scholarly journals Identification of Key Differentially Expressed MicroRNAs in Cancer Patients Through Pan-cancer Analysis

2018 ◽  
Author(s):  
Yu Hu ◽  
Hayley Dingerdissen ◽  
Samir Gupta ◽  
Robel Kahsay ◽  
Vijay Shanker ◽  
...  
Keyword(s):  
Differential Expression ◽  
Cancer Progression ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Differential Expression Analysis ◽  
The Cancer Genome Atlas ◽  
Differentially Expressed ◽  
Literature Mining ◽  
Wide Range ◽  
Cancer Types

AbstractA number of microRNAs (miRNAs) functioning in gene silencing have been associated with cancer progression. However, common expression patterns of abnormally expressed miRNAs and their potential roles in multiple cancer types have not yet been evaluated. To minimize the difference of patients, we collected miRNA sequencing data of 575 patients with tumor and adjacent non-tumorous tissues from 14 cancer types from The Cancer Genome Atlas (TCGA), and performed differential expression analysis using DESeq2 and edgeR. The results showed that cancer types can be grouped based on the distribution of miRNAs with different expression patterns. We found 81 significantly differentially expressed miRNAs (SDEmiRNAs) unique to one of the 14 cancers may affect patient survival rate, and 21 key SDEmiRNAs (nine overexpressed and 12 under-expressed) associated with at least eight cancers and enriched in more than 60% of patients per cancer, including four newly identified SDEmiRNAs (hsa-mir-4746, hsa-mir-3648, hsa-mir-3687, and hsa-mir-1269a). The downstream effect of these 21 SDEmiRNAs on cellular functions was evaluated through enrichment and pathway analysis of 7,186 protein-coding gene targets from literature mining with known differential expression profiles in cancers. It enables identification of their functional similarity in cell proliferation control across a wide range of cancers and to build common regulatory networks over cancer-related pathways. This is validated by construction of a regulatory network in PI3K pathway. This study provides evidence of the value of further analysis on SDEmiRNAs as potential biomarkers and therapeutic targets for cancer diagnosis and treatment.

scholarly journals Identification of Hub Prognosis-Associated Oxidative Stress Genes in Pancreatic Cancer Using Integrated Bioinformatics Analysis

2020 ◽  
Vol 11 ◽  
Author(s):  
Xin Qiu ◽  
Qin-Han Hou ◽  
Qiu-Yue Shi ◽  
Hai-Xing Jiang ◽  
Shan-Yu Qin
Keyword(s):  
Oxidative Stress ◽  
Gene Expression ◽  
Pancreatic Cancer ◽  
Cancer Progression ◽  
Risk Model ◽  
Cox Regression ◽  
Expression Profiles ◽  
The Cancer Genome Atlas ◽  
Differentially Expressed ◽  
Cox Regression Analysis

BackgroundIntratumoral oxidative stress (OS) has been associated with the progression of various tumors. However, OS has not been considered a candidate therapeutic target for pancreatic cancer (PC) owing to the lack of validated biomarkers.MethodsWe compared gene expression profiles of PC samples and the transcriptome data of normal pancreas tissues from The Cancer Genome Atlas (TCGA) and Genome Tissue Expression (GTEx) databases to identify differentially expressed OS genes in PC. PC patients’ gene profile from the Gene Expression Omnibus (GEO) database was used as a validation cohort.ResultsA total of 148 differentially expressed OS-related genes in PC were used to construct a protein-protein interaction network. Univariate Cox regression analysis, least absolute shrinkage, selection operator analysis revealed seven hub prognosis-associated OS genes that served to construct a prognostic risk model. Based on integrated bioinformatics analyses, our prognostic model, whose diagnostic accuracy was validated in both cohorts, reliably predicted the overall survival of patients with PC and cancer progression. Further analysis revealed significant associations between seven hub gene expression levels and patient outcomes, which were validated at the protein level using the Human Protein Atlas database. A nomogram based on the expression of these seven hub genes exhibited prognostic value in PC.ConclusionOur study provides novel insights into PC pathogenesis and provides new genetic markers for prognosis prediction and clinical treatment personalization for PC patients.

scholarly journals Quantitative Analysis of Differential Expression of HOX Genes in Multiple Cancers

