathway of oxidative stress-induced gene expression via Nrf2. In conclusion, Keap1 mRNA has a good diagnostic performance, but controversial prognostic efficacy for LUSC. The pathogenesis of lung cancer is associated with Keap1-Nfe2L2-co-expressed genes by signaling pathway of oxidative stress-induced gene expression via Nrf2.

The Choice of Candidates in Survival Markers Based on Coordinated Gene Expression in Renal Cancer

We aimed to identify and investigate genes that are essential for the development of clear cell renal cell carcinoma (ccRCC) and sought to shed light on the mechanisms of its progression and create prognostic markers for the disease. We used real-time PCR to study the expression of 20 genes that were preliminarily selected based on their differential expression in ccRCC, in 68 paired tumor/normal samples. Upon ccRCC progression, seven genes that showed an initial increase in expression showed decreased expression. The genes whose expression levels did not significantly change during progression were associated mainly with metabolic and inflammatory processes. The first group included CA9, NDUFA4L2, EGLN3, BHLHE41, VWF, IGFBP3, and ANGPTL4, whose expression levels were coordinately decreased during tumor progression. This expression coordination and gene function is related to the needs of tumor development at different stages. Specifically, the high correlation coefficient of EGLN3 and NDUFA4L2 expression may indicate the importance of the coordinated regulation of glycolysis and mitochondrial metabolism. A panel of CA9, EGLN3, BHLHE41, and VWF enabled the prediction of survival for more than 3.5 years in patients with ccRCC, with a probability close to 90%. Therefore, a coordinated change in the expression of a gene group during ccRCC progression was detected, and a new panel of markers for individual survival prognosis was identified.

A Nomogram Combining a Four-Gene Biomarker and Clinical Factors for Predicting Survival of Melanoma

Background

Currently there is no effective prognostic indicator for melanoma, the deadliest skin cancer. Thus, we aimed to develop and validate a nomogram predictive model for predicting survival of melanoma.

Methods

Four hundred forty-nine melanoma cases with RNA sequencing (RNA-seq) data from TCGA were randomly divided into the training set I (n = 224) and validation set I (n = 225), 210 melanoma cases with RNA-seq data from Lund cohort of Lund University (available in GSE65904) were used as an external test set. The prognostic gene biomarker was developed and validated based on the above three sets. The developed gene biomarker combined with clinical characteristics was used as variables to develop and validate a nomogram predictive model based on 379 patients with complete clinical data from TCGA (Among 470 cases, 91 cases with missing clinical data were excluded from the study), which were randomly divided into the training set II (n = 189) and validation set II (n = 190). Area under the curve (AUC), concordance index (C-index), calibration curve, and Kaplan-Meier estimate were used to assess predictive performance of the nomogram model.

Results

Four genes, i.e., CLEC7A, CLEC10A, HAPLN3, and HCP5 comprise an immune-related prognostic biomarker. The predictive performance of the biomarker was validated using tROC and log-rank test in the training set I (n = 224, 5-year AUC of 0.683), validation set I (n = 225, 5-year AUC of 0.644), and test set I (n = 210, 5-year AUC of 0.645). The biomarker was also significantly associated with improved survival in the training set (P < 0.01), validation set (P < 0.05), and test set (P < 0.001), respectively. In addition, a nomogram combing the four-gene biomarker and six clinical factors for predicting survival in melanoma was developed in the training set II (n = 189), and validated in the validation set II (n = 190), with a concordance index of 0.736 ± 0.041 and an AUC of 0.832 ± 0.071.

Conclusion

We developed and validated a nomogram predictive model combining a four-gene biomarker and six clinical factors for melanoma patients, which could facilitate risk stratification and treatment planning.

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.

Metabolite Sensing GPCRs: Promising Therapeutic Targets for Cancer Treatment?

G-protein-coupled receptors constitute the most diverse and largest receptor family in the human genome, with approximately 800 different members identified. Given the well-known metabolic alterations in cancer development, we will focus specifically in the 19 G-protein-coupled receptors (GPCRs), which can be selectively activated by metabolites. These metabolite sensing GPCRs control crucial processes, such as cell proliferation, differentiation, migration, and survival after their activation. In the present review, we will describe the main functions of these metabolite sensing GPCRs and shed light on the benefits of their potential use as possible pharmacological targets for cancer treatment.

