scholarly journals Overexpression of B7-H3 Is Associated With Poor Prognosis in Laryngeal Cancer

2021 ◽  
Vol 11 ◽  
Author(s):  
Yixuan Li ◽  
Qian Cai ◽  
Ximing Shen ◽  
Xiaoting Chen ◽  
Zhong Guan
Keyword(s):  
Gene Expression ◽  
Laryngeal Cancer ◽  
Poor Prognosis ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Expression Level ◽  
Normal Tissues ◽  
Qrt Pcr ◽  
Node Metastasis ◽  
B7 Family

The immune checkpoint molecule, B7-H3, which belongs to the B7 family, has been shown to be overexpressed in various cancers. Its role in tumors is not well defined, and many studies suggest that it is associated with poor clinical outcomes. The effect of B7-H3 on laryngeal cancer has not been reported. This study investigated the expression of B7-H3 in laryngeal squamous cell carcinoma (LSCC), and its relationship with clinicopathological factors and prognosis of LSCC patients. The gene expression quantification data and clinical data of LSCC retrieved from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database were analyzed to determine the diagnostic and prognostic roles of B7-H3. Quantitative real-time polymerase chain reaction (qRT-PCR) was then performed to determine the gene expression level of B7-H3 between LSCC tissues and paired normal adjacent tissues. In addition, TCGA RNA-seq data was analyzed to evaluate the expression level of B7 family genes. Next, the protein expression of B7-H3 and CD8 in LSCC was determined using immunohistochemistry and immunofluorescence. qRT-PCR results showed that the expression level of B7-H3 mRNA was significantly higher in LSCC tissues than in adjacent normal tissues. Similar results were obtained from the TCGA analysis. The expression of B7-H3 was significantly associated with T stage, lymph node metastasis, and pathological tumor node metastasis (TNM) stage, and it was also an independent factor influencing the overall survival time (OS) of patients with LSCC. In addition, B7-H3 was negatively correlated with CD8+T cells. These results show that B7-H3 is upregulated in LSCC. Therefore, B7-H3 may serve as a biomarker of poor prognosis and a promising therapeutic target in LSCC.

scholarly journals Novel Epigenetic Eight-Gene Signature Predictive of Poor Prognosis and MSI-Like Phenotype in Human Metastatic Colorectal Carcinomas

Cancers ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 158
Author(s):  
Valentina Condelli ◽  
Giovanni Calice ◽  
Alessandra Cassano ◽  
Michele Basso ◽  
Maria Grazia Rodriquenz ◽  
...  
Keyword(s):  
Gene Expression ◽  
Poor Prognosis ◽  
Cpg Island ◽  
Colon Adenocarcinoma ◽  
Gene Signature ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Cpg Island Methylator Phenotype ◽  
Prognostic Information ◽  
Global Methylation

Epigenetics is involved in tumor progression and drug resistance in human colorectal carcinoma (CRC). This study addressed the hypothesis that the DNA methylation profiling may predict the clinical behavior of metastatic CRCs (mCRCs). The global methylation profile of two human mCRC subgroups with significantly different outcome was analyzed and compared with gene expression and methylation data from The Cancer Genome Atlas COlon ADenocarcinoma (TCGA COAD) and the NCBI GENE expression Omnibus repository (GEO) GSE48684 mCRCs datasets to identify a prognostic signature of functionally methylated genes. A novel epigenetic signature of eight hypermethylated genes was characterized that was able to identify mCRCs with poor prognosis, which had a CpG-island methylator phenotype (CIMP)-high and microsatellite instability (MSI)-like phenotype. Interestingly, methylation events were enriched in genes located on the q-arm of chromosomes 13 and 20, two chromosomal regions with gain/loss alterations associated with adenoma-to-carcinoma progression. Finally, the expression of the eight-genes signature and MSI-enriching genes was confirmed in oxaliplatin- and irinotecan-resistant CRC cell lines. These data reveal that the hypermethylation of specific genes may provide prognostic information that is able to identify a subgroup of mCRCs with poor prognosis.

scholarly journals OSmfs: An Online Interactive Tool to Evaluate Prognostic Markers for Myxofibrosarcoma

