scholarly journals MethylResolver—a method for deconvoluting bulk DNA methylation profiles into known and unknown cell contents

2020 ◽  
Vol 3 (1) ◽  
Author(s):  
Douglas Arneson ◽  
Xia Yang ◽  
Kai Wang
Keyword(s):  
Dna Methylation ◽  
Immune Cell ◽  
Papillary Renal Cell Carcinoma ◽  
Least Trimmed Squares ◽  
Poor Survival ◽  
Cellular Content ◽  
Result Interpretation ◽  
Bulk Tissue ◽  
Pan Cancer ◽  
Methylation Profiling

AbstractBulk tissue DNA methylation profiling has been used to examine epigenetic mechanisms and biomarkers of complex diseases such as cancer. However, heterogeneity of cellular content in tissues complicates result interpretation and utility. In silico deconvolution of cellular fractions from bulk tissue data offers a fast and inexpensive alternative to experimentally measuring such fractions. In this study, we report the design, implementation, and benchmarking of MethylResolver, a Least Trimmed Squares regression-based method for inferring leukocyte subset fractions from methylation profiles of tumor admixtures. Compared to previous approaches MethylResolver is more accurate as unknown cellular content in the mixture increases and is able to resolve tumor purity-scaled immune cell-type fractions without a cancer-specific signature. We also present a pan-cancer deconvolution of TCGA, recapitulating that high eosinophil fraction predicts improved cervical carcinoma survival and identifying elevated B cell fraction as a previously unreported predictor of poor survival for papillary renal cell carcinoma.

scholarly journals Systematic Pan-Cancer Analysis Identifies TREM2 as an Immunological and Prognostic Biomarker

2021 ◽  
Vol 12 ◽  
Author(s):  
Xin Cheng ◽  
Xiaowei Wang ◽  
Kechao Nie ◽  
Lin Cheng ◽  
Zheyu Zhang ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Immune Cell ◽  
Lung Squamous Cell Carcinoma ◽  
The Cancer Genome Atlas ◽  
Immunoglobulin Superfamily ◽  
Cancer Types ◽  
Pan Cancer

Triggering receptor expressed on myeloid cells-2 (TREM2) is a transmembrane receptor of the immunoglobulin superfamily and a crucial signaling hub for multiple pathological pathways that mediate immunity. Although increasing evidence supports a vital role for TREM2 in tumorigenesis of some cancers, no systematic pan-cancer analysis of TREM2 is available. Thus, we aimed to explore the prognostic value, and investigate the potential immunological functions, of TREM2 across 33 cancer types. Based on datasets from The Cancer Genome Atlas, and the Cancer Cell Line Encyclopedia, Genotype Tissue-Expression, cBioPortal, and Human Protein Atlas, we employed an array of bioinformatics methods to explore the potential oncogenic roles of TREM2, including analyzing the relationship between TREM2 and prognosis, tumor mutational burden (TMB), microsatellite instability (MSI), DNA methylation, and immune cell infiltration of different tumors. The results show that TREM2 is highly expressed in most cancers, but present at low levels in lung cancer. Further, TREM2 is positively or negatively associated with prognosis in different cancers. Additionally, TREM2 expression was associated with TMB and MSI in 12 cancer types, while in 20 types of cancer, there was a correlation between TREM2 expression and DNA methylation. Six tumors, including breast invasive carcinoma, cervical squamous cell carcinoma and endocervical adenocarcinoma, kidney renal clear cell carcinoma, lung squamous cell carcinoma, skin cutaneous melanoma, and stomach adenocarcinoma, were screened out for further study, which demonstrated that TREM2 gene expression was negatively correlated with infiltration levels of most immune cells, but positively correlated with infiltration levels of M1 and M2 macrophages. Moreover, correlation with TREM2 expression differed according to T cell subtype. Our study reveals that TREM2 can function as a prognostic marker in various malignant tumors because of its role in tumorigenesis and tumor immunity.

