Stage-differentiated modelling of DNA methylation landscapes uncovers salient biomarkers and prognostic signatures in colorectal cancer progression

2021 ◽  
Author(s):  
Sangeetha Muthamilselvan ◽  
Abirami Raghavendran ◽  
Ashok Palaniappan
Keyword(s):  
Colorectal Cancer ◽  
Dna Methylation ◽  
Cpg Island ◽  
Early Stage ◽  
P Value ◽  
Consensus Analysis ◽  
One Stage ◽  
Differentially Methylated Genes ◽  
Methylation Patterns ◽  
The Impact

Abstract Background: Aberrant DNA methylation acts epigenetically to skew the gene transcription rate up or down, with causative roles in the etiology of cancers. However research on the role of DNA methylation in driving the progression of cancers is limited. In this study, we have developed a comprehensive computational framework for the stage-differentiated modelling of DNA methylation landscapes in colorectal cancer (CRC), and unravelled significant stagewise signposts of CRC progression. Methods: The methylation β - matrix was derived from the public-domain TCGA data, converted into M-value matrix, annotated with AJCC stages, and analysed for stage-salient genes using multiple approaches involving stage-differentiated linear modelling of methylation patterns and/or expression patterns. Differentially methylated genes (DMGs) were identified using a contrast against controls (adjusted p-value <0.001 and |log fold-change of M-value| >2). These results were filtered using a series of all possible pairwise stage contrasts (p-value <0.05) to obtain stage-salient DMGs. These were then subjected to a consensus analysis, followed by Kaplan–Meier survival analysis to evaluate the impact of methylation patterns of consensus stage-salient biomarkers on disease prognosis.Results: We found significant genome-wide changes in methylation patterns in cancer cases relative to controls agnostic of stage. Our stage-differentiated analysis yielded the following stage-salient genes: one stage-I gene (FBN1), one stage-II gene (FOXG1), one stage-III gene (HCN1) and four stage-IV genes (NELL1, ZNF135, FAM123A, LAMA1). All the biomarkers were hypermethylated, indicating down-regulation and signifying a CpG island Methylator Phenotype (CIMP) manifestation. A significant prognostic signature consisting of FBN1 and FOXG1 survived all the steps of our analysis pipeline, and represents a novel early-stage biomarker. Conclusions: We have designed a workflow for stage-differentiated consensus analysis, and identified stage-salient diagnostic biomarkers and an early-stage prognostic biomarker panel. Our studies further yield a novel CIMP-like signature of potential clinical import underlying CRC progression.

scholarly journals Stage-differentiated modelling of DNA methylation landscapes uncovers salient biomarkers and prognostic signatures in colorectal cancer progression

2020 ◽  
Author(s):  
Sangeetha Muthamilselvan ◽  
Abirami Raghavendran ◽  
Ashok Palaniappan
Keyword(s):  
Colorectal Cancer ◽  
Dna Methylation ◽  
Early Stage ◽  
P Value ◽  
Aberrant Methylation ◽  
Consensus Analysis ◽  
Biomarker Panel ◽  
One Stage ◽  
Differentially Methylated Genes ◽  
Methylation Patterns

ABSTRACTBackgroundAberrant methylation of DNA acts epigenetically to skew the gene transcription rate up or down. In this study, we have developed a comprehensive computational framework for the stage-differentiated modelling of DNA methylation landscapes in colorectal cancer. Methods: The methylation β - matrix was derived from the public-domain TCGA data, converted into M-value matrix, annotated with sample stages, and analysed for stage-salient genes using multiple approaches involving stage-differentiated linear modelling of methylation patterns and/or expression patterns. Differentially methylated genes (DMGs) were identified using a contrast against control samples (adjusted p-value <0.001 and |log fold-change of M-value| >2). These results were filtered using a series of all possible pairwise stage contrasts (p-value <0.05) to obtain stage-salient DMGs. These were then subjected to a consensus analysis, followed by Kaplan–Meier survival analysis to explore the relationship between methylation and prognosis for the consensus stage-salient biomarkers.ResultsWe found significant genome-wide changes in methylation patterns in cancer samples relative to controls agnostic of stage. Our stage-differentiated analysis yielded the following stage-salient genes: one stage-I gene (FBN1), one stage-II gene (FOXG1), one stage-III gene (HCN1) and four stage-IV genes (NELL1, ZNF135, FAM123A, LAMA1). All the biomarkers were hypermethylated, indicating down-regulation and signifying a CpG island Methylator Phenotype (CIMP) manifestation. A prognostic signature consisting of FBN1 and FOXG1was significantly associated with patient survival (p-value < 0.01) and could be used as a biomarker panel for early-stage CRC prognosis.ConclusionOur workflow for stage-differentiated consensus analysis has yielded stage-salient diagnostic biomarkers as well as an early-stage prognostic biomarker panel. In addition, our studies have affirmed a novel CIMP-like signature in colorectal cancer, urging clinical validation.

