Data di Pubblicazione:
2022
Citazione:
IDENTIFICATION OF NCAM1 AS A NOVEL PROGNOSTIC PROSTATE CANCER STEM CELL BIOMARKER / A. Castiglioni ; tutor: P. P. Di Fiore ; phd coordinator: S. Minucci. Dipartimento di Oncologia ed Emato-Oncologia, 2022 Dec 16. 34. ciclo, Anno Accademico 2022.
Abstract:
Serum prostate-specific antigen and Gleason grade are parameters routinely used for risk stratification in prostate cancer (PCa), but they present some limitations in the prediction of disease progression and in their use to guide clinical decision making. Prostate cancer stem cells (PCSCs) are widely considered to be responsible for tumorigenesis, disease progression and therapy failure. Their identification and characterization are mandatory for understanding the intricate intratumoral heterogeneity (spatial and molecular) of PCa and for developing relevant clinical tools to effectively manage patients and tailor therapy.
Here, we proposed the surface glycoprotein neural cell adhesion molecule (NCAM1/CD56), a known marker of neuroendocrine (NE) cells, as a novel PCSC marker that provides prognostic information and molecular insights into the process of tumorigenesis. NCAM1 defines clusters of cells enriched in proliferative inflammatory atrophy (PIA) regions, without NE traits (hereafter referred as NCAM1+). In a retrospective cohort of 406 PCa patients treated with radical prostatectomy (RP), we uncovered that NCAM1 is an independent prognostic marker for predicting distant metastasis and biochemical recurrence and its expression in radical prostatectomy biopsies concurred with diagnostic biopsies (concordance 87.6%).
Using the human cell lines, LNCaP (androgen-sensitive) and DU145 (androgen-insensitive), we found that NCAM1, but not other candidate PCSC markers, allowed FACS-based prospective purification of PCa cells displaying i) unique self-renewal ability in vitro, in a serial 3D-Matrigel organoid propagation assay, ii) tumorigenic potential upon limiting dilution transplantation in vivo. Relevant to real-life human PCa, we found that the ability to generate primary-derived organoids (PDOs) from dissociated high Gleason PCa biopsies exclusively resided in the purified NCAM1+ cell fraction, a property that was efficiently inhibited by treatment with an anti-NCAM1 blocking monoclonal antibody. We also found that the progressive development of adenocarcinoma in transgenic TRAMP mice crossed with NCAM1-/- mice was blocked at very early stages of tumorigenesis, indicating that genetic NCAM1 ablation prevents premalignant lesions to expand and progress to advanced stages.
PCa is a paradigm tumor model for clinical, spatial and molecular heterogeneity and this heterogeneity is reflected in the NCAM1+ cell population. Single cell-RNA sequencing (sc-RNASeq) of purified NCAM1+ cells (cell lines and primary human PCa biopsies) uncovered heterogenous cellular states reflected in several distinct clusters. Phylogenetic tree reconstruction of the evolutionary relationship among the different clusters along with single cell trajectory analysis revealed the existence of a cell fraction with basal traits (p63+/AR-/CD117+ cells) and a quiescent phenotype, sitting at the apex of the hierarchical structure of the NCAM1+ population. These cells were functionally characterized by Hedgehog signaling which drives NCAM1+/CD117+ -PCSC self-renewal ability. Moreover, they were molecularly characterized by a transcriptional signature called “Stem Score” which could have potential as a prognostic tool for identifying patients at risk of biochemical recurrence (BCR) and distant metastasis.
Androgen deprivation therapy (ADT) is the standard management for advanced PCa. Despite its initial effectiveness, the majority of patients relapse and develop castration resistant prostate cancer (CRPC), which is thought to be mediated by resistant PCSCs. ADT-treated NCAM1+ cells isolated from both dissociated human PCa biopsies and the LNCaP cell line enter into a quiescent state and retained the ability to generate organoids in vitro and tumors in vivo,
Tipologia IRIS:
Tesi di dottorato
Elenco autori:
A. Castiglioni
Link alla scheda completa: