Gene expression profiling analysis of osteosarcoma cell lines

Ribosomal protein L8 regulates the expression and splicing pattern of genes associated with cancer-related pathways

Background/aim

Ribosomal proteins have been shown to perform unique extraribosomal functions in cell apoptosis and other biological processes. Ribosomal protein L8 (RPL8) not only has important nonribosomal regulatory functions but also participates in the oncogenesis and development of tumors. However, the specific biological functions and pathways involved in this process are still unknown.

Materials and methods

RPL8 was overexpressed (RPL8-OE) in HeLa cells. MTT assay and flow cytometry were used to detect cell proliferation and apoptosis, respectively. Transcriptome sequencing was performed to analyze the differentially expressed genes (DEGs) and regulated alternative splicing events (RASEs) by RPL8-OE, both of which were validated by quantitative reverse transcription polymerase chain reaction (RT-qPCR) assay.

Results

RPL8-OE inhibited cell proliferation and promoted cell apoptosis. RPL8 regulated the differential expression of many oncogenic genes and the occurrence of RASEs. Many DEGs and RASE genes (RASGs) were enriched in tumorigenesis and tumor progression-related pathways, including angiogenesis, inflammation, and regulation of cell proliferation. RPL8 could regulate the RASGs enriched in the negative regulation of apoptosis, consistent with its proapoptosis function. Furthermore, RPL8 may influence cancer-related DEGs by modulating the alternative splicing of transcription factors.

Conclusion

RPL8 might affect the phenotypes of cancer cells by altering the transcriptome profiles, including gene expression and splicing, which provides novel insights into the biological functions of RPL8 in tumor development.

MAD2L1 is transcriptionally regulated by TEAD4 and promotes cell proliferation and migration in colorectal cancer

The molecular mechanism of network regulation in the occurrence and development of colorectal cancer (CRC) has been constantly improved. Here, we investigated the biological effects of TEAD4-MAD2L1 axis on proliferation and metastasis of human CRC cells. This study revealed that the expressions of MAD2L1 and TEAD4 in CRC tissues and CRC cell lines were significantly higher than those in adjacent epithelial tissues and normal intestinal epithelial cell line NCM460, and their expressions were significantly positively correlated; Moreover, inhibiting the expression of MAD2L1 or TEAD4 can inhibit the proliferation and migration of CRC cells and promote apoptosis. In addition, the promoter region of MAD2L1 gene has a TEAD4 binding site (motif sequence), and the transcription of MAD2L1 is positively regulated by TEAD4 protein; The inhibition of promotion/migration and promotion of apoptosis of CRC cells by silencing TEAD4 can be saved by the high expression of MAD2L1. In conclusion, our study suggests that the transcription and expression of MAD2L1 is regulated by TEAD4, which further promotes the proliferation and migration of CRC cells in vitro and in vivo, and inhibits apoptosis. MAD2L1 and TEAD4 are potential biomarkers for colorectal cancer.

Identification of Tumor Antigens and Immune Subtypes for the Development of mRNA Vaccines and Individualized Immunotherapy in Soft Tissue Sarcoma

Soft tissue sarcomas (STS) are a rare disease with high recurrence rates and poor prognosis. Missing therapy options together with the high heterogeneity of this tumor type gives impetus to the development of individualized treatment approaches. This study identifies potential tumor antigens for the development of mRNA tumor vaccines for STS and explores potential immune subtypes, stratifying patients for immunotherapy. RNA-sequencing data and clinical information were extracted from 189 STS samples from The Cancer Genome Atlas (TCGA) and microarray data were extracted from 103 STS samples from the Gene Expression Omnibus (GEO). Potential tumor antigens were identified using cBioportal, the Oncomine database, and prognostic analyses. Consensus clustering was used to define immune subtypes and immune gene modules, and graph learning-based dimensionality reduction analysis was used to depict the immune landscape. Finally, four potential tumor antigens were identified, each related to prognosis and antigen-presenting cell infiltration in STS: HLTF, ITGA10, PLCG1, and TTC3. Six immune subtypes and six gene modules were defined and validated in an independent cohort. The different immune subtypes have different molecular, cellular, and clinical characteristics. The immune landscape of STS reveals the immunity-related distribution of patients and intra-cluster heterogeneity of immune subtypes. This study provides a theoretical framework for STS mRNA vaccine development and the selection of patients for vaccination, and provides a reference for promoting individualized immunotherapy.

