DNA甲基化
头颈部癌
食管
头颈部鳞状细胞癌
喉
颈淋巴结
医学
癌症
淋巴结
病理
原发性肿瘤
甲基化
癌
肿瘤科
癌症研究
生物
内科学
DNA
转移
外科
基因表达
基因
遗传学
作者
Leonhard Stark,Atsuko Kasajima,Fabian Stögbauer,Benedikt Schmidl,Jakob Rinecker,Katharina Holzmann,S. Harrison Farber,Nicole Pfarr,Katja Steiger,Barbara Wollenberg,Jürgen Ruland,Christof Winter,Markus Wirth
标识
DOI:10.1186/s13148-024-01657-3
摘要
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 histologic 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 = 1103) 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.
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