Dataset Information

Comprehensive Analysis of Therapy-Related Messenger RNAs and Long Noncoding RNAs as Novel Biomarkers for Advanced Colorectal Cancer.

ABSTRACT: Colorectal cancer (CRC) is one of the most common types of human cancers. However, the mechanisms underlying CRC progression remained elusive. This study identified differently expressed messenger RNAs (mRNAs), long noncoding RNAs (lncRNAs), and small nucleolar RNAs (snoRNAs) between pre-therapeutic biopsies and post-therapeutic resections of locally advanced CRC by analyzing a public dataset, GSE94104. We identified 427 dysregulated mRNAs, 4 dysregulated lncRNAs, and 19 dysregulated snoRNAs between pre- and post-therapeutic locally advanced CRC samples. By constructing a protein-protein interaction network and co-expressing networks, we identified 10 key mRNAs, 4 key lncRNAs, and 7 key snoRNAs. Bioinformatics analysis showed therapy-related mRNAs were associated with nucleosome assembly, chromatin silencing at recombinant DNA, negative regulation of gene expression, and DNA replication. Therapy-related lncRNAs were associated with cell adhesion, extracellular matrix organization, angiogenesis, and sister chromatid cohesion. In addition, therapy-related snoRNAs were associated with DNA replication, nucleosome assembly, and telomere organization. We thought this study provided useful information for identifying novel biomarkers for CRC.

SUBMITTER: Li J

PROVIDER: S-EPMC6900565 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Comprehensive Analysis of Therapy-Related Messenger RNAs and Long Noncoding RNAs as Novel Biomarkers for Advanced Colorectal Cancer.

Li Jibin J Ma Siping S Lin Tao T Li Yanxi Y Yang Shihua S Zhang Wanchuan W Zhang Rui R Wang Yongpeng Y

Frontiers in genetics 20191120

Colorectal cancer (CRC) is one of the most common types of human cancers. However, the mechanisms underlying CRC progression remained elusive. This study identified differently expressed messenger RNAs (mRNAs), long noncoding RNAs (lncRNAs), and small nucleolar RNAs (snoRNAs) between pre-therapeutic biopsies and post-therapeutic resections of locally advanced CRC by analyzing a public dataset, GSE94104. We identified 427 dysregulated mRNAs, 4 dysregulated lncRNAs, and 19 dysregulated snoRNAs bet ...[more]

PMID: 31850052

Similar Datasets

Project description:Ovarian cancer (OC) is a highly malignant gynecologic tumor with few treatments available and poor prognosis with the currently available diagnostic markers and interventions. More effective methods for diagnosis and treatment are urgently needed. Although the current evidence implicates ferroptosis in the development and therapeutic responses of various types of tumors, it is unclear to what extent ferroptosis affects OC. To explore the potential of ferroptosis-related genes as biomarkers and molecular targets for OC diagnosis and intervention, this study collected several datasets from The Cancer Genome Atlas-OC (TCGA-OC), analyzed and identified the coexpression profiles of 60 ferroptosis-related genes and two subtypes of OC with respect to ferroptosis and further examined and analyzed the differentially expressed genes between the two subtypes. The results indicated that the expression levels of ferroptosis genes were significantly correlated with prognosis in patients with OC. Single-factor Cox and LASSO analysis identified eight lncRNAs from the screened ferroptosis-related genes, including lncRNAs RP11-443B7.3, RP5-1028K7.2, TRAM2-AS1, AC073283.4, RP11-486G15.2, RP11-95H3.1, RP11-958F21.1, and AC006129.1. A risk scoring model was constructed from the ferroptosis-related lncRNAs and showed good performance in the evaluation of OC patient prognosis. The high- and low-risk groups based on tumor scores presented obvious differences in clinical characteristics, tumor mutation burden, and tumor immune cell infiltration, indicating that the risk score has a good ability to predict the benefit of immunotherapy and may provide data to support the implementation of precise immunotherapy for OC. Although in vivo tests and research are needed in the future, our bioinformatics analysis powerfully supported the effectiveness of the risk signature of ferroptosis-related lncRNAs for prognosis prediction in OC. The findings suggest that these eight identified lncRNAs have great potential for development as diagnostic markers and intervention targets for OC and that patients with high ferroptosis-related lncRNA expression will receive greater benefits from conventional chemotherapy or treatment with ferroptosis inducers.

Project description:BackgroundPsoriasis is a chronic immune-mediated inflammatory dermatosis. Long noncoding RNAs (lncRNAs) play an important role in immune-related diseases. This study aimed to identify potential immune-related lncRNA biomarkers for psoriasis.MethodsWe screened differentially expressed immune-related lncRNAs biomarkers using GSE13355 (skin biopsy samples of 180 cases) from Gene Expression Omnibus (GEO). Moreover, Gene Ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, and Gene Set Enrichment Analysis (GSEA) were performed to explore biological mechanisms in psoriasis. In addition, we performed LASSO logistic regression to identify potential diagnostic lncRNAs and further verify the diagnostic value and relationship with drug response using two validation sets: GSE30999 (skin biopsy samples of 170 cases) and GSE106992 (skin biopsy samples of 192 cases). Furthermore, we estimated the degree of infiltrated immune cells and investigated the correlation between infiltrated immune cells and diagnostic lncRNA biomarkers.ResultsA total of 394 differentially expressed genes (DEGs) were extracted from gene expression profile. GO and KEGG analysis of target genes found that immune-related lncRNAs were primarily associated with epidermis development, skin development, collagen-containing extracellular matrix, and glycosaminoglycan binding and mainly enriched in cytokine-cytokine receptor interaction and influenza A and chemokine signaling pathway. We found that LINC01137, LINC01215, MAPKAPK5-AS1, TPT1-AS1, CARMN, CCDC18-AS1, EPB41L4A-AS, and LINC01214 exhibited well diagnostic efficacy. The ROC and ROC CI were 0.944 (0.907-0.982), 0.953 (0.919-0.987), 0.822 (0.758-0.887), 0.854 (0.797-0.911), 0.957(0.929-0.985), 0.894 (0.846-0.942), and 0.964 (0.937-0.991) for LINC01137, LINC01215, MAPKAPK5-AS1, TPT1-AS1,CARMN, CCDC18-AS1, EPB41L4A-AS1, and LINC01214. LINC01137, LINC01215, and LINC01214 were correlated with drug response. LINC01137, CCDC18-AS1, and CARMN were positively correlated with activated memory CD4 T cell, activated myeloid dendritic cell (DC), neutrophils, macrophage M1, and T follicular helper (Tfh) cells, while negatively correlated with T regulatory cell (Treg). LINC01215, MAPKAPK5-AS1, TPT1-AS1, EPB41L4A-AS, and LINC01214 were negatively correlated with activated memory CD4 T cell, activated myeloid DC, neutrophils, macrophage M1, and Tfh, while positively correlated with Treg.ConclusionsThese findings indicated that these immune-related lncRNAs may be used as potential diagnostic and predictive biomarkers for psoriasis.

Dataset Information

Comprehensive Analysis of Therapy-Related Messenger RNAs and Long Noncoding RNAs as Novel Biomarkers for Advanced Colorectal Cancer.

Publications

Comprehensive Analysis of Therapy-Related Messenger RNAs and Long Noncoding RNAs as Novel Biomarkers for Advanced Colorectal Cancer.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets