Identifying novel candidate biomarkers of RCC based on WGCNA analysis

Gene expression and oxidative stress markers profile associated with toxic metals in patients with renal cell carcinoma

BACKGROUND

Toxic metals are associated with cancer progression. Studies have reported the relation between some toxic metals and renal cell carcinoma (RCC).

METHODS AND RESULTS

Blood levels of Cd and Pb were determined in 94 RCC patients (RCC group) and 91 matched controls as well as blood level of malondialdehyde (MDA) and catalase (CAT) activity as markers of oxidative stress and antioxidant, respectively. Gene expression of MAP kinase pathway (P38 and JNK), hypoxia-inducible factor 1-alpha (HIF1α), vascular endothelial growth factor (VEGF), cytochrome C oxidase subunit 6 (COX6), metallothionein (MT2A), and heat shock protein (HSP90AA1) were evaluated in the obtained tissue specimens. Blood Cd and Pb levels were significantly higher in RCC group comparing to control group with preferential significant increase of Cd in chromophobe RCC (chRCC) sub-type. MDA level was significantly higher and CAT activity was lower in the RCC compared to controls. The difference was evident only in chRCC. The expressions of genes were significantly increased in the cancer tissues than in non-cancerous tissues in RCC sub-types and there was a significant correlation between Cd levels and expression of genes VEGF, MT2A, P38 and JNK in chRCC group. Immunohistochemical staining of clear cell RCC tissues shows a marked expression of VEGF and HIF-1α.While COX6 staining show marked expression in chRCC.

CONCLUSIONS

There is a positive correlation between Cd toxicity and the development of RCC, especially chRCC sub-type. Cd is strongly incriminated in the pathogenesis of chRCC through the effort on some genes and oxidative stress markers.

Dual-Organ Transcriptomic Analysis of Rainbow Trout Infected With Ichthyophthirius multifiliis Through Co-Expression and Machine Learning

Ichthyophthirius multifiliis is a major pathogen that causes a high mortality rate in trout farms. However, systemic responses to the pathogen and its interactions with multiple organs during the course of infection have not been well described. In this study, dual-organ transcriptomic responses in the liver and head kidney and hemato-serological indexes were profiled under I. multifiliis infection and recovery to investigate systemic immuno-physiological characteristics. Several strategies for massive transcriptomic interpretation, such as differentially expressed genes (DEGs), Poisson linear discriminant (PLDA), and weighted gene co-expression network analysis (WGCNA) models were used to investigate the featured genes/pathways while minimizing the disadvantages of individual methods. During the course of infection, 6,097 and 2,931 DEGs were identified in the head kidney and liver, respectively. Markers of protein processing in the endoplasmic reticulum, oxidative phosphorylation, and the proteasome were highly expressed. Likewise, simultaneous ferroptosis and cellular reconstruction was observed, which is strongly linked to multiple organ dysfunction. In contrast, pathways relevant to cellular replication were up-regulated in only the head kidney, while endocytosis- and phagosome-related pathways were notably expressed in the liver. Moreover, interestingly, most immune-relevant pathways (e.g., leukocyte trans-endothelial migration, Fc gamma R-mediated phagocytosis) were highly activated in the liver, but the same pathways in the head kidney were down-regulated. These conflicting results from different organs suggest that interpretation of co-expression among organs is crucial for profiling of systemic responses during infection. The dual-organ transcriptomics approaches presented in this study will greatly contribute to our understanding of multi-organ interactions under I. multifiliis infection from a broader perspective.

Weighted Gene Coexpression Network Analysis to Construct Competitive Endogenous RNA Network in Chromogenic Renal Cell Carcinoma

Aim

This study is aimed at constructing the competing endogenous RNA (ceRNA) network in chromophobe renal cell carcinoma (ChRCC).

Methods

Clinical and RNA sequence profiles of patients with ChRCC, including messenger RNAs (mRNAs), microRNAs (miRNAs), and long noncoding RNAs (lncRNAs), were obtained from The Cancer Genome Atlas (TCGA) database. “edgeR” and “clusterProfiler” packages were utilized to obtain the expression matrices of differential RNAs (DERNAs) and to conduct gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. Weighted gene coexpression network analysis (WGCNA) was performed to screen the highly related RNAs, and miRcode, StarBase, miRTarBase, miRDB, and TargetScan datasets were used to predict the connections between them. Univariate and multivariate Cox proportional hazards regressions were performed in turn to elucidate prognosis-related mRNAs in order to construct the ceRNA regulatory network.

