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Heat maps of WGCNA modules. WGCNA of the sequencing data identified five colorectal cancer liver metastasis related modules (i.e., brown, blue, grey, turquoise and yellow).
Source publication
Approximately 9% of cancer-related deaths are caused by colorectal cancer (CRC). CRC patients are prone to liver metastasis, which is the most important cause for the high CRC mortality rate. Understanding the molecular mechanism of CRC liver metastasis could help us to find novel targets for the effective treatment of this deadly disease. Using we...
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Methods:
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Citations
... However, just a few studies have looked into the relationship between these miRNAs and CRC [64]. In a study by Gao et al., they discovered that expression of hsa-miR-4518 gradually decreased during metastasis and that this miRNA plays an important role in regulating TFG beta-receptor [65]. Based on databases, we discovered that expression of GUCA2B in metastatic cells was significantly higher than primary cells, suggesting that there is an inverse association between down-regulation of hsa-miR-4518 and up-regulation of GUCA2B. ...
Background
Several serious attempts to treat colorectal cancer have been made in recent decades. However, no effective treatment has yet been discovered due to the complexities of its etiology.
Methods
we used Weighted Gene Co-expression Network Analysis (WGCNA) to identify key modules, hub-genes, and mRNA-miRNA regulatory networks associated with CRC. Next, enrichment analysis of modules has been performed using Cluepedia. Next, quantitative real-time PCR (RT-qPCR) was used to validate the expression of selected hub-genes in CRC tissues.
Results
Based on the WGCNA results, the brown module had a significant positive correlation (r = 0.98, p-value=9e-07) with CRC. Using the survival and DEGs analyses, 22 genes were identified as hub-genes. Next, three candidate hub-genes were selected for RT-qPCR validation, and 22 pairs of cancerous and non-cancerous tissues were collected from CRC patients referred to the Gastroenterology and Liver Clinic. The RT-qPCR results revealed that the expression of GUCA2B was significantly reduced in CRC tissues, which is consistent with the results of differential expression analysis. Finally, top miRNAs correlated with GUCA2B were identified, and ROC analyses revealed that GUCA2B has a high diagnostic performance for CRC.
Conclusions
The current study discovered key modules and GUCA2B as a hub-gene associated with CRC, providing references to understand the pathogenesis and be considered a novel candidate to CRC target therapy.
... Recently, with the rise in the anti-miRNAs strategy, to explore more miRNAs involved in crucial tumor-related pathways as prospective targets has become a shared purpose. Although the critical roles of miRNAs have always been manifested for CRC (56), even CRLM (57), no specific miRNA-based strategy has been reported yet, which indicated that the mining miRNAs with potential for approval was an urgent mission. Besides, increasing evidence indicated that immunotherapy has become a powerful clinical strategy for treating cancer (58). ...
A major complication of colorectal cancer (CRC), one of the most common and fatal types of cancers, is secondary liver metastasis. For patients with this fate, there are very few biomarkers available in clinical application, and the disease remains incurable. Recently, increasing studies demonstrated that tumorigenesis and development are closely related to immune escape, indicating that the roles of immune-related indicators might have been neglected in the past in colorectal cancer liver metastases (CRLM). Here, we unveil that elevated miR-425 and miR-576 promote CRLM through inhibiting PTEN-mediated cellular immune function. Specifically, miR-425 and miR-576 were identified for their significant upregulation in CRLM compared with the primary CRC tissues based on GSE81581 (n = 8) and GSE44121 (n = 18) datasets. Besides, we determined that the two microRNAs (miRNAs) coparticipated in restraining P53 and transforming growth factor beta (TGF-β) signaling pathways associated with tumor metastasis, and both shortened the overall survival of the patients with metastatic susceptibility. Notably, in situ hybridization on relatively large samples of paired CRC tissues (n = 157) not only substantiated that the expression of miR-425 and miR-576 was dramatically upregulated in CRLM but also revealed that they were closely related to tumor deterioration, especially liver metastases. Moreover, we further confirmed that the combination of miR-425 and miR-576 was an effective predictive model for liver metastases and poor clinical outcomes. Mechanically, downregulated PTEN (GSE81558, n = 6) was verified to be a shared target of miR-425 and miR-576 acting as metastasis-related oncogenes, on account of the presence of binding sites (+2928–+2934 and +4371–+4378, respectively) and the collaborative suppression of P53/TGF-β signaling in CRLM, which was further confirmed in CRC cells (HCT116 and SW480) based on systematic molecular biology experiments. Importantly, the target PTEN was strongly associated with microsatellite instability, tumor microenvironment, and immune cell infiltration. Thus, we speculate that miR-425 and miR-576 are novel biomarkers for CRLM prevention and immunotherapy and upstream inhibitors of the PTEN-P53/TGF-β function axis.
