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Prostate cancer (PC) is the 2nd most frequent cancer in men and the 5th leading cause of death worldwide1. Patient treatment and prognosis depend on the staging and grading (Gleason score) of the tumor, as evidenced by the higher 5-year survival rates of localized and low-grade tumors (Gleason grade 6) (99%) compared to high Gleason grades and metastatic tumors (31%)2.
PC local relapse and treatment failure have been linked to the characteristic high genetic intratumor heterogeneity of this tumor type3. Additionally, PC is considered to be a multifocal disease with several tumor foci exhibiting different morphological, histological, and molecular characteristics4, which may originate independently or derive from a common tumor cell ancestor5. Previous studies have shown that tumor evolution differs among patients based on specific genetic drivers that can promote metastasis or confine the cell lineage to the prostate5. Therefore, molecular characterization of the different tumor foci is crucial not only for providing a more accurate diagnosis and prognosis but also for tailoring effective and personalized treatment for the patient.
In this context, biomedical research and integrative multi-omics approaches are offering unprecedented opportunities to classify cancers into different subtypes, identify diagnostic and prognostic biomarkers, and discover markers related to treatment response. Furthermore, these approaches contribute to a better understanding of the biology of this disease6,7. Biological samples, whether tissues or biofluids, can be analyzed using various multi-omics platforms (genomics, transcriptomics, proteomics, metabolomics, etc.) to uncover the biological features underlying cancer pathophysiology, thereby addressing current limitations related to genetic and phenotypic heterogeneity6. However, it's important to consider that the quality of data derived from omics studies depends on the quality of the samples collected from tumors, their accurate characterization, and subsequent processing and storage8.
In this context, obtaining fresh PC tissue for research presents a methodological challenge due to the difficulty of successful tumor sampling9. Previous methods involved random sampling following radical prostatectomy, yielding poor results10. However, more recent approaches incorporate targeted protocols based on both magnetic resonance imaging (MRI) and biopsy data, resulting in improved efficacy in tumor sample collection11.
On the other hand, histopathological characterization of samples prior to their storage without significant tissue alteration also poses an interesting challenge. Consequently, in many cases, the histopathological determination of samples is performed after their analysis (e.g., HR 1H NMR metabolomic analysis)12. This practice entails unnecessary expenses, time consumption, and the loss of a significant number of samples that are eventually excluded from the analysis (for example, samples that, following histopathological analysis, turn out not to be tumor samples). In other cases, the histopathological characterization of samples is performed before their analysis. In fact, some previous studies have attempted to standardize methods for providing representative high-quality research samples from radical prostatectomy specimens for genomics and metabolomics13,14. Nevertheless, sampling efficiency is significantly higher when performed from already histologically confirmed sections (88%) that disrupt tissue, compared to when performed from unconfirmed sections (45%)1.
Here, a new methodology is presented to overcome these limitations, aiming to obtain fresh and well-characterized PC samples before storage in the Biobank. This method has been developed through collaborative efforts between different clinical services (Urology, Pathology, and the La Fe Hospital Biobank). It's important to highlight that Biobanks play an essential role in the collection, processing, preservation, and storage of biological samples while ensuring the high quality of samples and data, as well as compliance with ethical and legal requirements8,15,16.