Purpose: Triple-negative breast cancer (TNBC) is a particularly challenging subtype of breast cancer, with a poorer prognosis compared to other subtypes. Unfortunately, unlike luminal-type cancers, there is no validated biomarker to predict the prognosis of patients with early-stage TNBC. Accurate biomarkers are needed to establish effective therapeutic strategies. Materials and Methods: In this study, we analyzed gene expression profiles of tumor samples from 184 TNBC patients (training cohort, n=76; validation cohort, n=108) using RNA sequencing. Results: By combining weighted gene expression, we identified a 10-gene signature (DGKH, GADD45B, KLF7, LYST, NR6A1, PYCARD, ROBO1, SLC22A20P, SLC24A3, and SLC45A4) that stratified patients by risk score with high sensitivity (92.31%), specificity (92.06%), and accuracy (92.11%) for invasive disease-free survival. The 10-gene signature was validated in a separate institution cohort and supported by meta-analysis for biological relevance to well-known driving pathways in TNBC. Furthermore, the 10-gene signature was the only independent factor for invasive disease-free survival in multivariate analysis when compared to other potential biomarkers of TNBC molecular subtypes and T-cell receptor β diversity. 10-gene signature also further categorized patients classified as molecular subtypes according to risk scores. Conclusion Our novel findings may help address the prognostic challenges in TNBC and the 10-gene signature could serve as a novel biomarker for risk-based patient care.

Based on the clinical, histopathological, and perioperative data of a patient with differentiated thyroid cancer (DTC), risk stratification based on their initial recurrence risk is a crucial follow-up (FU) strategy during the first 1–2 years after initial therapy. However, restratifiying the recurrence risk on the basis of current clinical data that becomes available after considering the response to treatment (ongoing risk stratification, ORS) provides a more accurate prediction of the status at the final FU and a more tailored management approach. Since the 2015 American Thyroid Association Management Guidelines for Adult Patients with Thyroid Nodules and DTC, the latest guidelines that include the National Comprehensive Cancer Network clinical practice and European Association for Medical Oncology guidelines have been updated to reflect several recent evidence in ORS and thyroid-stimulating hormone (TSH) suppression of DTC. The current clinical practice guideline was developed by extracting FU surveillance after the initial treatment section from the previous version of guidelines and updating it to reflect recent evidence. The current revised guideline includes recommendations for recent ORS, TSH target level based on risk stratification, FU tools for detection of recurrence and assessment of disease status, and long-term FU strategy for consideration of the disease status. These evidence-based recommendations are expected to avoid overtreatment and intensive FU of the majority of patients who will have a very good prognosis after the initial treatment of DTC patients, thereby ensuring that patients receive the most appropriate and effective treatment and FU options.

Differentiated thyroid cancer demonstrates a wide range of clinical presentations, from very indolent cases to those with an aggressive prognosis. Therefore, diagnosing and treating each cancer appropriately based on its risk status is important. The Korean Thyroid Association (KTA) has provided and amended the clinical guidelines for thyroid cancer management since 2007. The main changes in this revised 2024 guideline include 1) individualization of surgical extent according to pathological tests and clinical findings, 2) application of active surveillance in low-risk papillary thyroid microcarcinoma, 3) indications for minimally invasive surgery, 4) adoption of World Health Organization pathological diagnostic criteria and definition of terminology in Korean, 5) update on literature evidence of recurrence risk for initial risk stratification, 6) addition of the role of molecular testing, 7) addition of definition of initial risk stratification and targeting thyroid stimulating hormone (TSH) concentrations according to ongoing risk stratification (ORS), 8) addition of treatment of perioperative hypoparathyroidism, 9) update on systemic chemotherapy, and 10) addition of treatment for pediatric patients with thyroid cancer.