scholarly journals Blood Cell DNA Methylation of Aging-Related Ubiquitination Gene DZIP3 Can Predict the Onset of Early Stage Colorectal Cancer

2020 ◽  
Vol 10 ◽  
Author(s):  
Yuan Quan ◽  
Fengji Liang ◽  
Deqing Wu ◽  
Xueqing Yao ◽  
Zhihuang Hu ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Dna Methylation ◽  
Immune System ◽  
T Cell ◽  
Immune Cell ◽  
Early Stage ◽  
Cd4 T Cell ◽  
P Value ◽  
Regulation Changes ◽  
Cell Proportion

There is a body of evidence that the aging immune system is linked to cancer. In this study, with aging- and immune-related DNA methylation data, we investigated the DNA methylation regulation changes in promoters with other regions of genes during aging and their association with the immune-cell proportion in the circulating whole blood of individuals. The analyses for aging- and CD4+ T cell proportion-derived differential genes showed that ubiquitination plays an important role in the aging immune system and tumorigenesis. Therefore, starting from a set of pre-annotated ubiquitination genes, we found that among the differentially ubiquitinated genes, DZIP3, an E3 ubiquitin ligase with no reports on its function in immune cells and tumorigenesis, was significantly associated with both aging (P-value = 3.86e-06) and CD4+ T cell proportion (P-value = 1.97e-05) in circulating blood. By collecting a cohort of 100 colon cancer patients and 50 healthy individuals, we validated that the 1st exon DNA methylation of DZIP3 could predict the onset of early stage (AUC = 0.833, OR = 8.82) and all pTNM stages of colorectal cancer (AUC = 0.782, OR = 5.70). Thus, the epigenetically regulated ubiquitination machine plays an important role in immune aging and tumorigenesis.

scholarly journals A Serum Metabolomics Classifier Derived from Elderly Patients with Metastatic Colorectal Cancer Predicts Relapse in the Adjuvant Setting

Cancers ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 2762
Author(s):  
Samantha Di Donato ◽  
Alessia Vignoli ◽  
Chiara Biagioni ◽  
Luca Malorni ◽  
Elena Mori ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Risk Stratification ◽  
Elderly Patients ◽  
Metastatic Colorectal Cancer ◽  
Early Stage ◽  
Prospective Trial ◽  
Proton Nuclear Magnetic Resonance ◽  
P Value ◽  
Resonance Spectroscopy ◽  
Metabolomic Fingerprinting

Adjuvant treatment for patients with early stage colorectal cancer (eCRC) is currently based on suboptimal risk stratification, especially for elderly patients. Metabolomics may improve the identification of patients with residual micrometastases after surgery. In this retrospective study, we hypothesized that metabolomic fingerprinting could improve risk stratification in patients with eCRC. Serum samples obtained after surgery from 94 elderly patients with eCRC (65 relapse free and 29 relapsed, after 5-years median follow up), and from 75 elderly patients with metastatic colorectal cancer (mCRC) obtained before a new line of chemotherapy, were retrospectively analyzed via proton nuclear magnetic resonance spectroscopy. The prognostic role of metabolomics in patients with eCRC was assessed using Kaplan–Meier curves. PCA-CA-kNN could discriminate the metabolomic fingerprint of patients with relapse-free eCRC and mCRC (70.0% accuracy using NOESY spectra). This model was used to classify the samples of patients with relapsed eCRC: 69% of eCRC patients with relapse were predicted as metastatic. The metabolomic classification was strongly associated with prognosis (p-value 0.0005, HR 3.64), independently of tumor stage. In conclusion, metabolomics could be an innovative tool to refine risk stratification in elderly patients with eCRC. Based on these results, a prospective trial aimed at improving risk stratification by metabolomic fingerprinting (LIBIMET) is ongoing.

