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Differential DNA methylation delineated using Illumina Infinium HumanMethylation450 BeadChip microarray platform in blood DNA collected prior to conventional diagnosis (pre-diagnostic) with hepatocellular carcinoma (HCC). Comparison of Illumina 450K array data of pre-diagnostic and post-diagnostic study groups. (A) Pie chart of the 971 CpG sites differentially methylated between pre-diagnostic HCC cases and matched healthy controls. Diff. refers to differential methylation (delta beta = case beta value -control beta value, where delta beta refers to methylation level). 76% of all differentially methylated CpGs in pre-diagnostic subgroup were hypomethylated. (B) A color-coded table showing median methylation levels and first and third quartile values (in brackets) in cases (average of n = 21) and matched controls (average of n = 21) for 11 CpG sites corresponding to 10 genes (probes) selected for further validation. (C) A bar chart shows CpG sites and genes differentially methylated in pre-and post-diagnostic subgroups as compared with matched healthy controls. (D) Classification of differentially methylated CpG sites in pre-diagnostic and post-diagnostic subgroups according to the location relative to CpG islands (CpGI, left panel) and transcription start site (TSS, right panel). Red bars correspond to hypermethylation (positive values) and blue bars represent hypomethylation (negative values). (E) Manhattan plots displaying differentially methylated CpG sites in pre-diagnostic (left panel) and post-diagnostic (middle panel) cases vs. matched healthy controls. Chromosomes are color coded to demonstrate the distribution of methylation changes. Each dot corresponds to a single CpG site and reflects a level of significance. The higher value of -log(P value) the more significant difference. (F) A bar chart shows common CpG sites and common genes differentially methylated in both pre-and post-diagnostic subgroups as compared with matched healthy controls.
Source publication
Late onset of clinical symptoms in hepatocellular carcinoma (HCC) results in late diagnosis and poor disease outcome. Approximately 85% of individuals with HCC have underlying liver cirrhosis. However, not all cirrhotic patients develop cancer. Reliable tools that would distinguish cirrhotic patients who will develop cancer from those who will not...
Contexts in source publication
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... 971 differentially methylated CpG sites were identified in pre-diagnostic HCC cases as compared with healthy controls (P <0.05, paired Wilcoxon test, ICC ≥0.5) (Figure 4(A)). Among 735 hypomethylated CpG sites, 438 sites were assigned to gene coding regions whereas 236 hypermethylated sites corresponded to 144 genes. ...
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... most robust changes with delta beta (diff.) higher than 0.30 were identified within 5ʹUTR of ACAN, CpG island of ATHL1, and CpG island shelf of RPTOR (Figure 4(B)). Figure 3. Differentially methylated regions within 5 hypomethylated probes: PCGF3, KDM2B, CTTN, TSPAN5, and SPATA13; and 7 hypermethylated probes: DPPA5, HIVEP3, JPH3, KIAA1210, LYNX1, LSP1, and SERPINB9, in hepatocellular carcinoma (HCC) cases vs. matched healthy controls. ...
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... the number of hyper-and hypo-methylated sites in post-diagnostic samples was practically equal (Figure 2(A-C)), nearly 76% of differentially methylated CpG sites in Study Group #2 (pre-diagnostic) showed lower levels of methylation in cases vs. controls (P = 2.973E-11, Wilcoxon test) (Figure 4(C)). This suggests a stronger regulatory role of hypomethylation in gene transcription in blood cells of individuals developing cancer which is consistent with previous findings [54]. ...
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... suggests a stronger regulatory role of hypomethylation in gene transcription in blood cells of individuals developing cancer which is consistent with previous findings [54]. Indeed, those hypomethylated loci are located in regulatory regions important for gene transcription such as CpG island shores, promoters, and 5'UTR (Figure 4(B,D)). The distribution of differentially methylated CpGs relative to CpG islands and TSS is similar between pre-and post-diagnostic groups (Figure 4(D)). ...
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... those hypomethylated loci are located in regulatory regions important for gene transcription such as CpG island shores, promoters, and 5'UTR (Figure 4(B,D)). The distribution of differentially methylated CpGs relative to CpG islands and TSS is similar between pre-and post-diagnostic groups (Figure 4(D)). Similarly to post-diagnostic patterns, genes hypomethylated in the Study Group #2 (prediagnostic) fall into category of multiple signaling pathways indicating a potential role for those genes in regulating functions of immune cells and subsequently the immune response at very early stages of cancer development. ...
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... in methylation expressed as median case -median control (delta beta = differential methylation) was higher than 0.1 in 20% of identified changes in Study Group #2 (pre-diagnostic) (Figure 4(A)). Level of significance for changes observed in the pre-diagnostic group was lower than at the post-diagnostic stage as indicated by Manhattan plots in Figure 4(E). ...
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... in methylation expressed as median case -median control (delta beta = differential methylation) was higher than 0.1 in 20% of identified changes in Study Group #2 (pre-diagnostic) (Figure 4(A)). Level of significance for changes observed in the pre-diagnostic group was lower than at the post-diagnostic stage as indicated by Manhattan plots in Figure 4(E). It could suggest progression of changes along with the disease development. ...