Identification of lncRNA and mRNA Expression Profile in Relapsed Graves' Disease

Background: Graves’ disease (GD) is a common autoimmune disease, and its pathogenesis is unclear. Studies have found that the occurrence of GD is related to the immune disorder caused by the interaction of genetic susceptibility and environmental factors. The CD4⁺ T cell subset is closely related to the immune disorder of GD. LncRNAs are RNA molecules with a length of more than 200 nt and are involved in a variety of autoimmune diseases. However, the roles of lncRNAs in recurrent GD are still elusive. The purpose of this study is to identify lncRNA and mRNA expression profile in relapsed Graves’ disease.

Method: CD4⁺ T cells from 12 recurrent GD and 8 healthy controls were collected for high-throughput sequencing. The gene-weighted co-expression network analysis (WGCNA) was used to construct the co-expression module relevant to recurrent GD, and the key genes in the module were verified by RT-PCR.

Results: There are 602 upregulated lncRNAs and 734 downregulated lncRNAs in CD4⁺ T cells in recurrent GD patients compared with the healthy controls. The module most relevant to GD recurrence was constructed using WGCNA, and the key genes in the module were verified by RT-PCR. We found that the expression of RPL8, OAS2, NFAT5, DROSHA, NONHSAT093153.2, NONHSAT118924.2, and NONHSAT209004.1 was significantly decreased in GD group (p < 0.001, p < 0.001, p < 0.01, p < 0.05, p < 0.001, p < 0.05, and p < 0.01, respectively).

Conclusion: LncRNAs are closely related to the recurrence of GD. For the first time, we constructed the expression profile of lncRNAs and mRNAs in CD4⁺ T cells in recurrent GD patients.

The role of PLCγ2 in immunological disorders, cancer, and neurodegeneration

Phosphatidylinositol-specific phospholipase Cγ2 (PLCγ2) is a critical signaling molecule activated downstream from a variety of cell surface receptors that contain an intracellular immunoreceptor tyrosine-based activation motif. These receptors recruit kinases such as Syk, BTK, and BLNK to phosphorylate and activate PLCγ2, which then generates 1D-myo-inositol 1,4,5-trisphosphate and diacylglycerol. These well-known second messengers are required for diverse membrane functionality including cellular proliferation, endocytosis, and calcium flux. As a result, PLCγ2 dysfunction is associated with a variety of diseases including cancer, neurodegeneration, and immune disorders. The diverse pathologies associated with PLCγ2 are exemplified by distinct genetic variants. Inherited mutations at this locus cause PLCγ2-associated antibody deficiency and immune dysregulation, in some cases with autoinflammation. Acquired mutations at this locus, which often arise as a result of BTK inhibition to treat chronic lymphocytic leukemia, result in constitutive downstream signaling and lymphocyte proliferation. Finally, a third group of PLCγ2 variants actually has a protective effect in a variety of neurodegenerative disorders, presumably by increased uptake and degradation of deleterious neurological aggregates. Therefore, manipulating PLCγ2 activity either up or down could have therapeutic benefit; however, we require a better understanding of the signaling pathways propagated by these variants before such clinical utility can be realized. Here, we review the signaling roles of PLCγ2 in hematopoietic cells to help understand the effect of mutations driving immune disorders and cancer and extrapolate from this to roles which may relate to protection against neurodegeneration.

Inhibition of BUB1 suppresses tumorigenesis of osteosarcoma via blocking of PI3K/Akt and ERK pathways