Cancers ◽  
2020 ◽  
Vol 12 (6) ◽  
pp. 1572
Author(s):  
Orit Adato ◽  
Yaron Orenstein ◽  
Juri Kopolovic ◽  
Tamar Juven-Gershon ◽  
Ron Unger
Keyword(s):  
Gene Expression ◽  
Quantitative Analysis ◽  
Differential Expression ◽  
Survival Data ◽  
Hox Genes ◽  
Expression Patterns ◽  
The Cancer Genome Atlas ◽  
Tumor Type ◽  
Hox Gene ◽  
Cancer Types

Transcription factors encoded by Homeobox (HOX) genes play numerous key functions during early embryonic development and differentiation. Multiple reports have shown that mis-regulation of HOX gene expression plays key roles in the development of cancers. Their expression levels in cancers tend to differ based on tissue and tumor type. Here, we performed a comprehensive analysis comparing HOX gene expression in different cancer types, obtained from The Cancer Genome Atlas (TCGA), with matched healthy tissues, obtained from Genotype-Tissue Expression (GTEx). We identified and quantified differential expression patterns that confirmed previously identified expression changes and highlighted new differential expression signatures. We discovered differential expression patterns that are in line with patient survival data. This comprehensive and quantitative analysis provides a global picture of HOX genes’ differential expression patterns in different cancer types.

scholarly journals The Association between TIF1 Family Members and Cancer Stemness in Solid Tumors

Cancers ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 1528
Author(s):  
Patrycja Czerwinska ◽  
Nikola Agata Wlodarczyk ◽  
Anna Maria Jaworska ◽  
Andrzej Adam Mackiewicz
Keyword(s):  
Gene Expression ◽  
Stem Cell ◽  
Solid Tumors ◽  
Cancer Progression ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Family Members ◽  
The Cancer Genome Atlas ◽  
Tumor Type ◽  
Cancer Stemness

Cancer progression entails a gradual loss of a differentiated phenotype in parallel with the acquisition of stem cell-like features. Cancer de-differentiation and the acquisition of stemness features are mediated by the transcriptional and epigenetic dysregulation of cancer cells. Here, using publicly available data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases and harnessing several bioinformatic tools, we characterized the association between Transcriptional Intermediary Factor 1 (TIF1) family members and cancer stemness in 27 distinct types of solid tumors. We aimed to define the prognostic value for TIF1 members in predicting a stem cell-like cancer phenotype and patient outcome. Our results demonstrate that high expression of only one member of the TIF1 family, namely TIF1β (also known as Tripartite Motif protein 28, TRIM28) is consequently associated with enriched cancer stemness across the tested solid tumor types, resulting in a worse prognosis for cancer patients. TRIM28 is highly expressed in higher grade tumors that exhibit stem cell-like traits. In contrast to other TIF1 members, only TIF1β/TRIM28-associated gene expression profiles were robustly enriched with stemness markers regardless of the tumor type. Our work demonstrates that TIF1 family members exhibit distinct expression patterns in stem cell-like tumors, despite their structural and functional similarity. Among other TIF1 members, only TRIM28 might serve as a marker of cancer stemness features.

scholarly journals Reproductive workers show queen-like gene expression in an intermediately eusocial insect, the buff-tailed bumble beeBombus terrestris.

2014 ◽  
Author(s):  
Mark C Harrison ◽  
Robert L Hammond ◽  
Eamonn B Mallon
Keyword(s):  
Differential Expression ◽  
Bombus Terrestris ◽  
Expression Patterns ◽  
Differential Expression Analysis ◽  
Division Of Labour ◽  
Differentially Expressed ◽  
Bumble Bee ◽  
Strong Shift ◽  
Single Genome ◽  
Eusocial Species

Bumble bees represent a taxon with an intermediate level of eusociality within Hymenoptera. The clear division of reproduction between a single founding queen and the largely sterile workers is characteristic for highly eusocial species, whereas the morphological similarity between the bumble bee queen and the workers is typical for more primitively eusocial hymenopterans. Also, unlike other highly eusocial hymenopterans, division of labour among worker sub-castes is plastic and not predetermined by morphology or age. We conducted a differential expression analysis based on RNA-seq data from 11 combinations of developmental stage and caste to investigate how a single genome can produce the distinct castes of queens, workers and males in the buff-tailed bumble beeBombus terrestris. Based on expression patterns, we found males to be the most distinct of all adult castes (2,411 transcripts differentially expressed compared to non-reproductive workers). However, only relatively few transcripts were differentially expressed between males and workers during development (larvae: 71, pupae: 162). This indicates the need for more distinct expression patterns to control behaviour and physiology in adults compared to those required to create different morphologies. Among female castes, reproductive workers and their non-reproductive sisters displayed differential expression in over ten times more transcripts compared to the differential expression found between reproductive workers and their mother queen. This suggests a strong shift towards a more queen-like behaviour and physiology when a worker becomes fertile. This contrasts with eusocial species where reproductive workers are more similar to non-reproductive workers than the queen.