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... indeed observed numerous such examples including genes selected as candidates for validation in pyrosequencing based on the microarray data in Study Group #1 (depicted in squares in Figure 2(F) (cg26764761) show a difference of 0.008 and 0.1, respectively, at pre-diagnostic stages, which progressed to 0.28 and 0.34 in diagnosed HCC. As shown in Figure 4(F), 44 CpG sites corresponding to 27 genes are differentially methylated at both preand post-diagnostic stages of HCC (Supplementary Table S3). Interestingly, although significant, changes at those common CpGs are subtle and rather constant throughout the disease development. ...
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... methylation within ATHL1, ACAN, BRUNOL5, BARD1, MAGEB3, FXYD6, TET1, PSG4, RPTOR, and CHRDL1, as quantified by pyrosequencing distinguishes blood of HCC cases prior to diagnosis from healthy controls Among DNA methylation differences detected in Study Group #2 (pre-diagnostic), we selected 11 CpG loci corresponding to 10 genes for further validation by pyrosequencing (Figures 4(B) and 5, Supplementary Figure S2). To increase the probability that the CpG loci are ubiquitously differentially methylated in pre-diagnostic blood samples of HCC cases vs. controls, we applied several criteria as described above. ...
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... the magnitude of the difference in DNA methylation was ≥0.1 with P <0.05, ICC threshold ≥0.70 [40], consistent difference within a given CpG locus across the majority of matched pairs (≥17/21 pairs), and location of the CpG locus in a gene regulatory region. Relative methylation levels (beta values) in cases (median of n = 21) and matched controls (median of n = 21) for those loci are shown in a color map in Figure 4(B). Two CpG sites were hypermethylated in cases vs. controls and corresponded to CHRDL1 and RPTOR. ...
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... remaining CpG sites, located within ACAN, ATHL1, PSG4, BRUNOL5, BARD1, FXYD6, TET1, or MAGEB3, demonstrated lower methylation levels in cases vs. controls based on the array data. All selected loci are located in regulatory gene regions including CpGI, CpGI shores and shelves, 5'UTR, or promoters (TSS1500) (Figure 4(B), gene maps in Supplementary Figure S2, left panel). The genes encompassing the selected loci are associated with a wide range of functions. ...
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... highest differences within CpG sites of interest (covered on the array, marked in squares) were detected for CpG#2 of ATHL1 (42.5% difference in median), CpG#1 of ACAN (26% difference in median), CpG#3 of CHRDL1 (17% difference in median), and CpG#4 of BARD1 (13.3% difference in median). Interestingly, ATHL1 and ACAN also show the highest differences on the microarray (Figure 4(B)). As in post-diagnostic samples, several genes do not show significant changes at a CpG covered on the array but instead have differences at neighboring CpGs. ...
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... was also found to be expressed in T-lymphoid cells [46]. 9 candidate probes indeed maintain consistent differences in DNA methylation in post-diagnostic Study Group #1 as compared with cirrhotic controls (Supplementary Figure S4(A)) and healthy controls (Figure 3, Supplementary Figure S4(B)). ...
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... was also found to be expressed in T-lymphoid cells [46]. 9 candidate probes indeed maintain consistent differences in DNA methylation in post-diagnostic Study Group #1 as compared with cirrhotic controls (Supplementary Figure S4(A)) and healthy controls (Figure 3, Supplementary Figure S4(B)). ...
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... discover more differences characteristic of pre-diagnostic stages of HCC, we mapped DNA methylation patterns in pre-diagnostic cases and matched healthy controls. Interestingly, we detected 7 times less differences in pre-diagnostic Study Group #2 than in HCC patients (Figures 2(A) and Figure 4(A)). The majority of differentially methylated CpG sites were hypomethylated in cases vs. controls (Figure 4(A)) and were located in gene regulatory regions (Figure 4(D)). ...
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... we detected 7 times less differences in pre-diagnostic Study Group #2 than in HCC patients (Figures 2(A) and Figure 4(A)). The majority of differentially methylated CpG sites were hypomethylated in cases vs. controls (Figure 4(A)) and were located in gene regulatory regions (Figure 4(D)). In both Study Groups, hypomethylated CpG sites were located in genes associated with regulation of transcription and signal transduction. ...
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... we detected 7 times less differences in pre-diagnostic Study Group #2 than in HCC patients (Figures 2(A) and Figure 4(A)). The majority of differentially methylated CpG sites were hypomethylated in cases vs. controls (Figure 4(A)) and were located in gene regulatory regions (Figure 4(D)). In both Study Groups, hypomethylated CpG sites were located in genes associated with regulation of transcription and signal transduction. ...