Results

A total of 1628 DElncRNAs, 104 DEmiRNAs, and 2619 DEmRNAs were identified. WGCNA showed significant correlation in 1534 DElncRNAs, 98 DEmiRNAs, and 2543 DEmRNAs, which were related to ChRCC. Fourteen DEmiRNAs, 113 DElncRNAs, and 43 DEmRNAs were screened. Nine mRNAs (ALPL, ARHGAP29, CADM2, KIT, KLRD1, MYBL1, PSD3, SFRP1, and SLC7A11) significantly contributed to the overall survival (OS) of patients with ChRCC (P < 0.05). Furthermore, two mRNAs (CADM2 and SFRP1) appeared to be independent risk factors for ChRCC.

Conclusion

The findings revealed the molecular mechanism of ChRCC and potential therapeutic targets for the disease.

Transcriptional Profiling Uncovers Biologically Significant RNAs and Regulatory Networks in Nucleus Pulposus from Intervertebral Disc Degeneration Patients

Objective. This study aimed to uncover biologically significant RNAs in nucleus pulposus tissues of human intervertebral disc degeneration (IVDD) by integrated transcriptional profiling. Methods. From the Gene Expression Omnibus (GEO) database, three IVDD-related microarray profiling datasets were retrieved and assessed by intragroup data repeatability test. Then, differentially expressed circRNAs, lncRNAs, mRNAs, and miRNAs were screened in nucleus pulposus tissues between IVDD and control samples via the limma package. Coexpression networks were separately conducted via weighted gene correlation network analysis (WGCNA). Based on the feature RNAs in the IVDD-related modules, IVDD-related circRNA-miRNA-mRNA and lncRNA-miRNA-mRNA networks were conducted. The differentially expressed mRNAs in the two networks were analyzed by protein-protein interaction (PPI) and functional enrichment analyses. Results. By the intragroup data repeatability test, outlier samples were removed. Abnormally expressed RNAs were separately identified in nucleus pulposus between IVDD and controls. Via WGCNA, IVDD-related coexpression modules were constructed and the feature circRNAs, lncRNAs, mRNAs, and miRNAs were identified. Then, the circRNA- and lncRNA-miRNA-mRNA networks were built for IVDD. These mRNAs in the network exhibited complex interactions. Moreover, they were involved in distinct IVDD-related biological processes and pathways such as transcription, cell proliferation, TNF, TGF-β, and HIF signaling pathways. Conclusion. This study revealed biologically significant noncoding RNAs and their complex regulatory networks for IVDD.

Identifying novel genetic alterations in pediatric acute lymphoblastic leukemia based on copy number analysis

Copy number variations (CNVs) analysis may reveal molecular biomarkers and provide information on the pathogenesis of acute lymphoblastic leukemia (ALL). We investigated the gene copy number in childhood ALL by microarray and select three new recurrent CNVs to evaluate by real-time PCR assay: DMBT1, KIAA0125 and PRDM16 were selected due to high frequency of CNVs in ALL samples and based on their potential biological functions in carcinogenesis described in the literature. DBMT1 deletion was associated with patients with chromosomal translocations and is a potential tumor suppressor; KIAA0125 and PRDM16 may act as an oncogene despite having a paradoxical behavior in carcinogenesis. This study reinforces that microarrays/aCGH is it is a powerful tool for detection of genomic aberrations, which may be used in the risk stratification.

Bioinformatics Analysis of Prognostic miRNA Signature and Potential Critical Genes in Colon Cancer

This study aims to lay a foundation for studying the regulation of microRNAs (miRNAs) in colon cancer by applying bioinformatics methods to identify miRNAs and their potential critical target genes associated with colon cancer and prognosis. Data of differentially expressed miRNAs (DEMs) and genes (DEGs) downloaded from two independent databases (TCGA and GEO) and analyzed by R software resulted in 472 DEMs and 565 DEGs in colon cancers, respectively. Next, we developed an 8-miRNA (hsa-mir-6854, hsa-mir-4437, hsa-mir-216a, hsa-mir-3677, hsa-mir-887, hsa-mir-4999, hsa-mir-34b, and hsa-mir-3189) prognostic signature for patients with colon cancer by Cox proportional hazards regression analysis. To predict the target genes of these miRNAs, we used TargetScan and miRDB. The intersection of DEGs with the target genes predicted for these eight miRNAs retrieved 112 consensus genes. GO and KEGG pathway enrichment analyses showed these 112 genes were mainly involved in protein binding, one-carbon metabolic process, nitrogen metabolism, proteoglycans in cancer, and chemokine signaling pathways. The protein-protein interaction network of the consensus genes, constructed using the STRING database and imported into Cytoscape, identified 14 critical genes in the pathogenesis of colon cancer (CEP55, DTL, FANCI, HMMR, KIF15, MCM6, MKI67, NCAPG2, NEK2, RACGAP1, RRM2, TOP2A, UBE2C, and ZWILCH). Finally, we verified the critical genes by weighted gene co-expression network analysis (WGCNA) of the GEO data, and further mined the core genes involved in colon cancer. In summary, this study identified an 8-miRNA model that can effectively predict the prognosis of colon cancer patients and 14 critical genes with vital roles in colon cancer carcinogenesis. Our findings contribute new ideas for elucidating the molecular mechanisms of colon cancer carcinogenesis and provide new therapeutic targets and biomarkers for future treatment and prognosis.

