Identification of a Methylation-Driven Gene Panel for Survival Prediction in Colon Cancer

2020 ◽  
Author(s):  
Yaojun Peng ◽  
Jing Zhao ◽  
Fan Yin ◽  
Gaowa Sharen ◽  
Qiyan Wu ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Colon Cancer ◽  
Cancer Patients ◽  
Cell Lines ◽  
Cox Regression ◽  
Gene Panel ◽  
Tnm Stage ◽  
Training Dataset ◽  
Survival Prediction ◽  
Analysis Tool

Abstract Background: Prediction and improvement of prognosis is important for effective clinical management of colon cancer patients. Accumulation of a variety of genetic as well as epigenetic changes in colon epithelial cells has been identified as one of the fundamental processes that drive the initiation and progression of colon cancer. This study aimed to explore functional genes regulated by DNA methylation and the potential of these DNA methylation changes to become biomarkers predictive of colon cancer prognosis.Methods: Methylation-driven genes (MDGs) were explored by applying an integrative analysis tool (MethylMix) to The Cancer Genome Atlas (TCGA) colon cancer project. TCGA colon cancer patients with available survival information (n=281) were randomly divided into training dataset (50%) for model construction and testing dataset (50%) for model validation. The prognostic MDG panel was identified in the training dataset by combining the Cox regression model with the least absolute shrinkage and selection operator regularization, a widely used approach to penalize the effect of multicollineatity. GSEA was employed to determine functional pathways associated with the prognostic 6-MDG panel. CD40 expression and methylation in colon cancer samples were also examined in datasets (expression profile [GSE8671] and methylation profile [GSE42752]) from Gene Expression Omnibus. Experimental confirmation of DNA methylation in colon cancer cell lines was performed using methylation specific PCR and bisulfite sequencing.Results: We identified and internal validated a prognostic methylation-driven gene panel consisting of six gene members (TMEM88, HOXB2, FGD1, TOGARAM1, ARHGDIB and CD40). High risk phenotype classified by the 6-MDGs panel was associated with cancer-related biological processes, including invasion and metastasis, angiogenesis and tumor immune microenvironment, among others. The prognostic value of the 6-MDGs panel was independent of TNM stage, and its combination with TNM stage and age could help improve survival prediction of colon cancer patients. Additionally, we validated that the expression of CD40 was regulated by promoter region methylation in colon cancer samples and cell lines. Conclusions: The proposed 6-MDGs panel represents a promising signature for estimating overall survival in patients with colon cancer.

scholarly journals Development and validation of epigenetic signature predict survival for patients with laryngeal squamous cell carcinoma

2020 ◽  
Author(s):  
Jie Cui ◽  
Liping Wang ◽  
Waisheng Zhong ◽  
Zhen Chen ◽  
Jie Chen ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Squamous Cell Carcinoma ◽  
Small Molecules ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Laryngeal Squamous Cell Carcinoma ◽  
Cox Regression ◽  
Tnm Stage ◽  
Survival Prediction

Abstract Background: Epigenetic alterations, such as DNA methylation patterns, yield an important role in the initiation, progression and prognosis of laryngeal squamous cell carcinoma (LSCC). We performed a genome-wide integrated analysis of methylation and the transcriptome to establish epigenetic signature to improve the accuracy of survival prediction and optimize therapeutic strategies for LSCC.Methods: LSCC DNA methylation datasets and RNA sequencing (RNA-seq) datasets were acquired from the Cancer Genome Atlas (TCGA). MethylMix was applied to detect DNA methylation-driven genes (MDGs). By univariate and multivariate Cox regression analyses, five genes of DNA MDGs was developed an epigenetic signature. The predictive accuracy and clinical value of the epigenetic signature were evaluated by receiver operating characteristic (ROC) and decision curve analysis (DCA), and compared with TNM stage system. Additionally, prognostic value of the epigenetic signature was validated by external Gene Expression Omnibus (GEO) database. According to 5 MDGs of epigenetic signature, the candidate small molecules for LSCC were screen out by the CMap database.Results: A total of 88 DNA MDGs were identified, five of which (MAGEB2, SUSD1, ZNF382, ZNF418 and ZNF732) were chosen to construct an epigenetic signature. The epigenetic signature can effectively divide patients into high-risk and low-risk group, with the area under curve (AUC) of 0.8 (5-year OS) and AUC of 0.745 (3-year OS). Stratification analysis affirmed that the epigenetic signature was still a significant statistical prognostic model in subsets of patients with different clinical variables. Multivariate Cox regression analysis indicated the efficacy of epigenetic signature appears independent of other clinicopathological characteristics. In terms of predictive capacity and clinical usefulness, the epigenetic signature was superior to traditional TNM stage. Additionally, the epigenetic signature was confirmed in external LSCC cohorts from GEO. Finally, CMap matched the 10 most significant small molecules as promising therapeutic drugs to reverse the LSCC gene expression.Conclusion: An epigenetic signature, with five DNA MDGs, was identified and validated in LSCC patients by integrating multidimensional genomic data. Compared TNM stage alone, it generates more accurate estimations of the survival probability and maybe offer novel research directions and prospects for individualized treatment of patients with LSCC.