Background: Turner syndrome (TS) is a common chromosomal abnormality, which is caused by loss of all or part of one X chromosome. Hormone replacement therapy in TS is important in terms of puberty, growth and prevention of osteoporosis however, such a study has never been conducted in Korea. Therefore, the purpose of our study was to determine relationship between the starting age, duration of estrogen replacement therapy (ERT) in TS and develop a hormone replacement protocol suitable for the situation in Korea. Methods: This is retrospective study analyzed the medical records in TS patients treated at the Severance hospital, Yonsei University College of Medicine, Seoul, Korea from 1997 to 2019. Total of 188 subjects who had received a bone density test at least once were included in the study. Korean National Health and Nutrition Examination Survey (KNHANES) was used for achieving bone mineral density (BMD) of normal control group. Student’s t-test, MannWhitney U test, ANOVA and correlation analysis were performed using SPSS 18.0. Results: Each BMD measurement was significantly lower in women with TS than in healthy Korean women. Early start and longer duration of ERT is associated with higher lumbar spine BMD but not femur neck BMD. Femur neck BMD, but not lumbar spine BMD was significantly higher in women with mosaicism than 45XO group. Conclusion Early onset and appropriate duration of hormone replacement therapy is important for increasing bone mineral density in patients with Turner syndrome. Also, ERT affects differently to TS patients according to mosaicism.

Objectives: This study used the Korean National Health and Nutrition Examination Survey (KNHANES) to determine the association between fractures and low muscle mass. Methods: This cross-sectional study used the 2010–2011 KNHANES data. Low muscle mass was defined as (appendicular skeletal muscle mass [kg]/Height2 [m2 ]) < 5.45 kg/m2 , which is < 2 SD below the sex-specific mean of a young reference group. Patients with T-scores between –1.0 and –2.5 indicated osteopenia, whereas those with T-scores lower than –2.5 indicated osteoporosis. Results: Out of 1,306 women enrolled in the study, 330 were diagnosed with low muscle mass according to the abovementioned diagnostic criterion. The prevalence of fractures at various sites was significantly higher in postmenopausal women with low muscle mass than in those without low muscle mass (relative risk [RR], 1.64; odds ratio [OR], 1.62; 95% confidence interval [CI], 1.06–2.48; P = 0.027). Furthermore, the prevalence of fractures was increased by the presence of osteopenia or osteoporosis in addition to low muscle mass (RR, 1.59; OR, 1.60; 95% CI, 1.02–2.49; P = 0.039) and by osteoporosis only (RR, 2.12; OR, 2.29; 95% CI, 1.11–4.70; P = 0.025). Conclusions Fracture was more prevalent in postmenopausal women with low muscle mass than in those without low muscle mass.This finding is consistent in a subgroup analysis that included women who had osteoporosis or osteopenia. Moreover, the risk of fractures increased as low muscle mass worsened.

Objective: To assess whether computed tomography (CT) conversion across different scan parameters and manufacturers using a routable generative adversarial network (RouteGAN) can improve the accuracy and variability in quantifying interstitial lung disease (ILD) using a deep learning-based automated software. Materials and Methods: This study included patients with ILD who underwent thin-section CT. Unmatched CT images obtained using scanners from four manufacturers (vendors A-D), standard- or low-radiation doses, and sharp or medium kernels were classified into groups 1–7 according to acquisition conditions. CT images in groups 2–7 were converted into the target CT sty le (Group 1: vendor A, standard dose, and sharp kernel) using a RouteGAN. ILD was quantified on original and converted CT images using a deep learning-based software (Aview, Coreline Soft). The accuracy of quantification was analyzed using the dice similarity coefficient (DSC) and pixel-wise overlap accuracy metrics against manual quantification by a radiologist. Five radiologists evaluated quantification accuracy using a 10-point visual scoring system. Results: Three hundred and fifty CT slices from 150 patients (mean age: 67.6 ± 10.7 years; 56 females) were included. The overlap accuracies for quantifying total abnormalities in groups 2–7 improved after CT conversion (original vs. converted: 0.63vs. 0.68 for DSC, 0.66 vs. 0.70 for pixel-wise recall, and 0.68 vs. 0.73 for pixel-wise precision; P < 0.002 for all). The DSCs of fibrosis score, honeycombing, and reticulation significantly increased after CT conversion (0.32 vs. 0.64, 0.19 vs. 0.47, and 0.23 vs. 0.54, P < 0.002 for all), whereas those of ground-glass opacity, consolidation, and emphysema did not change significantly or decreased slightly. The radiologists’ scores were significantly higher (P < 0.001) and less variable on converted CT. Conclusion CT conversion using a RouteGAN can improve the accuracy and variability of CT images obtained using different scan parameters and manufacturers in deep learning-based quantification of ILD.