RAC2 acts as a prognostic biomarker and promotes the progression of clear cell renal cell carcinoma

An R package for Survival-based Gene Set Enrichment Analysis

Functional enrichment analysis is usually used to assess the effects of experimental differences. However, researchers sometimes want to understand the relationship between transcriptomic variation and health outcomes like survival. Therefore, we suggest the use of Survival-based Gene Set Enrichment Analysis (SGSEA) to help determine biological functions associated with a disease's survival. We developed an R package and corresponding Shiny App called SGSEA for this analysis and presented a study of kidney renal clear cell carcinoma (KIRC) to demonstrate the approach. In Gene Set Enrichment Analysis (GSEA), the log-fold change in expression between treatments is used to rank genes, to determine if a biological function has a non-random distribution of altered gene expression. SGSEA is a variation of GSEA using the hazard ratio instead of a log fold change. Our study shows that pathways enriched with genes whose increased transcription is associated with mortality (NES > 0, adjusted p-value < 0.15) have previously been linked to KIRC survival, helping to demonstrate the value of this approach. This approach allows researchers to quickly identify disease variant pathways for further research and provides supplementary information to standard GSEA, all within a single R package or through using the convenient app.

Pancancer Analysis Revealed the Value of RAC2 in Immunotherapy and Cancer Stem Cell

Objective

To investigate the oncogenic effect and clinical significance of RAC2 in pancarcinoma from the perspective of tumor immunity and cancer stem cell.

Methods

After in-depth mining of TCGA, GEO, UCSC, and other databases, basic information of the RAC2 gene and its expression in tumor tissues as well as the relationship between RAC2 and tumor were analyzed based on survival, mutation, immune microenvironment, tumor stemness, and enrichment analysis on related pathways.

Results

RAC2 mRNA expression was increased in most tumor tissues and was associated with their prognosis. Compared to normal tissues, the RAC2 mutation rate was higher in patients with skin melanoma, uterine sarcoma, and endometrial cancer. RAC2 had a strong relation with immune cell infiltration, immunomodulators, immunotherapy markers, cancer stem cell of THYM, and immune-related pathways.

Conclusions

This study explored the potential importance of RAC2 in the prognosis, immunotherapy, and cancer stem cell of 33 cancers, laying the foundation for mechanistic experiments and its future application in clinical practice. However, the results using bioinformatics methods could be affected by the differences in patients across databases. Thus, the present results were preliminary and required further experimental validation.

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.

DIRAS3, GPR171 and RAC2 were identified as the key molecular patterns associated with brain metastasis of breast cancer

Objective

Brain metastasis is a primary cause of morbidity and mortality in breast cancer patients. Therefore, elucidation and understanding of the underlying mechanisms are essential for the development of new therapeutic strategies.

Methods

Differential gene analysis was performed for those with and without distant metastasis in The Cancer Genome Atlas (TCGA) database and those with and without recurrence in the brain in the dataset GSE12276. The differentially expressed genes procured from the two databases were intersected to obtain the intersecting genes associated with brain metastasis. Thereafter, the intersecting genes were subjected to LASSO model construction to screen for prognostic genes. The expression of the obtained genes in metastatic breast cancer was observed, and survival analysis was performed. Finally, GSEA analysis of the obtained genes was performed, and the relationship between them and immune cells was explored.

Results

A total of 335 differential genes for the occurrence of distant metastases were obtained based on the TCGA database. A total of 1070 differential genes for recurrence to the brain were obtained based on the dataset GSE12276. The Venn diagram showed 24 intersecting genes associated with brain metastasis. The LASSO prognostic model contained a total of five genes (GBP2, GPR171, DIRAS3, RAC2, and CACNA1D). Expression difference analysis showed that GBP2, GPR171, DIRAS3, and RAC2 were significantly down-regulated in expression in metastatic breast cancer compared with primary breast cancer tumors. Only GPR171, DIRAS3, and RAC2 were strongly correlated with the overall survival of breast cancer patients. Their correlation analysis with immune cells showed that the correlation coefficient between the expression levels of DIRAS3 and immune cells was low, and the expression levels of GPR171 and RAC2 were more closely correlated with B cells and macrophages.

Conclusions

The expression of DIRAS3, GPR171 and RAC2, genes associated with brain metastasis, was reduced in metastatic breast cancer, and GPR171 was found to promote brain metastasis of breast cancer cells by inducing B cells and thereby.

