{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["55"],"submitter":["Hwang J"],"pubmed_abstract":["Cancer of unknown primary (CUP) is a rare type of metastatic cancer in which the origin of the tumor is unknown. Since the treatment strategy for patients with metastatic tumors depends on knowing the primary site, accurate identification of the origin site is important. Here, we developed an image-based deep-learning model that utilizes a vision transformer algorithm for predicting the origin of CUP. Using DNA methylation dataset of 8,233 primary tumors from The Cancer Genome Atlas (TCGA), we categorized 29 cancer types into 18 organ classes and extracted 2,312 differentially methylated CpG sites (DMCs) from non-squamous cancer group and 420 DMCs from squamous cell cancer group. Using these DMCs, we created organ-specific DNA methylation images and used them for model training and testing"],"journal":["Neoplasia (New York, N.Y.)"],"pagination":["101021"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC11261876"],"repository":["biostudies-literature"],"pubmed_title":["Image-based deep learning model using DNA methylation data predicts the origin of cancer of unknown primary."],"pmcid":["PMC11261876"],"pubmed_authors":["Yoo SK","Kim JI","Lee Y","Hwang J"],"additional_accession":[]},"is_claimable":false,"name":"Image-based deep learning model using DNA methylation data predicts the origin of cancer of unknown primary.","description":"Cancer of unknown primary (CUP) is a rare type of metastatic cancer in which the origin of the tumor is unknown. Since the treatment strategy for patients with metastatic tumors depends on knowing the primary site, accurate identification of the origin site is important. Here, we developed an image-based deep-learning model that utilizes a vision transformer algorithm for predicting the origin of CUP. Using DNA methylation dataset of 8,233 primary tumors from The Cancer Genome Atlas (TCGA), we categorized 29 cancer types into 18 organ classes and extracted 2,312 differentially methylated CpG sites (DMCs) from non-squamous cancer group and 420 DMCs from squamous cell cancer group. Using these DMCs, we created organ-specific DNA methylation images and used them for model training and testing","dates":{"release":"2024-01-01T00:00:00Z","publication":"2024 Sep","modification":"2025-05-18T13:25:44.081Z","creation":"2025-05-18T13:25:44.081Z"},"accession":"S-EPMC11261876","cross_references":{"pubmed":["38943996"],"doi":["10.1016/j.neo.2024.101021"]}}