posted on 2025-10-23, 19:00authored byAdel T. Aref, Jason Grealey, Mohashin Pathan, Zainab Noor, Asim Anees, A.K.M. Azad, Daniela Lee Smith, Erin M. Humphries, Daniel Bucio-Noble, Jennifer M.S. Koh, Erin K. Sykes, Steven G. Williams, Ruth J. Lyons, Natasha Lucas, Dylan Xavier, Sumit Sahni, Anubhav Mittal, Jaswinder S. Samra, John V. Pearson, Nicola Waddell, Olga Kondrashova, Angela Chou, Loretta Sioson, Amy Sheen, Venkateswar Addala, Lesley Andrews, Jennifer Arena, Ray Asghari, Mo Ballal, Andrew P. Barbour, Claudio Bassi, Maria Beilin, Andrew V. Biankin, Nicola Blackburn, Mark E. Brooke-Smith, Diego Chacon Fajardo, Cecilia R. Chambers, David K. Chang, Lorraine A. Chantrill, John Chen, Angela Chou, Andrew D. Clouston, Vincenzo Corbo, Peter H. Cosman, Thomas R. Cox, Amitabha Das, Stephan B. Dreyer, Tanya Dwarte, Krishna Epari, James R. Eshleman, Jonathan W. Fawcett, Kynan Feeney, David Fletcher, Cindy Forrest, Anthony J. Gill, Annabel Goodwin, Peter Grimison, Sean M. Grimmond, Michael Hatzifotis, David Herrmann, Hilda A. High, Peter Hodgkinson, Oliver Hofmann, Oliver Holmes, Ralph H. Hruban, Kasim Ismail, Nigel B. Jamieson, Gloria Jeong, Amber L. Johns, James G. Kench, Judy Kirk, Rita T. Lawlor, Conrad Leonard, Ruth J. Lyons, Duncan McLeod, R. Scott Mead, Neil D. Merrett, Anubhav Mittal, Sanjay Mukhedkar, Adnan Nagrial, Felicity Newell, Nan Q. Nguyen, Mehrdad Nikfarjam, Max Nobis, Katia Nones, Thomas J. O’Rourke, Marina Pajic, Virginia Papangelis, Nick Pavlakis, John V. Pearson, Brooke Pereira, Sean Porazinski, Daniel A. Reed, Shona Ritchie, Alice Russo, Andrew R. Ruszkiewicz, Jaswinder S. Samra, Charbel Sandroussi, Aldo Scarpa, Kellee Slater, Allan Spigellman, Alina Stoita, Michael Texler, Paul Timpson, Katherine Tucker, Claire Vennin, Nicola Waddell, David Williams, Christopher L. Wolfgang, Scott Wood, Chris Worthley, Nikolajs Zeps, Peter G. Hains, Phillip J. Robinson, Qing Zhong, Roger R. Reddel, Anthony J. Gill
<p>Supplementary Figure 7 shows the proteomic signature performance based on the Receiver operator characteristic curve analysis. (A) Receiver operator characteristic curve (ROC) at 1 year of follow-up for the proteomic signature (purple) and other clinically relevant variables for PDA within our cohort. (B) An Area Under the Curve (AUC) plot displays the AUC as a function of time for the proteomic risk score (purple) and other clinically relevant variables for PDA within our cohort.</p>
Funding
PanKind, The Australian Pancreatic Cancer Foundation (PanKind)
Pancreatic ductal adenocarcinoma (PDA) is an aggressive malignancy that lacks reliable biomarkers to guide treatment decisions. Effective prognostic tools are needed to improve its clinical management. We conducted a comprehensive proteomic analysis on 115 PDA patient samples with matched adjacent normal tissue. A 20-protein diagnostic panel was identified (LGALS1, ANXA2, LGALS3BP, CTSD, S100P, COL12A1, SFN, THBS2, CTHRC1, THBS1, SERPINB5, LAMC2, POSTN, CEACAM6, CTSE, PLEC, PKM, S100A11, TAGLN2, ALDOA). Consensus clustering analysis identified four prognostic proteomic subtypes. Subtypes with poorer prognoses exhibited upregulation of neutrophil degranulation, extracellular matrix remodeling, focal adhesion, Mesenchymal Epithelial Transition, collagen formation, and PI3K-Akt-mTOR-related pathways, indicating a predominance of basal-like and activated stromal features. In tumors with homologous recombination deficiency or Catalogue of Somatic Mutations in Cancer Signature-3, several immune-related proteins were enriched. An 18-protein (PURB, SDCBP2, CD2BP2, GALM, SERPINA3, OAS3, FAN1, ZPR1, KRT2, NUDT2, SMNDC1, SERPINA4, CUTA, WDR36, POSTN, CLEC11A, PEX14, and PI4KA) risk score was developed and validated using multicox regression analyses with LASSO regularization. The risk score demonstrated independent prognostic significance for overall survival and recurrence, and was validated in an independent proteomic dataset generated using a different proteomic technology. This study thus introduces four novel prognostic PDA subtypes, and an 18-protein risk score validated in an independent dataset, which shows promise for improving survival prediction and could serve as a valuable tool for personalized treatment guidance.
The findings from this study have significant implications for the future of pancreatic cancer management. By identifying a 20-protein panel with diagnostic and screening potential, this research provides a foundation for developing early detection tools for PDA, an aggressive cancer with limited treatment options. The classification of PDA into four proteomic subtypes with distinct prognostic outcomes paves the way for subtype-specific therapeutic approaches, allowing clinicians to better stratify patients based on their risk profiles. Additionally, the validated 18-protein risk score, which enhances survival prediction and operates independently of existing clinical variables, represents a promising tool for personalized prognostic assessments. Incorporating these proteomic-based biomarkers into clinical practice could improve diagnostic accuracy, guide individualized treatment decisions, and ultimately enhance patient outcomes in PDA. This study underscores the potential of proteomic profiling to improve cancer treatment by providing targeted, actionable insights into tumor biology.