The Pyroptosis-Related Risk Genes APOBEC3D, TNFRSF14, and RAC2 Were Used to Evaluate Prognosis and as Tumor Suppressor Genes in Breast Cancer

Background

Pyroptosis is a type of cell death that plays an important role in predicting prognosis and immunoregulation in cancers. However, the pyroptosis-related gene signature for prognosis and immune infiltration prediction has not been studied in breast cancer (BC).

Methods

The Gene Expression Omnibus (GEO) and Cancer Genome Atlas (TCGA) databases were used to obtain the expression and clinical data of genes. 52 pyroptosis-related genes were obtained from TCGA-BC and estimated differentially expressed genes by the limma program. To categorize the molecular subtypes of pyroptosis-related genes, the ConsensusClusterPlus tool was utilized. Cox and Lasso regression analyses were used to create a signature. TCGA-BC dataset as the training set and the GSE37751 test set for risk research. Gene set enrichment analysis (GSEA) was used to conduct KEGG and GO studies of subtype groups. We also used the ssGSEA approach in the GSVA package to calculate the risk score of immune cells. Finally, pyroptosis-related genes in BC were validated using qPCR and immunohistochemical assays. Clone formation and EDU assays were used to explore the ability of signature genes to regulate the proliferation of BC cells.

Results

Based on pyroptosis-related genes, the C1 and C2 subtypes were obtained. Survival analysis results showed that the C2 group had a better prognosis. Then, a three-gene signature (APOBEC3D, TNFRSF14, and RAC2) were created by Lasso regression analysis, which had a good prediction effect in the TCGA-BC and GSE37751 datasets. Our nomogram has a fair degree of accuracy in predicting the survival rates of BC patients. The pyroptosis-related signature has a good predictive effect in evaluating the tumour microenvironment score, 28 types of immune cells and response to immune checkpoint therapy. Finally, qPCR and immunohistochemistry staining results indicated that APOBEC3D, TNFRSF14, and RAC2 expression in BC tissues was low. The results of clone formation and EdU assays showed that high expression of signature genes inhibited the proliferation ability of BC cells.

Conclusions

Based on pyroptosis-related genes (APOBEC3D, TNFRSF14, and RAC2), we built a novel prognostic molecular model for BC that might be used to assess prognostic risk and immune infiltration in BC patients. These signature genes are also tumor suppressor genes and may serve as potential targets for BC.

Single-Cell RNA Sequencing of Peripheral Blood Mononuclear Cells From Pediatric Coeliac Disease Patients Suggests Potential Pre-Seroconversion Markers

Celiac Disease (CeD) is a complex immune disorder involving villous atrophy in the small intestine that is triggered by gluten intake. Current CeD diagnosis is based on late-stage pathophysiological parameters such as detection of specific antibodies in blood and histochemical detection of villus atrophy and lymphocyte infiltration in intestinal biopsies. To date, no early onset biomarkers are available that would help prevent widespread villous atrophy and severe symptoms and co-morbidities. To search for novel CeD biomarkers, we used single-cell RNA sequencing (scRNAseq) to investigate PBMC samples from 11 children before and after seroconversion for CeD and 10 control individuals matched for age, sex and HLA-genotype. We generated scRNAseq profiles of 9559 cells and identified the expected major cellular lineages. Cell proportions remained stable across the different timepoints and health conditions, but we observed differences in gene expression profiles in specific cell types when comparing patient samples before and after disease development and comparing patients with controls. Based on the time when transcripts were differentially expressed, we could classify the deregulated genes as biomarkers for active CeD or as potential pre-diagnostic markers. Pathway analysis showed that active CeD biomarkers display a transcriptional profile associated with antigen activation in CD4+ T cells, whereas NK cells express a subset of biomarker genes even before CeD diagnosis. Intersection of biomarker genes with CeD-associated genetic risk loci pinpointed genetic factors that might play a role in CeD onset. Investigation of potential cellular interaction pathways of PBMC cell subpopulations highlighted the importance of TNF pathways in CeD. Altogether, our results pinpoint genes and pathways that are altered prior to and during CeD onset, thereby identifying novel potential biomarkers for CeD diagnosis in blood.

Prognostic model based on six PD-1 expression and immune infiltration-associated genes predicts survival in breast cancer

Background

The prognosis of breast cancer (BC) was associated with the expression of programmed cell death-1 (PD-1).

Methods

BC-related expression and clinical data were downloaded from TCGA database. PD-1 expression with overall survival and clinical factors were investigated. Gene set variation analysis (GSVA) and weighted gene correlation network analysis were performed to investigate the PD-1 expression-associated KEGG pathways and genes, respectively. Immune infiltration was analyzed using the ssGSEA algorithm and DAVID, respectively. Univariate and multivariable Cox and LASSO regression analyses were performed to select prognostic genes for modeling.

