Network analysis identifies DAPK3 as a potential biomarker for lymphatic invasion and colon adenocarcinoma prognosis.
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ABSTRACT:
SUBMITTER: Chen HM
PROVIDER: S-EPMC8326195 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Background:Increasing studies have suggested that aberrant expression of microRNAs might play essential roles in the progression of cancers. In this study, we sought to construct a high-specific and superior microRNAs signature to improve the survival prediction of colon adenocarcinoma (COAD) patients. Methods:The genome-wide miRNAs, mRNA and lncRNA expression profiles and corresponding clinical information of COAD were collected from the TCGA database. Differential expression analysis, Kaplan-Meier curve and time-dependent ROC curve were calculated and performed using R software and GraphPad Prism7. Univariate and multivariate Cox analysis was performed to evaluate the prognostic ability of signature. Functional enrichment analysis was analyzed using STRING database. Results:We identified ten prognosis-related microRNAs, including seven risky factors (hsa-miR-197, hsa-miR-32, hsa-miR-887, hsa-miR-3199-2, hsa-miR-4999, hsa-miR-561, hsa-miR-210) and three protective factors (hsa-miR-3917, hsa-miR-3189, hsa-miR-6854). The Kaplan-Meier survival analysis showed that the patients with high risk score had shorter overall survival (OS) in test series. And the similar results were observed in both validation and entire series. The time-dependent ROC curve suggested this signature have high accuracy of OS for COAD. The Multivariate Cox regression analysis and stratification analysis suggested that the ten-microRNA signature was an independent factor after being adjusted with other clinical characteristics. In addition, we also found microRNA signature have higher AUC than other signature. Furthermore, we identified some miRNA-target genes that affect lymphatic metastasis and invasion of COAD patients. Conclusion:In this study, we established a ten-microRNA signature as a potentially reliable and independent biomarker for survival prediction of COAD patients.
| S-EPMC6937800 | biostudies-literature
Project description:Increasing evidence indicates that Parkinson's disease (PD) and type 2 diabetes (T2DM) share dysregulated molecular networks. We identified 84 genes shared between PD and T2DM from curated disease-gene databases. Nitric oxide biosynthesis, lipid and carbohydrate metabolism, insulin secretion and inflammation were identified as common dysregulated pathways. A network prioritization approach was implemented to rank genes according to their distance to seed genes and their involvement in common biological pathways. Quantitative polymerase chain reaction assays revealed that a highly ranked gene, superoxide dismutase 2 (SOD2), is upregulated in PD patients compared to healthy controls in 192 whole blood samples from two independent clinical trials, the Harvard Biomarker Study (HBS) and the Diagnostic and Prognostic Biomarkers in Parkinson's disease (PROBE). The results from this study reinforce the idea that shared molecular networks between PD and T2DM provides an additional source of biologically meaningful biomarkers. Evaluation of this biomarker in de novo PD patients and in a larger prospective longitudinal study is warranted.
| S-EPMC4184821 | biostudies-other
Project description:The overall survival of metastatic colon adenocarcinoma (COAD) remains poor, so it is important to explore the mechanisms of metastasis and invasion. This study aimed to identify invasion-related genetic markers for prognosis prediction in patients with COAD. Three molecular subtypes (C1, C2, and C3) were obtained based on 97 metastasis-related genes in 365 COAD samples from The Cancer Genome Atlas (TCGA). A total of 983 differentially expressed genes (DEGs) were identified among the different subtypes by using the limma package. A 6-gene signature (ITLN1, HOXD9, TSPAN11, GPRC5B, TIMP1, and CXCL13) was constructed via Lasso-Cox analysis. The signature showed strong robustness and could be used in the training, testing, and external validation (GSE17537) cohorts with stable predictive efficiency. Compared with other published signatures, our model showed better performance in predicting outcomes. Pan-cancer expression analysis results showed that ITLN1, TSPAN11, CXCL13, and GPRC5B were downregulated and TIMP1 was upregulated in most tumor samples, including COAD, which was consistent with the results of the TCGA and GEO cohorts. Western blot analysis and immunohistochemistry were performed to validate protein expression. Tumor immune infiltration analysis results showed that TSPAN11, GPRC5B, TIMP1, and CXCL13 protein levels were significantly positively correlated with CD4+ T cells, macrophages, neutrophils, and dendritic cells. Further, the TIMP1 and CXCL13 proteins were significantly related to the tumor immune infiltration of CD8+ T cells. We recommend using our signature as a molecular prognostic classifier to assess the prognostic risk of patients with COAD.
