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Background: The relapse and distant metastasis in colon adenocarcinoma (COAD) patients with a poor prognosis. Autophagy has gained increasing attention recently. Methods: This study utilized univariate Cox analysis from the TCGA database to obtain 10 prognostic autophagy-related genes (ARGs). GO and KEGG functional annotation analysis suggested that the ARGs were significantly enriched in tumor metabolic processes. We verified the autophagy-related genes screened by TCGA clinical data. Then, we compared the expression of SERPINA1 in primary and metastatic tumor cells in the GEO database, and finally verified the relationship between SERPINA1 protein expression and prognosis with the CPTAC database. Results: The ROC curves showed SERPINA1 had robust prediction capability in judging the prognosis and disease process compared with the other 4 ARGs and risk score in COAD. Clinical relationship analysis further indicated SERPINA1 was related to TMN stage, clinical-stage, OS, RFS, and DMFS in COAD. Besides, survival analysis presented that higher expression of SERPINA1 was significantly associated with the longer OS, RFS, or DMFS. Moreover, SERPINA1 protein was validated to be associated with OS, RFS, and DMFS through our own IHC and CPTAC database. Finally, we exploratoryly combined the SERPINA1 mRNA and SERPINA1 protein as a new index for prognostics. Conclusion: This new combined index showed the highest prognostic value for OS, RFS, and DMFS, and had the potential to become a practical biomarker for prognosis. [ABSTRACT FROM AUTHOR]

Introduction: Colon adenocarcinoma (COAD) is the third most common tumor of the digestive tract. Recent studies reported that lncRNA's abnormal expression might play a vital role in the occurrence and development of COAD. Methods: In the present study, we investigated the expression of ILF3-AS1 in COAD cell lines, human normal colon epithelial cell line, patient tumor tissues and adjacent normal tissues by real-time quantitative PCR (RT-qPCR). Small interfering RNAs (siRNAs) were transfected into COAD cells to inhibit the expression of ILF3-AS1. The effects of ILF3-AS1 on cell proliferation, migration, invasion and apoptosis were measured by CCK-8 assay, transwell migration and invasion assay, and flow cytometry apoptosis assay, respectively. The direct binding of ILF3-AS1 and miR-619-5p/CAMK1D was validated by the luciferase reporter assay. The expression of CAMK1D and epithelial-mesenchymal transformation (EMT)-related proteins was detected by Western Blot analysis. Besides, in vivo experiments were conducted to demonstrate the oncogenic role of ILF3-AS1 in COAD. Results: The results showed that the expression of ILF3-AS1 was significantly higher in COAD tissue than in normal adjacent samples, and this conclusion was confirmed in the available public datasets. After ILF3-AS1 knockdown, the proliferation of COAD cell lines SW480 and HT29 was significantly inhibited. At the same time, the apoptosis was increased, and the invasion and migration abilities were decreased. After further exploring the mechanisms, we found that ILF3-AS1 serves as a competitive endogenous RNA of mir-619-5p. It can bind to mir-619-5p and reduce its expression, thus regulating the target gene CAMK1D. In addition, we found that high expression of ILF3-AS1 was significantly associated with tumor grade, tumor size, and distant metastasis in COAD samples. In vivo experiments confirmed that ILF3-AS1 promotes tumor growth in COAD models. Conclusion: The present study demonstrated that ILF3-AS1 plays an oncogenic role in COAD through regulating the miR-619-5p/CAMK1D axis, and inhibition of ILF3-AS1 may pave the way for COAD treatment. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to systematically analyze multi-omics data to explore new prognosis biomarkers in colon adenocarcinoma (COAD). Materials and Methods: Multi-omics data of COAD and clinical information were obtained from The Cancer Genome Atlas (TCGA). Univariate Cox analysis was used to select genes which significantly related to the overall survival. GISTIC 2.0 software was used to identify significant amplification or deletion. Mutsig 2.0 software was used to identify significant mutation genes. The 9-gene signature was screened by random forest algorithm and Cox regression analysis. GSE17538 dataset was used as an external dataset to verify the predictive ability of 9-gene signature. qPCR was used to detect the expression of 9 genes in clinical specimens. Results: A total of 71 candidate genes are obtained by integrating genomic variation, mutation and prognostic data. Then, 9-gene signature was established, which includes HOXD12, RNF25, CBLN3, DOCK3, DNAJB13, PYGO2, CTNNA1, PTPRK, and NAT1. The 9-gene signature is an independent prognostic risk factor for COAD patients. In addition, the signature shows good predicting performance and clinical practicality in training set, testing set and external verification set. The results of qPCR based on clinical samples showed that the expression of HOXD12, RNF25, CBLN3, DOCK3, DNAJB13, and PYGO2 was increased in colon cancer tissues and the expression of CTNNA1, PTPRK, NAT1 was decreased in colon cancer tissues. Conclusion: In this study, 9-gene signature is constructed as a new prognostic marker to predict the survival of COAD patients. [ABSTRACT FROM AUTHOR]