IgG+ Extracellular Vesicles Measure Therapeutic Response in Advanced Pancreatic Cancer

Cells. 2022 Sep 8;11(18):2800. doi: 10.3390/cells11182800.

Abstract

(1) Background: Pancreatic ductal adenocarcinoma (PDAC) is expected to be the second-leading cause of cancer deaths by 2030. Imaging techniques are the standard for monitoring the therapy response in PDAC, but these techniques have considerable limits, including delayed disease progression detection and difficulty in distinguishing benign from malignant lesions. Extracellular vesicle (EV) liquid biopsy is an emerging diagnosis modality. Nonetheless, the majority of research for EV-based diagnosis relies on point analyses of EVs at specified times, while longitudinal EV population studies before and during therapeutic interventions remain largely unexplored. (2) Methods: We analyzed plasma EV protein composition at diagnosis and throughout PDAC therapy. (3) Results: We found that IgG is linked with the diagnosis of PDAC and the patient's response to therapy, and that the IgG+ EV population increases with disease progression and reduces with treatment response. Importantly, this covers PDAC patients devoid of the standard PDAC seric marker CA19.9 expression. We also observed that IgG is bound to EVs via the tumor antigen MAGE B1, and that this is independent of the patient's inflammatory condition and IgG seric levels. (4) Conclusions: We here propose that a population analysis of IgG+ EVs in PDAC plasma represents a novel method to supplement the monitoring of the PDAC treatment response.

Keywords: IgG; biomarker; extracellular vesicles; liquid biopsy; pancreatic cancer.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Antigens, Neoplasm
  • Biomarkers, Tumor
  • Carcinoma, Pancreatic Ductal* / therapy
  • Disease Progression
  • Extracellular Vesicles* / pathology
  • Humans
  • Immunoglobulin G
  • Pancreatic Neoplasms* / diagnosis

Substances

  • Antigens, Neoplasm
  • Biomarkers, Tumor
  • Immunoglobulin G

Grants and funding

J.E. was supported by grant 765492 from H2020-MSCA-ITN-2017. J.M. was supported by “Fundação para a Ciência e a Tecnologia” (PD/BD/105866/2014). S.B. was supported by the EMBO Installation Grant 3921. This work was supported by the Champalimaud Foundation and grant LCF/PR/HR19/52160014 from “La Caixa” Foundation. M.O.’s research is partially supported by National Funds through FCT, Fundação para a Ciência e a Tecnologia, projects 343 UIDB/04674/2020 (CIMA) and H2020-MSCA-RISE-2020/101007950, with the title ”DecisionES—Decision Support for the Supply of Ecosystem Services under Global Change,” funded by the Marie Curie International Staff Exchange Scheme.