scholarly journals Multi-Omics Integrative Analysis Uncovers Molecular Subtypes and mRNAs as Therapeutic Targets for Liver Cancer

2021 ◽  
Vol 8 ◽  
Author(s):  
Yi Shen ◽  
Wei Xiong ◽  
Qi Gu ◽  
Qin Zhang ◽  
Jia Yue ◽  
...  
Keyword(s):  
Liver Cancer ◽  
Molecular Subtypes ◽  
Therapeutic Targets ◽  
Clinical Information ◽  
Copy Number Variations ◽  
The Cancer Genome Atlas ◽  
Liver Carcinoma ◽  
Normal Tissues ◽  
Omics Analysis ◽  
Cancer Tissues

Objective: This study aimed to systematically analyze molecular subtypes and therapeutic targets of liver cancer using integrated multi-omics analysis.Methods: DNA copy number variations (CNVs), simple nucleotide variations (SNVs), methylation, transcriptome as well as corresponding clinical information for liver carcinoma were retrieved from The Cancer Genome Atlas (TCGA). Multi-omics analysis was performed to identify molecular subtypes of liver cancer via integrating CNV, methylation as well as transcriptome data. Immune scores of two molecular subtypes were estimated using tumor immune estimation resource (TIMER) tool. Key mRNAs were screened and prognosis analysis was performed, which were validated using RT-qPCR. Furthermore, mutation spectra were analyzed in the different subtypes.Results: Two molecular subtypes (iC1 and iC2) were conducted for liver cancer. Compared with the iC2 subtype, the iC1 subtype had a worse prognosis and a higher immune score. Two key mRNAs (ANXA2 and CHAF1B) were significantly related to liver cancer patients' prognosis, which were both up-regulated in liver cancer tissues in comparison to normal tissues. Seventeen genes with p < 0.01 differed significantly for SNV loci between iC1 and iC2 subtypes.Conclusion: Our integrated multi-omics analyses provided new insights into the molecular subtypes of liver cancer, helping to identify novel mRNAs as therapeutic targets and uncover the mechanisms of liver cancer.

FADS1 is a Prognostic Biomarker in Bladder Cancer: A Study Based on TCGA Data

2020 ◽  
Vol 23 ◽  
Author(s):  
Ying Lu ◽  
Jing Shao ◽  
Xu Shu ◽  
Yaofei Jiang ◽  
Jianfang Rong ◽  
...  
Keyword(s):  
Bladder Cancer ◽  
Histological Grade ◽  
Clinical Stage ◽  
Fatty Acid Desaturase ◽  
Clinical Information ◽  
The Cancer Genome Atlas ◽  
Cancer Prognosis ◽  
Normal Tissues ◽  
Potential Biomarker ◽  
T Classification

Aim and Objective: Fatty acid desaturase 1 (FADS1) has been reported to be a potential biomarker in various cancers. However, no study has explored the relationship between FADS1 expression and bladder cancer. Our study aimed to investigate the role of FADS1 in bladder cancer prognosis via The Cancer Genome Atlas (TCGA). Materials and Methods: RNA-Seq expression of 414 tumor tissues and 19 paired normal tissues, as well as corresponding clinical data, were downloaded from TCGA database. Two cancer cases were excluded due to a lack of clinical information. The association between FADS1 and the clinicopathological features of bladder cancer was analyzed. This study was conducted in October of 2019 in China. Results: The high expression of FADS1 in bladder cancer was significantly related to histological grade (OR = 0.155 for low vs. high), clinical stage (OR=2.074 for III or IV vs. I or II), T classification (OR=2.326 for T3 or T4 vs. T1 or T2), lymphatic metastasis (OR=1.923 for N1 or N2 or N3 vs. N0) and distant metastasis (OR=4.883 for yes vs. no) (all p-values <0.05). Bladder cancer with high FADS1 levels was related to a worse prognosis than bladder cancer with low FADS1 levels (p= 1.626*10-5 ), according to median expression value 3.622. FADS1 was an independent factor of overall survival in bladder cancer, with a hazard ratio of 1.048 (95%CI: 1.020–1.077, p = 0.001). Conclusions: Increased FADS1 expression in bladder cancer is associated with advanced clinical pathological features and may be a potential biomarker for poor prognosis.

