Differential Genomic Instability-Associated LncRNAs Predict Differences of Clinical Outcome and Immunity in Left- And Right- Sided Colon Adenocarcinoma

Abstract Background: The left-sided and right-sided colon adenocarcinoma (LCCs and RCCs, respectively) have unique characteristics in various aspects, particularly molecular features and clinical heterogeneity. The purpose of our study was to develop a prognostic risk model based on differential genomic instability-associated (DGIA) Long non-coding RNAs (lncRNAs) of LCCs and RCCs, therefore the prognostic key lncRNAs could be identified.Methods: We adopted two independent gene data-sets, corresponding somatic mutation and clinical information from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Identification of differential DGIA lncRNAs from LCCs and RCCs were conducted with appliance of "Limma" analysis. Then, we screened out key lncRNAs based on univariate and multivariate Cox proportional hazard regression analysis. Meanwhile, DGIA lncRNAs related prognostic model (DRPM) was established. We employed the DRPM in the model group and internal verification group from TCGA for the purpose of risk grouping and accuracy verification of PRSM. We also verified the accuracy of key lncRNAs with GEO data. Finally, the differences of immune infiltration and functional pathways were analyzed within different risk groups. Results: A total of 123 DGIA lncRNAs were screened out by differential expression analysis. We obtained 6 DGIA lncRNAs by the construction of DRPM, including AC004009.1, AP003555.2, BOLA3-AS1, NKILA, LINC00543 and UCA1. After the risk grouping by these DGIA lncRNAs, we found the prognosis of high-risk group (HRG) was significantly worse than that in low-risk group (LRG) (all p＜0.05). In all TCGA samples and model group, the expression of CD8+ T cells in HRG was lower than that in LRG (all p＜0.05). The functional analysis indicated that there was significant up-regulation with regard of pathways related to both genetic instability and immunity in LRG, including cytosolic DNA sensing pathway, response to dsRNA, RIG-Ⅰ like receptor signaling pathway and Toll-like receptor signaling pathway.Conclusion: Through the analysis of the DGIA lncRNAs between LCCs and RCCs, we established a DRPM which could predicate prognosis of LCCs and RCCs, and 6 key DGIA lncRNAs were identified as well. They can not only predict the prognostic risk of patients, but also serve as biomarkers for evaluating the differences of genetic instability and immune infiltration.

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Prognostic Immunity and Therapeutic Sensitivity Analyses Based on Differential Genomic Instability-Associated LncRNAs in Left- and Right-Sided Colon Adenocarcinoma

Frontiers in Molecular Biosciences ◽

10.3389/fmolb.2021.668888 ◽

2021 ◽

Vol 8 ◽

Author(s):

Jun-Nan Guo ◽

Tian-Yi Xia ◽

Shen-Hui Deng ◽

Wei-Nan Xue ◽

Bin-Bin Cui ◽

...

Keyword(s):

Signaling Pathway ◽

Genomic Instability ◽

Genetic Instability ◽

Risk Group ◽

Risk Groups ◽

Receptor Signaling ◽

Model Group ◽

Immune Infiltration ◽

Receptor Signaling Pathway ◽

Risk Grouping

Background: The purpose of our study was to develop a prognostic risk model based on differential genomic instability-associated (DGIA) long non-coding RNAs (lncRNAs) of left-sided and right-sided colon cancers (LCCs and RCCs); therefore, the prognostic key lncRNAs could be identified.Methods: We adopted two independent gene datasets, corresponding somatic mutation and clinical information from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Identification of differential DGIA lncRNAs from LCCs and RCCs was conducted with the appliance of “Limma” analysis. Then, we screened out key lncRNAs based on univariate and multivariate Cox proportional hazard regression analysis. Meanwhile, DGIA lncRNAs related prognostic model (DRPM) was established. We employed the DRPM in the model group and internal verification group from TCGA for the purpose of risk grouping and accuracy verification of DRPM. We also verified the accuracy of key lncRNAs with GEO data. Finally, the differences of immune infiltration, functional pathways, and therapeutic sensitivities were analyzed within different risk groups.Results: A total of 123 DGIA lncRNAs were screened out by differential expression analysis. We obtained six DGIA lncRNAs by the construction of DRPM, including AC004009.1, AP003555.2, BOLA3-AS1, NKILA, LINC00543, and UCA1. After the risk grouping by these DGIA lncRNAs, we found the prognosis of the high-risk group (HRG) was significantly worse than that in the low-risk group (LRG) (all p < 0.05). In all TCGA samples and model group, the expression of CD8+ T cells in HRG was lower than that in LRG (all p < 0.05). The functional analysis indicated that there was significant upregulation with regard to pathways related to both genetic instability and immunity in LRG, including cytosolic DNA sensing pathway, response to double-strand RNA, RIG-Ⅰ like receptor signaling pathway, and Toll-like receptor signaling pathway. Finally, we analyzed the difference and significance of key DGIA lncRNAs and risk groups in multiple therapeutic sensitivities.Conclusion: Through the analysis of the DGIA lncRNAs between LCCs and RCCs, we identified six key DGIA lncRNAs. They can not only predict the prognostic risk of patients but also serve as biomarkers for evaluating the differences of genetic instability, immune infiltration, and therapeutic sensitivity.

