Dong-Chan Kim

Background/Objectives: Serum matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF/MS) profiling may complement breast cancer (BrC) assessment, but retrospective studies are vulnerable to demographic and batch confounding. We evaluated direct-serum (Workflow A) and acetonitrile (ACN)-assisted (Workflow B) profiling. Methods: Workflow A analyzed 60 archived sera (30 BrC, 30 controls) with sample-level nested 10-fold cross-validation and L2-regularized logistic regression. Workflow B included 40 sample groups (20 BrC, 20 negative/comparator; approximately four spots/sample); replicates were aggregated before repeated sample-level five-fold cross-validation and batch/source diagnostics. Results: Workflow A yielded an area under the receiver operating characteristic curve (AUC) of 0.932, but groups were not age matched (52 vs. 45 years; standardized mean difference approximately 1.03), precluding cancer-specific interpretation independent of age. Workflow B yielded a mean AUC of 0.978 ± 0.007 and a balanced accuracy of 0.968, but negative/comparator batch/date classification reached an AUC of 0.970, and cross-batch transfer was asymmetric (1.00 vs. 0.64); five comparator sera were commercially sourced. Conclusions: Workflow A provides preliminary group-discrimination evidence but remains age-confounded. Workflow B demonstrates strong apparent internal discrimination under substantial batch/source confounding and is best viewed as an analytical stress test, not independent validation. Candidate m/z signals remain unidentified; age-matched, batch-balanced external validation and orthogonal molecular identification are required before cancer-specific or biomarker claims.

Hyeyoung Lee, M.D., Ph.D., Donggun Seo, B.S., Hyun Ji Lee, B.S., Hyunjoo Lee, B.S., Sung-Il Cho, B.S., Jehyun Koo, M.S., Kei-Anne Garcia Baritugo, Ph.D., Gi-Ho Sung, Ph.D., Dong-Chan Kim, Ph.D., and Jayoung Kim, M.D., Ph.D.. Ann Lab Med -0001;0:. https://doi.org/10.3343/alm.2026.0069

Kyoung Bo Kim, M.D., Gi Su Lee, M.D., Soyoung Shin, Ph.D., Dong-Chan Kim, Ph.D. , Donggun Seo, B.S.P.H., Hyeongjin Kweon, B.S., Hyein Kang, M.D, Sunggyun Park, M.D., Do-Hoon Kim, Ph.D., Namhee Ryoo, Ph.D., Soyoung Lee, Ph.D., and Jung Sook Ha, Ph.D.. Ann Lab Med -0001;0:. https://doi.org/10.3343/alm.2024.0226

Argonaute (AGO), a component of RNA-induced silencing complexes (RISCs), is a representative RNA-binding protein (RBP) known to bind with mature microRNAs (miRNAs) and is directly involved in post-transcriptional gene silencing. However, despite the biological significance of miRNAs, the roles of other miRNA-binding proteins (miRBPs) remain unclear in the regulation of miRNA loading, dissociation from RISCs and extracellular release. In this study, we performed protein arrays to profile miRBPs and identify 118 RBPs that directly bind to miRNAs. Among those proteins, the RBP quaking (QKI) inhibits extracellular release of the mature microRNA let-7b by controlling the loading of let-7b into extracellular vesicles via additional miRBPs such as AUF1 (also known as hnRNPD) and hnRNPK. The enhanced extracellular release of let-7b after QKI depletion activates Toll-like receptor 7 (TLR7) and promotes the production of proinflammatory cytokines in recipient cells, leading to brain inflammation in the mouse cortex. Thus, this study reveals the contribution of QKI to the inhibition of brain inflammation via regulation of extracellular let-7b release.

Yun SY, et al. Yonsei Med J. 2022 Dec;63(12):1138-1143. https://doi.org/10.3349/ymj.2022.0271

Blood and serum N-glycans can be used as markers for cancer diagnosis, as alterations in protein glycosylation are associated with cancer pathogenesis and progression. We aimed to develop a platform for breast cancer (BrC) diagnosis based on serum N-glycan profiles using MALDI-TOF mass spectroscopy. Serum N-glycans from BrC patients and healthy volunteers were evaluated using NosQuest’s software “NosIDsys.” BrC-associated “NosID” N-glycan biomarkers were selected based on abundance and NosIDsys analysis, and their diagnostic potential was determined using NosIDsys and receiver operating characteristic curves. Results showed an efficient pattern recognition of invasive ductal carcinoma patients, with very high diagnostic performance [area under the curve (AUC): 0.93 and 95% confidence interval (CI): 0.917–0.947]. We achieved effective stage-specific differentiation of BrC patients from healthy controls with 82.3% specificity, 84.1% sensitivity, and 82.8% accuracy for stage 1 BrC and recognized hormone receptor-2 and lymph node invasion subtypes based on N-glycan profiles. Our novel technique supplements conventional diagnostic strategies for BrC detection and can be developed as an independent platform for BrC screening.