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Perera CJ, Hosen SZ, Khan T, Fang H, Mekapogu AR, Xu Z, Falasca M, Chari ST, Wilson JS, Pirola R, Greening DW, Apte MV. Proteomic profiling of small extracellular vesicles derived from mouse pancreatic cancer and stellate cells: Role in pancreatic cancer. Proteomics 2024:e2300067. [PMID: 38570832 DOI: 10.1002/pmic.202300067] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2023] [Revised: 02/17/2024] [Accepted: 03/18/2024] [Indexed: 04/05/2024]
Abstract
Small extracellular vesicles (sEVs) are cell-derived vesicles evolving as important elements involved in all stages of cancers. sEVs bear unique protein signatures that may serve as biomarkers. Pancreatic cancer (PC) records a very poor survival rate owing to its late diagnosis and several cancer cell-derived proteins have been reported as candidate biomarkers. However, given the pivotal role played by stellate cells (PSCs, which produce the collagenous stroma in PC), it is essential to also assess PSC-sEV cargo in biomarker discovery. Thus, this study aimed to isolate and characterise sEVs from mouse PC cells and PSCs cultured alone or as co-cultures and performed proteomic profiling and pathway analysis. Proteomics confirmed the enrichment of specific markers in the sEVs compared to their cells of origin as well as the proteins that are known to express in each of the culture types. Most importantly, for the first time it was revealed that PSC-sEVs are enriched in proteins (including G6PI, PGAM1, ENO1, ENO3, and LDHA) that mediate pathways related to development of diabetes, such as glucose metabolism and gluconeogenesis revealing a potential role of PSCs in pancreatic cancer-related diabetes (PCRD). PCRD is now considered a harbinger of PC and further research will enable to identify the role of these components in PCRD and may develop as novel candidate biomarkers of PC.
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Affiliation(s)
- Chamini J Perera
- Pancreatic Research Group, South Western Sydney Clinical Campus, School of Clinical Medicine, Faculty of Medicine and Health, UNSW Sydney, Sydney, Australia
- Ingham Institute of Applied Medical Research, Liverpool, NSW, Australia
| | - Sm Zahid Hosen
- Pancreatic Research Group, South Western Sydney Clinical Campus, School of Clinical Medicine, Faculty of Medicine and Health, UNSW Sydney, Sydney, Australia
- Ingham Institute of Applied Medical Research, Liverpool, NSW, Australia
| | - Tanzila Khan
- Pancreatic Research Group, South Western Sydney Clinical Campus, School of Clinical Medicine, Faculty of Medicine and Health, UNSW Sydney, Sydney, Australia
- Ingham Institute of Applied Medical Research, Liverpool, NSW, Australia
| | - Haoyun Fang
- Research Centre for Extracellular Vesicles, La Trobe University, Bundoora, Australia
- Baker Heart and Diabetes Institute, Melbourne, Australia
- Department of Cardiovascular Research, Translation and Implementation, School of Agriculture, Biomedicine and Environment, La Trobe University, Bundoora, Australia
- Department of Cardiometabolic Health, University of Melbourne, Melbourne, Australia
| | - Alpha Raj Mekapogu
- Pancreatic Research Group, South Western Sydney Clinical Campus, School of Clinical Medicine, Faculty of Medicine and Health, UNSW Sydney, Sydney, Australia
- Ingham Institute of Applied Medical Research, Liverpool, NSW, Australia
| | - Zhihong Xu
- Pancreatic Research Group, South Western Sydney Clinical Campus, School of Clinical Medicine, Faculty of Medicine and Health, UNSW Sydney, Sydney, Australia
- Ingham Institute of Applied Medical Research, Liverpool, NSW, Australia
| | - Marco Falasca
- Metabolic Signalling Group, Curtin Medical School Faculty of Health Sciences, Curtin University, Perth, Australia
| | - Suresh T Chari
- Department of Gastroenterology, Hepatology and Nutrition, M. D Anderson Cancer Centre, University of Texas, Houston, Texas, USA
| | - Jeremy S Wilson
- Pancreatic Research Group, South Western Sydney Clinical Campus, School of Clinical Medicine, Faculty of Medicine and Health, UNSW Sydney, Sydney, Australia
- Ingham Institute of Applied Medical Research, Liverpool, NSW, Australia
| | - Ron Pirola
- Pancreatic Research Group, South Western Sydney Clinical Campus, School of Clinical Medicine, Faculty of Medicine and Health, UNSW Sydney, Sydney, Australia
- Ingham Institute of Applied Medical Research, Liverpool, NSW, Australia
| | - David W Greening
- Research Centre for Extracellular Vesicles, La Trobe University, Bundoora, Australia
