71: Biosensor-based classification of chronic post-surgical pain using serum responses.

Topic: Basic Science
Subtopic: Pain category (ICD-11), Chronic postsurgical pain, , , , , , , , Omics (Proteomics/Metabolomics/Transcriptomics/Genomics),

Background and Aims: Chronic post-surgical pain (CPSP) remains difficult to identify objectively, as current assessment relies largely on behavioural and subjective measures that provide limited insight into the underlying biology (Fuller et al., 2023; Mackey et al., 2025). Circulating serum factors may reflect pathological processes associated with chronic pain and could therefore be exploited in functional biosensor systems (Gerdle & Ghafouri, 2020; Mackey et al., 2025). We investigated whether the nociceptor-like 50B11 cell line could detect and classify serum-associated signatures of CPSP across longitudinal stages following surgical injury, supported by complementary molecular profiling (Matusica et al., 2021).

Methods: Serum samples were collected from rats subjected to the Brennan post-surgical pain model at 1, 2, and 8 weeks after surgery, alongside sham-operated controls (Brennan et al., 1996). Serum from additional neuropathic pain models was also included to enable comparative discrimination across pain states. Functional responses were assessed in 50B11 cells using calcium imaging following serum exposure. Quantitative features extracted from single-cell calcium responses (maximum fluorescence intensity, time to maximum fluorescence intensity, first and second derivative maxima, time to derivative maxima, activation time, and area under the curve) were used for machine-learning-based classification. Complementary serum proteomic data were analysed in R using DEP, including filtering, variance-stabilising normalisation, imputation, principal component analysis, and differential abundance testing (Feng et al., 2023). Exploratory pathway enrichment, gene ontology over-representation, and protein-protein interaction analyses were also performed, with transcriptomic profiling included as an additional discriminating layer.

Results: 50B11 cells exhibited distinct calcium signalling patterns in response to sera from CPSP, sham, and neuropathic pain models. Feature extraction identified distinctive response signatures across post-surgical pain stages, indicating that circulating serum signals evolve longitudinally after surgery. Machine-learning models classified calcium response profiles according to pain condition, supporting discrimination between CPSP-related and other chronic pain-associated serum signatures. Proteomic analyses identified temporal differences between CPSP and sham groups, while downstream enrichment and network analyses suggested evolving systemic biological responses following surgical injury. Transcriptomic profiling provided an additional complementary dataset for molecular characterisation and potential diagnostic or therapeutic targets in these pain states.

Conclusions: Collectively, these results establish the 50B11 cells as a potential functional serum biosensor platform for objective classification of post-surgical pain trajectories in preclinical models of CPSP. The integrated use of calcium imaging, machine learning, and multi-omics profiling demonstrates a robust framework for not only identifying biosignatures that distinguish transient from persistent pain states, but provide a proof-of-concept platform for advancing translational strategies for precision pain diagnostics associated with the development and persistence of post-surgical pain.

References: Brennan, T. J., Vandermeulen, E. P., & Gebhart, G. F. (1996). Characterization of a rat model of incisional pain. PAIN, 64(3), 493-502. https://doi.org/10.1016/0304-3959(95)01441-1
Feng, Z., Fang, P., Zheng, H., & Zhang, X. (2023). DEP2: an upgraded comprehensive analysis toolkit for quantitative proteomics data. Bioinformatics, 39(8). https://doi.org/10.1093/bioinformatics/btad526
Fuller, A. M., Bharde, S., & Sikandar, S. (2023). The mechanisms and management of persistent postsurgical pain. Frontiers in Pain Research, 4, 1154597.
Gerdle, B., & Ghafouri, B. (2020). Proteomic studies of common chronic pain conditions - a systematic review and associated network analyses. Expert Rev Proteomics, 17(6), 483-505. https://doi.org/10.1080/14789450.2020.1797499
Mackey, S., Aghaeepour, N., Gaudilliere, B., Kao, M. C., Kaptan, M., Lannon, E., Pfyffer, D., & Weber, K. (2025). Innovations in acute and chronic pain biomarkers: enhancing diagnosis and personalized therapy. Reg Anesth Pain Med, 50(2), 110-120. https://doi.org/10.1136/rapm-2024-106030
Matusica, D., Canlas, J., Martin, A., Yingkai, W., Marri, S., Erickson, A., Barry, C., Brierley, S., Best, G., & Michael, M. (2021). Differentiation of the 50B11 dorsal root ganglion cells into NGF and GDNF responsive nociceptor subtypes. Molecular Pain, 16.

Presenting Author: Benjamin R Hoy
Submitting Author: Benjamin Hoy

Senior Author: Dusan Matusica

IASP 2026 Global Year theme of Neuropathic Pain: Yes

• Benjamin R Hoy - Anatomy, Histology and Pathology, Flinders Medical Research Institute (FHMRI), College of Medicine and Public Health, Flinders University, Bedford Park, South Australia, Australia
• Wendy Imlach: PhD - Department of Physiology, Monash Biomedicine Discovery Institute, Monash University, Clayton, Victoria, Australia
• Michael J Roach: PhD - Anatomy, Histology and Pathology, Flinders Medical Research Institute (FHMRI), College of Medicine and Public Health, Flinders University, Bedford Park, South Australia, Australia
• Guy D'Angelo: MD - Anatomy, Histology and Pathology, Flinders Medical Research Institute (FHMRI), College of Medicine and Public Health, Flinders University, Bedford Park, South Australia, Australia
• Daniel Pincher: PhD - Anatomy and Human Biology, School of Pharmacy and Biomedical Science, College of Health Adelaide University, Adelaide, South Australia, Australia
• Christine Barry: PhD - Anatomy, Histology and Pathology, Flinders Medical Research Institute (FHMRI), College of Medicine and Public Health, Flinders University, Bedford Park, South Australia, Australia
• Nicolas H Voelcker: PhD - Drug Delivery, Disposition and Dynamics, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Victora, Australia
• Peter Hoffmann: PhD - Anatomy and Human Biology, School of Pharmacy and Biomedical Science, College of Health Adelaide University, Adelaide, South Australia, Australia
• Rainer V Haberberger: PhD - Anatomy and Human Biology, School of Pharmacy and Biomedical Science, College of Health Adelaide University, Adelaide, South Australia, Australia
• Dusan Matusica: PhD - Anatomy, Histology and Pathology, Flinders Medical Research Institute (FHMRI), College of Medicine and Public Health, Flinders University, Bedford Park, South Australia, Australia