Multifaceted Role of PRDM Proteins in Human Cancer

The PR/SET domain family (PRDM) comprise a family of genes whose protein products share a conserved N-terminal PR [PRDI-BF1 (positive regulatory domain I-binding factor 1) and RIZ1 (retinoblastoma protein-interacting zinc finger gene 1)] homologous domain structurally and functionally similar to the catalytic SET [Su(var)3-9, enhancer-of-zeste and trithorax] domain of histone methyltransferases (HMTs). These genes are involved in epigenetic regulation of gene expression through their intrinsic HMTase activity or via interactions with other chromatin modifying enzymes. In this way they control a broad spectrum of biological processes, including proliferation and differentiation control, cell cycle progression, and maintenance of immune cell homeostasis. In cancer, tumor-specific dysfunctions of PRDM genes alter their expression by genetic and/or epigenetic modifications. A common characteristic of most PRDM genes is to encode for two main molecular variants with or without the PR domain. They are generated by either alternative splicing or alternative use of different promoters and play opposite roles, particularly in cancer where their imbalance can be often observed. In this scenario, PRDM proteins are involved in cancer onset, invasion, and metastasis and their altered expression is related to poor prognosis and clinical outcome. These functions strongly suggest their potential use in cancer management as diagnostic or prognostic tools and as new targets of therapeutic intervention.

Identifying hub genes of clear cell renal cell carcinoma associated with the proportion of regulatory T cells by weighted gene co-expression network analysis

BACKGROUND

Numerous patients with clear cell renal cell carcinoma (ccRCC) experience drug resistance after immunotherapy. Regulatory T (Treg) cells may work as a suppressor for anti-tumor immune response.

PURPOSE

We performed bioinformatics analysis to better understand the role of Treg cells in ccRCC.

RESULTS

Module 10 revealed the most relevance with Treg cells. Functional annotation showed that biological processes and pathways were mainly related to activation of the immune system and the processes of immunoreaction. Four hub genes were selected: LCK, MAP4K1, SLAMF6, and RHOH. Further validation showed that the four hub genes well-distinguished tumor and normal tissues and were good prognostic biomarkers for ccRCC.

CONCLUSION

The identified hub genes facilitate our knowledge of the underlying molecular mechanism of how Treg cells affect ccRCC in anti-tumor immune therapy.

METHODS

The CIBERSORT algorithm was performed to evaluate tumor-infiltrating immune cells based on the Cancer Genome Atlas cohort. Weighted gene co-expression network analysis was conducted to explore the modules related to Treg cells. Gene Ontology analysis and pathway enrichment analysis were performed for functional annotation and a protein-protein interaction network was built. Samples from the International Cancer Genomics Consortium database was used as a validation set.

Joint bioinformatics analysis of underlying potential functions of hsa-let-7b-5p and core genes in human glioma

Background

Glioma accounts for a large proportion of cancer, and an effective treatment for this disease is still lacking because of the absence of specific driver molecules. Current challenges in the treatment of glioma are the accurate and timely diagnosis of brain glioma and targeted treatment plans. To investigate the diagnostic biomarkers and prospective role of miRNAs in the tumorigenesis and progression of glioma, we analyzed the expression of miRNAs and key genes in glioma based on The Cancer Genome Atlas database.

Methods

Of the 701 cases that were downloaded, five were normal and 696 were glioma. Then, 1626 differentially expressed genes were identified, and 173 aberrantly expressed miRNAs were calculated by edgeR. GO and KEGG pathway enrichment analyses were performed using Cytoscape software. A coexpression network was built by weighted correlation network analysis (WGCNA). A cell scratch test and transwell, cell apoptosis and cell cycle assays were performed to validate the function of hsa-let-7b-5p.

Results

Based on crosstalk genes in the KEGG, PPI network, and WGCNA analyses, PLK1, CCNA2, cyclin B2 (CCNB2), and AURKA were screened as candidate diagnostic marker genes. The survival analysis revealed that high mRNA expression of PLK1, CCNA2, and AURKA was significantly associated with poor overall survival. Furthermore, hsa-let-7b-5p was identified as a core miRNA in the regulation of candidate genes involved in glioma development. We confirmed that hsa-let-7b-5p could inhibit the migration, invasion, and cell cycle of glioma cells.

Conclusions

This study provides four potential biomarkers for the diagnosis of glioma, offers a potential explanation of its pathogenesis, and proposes hsa-let-7b-5p as a therapeutic target.

Electronic supplementary material

The online version of this article (10.1186/s12967-019-1882-7) contains supplementary material, which is available to authorized users.