scholarly journals Pharmaceutical immunoglobulin G impairs anti-carcinoma activity of oxaliplatin in colon cancer cells

2021 ◽  
Author(s):  
Yuru Shang ◽  
Xianbin Zhang ◽  
Lili Lu ◽  
Ke Jiang ◽  
Mathias Krohn ◽  
...  
Keyword(s):  
Colon Cancer ◽  
Cell Viability ◽  
Cancer Patients ◽  
Cell Lines ◽  
Cancer Cell ◽  
Immunoglobulin G ◽  
Cancer Cell Lines ◽  
Human Igg ◽  
Western Blots ◽  
Igg Receptors

Abstract Background Recent evidence proves that intravenous human immunoglobulin G (IgG) can impair cancer cell viability. However, no study evaluated whether IgG application benefits cancer patients receiving chemotherapeutics. Methods Influence of pharmaceutical-grade human IgG on the viability of a series of patient-derived colon cancer cell lines with and without chemotherapeutic intervention was determined. Cell death was analysed flow cytometrically. In addition, the influence of oxaliplatin and IgG on the ERK1/2-signalling pathway was evaluated by western blots. Results We evaluated the effects of pharmaceutical IgG, such as PRIVIGEN® IgG and Tonglu® IgG, in combination with chemotherapeutics. We did not observe any significant effects of IgG on tumour cell viability directly; however, human IgG significantly impaired the anti-tumoral effects of oxaliplatin. Primary cancer cell lines express IgG receptors and accumulate human IgG intracellularly. Moreover, while oxaliplatin induced the activation of ERK1/2, the pharmaceutical IgG inhibited ERK1/2 activity. Conclusions The present study demonstrates that pharmaceutical IgG, such as PRIVIGEN® IgG and Tonglu® IgG, can impair the anti-carcinoma activity of oxaliplatin. These data strongly suggest that therapeutic IgG as co-medication might have harmful side effects in cancer patients. The clinical significance of these preclinical observations absolutely advises further preclinical, as well as epidemiological and clinical research.

scholarly journals Association of chemotherapy with survival in stage II colon cancer patients who received radical surgery: a retrospective cohort study

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Zhihao Lv ◽  
Yuqi Liang ◽  
Huaxi Liu ◽  
Delong Mo
Keyword(s):  
Colon Cancer ◽  
Overall Survival ◽  
Cancer Patients ◽  
Prediction Models ◽  
Radical Surgery ◽  
Survival Rates ◽  
Stage Ii ◽  
Survival Prediction ◽  
Stage Ii Colon Cancer ◽  
Overall Survival Rates

Abstract Background It remains controversial whether patients with Stage II colon cancer would benefit from chemotherapy after radical surgery. This study aims to assess the real effectiveness of chemotherapy in patients with stage II colon cancer undergoing radical surgery and to construct survival prediction models to predict the survival benefits of chemotherapy. Methods Data for stage II colon cancer patients with radical surgery were retrieved from the Surveillance, Epidemiology, and End Results (SEER) database. Propensity score matching (1:1) was performed according to receive or not receive chemotherapy. Competitive risk regression models were used to assess colon cancer cause-specific death (CSD) and non-colon cancer cause-specific death (NCSD). Survival prediction nomograms were constructed to predict overall survival (OS) and colon cancer cause-specific survival (CSS). The predictive abilities of the constructed models were evaluated by the concordance indexes (C-indexes) and calibration curves. Results A total of 25,110 patients were identified, 21.7% received chemotherapy, and 78.3% were without chemotherapy. A total of 10,916 patients were extracted after propensity score matching. The estimated 3-year overall survival rates of chemotherapy were 0.7% higher than non- chemotherapy. The estimated 5-year and 10-year overall survival rates of non-chemotherapy were 1.3 and 2.1% higher than chemotherapy, respectively. Survival prediction models showed good discrimination (the C-indexes between 0.582 and 0.757) and excellent calibration. Conclusions Chemotherapy improves the short-term (43 months) survival benefit of stage II colon cancer patients who received radical surgery. Survival prediction models can be used to predict OS and CSS of patients receiving chemotherapy as well as OS and CSS of patients not receiving chemotherapy and to make individualized treatment recommendations for stage II colon cancer patients who received radical surgery.

