1.Impact of Poloxamer/Alginate (Guardix-SGⓇ ) Volume on Drainage after Thyroid Lobectomy
Seok-Kyung KANG ; Miri RYU ; Meehyun LEE ; Hye Won KIM ; Han Pyo HONG ; Seungju LEE
International Journal of Thyroidology 2026;19(1):78-84
Background and Objectives:
Anti-adhesion agents based on hyaluronate-carboxymethyl cellulose (HA-CMC) are widely used in thyroid surgery to reduce postoperative adhesions. However, concerns persist that higher application volumes may increase postoperative drainage and prolong hospitalization. This study aimed to evaluate the impact of different doses of an HA-CMC solution (Guardix-SGⓇ ) on postoperative drainage and clinical outcomes after hemithyroidectomy.
Materials and Methods:
This prospective study included 107 patients who underwent hemithyroidectomy with central neck lymph node dissection for thyroid cancer between January and October 2024. Patients were randomly assigned to receive either 3 g (n=57) or 6 g (n=50) of Guardix-SGⓇ intraoperatively.Postoperative drainage volume, drain duration, and length of hospital stay were compared between groups.Analysis of covariance and quantile regression were performed to assess the effects of HA-CMC dose and clinical covariates on drainage outcomes.
Results:
Baseline demographic and pathological characteristics were comparable between the two groups. Total postoperative drainage volume did not differ significantly between the 3 g and 6 g groups, even after adjustment for hospital stay (p=0.283), nor did drain duration. Quantile regression analysis revealed that hypertension was independently associated with increased drainage volume in higher quantiles (0.25– 0.75), whereas the dose of HA-CMC solution had no significant effect across any quantile.
Conclusion
Application of a higher dose (6 g) of HA-CMC solution did not increase postoperative drainage or prolong drain duration after hemithyroidectomy. These findings support the safe and effective use of higher-dose Guardix-SGⓇ in thyroid surgery.
2.Identification of Poor Prognostic Markers in Triple-Negative Breast Cancer Using Whole Exome Sequencing
Seungju LEE ; Hyun Yul KIM ; Youn Joo JUNG ; Seok-Kyung KANG ; Miri RYU ; Meehyun LEE ; Sun Min LEE ; Seung Hwan OH ; Jieon LEE ; Seongdo JEONG ; Junho KANG ; Jee Yeon KIM
Journal of Breast Cancer 2025;28(6):406-418
Purpose:
Triple-negative breast cancer (TNBC) is a heterogeneous and aggressive subtype of breast cancer associated with poor clinical outcomes. Although programmed death ligand 1 (PD-L1) expression has emerged as both a prognostic and predictive biomarker, its utility remains limited, especially in PD-L1-negative tumors. The identification of additional molecular markers is crucial for improving prognostic stratification and guiding treatment strategies.
Methods:
Formalin-fixed, paraffin-embedded tumor tissues from 38 patients with TNBC were analyzed. PD-L1 expression was assessed using immunohistochemistry and categorized as positive or negative. Whole-exome sequencing was performed, and somatic variants were analyzed using Maftools. Mutational signatures were compared with the Catalogue Of Somatic Mutations In Cancer reference profiles. Survival analyses were performed to evaluate the prognostic significance of the identified variants.
Results:
Mutational landscape analysis revealed that C>T and G>A transitions were the most frequent base substitutions. PD-L1-negative tumors exhibited a predominance of single-base substitution (SBS) 5, whereas PD-L1-positive tumors resembled SBS6, reflecting potential differences in the underlying mutational processes. Comparative analysis identified 12 PD-L1-negative-specific and seven PD-L1-positive-specific variants. Among PD-L1-negative tumors, mutations in ANGPTL5 and KIAA1549L were significantly associated with worse overall survival.
Conclusion
Our findings highlight distinct mutational profiles and prognostic variants according to PD-L1 status in TNBC. ANGPTL5 and KIAA1549L variants may serve as potential prognostic markers for PD-L1-negative tumors. These results underscore the value of incorporating genomic information to refine the prognostic stratification of TNBC.

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