587 DNA Methylation Profiling Identifies Luminal a Breast Tumors With Poor Survival

2012 ◽  
Vol 48 ◽  
pp. S140
Author(s):  
T. Fleischer ◽  
J. Jovanovic ◽  
H. Edvardsen ◽  
G.I.G. Alns ◽  
B. Naume ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Breast Tumors ◽  
Poor Survival ◽  
Luminal A ◽  
Dna Methylation Profiling ◽  
Methylation Profiling

scholarly journals MPscore: A Novel Predictive and Prognostic Scoring for Progressive Meningioma

Cancers ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 1113
Author(s):  
Feili Liu ◽  
Jin Qian ◽  
Chenkai Ma
Keyword(s):  
Dna Methylation ◽  
Immune Cell ◽  
Predictive Accuracy ◽  
Recurrence Risk ◽  
Who Grade ◽  
Signature Genes ◽  
Atypical Meningiomas ◽  
Monocytic Lineage ◽  
Subtype 3 ◽  
Methylation Profiling

Meningioma is the most common tumor in central nervous system (CNS). Although most cases of meningioma are benign (WHO grade I) and curable by surgical resection, a few tumors remain diagnostically and therapeutically challenging due to the frequent recurrence and progression. The heterogeneity of meningioma revealed by DNA methylation profiling suggests the demand of subtyping for meningioma. Therefore, we performed a clustering analyses to characterize the progressive features of meningioma and constructed a meningioma progression score to predict the risk of the recurrence. A total of 179 meningioma transcriptome from RNA sequencing was included for progression subtype clustering. Four biologically distinct subtypes (subtype 1, subtype 2, subtype 3 and subtype 4) were identified. Copy number alternation and genomewide DNA methylation of each subtype was also characterized. Immune cell infiltration was examined by the microenvironment cell populations counter. All anaplastic meningiomas (7/7) and most atypical meningiomas (24/32) are enriched in subtype 3 while no WHO II or III meningioma presents in subtype 1, suggesting subtype 3 meningioma is a progressive subtype. Stemness index and immune response are also heterogeneous across four subtypes. Monocytic lineage is the most immune cell type in all meningiomas, except for subtype 1. CD8 positive T cells are predominantly observed in subtype 3. To extend the clinical utility of progressive meningioma subtyping, we constructed the meningioma progression score (MPscore) by the signature genes in subtype 3. The predictive accuracy and prognostic capacity of MPscore has also been validated in three independent cohort. Our study uncovers four biologically distinct subtypes in meningioma and the MPscore is potentially helpful in the recurrence risk prediction and response to treatments stratification in meningioma.

scholarly journals KIF18B is a Prognostic Biomarker and Correlates with Immune Infiltrates in Pan-Cancer

2021 ◽  
Vol 8 ◽  
Author(s):  
Meng-jun Qiu ◽  
Qiu-shuang Wang ◽  
Qiu-ting Li ◽  
Li-sheng Zhu ◽  
Ya-nan Li ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Immune Cell ◽  
Prognostic Biomarker ◽  
Tumor Mutation Burden ◽  
R Language ◽  
Normal Tissues ◽  
Expression Difference ◽  
Mutation Burden ◽  
Cancer Types ◽  
Pan Cancer

Background: Cancer is one of the deadliest diseases at present. Although effective screening and treatment can save lives to a certain extent, our knowledge of the disease is far from sufficient. KIF18B is a member of the kinesin-8 superfamily and plays a conserved regulatory role in the cell cycle. KIF18B reportedly functions as an oncogene in some human cancers, but the correlations between KIF18B and prognosis and immune-infiltrates in different cancers remain unclear.Methods: Data were collected from the TCGA, GTEx, CCLE, TIMER, and GSEA databases. The expression difference, survival, pathological stage, DNA methylation, tumor mutation burden (TMB), microsatellite instability (MSI), mismatch repairs (MMRs), tumor microenvironment (TME), immune cell infiltration, and gene co-expression of KIF18B were analyzed using the R language software.Results: KIF18B was widely upregulated in cancers, compared with normal tissues, and high KIF18B expression was associated with unfavorable prognoses. TMB, MSI, MMRs, and DNA methylation correlated with KIF18B dysregulation in cancers. KIF18B correlated closely with tumor immunity and interacted with different immune cells and genes in different cancer types.Conclusion: KIF18B could be used as a prognostic biomarker for determining prognosis and immune infiltration in pan-cancer.