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... samples from a cirrhotic Study Group #3, we found that 9 of the 19 validated probes located within regulatory regions of BARD1, MAGEB3, BRUNOL5, FXYD6, TET1, TSPAN5, DPPA5, KIAA1210, and LSP1 could potentially distinguish cirrhotic patients who will develop HCC within next 2 years from those who will stay cancer free within the same period of follow up ( Figure 6). They consistently separated pre-diagnostic HCC cases with underlying liver cirrhosis from cirrhotic controls ( Figure 6) as well as post-diagnostic HCC cases in Study Group #1 from cirrhotic controls (Supplementary Figure S4(A)). Hence, the discriminative power of those probes persist when the disease progresses which ensures lack of false negative results where a patient with developed HCC could be assessed as a cancer free-control ( Figure 6). ...
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... 971 differentially methylated CpG sites were identified in pre-diagnostic HCC cases as compared with healthy controls (P <0.05, paired Wilcoxon test, ICC ≥0.5) (Figure 4(A)). Among 735 hypomethylated CpG sites, 438 sites were assigned to gene coding regions whereas 236 hypermethylated sites corresponded to 144 genes. ...
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... most robust changes with delta beta (diff.) higher than 0.30 were identified within 5ʹUTR of ACAN, CpG island of ATHL1, and CpG island shelf of RPTOR (Figure 4(B)). Figure 3. Differentially methylated regions within 5 hypomethylated probes: PCGF3, KDM2B, CTTN, TSPAN5, and SPATA13; and 7 hypermethylated probes: DPPA5, HIVEP3, JPH3, KIAA1210, LYNX1, LSP1, and SERPINB9, in hepatocellular carcinoma (HCC) cases vs. matched healthy controls. ...
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... the number of hyper-and hypo-methylated sites in post-diagnostic samples was practically equal (Figure 2(A-C)), nearly 76% of differentially methylated CpG sites in Study Group #2 (pre-diagnostic) showed lower levels of methylation in cases vs. controls (P = 2.973E-11, Wilcoxon test) (Figure 4(C)). This suggests a stronger regulatory role of hypomethylation in gene transcription in blood cells of individuals developing cancer which is consistent with previous findings [54]. ...
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... suggests a stronger regulatory role of hypomethylation in gene transcription in blood cells of individuals developing cancer which is consistent with previous findings [54]. Indeed, those hypomethylated loci are located in regulatory regions important for gene transcription such as CpG island shores, promoters, and 5'UTR (Figure 4(B,D)). The distribution of differentially methylated CpGs relative to CpG islands and TSS is similar between pre-and post-diagnostic groups (Figure 4(D)). ...
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... those hypomethylated loci are located in regulatory regions important for gene transcription such as CpG island shores, promoters, and 5'UTR (Figure 4(B,D)). The distribution of differentially methylated CpGs relative to CpG islands and TSS is similar between pre-and post-diagnostic groups (Figure 4(D)). Similarly to post-diagnostic patterns, genes hypomethylated in the Study Group #2 (prediagnostic) fall into category of multiple signaling pathways indicating a potential role for those genes in regulating functions of immune cells and subsequently the immune response at very early stages of cancer development. ...
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... in methylation expressed as median case -median control (delta beta = differential methylation) was higher than 0.1 in 20% of identified changes in Study Group #2 (pre-diagnostic) (Figure 4(A)). Level of significance for changes observed in the pre-diagnostic group was lower than at the post-diagnostic stage as indicated by Manhattan plots in Figure 4(E). ...
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... in methylation expressed as median case -median control (delta beta = differential methylation) was higher than 0.1 in 20% of identified changes in Study Group #2 (pre-diagnostic) (Figure 4(A)). Level of significance for changes observed in the pre-diagnostic group was lower than at the post-diagnostic stage as indicated by Manhattan plots in Figure 4(E). It could suggest progression of changes along with the disease development. ...
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... indeed observed numerous such examples including genes selected as candidates for validation in pyrosequencing based on the microarray data in Study Group #1 (depicted in squares in Figure 2(F) (cg26764761) show a difference of 0.008 and 0.1, respectively, at pre-diagnostic stages, which progressed to 0.28 and 0.34 in diagnosed HCC. As shown in Figure 4(F), 44 CpG sites corresponding to 27 genes are differentially methylated at both preand post-diagnostic stages of HCC (Supplementary Table S3). Interestingly, although significant, changes at those common CpGs are subtle and rather constant throughout the disease development. ...
Context 27
... methylation within ATHL1, ACAN, BRUNOL5, BARD1, MAGEB3, FXYD6, TET1, PSG4, RPTOR, and CHRDL1, as quantified by pyrosequencing distinguishes blood of HCC cases prior to diagnosis from healthy controls Among DNA methylation differences detected in Study Group #2 (pre-diagnostic), we selected 11 CpG loci corresponding to 10 genes for further validation by pyrosequencing (Figures 4(B) and 5, Supplementary Figure S2). To increase the probability that the CpG loci are ubiquitously differentially methylated in pre-diagnostic blood samples of HCC cases vs. controls, we applied several criteria as described above. ...
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... the magnitude of the difference in DNA methylation was ≥0.1 with P <0.05, ICC threshold ≥0.70 [40], consistent difference within a given CpG locus across the majority of matched pairs (≥17/21 pairs), and location of the CpG locus in a gene regulatory region. Relative methylation levels (beta values) in cases (median of n = 21) and matched controls (median of n = 21) for those loci are shown in a color map in Figure 4(B). Two CpG sites were hypermethylated in cases vs. controls and corresponded to CHRDL1 and RPTOR. ...
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... remaining CpG sites, located within ACAN, ATHL1, PSG4, BRUNOL5, BARD1, FXYD6, TET1, or MAGEB3, demonstrated lower methylation levels in cases vs. controls based on the array data. All selected loci are located in regulatory gene regions including CpGI, CpGI shores and shelves, 5'UTR, or promoters (TSS1500) (Figure 4(B), gene maps in Supplementary Figure S2, left panel). The genes encompassing the selected loci are associated with a wide range of functions. ...
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... highest differences within CpG sites of interest (covered on the array, marked in squares) were detected for CpG#2 of ATHL1 (42.5% difference in median), CpG#1 of ACAN (26% difference in median), CpG#3 of CHRDL1 (17% difference in median), and CpG#4 of BARD1 (13.3% difference in median). Interestingly, ATHL1 and ACAN also show the highest differences on the microarray (Figure 4(B)). As in post-diagnostic samples, several genes do not show significant changes at a CpG covered on the array but instead have differences at neighboring CpGs. ...
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... was also found to be expressed in T-lymphoid cells [46]. 9 candidate probes indeed maintain consistent differences in DNA methylation in post-diagnostic Study Group #1 as compared with cirrhotic controls (Supplementary Figure S4(A)) and healthy controls (Figure 3, Supplementary Figure S4(B)). ...
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... was also found to be expressed in T-lymphoid cells [46]. 9 candidate probes indeed maintain consistent differences in DNA methylation in post-diagnostic Study Group #1 as compared with cirrhotic controls (Supplementary Figure S4(A)) and healthy controls (Figure 3, Supplementary Figure S4(B)). ...
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... discover more differences characteristic of pre-diagnostic stages of HCC, we mapped DNA methylation patterns in pre-diagnostic cases and matched healthy controls. Interestingly, we detected 7 times less differences in pre-diagnostic Study Group #2 than in HCC patients (Figures 2(A) and Figure 4(A)). The majority of differentially methylated CpG sites were hypomethylated in cases vs. controls (Figure 4(A)) and were located in gene regulatory regions (Figure 4(D)). ...
Context 34
... we detected 7 times less differences in pre-diagnostic Study Group #2 than in HCC patients (Figures 2(A) and Figure 4(A)). The majority of differentially methylated CpG sites were hypomethylated in cases vs. controls (Figure 4(A)) and were located in gene regulatory regions (Figure 4(D)). In both Study Groups, hypomethylated CpG sites were located in genes associated with regulation of transcription and signal transduction. ...
Context 35
... we detected 7 times less differences in pre-diagnostic Study Group #2 than in HCC patients (Figures 2(A) and Figure 4(A)). The majority of differentially methylated CpG sites were hypomethylated in cases vs. controls (Figure 4(A)) and were located in gene regulatory regions (Figure 4(D)). In both Study Groups, hypomethylated CpG sites were located in genes associated with regulation of transcription and signal transduction. ...
Context 36
... samples from a cirrhotic Study Group #3, we found that 9 of the 19 validated probes located within regulatory regions of BARD1, MAGEB3, BRUNOL5, FXYD6, TET1, TSPAN5, DPPA5, KIAA1210, and LSP1 could potentially distinguish cirrhotic patients who will develop HCC within next 2 years from those who will stay cancer free within the same period of follow up ( Figure 6). They consistently separated pre-diagnostic HCC cases with underlying liver cirrhosis from cirrhotic controls ( Figure 6) as well as post-diagnostic HCC cases in Study Group #1 from cirrhotic controls (Supplementary Figure S4(A)). Hence, the discriminative power of those probes persist when the disease progresses which ensures lack of false negative results where a patient with developed HCC could be assessed as a cancer free-control ( Figure 6). ...
Similar publications
DNA methylation in blood may adapt to conditions affecting our health, such as inflammation, and multiple studies have identified differential DNA methylation related to smoking, obesity and various diseases. The purpose of this study was to evaluate previously reported, and explore possible new, associations between levels of inflammatory markers...
Citations
... These studies showed that epigenetics is an important aspect of human health and disease due to variability in epigenetic modification and its potential for mediating the interaction between environmental exposures and phenotypic outcomes [9,[13][14][15]. Limited epigenome-wide association studies (EWAS) using Infinium HumanMethylation450k arrays identified selected DNA methylation marks related to liver cancer, using a nested case-control study design [16,17]. However, these liver cancer-related markers have not been assessed in AI/AN populations. ...
