scholarly journals Sex, age, tissue, and disease patterns of matrisome expression in GTEx transcriptome data

2021 ◽  
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 ◽  
Cancer Genome Atlas ◽  
Unknown Gene ◽  
Gene Expression Levels

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 recapitulated 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 388 genes varied by age and 222 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 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 matrix changes. Altogether, these findings indicate that the transcriptome, in general, and GTEx in particular, has value in understanding the state of organ ECM.

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 Data mining of immune-related prognostic genes in metastatic melanoma microenvironment

2020 ◽  
Vol 40 (11) ◽  
Author(s):  
Wei Han ◽  
Biao Huang ◽  
Xiao-Yu Zhao ◽  
Guo-Liang Shen
Keyword(s):  
Gene Expression ◽  
Tumor Microenvironment ◽  
Metastatic Melanoma ◽  
Interaction Network ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Protein Protein Interaction ◽  
Subtype Identification ◽  
Cancer Genome Atlas ◽  
Immune Related Genes

Abstract Skin cutaneous melanoma (SKCM) is one of the most deadly malignancies. Although immunotherapies showed the potential to improve the prognosis for metastatic melanoma patients, only a small group of patients can benefit from it. Therefore, it is urgent to investigate the tumor microenvironment in melanoma as well as to identify efficient biomarkers in the diagnosis and treatments of SKCM patients. A comprehensive analysis was performed based on metastatic melanoma samples from the Cancer Genome Atlas (TCGA) database and ESTIMATE algorithm, including gene expression, immune and stromal scores, prognostic immune-related genes, infiltrating immune cells analysis and immune subtype identification. Then, the differentially expressed genes (DEGs) were obtained based on the immune and stromal scores, and a list of prognostic immune-related genes was identified. Functional analysis and the protein–protein interaction network revealed that these genes enriched in multiple immune-related biological processes. Furthermore, prognostic genes were verified in the Gene Expression Omnibus (GEO) databases and used to predict immune infiltrating cells component. Our study revealed seven immune subtypes with different risk values and identified T cells as the most abundant cells in the immune microenvironment and closely associated with prognostic outcomes. In conclusion, the present study thoroughly analyzed the tumor microenvironment and identified prognostic immune-related biomarkers for metastatic melanoma.

scholarly journals ExonSkipDB: functional annotation of exon skipping event in human

2019 ◽  
Author(s):  
Pora Kim ◽  
Mengyuan Yang ◽  
Ke Yiya ◽  
Weiling Zhao ◽  
Xiaobo Zhou
Keyword(s):  
Functional Annotation ◽  
Exon Skipping ◽  
Tissue Expression ◽  
The Cancer Genome Atlas ◽  
Multiple Cancer ◽  
Annotation Database ◽  
Reading Frame ◽  
Normal Tissues ◽  
Cancer Genome Atlas ◽  
Functional Features

AbstractExon skipping (ES) is reported to be the most common alternative splicing event due to loss of functional domains/sites or shifting of the open reading frame (ORF), leading to a variety of human diseases and considered therapeutic targets. To date, systematic and intensive annotations of ES events based on the skipped exon units in cancer and normal tissues are not available. Here, we built ExonSkipDB, the ES annotation database available at https://ccsm.uth.edu/ExonSkipDB/, aiming to provide a resource and reference for functional annotation of ES events in multiple cancer and tissues to identify therapeutically targetable genes in individual exon units. We collected 14 272 genes that have 90 616 and 89 845 ES events across 33 cancer types and 31 normal tissues from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx). For the ES events, we performed multiple functional annotations. These include ORF assignment of exon skipped transcript, studies of lost protein functional features due to ES events, and studies of exon skipping events associated with mutations and methylations based on multi-omics evidence. ExonSkipDB will be a unique resource for cancer and drug research communities to identify therapeutically targetable exon skipping events.

scholarly journals Downregulated SPINK4 is associated with poor survival in colorectal cancer

BMC Cancer ◽  
2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Xiaojie Wang ◽  
Qian Yu ◽  
Waleed M. Ghareeb ◽  
Yiyi Zhang ◽  
Xingrong Lu ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Expression Data ◽  
Poor Survival ◽  
Protein Levels ◽  
Normal Tissues ◽  
Human Protein Atlas ◽  
Cancer Genome Atlas ◽  
Independent Indicator

Abstract Background SPINK4 is known as a gastrointestinal peptide in the gastrointestinal tract and is abundantly expressed in human goblet cells. The clinical significance of SPINK4 in colorectal cancer (CRC) is largely unknown. Methods We retrieved the expression data of 1168 CRC patients from 3 Gene Expression Omnibus (GEO) datasets (GSE24551, GSE39582, GSE32323) and The Cancer Genome Atlas (TCGA) to compare the expression level of SPINK4 between CRC tissues and normal colorectal tissues and to evaluate its value in predicting the survival of CRC patients. At the protein level, these results were further confirmed by data mining in the Human Protein Atlas and by immunohistochemical staining of samples from 81 CRC cases in our own center. Results SPINK4 expression was downregulated in CRC compared with that in normal tissues, and decreased SPINK4 expression at both the mRNA and protein levels was associated with poor prognosis in CRC patients from all 3 GEO datasets, the TCGA database and our cohort. Additionally, lower SPINK4 expression was significantly related to higher TNM stage. Moreover, in multivariate regression, SPINK4 was confirmed as an independent indicator of poor survival in CRC patients in all databases and in our own cohort. Conclusions We concluded that reduced expression of SPINK4 relates to poor survival in CRC, functioning as a novel indicator.

