scholarly journals Gene expression and DNA methylation analyses suggest that two immune related genes are prognostic factors of colorectal cancer

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Xiao-Liang Xing ◽  
Zhi-Yong Yao ◽  
Chaoqun Xing ◽  
Zhi Huang ◽  
Jing Peng ◽  
...  

Abstract Background Colorectal cancer (CRC) is the second most prevalent cancer, as it accounts for approximately 10% of all annually diagnosed cancers. Studies have indicated that DNA methylation is involved in cancer genesis. The purpose of this study was to investigate the relationships among DNA methylation, gene expression and the tumor-immune microenvironment of CRC, and finally, to identify potential key genes related to immune cell infiltration in CRC. Methods In the present study, we used the ChAMP and DESeq2 packages, correlation analyses, and Cox regression analyses to identify immune-related differentially expressed genes (IR-DEGs) that were correlated with aberrant methylation and to construct a risk assessment model. Results Finally, we found that HSPA1A expression and CCRL2 expression were positively and negatively associated with the risk score of CRC, respectively. Patients in the high-risk group were more positively correlated with some types of tumor-infiltrating immune cells, whereas they were negatively correlated with other tumor-infiltrating immune cells. After the patients were regrouped according to the median risk score, we could more effectively distinguish them based on survival outcome, clinicopathological characteristics, specific tumor-immune infiltration status and highly expressed immune-related biomarkers. Conclusion This study suggested that the risk assessment model constructed by pairing immune-related differentially expressed genes correlated with aberrant DNA methylation could predict the outcome of CRC patients and might help to identify those patients who could benefit from antitumor immunotherapy.

2021 ◽  
Vol 11 ◽  
Author(s):  
Qinglian He ◽  
Ziqi Li ◽  
Jinbao Yin ◽  
Yuling Li ◽  
Yuting Yin ◽  
...  

BackgroundColorectal cancer (CRC) is a common malignant solid tumor with an extremely low survival rate after relapse. Previous investigations have shown that autophagy possesses a crucial function in tumors. However, there is no consensus on the value of autophagy-associated genes in predicting the prognosis of CRC patients. This work screens autophagy-related markers and signaling pathways that may participate in the development of CRC, and establishes a prognostic model of CRC based on autophagy-associated genes.MethodsGene transcripts from the TCGA database and autophagy-associated gene data from the GeneCards database were used to obtain expression levels of autophagy-associated genes, followed by Wilcox tests to screen for autophagy-related differentially expressed genes. Then, 11 key autophagy-associated genes were identified through univariate and multivariate Cox proportional hazard regression analysis and used to establish prognostic models. Additionally, immunohistochemical and CRC cell line data were used to evaluate the results of our three autophagy-associated genes EPHB2, NOL3, and SNAI1 in TCGA. Based on the multivariate Cox analysis, risk scores were calculated and used to classify samples into high-risk and low-risk groups. Kaplan-Meier survival analysis, risk profiling, and independent prognosis analysis were carried out. Receiver operating characteristic analysis was performed to estimate the specificity and sensitivity of the prognostic model. Finally, GSEA, GO, and KEGG analysis were performed to identify the relevant signaling pathways.ResultsA total of 301 autophagy-related genes were differentially expressed in CRC. The areas under the 1-year, 3-year, and 5-year receiver operating characteristic curves of the autophagy-based prognostic model for CRC were 0.764, 0.751, and 0.729, respectively. GSEA analysis of the model showed significant enrichment in several tumor-relevant pathways and cellular protective biological processes. The expression of EPHB2, IL-13, MAP2, RPN2, and TRAF5 was correlated with microsatellite instability (MSI), while the expression of IL-13, RPN2, and TRAF5 was related to tumor mutation burden (TMB). GO analysis showed that the 11 target autophagy genes were chiefly enriched in mRNA processing, RNA splicing, and regulation of the mRNA metabolic process. KEGG analysis showed enrichment mainly in spliceosomes. We constructed a prognostic risk assessment model based on 11 autophagy-related genes in CRC.ConclusionA prognostic risk assessment model based on 11 autophagy-associated genes was constructed in CRC. The new model suggests directions and ideas for evaluating prognosis and provides guidance to choose better treatment strategies for CRC.


Cancers ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 876
Author(s):  
Boyoung Park ◽  
Sarah Yang ◽  
Jeonghee Lee ◽  
Il Ju Choi ◽  
Young-Il Kim ◽  
...  

