We are analyzing https://link.springer.com/article/10.1186/s13148-024-01657-3.

Title:
Head and neck cancer of unknown primary: unveiling primary tumor sites through machine learning on DNA methylation profiles | Clinical Epigenetics
Description:
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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Keywords {🔍}

primary, methylation, cancer, samples, article, pubmed, dna, neck, lymph, hncup, google, scholar, head, tumor, node, data, sites, classifier, squamous, cell, cohort, study, unknown, tissue, cervical, file, profiles, carcinoma, table, additional, metastases, fig, cas, analysis, metastasis, cases, clinical, patients, site, svm, size, origin, diagnostic, cup, cpg, central, accuracy, nodes, umap, full,

Topics {✒️}

genome–wide methylation profiling article download pdf squamous cell carcinomas ai-assisted molecular profiling squamous cell carcinoma keywords “lymph node cancer genome atlas dna methylation-based classification full size table optimal cross-array normalization small esophageal carcinomas p16/hpv-negative cases cervically metastasizing scc p16/hpv-positive hncup explore potential variations machine learning-based classifier privacy choices/manage cookies cervical lymph nodes dna methylation profiles eur arch otorhinolaryngol dna methylation profiling sample size underscores translational cancer research lymph node metastases single-cell methods [42] markus wirth lymph node metastasis full access cervical node dissection fdg-pet-ct support vector machine lymph node extirpation dna methylation level placental dna methylation lymph node tissue uniform manifold approximation tissue dna methylation dna methylation analysis methylation profiling identifies oropharyngeal carcinoma metastasizes resected laryngeal carcinoma phenomenon commonly observed p53 gene status neck lymph nodes creative commons licence limited sample size small primary tumor german cancer consortium lymph node samples local ethics committee

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Cancer of unknown primary site: real entity or misdiagnosed disease?

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         description: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. 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. 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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      headline:Head and neck cancer of unknown primary: unveiling primary tumor sites through machine learning on DNA methylation profiles
      description: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. 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. 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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            address:
               name:Institute of Clinical Chemistry and Pathobiochemistry, School of Medicine and Health, Technical University of Munich, Munich, Germany
               type:PostalAddress
            type:Organization
            name:TranslaTUM, Technical University of Munich
            address:
               name:Center for Translational Cancer Research, TranslaTUM, Technical University of Munich, Munich, Germany
               type:PostalAddress
            type:Organization
            name:German Cancer Consortium (DKTK)
            address:
               name:Partner Site Munich and German Cancer Research Center (DKFZ), German Cancer Consortium (DKTK), Heidelberg, Germany
               type:PostalAddress
            type:Organization
      name:Christof Winter
      affiliation:
            name:Technical University of Munich
            address:
               name:Institute of Clinical Chemistry and Pathobiochemistry, School of Medicine and Health, Technical University of Munich, Munich, Germany
               type:PostalAddress
            type:Organization
            name:TranslaTUM, Technical University of Munich
            address:
               name:Center for Translational Cancer Research, TranslaTUM, Technical University of Munich, Munich, Germany
               type:PostalAddress
            type:Organization
            name:German Cancer Consortium (DKTK)
            address:
               name:Partner Site Munich and German Cancer Research Center (DKFZ), German Cancer Consortium (DKTK), Heidelberg, Germany
               type:PostalAddress
            type:Organization
      name:Markus Wirth
      affiliation:
            name:Technical University of Munich
            address:
               name:Department of Otolaryngology, Head and Neck Surgery, School of Medicine and Health, Technical University of Munich, Munich, Germany
               type:PostalAddress
            type:Organization
            name:German Cancer Consortium (DKTK)
            address:
               name:Partner Site Munich and German Cancer Research Center (DKFZ), German Cancer Consortium (DKTK), Heidelberg, Germany
               type:PostalAddress
            type:Organization
PostalAddress:
      name:Department of Otolaryngology, Head and Neck Surgery, School of Medicine and Health, Technical University of Munich, Munich, Germany
      name:Institute of Clinical Chemistry and Pathobiochemistry, School of Medicine and Health, Technical University of Munich, Munich, Germany
      name:Institute of Pathology, School of Medicine and Health, Technical University of Munich, Munich, Germany
      name:Institute of Pathology, School of Medicine and Health, Technical University of Munich, Munich, Germany
      name:Department of Otolaryngology, Head and Neck Surgery, School of Medicine and Health, Technical University of Munich, Munich, Germany
      name:Department of Otolaryngology, Head and Neck Surgery, School of Medicine and Health, Technical University of Munich, Munich, Germany
      name:Department of Otolaryngology, Head and Neck Surgery, School of Medicine and Health, Technical University of Munich, Munich, Germany
      name:Department of Otolaryngology, Head and Neck Surgery, School of Medicine and Health, Technical University of Munich, Munich, Germany
      name:Institute of Pathology, School of Medicine and Health, Technical University of Munich, Munich, Germany
      name:Institute of Pathology, School of Medicine and Health, Technical University of Munich, Munich, Germany
      name:Department of Otolaryngology, Head and Neck Surgery, School of Medicine and Health, Technical University of Munich, Munich, Germany
      name:Partner Site Munich and German Cancer Research Center (DKFZ), German Cancer Consortium (DKTK), Heidelberg, Germany
      name:Institute of Clinical Chemistry and Pathobiochemistry, School of Medicine and Health, Technical University of Munich, Munich, Germany
      name:Center for Translational Cancer Research, TranslaTUM, Technical University of Munich, Munich, Germany
      name:Partner Site Munich and German Cancer Research Center (DKFZ), German Cancer Consortium (DKTK), Heidelberg, Germany
      name:Institute of Clinical Chemistry and Pathobiochemistry, School of Medicine and Health, Technical University of Munich, Munich, Germany
      name:Center for Translational Cancer Research, TranslaTUM, Technical University of Munich, Munich, Germany
      name:Partner Site Munich and German Cancer Research Center (DKFZ), German Cancer Consortium (DKTK), Heidelberg, Germany
      name:Department of Otolaryngology, Head and Neck Surgery, School of Medicine and Health, Technical University of Munich, Munich, Germany
      name:Partner Site Munich and German Cancer Research Center (DKFZ), German Cancer Consortium (DKTK), Heidelberg, Germany

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