Results

High PD-1 expression was related to prolonged survival time (P = 0.014). PD-1 expression status showed correlations with age, race, and pathological subtype. ER- and PR-negative patients exhibited high PD-1 expression. The GSVA revealed that high PD-1 expression was associated with various immune-associated pathways, such as T cell/B cell receptor signaling pathway or natural killer cell-mediated cytotoxicity. The patients in the high-immune infiltration group exhibited significantly higher PD-1 expression levels. In summary, 397 genes associated with both immune infiltration and PD-1 expression were screened. Univariate analysis and LASSO regression model identified the six most valuable prognostic genes, namely IRC3, GBP2, IGJ, KLHDC7B, KLRB1, and RAC2. The prognostic model could predict survival for BC patients.

Conclusion

High PD-1 expression was associated with high-immune infiltration in BC patients. Genes closely associated with PD-1, immune infiltration and survival prognosis were screened to predict prognosis.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12282-022-01344-2.

TIMP1 Indicates Poor Prognosis of Renal Cell Carcinoma and Accelerates Tumorigenesis via EMT Signaling Pathway

Renal cell carcinoma (RCC) is one of the most common malignancies in the urinary system. The mortality of advanced RCC remains high despite advances in systemic therapy of RCC. Considering the misdiagnosis of early-stage RCC, the identification of effective biomarkers is of great importance. Tissue inhibitor matrix metalloproteinase 1 (TIMP1), which belongs to TIMP gene family, is a natural inhibitor of the matrix metalloproteinases (MMPs). In this study, we found TIMP1 was significantly up-regulated in cell lines and RCC tissues. Kaplan-Meier analysis revealed that high expression of TIMP1 indicated a poor prognosis. Multivariate analysis further indicated that TIMP1 overexpression was an independent prognostic factor of RCC patients. Furthermore, knockdown of TIMP1 in vitro suppressed the proliferation, migration, and invasion of RCC cells, while upregulating TIMP1 accelerated the proliferation, migration, and invasion of RCC cells. In addition, we also found that TIMP1 prompted the progression of RCC via epithelial-to-mesenchymal transition (EMT) signaling pathway. In conclusion, the present results suggested that TIMP1 indicated poor prognosis of renal cell carcinoma and could serve as a potential diagnostic and prognostic biomarker for RCC.

Bioinformatics analysis of genes related to iron death in diabetic nephropathy through network and pathway levels based approaches

Diabetic nephropathy is one of the common microvascular complications of diabetes. Iron death is a recently reported way of cell death. To explore the effects of iron death on diabetic nephropathy, iron death score of diabetic nephropathy was analyzed based on the network and pathway levels. Furthermore, markers related to iron death were screened. Using RNA-seq data of diabetic nephropathy, samples were clustered uniformly and the disease was classified. Differentially expressed gene analysis was conducted on the typed disease samples, and the WGCNA algorithm was used to obtain key modules. String database was used to perform protein interaction analysis on key module genes for the selection of Hub genes. Moreover, principal component analysis method was applied to get transcription factors and non-coding genes, which interact with the Hub gene. All samples can be divided into two categories and principal component analysis shows that the two categories are significantly different. Hub genes (FPR3, C3AR1, CD14, ITGB2, RAC2 and ITGAM) related to iron death in diabetic nephropathy were obtained through gene expression differential analysis between different subtypes. Non-coding genes that interact with Hub genes, including hsa-miR-572, hsa-miR-29a-3p, hsa-miR-29b-3p, hsa-miR-208a-3p, hsa-miR-153-3p and hsa-miR-29c-3p, may be related to diabetic nephropathy. Transcription factors HIF1α, KLF4, KLF5, RUNX1, SP1, VDR and WT1 may be related to diabetic nephropathy. The above factors and Hub genes are collectively involved in the occurrence and development of diabetic nephropathy, which can be further studied in the future. Moreover, these factors and genes may be potential target for therapeutic drugs.