scholarly journals Development of prognosis model for colon cancer based on autophagy-related genes

2020 ◽  
Vol 18 (1) ◽  
Author(s):  
Xu Wang ◽  
Yuanmin Xu ◽  
Ting Li ◽  
Bo Chen ◽  
Wenqi Yang
Keyword(s):  
Colon Cancer ◽  
Regression Analysis ◽  
High Risk ◽  
Cancer Patients ◽  
Risk Score ◽  
Cox Regression ◽  
Patient Survival ◽  
Expression Profiles ◽  
Cox Regression Analysis ◽  
Risk Patients

Abstract Background Autophagy is an orderly catabolic process for degrading and removing unnecessary or dysfunctional cellular components such as proteins and organelles. Although autophagy is known to play an important role in various types of cancer, the effects of autophagy-related genes (ARGs) on colon cancer have not been well studied. Methods Expression profiles from ARGs in 457 colon cancer patients were retrieved from the TCGA database (https://portal.gdc.cancer.gov). Differentially expressed ARGs and ARGs related to overall patient survival were identified. Cox proportional-hazard models were used to investigate the association between ARG expression profiles and patient prognosis. Results Twenty ARGs were significantly associated with the overall survival of colon cancer patients. Five of these ARGs had a mutation rate ≥ 3%. Patients were divided into high-risk and low-risk groups based on Cox regression analysis of 8 ARGs. Low-risk patients had a significantly longer survival time than high-risk patients (p < 0.001). Univariate and multivariate Cox regression analysis showed that the resulting risk score, which was associated with infiltration depth and metastasis, could be an independent predictor of patient survival. A nomogram was established to predict 1-, 3-, and 5-year survival of colon cancer patients based on 5 independent prognosis factors, including the risk score. The prognostic nomogram with online webserver was more effective and convenient to provide information for researchers and clinicians. Conclusion The 8 ARGs can be used to predict the prognosis of patients and provide information for their individualized treatment.

scholarly journals Prognostic and Predictive Value of BGN in Colon Cancer Outcomes and Response to Immunotherapy

2022 ◽  
Vol 11 ◽  
Author(s):  
Zi-Xuan He ◽  
Sheng-Bing Zhao ◽  
Xue Fang ◽  
Ji-Fu E ◽  
Hong-Yu Fu ◽  
...  
Keyword(s):  
Colon Cancer ◽  
Immune Response ◽  
Cancer Patients ◽  
Immune Cells ◽  
Matrix Protein ◽  
Cox Regression ◽  
Extracellular Matrix Protein ◽  
Great Promise ◽  
Clinical Prognosis ◽  
Expression Levels

BackgroundColon cancer is one of the most frequent malignancies and causes high mortality worldwide. Exploring the tumor-immune interactions in the tumor microenvironment and identifying new prognostic and therapeutic biomarkers will assist in decoding the novel mechanism of tumor immunotherapy. BGN is a typical extracellular matrix protein that was previously validated as a signaling molecule regulating multiple processes of tumorigenesis. However, its role in tumor immunity requires further investigation.MethodsThe differentially expressed genes in three GEO datasets were analyzed, and BGN was identified as the target gene by intersection analysis of PPIs. The relevance between clinical outcomes and BGN expression levels was evaluated using data from the GEO database, TCGA and tissue microarray of colon cancer samples. Univariable and multivariable Cox regression models were conducted for identifying the risk factors correlated with clinical prognosis of colon cancer patients. Next, the association between BGN expression levels and the infiltration of immune cells as well as the process of the immune response was analyzed. Finally, we predicted the immunotherapeutic response rates in the subgroups of low and high BGN expression by TIS score, ImmuCellAI and TIDE algorithms.ResultsBGN expression demonstrated a statistically significant upregulation in colon cancer tissues than in normal tissues. Elevated BGN was associated with shorter overall survival as well as unfavorable clinicopathological features, including tumor size, serosa invasion and length of hospitalization. Mechanistically, pathway enrichment and functional analysis demonstrated that BGN was positively correlated with immune and stromal scores in the TME and primarily involved in the regulation of immune response. Further investigation revealed that BGN was strongly expressed in the immunosuppressive phenotype and tightly associated with the infiltration of multiple immune cells in colon cancer, especially M2 macrophages and induced Tregs. Finally, we demonstrated that high BGN expression presented a better immunotherapeutic response in colon cancer patients.ConclusionBGN is an encouraging predictor of diagnosis, prognosis and immunotherapeutic response in patients with colon cancer. Assessment of BGN expression represents a novel approach with great promise for identifying patients who may potentially benefit from immunotherapy.