... Conventional molecular biology methodology identifies DEGs, but it is difficult to correlate biological information provided by gene names with biological functions independently. WGCNA has emerged as an effective method to discover the relationship between networks, genes, phenotypes, and biological sample information, thus avoiding the shortcomings of the traditional methods (Bakhtiarizadeh et al., 2018;Gao et al., 2016;Magani et al., 2018). ...
Background
To identify the hub genes associated with chemoradiotherapy resistance in rectal cancer and explore the potential mechanism.
Methods
Weighted gene co-expression network analysis (WGCNA) was performed to identify the gene modules correlated with the chemoradiotherapy resistance of rectal cancer.
Results
The mRNA expression of 31 rectal cancer patients receiving preoperative chemoradiotherapy was described in our previous study. Through WGCNA, we demonstrated that the chemoradiotherapy resistance modules were enriched for translation, DNA replication, and the androgen receptor signaling pathway. Additionally, we identified and validated UTP6 as a new effective predictor for chemoradiotherapy sensitivity and a prognostic factor for the survival of colorectal cancer patients using our data and the GSE35452 dataset. Low UTP6 expression was correlated with significantly worse disease-free survival (DFS), overall survival (OS), and event- and relapse-free survival both in our data and the R2 Platform. Moreover, we verified the UTP6 expression in 125 locally advanced rectal cancer (LARC) patients samples by immunohistochemical analysis. The results demonstrated that low UTP6 expression was associated with worse DFS and OS by Kaplan-Meier and COX regression model analyses. Gene set enrichment and co-expression analyses showed that the mechanism of the UTP6-mediated chemoradiotherapy resistance may involve the regulation of FOXK2 expression by transcription factor pathways.
Conclusion
Low expression of the UTP6 was found to be associated with chemoradiotherapy resistance and the prognosis of colorectal cancer possibly via regulating FOXK2 expression by transcription factor pathways.
... But the majority of these studies focused on the role of individual ncRNAs in GC chemoresistance, which neglected the complexity and diversity of the gene regulatory network. Thanks to the rapid development of NGS sequencing technologies and bioinformatics, we used this effective method to identify the relationship between networks/genes, pathways and clinical characteristics to avoid the defects of the traditional method [34,35]. In this study, we identi ed 1,936 DElncRNAs, 2,194 DEmRNAs and 174 DEmiRNAs in one paired cisplatin-resistant GC cell lines by the whole-transcriptome RNA-sequencing. ...
Background: The development of chemoresistance is one of the leading causes of chemotherapy failure in gastric cancer (GC). Emerging evidence highlights the multifunctional role of noncoding RNAs (ncRNAs) in GC chemoresistance. However, the comprehensive expression profile and competing endogenous RNAs (ceRNAs) regulatory network between ncRNAs and mRNAs in GC chemoresistance remain unanswered.
Methods: GC cell line MGC-803 was employed to create cisplatin-resistant MGC-803/DDP cells by continuous exposure to increasing doses of cisplatin. The whole-transcriptome sequencing (RNA sequencing) was performed to comprehensively analyze the differentially expressed (DE) lncRNAs, miRNAs and mRNAs in MGC-803/DDP and MGC-803 cells. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted to investigate the biological functions implicated with the DEncRNAs. Then, the cisplatin-resistant-related ceRNA network and potential regulatory axes were constructed by bioinformatic analysis.