scholarly journals Data analysis of high-throughput sequencing and microarray to identify key signatures of microribonucleic acids in glioblastoma

2021 ◽  
Vol 8 (3) ◽  
pp. 21-33
Author(s):  
A. A. Pushkin ◽  
E. A. Dzenkova ◽  
N. N. Timoshkina ◽  
D. Yu. Gvaldin
Keyword(s):  
Mirna Expression ◽  
High Throughput Sequencing ◽  
Patient Survival ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Differential Expression Analysis ◽  
The Cancer Genome Atlas ◽  
Normal Brain ◽  
Sequencing Data ◽  
Tissue Samples

Purpose of the study. This research was devoted to study of mRNA and miRNA expression patterns in glioglastomas using The Cancer Genome Atlas (TCGA) data, to search for genetic determinants that determine the prognosis of patient survival and to create of interaction networks for glioblastomas.Materials and methods. Based on the data of the open TCGA database groups of glioblastomas and conventionally normal brain tissue samples were formed. Survival gene and miRNA expression data were extracted for each sample. After the data stratification by groups the differential expression analysis and search the genes affecting patient survival was carried out. The enrichment analysis by functional affiliation and an interactome analysis were performed.Results. A total of 156 glioblastoma samples with mRNA sequencing data, 571 samples with microarray microRNA analysis data, and 15 control samples were analyzed. Networks of mRNA-miRNA interactions were built and expression profiles of genes and miRNAs characteristic of glioblastomas were developed. We have determined the genes which aberrant level is associated with survival and shown the pairwise DEG and DE of microRNA correlations.Conclusion. The microRNA-mRNA regulatory pairs identified for glioblastomas can stimulate the development of new therapeutic approaches based on subtype-specific regulatory mechanisms of oncogenesis.

scholarly journals Identification of the circRNA-miRNA-mRNA Regulatory Network in Bladder Cancer by Bioinformatics Analysis

2021 ◽  
Vol 2021 ◽  
pp. 1-22
Author(s):  
Jiancheng Lv ◽  
Ping-an Chang ◽  
Xin Li ◽  
Xiao Yang ◽  
Jie Han ◽  
...  
Keyword(s):  
Bladder Cancer ◽  
Cancer Progression ◽  
Drug Targets ◽  
Regulatory Mechanism ◽  
Expression Profiles ◽  
Deep Understanding ◽  
Interaction Network ◽  
Circular Rna ◽  
The Cancer Genome Atlas ◽  
Differentially Expressed

In recent years, increasing evidence shows that circular RNA (circRNA) disorder is closely related to tumorigenesis and cancer progression. However, the regulatory functions of most circRNAs in bladder cancer (BCa) remain unclear. This study was aimed at exploring the molecular regulatory mechanism of circRNAs in BCa. We obtained four datasets of circRNA, microRNA (miRNA), and messenger (mRNA) expression profiles from the Gene Expression Omnibus and The Cancer Genome Atlas microarray databases and identified 434, 367, and 4799/4841 differentially expressed circRNAs, miRNAs, and mRNAs, respectively. With these differentially expressed RNAs, we established a circRNA-miRNA-mRNA targeted interaction network. A total of 18, 24, and 51 central circRNAs, miRNAs, and mRNAs were identified, respectively. Among them, the top 10 mRNAs that had high connectivity with other circRNAs and miRNAs were regarded as hub genes. We detected the expression levels of these 10 mRNAs in 16 pairs of BCa tissues and adjacent normal tissues through quantitative real-time polymerase chain reaction. The differentially expressed mRNAs and central mRNAs were enriched in the processes and pathways that are associated with the growth, differentiation, proliferation, and apoptosis of tumor cells. The outstanding genes (CDCA4, GATA6, LATS2, RHOB, ZBTB4, and ZFPM2) also interacted with numerous drugs, indicating their potency as biomarkers and drug targets. The findings of this study provide a deep understanding of the circRNA-related competitive endogenous RNA regulatory mechanism in BCa pathogenesis.