Association of immune-regulatory (FoxP3+)-T-cell tumor infiltration status with benefit from chemoimmunotherapy with gemcitabine, oxaliplatin, 5-FU/FA plus GM-CSF and aldesleukine (GOLFIG) in metastatic colon cancer patients

2009 ◽  
Vol 27 (15_suppl) ◽  
pp. 3045-3045
Author(s):  
P. Correale ◽  
P. Tagliaferri ◽  
M. T. Del Vecchio ◽  
C. Remondo ◽  
C. Migali ◽  
...  
Keyword(s):  
Colon Cancer ◽  
T Cells ◽  
Cancer Patients ◽  
Cox Regression ◽  
Treg Cells ◽  
Phase Iii ◽  
Metastatic Colon Cancer ◽  
Tumor Infiltration ◽  
Gm Csf ◽  
Independent Variable

3045 Background: GOLFIG is a novel chemoimmunotherapy regimen, combining gemcitabine, oxaliplatin, 5-FU/FA with immunoadjuvant GM-CSF and aldesleukine, which resulted safe and very active in colon cancer patients. Antitumor activity and immunity feedback to the treatment resulted strictly correlated. The best outcome was observed in patients showing autoimmunity signs, rise in central-memory-T cells, and decline in peripheral and tumor infiltrating immuno-regulatory T (Treg) cells. On these bases, we investigated a possible correlation between Treg tumor infiltration at diagnosis and clinical outcome of these patients. Methods: An immunohistochemistry study was carried out to quantify the infiltration of Treg (FoxP3+) lymphocytes in tumor samples of 41 colon cancer patients who received FOLFOX-4 chemotherapy or GOLFIG chemo-immunotherapy as enrolled in the ongoing phase III GOLFIG-2 trial. Treg tumor infiltration score (range 0 to 5) was then correlated with survival (OS) and time to progression (TTP). Results: A higher Treg tumor infiltration score (score 3–5) was associated to a longer OS and TTP in the whole patient population (high vs low score; TTP=18 vs 9.4 months; p=0.002; OS=55.7 vs 28.9 months; p=0.001); however, those patients with high tumor infiltration of FoxP3+-T cells who received GOLFIG regimen showed the most favorable outcome (high vs low score; TTP=20.8 vs 11.6 months; p=0.04; OS=68.1 vs 41 months; p=0.04). A Cox regression model demonstrated in these patients that a high Treg tumor infiltration score is an independent variable of long survival and prolonged TTP. Conclusions: Our results suggest that GOLFIG chemoimmunotherapy is highly effective in colon carcinoma patients with high FoxP3+ infiltration score and that Treg-tumor infiltration score may be a favorable prognostic marker in colon cancer patients. No significant financial relationships to disclose.

Prediction and prognostic validation of colorectal cancer therapeutic effect of WM-S1-030 using pre-clinical CTC animal model.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e15557-e15557
Author(s):  
Hae Ung Lee ◽  
Jai-Hee Moon ◽  
Joseph Kim ◽  
Seong Keun Kim ◽  
Jae Sik Shin ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Colon Cancer ◽  
Animal Model ◽  
Cancer Patients ◽  
Cell Lines ◽  
Tumor Size ◽  
Peripheral Blood ◽  
Colon Cancer Cell ◽  
Nsg Mice ◽  
Colon Cancer Cell Lines

