Abstract 5031: Identification of predictive/prognostic biomarkers in metastatic castration-resistant prostate cancer patients using plasma cell-free total RNA-sequencing
Authors: Giorgia Gurioli, Milena Urbini, Alessandra Virga, Chiara Casadei, Emilio Francesco Giunta, Nicole Brighi, Michela Cortesi, Michele Zanoni, Sara Bravaccini, Giovanni Martinelli, Paola Ulivi, Ugo De Giorgi
Journal: Cancer Research (2024)

Abstract Background Metastatic castration-resistant prostate cancer (mCRPC) is a heterogeneous disease that is still lacking an optimal patient selection strategy and a validated sequence of therapies. Therefore, there is an urgent need to identify non-invasive biomarkers to guide treatment choice in a perspective of personalized medicine. Plasma cell-free RNA profiling has emerged as a tool to investigate potential liquid biopsy biomarkers. In this study, we aimed to evaluate a method to capture total RNA content deriving from plasma and to identify potential biomarkers for mCRPC. Methods Plasma samples of 41 mCRPC patients treated with first line Abiraterone or Enzalutamide and 7 healthy donors were collected and stored from 2015 to 2022. Plasma cell-free RNA was purified using miRNeasy Serum/Plasma Advanced Kit (Qiagen) with DNase treatment. Bioanalyzer (Agilent) was used for the evaluation of RNA content and integrity profile of the samples. Sequencing libraries were generated using SMARTer Stranded Total RNA-Seq Kit v3 - Pico Input Mammalian (Takara Bio). An average of 80 millions reads pairs were sequenced on Novaseq 6000 (Illumina) using 100 bpx2 approach. After demultiplexing, reads were trimmed and aligned on hg19. Sequencing metrics were evaluated using Picard. Kallisto was used for gene expression analysis. Results A median of 10x109 bases per sample were aligned on hg19, of which a mean of 45% were located on coding or UTR regions. Storage time was investigated as a potential variable for RNA content and sequencing metrics, but no difference related to the year of storage was found. Unsupervised principal component analysis confirmed the absence of batch effects (including storage and sequencing analysis). PC1 seemed to reflect the different tumor RNA content of each sample, in which healthy donors and cancer patients were distinguished. Higher androgen receptor (AR) gene expression was found in mCRPC patients compared to healthy donors. Conclusions Despite enormous interest in extracellular nucleic acids, RNA-sequencing methods for total RNA content outside cells are rare and not standardized. In this study, we found a method to identify plasma non-invasive RNA biomarkers in mCRPC samples, retrieving coding and non-coding RNAs. Case series enlargement and differential gene expression analyses are ongoing. Citation Format: Giorgia Gurioli, Milena Urbini, Alessandra Virga, Chiara Casadei, Emilio Francesco Giunta, Nicole Brighi, Michela Cortesi, Michele Zanoni, Sara Bravaccini, Giovanni Martinelli, Paola Ulivi, Ugo De Giorgi. Identification of predictive/prognostic biomarkers in metastatic castration-resistant prostate cancer patients using plasma cell-free total RNA-sequencing [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5031.