Results: We successfully generated cisplatin-resistant GC cell line MGC-803/DDP. Differential expression analysis showed that a total of 1,936 DElncRNAs, 2,194 DEmRNAs and 174 DEmiRNAs were identified. Functional enrichment analysis indicated that those DEncRNAs were mainly involved in neuroactive ligand-receptor interaction, drug metabolism, Hippo signaling pathway, cAMP pathway and P53 pathway. Subsequently, the cisplatin-resistant-related ceRNA network consisting of 71 DElncRNAs, 121 DEmRNAs and 8 DEmiRNAs was constructed with the widely accepted vital chemo-resistant-related genes and signaling pathways. In addition, two constructed regulatory axes (include FAM66C/miR-129-5p/7 mRNAs and SFTA1P/miR-206/FN1 or NRP1) were successfully validated by the Genomic Data Commons (GDC) GC data.
Conclusion: Our study has shown that differentially expressed ncRNAs have complex and intricate interactions in the cisplatin resistance of GC. The novel ceRNA network and the potential regulatory axes may provide the most comprehensive view of GC chemoresistance to date. Our findings uncovered potential biomarkers for prognostic prediction and novel therapeutic targets for reversing cisplatin resistance in GC.
... In this study, we aimed to identify novel targets in primary CRC that can be used for the prediction of hepatic metastasis. Differential gene expression in primary CRC with or without metastasis was studied by comparing gene expression in paired primary CRC and matched liver metastasis samples through bioinformatic analysis of four different Gene Expression Omnibus (GEO) datasets [10][11][12][13], and Collagen Triple Helix Repeat Containing 1 (CTHRC1) was identified as a metastasis-associated gene in primary CRC to facilitate hepatic metastasis. ...
... To identify the potential metastasis-associated genes in primary CRC, we first analyzed three GEO datasets: GSE41568, GSE72718, and GSE14333 [11][12][13]. We compared the gene expression profiles between primary CRC with metastasis and primary CRC without metastasis, and found 20 significantly upregulated and 7 significantly downregulated genes shared between all three GEO datasets ( Supplementary Fig. 1A, B), which may be the critical genes that drive CRC metastasis in the primary site. ...
Metastasis is a major cause of cancer-related deaths. Tumor-intrinsic properties can determine whether tumor metastasis occurs or not. Here, by comparing the gene expression patterns in primary colorectal cancer (CRC) patients with or without metastasis, we found that Collagen Triple Helix Repeat Containing 1 (CTHRC1) in primary CRC served as a metastasis-associated gene. Animal experiments verified that CTHRC1 secreted by CRC cells promoted hepatic metastasis, which was closely correlated with macrophage infiltration. Depletion of macrophages by liposomal clodronate largely abolished the promoting effect of CTHRC1 on CRC liver metastasis. Furthermore, we demonstrated that CTHRC1 modulated macrophage polarization to M2 phenotypes through TGF-β signaling. A mechanistic study revealed that CTHRC1 bound directly to TGF-β receptor II and TGF-β receptor III, stabilized the TGF-β receptor complex, and activated TGF-β signaling. The combination treatment of CTHRC1 monoclonal antibody and anti-PD-1 blocking antibody effectively suppressed CRC hepatic metastasis. Taken together, our data demonstrated that CTHRC1 is an intrinsic marker of CRC metastasis and further revealed that CTHRC1 promoted CRC liver metastasis by reshaping infiltrated macrophages through TGF-β signaling, suggesting that CTHRC1 could be a potential biomarker for the early prediction of and a therapeutic target of CRC hepatic metastasis.
... Currently, WGCNA has emerged as an effective method to discover the relationship between networks/genes, phenotypes, and samples' biological information to avoid the defects of the traditional method (Gao et al., 2016;Bakhtiarizadeh et al., 2018;Magani et al., 2018). It can also be used to bridge gaps between individual genes and the occurrence and progression of diseases (Zhang and Horvath, 2005;Langfelder and Horvath, 2008;Tian et al., 2017). ...