e15557 Background: CTC (Circulating tumor cells) has the advantage of being able to effectively investigate non-invasive diagnosis, prediction, and prognosis for non-surgical carcinoma or tissue sample collection. We have developed WM-S1-030 (WMBIO) as a novel inhibitor for mtRTK (mutant receptor tyrosine kinase) identified important targets for cancer progression and metastasis in various cancers, including colorectal cancer, and have tried to prove the possibility of CTC diagnosis, prediction and prognosis of WM-S1-030 using tumor animal models. Methods: Six of colon cancer cell lines expressing mtRTK (pTyr-mtRTK) were transplanted into Balb.c nude mice and NSG mice to collect peripheral blood when the tumor size reached 1000 mm3. CTCs were quantified in peripheral blood using the Smart Biopsy cell isolator (Cytogen). The expression of pTyr-mtRTK in CTCs was analyzed via the Smart Biopsy Image Analyzer (Cytogen). Colon cancer cell lines expressing pTyr-mtRTK were transplanted into NSG mice and we examined the tumor suppression, the enumeration of CTCs and pTyr-mtRTK expression in CTCs after administration of WM-S1-030. We also identified CTCs in peripheral blood of colon cancer patients and analyzed expression of pTyr-mtRTK in CTCs through Smart Biopsy system. Results: As results of the enumeration of CTCs after tumor transplantation into Balb.c nude mice and NSG mice, the number of CTC was 8 ~ 20 times higher peripheral blood in the NSG model, which indicates innate immune responses are critical for the survival of CTCs. Half of CTCs isolated from the blood expressed pTyr-mtRTK. The tumor size, the number of CTCs, and the expression of pTyr-mtRTK in CTCs were examined after the administration of WM-S1-030. The volume of tumor decreased by 67% in the WM-S1-030 group compared to the vehicle. The number of CTCs was reduced by approximately three times after the treatment of WM-S1-030 and also the number of CTCs expressing pTyr-mtRTK was significantly decreased. CTC detection and pTyr-mtRTK expression analysis in the peripheral blood of colon cancer patients detected 9 CTCs per 10 ml of peripheral blood, of which 11 % of CTCs representing pTyr-mtRTK were confirmed. Conclusions: WM-S1-030 was developed and confirmed in the CTC-based animal model, which implies that the analysis of CTCs is the powerful tool for predicting/ prognosing WM-S1-030 in the pre-clinical analysis. Currently, we are conducting clinical diagnostic validation using CTC in the blood of colorectal cancer patients and preparing for clinical trial of WM-S1-030.

scholarly journals Development of a novel prognostic signature for predicting the overall survival of bladder cancer patients

2020 ◽  
Vol 40 (6) ◽  
Author(s):  
Huamei Tang ◽  
Lijuan Kan ◽  
Tong Ou ◽  
Dayang Chen ◽  
Xiaowen Dou ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Overall Survival ◽  
Bladder Cancer ◽  
Cancer Patients ◽  
Cox Regression ◽  
Test Group ◽  
Training Group ◽  
The Cancer Genome Atlas ◽  
Methylation Site ◽  
Cox Regression Analysis

Abstract Background: Bladder cancer is one of the most common malignancies. So far, no effective biomarker for bladder cancer prognosis has been identified. Aberrant DNA methylation is frequently observed in the bladder cancer and holds considerable promise as a biomarker for predicting the overall survival (OS) of patients. Materials and methods: We downloaded the DNA methylation and transcriptome data for bladder cancer from The Cancer Genome Atlas (TCGA), a public database, screened hypo-methylated and up-regulated genes, similarly, hyper-methylation with low expression genes, then retrieved the relevant methylation sites. Cox regression analysis was used to identify a nine-methylation site signature of a training group. Predictive ability was validated in a test group by receiver operating characteristic (ROC) analysis. Results: We identified nine bladder cancer-specific methylation sites as potential prognostic biomarkers and established a risk score system based on the methylation site signature to evaluate the OS. The performance of the signature was accurate, with area under curve was 0.73 in the training group and 0.71 in the test group. Taking clinical features into consideration, we constructed a nomogram consisting of the nine-methylation site signature and patients’ clinical variables, and found that the signature was an independent risk factor. Conclusions: Overall, the significant nine methylation sites could be novel prediction biomarkers, which could aid in treatment and also predict the overall survival likelihoods of bladder cancer patients.

scholarly journals Identification of Distinct Molecular Patterns and a Four-Gene Signature in Colon Cancer Based on Invasion-Related Genes

