IQUIBICEN   23947
INSTITUTO DE QUIMICA BIOLOGICA DE LA FACULTAD DE CIENCIAS EXACTAS Y NATURALES
Unidad Ejecutora - UE
congresos y reuniones científicas
Título:
Early metabolic rewiring of prostate cancer cells triggered by bone progenitors defines survival of metastatic prostate cancer.
Autor/es:
LAVIGNOLLE, ROSARIO; BIZZOTTO, JUAN; SENIUK, ROCIO; COTIGNOLA, JAVIER; ANSELMINO, NICOLÁS; LABANCA, ESTEFANIA; PASCUAL, GASTON; NAVONE, NORA; GUERON, GERALDINE; SANCHIS, PABLO; SABATER, AGUSTINA; LAGE VICKERS, SOFIA; TORO, AYELÉN; VAZQUEZ, ELBA
Lugar:
New Orleans
Reunión:
Congreso; AACR Anual Meeting 2022; 2022
Resumen:
Bone hosts the 88% of Prostate Cancer (PCa) metastases and no curative therapy is currently available for this stage. Arrival of PCa cells to the bone homing organ is accompanied by a metabolic adaptation, which may be mediated by bone secreted factors. Herein, we sought to identify key metabolic genes fueling PCa bone metastasis and soluble factors secreted by bone cells leading to the metabolic rewiring of tumoral cells. By an indirect transwell co-culture system of PCa (PC3) and bone progenitor cells (MC3T3, pre-osteoblasts; or Raw264.7, pre-osteoclasts) we analyzed the transcriptome (RNA-seq) of PC3 cells modulated by soluble factors released from bone precursors. GSEA showed a strong activation of lipid metabolism, including PPAR and PI3K-Akt pathways, fat absorption and digestion. We then performed a Principal Component Analysis using transcriptomic data from human PCa and bone metastasis samples (GSE74685), showcasing that those metabolic genes that appeared significantly dysregulated in the co-culture model could accurately cluster samples by their tissue of origin in two defined groups: primary PCa and bone metastasis. This result was confirmed by an unsupervised clustering analysis, highlighting that the transcriptional metabolic profile triggered in the in vitro model has a clinical correlate in human bone metastasis samples. Interestingly, when performing a survival analysis for those genes in the SU2C-PCF dataset, we observed that 4 lipid-associated genes, PPARA, VDR, SLC16A1 and GPX1, correlated with a shorter overall survival time, and appeared as independent risk-predictors of death (HR: 4.96, 2.85, 3.93 and 3.67, respectively; P