A 5-marker immunohistochemical panel of CK17, MEP1A, PAX8, SMAD4, and CDX2 to distinguish ovarian mucinous carcinoma from metastatic pancreatic ductal adenocarcinoma.
1/5 보강
[AIMS] Metastatic pancreatic adenocarcinoma (PDAC), albeit uncommon, may involve the ovary, and distinction from primary ovarian mucinous tumours (OMT) poses a diagnostic challenge.
APA
De Boeck A, Kang EY, et al. (2026). A 5-marker immunohistochemical panel of CK17, MEP1A, PAX8, SMAD4, and CDX2 to distinguish ovarian mucinous carcinoma from metastatic pancreatic ductal adenocarcinoma.. Histopathology, 88(2), 402-413. https://doi.org/10.1111/his.70002
MLA
De Boeck A, et al.. "A 5-marker immunohistochemical panel of CK17, MEP1A, PAX8, SMAD4, and CDX2 to distinguish ovarian mucinous carcinoma from metastatic pancreatic ductal adenocarcinoma.." Histopathology, vol. 88, no. 2, 2026, pp. 402-413.
PMID
40970686 ↗
Abstract 한글 요약
[AIMS] Metastatic pancreatic adenocarcinoma (PDAC), albeit uncommon, may involve the ovary, and distinction from primary ovarian mucinous tumours (OMT) poses a diagnostic challenge. Our aim was to develop an ancillary immunohistochemical (IHC) panel to aid in diagnosis and to validate the morphological features of metastatic PDAC.
[METHODS AND RESULTS] Six IHC markers (CDX2, CK17, MEP1A, MUC2, PAX8, SMAD4) selected based on a literature review were stained on tissue microarrays containing 256 PDAC, 102 mucinous ovarian carcinomas (MC) and 58 mucinous borderline ovarian tumours (MBOT). Detailed morphological features were reviewed in 16 ovarian metastases from PDAC, 25 MC, and 9 MBOT. We confirmed that tumours with a size less than 13 cm, bilaterality, ovarian surface involvement, low-power nodularity, infiltrative invasion, pseudomyxoma ovarii despite cystadenoma or borderline areas, and moderate nuclear atypia should raise suspicion for metastatic PDAC and prompt evaluation with the recommended IHC panel. A 5-marker panel consisting of CK17, MEP1A, PAX8, SMAD4, and CDX2 had an overall accuracy of 91.8% (95% CI 88.8%-94.3%) using recursive partitioning, with the highest weight resting on CK17. CK17 was expressed in 80.9% of PDAC compared to 18.6% of MC and 1.7% of MBOT, respectively.
[CONCLUSIONS] This is the first ancillary IHC panel to distinguish between PDAC and OMT with high accuracy. These results inform further studies on diagnostic workflows tailored to the complexity of metastatic presentations of tumours at the ovary.
[METHODS AND RESULTS] Six IHC markers (CDX2, CK17, MEP1A, MUC2, PAX8, SMAD4) selected based on a literature review were stained on tissue microarrays containing 256 PDAC, 102 mucinous ovarian carcinomas (MC) and 58 mucinous borderline ovarian tumours (MBOT). Detailed morphological features were reviewed in 16 ovarian metastases from PDAC, 25 MC, and 9 MBOT. We confirmed that tumours with a size less than 13 cm, bilaterality, ovarian surface involvement, low-power nodularity, infiltrative invasion, pseudomyxoma ovarii despite cystadenoma or borderline areas, and moderate nuclear atypia should raise suspicion for metastatic PDAC and prompt evaluation with the recommended IHC panel. A 5-marker panel consisting of CK17, MEP1A, PAX8, SMAD4, and CDX2 had an overall accuracy of 91.8% (95% CI 88.8%-94.3%) using recursive partitioning, with the highest weight resting on CK17. CK17 was expressed in 80.9% of PDAC compared to 18.6% of MC and 1.7% of MBOT, respectively.
[CONCLUSIONS] This is the first ancillary IHC panel to distinguish between PDAC and OMT with high accuracy. These results inform further studies on diagnostic workflows tailored to the complexity of metastatic presentations of tumours at the ovary.
🏷️ 키워드 / MeSH 📖 같은 키워드 OA만
- Humans
- Female
- Ovarian Neoplasms
- Biomarkers
- Tumor
- Pancreatic Neoplasms
- Carcinoma
- Pancreatic Ductal
- Adenocarcinoma
- Mucinous
- Diagnosis
- Differential
- Smad4 Protein
- Immunohistochemistry
- PAX8 Transcription Factor
- CDX2 Transcription Factor
- Aged
- Middle Aged
- Adult
- Keratin-17
- 80 and over
- CK17
- MEP1A
- SMAD4
… 외 3개
🏷️ 같은 키워드 · 무료전문 — 이 논문 MeSH/keyword 기반
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