Oxaliplatin, fluorouracil plus leucovorin (FOLFOX) regimen is the first-line chemotherapy of patients with metastatic colorectal cancer (mCRC). However, studies are limited regarding long non-coding RNAs (lncRNAs) associated with FOLFOX chemotherapy response and prognosis. This study aimed to identify lncRNAs associated with FOLFOX chemotherapy response and prognosis in mCRC patients and to construct a predictive model. We analyzed lncRNA expression in 11 mCRC patients treated with FOLFOX chemotherapy before surgery (four sensitive, seven resistant) by Gene Array Chip. The top eight lncRNAs (AC007193.8, CTD-2008N3.1, FLJ36777, RP11-509J21.4, RP3-508I15.20, LOC100130950, RP5-1042K10.13, and LINC00476) for chemotherapy response were identified according to weighted correlation network analysis (WGCNA). A competitive endogenous RNA (ceRNA) network was then constructed. The crucial functions of the eight lncRNAs enriched in chemotherapy resistance were mitogen-activated protein kinase (MAPK) and proteoglycans signaling pathway. Receiver operating characteristic (ROC) analysis demonstrated that the eight lncRNAs were potent predictors for chemotherapy resistance of mCRC patients. To further identify a signature model lncRNA chemotherapy response and prognosis, the validation set consisted of 196 CRC patients from our center was used to validate lncRNAs expression and prognosis by quantitative PCR (qPCR). The expression of the eight lncRNAs expression between CRC cancerous and adjacent non-cancerous tissues was also verified in the validation data set to determine the prognostic value. A generalized linear model was established to predict the probability of chemotherapy resistance and survival. Our findings showed that the eight-lncRNA signature may be a novel biomarker for the prediction of FOLFOX chemotherapy response and prognosis of mCRC patients.
... However, the pathogenic mechanisms of AP and PAITA have not been studied thoroughly. Previous studies have observed that complex genetic network regulation, including coding genes and non-coding genes, is involved in the pathogenesis and development of diseases (35,36). Thus, in the present study, gene chips were used to discover the gene networks and corresponding important network nodes involved in a cell model of PAITA. ...
Acute pancreatitis (AP) is a common digestive disorder with high morbidity and mortality. The present study aimed to investigate the expression of early growth response protein 1 (Egr1), and the effect of competing endogenous (ce)RNA network on trypsinogen activation. Pancreatic acinar intracellular trypsinogen activation (PAITA) is an important event in the early stage of AP; however, the underlying mechanisms remain unclear. The present study used taurolithocholic acid 3‑sulfate (TLC‑S)‑treated AR42J cells (pancreatic cell line) to establish a PAITA model. A gene microarray and bioinformatics analysis was performed to identify the potential key targets in PAITA. The results demonstrated that Egr1, an important transcription factor, was significantly overexpressed in PAITA. In Egr1 small interfering (si)RNA‑transfected cells, Egr1 expression was decreased and trypsinogen activation was significantly decreased compared with negative control siRNA‑transfected cells, indicating that in TLC‑S‑induced PAITA, overexpression of Egr1 enhanced trypsinogen activation. A ceRNA network [mRNA‑microRNA (miRNA/miR)‑long non‑coding (lnc)RNA] generated using the PAITA model revealed that the effects of Egr1 on PAITA may be regulated by multiple ceRNA pairs, and the lncRNAs (including NONRATT022624 and NONRATT031002) and miRNAs [including Rattus norvegicus (rno)‑miR‑214‑3p and rno‑miR‑764‑5p] included in the ceRNA pairs may serve roles in PAITA by regulating the expression of Egr1. The results of the present study may provide novel targets for researching the underlying mechanisms of, and developing treatments for AP.
... However, the traditional molecular biology methodology identifies differentially expressed genes and it is always difficult to examine the biological information between the genes and biological functions in each sample. WGCNA has emerged as an effective method to discover the relationship between networks/ genes, phenotypes and samples to avoid the defects of the traditional method (Gao et al., 2016;Bakhtiarizadeh et al., 2018;Magani et al., 2018). In this study, we detected the mRNA expression in 11 mCRC patients who were defined as chemotherapy-resistant or -sensitive according to the RESIST criterion using microarray analysis. ...
Background
FOLFOX chemotherapy is one of the most commonly used treatments for colorectal cancer (CRC) patients. However, the efficacy and tolerance of FOLFOX therapy varies between patients. The purpose of this study was to explore hub genes associated with primary chemotherapy-resistance and to explore the possible mechanisms involved from non-European patients.
Method
A weighted gene co-expression network was constructed to identify gene modules associated with chemotherapy resistance in mCRC from China.
