A methylation-based prognostic model predicts survival in patients with colorectal cancer.
01 Aug 2021-Journal of gastrointestinal oncology (AME Publishing Company)-Vol. 12, Iss: 4, pp 1590-1600
TL;DR: In this article, a model that could effectively predict the prognosis of colorectal cancer (CRC) by searching for methylated-differentially expressed genes (MDEGs) was proposed.
Abstract: Background To construct a model that could effectively predict the prognosis of colorectal cancer (CRC) by searching for methylated-differentially expressed genes (MDEGs). Methods We identified MDEGs through four databases from Gene Expression Omnibus (GEO) and annotated their functions via bioinformatics analysis. Subsequently, after adjusting for gender, age, and grading, multivariate Cox hazard analysis was utilized to select MDEGs interrelated with the prognosis of CRC, and LASSO analysis was utilized to fit the prediction model in the training set. Furthermore, another independent dataset was harnessed to verify the effectiveness of the model in predicting prognosis. Results In total, 252 hypomethylated and up-regulated genes and 132 hypermethylated and down-regulated genes were identified, 27 of which were correlated with the prognosis of CRC, and a 10-gene prognostic model was established after LASSO analysis. The overall survival rate could be effectively grouped into different risks by the median score of this model in the training set [risk ratio (HR) =2.27, confidence interval (95% CI), 1.69-3.13, P=8.15×10-8], and the validity of its effect in predicting prognosis in CRC was verified in the validation dataset (HR =1.75, 95% CI, 1.15-2.70, P=9.32×10-3). Conclusions Our model could effectively predict the overall survival rate of patients with CRC and provides potential application guidelines for its clinically personalized treatment.
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TL;DR: In this article , an ERS-related genes (ERSRGs) model was developed to aid in the prognostic evaluation and treatment of colorectal cancer patients, where the ERS was used to identify the most likely ERS genes.
Abstract: An increasing body of evidence supports an essential role for endoplasmic reticulum stress (ERS) in colorectal cancer (CRC). In this study, we developed an ERS‐related genes (ERSRGs) model to aid in the prognostic evaluation and treatment of CRC patients.
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TL;DR: This study investigated genomic regions in which methylation changes can affect gene expression and proposed that aberrantly expressed genes due to DNA methylation can lead to CRC pathogenesis by the immune system.
Abstract: Simple Summary Abnormal DNA methylation is known to regulate gene expression, and its features have been frequently observed in colorectal cancer (CRC) patients. In addition, alterations in DNA methylation can be proposed as biomarkers for cancer prognosis, as they occur in the early stage of carcinogenesis. Although numerous studies have attempted to shed light on the impacts of DNA methylation on gene expression, it is still unclear which specific regions regulate gene expression and how they are associated with patient survival. In this study, we elucidated the intricate relationship between DNA methylation and gene expression. Furthermore, we found genes that were influenced by DNA methylation and were associated with survival; these genes were mainly enriched in immune-related pathways. Abstract The aberrant expression of cancer-related genes can lead to colorectal cancer (CRC) carcinogenesis, and DNA methylation is one of the causes of abnormal expression. Although many studies have been conducted to reveal how DNA methylation affects transcription regulation, the ways in which it modulates gene expression and the regions that significantly affect DNA methylation-mediated gene regulation remain unclear. In this study, we investigated how DNA methylation in specific genomic areas can influence gene expression. Several regression models were constructed for gene expression prediction based on DNA methylation. Among these models, ElasticNet, which had the best performance, was chosen for further analysis. DNA methylation near transcription start sites (TSS), especially from 2 kb upstream to 7 kb downstream of TSS, had an essential regulatory role in gene expression. Moreover, methylation-affected and survival-associated genes were compiled and found to be mainly enriched in immune-related pathways. This study investigated genomic regions in which methylation changes can affect gene expression. In addition, this study proposed that aberrantly expressed genes due to DNA methylation can lead to CRC pathogenesis by the immune system.
TL;DR: In this article , a systematic review summarizes the current use of ML-based methods in epigenome-wide studies for the identification of DNA methylation signatures associated with cancer prognosis.
TL;DR: In this paper , a systematic review summarizes the current use of ML-based methods in epigenome-wide studies for the identification of DNA methylation signatures associated with cancer prognosis.