- Baker Heart and Diabetes Institute, Melbourne, Australia
- Department of Cardiovascular Research, Translation and Implementation, School of Agriculture, Biomedicine and Environment, La Trobe University, Bundoora, Australia
- Department of Cardiometabolic Health, University of Melbourne, Melbourne, Australia
| | - Minoti V Apte
- Pancreatic Research Group, South Western Sydney Clinical Campus, School of Clinical Medicine, Faculty of Medicine and Health, UNSW Sydney, Sydney, Australia
- Ingham Institute of Applied Medical Research, Liverpool, NSW, Australia
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Senadheera I, Larssen BC, Mak-Yuen YYK, Steinfort S, Carey LM, Alahakoon D. Profiling Somatosensory Impairment after Stroke: Characterizing Common "Fingerprints" of Impairment Using Unsupervised Machine Learning-Based Cluster Analysis of Quantitative Measures of the Upper Limb. Brain Sci 2023; 13:1253. [PMID: 37759854 PMCID: PMC10526214 DOI: 10.3390/brainsci13091253] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Revised: 08/14/2023] [Accepted: 08/21/2023] [Indexed: 09/29/2023] Open
Abstract
Altered somatosensory function is common among stroke survivors, yet is often poorly characterized. Methods of profiling somatosensation that illustrate the variability in impairment within and across different modalities remain limited. We aimed to characterize post-stroke somatosensation profiles ("fingerprints") of the upper limb using an unsupervised machine learning cluster analysis to capture hidden relationships between measures of touch, proprioception, and haptic object recognition. Raw data were pooled from six studies where multiple quantitative measures of upper limb somatosensation were collected from stroke survivors (n = 207) using the Tactile Discrimination Test (TDT), Wrist Position Sense Test (WPST) and functional Tactile Object Recognition Test (fTORT) on the contralesional and ipsilesional upper limbs. The Growing Self Organizing Map (GSOM) unsupervised machine learning algorithm was used to generate a topology-preserving two-dimensional mapping of the pooled data and then separate it into clusters. Signature profiles of somatosensory impairment across two modalities (TDT and WPST; n = 203) and three modalities (TDT, WPST, and fTORT; n = 141) were characterized for both hands. Distinct impairment subgroups were identified. The influence of background and clinical variables was also modelled. The study provided evidence of the utility of unsupervised cluster analysis that can profile stroke survivor signatures of somatosensory impairment, which may inform improved diagnosis and characterization of impairment patterns.
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Affiliation(s)
- Isuru Senadheera
- Centre for Data Analytics and Cognition, La Trobe Business School, La Trobe University, Melbourne, VIC 3086, Australia;
- Occupational Therapy, School of Allied Health, Human Services and Sport, La Trobe University, Melbourne, VIC 3086, Australia; (B.C.L.); (Y.Y.K.M.-Y.); (S.S.); (L.M.C.)
| | - Beverley C. Larssen
- Occupational Therapy, School of Allied Health, Human Services and Sport, La Trobe University, Melbourne, VIC 3086, Australia; (B.C.L.); (Y.Y.K.M.-Y.); (S.S.); (L.M.C.)
- Department of Physical Therapy, University of British Columbia, Vancouver, BC V6T 1Z3, Canada
| | - Yvonne Y. K. Mak-Yuen
- Occupational Therapy, School of Allied Health, Human Services and Sport, La Trobe University, Melbourne, VIC 3086, Australia; (B.C.L.); (Y.Y.K.M.-Y.); (S.S.); (L.M.C.)
- Neurorehabilitation and Recovery, Florey Institute of Neuroscience and Mental Health, Melbourne, VIC 3086, Australia
- Department of Occupational Therapy, St. Vincent’s Hospital Melbourne, Fitzroy, VIC 3065, Australia
| | - Sarah Steinfort
- Occupational Therapy, School of Allied Health, Human Services and Sport, La Trobe University, Melbourne, VIC 3086, Australia; (B.C.L.); (Y.Y.K.M.-Y.); (S.S.); (L.M.C.)
- Neurorehabilitation and Recovery, Florey Institute of Neuroscience and Mental Health, Melbourne, VIC 3086, Australia
| | - Leeanne M. Carey
- Occupational Therapy, School of Allied Health, Human Services and Sport, La Trobe University, Melbourne, VIC 3086, Australia; (B.C.L.); (Y.Y.K.M.-Y.); (S.S.); (L.M.C.)
- Neurorehabilitation and Recovery, Florey Institute of Neuroscience and Mental Health, Melbourne, VIC 3086, Australia
| | - Damminda Alahakoon
- Centre for Data Analytics and Cognition, La Trobe Business School, La Trobe University, Melbourne, VIC 3086, Australia;
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