scholarly journals The role of miR-92b in cholangiocarcinoma patients

2018 ◽  
Vol 33 (3) ◽  
pp. 293-300 ◽  
Author(s):  
Min-hang Zhou ◽  
Hong-wei Zhou ◽  
Mo Liu ◽  
Jun-zhong Sun
Keyword(s):  
Gene Expression ◽  
Overall Survival ◽  
Gene Expression Omnibus ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Positive Regulation ◽  
Cancer Genome Atlas ◽  
High Level ◽  
Genome Atlas

Purpose: The role of microRNA (miRNA) in cholangiocarcinoma was not clear. The aim of this study was to find the potential diagnostic and prognostic miRNA in cholangiocarcinoma patients. Methods: The miRNA expression profiles in cholangiocarcinoma patients from The Cancer Genome Atlas and Gene Expression Omnibus (GSE53870) were analyzed. The comparison of overall survival was performed using the Kaplan–Meier method. The targeted genes of prognostic miRNA were identified in miRanda, PicTar, or TargetScan, and their cell signaling pathways were analyzed by the Database for Annotation, Visualization and Integrated Discovery. Results: In The Cancer Genome Atlas and the Gene Expression Omnibus miRNA dataset, miR-92b and miR-99a were found with concordant directionality, up-regulated and down-regulated, respectively. In The Cancer Genome Atlas survival data, patients with the high level of miR-99b had obviously shorter overall survival time ( P=0.038). However, the level of miR-99a was not found to be significant. The 17 shared target genes of miR-92b were identified, such as DAB21IP, BCL21L11, SPHK2, PER2, and TSC1. The related pathways included positive regulation of transcription, positive regulation of cellular biosynthetic process, regulation of programmed cell death, etc. Conclusion: miR-92b was up-regulated in cholangiocarcinoma compared with normal controls. The high level of miR-92b was associated with adverse outcomes in cholangiocarcinoma patients, which might be partly explained by the targeted genes of miR-92b and their signaling pathways.

scholarly journals Tumor microenvironment characterization in stage IV gastric cancer

2021 ◽  
Vol 41 (1) ◽  
Author(s):  
Xianxue Zhang ◽  
Feng Yang ◽  
Zhenbao Wang
Keyword(s):  
Gene Expression ◽  
Gastric Cancer ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Stage Iv ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Stage Iv Gastric Cancer ◽  
Th 17 ◽  
Cancer Genome Atlas

Abstract Immunotherapy is remarkably affected by the immune environment of the principal tumor. Nonetheless, the immune environment’s clinical relevance in stage IV gastric cancer (GC) is largely unknown. The gene expression profiles of 403 stage IV GC patients in the three cohorts: GEO (Gene Expression Omnibus, GSE84437 (n=292) and GSE62254 (n=77), and TCGA (The Cancer Genome Atlas, n=34) were used in the present study. Using four publicly available stage IV GC expression datasets, 29 immune signatures were expression profiled, and on this basis, we classified stage IV GC. The classification was conducted using the hierarchical clustering method. Three stage IV GC subtypes L, M, and H were identified representing low, medium, and high immunity, respectively. Immune correlation analysis of these three types revealed that Immune H exhibited a better prognostic outcome as well as a higher immune score compared with other subtypes. There was a noticeable difference in the three subgroups of HLA genes. Further, on comparing with other subtypes, CD86, CD80, CD274, CTLA4, PDCD1, and PDCD1LG2 had higher expression in the Immunity H subtype. In stage IV GC, potentially positive associations between immune and pathway activities were displayed, due to the enrichment of pathways including TNF signaling, Th-17 cell differentiation, and JAK-STAT signaling pathways in Immunity H vs Immunity L subtypes. External cohorts from TCGA cohort ratified these results. The identification of stage IV GC subtypes has potential clinical implications in stage IV GC treatment.

Using machine learning method to identify MYLK as a novel marker to predict biochemical recurrence in prostate cancer

2021 ◽  
Vol 15 (1) ◽  
pp. 29-41
Author(s):  
Peng Qiao ◽  
Di Zhang ◽  
Song Zeng ◽  
Yicun Wang ◽  
Biao Wang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Prostate Cancer ◽  
Biochemical Recurrence ◽  
Surgical Margin ◽  
Gene Expression Omnibus ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Support Vector ◽  
Cancer Genome Atlas ◽  
Genome Atlas

Aim: This study aims to identify novel marker to predict biochemical recurrence (BCR) in prostate cancer patients after radical prostatectomy with negative surgical margin. Materials & methods: The Cancer Genome Atlas database, Gene Expression Omnibus database and Cancer Cell Line Encyclopedia database were employed. The ensemble support vector machine-recursive feature elimination method was performed to select crucial gene for BCR. Results: We identified MYLK as a novel and independent biomarker for BCR in The Cancer Genome Atlas training cohort and confirmed in four independent Gene Expression Omnibus validation cohorts. Multi-omic analysis suggested that MYLK was a DNA methylation-driven gene. Additionally, MYLK had significant positive correlations with immune infiltrations. Conclusion: MYLK was identified and validated as a novel, robust and independent biomarker for BCR in prostate cancer.

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.

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