... The goals of this study are to conduct an epigenomewide association study (EWAS) to identify differentially methylated positions (DMPs) associated with liver cancer and to validate the DMPs associated with liver cancer from previous studies [16,17]. In addition, we determined associations between circulating leukocyte subtypes and risk of liver cancer. ...
... We calculated follow-up from the date of baseline examination to the date of death or 31 December 2017, whichever occurred first. We ran Cox proportional hazards models using follow-up time as timescale to determine the hazard ratios (HRs) for each DMP identified as significant from the EWAS as well as from previous, nested case-control studies [16,17]. Our HRs and confidence intervals are standardized by one standard deviation (SD) increase in methylation (Beta value) to control for small sample size and outliers. ...
Purpose
Liver cancer incidence among American Indians/Alaska Natives has risen over the past 20 years. Peripheral blood DNA methylation may be associated with liver cancer and could be used as a biomarker for cancer risk. We evaluated the association of blood DNA methylation with risk of liver cancer.
Methods
We conducted a prospective cohort study in 2324 American Indians, between age 45 and 75 years, from Arizona, Oklahoma, North Dakota and South Dakota who participated in the Strong Heart Study between 1989 and 1991. Liver cancer deaths (n = 21) were ascertained using death certificates obtained through 2017. The mean follow-up duration (SD) for non-cases was 25.1 (5.6) years and for cases, 11.0 (8.8) years. DNA methylation was assessed from blood samples collected at baseline using MethylationEPIC BeadChip 850 K arrays. We used Cox regression models adjusted for age, sex, center, body mass index, low-density lipoprotein cholesterol, smoking, alcohol consumption, and immune cell proportions to examine the associations.
Results
We identified 9 CpG sites associated with liver cancer. cg16057201 annotated to MRFAP1) was hypermethylated among cases vs. non-cases (hazard ratio (HR) for one standard deviation increase in methylation was 1.25 (95% CI 1.14, 1.37). The other eight CpGs were hypomethylated and the corresponding HRs (95% CI) ranged from 0.58 (0.44, 0.75) for cg04967787 (annotated to PPRC1) to 0.77 (0.67, 0.88) for cg08550308. We also assessed 7 differentially methylated CpG sites associated with liver cancer in previous studies. The adjusted HR for cg15079934 (annotated to LPS1) was 1.93 (95% CI 1.10, 3.39).
Conclusions
Blood DNA methylation may be associated with liver cancer mortality and may be altered during the development of liver cancer.
... CELF5 regulates gene transcription and function through involvement in posttranscriptional modi cations, including mRNA editing and pre-mRNA alternative splicing [3] . Katarzyna et al. reported that CELF5 was a promising candidate biomarker for the detection of populations with hepatocellular carcinoma [42] . It has been reported that CELF5 could regulate the synthesis of human cytomegalovirus (HCMV) genomic DNA, which participates in tumour cell migration, invasion and apoptosis [43,44] . ...
Background
The CELF gene family is a set of highly conserved genes that encode a family of RNA-binding proteins in human tissues and participate in posttranscriptional modifications. The CELF gene family has been reported to be associated with a variety of cancers, including lung cancer, liver cancer and colorectal cancer. However, the expression, function and clinical relevance of CELF family members in glioma remain uncertain because of the lack of relevant studies.
Materials & methods
Bioinformatics analysis was used to determine the prognostic value and immune infiltration associations of CELF gene family members in glioma. Transcription and survival data related to CELF gene family members in glioma patients were obtained from the Oncomine, Gene Expression Profiling Interactive Analysis (GEPIA) and cBioPortal databases.
Results
The results revealed that compared to that in normal tissues, the expression of CELF2-6 was notably lower but that of CELF1 was higher in glioma tissues. Survival analysis using the GEPIA database revealed that high transcript levels of CELF1 were associated with unfavourable OS in all patients with LGG. Conversely, high CELF3/4/5 levels predicted favourable OS in these patients.
Conclusion
This study implied that CELF1/3/4/5 are new prognostic markers and potential therapeutic targets for LGG.
... Immune cell infiltration is known to influence the effectiveness of cancer treatments, including immunotherapy and adjuvant therapy, as well as patient outcomes [28,29]. Here, we found a positive relationship between MELK and TILs, including B cells, CD8+ T cells, CD4+ T cells, macrophages, neutrophils, and dendritic cells, in HCC. ...
Object:
Maternal embryonic leucine zipper kinase (MELK) is involved in the development and progression of various cancers. This work investigated the usefulness of MELK in the prediction of hepatocellular carcinoma (HCC) prognosis.
Methods:
Information on MELK expression was obtained by pan-cancer analysis using The Cancer Genome Atlas (TCGA) database. The TCGA-liver hepatic cancer (TCGA-LIHC), Oncomine datasets, International Cancer Genome Consortium (ICGC) datasets were used to investigate MELK expression in HCC. The prognostic roles of MELK in HCC were assessed by univariate and multivariate survival analyses. The underlying mechanism for noncoding RNAs (ncRNAs) involved in MELK expression was investigated by in silico studies, correlation, methylation, and survival analyses. The relationships between MELK expression and immune cells, immune markers, and checkpoint markers were also analyzed.