We investigated the performance of a gastric cancer (GC) risk assessment model in combination with single-nucleotide polymorphisms (SNPs) as a polygenic risk score (PRS) in consideration of Helicobacter pylori (H. pylori) infection status. Six SNPs identified from genome-wide association studies and a marginal association with GC in the study population were included in the PRS. Discrimination of the GC risk assessment model, PRS, and the combination of the two (PRS-GCS) were examined regarding incremental risk and the area under the receiver operating characteristic curve (AUC), with grouping according to H. pylori infection status. The GC risk assessment model score showed an association with GC, irrespective of H. pylori infection. Conversely, the PRS exhibited an association only for those with H. pylori infection. The PRS did not discriminate GC in those without H. pylori infection, whereas the GC risk assessment model showed a modest discrimination. Among individuals with H. pylori infection, discrimination by the GC risk assessment model and the PRS were comparable, with the PRS-GCS combination resulting in an increase in the AUC of 3%. In addition, the PRS-GCS classified more patients and fewer controls at the highest score quintile in those with H. pylori infection. Overall, the PRS-GCS improved the identification of a GC-susceptible population of people with H. pylori infection. In those without H. pylori infection, the GC risk assessment model was better at identifying the high-risk group.


2020 ◽  
Vol 20 ◽  
Author(s):  
Zsuzsanna Molnár ◽  
Zsófia Bánlaki ◽  
Anikó Somogyi ◽  
Zoltán Herold ◽  
Magdolna Herold ◽  
...  

Background: Type 2 diabetes (T2DM) and colorectal cancer (CRC) are both known to modulate gene expression patterns in peripheral blood leukocytes (PBLs). Objective : As T2DM has been shown to increase the incidence of CRC, we were prompted to check whether diabetes affects mRNA signatures in PBLs isolated from CRC patients. Methods : 22 patients were recruited to the study and classified into four cohorts (healthy controls; T2DM; CRC; CRC and T2DM). Relative expression levels of 573 cell signaling gene transcripts were determined by reverse transcription real-time PCR assays run on low-density OpenArray platforms. Enrichment analysis was performed with the g:GOSt profiling tool to order differentially expressed genes into functional pathways. Results : 49 genes were found to be significantly up- or downregulated in tumorous diabetic individuals as compared to tumor-free diabetic controls, while 11 transcripts were differentially regulated in patients with CRC versus healthy, tumor-free and non-diabetic controls. Importantly, these gene sets were completely distinct, implying that diabetes exerts profound influence on the transcription of signaling genes in CRC. The top 5 genes showing most significant expression differences in both contexts were PCK2, MAPK9, CCND1, HMBS, TLR3 (p≤ 0.0040) and CREBBP, PPIA, NFKBIL1, MDM2 and SELPLG (p0.0121), respectively. Functional analysis revealed that most significantly affected pathways were cytokine, interleukin and PI3K/Akt/mTOR signaling cascades as well as mitotic regulation. Conclusions : We propose that differentially expressed genes listed above might be potential biomarkers of CRC and should be studied further on larger patient groups. Diabetes might promote colorectal carcinogenesis by impairing signaling pathways in PBLs.


2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Cheng Zhang ◽  
Bingye Zhang ◽  
Di Meng ◽  
Chunlin Ge

Abstract Background The incidence of cholangiocarcinoma (CCA) has risen in recent years, and it has become a significant health burden worldwide. However, the mechanisms underlying tumorigenesis and progression of this disease remain largely unknown. An increasing number of studies have demonstrated crucial biological functions of epigenetic modifications, especially DNA methylation, in CCA. The present study aimed to identify and analyze methylation-regulated differentially expressed genes (MeDEGs) involved in CCA tumorigenesis and progression by bioinformatics analysis. Methods The gene expression profiling dataset (GSE119336) and gene methylation profiling dataset (GSE38860) were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) and differentially methylated genes (DMGs) were identified using the limma packages of R and GEO2R, respectively. The MeDEGs were obtained by overlapping the DEGs and DMGs. Functional enrichment analyses of these genes were then carried out. Protein–protein interaction (PPI) networks were constructed using STRING and visualized in Cytoscape to determine hub genes. Finally, the results were verified based on The Cancer Genome Atlas (TCGA) database. Results We identified 98 hypermethylated, downregulated genes and 93 hypomethylated, upregulated genes after overlapping the DEGs and DMGs. These genes were mainly enriched in the biological processes of the cell cycle, nuclear division, xenobiotic metabolism, drug catabolism, and negative regulation of proteolysis. The top nine hub genes of the PPI network were F2, AHSG, RRM2, AURKB, CCNA2, TOP2A, BIRC5, PLK1, and ASPM. Moreover, the expression and methylation status of the hub genes were significantly altered in TCGA. Conclusions Our study identified novel methylation-regulated differentially expressed genes (MeDEGs) and explored their related pathways and functions in CCA, which may provide novel insights into a further understanding of methylation-mediated regulatory mechanisms in CCA.


