Purpose: Epidermal growth factor receptor (EGFR), anaplastic lymphoma kinase (ALK), and ROSproto-oncogene 1 (ROS1) are ‘must-test’ biomarkers in the molecular diagnostics of advanced-stage lung cancer patients. Although single-gene assays are currently considered thegold standard for these genes, next-generation sequencing (NGS) tests are being introducedto clinical practices. We compared the results of current diagnostics and aimed to suggesttimely effective guidance for their clinical use. Materials and Methods: Patients with lung cancer who received both conventional single-gene assays and subsequenttargeted NGS testing were enrolled, and the results of their tests were compared. Results: A total of 241 patients were enrolled, and the EGFR real-time polymerase chain reaction,ALK fluorescence in situ hybridization (FISH), and ROS1 FISH assays exhibited 92.9%,99.6%, and 99.5% concordance with the NGS tests, respectively. The discordant cases weremostly false-negatives of the single-gene assays, probably due to technical limitation. Of158 cases previously designated as wild-type, EGFR, ALK, and ROS1 alterations were identifiedin 10.1%, 1.9%, and 1.3%, respectively, and other targetable alterations were identifiedin 36.1% of the cases. Of patients with additionally identified actionable alterations, 32.6%(31/95) received matched therapy with a clinical benefit of 48.4% (15/31). Conclusion Even though the conventional and NGS methods were concordant in the majority of cases,NGS testing still revealed a considerable number of additional EGFR, ALK, and ROS1 alterations,as well as other targetable alterations, in Korean advanced-stage lung cancer patients.Given the high frequency of EGFR and other targetable mutations identified in thepresent study, NGS testing is highly recommended in the diagnosis of Korean lung cancerpatients.

High-grade serous ovarian carcinoma (HGSC) exhibits significant heterogeneity, posing challenges for effective clinical categorization. Understanding the histomorphological diversity within HGSC could lead to improved prognostic stratification and personalized treatment approaches. Methods: We applied the Histomic Atlases of Variation Of Cancers model to whole slide images from The Cancer Genome Atlas dataset for ovarian cancer. Histologically distinct tumor clones were grouped into common histomic clusters. Principal component analysis and K-means clustering classified HGSC samples into three groups: highly differentiated (HD), intermediately differentiated (ID), and lowly differentiated (LD). Results: HD tumors showed diverse patterns, lower densities, and stronger eosin staining. ID tumors had intermediate densities and balanced staining, while LD tumors were dense, patternless, and strongly hematoxylin-stained. RNA sequencing revealed distinct patterns in mitochondrial oxidative phosphorylation and energy metabolism, with upregulation in the HD, downregulation in the LD, and the ID positioned in between. Survival analysis showed significantly lower overall survival for the LD compared to the HD and ID, underscoring the critical role of mitochondrial dynamics and energy metabolism in HGSC progression. Conclusions: Deep learning-based histologic analysis effectively stratifies HGSC into clinically relevant prognostic groups, highlighting the role of mitochondrial dynamics and energy metabolism in disease progression. This method offers a novel approach to HGSC categorization.

High-grade serous ovarian carcinoma (HGSC) exhibits significant heterogeneity, posing challenges for effective clinical categorization. Understanding the histomorphological diversity within HGSC could lead to improved prognostic stratification and personalized treatment approaches. Methods: We applied the Histomic Atlases of Variation Of Cancers model to whole slide images from The Cancer Genome Atlas dataset for ovarian cancer. Histologically distinct tumor clones were grouped into common histomic clusters. Principal component analysis and K-means clustering classified HGSC samples into three groups: highly differentiated (HD), intermediately differentiated (ID), and lowly differentiated (LD). Results: HD tumors showed diverse patterns, lower densities, and stronger eosin staining. ID tumors had intermediate densities and balanced staining, while LD tumors were dense, patternless, and strongly hematoxylin-stained. RNA sequencing revealed distinct patterns in mitochondrial oxidative phosphorylation and energy metabolism, with upregulation in the HD, downregulation in the LD, and the ID positioned in between. Survival analysis showed significantly lower overall survival for the LD compared to the HD and ID, underscoring the critical role of mitochondrial dynamics and energy metabolism in HGSC progression. Conclusions: Deep learning-based histologic analysis effectively stratifies HGSC into clinically relevant prognostic groups, highlighting the role of mitochondrial dynamics and energy metabolism in disease progression. This method offers a novel approach to HGSC categorization.

High-grade serous ovarian carcinoma (HGSC) exhibits significant heterogeneity, posing challenges for effective clinical categorization. Understanding the histomorphological diversity within HGSC could lead to improved prognostic stratification and personalized treatment approaches. Methods: We applied the Histomic Atlases of Variation Of Cancers model to whole slide images from The Cancer Genome Atlas dataset for ovarian cancer. Histologically distinct tumor clones were grouped into common histomic clusters. Principal component analysis and K-means clustering classified HGSC samples into three groups: highly differentiated (HD), intermediately differentiated (ID), and lowly differentiated (LD). Results: HD tumors showed diverse patterns, lower densities, and stronger eosin staining. ID tumors had intermediate densities and balanced staining, while LD tumors were dense, patternless, and strongly hematoxylin-stained. RNA sequencing revealed distinct patterns in mitochondrial oxidative phosphorylation and energy metabolism, with upregulation in the HD, downregulation in the LD, and the ID positioned in between. Survival analysis showed significantly lower overall survival for the LD compared to the HD and ID, underscoring the critical role of mitochondrial dynamics and energy metabolism in HGSC progression. Conclusions: Deep learning-based histologic analysis effectively stratifies HGSC into clinically relevant prognostic groups, highlighting the role of mitochondrial dynamics and energy metabolism in disease progression. This method offers a novel approach to HGSC categorization.

Background: Sentinel lymph node (SLN) mapping has been suggested as an alternative surgical technique to full lymphadenectomy for early-stage endometrial cancer. However, the survival outcomes of SLN mapping compared with lymphadenectomy have not been established via a prospective study. Methods A multi-center, single-blind, randomized controlled trial has been designed to determine the prognostic value of SLN mapping alone compared with conventional lymphadenectomy for patients with clinical stage I-II endometrial cancer. Eligible participants will be randomly assigned in a 1:1 ratio between the group to undergo SLN mapping using indocyanine green and the conventional lymph node dissection group. A high-risk group will undergo a 2-step SLN mapping procedure. The primary endpoint is the 3-year disease-free survival (DFS). The secondary endpoints are 3-year overall survival (OS), 5-year DFS, 5-year OS after surgery, pattern of recurrence, immediate surgical outcomes, success rate of SLN mapping, postoperative lymph-related complications, postoperative quality of life, and postoperative cost effectiveness. The role of pathologic ultrastaging of SLNs will also be assessed.

No abstract available.
Pancreas* ; Vitelline Duct*

No abstract available.
Adenocarcinoma

Objective: The RAD51 assay is a recently developed functional assay for homologous recombination deficiency (HRD) that reflects real-time HRD status. We aimed to identify the applicability and predictive value of RAD51 immunohistochemical expression in pre- and post-neoadjuvant chemotherapy (NAC) samples of ovarian high-grade serous carcinoma (HGSC). Methods: We evaluated the immunohistochemical expression of RAD51/geminin/γH2AX in ovarian HGSC before and after NAC. Results: In pre-NAC tumors (n=51), 74.5% (39/51) showed at least 25% of γH2AX-positive tumor cells, suggesting endogenous DNA damage. The RAD51-high group (41.0%, 16/39) showed significantly worse progression-free survival (PFS) compared to the RAD51-low group (51.3%, 20/39) (p=0.032). In post-NAC tumors (n=50), the RAD51-high group (36.0%, 18/50) showed worse PFS (p=0.013) and tended to present worse overall survival (p=0.067) compared to the RAD51-low group (64.0%, 32/50). RAD51-high cases were more likely to progress than RAD51-low cases at both 6 months and 12 months (p=0.046 and p=0.019, respectively). Of 34 patients with matched pre- and post-NAC RAD51 results, 44% (15/34) of pre-NAC RAD51 results were changed in the post-NAC tissue, and the RAD51 high-to-high group showed the worst PFS, while the low-to-low group showed the best PFS (p=0.031). Conclusion High RAD51 expression was significantly associated with worse PFS in HGSC, and post-NAC RAD51 status showed higher association than pre-NAC RAD51 status. Moreover, RAD51 status can be evaluated in a significant proportion of treatment-naïve HGSC samples. As RAD51 status dynamically changes, sequential follow-up of RAD51 status might reflect the biological behavior of HGSCs.

BACKGROUND: Aquaporin 1 (AQP1) overexpression has been shown to be associated with uncontrolled cell replication, invasion, migration, and tumor metastasis. We aimed to evaluate AQP1 expression in lung adenocarcinomas and to examine its association with clinicopathological features and prognostic significance. We also investigated the association between AQP1 overexpression and epithelial-mesenchymal transition (EMT) markers. METHODS: We examined AQP1 expression in 505 cases of surgically resected lung adenocarcinomas acquired at the Seoul National University Bundang Hospital from 2003 to 2012. Expression of AQP1 and EMT-related markers, including Ecadherin and vimentin, were analyzed by immunohistochemistry and tissue microarray. RESULTS: AQP1 overexpression was associated with several aggressive pathological parameters, including venous invasion, lymphatic invasion, and tumor recurrence. AQP1 overexpression tended to be associated with higher histological grade, advanced pathological stage, and anaplastic lymphoma kinase (ALK) translocation; however, these differences were not statistically significant. In addition, AQP1 overexpression positively correlated with loss of E-cadherin expression and acquired expression of vimentin. Lung adenocarcinoma patients with AQP1 overexpression showed shorter progression-free survival (PFS, 46.1 months vs. 56.2 months) compared to patients without AQP1 overexpression. Multivariate analysis confirmed that AQP1 overexpression was significantly associated with shorter PFS (hazard ratio, 1.429; 95% confidence interval, 1.033 to 1.977; p=.031). CONCLUSIONS: AQP1 overexpression was thereby concluded to be an independent factor of poor prognosis associated with shorter PFS in lung adenocarcinoma. These results suggested that AQP1 overexpression might be considered as a prognostic biomarker of lung adenocarcinoma.
Adenocarcinoma* ; Aquaporin 1* ; Cadherins ; Disease-Free Survival ; Epithelial-Mesenchymal Transition ; Humans ; Immunohistochemistry ; Lung* ; Lymphoma ; Multivariate Analysis ; Neoplasm Metastasis ; Phosphotransferases ; Prognosis* ; Recurrence ; Seoul ; Tissue Array Analysis ; Vimentin

BACKGROUND: Insulin-like growth factor-1 receptor (IGF1R) is a membrane receptor-type tyrosine kinase that has attracted considerable attention as a potential therapeutic target, although its clinical significance in non-small cell lung cancer (NSCLC) is controversial. This study aimed to clarify the clinical significance of IGF1R expression in human NSCLC. METHODS: IGF1R protein expression was evaluated using immunohistochemistry in 372 patients with NSCLC who underwent curative surgical resection (146 squamous cell carcinomas [SqCCs] and 226 adenocarcinomas [ADCs]). We then analyzed correlations between expression of IGF1R and clinicopathological and molecular features and prognostic significance. RESULTS: Membranous and cytoplasmic IGF1R expression were significantly higher in SqCCs than in ADCs. In patients with SqCC, membranous IGF1R expression was associated with absence of vascular, lymphatic, and perineural invasion; lower stage; and better progression-free survival (PFS) (hazard ratio [HR], 0.586; p = .040). In patients with ADC, IGF1R expression did not have a significant prognostic value; however, in the subgroup of epidermal growth factor receptor (EGFR)-mutant ADC, membranous IGF1R expression was associated with lymphatic and perineural invasion, solid predominant histology, and higher cancer stage and was significantly associated with worse PFS (HR, 2.582; p = .009). CONCLUSIONS: Lung ADC and SqCC showed distinct IGF1R expression profiles that demonstrated prognostic significance. High membranous IGF1R expression was predictive of poor PFS in EGFR-mutant lung ADC, while it was predictive of better PFS in SqCC. These findings will help improve study design for subsequent investigations and select patients for future anti-IGF1R therapy.
Adenocarcinoma* ; Carcinoma, Non-Small-Cell Lung ; Carcinoma, Squamous Cell ; Cytoplasm ; Disease-Free Survival ; Epidermal Growth Factor* ; Humans ; Immunohistochemistry ; Lung ; Membranes ; Prognosis* ; Protein-Tyrosine Kinases ; Receptor, Epidermal Growth Factor*