scholarly journals Clinicopathological features of Egyptian colorectal cancer patients regarding somatic genetic mutations especially in KRAS gene and microsatellite instability status: a pilot study

2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Neemat M. Kassem ◽  
Gamal Emera ◽  
Hebatallah A. Kassem ◽  
Nashwa Medhat ◽  
Basant Nagdy ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Microsatellite Instability ◽  
Cpg Island ◽  
Human Cancer ◽  
Statistical Significance ◽  
Public Health Problem ◽  
World Health ◽  
Cpg Island Methylator Phenotype ◽  
Number Of Patients ◽  
The Impact

Abstract Background Colorectal cancer (CRC) is the third most common cause of cancer-related deaths which contributes to a significant public health problem worldwide with 1.8 million new cases and almost 861,000 deaths in 2018 according to the World Health Organization. It exhibits 7.4% of all diagnosed cancer cases in the region of the Middle East and North Africa. Molecular changes that happen in CRCs are chromosomal instability, microsatellite instability (MSI), and CpG island methylator phenotype. The human RAS family (KRAS, NRAS, and HRAS) is the most frequently mutated oncogenes in human cancer appearing in 45% of colon cancers. Determining MSI status across CRCs offers the opportunity to identify patients who are likely to respond to targeted therapies such as anti-PD-1. Therefore, a method to efficiently determine MSI status for every cancer patient is needed. Results KRAS mutations were detected in 31.6% of CRC patients, namely in older patients (p = 0.003). Codons 12 and 13 constituted 5/6 (83.3%) and 1/6 (16.7%) of all KRAS mutations, respectively. We found three mutations G12D, G12C, and G13D which occur as a result of substitution at c.35G>A, c.34G>T, and c.38G>A and have been detected in 4/6 (66.6%), 1/6 (16.7%), and 1/6 (16.7%) patients, respectively. Eleven (57.9%) patients had microsatellite instability-high (MSI-H) CRC. A higher percentage of MSI-H CRC was detected in female patients (p = 0.048). Eight patients had both MSI-H CRC and wild KRAS mutation with no statistical significance was found between MSI status and KRAS mutation in these studied patients. Conclusion In conclusion, considering that KRAS mutations confer resistance to EGFR inhibitors, patients who have CRC with KRAS mutation could receive more tailored management by defining MSI status. MSI-high patients have enhanced responsiveness to anti-PD-1 therapies. Thus, the question arises as to whether it is worth investigating this association in the routine clinical setting or not. Further studies with a larger number of patients are needed to assess the impact of MSI status on Egyptian CRC care.

scholarly journals Exploring Differentially Methylated Genes in Vulvar Squamous Cell Carcinoma

Cancers ◽  
2021 ◽  
Vol 13 (14) ◽  
pp. 3580
Author(s):  
Shatavisha Dasgupta ◽  
Patricia C. Ewing-Graham ◽  
Sigrid M. A. Swagemakers ◽  
Thierry P. P. van den Bosch ◽  
Peggy N. Atmodimedjo ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Dna Sequences ◽  
Cpg Island ◽  
Epigenetic Modification ◽  
Vulvar Squamous Cell Carcinoma ◽  
Differentially Methylated Genes ◽  
Methylation Profiling

DNA methylation is the most widely studied mechanism of epigenetic modification, which can influence gene expression without alterations in DNA sequences. Aberrations in DNA methylation are known to play a role in carcinogenesis, and methylation profiling has enabled the identification of biomarkers of potential clinical interest for several cancers. For vulvar squamous cell carcinoma (VSCC), however, methylation profiling remains an under-studied area. We sought to identify differentially methylated genes (DMGs) in VSCC, by performing Infinium MethylationEPIC BeadChip (Illumina) array sequencing, on a set of primary VSCC (n = 18), and normal vulvar tissue from women with no history of vulvar (pre)malignancies (n = 6). Using a false-discovery rate of 0.05, beta-difference (Δβ) of ± 0.5, and CpG-island probes as cut-offs, 199 DMGs (195 hyper-methylated, 4 hypo-methylated) were identified for VSCC. Most of the hyper-methylated genes were found to be involved in transcription regulator activity, indicating that disruption of this process plays a vital role in VSCC development. The majority of VSCCs harbored amplifications of chromosomes 3, 8, and 9. We identified a set of DMGs in this exploratory, hypothesis-generating study, which we hope will facilitate epigenetic profiling of VSCCs. Prognostic relevance of these DMGs deserves further exploration in larger cohorts of VSCC and its precursor lesions.