scholarly journals deepBase v3.0: expression atlas and interactive analysis of ncRNAs from thousands of deep-sequencing data

2020 ◽  
Vol 49 (D1) ◽  
pp. D877-D883
Author(s):  
Fangzhou Xie ◽  
Shurong Liu ◽  
Junhao Wang ◽  
Jiajia Xuan ◽  
Xiaoqin Zhang ◽  
...  
Keyword(s):  
High Throughput Sequencing ◽  
Clinical Information ◽  
Sequencing Data ◽  
Normal Tissues ◽  
Interactive Analysis ◽  
High Throughput Sequencing Data ◽  
Expression Atlas ◽  
Expression Evolution ◽  
Noninvasive Biomarkers ◽  
Cancer Tissues

Abstract Eukaryotic genomes encode thousands of small and large non-coding RNAs (ncRNAs). However, the expression, functions and evolution of these ncRNAs are still largely unknown. In this study, we have updated deepBase to version 3.0 (deepBase v3.0, http://rna.sysu.edu.cn/deepbase3/index.html), an increasingly popular and openly licensed resource that facilitates integrative and interactive display and analysis of the expression, evolution, and functions of various ncRNAs by deeply mining thousands of high-throughput sequencing data from tissue, tumor and exosome samples. We updated deepBase v3.0 to provide the most comprehensive expression atlas of small RNAs and lncRNAs by integrating ∼67 620 data from 80 normal tissues and ∼50 cancer tissues. The extracellular patterns of various ncRNAs were profiled to explore their applications for discovery of noninvasive biomarkers. Moreover, we constructed survival maps of tRNA-derived RNA Fragments (tRFs), miRNAs, snoRNAs and lncRNAs by analyzing &gt;45 000 cancer sample data and corresponding clinical information. We also developed interactive webs to analyze the differential expression and biological functions of various ncRNAs in ∼50 types of cancers. This update is expected to provide a variety of new modules and graphic visualizations to facilitate analyses and explorations of the functions and mechanisms of various types of ncRNAs.

scholarly journals An angiogenesis-related long noncoding RNA signature correlates with prognosis in patients with hepatocellular carcinoma

2021 ◽  
Vol 41 (4) ◽  
Author(s):  
Dengliang Lei ◽  
Yue Chen ◽  
Yang Zhou ◽  
Gangli Hu ◽  
Fang Luo
Keyword(s):  
Hepatocellular Carcinoma ◽  
Liver Cancer ◽  
Long Noncoding Rna ◽  
Noncoding Rna ◽  
Enrichment Analysis ◽  
Clinical Information ◽  
Roc Curves ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Highly Correlated

Abstract Hepatocellular carcinoma (HCC) is one of the most prevalent and lethal cancers worldwide. Neovascularization is closely related to the malignancy of tumors. We constructed a signature of angiogenesis-related long noncoding RNA (lncRNA) to predict the prognosis of patients with HCC. The lncRNA expression matrix of 424 HCC patients was downloaded from The Cancer Genome Atlas (TCGA). First, gene set enrichment analysis (GSEA) was used to distinguish the differentially expressed genes of the angiogenesis genes in liver cancer and adjacent tissues. Next, a signature of angiogenesis-related lncRNAs was constructed using univariate and multivariate analyses, and receiver operating characteristic (ROC) curves were used to assess the accuracy. The signature and relevant clinical information were used to construct the nomogram. A 5-lncRNA signature was highly correlated with overall survival (OS) in HCC patients and performed well in evaluations using the C-index, areas under the curve, and calibration curves. In summary, the 5-lncRNA model can serve as an accurate signature to predict the prognosis of patients with liver cancer, but its mechanism of action must be further elucidated by experiments.