Results:
(1) MELK was identified as an independent predictor of overall survival (OS) in HCC patients (MELK high vs. low expression, HR 2.469; 95% CI 1.217-5.008; p = 0.012) in a multivariate Cox analysis, with a concordance index (C-index) value of 0.727 (95% CI 0.750-0.704). (2) The noncoding RNA miR3142HG and the LINC00265/has-miR-101-3p axis were found to regulate MELK expression in HCC tissue. (3) MELK levels were linked to various immune functions, including tumor infiltration and the expression of immune checkpoints and biomarkers in HCC.
Conclusion:
MELK may have an oncogenic function in HCC and was found to be up-regulated by ncRNAs and associated with immune cell infiltration and unfavorable prognosis.
... Aberrations in DNA methylation patterns have been linked to cancer initiation, progression, and metastasis [12,19]. Hypermethylation and silencing of tumour suppressor genes, and hypomethylation and activation of oncogenes and pro-metastatic genes, have been described in tumours from nearly all types of cancer, including HCC [12,14,[21][22][23][24]. ...
... Studies using omics approaches, including our work, re-enforced the role of epigenetics in HCC [12][13][14][21][22][23][24]36]. We established, for the first time, an epigenomic-transcriptomic signature of human HCC and a functional map of this signature [12]. ...
... We established, for the first time, an epigenomic-transcriptomic signature of human HCC and a functional map of this signature [12]. Aberrant DNA methylation within certain genes was proposed to serve as a biomarker for early HCC detection [13,24], and targeting some of the differentially methylated genes was mechanistically shown to exert anti-cancer effects [14,21,36]. Despite all the pieces of evidence for the role of epigenetics in HCC, a comprehensive investigation of the link between the dysregulated epigenome, transcriptome, and liver carcinogenesis remains to be undertaken. ...
Hepatocellular carcinoma (HCC) is mostly triggered by environmental and life-style factors and may involve epigenetic aberrations. However, a comprehensive documentation of the link between the dysregulated epigenome, transcriptome, and liver carcinogenesis is lacking. In the present study, Fischer-344 rats were fed a choline-deficient (CDAA, cancer group) or choline-sufficient (CSAA, healthy group) L-amino acid-defined diet. At the end of 52 weeks, transcriptomic alterations in livers of rats with HCC tumours and healthy livers were investigated by RNA sequencing. DNA methylation and gene expression were assessed by pyrosequencing and quantitative reverse-transcription PCR (qRT-PCR), respectively. We discovered 1,848 genes that were significantly differentially expressed in livers of rats with HCC tumours (CDAA) as compared with healthy livers (CSAA). Upregulated genes in the CDAA group were associated with cancer-related functions, whereas macronutrient metabolic processes were enriched by downregulated genes. Changes of highest magnitude were detected in numerous upregulated genes that govern key oncogenic signalling pathways, including Notch, Wnt, Hedgehog, and extracellular matrix degradation. We further detected perturbations in DNA methylating and demethylating enzymes, which was reflected in decreased global DNA methylation and increased global DNA hydroxymethylation. Four selected upregulated candidates, Mmp12, Jag1, Wnt4, and Smo, demonstrated promoter hypomethylation with the most profound decrease in Mmp12. MMP12 was also strongly overexpressed and hypomethylated in human HCC HepG2 cells as compared with primary hepatocytes, which coincided with binding of Ten-eleven translocation 1 (TET1). Our findings provide comprehensive evidence for gene expression changes and dysregulated epigenome in HCC pathogenesis, potentially revealing novel targets for HCC prevention/treatment.
... 20 Previous work has demonstrated that LSP1 suppresses hepatocellular proliferation following twothirds hepatectomy and inhibits proliferation and migration of rat cancer cell lines in vitro 21,22 Additional studies have found genomic alterations of LSP1 in breast cancer, colorectal cancer, and lung cancer, as well as its down-regulation in bladder cancer, resulting in drug resistance. 12,14,23e25 The LSP1 gene is hypermethylated in hepatocellular carcinoma samples versus cirrhotic controls, providing additional indication that LSP1 plays a role in hepatocarcinogenesis. 26 Given the previous findings of LSP1 acting as a suppressor of hepatocellular proliferation, hepatocytespecific Lsp1 transgenic mice as well as global Lsp1 knockout mice were treated with TCPOBOP. Whether LSP1 could regulate CAR-driven TCPOBOP-stimulated proliferation and hypertrophy, and/or alter CAR-regulated drug metabolism, was investigated. ...
... In view of the F-actin binding of LSP1 36 and its effects on the cytoskeleton, LSP1 is an important contributor to the mechanosensory effects of regulation of cell proliferation and function. Because LSP1 is involved in breast, 13e15 bladder, 12 and liver 10,21,22,24,26 cancers, understanding how LSP1 functions to suppress hepatocellular proliferation can provide new avenues of investigation to develop novel therapeutics. ajp.amjpathol.org ...