scholarly journals Correlation of Body Mass Index with Oncologic Outcomes in Colorectal Cancer Patients: A Large Population-Based Study

Cancers ◽  
2021 ◽  
Vol 13 (14) ◽  
pp. 3592
Author(s):  
Chong-Chi Chiu ◽  
Chung-Han Ho ◽  
Chao-Ming Hung ◽  
Chien-Ming Chao ◽  
Chih-Cheng Lai ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Body Mass Index ◽  
Body Weight ◽  
Body Mass ◽  
Survival Rates ◽  
Normal Weight ◽  
P Value ◽  
Administrative Claims ◽  
The Impact

It has been acknowledged that excess body weight increases the risk of colorectal cancer (CRC); however, there is little evidence on the impact of body mass index (BMI) on CRC patients’ long-term oncologic results in Asian populations. We studied the influence of BMI on overall survival (OS), disease-free survival (DFS), and CRC-specific survival rates in CRC patients from the administrative claims datasets of Taiwan using the Kaplan–Meier survival curves and the log-rank test to estimate the statistical differences among BMI groups. Underweight patients (<18.50 kg/m2) presented higher mortality (56.40%) and recurrence (5.34%) rates. Besides this, they had worse OS (aHR:1.61; 95% CI: 1.53–1.70; p-value: < 0.0001) and CRC-specific survival (aHR:1.52; 95% CI: 1.43–1.62; p-value: < 0.0001) rates compared with those of normal weight patients (18.50–24.99 kg/m2). On the contrary, CRC patients belonging to the overweight (25.00–29.99 kg/m2), class I obesity (30.00–34.99 kg/m2), and class II obesity (≥35.00 kg/m2) categories had better OS, DFS, and CRC-specific survival rates in the analysis than the patients in the normal weight category. Overweight patients consistently had the lowest mortality rate after a CRC diagnosis. The associations with being underweight may reflect a reverse causation. CRC patients should maintain a long-term healthy body weight.

scholarly journals Aberrant septin 9 DNA methylation in colorectal cancer is restricted to a single CpG island

BMC Cancer ◽  
2013 ◽  
Vol 13 (1) ◽  
Author(s):  
Reinhold Wasserkort ◽  
Alexandra Kalmar ◽  
Gabor Valcz ◽  
Sandor Spisak ◽  
Manuel Krispin ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Dna Methylation ◽  
Cpg Island ◽  
Septin 9

scholarly journals Atlas of Age- and Tissue-specific DNA Methylation during Early Development of Barley (Hordeum vulgare)

2018 ◽  
Author(s):  
Moumouni Konate ◽  
Michael J. Wilkinson ◽  
Banjamin Mayne ◽  
Eileen Scott ◽  
Bettina Berger ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Hordeum Vulgare ◽  
Organ Function ◽  
Tissue Specific ◽  
Organ Differentiation ◽  
Differentiated Cells ◽  
Differentially Methylated Genes ◽  
Organ Specific ◽  
Development And Differentiation ◽  
Methylation Patterns

The barley (Hordeum vulgare) genome comprises over 32,000 genes, with differentiated cells expressing only a subset of genes; the remainder being silent. Mechanisms by which tissue-specific genes are regulated are not entirely understood, although DNA methylation is likely to be involved. DNA methylation patterns are not static during plant development, but it is still unclear whether different organs possess distinct methylation profiles. Methylation-sensitive GBS was used to generate DNA methylation profiles for roots, leaf-blades and leaf-sheaths from five barley varieties, using seedlings at the three-leaf stage. Differentially Methylated Markers (DMMs) were characterised by pairwise comparisons of roots, leaf-blades and leaf-sheaths of three different ages. While very many DMMs were found between roots and leaf parts, only a few existed between leaf-blades and leaf-sheaths, with differences decreasing with leaf rank. Organ-specific DMMs appeared to target mainly repeat regions, implying that organ differentiation partially relies on the spreading of DNA methylation from repeats to promoters of adjacent genes. Furthermore, the biological functions of differentially methylated genes in the different organs correlated with functional specialisation. Our results indicate that different organs do possess diagnostic methylation profiles and suggest that DNA methylation is important for both tissue development and differentiation and organ function.

