Survival stratification for colorectal cancer via multi-omics integration using an autoencoder-based model

2021 ◽  
pp. 153537022110650
Author(s):  
Hu Song ◽  
Chengwei Ruan ◽  
Yixin Xu ◽  
Teng Xu ◽  
Ruizhi Fan ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Dna Methylation ◽  
Target Genes ◽  
Proportional Hazards ◽  
Expression Profiles ◽  
Principal Component ◽  
Good Prognosis ◽  
Cox Proportional Hazards ◽  
The Cancer Genome Atlas ◽  
Prognosis Group

Prognosis stratification in colorectal cancer helps to address cancer heterogeneity and contributes to the improvement of tailored treatments for colorectal cancer patients. In this study, an autoencoder-based model was implemented to predict the prognosis of colorectal cancer via the integration of multi-omics data. DNA methylation, RNA-seq, and miRNA-seq data from The Cancer Genome Atlas (TCGA) database were integrated as input for the autoencoder, and 175 transformed features were produced. The survival-related features were used to cluster the samples using k-means clustering. The autoencoder-based strategy was compared to the principal component analysis (PCA)-, t-distributed random neighbor embedded (t-SNE)-, non-negative matrix factorization (NMF)-, or individual Cox proportional hazards (Cox-PH)-based strategies. Using the 175 transformed features, tumor samples were clustered into two groups (G1 and G2) with significantly different survival rates. The autoencoder-based strategy performed better at identifying survival-related features than the other transformation strategies. Further, the two survival groups were robustly validated using “hold-out” validation and five validation cohorts. Gene expression profiles, miRNA profiles, DNA methylation, and signaling pathway profiles varied from the poor prognosis group (G2) to the good prognosis group (G1). miRNA–mRNA networks were constructed using six differentially expressed miRNAs (let-7c, mir-34c, mir-133b, let-7e, mir-144, and mir-106a) and 19 predicted target genes. The autoencoder-based computational framework could distinguish good prognosis samples from bad prognosis samples and facilitate a better understanding of the molecular biology of colorectal cancer.

scholarly journals SELE gene as a characteristic prognostic biomarker of colorectal cancer

2021 ◽  
Vol 49 (4) ◽  
pp. 030006052110043
Author(s):  
Na Li ◽  
Honghe Xiao ◽  
Jiangli Shen ◽  
Ximin Qiao ◽  
Fenjuan Zhang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Colorectal Cancer ◽  
Proportional Hazards ◽  
Cox Regression ◽  
Expression Profiles ◽  
Immunohistochemical Analysis ◽  
Cox Proportional Hazards ◽  
The Cancer Genome Atlas ◽  
Clinical Value ◽  
Cox Regression Analysis

Objective To investigate the expression and clinical value of the E-selectin gene ( SELE) in colorectal cancer (CRC). Methods Using gene expression profiles and clinicopathological data for patients with CRC from The Cancer Genome Atlas, and tumor and adjacent normal tissues from 31 patients with CRC from Xianyang Central Hospital, we studied the correlation between SELE gene expression and clinical parameters using Kaplan–Meier and Cox proportional hazards regression analyses. Results Higher expression of SELE was significantly associated with a poorer prognosis and shorter survival in patients with CRC. The median expression level of SELE was significantly higher in CRC tissues compared with healthy adjacent tissue. Cox regression analysis showed that the prognosis of CRC was significantly correlated with the expression of SELE. Immunohistochemical analysis also showed that positive expression of E-selectin increased significantly in line with increasing TNM stage. Conclusion: This study confirmed that SELE gene expression is an independent prognostic factor in patients with CRC.

scholarly journals Eps15 Homology Domain-Containing Protein 3 Hypermethylation as a Prognostic and Predictive Marker for Colorectal Cancer

Biomedicines ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 453
Author(s):  
Yu-Han Wang ◽  
Shih-Ching Chang ◽  
Muhamad Ansar ◽  
Chin-Sheng Hung ◽  
Ruo-Kai Lin
Keyword(s):  
Colorectal Cancer ◽  
Overall Survival ◽  
Mrna Expression ◽  
Proportional Hazards ◽  
Uterine Cancer ◽  
Colonic Polyps ◽  
Predictive Marker ◽  
Cox Proportional Hazards ◽  
The Cancer Genome Atlas ◽  
Eps15 Homology Domain