The glycobiological landscape of breast cancer: insights into galectins and O-GlcNAc homeostasis-related genes

2021 ◽  
Author(s):  
Rada Tazhitdinova ◽  
Alexander V Timoshenko
Keyword(s):  
Breast Cancer ◽  
Cancer Biology ◽  
Breast Cancer Subtype ◽  
The Cancer Genome Atlas ◽  
Correlation Relationship ◽  
Cancer Data ◽  
Normal Tissues ◽  
Genes Encoding ◽  
Genetic Landscape ◽  
Cancer Tissues

Abstract Purpose This study aimed to assess the functional associations between genes of the glycobiological landscape encoding galectins and O-GlcNAc cycle enzymes in the context of breast cancer biology and clinical applications. Methods An in silico analysis of the breast cancer data from The Cancer Genome Atlas was conducted comparing expression, pairwise correlations, and prognostic value for 17 genes encoding galectins, O-GlcNAc cycle enzymes, and cell stemness-related transcription factors. Results Multiple general and breast cancer subtype-specific differences in galectin/O-GlcNAc genetic landscape markers were observed and classified. Specifically, LGALS12 was found to be significantly downregulated in breast cancer tissues across all subtypes while LGALS2 and GFPT1 showed potential as prognostic markers. Remarkably, there was an overall loss of both correlation strength and correlation relationship between expression of galectin/O-GlcNAc landscape genes in the breast cancer samples versus normal tissues. Six gene pairs (GFPT1/LGALS1, GFPT1/LGALS3, GFPT1/LGALS12, GFPT1/KLF4, OGT/LGALS12, and OGT/KLF4) were found to be potential diagnostic markers for breast cancer. Conclusions These findings indicate that the glycobiological landscape of breast cancer underwent significant remodeling, which might be associated with switching galectin gene regulation within a framework of O-GlcNAc homeostasis.

scholarly journals Putatively cancer-specific exon–exon junctions are shared across patients and present in developmental and other non-cancer cells

NAR Cancer ◽  
2020 ◽  
Vol 2 (1) ◽  
Author(s):  
Julianne K David ◽  
Sean K Maden ◽  
Benjamin R Weeder ◽  
Reid F Thompson ◽  
Abhinav Nellore
Keyword(s):  
Rna Splicing ◽  
Tissue Expression ◽  
The Body ◽  
The Cancer Genome Atlas ◽  
Cancer Type ◽  
Rna Seq ◽  
Normal Tissues ◽  
Cancer Types ◽  
Exon Junctions ◽  
Cancer Tissues

Abstract This study probes the distribution of putatively cancer-specific junctions across a broad set of publicly available non-cancer human RNA sequencing (RNA-seq) datasets. We compared cancer and non-cancer RNA-seq data from The Cancer Genome Atlas (TCGA), the Genotype-Tissue Expression (GTEx) Project and the Sequence Read Archive. We found that (i) averaging across cancer types, 80.6% of exon–exon junctions thought to be cancer-specific based on comparison with tissue-matched samples (σ = 13.0%) are in fact present in other adult non-cancer tissues throughout the body; (ii) 30.8% of junctions not present in any GTEx or TCGA normal tissues are shared by multiple samples within at least one cancer type cohort, and 87.4% of these distinguish between different cancer types; and (iii) many of these junctions not found in GTEx or TCGA normal tissues (15.4% on average, σ = 2.4%) are also found in embryological and other developmentally associated cells. These findings refine the meaning of RNA splicing event novelty, particularly with respect to the human neoepitope repertoire. Ultimately, cancer-specific exon–exon junctions may have a substantial causal relationship with the biology of disease.

scholarly journals miR-183-5p promotes proliferation and migration in hepatocellular carcinoma by targeting IRS1 and its association with patient survival

2020 ◽  
Vol 35 (3) ◽  
pp. 83-89
Author(s):  
Rong Yan ◽  
Kang Li ◽  
Dawei Yuan ◽  
Haonan Wang ◽  
Wei Chen ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Liver Cancer ◽  
Cancer Progression ◽  
Normal Tissues ◽  
Report Analysis ◽  
In Vitro Effects ◽  
And Migration ◽  
Cancer Tissues ◽  
Proliferation And Migration