scholarly journals Meningioma epigenetic grouping reveals biologic drivers and therapeutic vulnerabilities

2020 ◽  
Author(s):  
David Raleigh ◽  
Stephen Magill ◽  
Charlotte Eaton ◽  
Briana Prager ◽  
William Chen ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Dna Methylation ◽  
Central Nervous System ◽  
Nervous System ◽  
Immune Cell ◽  
Lymphatic Vessels ◽  
Intermediate Outcomes ◽  
Dna Methylation Profiling ◽  
New Treatments ◽  
Methylation Profiling

Abstract Meningiomas arising from the meningothelial central nervous system lining are the most common primary intracranial tumors, and a significant cause of neurologic morbidity and mortality1. There are no effective medical therapies for meningioma patients2,3, and new treatments have been encumbered by limited understanding of meningioma biology. DNA methylation profiling provides robust classification of central nervous system tumors4, and can elucidate targets for molecular therapy5. Here we use DNA methylation profiling on 565 meningiomas integrated with genetic, transcriptomic, biochemical, and single-cell approaches to show meningiomas are comprised of 3 epigenetic groups with distinct clinical outcomes and biological features informing new treatments for meningioma patients. Merlin-intact meningiomas (group A, 34%) have the best outcomes and are distinguished by a novel apoptotic tumor suppressor function of NF2/Merlin. Immune-enriched meningiomas (group B, 38%) have intermediate outcomes and are distinguished by immune cell infiltration, HLA expression, and lymphatic vessels. Hypermitotic meningiomas (group C, 28%) have the worst outcomes and are distinguished by convergent genetic mechanisms misactivating the cell cycle. Consistently, we find cell cycle inhibitors block meningioma growth in cell culture, organoids, xenografts, and patients. Our results establish a framework for understanding meningioma biology, and provide preclinical rationale for new therapies to treat meningioma patients.

scholarly journals Pan-Cancer Analysis of FURIN as a Potential Prognostic and Immunological Biomarker

2021 ◽  
Vol 8 ◽  
Author(s):  
Bolun Zhou ◽  
Shugeng Gao
Keyword(s):  
Dna Methylation ◽  
Immune Checkpoint ◽  
Immune Cell ◽  
Checkpoint Inhibitors ◽  
Strong Association ◽  
Strongly Correlated ◽  
Calcium Dependent ◽  
Free Interval ◽  
Tumor Mutational Burden ◽  
Pan Cancer

BackgroundFurin is a calcium-dependent protease that processes various precursor proteins through diverse secretory pathways. The deregulation of FURIN correlated with the prognosis of patients in numerous diseases. However, the role of FURIN in human pan-cancer is still largely unknown.MethodsMultiple bioinformatic methods were employed to comprehensively analyze the correlation of FURIN expression with prognosis, mismatch repair (MMR), microsatellite instability (MSI), tumor mutational burden (TMB), DNA methylation, tumor immune infiltration, and common immune checkpoint inhibitors (ICIs) from the public database, and aim to evaluate the potential prognostic value of FURIN across cancers.ResultsFURIN was aberrantly expressed and was strongly correlated with MMR, MSI, TMB, and DNA methylation in multiple types of cancer. Moreover, survival analysis across cancers revealed that FURIN expression was correlated with overall survival (OS) in four cancers, disease-specific survival (DSS) in five cancers, progression-free interval (PFI) in seven cancers, and disease-free interval (DFI) in two cancers. Also, FURIN expression was related to immune cell infiltration in 6 cancers and ImmuneScore/StromalScore in 10 cancers, respectively. In addition, FURIN expression also showed strong association between expression levels and immune checkpoint markers in three cancers.ConclusionFURIN can serve as a significant prognostic biomarker and correlate with tumor immunity in human pan-cancer.

scholarly journals Meningioma epigenetic grouping reveals biologic drivers and therapeutic vulnerabilities

