&lt;p&gt;Potential Prognostic and Diagnostic Values of CDC6, CDC45, ORC6 and SNHG7 in Colorectal Cancer&lt;/p&gt;

Hu, Yang; Wang, Liping; Li, Zhixing; Wan, Zhenzhen; Shao, Minghai; Wu, Shaobin; Guo, Wei

doi:10.2147/ott.s231941

Cited by 55 publications

(54 citation statements)

References 47 publications

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“…GO analysis indicated that negative regulation of growth, bicarbonate transport, and transporter activity ( 38 – 40 ) were closely related to the development and growth of cancer; some KEGG pathways, such as nitrogen metabolism and retinol metabolism, were also linked to the pathogenesis of CRC. Nitrogen is an essential biomolecule in humans and regulates cellular metabolism, and retinol is a form of vitamin A closely related to immune functions ( 41 , 42 ). Based on the results of the GO and KEGG enrichment analyses, the DEGs were closely associated with CRC occurrence and development.…”

Section: Discussionmentioning

confidence: 99%

Differential Expression Analysis Revealing CLCA1 to Be a Prognostic and Diagnostic Biomarker for Colorectal Cancer

et al. 2020

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Colorectal cancer (CRC) is a common malignant tumor of the digestive tract and lacks specific diagnostic markers. In this study, we utilized 10 public datasets from the NCBI Gene Expression Omnibus (NCBI-GEO) database to identify a set of significantly differentially expressed genes (DEGs) between tumor and control samples and WGCNA (Weighted Gene Co-Expression Network Analysis) to construct gene co-expression networks incorporating the DEGs from The Cancer Genome Atlas (TCGA) and then identify genes shared between the GEO datasets and key modules. Then, these genes were screened via MCC to identify 20 hub genes. We utilized regression analyses to develop a prognostic model and utilized the random forest method to validate. All hub genes had good diagnostic value for CRC, but only CLCA1 was related to prognosis. Thus, we explored the potential biological value of CLCA1. The results of gene set enrichment analysis (GSEA) and immune infiltration analysis showed that CLCA1 was closely related to tumor metabolism and immune invasion of CRC. These analysis results revealed that CLCA1 may be a candidate diagnostic and prognostic biomarker for CRC.

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Section: Discussionmentioning

confidence: 99%

Differential Expression Analysis Revealing CLCA1 to Be a Prognostic and Diagnostic Biomarker for Colorectal Cancer

et al. 2020

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“…A visualization of the network for KLF5 and its co-regulatory TFs is presented in Fig. 2 e. Some of these targets have been confirmed to be associated with CRC such as MIR17HG [ 58 ] and SNHG7 [ 59 ]. KLF5 may co-operate or form a transcription complex with AR or HSF 1 to promote tumorigenesis in CRC.…”

Section: Resultsmentioning

confidence: 99%

Network analysis of KLF5 targets showing the potential oncogenic role of SNHG12 in colorectal cancer

Liao¹,

Chen²,

Zhang³

et al. 2020

Cancer Cell Int

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Background KLF5 is a member of the Kruppel-like factor, subfamily of zinc finger proteins that are involved in cancers. KLF5 functions as a transcription factor and regulates the diverse protein-coding genes (PCGs) in colorectal cancer (CRC). However, the long non-coding RNAs (lncRNAs) regulated by KLF5 in CRC are currently unknown. Methods In this study, we first designed a computational pipeline to determine the PCG and lncRNA targets of KLF5 in CRC. Then we analyzed the motif pattern of the binding regions for the lncRNA targets. The regulatory co-factors of KLF5 were then searched for through bioinformatics analysis. We also constructed a regulatory network for KLF5 and annotated its functions. Finally, one of the KLF5 lncRNA targets, SNHG12, was selected to further explore its expression pattern and functions in CRC. Results We were able to identify 19 lncRNA targets of KLF5 and found that the motifs of the lncRNA binding sites were GC-enriched. Next, we pinpointed the transcription factors AR and HSF1 as the regulatory co-factors of KLF5 through bioinformatics analysis. Then, through the analysis of the regulatory network, we found that KLF5 may be involved in DNA replication, DNA repair, and the cell cycle. Furthermore, in the cell cycle module, the SNHG12 up-regulating expression pattern was verified in the CRC cell lines and tissues, associating it to CRC invasion and distal metastasis. This indicates that SNHG12 may play a critical part in CRC tumorigenesis and progression. Additionally, expression of SNHG12 was found to be down-regulated in CRC cell lines when KLF5 expression was knocked-down by siRNA; and a strong correlation was observed between the expression levels of SNHG12 and KLF5, further alluding to their regulatory relationship. Conclusions In conclusion, the network analysis of KLF5 targets indicates that SNHG12 may be a significant lncRNA in CRC.

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“…CDC45 is an essential DNA replication factor [ 29 ]. It is required for DNA synthesis during genome duplication, as a component of the Cdc45-MCM-GINS (CMG) helicase [ 30 ] and implicated in diverse human cancers [ 31 , 32 , 33 ] including BC [ 34 ]. ESPL1 is involved in sister chromatids separation during anaphase and its oncogenic activity was found in BC [ 35 , 36 ] and endometrial cancer [ 37 ].…”

Section: Discussionmentioning

confidence: 99%

The New Paradigm of Network Medicine to Analyze Breast Cancer Phenotypes

Grimaldi

Conte

Pane

et al. 2020

IJMS

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Breast cancer (BC) is a heterogeneous and complex disease as witnessed by the existence of different subtypes and clinical characteristics that poses significant challenges in disease management. The complexity of this tumor may rely on the highly interconnected nature of the various biological processes as stated by the new paradigm of Network Medicine. We explored The Cancer Genome Atlas (TCGA)-BRCA data set, by applying the network-based algorithm named SWItch Miner, and mapping the findings on the human interactome to capture the molecular interconnections associated with the disease modules. To characterize BC phenotypes, we constructed protein–protein interaction modules based on “hub genes”, called switch genes, both common and specific to the four tumor subtypes. Transcriptomic profiles of patients were stratified according to both clinical (immunohistochemistry) and genetic (PAM50) classifications. 266 and 372 switch genes were identified from immunohistochemistry and PAM50 classifications, respectively. Moreover, the identified switch genes were functionally characterized to select an interconnected pathway of disease genes. By intersecting the common switch genes of the two classifications, we selected a unique signature of 28 disease genes that were BC subtype-independent and classification subtype-independent. Data were validated both in vitro (10 BC cell lines) and ex vivo (66 BC tissues) experiments. Results showed that four of these hub proteins (AURKA, CDC45, ESPL1, and RAD54L) were over-expressed in all tumor subtypes. Moreover, the inhibition of one of the identified switch genes (AURKA) similarly affected all BC subtypes. In conclusion, using a network-based approach, we identified a common BC disease module which might reflect its pathological signature, suggesting a new vision to face with the disease heterogeneity.

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<p>Potential Prognostic and Diagnostic Values of CDC6, CDC45, ORC6 and SNHG7 in Colorectal Cancer</p>

Cited by 55 publications

References 47 publications

Differential Expression Analysis Revealing CLCA1 to Be a Prognostic and Diagnostic Biomarker for Colorectal Cancer

Differential Expression Analysis Revealing CLCA1 to Be a Prognostic and Diagnostic Biomarker for Colorectal Cancer

Network analysis of KLF5 targets showing the potential oncogenic role of SNHG12 in colorectal cancer

The New Paradigm of Network Medicine to Analyze Breast Cancer Phenotypes

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