Master Regulators of Epithelial-Mesenchymal Transition and WNT Signaling Pathways in Juvenile Nasopharyngeal Angiofibromas

Juvenile nasopharyngeal angiofibroma (JNA) is a rare fibrovascular benign tumor showing an invasive growth pattern and affecting mainly male adolescents. We investigated the role of epithelial–mesenchymal transition (EMT) and WNT signaling pathways in JNA. Gene expression profiles using nine JNA paired with four inferior nasal turbinate samples were interrogated using a customized 2.3K microarray platform containing genes mainly involved in EMT and WNT/PI3K pathways. The expression of selected genes (BCL2, CAV1, CD74, COL4A2, FZD7, ING1, LAMB1, and RAC2) and proteins (BCL2, CAV1, CD74, FZD7, RAF1, WNT5A, and WNT5B) was investigated by RT-qPCR (28 cases) and immunohistochemistry (40 cases), respectively. Among 104 differentially expressed genes, we found a significantly increased expression of COL4A2 and LAMB1 and a decreased expression of BCL2 and RAC2 by RT-qPCR. The immunohistochemistry analysis revealed a low expression of BCL2 and a negative to moderate expression of FZD7 in most samples, while increased CAV1 and RAF1 expression were detected. Moderate to strong CD74 protein expression was observed in endothelial and inflammatory cells. A significant number of JNAs (78%) presented reduced WNT5A and increased WNT5B expression. Overall, the transcript and protein profile indicated the involvement of EMT and WNT pathways in JNA. These candidates are promising druggable targets for treating JNA.

Low Expression Levels of SLC22A12 Indicates a Poor Prognosis and Progresses Clear Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) accounts for approximately 4/5 of all kidney cancers. Accumulation of minor changes in the cellular homeostasis may be one cause of ccRCC. Therefore, we downloaded the RNA sequencing and survival data of the kidney renal cell carcinoma (KIRC) cohort from the Cancer Genome Atlas (TCGA) database. After the univariate and multivariate Cox regression analyses, 19 kidney-specific differentially expressed genes (DEGs) were found. Solute Carrier Family 22 Member 12 (SLC22A12) resulted in an independent prognostic predictor for both overall survival (OS) and disease-free survival (DFS). SLC22A12 expression was lower in tumoral tissue compared to normal tissue. Moreover, patients in the SLC22A12 low expression group had a higher pathological stage and worse survival than the high expression group. Additionally, qRT-PCR assay, immunoblotting test (IBT), and immunohistochemical (IHC) analyses of cancer tissues/cells and the corresponding normal controls verified that SLC22A12 is downregulated in ccRCC. Receiver operator characteristic (ROC) curves showed that the low expression level of SLC22A12 could be a good diagnostic marker for ccRCC (AUC=0.7258; p <0.0001). Gene set enrichment analysis (GSEA) showed that SLC22A12 expression levels are related to metabolism, cell cycle, and tumor-related signaling pathways. GO and KEGG analyses revealed that SLC22A12 transports multiple organic compounds, ions, and hormones and participates in the extracellular structure organization. Furthermore, SLC22A12 over-expression in vitro inhibited the proliferation, migration, and invasion of renal cancer cells by regulating PI3K/Akt pathways. Such effects were reversed when knocking out SLC22A12. In summary, as a transporter for many vital metabolites, SLC22A12 may affect tumor cell survival through its impacts on the mentioned metabolites. In conclusion, this study uncovered that SLC22A12 is a promising prognostic and diagnostic biomarker for ccRCC.

Transcriptomic Analysis of the Mechanisms for Alleviating Psoriatic Dermatitis Using Taodan Granules in an Imiquimod-Induced Psoriasis-like Mouse Model

Taodan granules (TDGs) are clinically efficacious for treating psoriasis, buttheir specific mechanisms of action are unclear. In this study, we determined the concentrations of tanshinone IIA and curcumol using high-performance liquid chromatography (HPLC) to establish quality control parameters for assessing the mechanism of TDGs in treating psoriasis. Thereafter, a mouse model of psoriasis was treated with TDGs. TDGs attenuated imiquimod-induced typical erythema, scales, and thickening of the back and ear lesions in the psoriatic mouse model. Furthermore, PCNA and Ki67-positive cells were reduced in the epidermis of psoriatic lesions following TDG treatment. Finally, the sequencing results were verified using a multitude of methods, and the mechanism of action of TDGs against psoriasis was found to be via the upregulation of metabolic signaling pathways such as the Gly-Ser-Thr axis, the downregulation of immune and inflammatory pathways, and the decrease in Rac2 and Arhgdib concentrations. Overall, this study clarified the mechanism of TDG treatment for psoriasis and provided evidence for its clinical application.

