Multiplex protein analysis and ensemble machine learning methods of fine needle aspirates from prostate cancer patients reveal potential diagnostic signatures associated with tumour grade.
biomarkers
fine needle aspiration biopsy
immune signalling
machine learning
prostate cancer
proximity extension assay
Journal
Cytopathology : official journal of the British Society for Clinical Cytology
ISSN: 1365-2303
Titre abrégé: Cytopathology
Pays: England
ID NLM: 9010345
Informations de publication
Date de publication:
07 2023
07 2023
Historique:
revised:
06
02
2023
received:
01
12
2022
accepted:
16
02
2023
medline:
12
6
2023
pubmed:
26
2
2023
entrez:
25
2
2023
Statut:
ppublish
Résumé
Improved molecular diagnosis is needed in prostate cancer (PC). Fine needle aspiration (FNA) is a minimally invasive biopsy technique, less traumatic compared to core needle biopsy, and could be useful for diagnosis of PC. Molecular biomarkers (BMs) in FNA-samples can be assessed for prediction, eg of immunotherapy efficacy before treatment as well as at treatment decision time points during disease progression. In the present pilot study, the expression levels of 151 BM proteins were analysed by proximity extension assay in FNA-samples from 16 patients, including benign prostate lesions (n = 3) and cancers (n = 13). An ensemble data analysis strategy was applied using several machine learning models. Twelve potentially predictive BM proteins correlating with International Society of Urological Pathology grade groups were identified, among them vimentin, tissue factor pathway inhibitor 2, and integrin beta-5. The validity of the results was supported by network analysis that showed functional associations between most of the identified putative BMs. We also showed that multiple immune checkpoint targets can be assessed (eg PD-L1, CD137, and Galectin-9), which may support the selection of immunotherapy in advanced PC. Results are promising but need further validation in a larger cohort. Our pilot study represents a "proof of concept" and shows that multiplex profiling of potential diagnostic and predictive BM proteins is feasible on tumour material obtained by FNA sampling of prostate cancer. Moreover, our results demonstrate that an ensemble data analysis strategy may facilitate the identification of BM signatures in pilot studies when the patient cohort is limited.
Sections du résumé
BACKGROUND
Improved molecular diagnosis is needed in prostate cancer (PC). Fine needle aspiration (FNA) is a minimally invasive biopsy technique, less traumatic compared to core needle biopsy, and could be useful for diagnosis of PC. Molecular biomarkers (BMs) in FNA-samples can be assessed for prediction, eg of immunotherapy efficacy before treatment as well as at treatment decision time points during disease progression.
METHODS
In the present pilot study, the expression levels of 151 BM proteins were analysed by proximity extension assay in FNA-samples from 16 patients, including benign prostate lesions (n = 3) and cancers (n = 13). An ensemble data analysis strategy was applied using several machine learning models.
RESULTS
Twelve potentially predictive BM proteins correlating with International Society of Urological Pathology grade groups were identified, among them vimentin, tissue factor pathway inhibitor 2, and integrin beta-5. The validity of the results was supported by network analysis that showed functional associations between most of the identified putative BMs. We also showed that multiple immune checkpoint targets can be assessed (eg PD-L1, CD137, and Galectin-9), which may support the selection of immunotherapy in advanced PC. Results are promising but need further validation in a larger cohort.
CONCLUSIONS
Our pilot study represents a "proof of concept" and shows that multiplex profiling of potential diagnostic and predictive BM proteins is feasible on tumour material obtained by FNA sampling of prostate cancer. Moreover, our results demonstrate that an ensemble data analysis strategy may facilitate the identification of BM signatures in pilot studies when the patient cohort is limited.
Substances chimiques
Biomarkers
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
286-294Subventions
Organisme : Cancerföreningen i Stockholm
ID : CAN 2015/401
Organisme : Cancerföreningen i Stockholm
ID : CAN 2018/597
Organisme : Cancerföreningen i Stockholm
ID : CAN2021/1469 Pj01 H
Organisme : Familjen Erling-Perssons Stiftelse
Organisme : Karolinska FOUU funding
ID : #962324
Organisme : Percy Falks Stiftelse för Forskning Beträffande Prostata- och Bröstcancer
Organisme : Stockholm County Council
ID : #20160287
Organisme : Stockholm County Council
ID : #20180404
Organisme : Swedish Prostate Cancer Association
Informations de copyright
© 2023 The Authors. Cytopathology published by John Wiley & Sons Ltd.
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