2020 ◽  
Author(s):  
Abrar Choudhury ◽  
Stephen T. Magill ◽  
Charlotte D. Eaton ◽  
Briana C. Prager ◽  
William C. Chen ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Dna Methylation ◽  
Central Nervous System ◽  
Nervous System ◽  
Immune Cell ◽  
Molecular Therapy ◽  
Intermediate Outcomes ◽  
Dna Methylation Profiling ◽  
New Treatments ◽  
Methylation Profiling

SUMMARYMeningiomas arising from the meningothelial central nervous system lining are the most common primary intracranial tumors, and a significant cause of neurologic morbidity and mortality1. There are no effective medical therapies for meningioma patients2,3, and new treatments have been encumbered by limited understanding of meningioma biology. DNA methylation profiling provides robust classification of central nervous system tumors4, and can elucidate targets for molecular therapy5. Here we use DNA methylation profiling on 565 meningiomas integrated with genetic, transcriptomic, biochemical, and single-cell approaches to show meningiomas are comprised of 3 epigenetic groups with distinct clinical outcomes and biological features informing new treatments for meningioma patients. Merlin-intact meningiomas (group A, 34%) have the best outcomes and are distinguished by a novel apoptotic tumor suppressor function of NF2/Merlin. Immune-enriched meningiomas (group B, 38%) have intermediate outcomes and are distinguished by immune cell infiltration, HLA expression, and lymphatic vessels. Hypermitotic meningiomas (group C, 28%) have the worst outcomes and are distinguished by convergent genetic mechanisms misactivating the cell cycle. Consistently, we find cell cycle inhibitors block meningioma growth in cell culture, organoids, xenografts, and patients. Our results establish a framework for understanding meningioma biology, and provide preclinical rationale for new therapies to treat meningioma patients.

scholarly journals Blood Surrogate Epigenetic Biomarkers of Atherosclerosis Reveal Common Signature of Inflamm-Aging-Disorders

Proceedings ◽  
2019 ◽  
Vol 11 (1) ◽  
pp. 39
Author(s):  
Ken Declerck ◽  
Wim Vanden Berghe
Keyword(s):  
Dna Methylation ◽  
Immune Cell ◽  
Epigenetic Mark ◽  
Epigenetic Clock ◽  
Blood Samples ◽  
Associated Diseases ◽  
Epigenetic Biomarkers ◽  
Cardiometabolic Disorders ◽  
Dna Methylation Profiling ◽  
Methylation Profiling

DNA methylation is the most well-known epigenetic modification of DNA. This epigenetic mark is crucial in controlling gene expression profiles, maintaining cellular identity, genomic imprinting and X-chromosome inactivation. Furthermore, DNA methylation is plastic and can adapt to environmental stimuli, acting as a cellular memory of past events. Whereas epigenetic DNA methylation profiling in cancer diagnostics is now well established, associations with other chronic age-associated diseases, including obesity, diabetes, cardiovascular and neurological diseases have recently started to be explored for prognostic, diagnostic and therapeutic applications. Upon genome-wide DNA methylation profiling of whole blood samples from atherosclerotic patients, we characterized various atherosclerosis specific differentially methylated regions (DMRs). Interestingly, similar DMRs were also observed in other age-and inflammation-associated diseases, like obesity, cancer, Alzheimer’s and Parkinson’s disease, both in blood as well as in brain and tumor tissues. This suggests that inflammaging diseases share a common epigenetic signature of the immune system, which is different from the classic epigenetic clock signature. Furthermore, a cardio-protective flavanol-rich diet intervention can partially reverse this inflammaging disease associated epigenetic pattern. We found that this methylation profile mainly reflects shifts in immune cell type composition and infiltrating immune cell populations. Upon correcting for differences in immune cell composition in blood samples, we identified BRCA1 DNA methylation as an atherosclerosis-specific methylation biomarker irrespective of variations in immune cell biomarkers. How BRCA1 DNA methylation differentially promotes cancer, neurodegeneration or atherosclerosis pathologies requires further investigation. In conclusion, atherosclerosis patient blood samples reveal inflammaging and atherosclerosis-specific DNA methylation biomarkers, which could potentially be used as lifestyle biomarkers to estimate disease risk of neurodegeneration, cardiometabolic disorders and cancer in aging populations.

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