A cluster of metabolism-related genes predict prognosis and progression of clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) has long been considered as a metabolic disease characterized by metabolic reprogramming due to the abnormal accumulation of lipid droplets in the cytoplasm. However, the prognostic value of metabolism-related genes in ccRCC remains unclear. In our study, we investigated the associations between metabolism-related gene profile and prognosis of ccRCC patients in the Cancer Genome Atlas (TCGA) database. Importantly, we first constructed a metabolism-related prognostic model based on ten genes (ALDH6A1, FBP1, HAO2, TYMP, PSAT1, IL4I1, P4HA3, HK3, CPT1B, and CYP26A1) using Lasso cox regression analysis. The Kaplan–Meier analysis revealed that our model efficiently predicts prognosis in TCGA_KIRC Cohort and the clinical proteomic tumor analysis consortium (CPTAC_ccRCC) Cohort. Using time-dependent ROC analysis, we showed the model has optimal performance in predicting long-term survival. Besides, the multivariate Cox regression analysis demonstrated our model is an independent prognostic factor. The risk score calculated for each patient was significantly associated with various clinicopathological parameters. Notably, the gene set enrichment analysis indicated that fatty acid metabolism was enriched considerably in low-risk patients. In contrast, the high-risk patients were more associated with non-metabolic pathways. In summary, our study provides novel insight into metabolism-related genes’ roles in ccRCC.

Effect of Grilled Nux Vomica on Differential RNA Expression Profile of Gastrocnemius Muscle and Toll‑Like Receptor 4 (TLR-4)/Nuclear Factor kappa B (NF-κB) Signaling in Experimental Autoimmune Myasthenia Gravis Rats

BACKGROUND Myasthenia gravis (MG) is a progressive autoimmune disorder caused by the production of antibodies directed against acetylcholine receptors (AChRs), resulting in muscle weakness and fatigue. This study aimed to explore the effect and mechanism of grilled nux vomica (GNV) in experimental autoimmune myasthenia gravis (EAMG) rats. MATERIAL AND METHODS Rat 97-116 peptides were used to mediate disease in the EAMG model in SPF female Lewis rats. The treatment groups received grilled nux vomica (75 mg/kg, 150 mg/kg, and 225 mg/kg). The autoantibody and inflammatory cytokines levels were measured by enzyme-linked immunosorbent assay (ELISA). RNA profiling was performed on high-dose and model group rats. Profiling results and TLR-4/NF-kappaB signaling were validated by q-PCR and Western blot analysis. RESULTS The results showed that GNV could attenuate the symptoms of EAMG rats. There was a decreased level of AChR-ab, IFN-γ, TNF-alpha, IL-2, IL-4, and IL-17 levels, and an increased level of TGF-ß1. In total, 235 differentially expressed genes (DEGs), consisting of 175 upregulated DEGs and 60 downregulated DEGs, were identified. Functional annotation demonstrated that DEGs were largely associated with leukocyte cell-cell adhesion, NF-kappa B signaling pathway, muscle contraction, and cardiac muscle contraction pathway. Rac2, Itgb2, Lcp2, Myl3, and Tnni1 were considered as hub genes with a higher degree value in the protein-protein interaction (PPI) network. The q-PCR and Western blot results of hub genes were consistent with RNA profiles. GNV treatment also significantly reduced the TLR-4 and NF-kappaB p65 protein expression in EAMG rats. CONCLUSIONS These results indicate that grilled nux vomica ameliorates EAMG by depressing the TLR-4/NF-kappaB signaling pathway, and hub genes may serve as potential targets for MG treatment.

ISG20 serves as a potential biomarker and drives tumor progression in clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is one of the most common malignancies and lacks reliable biomarkers for diagnosis and prognosis, which results in high incidence and mortality rates of ccRCC. In this study, ISG20, HJURP, and FOXM1 were identified as hub genes via weighted gene co-expression network analysis (WGCNA) and Cox regression analysis. Samples validation showed that only ISG20 was up-regulated in ccRCC. Therefore, ISG20 was selected for further study. High ISG20 expression was associated with poor overall survival and disease-free survival. Furthermore, the expression of ISG20 could effectively differentiate ccRCC from normal tissues and was positively correlated to clinical stages. Functional experiments proved that knockdown of ISG20 expression could obviously inhibit cell growth, migration, and invasion in ccRCC cells. To find the potential mechanisms of ISG20, gene set enrichment analysis (GSEA) was performed and revealed that high expression of ISG20 was significantly involved in metastasis and cell cycle pathways. In addition, we found that ISG20 could regulate the expression of MMP9 and CCND1. In conclusion, these findings suggested that ISG20 promoted cell proliferation and metastasis via regulating MMP9/CCND1 expression and might serve as a potential biomarker and therapeutic target in ccRCC.