| S-EPMC7881672 | biostudies-literature
Project description:BackgroundLong non-coding RNAs (lncRNAs), acting as competing endogenous RNA (ceRNA) have been reported to regulate the expression of targeted genes by sponging miRNA in colon adenocarcinoma (COAD).MethodsHowever, their potential implications for recurrence free survival prognosis and functional roles remains largely unclear in COAD. In this study, we downloaded the TCGA dataset (training dataset) and GSE39582 (validation dataset) of COAD patients with prognostic information.ResultsA total of 411 differentially expressed genes (DElncRNAs: 12 downregulated and 43 upregulated), 18 DE miRNAs (9 downregulated and 9 upregulated) and 338 DEmRNAs (113 downregulated and 225 upregulated) were identified in recurrence samples compared with non-recurrence samples with the thresholds of FDR < 0.05 and |log2FC|> 0.263. Based on six signature lncRNAs (LINC00899, LINC01503, PRKAG2-AS1, RAD21-AS1, SRRM2-AS1 and USP30-AS1), the risk score (RS) system was constructed. Two prognostic clinical features, including pathologic stage and RS model status were screened for building the nomogram survival model. Moreover, a recurrent-specific ceRNA network was successfully constructed with 2 signature lncRNAs, 4 miRNAs and 113 mRNAs. Furthermore, we further manifested that SRRM2-AS1 predicted a poor prognosis in COAD patients. Furthermore, knockdown of SRRM2-AS1 significantly suppressed cell proliferation, migration, invasion and EMT markers in HT-29 and SW1116 cells.ConclusionThese identified novel lncRNA signature and ceRNA network associated with recurrence prognosis might provide promising therapeutic targets for COAD patients.
| S-EPMC8259330 | biostudies-literature
Project description:BackgroundHistone deacetylase 6 (HDAC6) regulates cytoplasmic signaling networks through the deacetylation of various cytoplasmic substrates. Recent studies have identified the role of HDAC6 in tumor development and immune metabolism, but its specific function remains unclear.MethodsThe current study determined the role of HDAC6 in tumor metabolism and tumor immunity through a multi-database pan-cancer analysis. The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), and Cancer Cell Line Encyclopedia (CCLE) datasets were used to determine the expression levels, prognosis, tumor progression, immune checkpoints, and immune metabolism of HDAC6 in 33 tumors. Pathways, immune checkpoints, immune neoantigens, immune microenvironment, tumor mutational burden (TMB), microsatellite instability (MSI), DNA mismatch repair (MMR), and the value of methyltransferases. The R package was used for quantitative analysis and panoramic description.ResultsIn the present study, we determined that HDAC6 is differentially expressed in pan carcinomas, and by survival, we found that HDAC6 was generally associated with the prognosis of pancreatic adenocarcinoma, Thymoma, and uveal melanoma, where low expression of HDAC6 had a significantly worse prognosis. Secondly, through this experiment, we confirmed that HDAC6 expression level was associated with tumor immune infiltration and tumor microenvironment, especially in PAAD. Finally, HDAC6 was associated with immune neoantigen and immune checkpoint gene expression profiles in all cancers in addition to TMB and MSI in pan-cancers.ConclusionHDAC6 is differentially expressed in pan-cancers and plays an essential role in tumor metabolism and immunity. HDAC6 holds promise as a tumor potential prognostic marker, especially in colon cancer.