Blood ◽  
2013 ◽  
Vol 122 (21) ◽  
pp. 3671-3671
Author(s):  
Michael Getman ◽  
Jeffrey Malik ◽  
James Palis ◽  
Laurie A Steiner

Abstract The molecular mechanisms that drive the maturation of a committed erythroid progenitor to a functional red blood cell are incompletely understood. LSD1 (Lysine-Specific Histone Demethylase 1) is a widely expressed histone demethylase that plays an important role in erythroid maturation (Kereyni, elife, 2013). Although LSD1 is important for a number of biologic processes ranging from embryonic development to leukemogenesis, the molecular mechanisms underlying the influence of LSD1 on gene expression are incompletely understood. The goal of our study is to elucidate the molecular mechanisms by which LSD1 regulates erythroid gene expression and influences erythroid maturation. We hypothesize that LSD1 promotes specific patterns of histone and DNA methylation that facilitate gene expression changes necessary for normal erythroid maturation to occur. To address this hypothesis, the functional and molecular consequences of LSD1 knockdown were assessed in Extensively Self Renewing Erythroblasts (ESREs), a non-transformed, karyotypically normal model of terminal erythroid maturation (England, Blood, 2011). Primary fetal liver was cultured in the presence of EPO, SCF, IGF1 and dexamethasone to derive ESREs. The ESREs were capable of extensive ex-vivo expansion, doubling daily at the proerythroblast phase, however when matured, >90% of cells became benzidine positive and >65% enucleated within 3 days. Lentiviral-mediated shRNA was used to knock down LSD1 in expanding ESREs. Imaging flow cytometry done on maturation day 3 demonstrated that the knockdown cells had impairments in multiple facets of maturation, with larger cell and nuclear areas, higher kit expression, and lower rates of enucleation than the scramble control. LSD1 knockdown was also associated with impaired hemoglobin accumulation (78% vs. 95% benzidine positive; p<0.005). Treatment of ESREs with an inhibitor to LSD1 (Tranylcypromine; TCP) resulted in similar abnormalities in cell and nuclear size, kit expression, hemoglobin accumulation, and enucleation (40% vehicle vs.1% TCP). The functional deficits in maturation, including abnormal kit expression and low rates of enucleation, persisted on maturation day 4. To delineate the molecular mechanisms underlying this maturation impairment, RNA-seq was done in LSD1 knockdown and scramble control samples, and 230 differentially expressed genes (FDR<0.01) were identified using cuffdiff (Trapnell, Nat Biotech, 2013). Consistent with LSD1’s role in erythroid maturation, Ingenuity Pathway Analysis identified multiple networks involving hemoglobin synthesis, and GATA1, EPO, and KLF1 were all predicted as upstream regulators (p-values of 8.24e10-11, 7.25 e10-6, and 3.86e10-4, respectively). To better understand how LSD1 influences gene expression, chromatin immunoprecipitation coupled with high throughput sequencing was used to identify sites of H3K4me2 binding in the differentially expressed genes. 214/230 differentially expressed genes were associated with sites of H3K4me2 occupancy. Quantitative ChIP demonstrated that LSD1 inhibition was associated with increases in H3K4me2 levels at a subset of these sites, however consistent with previous studies, global levels of H3K4me2, determined by Enzyme Linked Immunosorbent Assay (ELIZA), did not change significantly. Although it is known that LSD1 demethylates and stabilizes the maintenance DNA methyltransferase DNMT1 (Wang, Nat Genet 2009), the consequences of LSD1 loss on DNA methylation (5-methyl cytosine; 5-mC) have yet to be investigated. To gain a comprehensive understanding of how LSD1 regulates erythroid gene expression, changes in the level of 5-mC were assessed after knockdown or inhibition of LSD1. Global 5-mC levels, determined by ELIZA assay, were ∼30% lower in TCP treated samples than vehicle treated control (p<0.02) and western blot demonstrated a 3-fold decrease in DNMT1 protein in the TCP treated samples. Both methyl binding domain pull-down coupled with quantitative PCR and genome-wide bisulfite sequencing were utilized to assess changes in 5-mC levels in the differentially expressed genes. Loss of LSD1 was associated with significantly lower levels of 5-mC at several differentially expressed, erythroid-specific genes, such as bh1. Taken together, these data support the hypothesis that LSD1 influences both histone and DNA methylation at genes important for erythroid maturation. Disclosures: No relevant conflicts of interest to declare.


