Methylation profiling

Dataset Information

0

DNA methylation profiles of lymph node tissue of head and neck cancer of unknown primary


ABSTRACT: Background. The unknown tissue of origin in head and neck cancer of unknown primary (hnCUP) leads to invasive diagnostic procedures and unspecific and potentially inefficient treatment options for patients. The most common histological subtype, squamous cell carcinoma, can stem from various tumor primary sites, including the oral cavity, oropharynx, larynx, head and neck skin, lungs, and esophagus. DNA methylation profiles are highly tissue-specific and have been successfully used to classify tissue origin. We therefore developed a support vector machine (SVM) classifier trained with publicly available DNA methylation profiles of commonly cervically metastasizing squamous cell carcinomas (n = 1,103) in order to identify the primary tissue of origin of our own cohort of squamous cell hnCUP patient’s samples (n = 28). Methylation analysis was performed with Infinium MethylationEPIC v1.0 BeadChip by Illumina. Results. The SVM algorithm achieved the highest overall accuracy of tested classifiers, with 87%. Squamous cell hnCUP samples on DNA methylation level resembled squamous cell carcinomas commonly metastasizing into cervical lymph nodes. The most frequently predicted cancer localization was the oral cavity in 11 cases (39%), followed by the oropharynx and larynx (both 7, 25%), skin (2, 7%), and esophagus (1, 4%). These frequencies concord with the expected distribution of lymph node metastases in epidemiological studies. Conclusions. On DNA methylation level, hnCUP is comparable to primary tumor tissue cancer types that commonly metastasize to cervical lymph nodes. Our SVM-based classifier can accurately predict these cancers’ tissues of origin and could significantly reduce the invasiveness of hnCUP diagnostics and enable a more precise therapy after clinical validation.

ORGANISM(S): Homo sapiens

PROVIDER: GSE256413 | GEO | 2024/03/04

REPOSITORIES: GEO

Dataset's files

Source:
Action DRS
Other
Items per page:
1 - 1 of 1

Similar Datasets

2008-06-18 | E-GEOD-9349 | biostudies-arrayexpress
2021-12-08 | GSE171994 | GEO
2014-07-07 | GSE58911 | GEO
2014-07-07 | E-GEOD-58911 | biostudies-arrayexpress
2011-10-27 | E-GEOD-25089 | biostudies-arrayexpress
2014-12-25 | GSE59102 | GEO
2011-10-28 | GSE25091 | GEO
2011-10-28 | GSE25089 | GEO
2011-10-28 | GSE25083 | GEO
2011-10-27 | E-GEOD-25083 | biostudies-arrayexpress