Abstract: Background: DNA methylation biomarkers have great potential in improving prognostic classification systems for patients with cancer. Machine learning (ML)- based analytic techniques might help overcome the challenges of analyzing high- dimensional data in relatively small sample sizes. This systematic review summarizes the current use of ML-based methods in epigenome-wide studies for the identification of DNA methylation signatures associated with cancer prognosis. Methods: We searched three electronic databases including PubMed, EMBASE, and Web of Science for articles published until 8 June 2022. ML-based methods and workflows used to identify DNA methylation signatures associated with cancer prognosis were extracted and summarized. Two authors independently assessed the methodological quality of included studies by a seven-item checklist adapted from relevant guidelines. Results: Seventy-six studies were included in this review. Three major types of ML- based workflows were identified: 1) unsupervised clustering, 2) supervised feature selection, and 3) deep learning-based feature transformation. For the three workflows, the most frequently used ML techniques were consensus clustering, least absolute shrinkage and selection operator (LASSO), and autoencoder, respectively. The systematic review revealed that the performance of these approaches has not 2 been adequately evaluated yet and that methodological and reporting flaws were common in the identified studies using ML techniques. Conclusions: There is great heterogeneity in ML-based methodological strategies used by epigenome-wide studies to identify DNA methylation markers associated with cancer prognosis. Benchmarking studies are needed to compare the relative performance of various approaches for specific cancer types. Adherence to relevant methodological and reporting guidelines are urgently needed.
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TL;DR: Progress against CRC can be accelerated by increasing access to guideline‐recommended screening and high‐quality treatment, particularly among Alaska Natives, and elucidating causes for rising incidence in young and middle‐aged adults.
Abstract: Colorectal cancer (CRC) is the second most common cause of cancer death in the United States. Every 3 years, the American Cancer Society provides an update of CRC occurrence based on incidence data (available through 2016) from population-based cancer registries and mortality data (through 2017) from the National Center for Health Statistics. In 2020, approximately 147,950 individuals will be diagnosed with CRC and 53,200 will die from the disease, including 17,930 cases and 3,640 deaths in individuals aged younger than 50 years. The incidence rate during 2012 through 2016 ranged from 30 (per 100,000 persons) in Asian/Pacific Islanders to 45.7 in blacks and 89 in Alaska Natives. Rapid declines in incidence among screening-aged individuals during the 2000s continued during 2011 through 2016 in those aged 65 years and older (by 3.3% annually) but reversed in those aged 50 to 64 years, among whom rates increased by 1% annually. Among individuals aged younger than 50 years, the incidence rate increased by approximately 2% annually for tumors in the proximal and distal colon, as well as the rectum, driven by trends in non-Hispanic whites. CRC death rates during 2008 through 2017 declined by 3% annually in individuals aged 65 years and older and by 0.6% annually in individuals aged 50 to 64 years while increasing by 1.3% annually in those aged younger than 50 years. Mortality declines among individuals aged 50 years and older were steepest among blacks, who also had the only decreasing trend among those aged younger than 50 years, and excluded American Indians/Alaska Natives, among whom rates remained stable. Progress against CRC can be accelerated by increasing access to guideline-recommended screening and high-quality treatment, particularly among Alaska Natives, and elucidating causes for rising incidence in young and middle-aged adults.
2,928 citations
TL;DR: The basic principles behind DNA methylation, histone modification, nucleosome remodeling, and RNA-mediated targeting are presented and the evidence suggesting that their misregulation can culminate in cancer is highlighted.
2,501 citations
TL;DR: Progress in the understanding of aberrant methylation in CRC has led to epigenetic alterations being developed as clinical biomarkers for diagnostic, prognostic and therapeutic applications, and it is suggested that these methylated alterations will be commonly used in the near future to direct the prevention and treatment of CRC.
Abstract: Colorectal cancer (CRC) is a leading cause of cancer deaths worldwide. It results from an accumulation of genetic and epigenetic changes in colon epithelial cells, which transforms them into adenocarcinomas. Over the past decade, major advances have been made in understanding cancer epigenetics, particularly regarding aberrant DNA methylation. Assessment of the colon cancer epigenome has revealed that virtually all CRCs have aberrantly methylated genes and that the average CRC methylome has hundreds to thousands of abnormally methylated genes. As with gene mutations in the cancer genome, a subset of these methylated genes, called driver genes, is presumed to have a functional role in CRC. The assessment of methylated genes in CRCs has also revealed a unique molecular subgroup of CRCs called CpG island methylator phenotype (CIMP) cancers; these tumors have a particularly high frequency of methylated genes. These advances in our understanding of aberrant methylation in CRC have led to epigenetic alterations being developed as clinical biomarkers for diagnostic, prognostic and therapeutic applications. Progress in this field suggests that these epigenetic alterations will be commonly used in the near future to direct the prevention and treatment of CRC.
586 citations
TL;DR: Assessment of the colon cancer "epigenome" has revealed that virtually all CRCs have aberrantly methylated genes and altered miRNA expression, and progress in this field suggests that these epigenetic alterations will be commonly used in the near future to direct the prevention and treatment of CRC.
527 citations
TL;DR: Despite the ongoing development of novel antitumor agents and therapeutic principles as the authors enter the era of personalized cancer medicine, systemic chemotherapy involving infusional 5-FU/leucovorin continues to be the cornerstone of treatment for patients with CRC.
387 citations