Colorectal cancer (CRC) arises from chromosomal instability, resulting from aberrant hypermethylation in tumor suppressor genes. This study identified hypermethylated genes in CRC and investigated how they affect clinical outcomes. Methylation levels of specific genes were analyzed from The Cancer Genome Atlas dataset and 20 breast cancer, 16 esophageal cancer, 33 lung cancer, 15 uterine cancer, 504 CRC, and 9 colon polyp tissues and 102 CRC plasma samples from a Taiwanese cohort. In the Asian cohort, Eps15 homology domain-containing protein 3 (EHD3) had twofold higher methylation in 44.4% of patients with colonic polyps, 37.3% of plasma from CRC patients, and 72.6% of CRC tissues, which was connected to vascular invasion and high microsatellite instability. Furthermore, EHD3 hypermethylation was detected in other gastrointestinal cancers. In the Asian CRC cohort, low EHD3 mRNA expression was found in 45.1% of patients and was connected to lymph node metastasis. Multivariate Cox proportional-hazards survival analysis revealed that hypermethylation in women and low mRNA expression were associated with overall survival. In the Western CRC cohort, EHD3 hypermethylation was also connected to overall survival and lower chemotherapy and antimetabolite response rates. In conclusion, EHD3 hypermethylation contributes to the development of CRC in both Asian and Western populations.

Il-8 as an underutilized prognostic factor in metastatic colorectal cancer.

2014 ◽  
Vol 32 (3_suppl) ◽  
pp. 409-409
Author(s):  
Manasi S Shah ◽  
David R. Fogelman ◽  
Carrie Daniel-MacDougall ◽  
Kanwal Pratap Singh Raghav ◽  
John Heymach ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Metastatic Colorectal Cancer ◽  
Proportional Hazards ◽  
Principal Component ◽  
Cox Proportional Hazards ◽  
Mortality Data ◽  
Subsequent Work ◽  
Term Survival ◽  
Inflammatory Biomarker ◽  
Kaplan Meier

409 Background: Cancer-associated inflammation has been identified as a key determinant of disease progression and survival in colorectal cancer. We investigated the association between circulating inflammatory cytokines and survival in metastatic colorectal cancer (mCRC) patients. Methods: Plasma levels of 47 cytokines were measured using multiplex-bead assays in a cohort of 168 previously untreated mCRC patients. Demographic, clinical-pathological features, body mass index, and mortality data were abstracted from patient medical records. Overall survival (OS) was evaluated by Kaplan-Meier analysis and Cox proportional hazards regression. Results: Using principal component analysis, we identified a subset of cytokines explaining the maximum variance in OS; and found interleukin (IL)-1b, IL-5, IL-8, IL-12 and VEGF to be significantly associated with OS. However, only IL-8 was significantly and independently associated with OS in multivariable-adjusted models. For each 100 pg/ml increase in the level of circulating IL-8, hazard rate for death increased by 1.6 (95% CI 1.24-1.97). IL-8 measurements ranged from <1 to 413 pg/ml with a median value of 22 pg/ml. Median uncensored survival was 26.5 and 15.5 months among patients with IL-8 levels below and above this value, respectively. ROC analysis of IL-8 demonstrated an AUC of 0.69 (95% CI 0.60-0.76), as compared to 0.52 for CEA (95% CI 0.46-0.59). Conclusions: We identified an association between IL-8 and OS in previously untreated mCRC patients, suggesting its potential role as a prognostic inflammatory biomarker. In this dataset, IL-8 outperformed CEA as a prognostic biomarker, a finding which requires validation in subsequent work. Appropriately identifying, monitoring and managing chronic inflammation and the host inflammatory response during colorectal cancer treatment may be important for improving long-term survival.

scholarly journals A Prognostic Nomogram Combining Gene Expression Profiles and TNM Stage Predicts Survival in Gastric Cancer

2021 ◽  
Author(s):  
Jian Huang ◽  
Dongcun Wang ◽  
Xiaoliang Wang ◽  
Xiaoxing Ye ◽  
Jiping Da
Keyword(s):  
Gene Expression ◽  
Risk Score ◽  
Proportional Hazards ◽  
Expression Profiles ◽  
Tnm Staging ◽  
Cox Proportional Hazards ◽  
Tnm Stage ◽  
The Cancer Genome Atlas ◽  
Prognostic Indicators ◽  
High Morbidity