scholarly journals Individualized lncRNA differential expression profile reveals heterogeneity of breast cancer

Oncogene ◽  
2021 ◽  
Author(s):  
Zhangxiang Zhao ◽  
YingYing Guo ◽  
Yaoyao Liu ◽  
Lichun Sun ◽  
Bo Chen ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Differential Expression ◽  
Epithelial Mesenchymal Transition ◽  
Expression Profiles ◽  
Breast Cancer Subtype ◽  
Differential Expression Analysis ◽  
Differentially Expressed ◽  
Migration And Invasion ◽  
Response Analysis ◽  
Mesenchymal Transition

AbstractLong non-coding RNAs (lncRNAs) play key regulatory roles in breast cancer. However, population-level differential expression analysis methods disregard the heterogeneous expression of lncRNAs in individual patients. Therefore, we individualized lncRNA expression profiles for breast invasive carcinoma (BRCA) using the method of LncRNA Individualization (LncRIndiv). After evaluating the robustness of LncRIndiv, we constructed an individualized differentially expressed lncRNA (IDElncRNA) profile for BRCA and investigated the subtype-specific IDElncRNAs. The breast cancer subtype-specific IDElncRNA showed frequent co-occurrence with alterations of protein-coding genes, including mutations, copy number variation and differential methylation. We performed hierarchical clustering to subdivide TNBC and revealed mesenchymal subtype and immune subtype for TNBC. The TNBC immune subtype showed a better prognosis than the TNBC mesenchymal subtype. LncRNA PTOV1-AS1 was the top differentially expressed lncRNA in the mesenchymal subtype. And biological experiments validated that the upregulation of PTOV1-AS1 could downregulate TJP1 (ZO-1) and E-Cadherin, and upregulate Vimentin, which suggests PTOV1-AS1 may promote epithelial-mesenchymal transition and lead to migration and invasion of TNBC cells. The mesenchymal subtype showed a higher fraction of M2 macrophages, whereas the immune subtype was more associated with CD4 + T cells. The immune subtype is characterized by genomic instability and upregulation of immune checkpoint genes, thereby suggesting a potential response to immunosuppressive drugs. Last, drug response analysis revealed lncRNA ENSG00000230082 (PRRT3-AS1) is a potential resistance biomarker for paclitaxel in BRCA treatment. Our analysis highlights that IDElncRNAs can characterize inter-tumor heterogeneity in BRCA and the new TNBC subtypes indicate novel insights into TNBC immunotherapy.

scholarly journals RNA sequencing reveals interacting key determinants of osteoarthritis acting in subchondral bone and articular cartilage

2020 ◽  
Author(s):  
Margo Tuerlings ◽  
Marcella van Hoolwerff ◽  
Evelyn Houtman ◽  
Eka (H.E.D.) Suchiman ◽  
Nico Lakenberg ◽  
...  
Keyword(s):  
Differential Expression ◽  
Rna Sequencing ◽  
Differentially Expressed Genes ◽  
Subchondral Bone ◽  
Expression Patterns ◽  
Differential Expression Analysis ◽  
Differentially Expressed ◽  
Risk Genes ◽  
Joint Replacement Surgery ◽  
And Cartilage

ABSTRACTObjectiveThe aim of this study was to identify key determinants of the interactive osteoarthritis (OA) pathophysiological processes of subchondral bone and cartilage.MethodsWe performed RNA sequencing on macroscopically preserved and lesioned OA subchondral bone of patients that underwent joint replacement surgery due to OA (N=24 pairs; 6 hips, 18 knees, RAAK-study). Unsupervised hierarchical clustering and differential expression analyses were performed. Results were combined with previously identified, differentially expressed genes in cartilage (partly overlapping samples) as well as with recently identified OA risk genes.ResultsWe identified 1569 genes significantly differentially expressed between lesioned and preserved subchondral bone, including CNTNAP2 (FC=2.4, FDR=3.36×10−5) and STMN2 (FC=9.6, FDR=3.36×10−3). Among the identified genes, 305 were also differentially expressed and with same direction of effects in cartilage, including IL11 and CHADL, recently acknowledged OA susceptibility genes. Upon differential expression analysis stratifying for joint site, we identified 509 genes exclusively differentially expressed in subchondral bone of the knee, such as KLF11 and WNT4. These exclusive knee genes were enriched for involvement in epigenetic processes, characterized by for instance HIST1H3J and HIST1H3H.ConclusionTo our knowledge, we are the first to report on differential gene expression patterns of paired OA subchondral bone tissue using RNA sequencing. Among the most consistently differentially expressed genes with OA pathophysiology in both bone and cartilage were IL11 and CHADL. As these genes were recently also identified as robust OA risk genes they classify as attractive druggable targets acting on two OA disease relevant tissues.