2017 ◽  
Vol 24 (3) ◽  
pp. 471-476 ◽  
Author(s):  
Y. Wang ◽  
B. M. Attar ◽  
H. E. Fuentes ◽  
J. Yu ◽  
Huiyuan Zhang ◽  
...  

Cancer-associated venous thromboembolism (VTE) is one of the leading causes of mortality and morbidity among patients with malignancy. The Khorana risk score (KRS) is currently the best validated risk assessment model to stratify risks of VTE development in ambulatory patients with cancer. In the current study, we assessed the performance of KRS in patients with hepatocellular carcinoma (HCC). We retrospectively analyzed patients with diagnosis of HCC (screened by International Classification of Diseases [ ICD-9] and ICD-10 code, confirmed with radiographic examination and/or histopathology) at a large public hospital over 15 years (January 2000 through July 2015). Cases with VTE were identified through radiographic examination and blindly adjudicated. Khorana risk score was calculated for each patient, and its association with VTE development and mortality was assessed. Among 270 patients with HCC, 16 (5.9%) cases of VTE were identified, including 7 (43.8%) pulmonary embolism, 4 (25%) peripheral deep vein thrombosis, and 6 (37.5%) intra-abdominal thrombosis. One hundred eighty-four (68.1%) patients had a KRS of 0 and 86 (31.9%) patients had a KRS >0. Most of the thrombotic (n = 9, 56%) events occurred in the low-risk group. In univariate analysis, only prechemotherapy leukocyte count equal to or greater than 11 000/μL was statistically significant in the prediction of VTE incidence. After adjusting for confounding factors in multivariate analysis, KRS >0 was not predictive of VTE (hazard ratio [HR] = 1.83, 95% confidence interval [CI] = 0.81-4.15, P = .15) or mortality (HR = 1.61, 95% CI = 0.92-2.81, P = .09). Khorana risk score did not predict VTE development or mortality in patients with HCC. Design of HCC-specific risk assessment model for VTE development is necessary.


2020 ◽  
Vol 2020 ◽  
pp. 1-6
Author(s):  
Hikmat Abdel-Razeq ◽  
Luna Zaru ◽  
Ahmed Badheeb ◽  
Shadi Hijjawi

Background and Objectives. Breast cancer has been the most common cancer affecting women in Jordan. In the process of implementing breast cancer prevention and early detection programs, individualized risk assessment can add to the cost-effectiveness of such interventions. Gail model is a widely used tool to stratify patients into different risk categories. However, concerns about its applicability across different ethnic groups do exist. In this study, we report our experience with the application of a modified version of this model among Jordanian women. Methods. The Gail risk assessment model (RAM) was modified and used to calculate the 5-year and lifetime risk for breast cancer. Patients with known breast cancer were used to test this model. Medical records and hospital database were utilized to collect information on known risk factors. The mean calculated risk score for women tested was 0.65. This number, which corresponds to the Gail original score of 1.66, was used as a cutoff point to categorize patients as high risk. Results. A total of 1786 breast cancer patients with a mean age of 50 (range: 19–93) years were included. The modified version of the Gail RAM was applied on 1213 patients aged 35–59.9 years. The mean estimated risk for developing invasive breast cancer over the following five years was 0.54 (95% CI: 0.52, 0.56), and the lifetime risk was 3.42 (95% CI: 3.30, 3.53). Only 210 (17.3%) women had a risk score >0.65 and thus categorized as high risk. First-degree family history of breast cancer was identified among 120 (57.1%) patients in this high-risk group. Conclusions. Among a group of patients with an established diagnosis of breast cancer, a modified Gail risk assessment model would have been able to stratify only 17% into the high-risk category. The family history of breast cancer contributed the most to the risk score.


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