A panel of DNA methylation markers for the classification of consensus molecular subtypes 2 and 3 in patients with colorectal cancer.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. 3545-3545
Author(s):  
Inge van Den Berg ◽  
Marcel Smid ◽  
Robert R.J. Coebergh van den Braak ◽  
Mark A van de Wiel ◽  
Carolien H. M. Van Deurzen ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Dna Methylation ◽  
Prediction Models ◽  
Molecular Subtypes ◽  
Cpg Island ◽  
Methylation Marker ◽  
Marker Selection ◽  
Fresh Frozen ◽  
Classification Tool

3545 Background: Consensus molecular subtypes (CMSs) can guide precision treatment of colorectal cancer (CRC). Currently available assays can identify CMS1 and CMS4 cases well, while a dedicated test to distinguish CMS2 and 3 is lacking. This study aimed to identify a panel of methylation markers to distinguish between CMS2 and 3 in patients with CRC. Methods: Fresh-frozen tumor tissue of 239 patients with stage I-III CRC was included. CMS classification was performed on RNA-seq data using the single-sample-prediction parameter from the “CMSclassifier” package. Methylation profiles were obtained using the Infinium HumanMethylation450 BeadChip. We performed adaptive group-regularised logistic ridge-regression with post-hoc group-weighted elastic net marker selection to build prediction models for classification of CMS2 and CMS3 based on 15, 10 or 5 markers. Data from TCGAwas used for validation. Results: Overall methylation profiles differed between CMS2 and CMS3. Group-regularisation of the probes was done based on their location either relative to a CpG island or relative to a gene present in the CMS classifier resulting in two different prediction models and subsequently different marker panels. For both panels, even when using only 5 markers, sensitivity, specificity, and accuracy were > 90%. Validation showed comparable performances. Conclusions: Our highly sensitive and specific methylation marker panel can be used to distinguish CMS2 and 3. This enables development of a qPCR DNA methylation assay in patients with CRC to provide a specific and non-invasive classification tool.

scholarly journals Diet quality associated peripheral blood DNA methylation signatures

2020 ◽  
Vol 79 (OCE2) ◽  
Author(s):  
Jiantao Ma ◽  
Casey Rebholz ◽  
Kim Braun ◽  
Lindsay Reynolds ◽  
Stella Aslibekyan ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Diet Quality ◽  
Peripheral Blood ◽  
Molecular Mechanisms ◽  
Healthy Eating Index ◽  
European Ancestry ◽  
P Value ◽  
Primary Analysis ◽  
Habitual Diet ◽  
Methylation Patterns

AbstractLeukocyte DNA methylation patterns associated with habitual diet may reveal molecular mechanisms involved in the pathogenesis of diet-related chronic diseases and highlight targets for prevention and treatment. We aimed to examine peripheral blood derived leukocyte DNA methylation signatures associated with diet quality. We meta-analyzed epigenome-wide associations between diet quality and DNA methylation levels at over 400,000 cytosine-guanine dinucleotides (CpGs). We conducted analysis primarily in 6,662 European ancestry (EA) participants and secondarily in a group additionally including 3,062 participants of non-European ancestry from five population-based cohort studies. DNA methylation profiles were measured in whole blood, CD4 + T-cells, or CD14 + monocytes. We used food frequency questionnaires to assess habitual intake and constructed two diet quality scores: the Mediterranean-style diet score (MDS) and Alternative Healthy Eating Index (AHEI). Our primary analysis identified 32 diet-associated CpGs, 12 CpGs for MDS and 24 CpGs for AHEI (at FDR < 0.05, corresponding p-values = 1.2×10-6 and 3.1×10-6, respectively) in EA participants. Four of these CpGs were associated with both MDS and AHEI. In addition, Mendelian randomization analysis indicated that seven diet-associated CpGs were causally linked to at least one of the CVD risk factors. For example, hypermethylation of cg11250194 (FADS2), which was associated with higher diet quality scores, was also associated with lower fasting triglycerides concentrations (p-value = 1.5×10-14) and higher high-density lipoprotein cholesterol concentrations (p-value = 1.7×10-8). Transethnic meta-analysis identified nine additional CpGs associated with diet quality (either MDS or AHEI) at FDR < 0.05. Overall quality of habitual diet was associated with differential peripheral leukocyte DNA methylation levels of 32 CpGs in EA participants. The diet-associated CpGs may serve as biomarkers and targets for preventive measures in CVD health. Future studies are warranted to examine diet-associated DNA methylation patterns in larger, ethnically diverse study samples.

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