Evolving transcriptomic fingerprint based on genome-wide data as prognostic tools in prostate cancer

Area of Science:

• Genomics and Molecular Biology
• Cancer Research
• Translational Medicine

Background:

• Prostate cancer (PCa) exhibits significant heterogeneity, making it challenging to identify patients at risk of metastasis and lethal disease.
• Accurate risk stratification is crucial for effective PCa management and requires understanding molecular drivers of tumor progression.
• Genomic fingerprinting offers a potential avenue for elucidating molecular variation and improving prognostic accuracy for PCa aggressiveness.

Purpose of the Study:

• To explore transcriptomic differences between patients with indolent prostate cancer and those who develop metastasis post-prostatectomy.
• To define a genomic fingerprint that can predict tumor aggressiveness and metastatic potential.
• To assess the utility of this fingerprint as an early prognostic biomarker in the post-radical prostatectomy setting.

Main Methods:

• Genome-wide expression data analysis of prostatectomy specimens.
• Differential gene expression analysis to identify transcriptomic signatures.
• Validation of the identified metastatic fingerprint in independent patient cohorts and metastasis lesions.

Main Results:

• A distinct transcriptomic fingerprint associated with higher metastasis risk was identified in prostatectomy specimens.
• Non-coding RNAs constituted nearly half of the fingerprint features, indicating their significant role in PCa progression.
• The metastatic fingerprint was validated in independent cohorts and metastasis lesions, confirming its prognostic value for early detection of metastatic changes.

Conclusions:

• Transcriptomic patterns indicative of metastatic prostate cancer can be detected early after radical prostatectomy.
• This metastatic fingerprint demonstrates prognostic potential for impacting PCa treatment management.
• The findings suggest the fingerprint could help avoid unnecessary therapies by accurately identifying patients at risk of progression.