Background: MiR-183-5p plays an important role in the pathophysiology of many tumors, while the role of MiR-183-5p in liver cancer is unclear. Methods: In this study, quantitative reverse transcription-polymerase chain reaction and Western blotting were used to detect the expression of miR-183-5p in liver cancer cell lines, liver cancer tissues, and normal tissues adjacent to the cancer, and to explore the mechanism of miR-183-5p regulating liver cancer progression. The in vitro effects of miR-183-5p were evaluated by CCK-8, colony formation test, and wound healing test. Various databases were used to predict the target mRNA of miR-183-5p and verified by luciferase report analysis. In addition, the effects of miR-183-5p and its target gene on the survival of patients with liver cancer were also analyzed. Results: miR-183-5p was highly expressed in hepatocellular carcinoma cells and tissues, and was related to some clinicopathological features. MiR-183-5p can promote the proliferation and migration of liver cancer cells. Using the bioinformatics database, we proved that miR-183-5p is related to the survival of liver cancer patients. Insulin receptor substrate 1 (IRS1) is a target of miR-183-5p, and luciferase analysis confirmed that miR-183-5p combines with the 3′-untranslated region (3′-UTR) of IRS1. Conclusion: The miR-183-5p/IRS1 axis may be a new target for liver cancer research.

scholarly journals The expression and Clinical Significance of miRNA-135a and Bach1 in colorectal cancer

2021 ◽  
Author(s):  
Yang zhi Jiang ◽  
Qing Guo Tao ◽  
fei yan Zhu
Keyword(s):  
Colorectal Cancer ◽  
Colon Cancer ◽  
Clinical Information ◽  
Control Group ◽  
Tumor Control ◽  
Cancer Tissue ◽  
Expression Levels ◽  
Real Time Quantitative Pcr ◽  
Normal Tissues ◽  
Cancer Tissues

BACKGROUND AIM To explore the correlation between the expression of miRNA-135a and Bach1 in colorectal cancer tissue and the patient's clinical information.  Methods   60 patients with colorectal carcinoma were treated as a control group. Real-time quantitative PCR assays and immunohistochemistry method were performed to detect the expression of miRNA-135a and Bach1 in 60 colorectal carcinomas and adjacent normal tissues, and the clinical and pathological classifications had also been investigated. The SPSS 19.00 software was used. All data represented mean±SD of three independent experiments. P&lt;0.05 was considered statistically significant. Results  miRNA-135a expression levels increased significantly in the colon cancer tissues compared with the non-tumor control tissues(P&lt;0.01). miRNA-135a expression levels were higher in stage III/IV than in stage I/II colon cancer patients. The expression level of Bach1 in colorectal cancer was significantly lower(P&lt;0.01). Bach1 and miRNA-135a were negatively correlated.  Conclusions:  The levels of miRNA-135a and Bach1 were opposite, the over-expression of miRNA-135a might downregulated the expression of Bach1, which might be involved in the pathogenesis of colorectal cancer.

scholarly journals Multi-omics analysis to identify driving factors in colorectal cancer

Epigenomics ◽  
2020 ◽  
Vol 12 (18) ◽  
pp. 1633-1650
Author(s):  
Xi Xu ◽  
Chaoju Gong ◽  
Yunfeng Wang ◽  
Yanyan Hu ◽  
Hong Liu ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Molecular Mechanisms ◽  
Copy Number Variations ◽  
The Cancer Genome Atlas ◽  
Single Nucleotide Variants ◽  
Single Nucleotide ◽  
Omics Analysis ◽  
Competing Endogenous Rna Network ◽  
Cancer Genome Atlas

Aim: We aim to identify driving genes of colorectal cancer (CRC) through multi-omics analysis. Materials & methods: We downloaded multi-omics data of CRC from The Cancer Genome Atlas dataset. Integrative analysis of single-nucleotide variants, copy number variations, DNA methylation and differentially expressed genes identified candidate genes that carry CRC risk. Kernal genes were extracted from the weighted gene co-expression network analysis. A competing endogenous RNA network composed of CRC-related genes was constructed. Biological roles of genes were further investigated in vitro. Results: We identified LRRC26 and REP15 as novel prognosis-related driving genes for CRC. LRRC26 hindered tumorigenesis of CRC in vitro. Conclusion: Our study identified novel driving genes and may provide new insights into the molecular mechanisms of CRC.

scholarly journals A Simple Competing Endogenous RNA Network Identifies Novel mRNA, miRNA, and lncRNA Markers in Human Cholangiocarcinoma