2021 ◽  
Vol 12 ◽  
Author(s):  
Yunfei Dong ◽  
Tao Shang ◽  
HaiXin Ji ◽  
Xiukou Zhou ◽  
Zhi Chen
Keyword(s):  
Gene Expression ◽  
Colon Cancer ◽  
Cancer Patients ◽  
Risk Group ◽  
Univariate Analysis ◽  
Gene Signature ◽  
The Cancer Genome Atlas ◽  
Training Dataset ◽  
Lasso Regression ◽  
Independent Predictive Factor

BackgroundThe pathological stage of colon cancer cannot accurately predict recurrence, and to date, no gene expression characteristics have been demonstrated to be reliable for prognostic stratification in clinical practice, perhaps because colon cancer is a heterogeneous disease. The purpose was to establish a comprehensive molecular classification and prognostic marker for colon cancer based on invasion-related expression profiling.MethodsFrom the Gene Expression Omnibus (GEO) database, we collected two microarray datasets of colon cancer samples, and another dataset was obtained from The Cancer Genome Atlas (TCGA). Differentially expressed genes (DEGs) further underwent univariate analysis, least absolute shrinkage, selection operator (LASSO) regression analysis, and multivariate Cox survival analysis to screen prognosis-associated feature genes, which were further verified with test datasets.ResultsTwo molecular subtypes (C1 and C2) were identified based on invasion-related genes in the colon cancer samples in TCGA training dataset, and C2 had a good prognosis. Moreover, C1 was more sensitive to immunotherapy. A total of 1,514 invasion-related genes, specifically 124 downregulated genes and 1,390 upregulated genes in C1 and C2, were identified as DEGs. A four-gene prognostic signature was identified and validated, and colon cancer patients were stratified into a high-risk group and a low-risk group. Multivariate regression analyses and a nomogram indicated that the four-gene signature developed in this study was an independent predictive factor and had a relatively good predictive capability when adjusting for other clinical factors.ConclusionThis research provided novel insights into the mechanisms underlying invasion and offered a novel biomarker of a poor prognosis in colon cancer patients.

scholarly journals Effect of Aging-Related Genes on the Prognosis of Colon Cancer

2021 ◽  
Author(s):  
Yushu Liu ◽  
Jiantao Gong ◽  
Yanyi Huang ◽  
Qunguang Jiang
Keyword(s):  
Colon Cancer ◽  
Cancer Patients ◽  
Clinical Characteristics ◽  
Cox Regression ◽  
Validation Cohort ◽  
External Validation ◽  
Predictive Ability ◽  
Lasso Regression ◽  
Internal Validation ◽  
Cox Regression Analysis

Abstract Background:Colon cancer is a common malignant cancer with high incidence and poor prognosis. Cell senescence and apoptosis are important mechanisms of tumor occurrence and development, in which aging-related genes(ARGs) play an important role. This study aimed to establish a prognostic risk model based on ARGs for diagnosis and prognosis prediction of colon cancer .Methods: We downloaded transcriptome data and clinical information of colon cancer patients from the Cancer Genome Atlas(TCGA) database and the microarray dataset(GSE39582) from the Gene Expression Omnibus(GEO) database. Univariate COX, least absolute shrinkage and selection operator(LASSO) regression algorithm and multivariate COX regression analysis were used to construct a 6-ARG prognosis model and calculated the riskScore. The prognostic signatures is validated by internal validation cohort and external validation cohort(GSE39582).In addition, functional enrichment pathways and immune microenvironment of aging-related genes(ARGs) were also analyzed. We also analyzed the correlation between rsikScore and clinical features and constructed a nomogram based on riskScore. We are the first to construct prognostic nomogram based on ARGs.Results: Through univariate COX,LASSO regression algorithm and multivariate COX regression analysis,6 prognostic ARGs (PDPK1,RAD52,GSR,IL7,BDNF and SERPINE1) were screened out and riskScore was constructed. We have verified that riskScore has good prognostic value in both internal validation cohort and external validation cohort. Pathway enrichment and immunoanalysis of ARGs provide a direction for the treatment of colon cancer patients. We also found that riskScore was closely related to the clinical characteristics of patients. Based on riskScore and related clinical features, we constructed a nomogram, which has good predictive performance.Conclusion: The 6-ARG prognostic signature we constructed has a certain clinical predictive ability. Its riskScore is also closely related to clinical characteristics, and nomogram based on this has stronger predictive ability than a single indicator. ARGs and the nomogram we constructed may provide a promising treatment for colon cancer patients.

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