Osteosarcoma (OS) is a primary malignant bone tumour that mainly affects teenagers, with patients displaying poor prognosis. Budding uninhibited by benzimidazoles 1 (BUB1), a type of serine/threonine kinase that is linked to pro-tumorigenic phenomena, has not been well studied in OS. Hence, this study aimed to explore the role of BUB1 in OS. The expression of BUB1 in OS specimens and cell lines was assessed using immunohistochemistry and Western blot analysis. Univariate and multivariate analyses were applied to evaluate the impact of BUB1 on patient survival. Cell counting kit-8, wound-healing and Transwell assays, as well as flow cytometry, were used to investigate the influence of BUB1 inhibition on OS in vitro. Moreover, a tumour xenograft model was established to investigate the in vivo effect of BUB1 inhibition on OS tumour growth. Results showed that BUB1 was overexpressed in OS specimens and cell lines. Furthermore, BUB1 overexpression was closely associated with the poor clinical outcomes of patients with OS. Inhibition of BUB1 markedly suppressed cell proliferation and tumour growth, cell migration, invasion and induced cell apoptosis of OS by blocking the PI3K/Akt and ERK signalling pathways. Thus, our study suggested that overexpression of BUB1 protein contributed to poor survival of OS patients and that inhibition of BUB1 resulted in considerable anti-tumour activity associated with proliferation, migration, invasion and apoptosis of OS.

Computational screening of potential glioma-related genes and drugs based on analysis of GEO dataset and text mining

BACKGROUND

Considering the high invasiveness and mortality of glioma as well as the unclear key genes and signaling pathways involved in the development of gliomas, there is a strong need to find potential gene biomarkers and available drugs.

METHODS

Eight glioma samples and twelve control samples were analyzed on the GSE31095 datasets, and differentially expressed genes (DEGs) were obtained via the R software. The related glioma genes were further acquired from the text mining. Additionally, Venny program was used to screen out the common genes of the two gene sets and DAVID analysis was used to conduct the corresponding gene ontology analysis and cell signal pathway enrichment. We also constructed the protein interaction network of common genes through STRING, and selected the important modules for further drug-gene analysis. The existing antitumor drugs that targeted these module genes were screened to explore their efficacy in glioma treatment.

RESULTS

The gene set obtained from text mining was intersected with the previously obtained DEGs, and 128 common genes were obtained. Through the functional enrichment analysis of the identified 128 DEGs, a hub gene module containing 25 genes was obtained. Combined with the functional terms in GSE109857 dataset, some overlap of the enriched function terms are both in GSE31095 and GSE109857. Finally, 4 antitumor drugs were identified through drug-gene interaction analysis.

CONCLUSIONS

In this study, we identified that two potential genes and their corresponding four antitumor agents could be used as targets and drugs for glioma exploration.

Identification of key genes associated with progression and prognosis for lung squamous cell carcinoma

Background

Lung squamous cell carcinoma (LUSC) is a major subtype of lung cancer with limited therapeutic options and poor clinical prognosis.

Methods

Three datasets (GSE19188, GSE33532 and GSE33479) were obtained from the gene expression omnibus (GEO) database. Differentially expressed genes (DEGs) between LUSC and normal tissues were identified by GEO2R, and functional analysis was employed using the Database for Annotation, Visualization and Integrated Discovery (DAVID) online tool. Protein-protein interaction (PPI) and hub genes were identified via the Search Tool for the Retrieval of Interacting Genes (STRING) and Cytoscape software. Hub genes were further validated in The Cancer Genome Atlas (TCGA) database. Subsequently, survival analysis was performed using the Kapla-Meier curve and Cox progression analysis. Based on univariate and multivariate Cox progression analysis, a gene signature was established to predict overall survival. Receiver operating characteristic curve was used to evaluate the prognostic value of the model.

Results

A total of 116 up-regulated genes and 84 down-regulated genes were identified. These DEGs were mainly enriched in the two pathways: cell cycle and p53 signaling way. According to the degree of protein nodes in the PPI network, 10 hub genes were identified. The mRNA expression levels of the 10 hub genes in LUSC were also significantly up-regulated in the TCGA database. Furthermore, a novel seven-gene signature (FLRT3, PPP2R2C, MMP3, MMP12, CAPN8, FILIP1 and SPP1) from the DEGs was constructed and acted as a significant and independent prognostic signature for LUSC.

Conclusions

The 10 hub genes might be tightly correlated with LUSC progression. The seven-gene signature might be an independent biomarker with a significant predictive value in LUSC overall survival.