Genes ◽  
2020 ◽  
Vol 11 (12) ◽  
pp. 1523
Author(s):  
Huimin Li ◽  
Longxiang Xie ◽  
Qiang Wang ◽  
Yifang Dang ◽  
Xiaoxiao Sun ◽  
...  
Keyword(s):  
Gene Expression ◽  
Poor Prognosis ◽  
Analysis Data ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Prognostic Biomarkers ◽  
Rank Test ◽  
Web Tool ◽  
Kaplan Meier ◽  
Cox Analysis

Myxofibrosarcoma is a complex genetic disease with poor prognosis. However, more effective biomarkers that forebode poor prognosis in Myxofibrosarcoma remain to be determined. Herein, utilizing gene expression profiling data and clinical follow-up data of Myxofibrosarcoma cases in three independent cohorts with a total of 128 Myxofibrosarcoma samples from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, we constructed an easy-to-use web tool, named Online consensus Survival analysis for Myxofibrosarcoma (OSmfs) to analyze the prognostic value of certain genes. Through retrieving the database, users generate a Kaplan–Meier plot with log-rank test and hazard ratio (HR) to assess prognostic-related genes or discover novel Myxofibrosarcoma prognostic biomarkers. The effectiveness and availability of OSmfs were validated using genes in ever reports predicting the prognosis of Myxofibrosarcoma patients. Furthermore, utilizing the cox analysis data and transcriptome data establishing OSmfs, seven genes were selected and considered as more potentially prognostic biomarkers through overlapping and ROC analysis. In conclusion, OSmfs is a promising web tool to evaluate the prognostic potency and reliability of genes in Myxofibrosarcoma, which may significantly contribute to the enrichment of novelly potential prognostic biomarkers and therapeutic targets for Myxofibrosarcoma.

scholarly journals Down-regulation of miRNA-30c predicts poor prognosis in Colorectal Cancer patients

2016 ◽  
Vol 24 (4) ◽  
pp. 369-375
Author(s):  
Liu Bin ◽  
Meng Zhang ◽  
Liu Lixia ◽  
Zang Aimin ◽  
Yang Hua ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Poor Prognosis ◽  
Univariate Analysis ◽  
Clinicopathological Features ◽  
Expression Level ◽  
Rt Pcr ◽  
Normal Tissues ◽  
Node Metastasis ◽  
Treatment Measures ◽  
Colorectal Cancer Patients

Abstract Background: MiRNA-30c was a tumor suppressor in several human cancers, however, its association with clinicopathological features and prognosis in colorectal cancer (CRC) is unclear. Materials and Methods: The expression level of miRNA-30c in 192 pairs of colorectal cancer and adjacent normal tissues was detected by Quantitative RT-PCR, the association between miRNA-30c expression and clinical characteristics and prognosis were statistically analyzed. Results: miRNA-30c was significantly lower in CRC tissues specimens compared with matched normal adjacent tissue (P<0.001). MiRNA-30c was positively correlated with tumor size (P=0.012), TMN stage (P=0.002) and lymph node metastasis (P=0.004). The univariate analysis showed CRC patients with low miRNA-30c had distinctly shorter overall survival (P<0.001) than patients with high miRNA-30c expression level. The multivariate analysis was performed and informed that low miRNA-30c expression (P<0.001) might be an independent prognostic predictor for poor prognosis. Conclusion: miRNA-30c could predict the prognosis of colorectal cancer which is helpful to choose reasonable treatment measures.

scholarly journals Overexpression of VEGF-C and MMP-9 predicts poor prognosis in Kazakh patients with esophageal squamous cell carcinoma

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e8182 ◽  
Author(s):  
Jiangfen Li ◽  
Yufang Xie ◽  
Xueli Wang ◽  
Chenhao Jiang ◽  
Xin Yuan ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Esophageal Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Poor Prognosis ◽  
Positive Association ◽  
Gene Expression Omnibus ◽  
Tnm Staging ◽  
The Cancer Genome Atlas ◽  
Node Metastasis