Results
A Gene Array Chip was used to detect mRNA expression in 11 mCRC patients receiving preoperative FOLFOX chemotherapy. The immune response was associated with chemotherapy-resistance in microarray data. Through the use of WGCNA, we demonstrated that the crucial functions enriched in chemotherapy-resistance modules were cell proliferation, MAPK signaling pathways, and PI3K signaling pathways. Additionally, we identified and validated FBXW4 as a new effective predictor for chemotherapy sensitivity and a prognostic factor for survival of CRC patients by using our own data and GSE69657. Furthermore, a meta-analysis of 15 Gene Expression Omnibus–sourced datasets showed that FBXW4 messenger RNA levels were significantly lower in CRC tissues than in normal colon tissues. An analysis of the data from the R2: Genomics Analysis and Visualization Platform showed that low FBXW4 expression was correlated with a significantly worse event- and relapse-free survival. Gene set enrichment analysis showed that the mechanism of FBXW4-mediated chemotherapy resistance may involve the DNA replication signal pathway and the cell cycle.
Conclusion
FBXW4 is associated with chemotherapy resistance and prognosis of CRC probably by regulating DNA replication signaling pathways and the cell cycle.
... In recent years, a systems biology approach, namely, WGCNA, has been widely used to identify potential and novel biomarkers in different kinds of tumors, such as adrenocortical cancer, clear cell renal cell cancer, oral squamous cell cancer and CRC [33-35, 13, 12]. By performing WGCNA, Gao et al. reported distinct gene modules existing only in CRC liver metastatic tissues, which were not found in non-metastatic CRC samples [36]. In addition, Liu et al. identified a novel prognostic maker, CENPA, which was associated with favorable survival outcome in CRC [14]. ...
Colorectal cancer (CRC) is one of the most common carcinomas and the fourth leading cause of cancer-related death worldwide. One of the obstacles in the successful treatment of CRC is a high rate of recurrence. We aimed to construct weighted gene co-expression network analysis (WGCNA) to identify key modules and hub genes in association with recurrence in CRC patients. We firstly used the microarray data, GSE41258, to construct a co-expression network and identify gene modules. Furthermore, protein and protein interaction (PPI) network was also performed to screen hub genes. To validate the hub genes, an independent dataset GSE17536 was used for survival analyses. Additionally, another two databases were also performed to investigate the survival rates and expression levels of hub genes. Gene set enrichment analyses (GSEA) combined with gene ontology (GO) were performed to further explore function and mechanisms. In our study, the midnightblue module was identified to be significant, 15 hub genes were screened, four of which were identified as hub nodes in the PPI network. In the test dataset, we found higher expression of MYL9 and CNN1 were significantly associated with shorter survival time of CRC patients. GO analyses showed that MYL9 and CNN1 were enriched in "muscle system process" and "cytoskeletal protein binding". GSEA found the two hub genes were enriched in "pathways in cancer" and "calcium signaling pathway". In conclusion, our study demonstrated that MYL9 and CNN1 were hub genes associated with the recurrence of CRC, which may contribute to the improvement of recurrence-free survival time of CRC patients.
... 10(a) through (d), where we observe similar means between early and late-stage cohorts, but distinctly heavier right-tails (subpopulations with higher expression) in the early-stage cohort for GDF10 and in the late-stage cohort for CALCB. In the literature, both GDF10 [71], [72] and CALCB [73], [74] have been suggested to be affected in colon cancer. Table 5 lists OBFM-JP means and standard deviations for each selection algorithm. ...
We present a novel Bayesian validation paradigm with several validation metrics tailored to biomarker discovery, including moments (the mean and variance) of the number of false discoveries, the number of missed discoveries, and the false discovery rate. All of these validation metrics can be used with a variety of Bayesian variable selection methods already available in the literature. When used in conjunction with Bayesian models with independent Gaussian features, we call these validation metrics optimal Bayesian feature filtering moments (OBFMs). We find closed-form expressions for OBFMs and show that they are asymptotically Gaussian and consistent even when the modeling assumptions are violated. In both synthetic simulations and real data analysis, OBFMs perform very well in biomarker discovery relative to other methods from the literature.