Gene Prioritization through Consensus Strategy, Enrichment Methodologies Analysis, and Networking for Osteosarcoma Pathogenesis

Osteosarcoma is the most common subtype of primary bone cancer, affecting mostly adolescents. In recent years, several studies have focused on elucidating the molecular mechanisms of this sarcoma; however, its molecular etiology has still not been determined with precision. Therefore, we applied a consensus strategy with the use of several bioinformatics tools to prioritize genes involved in its pathogenesis. Subsequently, we assessed the physical interactions of the previously selected genes and applied a communality analysis to this protein-protein interaction network. The consensus strategy prioritized a total list of 553 genes. Our enrichment analysis validates several studies that describe the signaling pathways PI3K/AKT and MAPK/ERK as pathogenic. The gene ontology described TP53 as a principal signal transducer that chiefly mediates processes associated with cell cycle and DNA damage response It is interesting to note that the communality analysis clusters several members involved in metastasis events, such as MMP2 and MMP9, and genes associated with DNA repair complexes, like ATM, ATR, CHEK1, and RAD51. In this study, we have identified well-known pathogenic genes for osteosarcoma and prioritized genes that need to be further explored.

Identification of osteosarcoma driver genes using a network method

Osteosarcoma (OS) is a severe disease that is generally caused by genetic alterations. Systematic identification of driver genes may be used to increase the understanding of the mechanisms underlying the disease. The present study identified a framework to predict driver genes, with the hypothesis that driver genes operate through a number of connected functional genes. OS-related genes were extracted from the Catalogue Of Somatic Mutations In Cancer and subsequently ranked by virtue of their effect on a set of functional genes using a network-based algorithm. This revealed the driver genes associated with dysregulated networks. In addition, compared with the Mutations For Functional Impact on Network Neighbors algorithm, the results obtained using the aforementioned network-based algorithm revealed that the proposed method is effective. Gene functional analysis demonstrated that the potential OS driver genes were involved in OS-associated pathways. Through the validation of the 15 candidate OS driver genes, the classifier constructed in the present study revealed that the identified driver genes were able to distinguish 184 cancer samples from controls. Therefore, the present study provided insights into the identification of driver genes from a vast amount of sequencing data.

Overexpression of CDCA8 promotes the malignant progression of cutaneous melanoma and leads to poor prognosis

Cutaneous melanoma is very aggressive and results in high mortality rates for cancer patients. Determining molecular targets is important for developing novel therapies for cutaneous melanoma. Cell division cycle associated 8 (CDCA8) is a putative oncogene that is upregulated in multiple types of cancer. The present study aimed to examine the role of CDCA8 in cutaneous melanoma, with a focus on the association of its expression to prognosis and metastasis. First, the mRNA expression of CDCA8 in cutaneous melanoma tissues was investigated using the ONCOMINE and Gene Expression Omnibus (GEO) databases. Furthermore, the relationship between the expression of CDCA8 and cutaneous melanoma patient survival was analyzed using a Kaplan‑Meier plot and Log Rank test. In addition, the effects of CDCA8 on proliferation, migration and invasion of cutaneous melanoma cell lines were investigated using reverse transcription‑quantitative polymerase chain reaction (RT‑qPCR), Cell Counting kit‑8, colony formation assay, wound healing and Matrigel assay. Finally, the expression levels of key proteins related to the Rho‑associated coiled‑coil‑containing protein kinase (ROCK) signaling pathway were measured by western blot assay. The results demonstrated that CDCA8 was overexpressed in cutaneous melanoma tissues and cells lines compared with normal tissues, and high expression of CDCA8 was significantly associated with poorer prognosis in patients with cutaneous melanoma. In in vitro experiments, CDCA8 knockdown inhibited A375 and MV3 cell proliferation, migration and invasion. In addition, CDCA8 knockdown reduced the phosphorylation levels of ROCK1 and myosin light chain, two downstream effector proteins of the ROCK pathway. In summary, the present findings suggested that CDCA8 may be a promising therapeutic target for the treatment of cutaneous melanoma.

The protective value of miR-204-5p for prognosis and its potential gene network in various malignancies: a comprehensive exploration based on RNA-seq high-throughput data and bioinformatics

Purpose

The prognostic role of miR-204-5p (previous ID: miR-204) is varied and inconclusive in diverse types of malignant neoplasm. Therefore, the purposes of the study comprehensively explore the overall prognostic role of miR-204-5p based on high-throughput microRNA sequencing data, and to investigate the potential role of miR-204-5p via bioinformatics approaches.