2019 ◽  
Vol 2019 ◽  
pp. 1-13 ◽  
Author(s):  
Cheng Zhang ◽  
Chunlin Ge
Keyword(s):  
Cox Regression ◽  
Clinical Information ◽  
The Cancer Genome Atlas ◽  
Primary Liver Tumor ◽  
Normal Tissues ◽  
Cerna Network ◽  
Tumorigenesis And Progression ◽  
Competing Endogenous Rna Network ◽  
Cancer Genome Atlas ◽  
Novel Biomarkers

Background. Cholangiocarcinoma (CCA) is the second most common malignant primary liver tumor and has shown an alarming increase in incidence over the last two decades. However, the mechanisms behind tumorigenesis and progression remain insufficient. The present study aimed to uncover the underlying regulatory mechanism on CCA and find novel biomarkers for the disease prognosis. Method. The RNA-sequencing (RNA-seq) datasets of lncRNAs, miRNAs, and mRNAs in CCA as well as relevant clinical information were obtained from the Cancer Genome Atlas (TCGA) database. After pretreatment, differentially expressed RNAs (DERNAs) were identified and further interrogated for their correlations with clinical information. Prognostic RNAs were selected using univariate Cox regression. Then, a ceRNA network was constructed based on these RNAs. Results. We identified a total of five prognostic DEmiRNAs, 63 DElncRNAs, and 90 DEmRNAs between CCA and matched normal tissues. Integrating the relationship between the different types of RNAs, an lncRNA-miRNA-mRNA network was established and included 28 molecules and 47 interactions. Screened prognostic RNAs involved in the ceRNA network included 3 miRNAs (hsa-mir-1295b, hsa-mir-33b, and hsa-mir-6715a), 7 lncRNAs (ENSG00000271133, ENSG00000233834, ENSG00000276791, ENSG00000241155, COL18A1-AS1, ENSG00000274737, and ENSG00000235052), and 18 mRNAs (ANO9, FUT4, MLLT3, ABCA3, FSCN2, GRID2IP, NCK2, MACC1, SLC35E4, ST14, SH2D3A, MOB3B, ACTL10, RAB36, ATP1B3, MST1R, SEMA6A, and SEL1L3). Conclusions. Our study identified novel prognostic makers and predicted a previously unknown ceRNA regulatory network in CCA and may provide novel insight into a further understanding of lncRNA-mediated ceRNA regulatory mechanisms in CCA.

scholarly journals Uncovering Prognosis-Related Genes and Pathways by Multi-Omics Analysis in Lung Cancer

Biomolecules ◽  
2020 ◽  
Vol 10 (4) ◽  
pp. 524 ◽  
Author(s):  
Ken Asada ◽  
Kazuma Kobayashi ◽  
Samuel Joutard ◽  
Masashi Tubaki ◽  
Satoshi Takahashi ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Patient Survival ◽  
Clinical Information ◽  
The Cancer Genome Atlas ◽  
Support Vector ◽  
Rna Expression ◽  
Bioinformatics Analyses ◽  
Expression Levels ◽  
Individual Level ◽  
Omics Analysis

Lung cancer is one of the leading causes of death worldwide. Therefore, understanding the factors linked to patient survival is essential. Recently, multi-omics analysis has emerged, allowing for patient groups to be classified according to prognosis and at a more individual level, to support the use of precision medicine. Here, we combined RNA expression and miRNA expression with clinical information, to conduct a multi-omics analysis, using publicly available datasets (the cancer genome atlas (TCGA) focusing on lung adenocarcinoma (LUAD)). We were able to successfully subclass patients according to survival. The classifiers we developed, using inferred labels obtained from patient subtypes showed that a support vector machine (SVM), gave the best classification results, with an accuracy of 0.82 with the test dataset. Using these subtypes, we ranked genes based on RNA expression levels. The top 25 genes were investigated, to elucidate the mechanisms that underlie patient prognosis. Bioinformatics analyses showed that the expression levels of six out of 25 genes (ERO1B, DPY19L1, NCAM1, RET, MARCH1, and SLC7A8) were associated with LUAD patient survival (p < 0.05), and pathway analyses indicated that major cancer signaling was altered in the subtypes.

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