scholarly journals The Mechanobiome: A Goldmine for Cancer Therapeutics

2020 ◽  
Author(s):  
Eleana Parajón ◽  
Alexandra Surcel ◽  
Douglas N. Robinson
Keyword(s):  
Cancer Progression ◽  
Expression Patterns ◽  
Cancer Therapeutics ◽  
Cellular Systems ◽  
Cancer Drug ◽  
Altered Expression ◽  
Mechanical Adaptation ◽  
Gene And Protein Expression ◽  
Wide Range ◽  
Cancer Types

Cancer progression is dependent on heightened mechanical adaptation, both for the cells' ability to change shape and to interact with varying mechanical environments. This type of adaptation is dependent on mechanoresponsive proteins that sense and respond to mechanical stress, as well as their regulators. Mechanoresponsive proteins are part of the mechanobiome, which is the larger network that constitutes the cell's mechanical systems that are also highly integrated with many other cellular systems, such as gene expression, metabolism, and signaling. Despite the altered expression patterns of key mechanobiome proteins across many different cancer types, pharmaceutical targeting of these proteins has been overlooked. Here we review the biochemistry of key mechanoresponsive proteins, specifically nonmuscle myosin II, α-actinins, and filamins, as well as the partnering proteins 14-3-3 and CLP36. We also examined a wide range of data sets to assess how gene and protein expression levels of these proteins are altered across many different cancer types. Finally, we determined the potential of targeting these proteins to mitigate invasion or metastasis and suggest that the mechanobiome is a goldmine of opportunity for anti-cancer drug discovery and development.

scholarly journals Screening and Comprehensive Analysis of Cancer-Associated tRNA-Derived Fragments

2022 ◽  
Vol 12 ◽  
Author(s):  
Yiran Zhou ◽  
Qinghua Cui ◽  
Yuan Zhou
Keyword(s):  
Signaling Pathway ◽  
Cancer Progression ◽  
Expression Profiles ◽  
The Cancer Genome Atlas ◽  
Cancer Prognosis ◽  
Composition Analysis ◽  
Multiple Cancer ◽  
Systematic Analysis ◽  
Cancer Subtypes ◽  
Cancer Types

tRNA-derived fragments (tRFs) constitute a novel class of small non-coding RNA cleaved from tRNAs. In recent years, researches have shown the regulatory roles of a few tRFs in cancers, illuminating a new direction for tRF-centric cancer researches. Nonetheless, more specific screening of tRFs related to oncogenesis pathways, cancer progression stages and cancer prognosis is continuously demanded to reveal the landscape of the cancer-associated tRFs. In this work, by combining the clinical information recorded in The Cancer Genome Atlas (TCGA) and the tRF expression profiles curated by MINTbase v2.0, we systematically screened 1,516 cancer-associated tRFs (ca-tRFs) across seven cancer types. The ca-tRF set collectively combined the differentially expressed tRFs between cancer samples and control samples, the tRFs significantly correlated with tumor stage and the tRFs significantly correlated with patient survival. By incorporating our previous tRF-target dataset, we found the ca-tRFs tend to target cancer-associated genes and onco-pathways like ATF6-mediated unfolded protein response, angiogenesis, cell cycle process regulation, focal adhesion, PI3K-Akt signaling pathway, cellular senescence and FoxO signaling pathway across multiple cancer types. And cell composition analysis implies that the expressions of ca-tRFs are more likely to be correlated with T-cell infiltration. We also found the ca-tRF expression pattern is informative to prognosis, suggesting plausible tRF-based cancer subtypes. Together, our systematic analysis demonstrates the potentially extensive involvements of tRFs in cancers, and provides a reasonable list of cancer-associated tRFs for further investigations.

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