Multiplex protein analysis and ensemble machine learning methods of fine needle-aspirates from prostate cancer patients reveal potential diagnostic signatures associated with tumor grade.
Pontus RöbeckBo FranzénRafaele Cantera-AhlmanAnca DragomirGert AuerHåkan JorulfSven P JacobssonKristina ViktorssonRolf LewensohnMichael HäggmanSam LadjevardiPublished in: Cytopathology : official journal of the British Society for Clinical Cytology (2023)
Our pilot study represents a "proof of concept" and shows that multiplex profiling of potential diagnostic and predictive BM proteins is feasible on tumor 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.
Keyphrases
- prostate cancer
- data analysis
- machine learning
- genome wide
- high throughput
- radical prostatectomy
- single cell
- real time pcr
- convolutional neural network
- case report
- ultrasound guided
- randomized controlled trial
- artificial intelligence
- study protocol
- clinical trial
- dna methylation
- big data
- amino acid
- fine needle aspiration
- protein protein
- climate change