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Comprehensive Analysis of the Immune and Prognostic Implication of MMP14 in Lung Cancer

Disease Markers ◽

10.1155/2021/5917506 ◽

2021 ◽

Vol 2021 ◽

pp. 1-21

Author(s):

Chun-long Zheng ◽

Qiang Lu ◽

Nian Zhang ◽

Peng-yu Jing ◽

Ji-peng Zhang ◽

...

Keyword(s):

Lung Cancer ◽

Signaling Pathway ◽

Lung Squamous Cell Carcinoma ◽

Enrichment Analysis ◽

Cell Receptor ◽

Risk Scores ◽

Pathway Enrichment Analysis ◽

Receptor Signaling ◽

Immune Infiltration ◽

Receptor Signaling Pathway

More and more studies have indicated an association between immune infiltration in lung cancer and clinical outcomes. Matrix metalloproteinase 14 (MMP14) has been reported to be dysregulated in many types of tumors and involved in the development and progression of tumors. However, its contribution to cancer immunity was rarely reported. In the study, we found that MMP14 expression was distinctly upregulated in lung cancer specimens compared with nontumor lung specimens. High MMP14 expression predicted a poor prognosis of lung squamous cell carcinoma (LUSC) patients. Increased MMP14 expressions were observed to be positively related to high immune infiltration levels in most of the immune cells. A pathway enrichment analysis of 32 MMP14-associated immunomodulators indicated the involvement of T cell receptor signaling pathway and Toll-like receptor signaling pathway. Based on MMP14-associated immunomodulators, we applied multivariate assays to construct multiple-gene risk prediction signatures. We observed that risk scores were independently associated with overall survival. These data highlighted that MMP14 was involved in tumor immunity, indicating that MMP14 could serve as a novel prognostic biomarker and therapeutic target for lung cancer. Our data suggest that the four genes identified in this study may serve as valuable biomarkers of lung cancer patient outcomes.

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Immune Infiltration Characteristics of Related Receptor Signaling Pathways in Primary Sjögren’s Syndrome

10.21203/rs.3.rs-948466/v1 ◽

2021 ◽

Author(s):

Lingling Wu ◽

Huayun Ling ◽

Hong Wang ◽

Lijuan Qiu ◽

Ying Zhou ◽

...

Keyword(s):

Dendritic Cells ◽

Signaling Pathways ◽

Signaling Pathway ◽

Immune Cells ◽

Primary Sjögren’S Syndrome ◽

Receptor Signaling ◽

Primary Sjogren’S Syndrome ◽

Primary Sjögren's Syndrome ◽

Immune Infiltration ◽

Receptor Signaling Pathway

Abstract Background: Primary Sjögren’s Syndrome (pSS) is a chronic systemic autoimmune disease characterized by a broad spectrum of clinical features. It is considered to be associated with immune cells and genetic. Since the pathogenesis of pSS has not been studied thoroughly enough, it is significant to explore the relevant mechanisms using bioinformatics methods.Methods: We downloaded the GSE84844, GSE66795 and GSE51092 datasets from the GEO database, and then conducted a comprehensive bioinformatics analysis including differentially expressed genes (DEGs), functional enrichment pathways and immune infiltration characteristics. Results：DEGs analysis identified a total of 89 up-regulated genes and 11 down-regulated genes in the dataset. These DEGs were enriched in NOD-like and RIG-I-like receptor signaling pathway, which were significantly associated with the expression of immune cells such as neutrophils and activated dendritic cells, respectively.Conclusion: The NOD-like and RIG-I-like receptor signaling pathway and the pathogenesis of pSS may be closely associated. Neutrophils and dendritic cells also play an important role in pSS, and the expression of these two kinds of cells is closely associated with the signaling pathways of NOD-like and RIG-I-like receptors.

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