Vascular endothelial growth factor (VEGF) and Matrix metalloproteinases (MMPs) are believed to participate in infiltration of tumors. High mortality of esophageal squamous cell carcinoma (ESCC) related to its primary infiltration; however, it is not clear whether the expression of VEGF and MMPs is involved in this process. Screening of The Cancer Genome Atlas (TCGA) database showed that among the VEGF family and MMP9, VEGF-A, VEGF-C, and MMP-9 mRNA were overexpression in ESCC. This result was verified using the Oncomine database and in Kazakh patients with ESCC. Overexpression of VEGF-C and MMP-9 and positive association with advanced esophageal cancer and invading ESCC cells (Gene Expression Omnibus (GEO): GSE21293). Immunohistochemical staining revealed that VEGF-C and MMP-9 were overexpressed in Kazakh ESCCs. VEGF-C expression was related to invasive depth, tumor-node-metastasis (TNM) staging, lymphatic, and lymph node metastasis of ESCC. The linear association between them was further confirmed in TCGA database and the specimens from Kazakh patients with ESCC. Patients with both proteins expression had tumors with greater aggressiveness, suffered from poor prognosis compared with patients who did not express either protein or expressed protein alone. Both proteins expression predicted high invasiveness of ESCC, which is related to worse prognosis of Kazakh ESCCs.

scholarly journals Tissue, age, sex, and disease patterns of matrisome expression in GTEx transcriptome data

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Tim O. Nieuwenhuis ◽  
Avi Z. Rosenberg ◽  
Matthew N. McCall ◽  
Marc K. Halushka
Keyword(s):  
Gene Expression ◽  
Expression Patterns ◽  
Tissue Expression ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Normal Tissues ◽  
Disease Patterns ◽  
Generalized Matrix ◽  
Gene Transcripts ◽  
Matrix Control

AbstractThe extracellular matrix (ECM) has historically been explored through proteomic methods. Whether or not global transcriptomics can yield meaningful information on the human matrisome is unknown. Gene expression data from 17,382 samples across 52 tissues, were obtained from the Genotype-Tissue Expression (GTEx) project. Additional datasets were obtained from The Cancer Genome Atlas (TCGA) program and the Gene Expression Omnibus for comparisons. Gene expression levels generally matched proteome-derived matrisome expression patterns. Further, matrisome gene expression properly clustered tissue types, with some matrisome genes including SERPIN family members having tissue-restricted expression patterns. Deeper analyses revealed 382 gene transcripts varied by age and 315 varied by sex in at least one tissue, with expression correlating with digitally imaged histologic tissue features. A comparison of TCGA tumor, TCGA adjacent normal and GTEx normal tissues demonstrated robustness of the GTEx samples as a generalized matrix control, while also determining a common primary tumor matrisome. Additionally, GTEx tissues served as a useful non-diseased control in a separate study of idiopathic pulmonary fibrosis (IPF) matrix changes, while identifying 22 matrix genes upregulated in IPF. Altogether, these findings indicate that the transcriptome, in general, and GTEx in particular, has value in understanding the state of organ ECM.

scholarly journals Prognostic Value of Genes Related with Tumor Microenvironment in Ovarian Cancer

2020 ◽  
Author(s):  
Shimei Li ◽  
Jiyi Yao ◽  
Shen Zhang ◽  
Xinchuan Zhou ◽  
Xinbao Zhao ◽  
...  
Keyword(s):  
Gene Expression ◽  
Ovarian Cancer ◽  
Tumor Microenvironment ◽  
Poor Prognosis ◽  
External Validation ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Gene Expression Signatures ◽  
Poor Outcomes ◽  
Geo Database

Abstract Background Ovarian cancer (OV) is the fifth leading cause of cancer death among females. Growing evidence supports a key role of tumor microenvironment in growth, progress, and metastasis of OV. However, the impacts of gene expression signatures related with OV microenvironment on prognosis have not been well-established . This study aimed to apply ESTIMATE algorithm to extract genes related with tumor microenvironment that predicted poor outcomes in OV patients. Methods The gene expression profile of OV samples were downloaded from The Cancer Genome Atlas (TCGA) database. The immune scores and stromal scores of 469 OV samples were available based on the ESTIMATE algorithm. To better understand impacts of gene expression signatures related with OV microenvironment on prognosis, these samples were categorized based on their ESTIMATE scores into high and low score groups. A different OV cohort from the Gene Expression Omnibus (GEO) database was used for external validation. Results The molecular subtypes in OV patients were correlated with stromal scores, in which the mesenchymal subtype had the highest stromal scores (p < 0.0001). Poor prognosis were found in patients (especially for patients with overall survivals (OS) < 5 years) with higher stromal score (p = 0.0376). 449 differentially expressed genes (DEGs) in stromal scores group were identified and 26 DEGs were significantly associated with poor prognosis in OV patients (p < 0.05). Eventually, 6 genes have further validated to be significantly associated with poor outcomes in 40 patients from a different OV cohort of GEO database (p < 0.05). Conclusion In this study, several genes related with tumor microenvironment that predicted poor prognosis in OV patients were extracted. In addition, some previously overlooked genes could be potential prognostic biomarkers for OV.

scholarly journals High SLC7A11 Expression Is Correlated With Poor Prognosis and Associated With Ferroptosis in Ovarian Cancer 

2021 ◽  
Author(s):  
Mengqi Deng ◽  
Yanqin Zhang ◽  
Xiangyu Chang ◽  
Di Wu ◽  
Chunyu Xu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Ovarian Cancer ◽  
Protein Expression ◽  
Differentially Expressed Genes ◽  
Poor Prognosis ◽  
Bioinformatic Analysis ◽  
Gene Expression Omnibus ◽  
Differentially Expressed ◽  
Normal Tissues ◽  
And Control

Abstract The current treatments of ovarian cancer (OC) do not yield satisfactory outcomes. Hence, it is necessary to find new treatment targets for OC. In this study, a comprehensive bioinformatic analysis was conducted to identify differentially expressed genes (DEGs) between OC and control tissues. Five datasets were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were screened by comparing gene expression between OC and control tissues. Module analysis of DEGs was performed on the STRING database and GEPIA. Kaplan Meier plotter and GEPIA database analysis the overall survival. Finally, SLC7A11 was found to be is the hubgene. And we confirm that the protein expression of SLC7A11 was increased in OC tissues. Analysis of a variety of tumor gene databases showed that SLC7A11 gene regulated the processes of OC. The low mutation rate of the gene (which were of amplified type) and high mRNA expression were associated with poor prognosis of OC patients.Using erastin-treated ovarian cancer (OC) cell lines, we examined the relationship between ferroptosis and OC. Results showed that OC tissues contained higher malondialdehyde (MDA) levels than normal tissues. Unlike normal ovarian epithelial cells which are not sensitive to erastin, the OC cell line, ES-2 is very sensitive to erastin. Here, we found that ferrostatin-1 treatment increased levels of reactive oxygen species (ROS), malondialdehyde, and SLC7A11 protein expression. These results provide an important theoretical basis for further studies into the role of SLC7A11, the effective biomarker and potential drug target, in the occurrence and development of OC.

scholarly journals Identification of Mirna Signature and Key Genes in Colorectal Cancer Lymph Node Metastasis

2021 ◽  
Author(s):  
Xi Wang ◽  
Guangyu Gao ◽  
Zhengrong Chen ◽  
Zhihao Chen ◽  
Mingxiao Han ◽  
...  
Keyword(s):  
Gene Expression ◽  
Colorectal Cancer ◽  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Bioinformatic Analysis ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Cancer Statistics ◽  
Node Metastasis ◽  
Novel Mirna