Materials and Methods

The data of microRNA sequencing and survival were downloaded from The Cancer Genome Atlas (TCGA), and the prognostic value of miR-204-5p was analyzed by using Kaplan-Meier and univariate cox regressions. Then a meta-analysis was conducted with all TCGA data and relevant studies collected from literature. Pooled hazard ratios (HRs) with 95% confidence intervals (CIs) were calculated. The prospective molecular mechanism of miR-204-5p was also assessed at a functional level with Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and protein-to-protein interactions (PPI) network.

Results

From TCGA data, the prognostic value of miR-204-5p obviously varied among 20 types of cancers. The pooled HR was 0.928 (95% CI: 0.774-1.113, P = 0.386, 6203 cases of malignancies). For the meta-analysis based on 15 studies from literature, the pooled HR was 0.420 (95% CI: 0.306-0.576, P < 0.001, 1783 cases of malignancies) for overall survival (OS). Furthermore, the combined HR from both TCGA and literature was 0.708 (95% CI: 0.600-0.834, P < 0.001, 7986 cases of malignancies). Subgroup analyses revealed that miR-204-5p could act as a prognostic marker in cancers of respiratory system and digestive system. Functional analysis was conducted on genes predicted as targets (n = 2057) after the overlay genes from six out of twelve software were extracted. Two significant KEGG pathways were enriched (hsa04360: Axon guidance and hsa04722: Neurotrophin signaling pathway). PPI network revealed some hub genes/proteins (CDC42, SOS1, PIK3R1, MAPK1, PLCG1, ESR1, MAPK11, and AR).

Conclusions

The current study demonstrates that over-expression of miR-204-5p could be a protective factor for a certain group of cancers. Clinically, the low miR-204-5p level could gain a predictive value for a poor survival in cancers of respiratory system and digestive system. The detailed molecular mechanisms of miR-204-5p remain to be verified.

Multitype Network-Guided Target Controllability in Phenotypically Characterized Osteosarcoma: Role of Tumor Microenvironment

This study highlights the relevance of network-guided controllability analysis as a precision oncology tool. Target controllability through networks is potentially relevant to cancer research for the identification of therapeutic targets. With reference to a recent study on multiple phenotypes from 22 osteosarcoma (OS) cell lines characterized both in vitro and in vivo, we found that a variety of critical proteins in OS regulation circuits were in part phenotype specific and in part shared. To generalize our inference approach and match cancer phenotypic heterogeneity, we employed multitype networks and identified targets in correspondence with protein sub-complexes. Therefore, we established the relevance for diagnostic and therapeutic purposes of inspecting interactive targets, namely those enriched by significant connectivity patterns in protein sub-complexes. Emerging targets appeared with reference to the OS microenvironment, and relatively to small leucine-rich proteoglycan members and D-type cyclins, among other collagen, laminin, and keratin proteins. These described were evidences shared across all phenotypes; instead, specific evidences were provided by critical proteins including IGFBP7 and PDGFRA in the invasive phenotype, and FGFR3 and THBS1 in the colony forming phenotype.

Immuno-Oncology Integrative Networks: Elucidating the Influences of Osteosarcoma Phenotypes

In vivo and in vitro functional phenotyping characterization was recently obtained with reference to an experimental pan-cancer study of 22 osteosarcoma (OS) cell lines. Here, differentially expressed gene (DEG) profiles were recomputed from the publicly available data to conduct network inference on the immune system regulatory activity across the characterized OS phenotypes. Based on such DEG profiles, and for each phenotype that was analyzed, we obtained coexpression networks and bio-annotations for them. Then, we described the immune-modulated influences in phenotype-specific networks' integrating pathway, transcription factor, and microRNA regulations. Overall, this approach seems suitable for representing heterogeneity in OS tumorigenesis.

An integrative analysis of DNA methylation in osteosarcoma

Background

The study aimed to analyze aberrantly methylated genes, relevant pathways and transcription factors (TFs) in osteosarcoma (OS) development.

Methods

Based on the DNA methylation microarray data GSE36002 that were downloaded from GEO database, the differentially methylated genes in promoter regions were identified between OS and normal samples. Pathway and function enrichment analyses of differentially methylated genes was performed. Subsequently, protein-protein interaction (PPI) network was constructed, followed by identification of cancer-associated differentially methylated genes and significant differentially methylated TFs.

