Authors: Mini Thomas | Kaleb Byers | Daniel A. Sheik | Kelli Ann Ifuku | Michael Poderycki | Curtis Ramsey | Michele Yip-Schneider | Cássia Regina Oliveira Santos | C. Max Schmidt | Thi Hong Tran | Kimberly S. Kirkwood | Randall E. Brand | Mohammad Al‐Haddad | V. Jo Davisson
Source: Clinical Chemistry (article, 2025-10-01)
Field: Materials Science — Materials Chemistry

B-366 Determination of mucinous pancreatic cystic lesion dysplasia grade using a Surface-Enhanced Raman Spectroscopy (SERS)-enabled multi-analyte biomarker panel Abstract Background Pancreatic cystic lesions (PCLs), a subset of which have the potential to develop into pancreatic cancer, are increasingly detected on cross-sectional imaging and pose challenges to clinicians due to the lack of diagnostic tools capable of accurately stratifying their malignant potential. Non-mucinous PCLs, of which there are several subtypes, have very low malignant potential and typically do not require treatment if asymptomatic. On the other hand, mucinous PCLs have variable short- and long-term risk potential and therefore require active management with surveillance or surgical resection. To this end, Amplified Sciences previously secured CLIA regulatory clearance for PanCystProTM, a tri-analyte marker panel powered by an algorithm capable of distinguishing mucinous from non-mucinous PCLs from &amp;lt;50 µL of cyst fluid with a high negative predictive value. The current study builds upon this work by stratifying risk for the most common and worrisome mucinous cyst subtype, Intraductal Papillary Mucinous Neoplasms (IPMNs), using a multi-dimensional analyte panel consuming ultra-low sample volume. Methods Surface-Enhanced Raman Spectroscopy (SERS) a cutting-edge optical detection platform enables clinical diagnostics using ultra-low sample volumes. A novel multi-analyte panel utilizing Amplified Sciences’ highly sensitive proprietary SERS reporter dyes was developed and tested retrospectively in a blinded cohort of 66 histopathologically confirmed surgically resected IPMN cysts. Thirty-four IPMNs had low-grade dysplasia (LGD), twelve high-grade (HGD) and twenty invasive carcinomas, with the latter two diagnoses grouped together in the analysis given the clinical need to identify more aggressive IPMNs for potential surgical resection. The 6-marker panel incorporates a combination of enzymatic activity assays and mass-based (immuno-SERS or iSERS) assays. Results The biomarker panel, which includes an iSERS assay for neutrophil elastase (Figure 1), was tested against the 66-sample IPMN cohort, and a predictive machine learning algorithm distinguishing HGD/invasive- from LGD IPMNs was developed. This approach resulted in sensitivity of 97.1% and a negative predictive value (NPV) of 96.6%, along with specificity of 87.5% and a positive predictive value (PPV) of 89.2%. Overall accuracy was 92.4%. Importantly, the iSERS method using antibody pairs is analogous to traditional sandwich-based ELISA methods but without the requirement for an enzymatic amplification step for detection; moreover, the sensitivity of antibody-SERS dye reporter conjugates enables a drastic reduction in sample volume requirements (1-2 µL per marker). Conclusion The Amplified Sciences’ platform leverages SERS to quantitate multiple low-abundance biomarkers in ultra-low sample volumes. This property is particularly advantageous for PCLs and will enable rapid refinement of the current promising HGD-LGD panel, focusing on testing of multiple biologically relevant marker classes (inflammation, hypoxia, etc.). Future work includes clinical validation in a larger training set with sufficient statistical power and incorporating complementary clinical information into a predictive algorithm. Dysplasia ; Cyst ; Biomarker ; Pancreas ; Intraductal papillary mucinous neoplasm ; Medical diagnosis Advanced Nanomaterials in Catalysis