Abstract Background: miRNAs and mRNAs can serve as biomarkers for the diagnosis, prognosis and therapy of colorectal cancer (CRC), whose metastasis to lymph node is closely related to the poor prognosis. The current study aimed to identify the novel gene signatures in the lymph node metastasis of CRC.Methods: GSE56350, GSE70574 and GSE95109 were downloaded from the Gene Expression Omnibus (GEO) database and 569 colorectal cancer statistics were also downloaded from the The Cancer Genome Atlas (TCGA) database. Differentially expressed miRNAs (DE-miRNAs) were calculated by using R software. Besides, gene ontology and Enriched pathway analysis of target mRNAs were analyzed by using FunRich. Furthermore, the mRNA-miRNA network was constructed using Cytoscape software. Gene expression level was verified by GEO datasets and forty paired lymph node non-metastasis CRC tissues and lymph node metastatic CRC tissues obtained from patients with CRC using quantitative real-time PCR (qPCR) .Results: In total, five DE-miRNAs were selected, and 34 mRNAs were identified after filtering. Moreover, 2 key miRNAs and one gene were identified including hsa-miR-99a, has-miR-100 and heparan sulfate-glucosamine 3-sulfotransferase 2 (HS3ST2). The GEO datasets analysis and qPCR results showed the expression of key miRNA and genes were consistent with that in the bioinformatic analysis. A novel miRNA-mRNA network, hsa-miR-99a-HS3ST2-has-miR-100 was found in lymph node metastasis of CRC after expression analysis, prognostic prediction and experiments confirmation.Conclusions: In summary, the potential miRNAs and genes were found and a novel miRNA-mRNA network was established in CRC lymph node metastasis by systematic bioinformatic analysis and experiments validation, which may be used as potential biomarkers in the development of lymph node metastatic CRC.

scholarly journals FXYD5 is a Marker for Poor Prognosis and a Potential Driver for Metastasis in Ovarian Carcinomas

2015 ◽  
Vol 14 ◽  
pp. CIN.S30565 ◽  
Author(s):  
Pichai Raman ◽  
Timothy Purwin ◽  
Richard Pestell ◽  
Aydin Tozeren
Keyword(s):  
Gene Expression ◽  
Copy Number ◽  
Poor Prognosis ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Ovarian Carcinomas ◽  
Tissue Arrays ◽  
Cancer Genome Atlas ◽  
Underlying Causes ◽  
Web Platform

Ovarian cancer (OC) is a leading cause of cancer mortality, but aside from a few well-studied mutations, very little is known about its underlying causes. As such, we performed survival analysis on ovarian copy number amplifications and gene expression datasets presented by The Cancer Genome Atlas in order to identify potential drivers and markers of aggressive OC. Additionally, two independent datasets from the Gene Expression Omnibus web platform were used to validate the identified markers. Based on our analysis, we identified FXYD5, a glycoprotein known to reduce cell adhesion, as a potential driver of metastasis and a significant predictor of mortality in OC. As a marker of poor outcome, the protein has effective antibodies against it for use in tissue arrays. FXYD5 bridges together a wide variety of cancers, including ovarian, breast cancer stage II, thyroid, colorectal, pancreatic, and head and neck cancers for metastasis studies.

scholarly journals An independent poor-prognosis subtype of hepatocellular carcinoma based on the tumor microenvironment

2021 ◽  
Vol 49 (2) ◽  
pp. 030006052098064
Author(s):  
Junfeng Wang ◽  
Jianying Lou ◽  
Lei Fu ◽  
Qu Jin
Keyword(s):  
Gene Expression ◽  
Hepatocellular Carcinoma ◽  
Tumor Microenvironment ◽  
Poor Prognosis ◽  
Molecular Mechanisms ◽  
Immune Cell ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Using Data

Background Hepatocellular carcinoma (HCC) is a highly malignant tumor with a particularly poor prognosis. The tumor microenvironment (TME) is closely associated with tumorigenesis, progression, and treatment. However, the relationship between TME genes and HCC patient prognosis is poorly understood. Methods In this study, we identified two prognostic subtypes based on the TME using data from The Cancer Genome Atlas and Gene Expression Omnibus. The Microenvironment Cell Populations-counter method was used to evaluate immune cell infiltration in HCC. Differentially expressed genes between molecular subtypes were calculated with the Limma package, and clusterProfiler was used for Gene Ontology and Kyoto Encyclopedia of Genes and Genomes functional enrichment analyses to identify genes related to the independent subtypes. We also integrated mRNA expression data into our bioinformatics analysis. Results We identified 4227 TME-associated genes and 640 genes related to the prognosis of HCC. We defined two major subtypes (Clusters 1 and 2) based on the analysis of TME-associated gene expression. Cluster 1 was characterized by increased expression of immune-associated genes and a worse prognosis than Cluster 2. Conclusions The identification of these HCC subtypes based on the TME provides further insight into the molecular mechanisms and prediction of HCC prognosis.

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