Aim: In order to enhance risk stratification in early-stage endometrial cancer (EC), we conducted molecular classification using surrogate markers, including the POLE droplet digital polymerase chain reaction (ddPCR) and L1CAM immunohistochemistry (IHC). Method: We analyzed archival tumor tissue from 183 early-stage EC patients. POLE pathogenic mutations of P286R, V411L, S297F, A456P, and S459F within exons 9, 13, and 14 were detected using a ddPCR, while the mismatch repair (MMR) status was determined by MMR protein IHC and MSI tests. Additionally, we conducted IHC for p53 and L1CAM. Results: The 183 ECs were categorized into four subgroups: POLE-mutated (15.9%), MMR-deficient (29.0%), p53-abnormal (8.7%), and non-specific molecular profile (NSMP, 46.4%). We further subcategorized the NSMP subgroup into NSMP-L1CAMneg (41.5%) and NSMP-L1CAMpos (4.9%), which we refer to as the molecular L1CAM classification. The molecular L1CAM classification was an independent prognostic factor for recurrence-free survival (RFS) and overall survival (OS) (p < 0.001, each). Conclusion: Integrating molecular L1CAM classification can enhance risk stratification in early-stage EC, providing valuable prognostic information to guide treatment decisions and improve patient outcomes. POLE ddPCR might be a cost-effective and easy-to-perform test as an alternative to POLE NGS.

Breast cancer with liver metastasis (BCLM) frequently cause hepatic failure owing to extensive liver metastasis compared to other cancers; however, there are no clinicopathologic or radiologic parameters for estimating BCLM prognosis. We analyzed the relationship between radiologic and clinicopathologic characteristics with survival outcomes in BCLM. During 2009–2019, baseline and final abdomen computed tomography or liver magnetic resonance imaging of BCLM patients were reviewed. Liver metastasis patterns were classified as oligometastasis (≤3 metastatic lesions), non-confluent or confluent mass formation, infiltration, and pseudocirrhosis. Thirty-one surgical or biopsy specimens for liver metastasis were immunostained for L1 adhesion molecule (L1CAM), Yes-associated protein 1/Transcriptional co-activator with PDZ-binding motif (YAP/TAZ), and β1-integrin. Out of 156 patients, 77 initially had oligometastasis, 58 had nonconfluent mass formation, 14 had confluent mass formation, and 7 had infiltrative liver metastasis. Confluent or infiltrative liver metastasis showed inferior liver metastasis-associated survival (LMOS) compared to others (p = 0.001). Positive staining for L1CAM and YAP/TAZ was associated with inferior survival, and YAP/TAZ was related to final liver metastasis. Initial hepatic metastasis was associated with LMOS, especially confluent mass formation, and infiltrative liver metastasis pattern was associated with poor survival. Positive staining for YAP/TAZ and L1CAM was associated with inferior LMOS, and YAP/TAZ was related to final liver metastasis.

Aim: To improve risk stratification in early-stage endometrial cancer (EC), we performed mo-lecular classification, and L1CAM immunohistochemistry (IHC) for additional risk assessment. Method: We analyzed archival tumor tissue from 247 early-stage EC patients. POLE mutations were detected using a Droplet digital polymerase chain reaction assay and Sanger sequencing, while the mismatch repair (MMR) status was determined by MMR protein IHC and MSI test. Additionally, we conducted IHC of p53 and L1CAM. Results: The 247 ECs were categorized into four subgroups: POLE-mutated (13.0%), MMR-deficient (27.9%), p53-abnormal (8.5%), and non-specific molecular profile (NSMP, 50.6%). We further subcategorized NSMP subgroup into NSMP-L1CAMneg (44.9%) and NSMP-L1CAMpos (5.7%), which we refer to as the molecu-lar-L1CAM classification. The molecular-L1CAM classification was an independent prognostic factor for recurrence-free survival (RFS) and overall survival (OS) (p <0.001, each). Similarly, the simplified L1CAM-p53 categorization, for practical use, remained an independent prognostic factor for RFS and OS (p <0.001, p =0.003, respectively). Conclusion: Integrating the molecu-lar-L1CAM classification or the simplified L1CAM/p53 categorization can enhance risk stratifi-cation in early-stage EC, providing valuable prognostic information to guide treatment deci-sions and improve patient outcomes.