Asset Details
MbrlCatalogueTitleDetail
Do you wish to reserve the book?
Genome‐wide DNA methylation profiling and identification of potential pan‐cancer and tumor‐specific biomarkers
by
Op de Beeck, Ken
, Peeters, Marc
, Van Camp, Guy
, Ibrahim, Joe
, Fransen, Erik
in
Biological markers
/ biomarker
/ Biomarkers
/ Breast cancer
/ Cancer
/ Computer applications
/ CpG islands
/ Datasets
/ Diagnosis
/ Discriminant analysis
/ DNA
/ DNA fingerprinting
/ DNA methylation
/ Esophageal cancer
/ Gene expression
/ Gene loci
/ Genetic aspects
/ Genomes
/ genome‐wide analysis
/ Genomics
/ Liver cancer
/ Methylation
/ pan‐cancer
/ Prediction models
/ Prostate
/ Thyroid cancer
/ Tumors
/ tumor‐specific
2022
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
You are currently in the queue to collect this book. You will be notified once it is your turn to collect the book.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
Genome‐wide DNA methylation profiling and identification of potential pan‐cancer and tumor‐specific biomarkers
by
Op de Beeck, Ken
, Peeters, Marc
, Van Camp, Guy
, Ibrahim, Joe
, Fransen, Erik
in
Biological markers
/ biomarker
/ Biomarkers
/ Breast cancer
/ Cancer
/ Computer applications
/ CpG islands
/ Datasets
/ Diagnosis
/ Discriminant analysis
/ DNA
/ DNA fingerprinting
/ DNA methylation
/ Esophageal cancer
/ Gene expression
/ Gene loci
/ Genetic aspects
/ Genomes
/ genome‐wide analysis
/ Genomics
/ Liver cancer
/ Methylation
/ pan‐cancer
/ Prediction models
/ Prostate
/ Thyroid cancer
/ Tumors
/ tumor‐specific
2022
Oops! Something went wrong.
While trying to remove the title from your shelf something went wrong :( Kindly try again later!
Do you wish to request the book?
Genome‐wide DNA methylation profiling and identification of potential pan‐cancer and tumor‐specific biomarkers
by
Op de Beeck, Ken
, Peeters, Marc
, Van Camp, Guy
, Ibrahim, Joe
, Fransen, Erik
in
Biological markers
/ biomarker
/ Biomarkers
/ Breast cancer
/ Cancer
/ Computer applications
/ CpG islands
/ Datasets
/ Diagnosis
/ Discriminant analysis
/ DNA
/ DNA fingerprinting
/ DNA methylation
/ Esophageal cancer
/ Gene expression
/ Gene loci
/ Genetic aspects
/ Genomes
/ genome‐wide analysis
/ Genomics
/ Liver cancer
/ Methylation
/ pan‐cancer
/ Prediction models
/ Prostate
/ Thyroid cancer
/ Tumors
/ tumor‐specific
2022
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
Genome‐wide DNA methylation profiling and identification of potential pan‐cancer and tumor‐specific biomarkers
Journal Article
Genome‐wide DNA methylation profiling and identification of potential pan‐cancer and tumor‐specific biomarkers
2022
Request Book From Autostore
and Choose the Collection Method
Overview
DNA methylation alterations have already been linked to cancer, and their usefulness for therapy and diagnosis has encouraged research into the human epigenome. Several biomarker studies have focused on identifying cancer types individually, yet common cancer and multicancer markers are still underexplored. We used The Cancer Genome Atlas (TCGA) to investigate genome‐wide methylation profiles of 14 different cancer types and developed a three‐step computational approach to select candidate biomarker CpG sites. In total, 1991 pan‐cancer and between 75 and 1803 cancer‐specific differentially methylated CpG sites were discovered. Differentially methylated blocks and regions were also discovered for the first time on such a large scale. Through a three‐step computational approach, a combination of four pan‐cancer CpG markers was identified from these sites and externally validated (AUC = 0.90), maintaining comparable performance across tumor stages. Additionally, 20 tumor‐specific CpG markers were identified and made up the final type‐specific prediction model, which could accurately differentiate tumor types (AUC = 0.87–0.99). Our study highlights the power of the methylome as a rich source of cancer biomarkers, and the signatures we identified provide a new resource for understanding cancer mechanisms on the wider genomic scale with strong applicability in the context of new minimally invasive cancer detection assays. We used The Cancer Genome Atlas to study genome‐wide methylation profiles of 14 different cancer types. We identified and validated a combination of four candidate pan‐cancer methylation CpG biomarkers and 20 candidate cancer type‐specific markers. This highlights the methylome as a rich source of biomarkers which can be used in the context of new minimally invasive cancer detection assays.
This website uses cookies to ensure you get the best experience on our website.