Abstract BackgroundGastric carcinoma (GC) is a highly aggressive malignancy and is associated with high morbidity and mortality rates around the world, the current tumor-node-metastasis (TNM) staging system is inadequate to predict overall survival (OS) in GC patients. therefore, potential forecasting methods for prognosis are important to investigate.MethodsDifferentially expressed genes (DEGs) were screened using gene expression data from The Cancer Genome Atlas (TCGA). We then construct a risk score signature model by univariate Cox proportional hazards regression (CPHR) analysis, the Kaplan-Meier method（KM）and multivariate CPHR analysis. Using TNM stage, we developed a signature-based nomogram. Finally, we utilize an independent Gene Expression Omnibus dataset (GSE62254) validate the prognostic value of risk score signature model and nomogram.ResultsWe identified five OS-related mRNAs among 1113 mRNAs that were differentially expressed between GC and normal samples in the TCGA dataset. We then constructed a five-mRNA signature model, which efficiently distinguished high-risk from low-risk patient in both cohort, and even viable in the TNM stage-III, gender(male, female) and age(＜65-year-old, ≥65-year-old) subgroups (P<0.05). Utilizing TNM stage, we developed a signature-based nomogram, which performed better than use the TNM stage or five-mRNA signature alone for prognostic prediction in the TCGA and GSE62254 dataset.ConclusionsThese results suggest that both risk signature and nomogram were effective prognostic indicators for patients with GCs, and could potentially be used for individualized management of such patients.

scholarly journals Identification of a Novel Immune-Related CpG Methylation Signature to Predict Prognosis in Stage II/III Colorectal Cancer

2021 ◽  
Vol 12 ◽  
Author(s):  
Feng Chen ◽  
Lijuan Pei ◽  
Siyao Liu ◽  
Yan Lin ◽  
Xinyin Han ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Dna Methylation ◽  
Cox Regression ◽  
Characteristic Curve ◽  
Cox Proportional Hazards ◽  
The Cancer Genome Atlas ◽  
Stage Ii ◽  
Risk Scores ◽  
Cox Regression Analysis ◽  
Methylation Patterns

With the increasing incidence of colorectal cancer (CRC) and continued difficulty in treating it using immunotherapy, there is an urgent need to identify an effective immune-related biomarker associated with the survival and prognosis of patients with this disease. DNA methylation plays an essential role in maintaining cellular function, and changes in methylation patterns may contribute to the development of autoimmunity, aging, and cancer. In this study, we aimed to identify a novel immune-related methylated signature to aid in predicting the prognosis of patients with CRC. We investigated DNA methylation patterns in patients with stage II/III CRC using datasets from The cancer genome atlas (TCGA). Overall, 182 patients were randomly divided into training (n = 127) and test groups (n = 55). In the training group, five immune-related methylated CG sites (cg11621464, cg13565656, cg18976437, cg20505223, and cg20528583) were identified, and CG site-based risk scores were calculated using univariate Cox proportional hazards regression in patients with stage II/III CRC. Multivariate Cox regression analysis indicated that methylated signature was independent of other clinical parameters. The Kaplan–Meier analysis results showed that CG site-based risk scores could significantly help distinguish between high- and low-risk patients in both the training (P = 0.000296) and test groups (P = 0.022). The area under the receiver operating characteristic curve in the training and test groups were estimated to be 0.771 and 0.724, respectively, for prognosis prediction. Finally, stratified analysis results suggested the remarkable prognostic value of CG site-based risk scores in CRC subtypes. We identified five methylated CG sites that could be used as an efficient overall survival (OS)-related biomarker for stage II/III CRC patients.

scholarly journals Expression and Prognostic Significance of NPC1L1 in Colorectal Cancer: A Retrospective Cohort Study

2021 ◽  
Author(s):  
Ryuk Jun Kwon ◽  
Soo Min Son ◽  
Eun Ju Park ◽  
Sang Yeoup Lee ◽  
Jungin Choi ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Proportional Hazards ◽  
Prognostic Significance ◽  
Gene Expression Omnibus ◽  
Cox Proportional Hazards ◽  
The Cancer Genome Atlas ◽  
Rank Test ◽  
Chi Square ◽  
Independent Prognostic Marker ◽  
Niemann Pick

