Your browser doesn't support javascript.
loading
Profiling of extracellular vesicles of metastatic urothelial cancer patients to discover protein signatures related to treatment outcome.
Viktorsson, Kristina; Hååg, Petra; Shah, Carl-Henrik; Franzén, Bo; Arapi, Vasiliki; Holmsten, Karin; Sandström, Per; Lewensohn, Rolf; Ullén, Anders.
Afiliación
  • Viktorsson K; Department of Oncology-Pathology, Karolinska Institutet, Solna, Sweden.
  • Hååg P; Department of Oncology-Pathology, Karolinska Institutet, Solna, Sweden.
  • Shah CH; Department of Oncology-Pathology, Karolinska Institutet, Solna, Sweden.
  • Franzén B; Department of Pelvic Cancer, Genitourinary Oncology and Urology Unit, Karolinska University Hospital, Solna, Sweden.
  • Arapi V; Department of Oncology-Pathology, Karolinska Institutet, Solna, Sweden.
  • Holmsten K; Department of Oncology-Pathology, Karolinska Institutet, Solna, Sweden.
  • Sandström P; Department of Oncology-Pathology, Karolinska Institutet, Solna, Sweden.
  • Lewensohn R; Department of Oncology, Capio Sankt Görans Hospital, Stockholm, Sweden.
  • Ullén A; Department of Oncology-Pathology, Karolinska Institutet, Solna, Sweden.
Mol Oncol ; 16(20): 3620-3641, 2022 Oct.
Article en En | MEDLINE | ID: mdl-35838333
The prognosis of metastatic urothelial carcinoma (mUC) patients is poor, and early prediction of systemic therapy response would be valuable to improve outcome. In this exploratory study, we investigated protein profiles in sequential plasma-isolated extracellular vesicles (EVs) from a subset of mUC patients treated within a Phase I trial with vinflunine combined with sorafenib. The isolated EVs were of exosome size and expressed exosome markers CD9, TSG101 and SYND-1. We found, no association between EVs/ml plasma at baseline and progression-free survival (PFS). Protein profiling of EVs, using an antibody-based 92-plex Proximity Extension Assay on the Oncology II® platform, revealed a heterogeneous protein expression pattern. Qlucore bioinformatic analyses put forward a protein signature comprising of SYND-1, TNFSF13, FGF-BP1, TFPI-2, GZMH, ABL1 and ERBB3 to be putatively associated with PFS. Similarly, a protein signature from EVs that related to best treatment response was found, which included FR-alpha, TLR 3, TRAIL and FASLG. Several of the markers in the PFS or best treatment response signatures were also identified by a machine learning classification algorithm. In conclusion, protein profiling of EVs isolated from plasma of mUC patients shows a potential to identify protein signatures that may associate with PFS and/or treatment response.
Asunto(s)
Palabras clave

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Neoplasias de la Vejiga Urinaria / Carcinoma de Células Transicionales / Vesículas Extracelulares Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Mol Oncol Asunto de la revista: BIOLOGIA MOLECULAR / NEOPLASIAS Año: 2022 Tipo del documento: Article País de afiliación: Suecia

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Neoplasias de la Vejiga Urinaria / Carcinoma de Células Transicionales / Vesículas Extracelulares Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Mol Oncol Asunto de la revista: BIOLOGIA MOLECULAR / NEOPLASIAS Año: 2022 Tipo del documento: Article País de afiliación: Suecia