Targeting lipid droplet lysophosphatidylcholine for cisplatin chemotherapy

This study aims to explore lipidic mechanism towards low‐density lipoprotein receptor (LDLR)‐mediated platinum chemotherapy resistance. By using the lipid profiling technology, LDLR knockdown was found to increase lysosomal lipids and decrease membranous lipid levels in EOC cells. LDLR knockdown also down‐regulated ether‐linked phosphatidylethanolamine (PE‐O, lysosomes or peroxisomes) and up‐regulated lysophosphatidylcholine [LPC, lipid droplet (LD)]. This implies that the manner of using Lands cycle (conversion of lysophospholipids) for LDs might affect cisplatin sensitivity. The bioinformatics analyses illustrated that LDLR‐related lipid entry into LD, rather than an endogenous lipid resource (eg Kennedy pathway), controls the EOC prognosis of platinum chemotherapy patients. Moreover, LDLR knockdown increased the number of platinum‐DNA adducts and reduced the LD platinum amount. By using a manufactured LPC‐liposome‐cisplatin (LLC) drug, the number of platinum‐DNA adducts increased significantly in LLC‐treated insensitive cells. Moreover, the cisplatin content in LDs increased upon LLC treatment. Furthermore, lipid profiles of 22 carcinoma cells with differential cisplatin sensitivity (9 sensitive vs 13 insensitive) were acquired. These profiles revealed low storage lipid levels in insensitive cells. This result recommends that LD lipidome might be a common pathway in multiple cancers for platinum sensitivity in EOC. Finally, LLC suppressed both cisplatin‐insensitive human carcinoma cell training and testing sets. Thus, LDLR‐platinum insensitivity can be due to a defective Lands cycle that hinders LPC production in LDs. Using lipidome assessment with the newly formulated LLC can be a promising cancer chemotherapy method.

Exploring Molecular Mechanism of Huangqi in Treating Heart Failure Using Network Pharmacology

Heart failure (HF), a clinical syndrome with a high incidence due to various reasons, is the advanced stage of most cardiovascular diseases. Huangqi is an effective treatment for cardiovascular disease, which has multitarget, multipathway functions. Therefore, we used network pharmacology to explore the molecular mechanism of Huangqi in treating HF. In this study, 21 compounds of Huangqi, which involved 407 targets, were obtained and reconfirmed using TCMSP and PubChem databases. Moreover, we used Cytoscape 3.7.1 to construct compound-target network and screened the top 10 compounds. 378 targets related to HF were obtained from CTD and GeneCards databases and HF-target network was constructed by Cytoscape 3.7.1. The 46 overlapping targets of HF and Huangqi were gotten by Draw Venn Diagram. STRING database was used to set up a protein-protein interaction network, and MCODE module and the top 5 targets with the highest degree for overlapping targets were obtained. GO analysis performed by Metascape indicated that the overlapping targets were mainly enriched in blood vessel development, reactive oxygen species metabolic process, response to wounding, blood circulation, and so on. KEGG analysis analyzed by ClueGO revealed that overlapping targets were mainly enriched in AGE-RAGE signaling pathway in diabetic complications, IL-17 signaling pathway, HIF-1 signaling pathway, c-type lectin receptor signaling pathway, relaxin signaling pathway, and so on. Finally, molecular docking showed that top 10 compounds of Huangqi also had good binding activities to important targets compared with digoxin, which was carried out in CB-Dock molecular docking server. In conclusion, Huangqi has potential effect on regulating overlapping targets and GE-RAGE signaling pathway in diabetic complications, IL-17 signaling pathway, HIF-1 signaling pathway, and so on to be a latent multitarget, multipathway treatment for HF.

Proton-sensing G protein-coupled receptors: detectors of tumor acidosis and candidate drug targets

Cells in tumor microenvironments (TMEs) use several mechanisms to sense their low pH (<7.0), including via proton-sensing G protein-coupled receptors (psGPCRs): GPR4, GPR65/TDAG8, GPR68/OGR1 and GPR132/G2A. Numerous cancers have increased expression of psGPCRs. The psGPCRs may contribute to features of the malignant phenotype via actions on specific cell-types in the TME and thereby promote tumor survival and growth. Here, we review data regarding psGPCR expression in tumors and cancer cells, impact of psGPCRs on survival in solid tumors and a bioinformatics approach to infer psGPCR expression in cell types in the TME. New tools are needed to help define contributions of psGPCRs in tumor biology and to identify potentially novel therapeutic agents for a variety of cancers.