Abstract Background: Colorectal cancer (CRC) is a malignant tumor of the large intestine. Studies have shown that the development and prognosis of CRC are associated with altered lipid metabolism. Niemann-Pick C1-Like 1 (NPC1L1), the target of ezetimibe, plays an essential role in the absorption of intestinal cholesterol. However, the role of altered NPC1L1 expression in the development and prognosis of CRC has not yet been determined.Methods: Datasets of patients with CRC were obtained from The Cancer Genome Atlas (TCGA) database. To compare the expression of NPC1L1 in normal and CRC tissues, datasets obtained from the GDAC platform were used. To support these results, we also analyzed other datasets from the Gene Expression Omnibus (GEO) database. Student’s t-test and chi-square test were used for the analyses. The log-rank test and multivariate Cox proportional hazards regression analysis were performed to determine whether NPC1L1 is a significant factor affecting the prognosis of CRC.Results: The mRNA expression of NPC1L1 was found to be upregulated in CRC, and was significantly associated with the N- and pathological stages, but not with the histological type, age, and sex. Moreover, an increase in NPC1L1 expression in CRC was associated with poorer survival, based on the Kaplan–Meier and multivariate regression analyses.Conclusions: High expression of NPC1L1 is associated with CRC development, pathological stage, and prognosis. The present study suggests that NPC1L1 represents a potential independent prognostic marker for CRC.

scholarly journals Identification of prognostic-associated genes in colorectal cancer based on genome-wide expression profiles

2020 ◽  
Author(s):  
Siyu Hou ◽  
Jinfeng Zhang ◽  
Yanbo Chen ◽  
Shipeng Ning ◽  
Guozheng Li ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Prognostic Value ◽  
Proportional Hazards ◽  
Kegg Pathway ◽  
Expression Profiles ◽  
Severe Disease ◽  
Gene Expression Omnibus ◽  
Cox Proportional Hazards ◽  
Data Set ◽  
Go Terms

Abstract Background: Colorectal cancer (CRC), a severe disease in the world. The dysregulation of genes plays a significant role in cancer. Method: In the present study, we first identified differentially expressed genes (DEGs) of CRC in the GSE71187 data set from the Gene Expression Omnibus (GEO) database. And through GO terminology and Gene and Genome (KEGG) pathway, the up-regulated DEG and down-regulated genes were enriched. Then, we selected hub genes and studied their related prognostic value through protein-protein interaction (PPI) network and integrated bioinformatics analysis. Finally, 7 genes with prognostic value were obtained by survival analysis and multivariate Cox proportional hazards regression models, as well as verified in the Oncomine and UALCAN database.Result: A total of 3,588 DEGs were identified with 1,474 upregulated and 3,114 downregulated. Then, GO terms and Genes and Genomes (KEGG) pathway analysis revealed that upregulated DEGs and down-regulated genes were mainly involved in important GO terms and KEGG pathway, for example, defense response to other organism, leukocyte differentiation and epidermis developmen. In the PP network analysis, 6 hub modules and 86 module genes were identified. In the end, 7 genes with prognostic value were obtained through survival and multi-factor analysis. They have significant differences in varying degrees at the level of DNA, mRNA and protein.Conclusion: The results of the study may provide novel insight into the genes and associated pathways involved in CRC, and aid the identifcation of novel therapeutic targets and prognostic marker of CRC.

Prognostic effect of inflammatory genes on stage I-III colorectal cancer – integrative analysis of TCGA data

2020 ◽  
Author(s):  
Eun Kyung Choe ◽  
Sangwoo Lee ◽  
So Yeon Kim ◽  
Manu Shivakumar ◽  
Kyu Joo Park ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Overall Survival ◽  
Clinical Features ◽  
Proportional Hazards ◽  
Cox Proportional Hazards ◽  
Integrative Analysis ◽  
Stage I ◽  
The Cancer Genome Atlas ◽  
Integrative Model ◽  
Inflammatory Status

Abstract Background Inflammatory status indicators have been reported as a prognostic biomarker of colorectal cancer (CRC). However, since the inflammatory interactions with colon involve various modes of action, the biological mechanism to link inflammation and CRC prognosis is not fully elucidated. We comprehensively evaluated the predictive role of the expression and methylation level of inflammation-related genes for CRC prognosis and their pathophysiological associations. Method An integrative analysis was conducted on 247 patients of stage I-III CRC from The Cancer Genome Atlas. Lasso-penalized Cox proportional hazards regression (Lasso-Cox) and statistical Cox proportional hazard regression (CPH) were used for analysis. Result Models to predict overall survival were designed with respective combinations of clinical variables, including age, sex, stage, gene expression, and methylation. An integrative model combining expression, methylation, and clinical features had the highest performance (median C-index=0.756), compared to the model with clinical features alone (median C-index=0.726). By multivariate CPH with features from the best model, methylation levels of CEP250, RAB21 and TNPO3 were significantly associated with overall survival. They did not share any biological process in functional networks. The 5-year survival rate was 29.8% in a low methylation group of CEP250 and 79.1% in a high (P <0.001). Conclusion Our study result implicates the importance of integrating the expression and methylation information along with clinical information in prediction of survival. CEP250, RAB21 and TNPO3, in the prediction model might have a crucial role in CRC prognosis and further improve our understanding of potential mechanisms linking inflammatory reaction and CRC progression.

