期刊
FRONTIERS IN ONCOLOGY
卷 12, 期 -, 页码 -出版社
FRONTIERS MEDIA SA
DOI: 10.3389/fonc.2022.942735
关键词
endometrial cancer; Papanicolaou (PAP) smear; circulating tumor DNA (ctDNA); molecular classification and biomarkers; immunohistochemistry
类别
资金
- Severance Hospital Research fund for clinical excellence (SHRC)
- [C-2022-0013]
This study investigated the feasibility of genomic profiling based on tumor DNA analysis from cervical smear samples in endometrial cancer patients. It found that cervical swab-based gDNA analysis showed improved detection potential and allowed patient classification, with predictive and prognostic implications.
PurposeCervical smear samples are easily obtainable and may effectively reflect the tumor microenvironment in gynecological cancers. Therefore, we investigated the feasibility of genomic profiling based on tumor DNA analysis from cervical smear samples from endometrial cancer patients. Materials and methodsPreoperative cervical smear samples were obtained via vaginal sampling in 50 patients, including 39 with endometrial cancer and 11 with benign uterine disease. Matched blood samples were obtained simultaneously. Genomic DNA (gDNA) from cervical smear and/or cell-free DNA from whole blood were extracted and sequenced using the Pan100 panel covering 100 endometrial cancer-related genes. ResultsCervical swab-based gDNA analysis detected cancer with 67% sensitivity and 100% specificity, showing a superior performance compared to that of the matched blood or Pap smear tests. Cervical swab-based gDNA effectively identified patients with loss of MSH2 or MSH6 and aberrant p53 expression based on immunohistochemistry. Genomic landscape analysis of cervical swab-based gDNA identified PTEN, PIK3CA, TP53, and ARID1A as the most frequently altered genes. Furthermore, 26 endometrial cancer patients could be classified according to the Proactive Molecular Risk Classifier for Endometrial Cancer. ConclusionCervical swab-based gDNA test showed an improved detection potential and allowed the classification of patients, which has both predictive and prognostic implications.
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