Pakornkiat Tanasuka

Cholangiocarcinoma (CCA) in Northeast Thailand is characterized by late diagnosis and poor prognosis, creating a critical need for effective early-detection biomarkers. This study utilized a multi-omics approach to identify novel diagnostic targets and improve CCA screening. Initial serum proteomic and transcriptomic analyses revealed significant upregulation of the luteinizing hormone/choriogonadotropin receptor (LHCGR) in CCA patients, correlating with advanced disease stages. Interaction network analysis subsequently identified its circulating ligand, beta-human chorionic gonadotropin (β-hCG), as a highly translatable clinical target. The protein expression of β-hCG was assessed via immunohistochemistry (IHC) in 100 tissue samples, and serum levels of β-hCG, alongside routine markers (CA19-9, AFP, and CEA), were quantified in a cohort of 405 individuals, including 153 CCA patients. IHC confirmed significantly higher β-hCG expression in tumor tissues compared to adjacent areas (p < 0.0001). Serum β-hCG levels were significantly elevated in CCA patients and correlated with tumor volume and reduced overall survival. Diagnostically, a combined multiparameter panel (β-hCG, carbohydrate antigen 19-9, carcinoembryonic antigen, and alpha-fetoprotein) yielded excellent accuracy in distinguishing CCA from healthy controls (AUC: 0.962) and hepatocellular carcinoma cases (AUC: 0.890). However, discriminatory efficiency was notably lower when differentiating CCA from benign biliary diseases (AUC: 0.680) and liver metastases (AUC: 0.705). In conclusion, activation of the LHCGR signaling axis is a novel pathophysiological feature in CCA. When integrated into a multi-marker blood panel, circulating β-hCG serves as a valuable complementary risk-stratification and prognostic tool, though further optimization is required to overcome limited specificity in the presence of confounding liver pathologies before routine clinical implementation.

Background: Cholangiocarcinoma (CCA) is a deadly cancer often detected late. Current diagnostic methods, such as ultrasound and invasive biopsies, have limitations; there is a critical need for a rapid, minimally invasive and effective strategy for the early diagnosis and staging of CCA. Methods: We aimed to address this need using serum samples and label-free surface-enhanced Raman spectroscopy (SERS) combined with machine learning. CCA development was induced in hamsters using a combination of Opisthorchis viverrini infection and administration of N -nitrosodimethylamine, with induction time courses spanning 1–5 month(s). Normal and pathological stages (inflammation, precancerous lesion, and CCA) were assigned based on histopathological features, as well as the expression of cytokeratin 19 and alpha-fetoprotein. Raman spectra were subjected to dimensionality reduction using principal component analysis, and diagnostic clusters were acquired using partial least-squares discriminant analysis. Results: Histopathological analysis confirmed a clear path towards CCA, initiated by marked inflammation, progressing to include significant cholangiofibrosis and cholangiofibroma in the precancerous stage, and culminating in definitive CCA tumor development. The integration of SERS and machine learning achieved a diagnostic sensitivity of 93%, specificity of 95%, and accuracy of ≥ 67% for precancerous lesions and CCA, with an area under the receiver operating characteristic curve exceeding 0.67. Conclusions: Our findings demonstrate that this cost-effective, label-free SERS approach can accurately detect precancerous and cancerous stages of cholangiocarcinoma in a hamster model, highlighting its strong potential for future development as a community-based screening tool.

Cholangiocarcinoma (CCA), particularly when associated with Opisthorchis viverrini infection, is often diagnosed at a late stage and exhibits high resistance to chemotherapy, notably gemcitabine. While kinesin family member 18A (KIF18A) is upregulated in opisthorchiasis-associated CCA, its precise function, especially in gemcitabine-resistant CCA, remains largely unexplored. Herein, expression of KIF18A in relation to survival and progression was assayed by TCGA database mining and immunohistochemistry of a tissue microarray derived from 84 CCA patients. For functional study, KIF18A was suppressed in gemcitabine-resistant CCA cells (KKU-213B^GemR) using a CRISPR/Cas9 technique, followed by cellular and molecular analyses. Our results showed that KIF18A was highly expressed in CCA tissues compared to normal counterparts. Its expression was significantly correlated with tumor size and histological type of CCA but not with overall survival time. In vitro, KIF18A expression levels were increased in CCA cell lines, particularly KKU-213B^GemR. Suppression of KIF18A significantly inhibited colony formation, migration and invasion by KKU-213B^GemR cells. In addition, KIF18A knockdown led to a significant increase in the sub-G1 population, indicating the occurrence of cellular apoptosis. Flow cytometry confirmed that suppression of KIF18A significantly induced early apoptotic cell death of KKU-213B^GemR cells. Suppression of KIF18A dramatically downregulated the expression of key oncogenic and survival signaling proteins, including PI3K (total and p-PI3K), Akt (total and p-Akt), mTOR (total and p-mTOR), NF-κB (total and p-NF-κB) and Bcl-2 in KKU-213B^GemR cells. Taken together, our findings suggest that KIF18A plays crucial roles in promoting the progression and survival of gemcitabine-resistant CCA cells, partly by modulating PI3K/Akt/mTOR and NF-κB pathways. Therefore, despite its lack of prognostic utility, KIF18A represents a promising therapeutic target for improving treatment outcomes in CCA patients, especially those who do not respond to gemcitabine treatment.