Results

A total of 1379 hyper-methylation regions and 169 hypo-methylation regions in promoter regions were identified in OS samples compared to normal samples. The differentially hyper-methylated genes were significantly enriched in Neuroactive ligand-receptor interaction pathway, and Peroxisome proliferator activated receptor (PPAR) signaling pathway. The differentially hypo-methylated genes were significantly enriched in Toll-like receptor signaling pathway. In PPI network, signal transducers and activators of transcription (STAT3) had high degree (degree=21). MAX interactor 1, dimerization protein (MXI1), STAT3 and T-cell acute lymphocytic leukemia 1 (TAL1) were significant TFs enriched with target genes in OS samples. They were found to be cancer-associated and hyper-methylated in OS samples.

Conclusion

Neuroactive ligand-receptor interaction, PPAR signaling, Toll-like receptor signaling pathways are implicated in OS. MXI1, STAT3, and TAL1 may be important TFs involved in OS development.

Systematic analysis of mRNA expression profiles in NSCLC cell lines to screen metastasis-related genes

Lung cancer is the most prevalent cancer in humans and has the lowest survival outcomes due to its high metastatic potential. The aim of the present study was to screen for metastasis-related genes (MRGs) by investigating the differential expression genes (DEGs) identified by the mRNA expression profiles in SPC-A-1sci (highly metastatic) and SPC-A-1 (parental) cells. DEGs were screened using Genespring software. Gene Ontology and pathway enrichment analyses of these DEGs were performed. Interaction networks between the proteins encoded by the DEGs were identified using the database BioGRID and were visualized by Cytoscape. Modular analysis of the protein-protein interaction network was performed in CFinder. Among these DEGs, the expression levels of 18 genes were examined in SPC-A-1sci and SPC-A-1 cell lines with reverse transcription-quantitative polymerase chain reaction, and 10 of the 18 genes were assessed by western blotting to validate the results of the microarray. Furthermore, the role of metallothionein 1X (MT1X) in non-small cell lung cancer was explored in functional assays and 72 pairs of clinical samples in vitro. Finally, 4,838 DEGs were screened, including 798 upregulated and 4,040 downregulated genes. The significantly enriched functions included gene expression, cytosol and poly-(A) RNA binding, and the most enriched pathway was biosynthesis of antibiotics. Furthermore, MT1X was revealed to promote the migration and invasion ability in SPC-A-1sci and PC-9 lung cancer cell lines. Therefore, MT1X was identified as a candidate MRG through systematic analysis in the present microarray, which was demonstrated to offer potential reference value in screening MRGs.

Integrated analysis of gene expression and genomic aberration data in osteosarcoma (OS)

Cytogenetic analyses have revealed that complex karyotypes with numerous and highly variable genomic aberrations including single-nucleotide polymorphisms (SNPs) and copy number variants (CNVs), are observed in most of the conventional osteosarcomas (OSs). Several genome-wide studies have reported that the dysregulated expression of many genes is correlated with genomic aberrations in OS. We first compared OS gene expression in Gene Expression Omnibus (GEO) data sets and genomic aberrations in International Cancer Genome Consortium (ICGC) database to identify differentially expressed genes (DEGs) associated with SNPs or CNVs in OS. Then the function annotation of SNP- or CNV-associated DEGs was performed in terms of gene ontology analysis, pathway analysis and protein-protein interactions (PPIs). Finally, the expression of genes correlated with both SNPs and CNVs were confirmed by quantitative reverse-transcription PCR. Eight publicly available GEO data sets were obtained, and a set of 979 DEGs were identified (472 upregulated and 507 downregulated DEGs). Moreover, we obtained 1039 SNPs mapped in 938 genes, and 583 CNV sites mapped in 2915 genes. Comparing genomic aberrations and DGEs, we found 41 SNP-associated DEGs and 124 CNV-associated DEGs, in which 7 DGEs were associated with both SNPs and CNVs, including WWP1, EXT1, LDHB, C8orf59, PLEKHA5, CCT3 and VWF. The result of function annotation showed that ossification, bone development and skeletal system development were the significantly enriched terms of biological processes for DEGs. PPI network analysis showed that CCT3, COPS3 and WWP1 were the significant hub proteins. We conclude that these genes, including CCT3, COPS3 and WWP1 are candidate driver genes of importance in OS tumorigenesis.