Activation of CAR transcription factor by xenobiotics promotes hepatocellular proliferation, hypertrophy without liver injury, and induces drug metabolism genes. Our previous work demonstrated lymphocyte specific protein-1 (LSP1), an F-actin binding protein and gene involved in human HCC, suppresses hepatocellular proliferation after partial hepatectomy. In this study, we investigated the role of LSP1 in liver enlargement induced by chemical mitogens, a regenerative process independent of tissue loss. We administered TCPOBOP, a direct CAR ligand and strong chemical mitogen, to global Lsp1 knockout (KO) and hepatocyte specific Lsp1 transgenic (TG) mice and measured cell proliferation, hypertrophy, and expression of CAR dependent drug metabolism genes. TG livers displayed a significant decrease in Ki67 labeling and liver to body weight ratios compared to WT on day 2. Surprisingly, this was reversed by day 5, due to hepatocyte hypertrophy. There was no difference in CAR regulated drug metabolism genes between WT and TG. TG livers displayed increased YAP phosphorylation, decreased nuclear YAP and direct interaction between LSP1 and YAP, suggesting LSP1 suppresses TCPOBOP driven hepatocellular proliferation, but not hepatocyte volume, through YAP. Conversely, loss of LSP1 led to increased hepatocellular proliferation on days 2, 5 and 7. LSP1 selectively suppresses CAR induced hepatocellular proliferation, but not drug metabolism, through the interaction of LSP1 with YAP, supporting the role of LSP1 as a selective growth suppressor.
... Viruses can alter the chromatin structure by redirecting the modifications of chromatin and consequently affecting host cell transcription, which may contribute to oncogenesis (54,55). Epigenetics refers to changes of gene expression without altering the underlying DNA sequence, and comprises three major components: histone modifications, DNA methylation, and noncoding RNA mechanisms (56). Hepatocellular carcinoma is caused by the somatic mutations leading to the abnormalities of chromatin regulations and epigenetic characteristics (57). ...
Hepatitis B virus (HBV) specifically infects liver cells, leading to progressive liver cirrhosis and significantly increasing the risk of hepatocellular carcinoma (HCC). The maturity of sequencing technology, improvement in bioinformatics data analysis and progress of omics technologies had improved research efficiency. The occurrence and progression of HCC are affected by multisystem and multilevel pathological changes. With the application of single-omics technologies, including genomics, transcriptomics, metabolomics and proteomics in tissue and body fluid samples, and even the novel development of multi-omics analysis on a single-cell platform, HBV-associated HCC changes can be better analyzed. The review summarizes the application of single omics and combined analysis of multi-omics data in HBV-associated HCC and proposes the importance of multi-omics analysis in the type of HCC, which provide the possibility for the precise diagnosis and therapy of HBV-associated HCC.
... The prognosis of patients with cirrhosis correlates with the epigenetic modification of TSPAN5. Lubecka et al. reported that among HBV-negative cirrhosis patients, hypomethylation of TSPAN5 gene is more frequently found in the patients who eventually develop HCC (26). Therefore, the locus-specific DNA methylation may be a useful biomarker for screening at-risk populations, and the expression TSPAN5 may be an indicator for carcinogenesis. ...
Hepatocellular carcinoma (HCC) is characterized by high prevalence, morbidity, and mortality. Liver cancer is the sixth most common cancer worldwide; and its subtype, HCC, accounts for nearly 80% of cases. HCC progresses rapidly, and to date, there is no efficacious treatment for advanced HCC. Tetraspanins belong to a protein family characterized by four transmembrane domains. Thirty-three known tetraspanins are widely expressed on the surface of most nucleated cells and play important roles in different biological processes. In our review, we summarize the functions of tetraspanins and their underlying mechanism in the life cycle of HCC, from its initiation, progression, and finally to treatment. CD9, TSPAN15, and TSPAN31 can promote HCC cell proliferation or suppress apoptosis. CD63, CD151, and TSPAN8 can also facilitate HCC metastasis, while CD82 serves as a suppressor of metastasis. TSPAN1, TSPAN8, and CD151 act as prognosis indicators and are inversely correlated to the overall survival rate of HCC patients. In addition, we discuss the potential of role of the tetraspanin family proteins as novel therapeutic targets and as an approach to overcome drug resistance, and also provide suggestions for further research.
... The determined sites include locus specific hypomethylated with higher frequency than the hypermethylated sites. The locus specific hypomethylated sites are present at the CpG islands and CpG island shores located within the 5 ′ UTR regions and promoter sites [19]. As demonstrated, the dysregulated epigenetic regulators are associated with the interruption in the epigenome. ...
... Furthermore, these variedly expressed loci actively participate in pathways and are related to immune functions like lymphocyte migration. Lubecka et al. [19] for the first time detected differential DNA methylation at the specific gene loci from the blood samples of an individual diagnosed with HCC. Additionally, from their pre-diagnostic study, they also showed hypomethylated genes including CSF2, IFITM5 and IL9 to be implicated in immunomodulation. ...
