Kwan Ho Lee

Membrane‐associated proteins, including those embedded in exosomal membranes or bound to plasma lipids, are promising disease biomarkers. However, their hydrophobic nature limits detection through conventional proteomic workflows, which primarily capture soluble proteins. In this study, we developed and optimized a lipase‐based pretreatment strategy to improve the detection of insoluble membrane proteins in human plasma. Lipase treatment using porcine pancreas‐derived enzymes was optimized to 37°C, 3 U, and 1 h, based on overall protein yield and membrane protein enrichment. Sequential application after depletion of high‐abundance proteins increased the proportion of membrane proteins from 12%–20%. Using this optimized workflow, we performed data‐independent acquisition‐based LC–MS/MS analysis of plasma samples from patients with early‐stage breast cancer and benign disease ( n = 6 each). Notably, 38% of the uniquely detected or enriched proteins in cancer plasma were membrane‐associated. Among them, protocadherin 12 (PCDH12) was significantly elevated in the plasma of patients with breast cancer, indicating its potential as a novel diagnostic biomarker. This study highlights the use of lipase‐enhanced proteomics for revealing plasma membrane proteins and advancing noninvasive biomarker discovery for cancer.

BackgroundAdjuvant chemotherapy decisions in HR+/HER2– early breast cancer remain challenging. The 21-gene Oncotype DX Recurrence Score (RS) is inaccessible in many settings due to cost, creating an unmet need for validated surrogate tools. This study developed a clinicopathologic nomogram and simplified clinical rules to identify low-risk RS (≤25) using automated Ki-67.MethodsA retrospective cohort of 439 patients with HR+/HER2– early breast cancer who underwent Oncotype DX testing was analyzed. Ki-67 was quantified using an automated digital pathology workflow to reduce interobserver variability. Multivariable logistic regression identified predictors of low-risk RS and informed nomogram construction. Grid search optimized thresholds prioritizing PPV with ≥50% cohort coverage.ResultsPR Allred score, automated Ki-67 index, and histologic grade were independent predictors of low-risk RS. The nomogram demonstrated strong discrimination (AUC 0.914), further improved by MRI integration (AUC 0.935; DeLong P = 0.031). The optimized simple rule — PR Allred score ≥6, Ki-67 ≤13%, histologic grade ≤2 — identified 52.6% of the cohort as low-risk candidates with a PPV of 98.7% (228/231). A “Red Flag” combination (PR score 0, Ki-67 ≥10%) predicted RS >25 with a PPV of 100%. Among premenopausal women meeting the rule, only 5.8% fell into the grey zone where chemotherapy benefit is debated.ConclusionA simplified three-variable rule using automated Ki-67 provides a highly accurate, no-cost strategy for safe chemotherapy omission when genomic testing is unavailable. This framework supports practical decision-making in HR+/HER2– early breast cancer across diverse settings.

Ahn SG, et al. J Breast Cancer. 2026 Jan;29:e4. https://doi.org/10.4048/jbc.2025.0181

Jang JG, et al. J Korean Med Sci. 2022 Nov;37(46):e327. https://doi.org/10.3346/jkms.2022.37.e327

Hong KS, et al. J Korean Med Sci. 2021 May;36(24):e176. https://doi.org/10.3346/jkms.2021.36.e176

BackgroundsLateral lymph node metastasis (LNM), which significantly impacts papillary thyroid carcinoma (PTC) patients’ prognosis. Papillary thyroid microcarcinoma (PTMC) is known to have a much better prognosis than non-PTMC, but it has not been known whether there is such a difference even with lateral LNM. MethodsThis retrospective study included a series of 3336 consecutive PTC patients who underwent thyroidectomy. Of them, 206 had lateral LNM and were divided into the PTMC and non-PTMC groups by tumor size (1-cm) for comparing the prevalence of prognostic factors. ResultsLNM was in 157/1131 (13.9%) non-PTMC patients and 49/2205 (2.2%) PTMC patients. Eleven of the 206 (5.3%) lateral LNM cases not found on US were only seen on computed tomography. The prevalence of prognostic factors which include an age of >55 years, >5 metastatic lymph nodes (LNs), high metastatic-to-examined LN ratio, and large metastatic LNs (>3 cm) were not significantly different between PTMC and non-PTMC group. ConclusionIn PTC with lateral LNM, the prognosis is likely to be similar regardless of tumor size. Considering the modest risk of lateral LNM in PTMC, FNA for small thyroid tumor and radiologic tests for lateral LNM should be encouraged.