scholarly journals Prognostic Value of a Three-DNA Methylation Biomarker in Patients with Soft Tissue Sarcoma

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Yuxiao Chen ◽  
Rui Zhu ◽  
Min Chen ◽  
Wenna Guo ◽  
Xin Yang ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Soft Tissue ◽  
Proportional Hazards ◽  
Prognostic Biomarker ◽  
Close Association ◽  
Characteristic Curve ◽  
Soft Tissue Sarcomas ◽  
Cox Proportional Hazards ◽  
The Cancer Genome Atlas ◽  
Mesenchymal Tumors

Soft tissue sarcomas (STS) are a highly aggressive and heterogeneous group of malignant mesenchymal tumors. The prognosis of patients with advanced or metastatic STS remains poor, and the main therapy of STS patients combines primary surgery, radiotherapy, and chemotherapy. Aberrant DNA methylation shows close association with the pathogenesis and tumor progression. Therefore, DNA methylation biomarkers might have the potential in accurately predicting the survival of STS patients. In order to identify a prognostic biomarker based on DNA methylation sites, a comprehensive analysis of the DNA methylation profile of STS patients in the Cancer Genome Atlas (TCGA) database was performed. All samples were randomly divided into training and testing datasets. Cox proportional hazards regression analysis was performed to identify a prognostic biomarker that contains three DNA methylation sites. The Kaplan–Meier analysis demonstrated that the 3-DNA methylation biomarker discriminated patients into high-risk and low-risk groups, both in the training and in the testing datasets, and the area under the receiver operating characteristic curve values (AUCs) were 0.844 (P<0.001, 95% CI: 0.740–0.948) and 0.710 (P=0.002, 95% CI: 0.595–0.823), respectively. Besides, this biomarker presented superior prognostic performance in STS patients with different age, sex, tissue of origin, therapy, and histologic subtypes. Compared with other prognostic biomarkers, this biomarker tended to be a more precise prognostic factor in STS patients. Moreover, methylation sites in this biomarker might provide a new way for clinicians to make decisions regarding the intervention and assess the effectiveness of an individual therapeutic strategy.

scholarly journals The Prognostic Significance of PDE7B in Cytogenetically Normal Acute Myeloid Leukemia

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Ling Cao ◽  
Weilong Zhang ◽  
Xiaoni Liu ◽  
Ping Yang ◽  
Jing Wang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Acute Myeloid Leukemia ◽  
Myeloid Leukemia ◽  
Proportional Hazards ◽  
Expression Profiles ◽  
Prognostic Significance ◽  
Gene Expression Profiles ◽  
Cox Proportional Hazards ◽  
The Cancer Genome Atlas ◽  
Acute Myeloid

AbstractAcute myeloid leukemia (AML) is a malignant hematological disease in which nearly half have normal cytogenetics. We have tried to find some significant molecular markers for this part of the cytogenetic normal AML, which hopes to provide a benefit for the diagnosis, molecular typing and prognosis prediction of AML patients. In the present study, we calculated and compared the gene expression profiles of cytogenetically normal acute myeloid leukemia (CN-AML) patients in database of The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO) and dataset Vizome (a total of 632 CN-AML samples), and we have demonstrated a correlation between PDE7B gene and CN-AML. Then we proceeded to a survival analysis and prognostic risk analysis between the expression levels of PDE7B gene and CN-AML patients. The result showed that the event-free survival (EFS) and overall survival (OS) were significantly shorter in CN-AML patients with high PDE7B levels in each dataset. And we detected a significantly higher expression level of PDE7B in the leukemia stem cell (LSC) positive group. The Cox proportional hazards regression model showed that PDE7B is an independent risk predictor for CN-AML. All results indicate that PDE7B is an unfavorable prognostic factor for CN-AML.

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