Hepatocellular carcinoma (HCC) is the most common primary malignancy of the liver and has a high fatality rate. Genetic and epigenetic aberrations are commonly observed in HCC. The epigenetic processes include chromatin remodelling, histone alterations, DNA methylation, and noncoding RNA (ncRNA) expression and are connected with the progression and metastasis of HCC. Due to their potential reversibility, these epigenetic alterations are widely targeted for the development of biomarkers. In-depth understanding of the epigenetics of HCC is critical for developing rational clinical strategies that can provide a meaningful improvement in overall survival and prediction of therapeutic outcomes. In this article, we have summarised the epigenetic modifications involved in HCC progression and highlighted the potential biomarkers for diagnosis and drug development.
... 76 Epigenetic regulation of both ZBTB47 and HIVEP3 is known to be associated with cancer. 77,78 Because our sample size in combination with a stringent correction for repeated sampling limits the power to detect subtle differences, we do expect to find a fraction of the number of differentially methylated CpGs. 79 All of the three gene-related differentially methylated CpG sites were found in the gene body region, in both intron (IGF2BP1) and exons (ZBTB47 and HIVEP3). ...
Pollutants, such as toxic metals, negatively influence organismal health and performance, even leading to population collapses. Studies in model organisms have shown that epigenetic marks, such as DNA methylation, can be modulated by various environmental factors, including pollutants, influencing gene expression, and various organismal traits. Yet experimental data on the effects of pollution on DNA methylation from wild animal populations are largely lacking. We here experimentally investigated for the first time the effects of early-life exposure to environmentally relevant levels of a key pollutant, arsenic (As), on genome-wide DNA methylation in a wild bird population. We experimentally exposed nestlings of great tits (Parus major) to arsenic during their postnatal developmental period (3 to 14 days post-hatching) and compared their erythrocyte DNA methylation levels to those of respective controls. In contrast to predictions, we found no overall hypomethylation in the arsenic group. We found evidence for loci to be differentially methylated between the treatment groups, but for five CpG sites only. Three of the sites were located in gene bodies of zinc finger and BTB domain containing 47 (ZBTB47), HIVEP zinc finger 3 (HIVEP3), and insulin-like growth factor 2 mRNA binding protein 1 (IGF2BP1). Further studies are needed to evaluate whether epigenetic dysregulation is a commonly observed phenomenon in polluted populations and what are the consequences for organism functioning and for population dynamics.
... 85% of hepatocellular carcinoma (HCC) cases are preceded by cirrhosis [110], and the high worldwide incidence is largely attributed to viral infection (hepatitis B and C, or HBV and HCV) or fatty liver (alcoholic and non-alcoholic) [98,110]. Therefore, detecting early changes is important as surveillance for the development of liver cancer in cirrhotic patients. ...
... 85% of hepatocellular carcinoma (HCC) cases are preceded by cirrhosis [110], and the high worldwide incidence is largely attributed to viral infection (hepatitis B and C, or HBV and HCV) or fatty liver (alcoholic and non-alcoholic) [98,110]. Therefore, detecting early changes is important as surveillance for the development of liver cancer in cirrhotic patients. ...
... Therefore, detecting early changes is important as surveillance for the development of liver cancer in cirrhotic patients. Lubecka et al. examined DNA methylation in white blood cells (WBCs) of HBV-negative populations and detected pre-diagnostic epigenetic changes that could be utilized for identification of those at risk for the development of HCC [110]. Patients with pre-diagnosed HCC had significant hypomethylation of the BARD1 gene compared to healthy patients as measured by a 13.3% difference between the groups. ...
Breast Cancer 1 (BRCA1) gene is a well-characterized tumor suppressor gene, mutations of which are primarily found in women with breast and ovarian cancers. BRCA1-associated RING domain 1 (BARD1) gene has also been identified as an important tumor suppressor gene in breast, ovarian, and uterine cancers. Underscoring the functional significance of the BRCA1 and BARD1 interactions, prevalent mutations in the BRCA1 gene are found in its RING domain, through which it binds the RING domain of BARD1. BARD1-BRCA1 heterodimer plays a crucial role in a variety of DNA damage response (DDR) pathways, including DNA damage checkpoint and homologous recombination (HR). However, many mutations in both BARD1 and BRCA1 also exist in other domains that significantly affect their biological functions. Intriguingly, recent genome-wide studies have identified various single nucleotide polymorphisms (SNPs), genetic alterations, and epigenetic modifications in or near the BARD1 gene that manifested profound effects on tumorigenesis in a variety of non-breast and non-gynecological cancers. In this review, we will briefly discuss the molecular functions of BARD1, including its BRCA1-dependent as well as BRCA1-independent functions. We will then focus on evaluating the common BARD1 related SNPs as well as genetic and epigenetic changes that occur in the non-BRCA1-dominant cancers, including neuroblastoma, lung, and gastrointestinal cancers. Furthermore, the pro- and anti-tumorigenic functions of different SNPs and BARD1 variants will also be discussed.