Hong KS, et al. Yonsei Med J. 2020 May;61(5):431-437. https://doi.org/10.3349/ymj.2020.61.5.431

Background In patients diagnosed with ductal carcinoma in situ (DCIS) with needle biopsy before surgery, invasive component (IC) is often found in the postoperative tissue, which results in altered post-surgical care. However, there are no clinically available factors to predict IC, and few MRI studies are available for the detection of IC in DCIS patients. The purpose of this study was to evaluate which risk factors can predict IC preoperatively.Methods Patients with a DCIS diagnosis based on preoperative biopsy, who underwent breast surgery Kangbuk Samsung Hospital between Jan 2005 and June 2018, were retrospectively evaluated. Clinico-pathological and breast MRI factors were compared between DCIS and DCIS with IC in postsurgical specimens.Results Of the 431 patients with a preoperative diagnosis of DCIS, 34 (7.9%) showed IC during the postoperative pathological investigations, and 217 (50.3%) underwent breast MRI. Among MRI-related factors, Mass-like enhancement on MRI was the sole but significant predictor of IC (HR=0.26, C.I.=0.07-0.93, p=0.038), while nipple-areolar complex invasion, enhancement peak and pattern were not statistically significant. Nuclear grade was the only significant predictor of IC in the analysis of other clinico-pathological factors (HR=2.39, C.I.=1.05-5.42, p=0.038 in univariate analysis, HR=2.86, C.I.=1.14-7.14, p=0.025 in multivariate analysis).Conclusions Mass-like enhancement on MRI and high nuclear grade were associated with IC in patients with preoperative diagnosis of DCIS. Considering the high sensitivity of breast MRI for IC, further evaluation of the predictive value of MRI in preoperative DCIS patients is desirable.

Background In patients diagnosed with ductal carcinoma in situ (DCIS) with needle biopsy before surgery, invasive component (IC) is often found in the postoperative tissue, which results in altered post-surgical care. However, there are no clinically available factors to predict IC, and few MRI studies are available for the detection of IC in DCIS patients. The purpose of this study was to evaluate which risk factors can predict IC preoperatively.Methods Patients with a DCIS diagnosis based on preoperative biopsy, who underwent breast surgery Kangbuk Samsung Hospital between Jan 2005 and June 2018, were retrospectively evaluated. Clinico-pathological and breast MRI factors were compared between DCIS and DCIS with IC in postsurgical specimens.Results Of the 431 patients with a preoperative diagnosis of DCIS, 34 (7.9%) showed IC during the postoperative pathological investigations, and 217 (50.3%) underwent breast MRI. Among MRI-related factors, Mass-like enhancement on MRI was the sole but significant predictor of IC (HR=0.26, C.I.=0.07-0.93, p=0.038), while nipple-areolar complex invasion, enhancement peak and pattern were not statistically significant. Nuclear grade was the only significant predictor of IC in the analysis of other clinico-pathological factors (HR=2.39, C.I.=1.05-5.42, p=0.038 in univariate analysis, HR=2.86, C.I.=1.14-7.14, p=0.025 in multivariate analysis).Conclusions Mass-like enhancement on MRI and high nuclear grade were associated with IC in patients with preoperative diagnosis of DCIS. Considering the high sensitivity of breast MRI for IC, further evaluation of the predictive value of MRI in preoperative DCIS patients is desirable.