| S-EPMC8416150 | biostudies-literature
Project description:BackgroundAs one of the most common cancers with high mortality in the world, we are still facing a huge challenge in the prevention and treatment of colon cancer. With the rapid development of high throughput technologies, new biomarkers identification for colon cancer has been confronted with the new opportunities and challenges.MethodsWe firstly constructed functional networks for each sample of colon adenocarcinoma (COAD) by using a sample-specific network (SSN) method which can construct individual-specific networks based on gene expression profiles of a single sample. The functional genes and interactions were identified from the functional networks, respectively.ResultsClassification and subtyping were used to test the function of the functional genes and interactions. The results of classification showed that the functional genes could be used as diagnostic biomarkers. The subtypes displayed different mechanisms, which were shown by the functional and pathway enrichment analysis for the representative genes of each subtype. Besides, subtype-specific molecular patterns were also detected, such as subtype-specific clinical and mutation features. Finally, 12 functional genes and 13 functional edges could serve as prognosis biomarkers since they were associated with the survival rate of COAD.ConclusionsIn conclusion, the functional genes and interactions in the constructed functional network could be used as new biomarkers for COAD.
| S-EPMC7367377 | biostudies-literature
Project description:Wnt2 mRNA is widely expressed in various tumor tissues. Wnt2 overexpression promotes tumor growth, migration, invasion, and metastasis. However, its underlying molecular action mechanisms and clinical implications in colon adenocarcinoma (COAD) remain unclear. mRNA expression data, obtained from tissue samples, and pathophysiological data of 368 COAD patients were obtained from the Cancer Genome Atlas (TCGA) database. Further, Pearson's correlation analysis was performed to explore the correlation between the expression levels of Wnt2 and other genes in the human genome. Subsequently, a protein-protein interaction (PPI) network was constructed for hub gene identification. Overall survival and significance were determined by Kaplan-Meier analysis, and the log-rank test was used to further identify genes with prognostic significance in COAD from GEO datasets (GSE17538 and GSE39582). Subsequently, 158 tissue samples from Affiliated Hospital of Jiangnan University were used for expression verification. Gene set enrichment analysis (GSEA) was performed on high and low Wnt2 expression datasets to identify potential signaling pathways activated in COAD. In all, 10 hub genes associated with Wnt2 were screened by Pearson's correlation analysis and PPI network, with Wnt2 and COL8A1 having significantly poor prognosis by Kaplan-Meier analysis and log-rank test. Furthermore, high expressions of COL8A1 and Wnt2 were associated with poor survival both in TCGA and GEO cohorts. We further found a correlation between the expressions of Wnt2 and COL8A1 in COAD as per immunohistochemical analysis. To further elucidate the underlying molecular mechanisms of Wnt2 in COAD, we searched for pathways enriched in Wnt2 overexpressing datasets by GSEA. Our findings revealed that high Wnt2 levels were significantly associated with extracellular matrix receptor and focal adhesion pathways. Wnt2 expression correlated with COL8A1 expression in COAD; patients with high Wnt2 and COL8A1 expressions had worse survival outcomes. Pathways identified in this study prompt the molecular role of Wnt2 in COAD and provide directions to further elucidate the involved molecular mechanisms in COAD.
| S-EPMC7484937 | biostudies-literature
Project description:The aim of this study was to examine whether lymphatic invasion in papillary thyroid carcinoma (PTC) occurs when tumour-associated macrophages (TAMs) injure lymphatic vessels together with cancer cells. While there was no difference in the lymphatic vessel density in PTC and follicular thyroid carcinoma (FTC), the number of TAMs around the lymphatic vessels was increased in PTC compared to that in FTC. In particular, TAMs were observed together with cancer cells in lymphatic invasive lesions, and the number of M2 cells inside and outside the lymphatic vessels showed a significant correlation. MMP-2 mRNA was expressed in nonneoplastic stromal cells as well as cancer cells, and double immunofluorescence staining confirmed M2 positivity. Consequently, this study reveals that M2 TAMs around lymphatic vessels within the tumour border of PTC may be associated with the lymphatic invasion of cancer cells. This study represents a step forward in elucidating the mechanism of lymphatic invasion.
