Cholangiocarcinoma (CCA) is a fatal disease often detected late in unresectable stages. Currently, there are no effective diagnostic methods or biomarkers to detect CCA early with high confidence. Analysis of tumor-derived extracellular vesicles (tEVs) harvested from liquid biopsies can provide a new opportunity to achieve this goal. Here, an advanced nanoplasmonic sensing technology is reported, termed FLEX (fluorescence-amplified extracellular vesicle sensing technology), for sensitive and robust single EV analysis. In the FLEX assay, EVs are captured on a plasmonic gold nanowell surface and immunolabeled for cancer-associated biomarkers to identify tEVs. The underlying plasmonic gold nanowell structures then amplify EVs' fluorescence signals, an effective amplification process at the single EV level. The FLEX EV analysis revealed a wide heterogeneity of tEVs and their marker levels. FLEX also detected small tEVs not detected by conventional EV fluorescence imaging due to weak signals. Tumor markers (MUC1, EGFR, and EPCAM) are identified in CCA, and this marker combination is applied to detect tEVs in clinical bile samples. The FLEX assay detected CCA with an area under the curve of 0.93, significantly better than current clinical markers. The sensitive and accurate nanoplasmonic EV sensing technology can aid in early CCA diagnosis.
Background: Pancreatic cancer is the most dreadful malignant tumor and expected becoming the second cause of death in 2030. Despites of vigorous studies, there were no definitive prognostic biomoleculars marker for pancreatic cancer. Herein, we already established primary pancreatic cancer cell lines from the real patients of pancreatic cancer, using conditionally reprogrammed cell culture (CRC). We tried to find novel prognostic biomarkers with multi-omics analysis of our primary pancreatic cancer cell lines. Methods: In this study, we selected pancreatic cancer prognostic markers using established CRCs and FFPE samples and validated the molecular mechanism of LXN. As the first step, we performed both transcriptome and proteome analysis using RNA sequencing and liquid chromatography-tandem mass spectrometry (LC/MS-MS) with 6 primary pancreatic cancer cell lines established by CRC. After analysis, we mined several candidate markers of prognosis including latexin (LXN) and sialic acid acetylesterease (SIAE). And we validated these markers clinicopathologically using immunohistochemical (IHC) staining of 136 tissues from a different set of pancreatic cancer patients. And we confirmed the knock-down effect of LXN using siLXN in pancreatic cancer cells. Results: We selected 2 highly prognostic markers with LXN and SIAE after transcriptome and proteome analysis. In these genes, high LXN expression group showed longer median overall survival (OS) than low expression group, respectively (14.8 vs. 10.4 months, P-value=0.28), respectively. For the evaluation of IHC, we established 3D organoid model using CRCs and confirmed the correlation between mRNA expression and protein expression with western blotting and IHC. The expression of Akt/mTOR was decreased after siLXN treatment compared to control groups. In order to validation as a prognostic marker, we stained formalin-fixed, paraffin-embedded (FFPE) slide from 136 pancreatic cancer patients. After IHC analysis, LXN high group (H-score > 12) showed significantly longer OS than low LXN group (52 vs. 28 months, P-value = 0.043). Conclusion: In this study, we found LXN as a prognostic marker with inhibition of proliferation utilizing patient-derived cancer model and FFPE samples. Citation Format: Chan Hee Park, Hee Seung Lee, Jin Su Kim, Yoo Keung Tae, Jin Young Lee, Seungmin Bang. Functional evaluation of pancreatic cancer prognostic marker, LXN, utilizing multiomics analysis based on patient-derived cancer model. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3955.
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