| S-EPMC7806843 | biostudies-literature
Project description:Background The survival prognosis is the hallmark of cancer progression. Here, we aimed to develop a recurrence-related gene signature to predict the prognosis of colon adenocarcinoma (COAD). Methods The proteomic data from the Clinical Proteomic Tumor Analysis Consortium (CPTAC) and genomic data from the cancer genomic maps [The Cancer Genome Atlas (TCGA)] dataset were analyzed to identify co-differentially expressed genes (cDEGs) between recurrence samples and non-recurrence samples in COAD using limma package. Functional enrichment analysis, including Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway was conducted. Univariate and multivariate Cox regressions were applied to identify the independent prognostic feature cDEGs and establish the signature whose performance was evaluated by Kaplan–Meier curve, receiver operating characteristic (ROC), Harrell’s concordance index (C-index), and calibration curve. The area under the receiver operating characteristic (ROC) curve (AUROC) and a nomogram were calculated to assess the predictive accuracy. GSE17538 and GSE39582 were used for external validation. Quantitative real-time PCR and Western blot analysis were carried out to validate our findings. Results We identified 86 cDEGs in recurrence samples compared with non-recurrence samples. These genes were primarily enriched in the regulation of carbon metabolic process, fructose and mannose metabolism, and extracellular exosome. Then, an eight-gene-based signature (CA12, HBB, NCF1, KBTBD11, MMAA, DMBT1, AHNAK2, and FBLN2) was developed to separate patients into high- and low-risk groups. Patients in the low-risk group had significantly better prognosis than those in the high-risk group. Four prognostic clinical features, including pathological M, N, T, and RS model status, were screened for building the nomogram survival model. The PCR and Western blot analysis results suggested that CA12 and AHNAK2 were significantly upregulated, while MMAA and DMBT1 were downregulated in the tumor sample compared with adjacent tissues, and in non-recurrent samples compared with non-recurrent samples in COAD. Conclusion These identified recurrence-related gene signatures might provide an effective prognostic predictor and promising therapeutic targets for COAD patients.
| S-EPMC9281446 | biostudies-literature
Project description:BackgroundColon adenocarcinoma (COAD) is the most common colon cancer exhibiting high mortality. Due to their association with cancer progression, long noncoding RNAs (lncRNAs) are now being used as prognostic biomarkers. In the present study, we used relevant clinical information and expression profiles of lncRNAs originating from The Cancer Genome Atlas database, aiming to construct a prognostic lncRNA signature to estimate the prognosis of patients.MethodsThe samples were randomly spilt into training and validation cohorts. In the training cohort, prognosis-related lncRNAs were selected from differentially expressed lncRNAs using the univariate Cox analysis. Furthermore, the least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox analysis were employed for identifying prognostic lncRNAs. The prognostic signature was constructed by these lncRNAs.ResultsThe prognostic model was able to calculate each COAD patient's risk score and split the patients into groups of low and high risks. Compared to the low-risk group, the high-risk group had significant poor prognosis. Next, the prognostic signature was validated in the validation, as well as all cohorts. The receiver operating characteristic (ROC) curve and c-index were determined in all cohorts. Moreover, these prognostic lncRNA signatures were combined with clinicopathological risk factors to construct a nomogram for predicting the prognosis of COAD in the clinic. Finally, seven lncRNAs (CTC-273B12.10, AC009404.2, AC073283.7, RP11-167H9.4, AC007879.7, RP4-816N1.7, and RP11-400N13.2) were identified and validated by different cohorts. The Kyoto Encyclopedia of Genes and Genomes analysis of the mRNAs co-expressed with the seven prognostic lncRNAs suggested four significantly upregulated pathways, which were AGE-RAGE, focal adhesion, ECM-receptor interaction, and PI3K/Akt signaling pathways.ConclusionThus, our study verified that the seven lncRNAs mentioned can be used as biomarkers to predict the prognosis of COAD patients and design personalized treatments.
| S-EPMC7153553 | biostudies-literature