Clinical Significance of Stratifying Prostate Cancer Patients Through Specific Circulating Genes

Academic Background

Prostate Cancer (PCA) is the most common cancer among men in North America and a leading cause of cancer-related mortality. Although many patients are diagnosed with organ-confined disease, 25-35% experience recurrence after curative treatments. This clinical heterogeneity highlights the current inability to accurately predict cancer aggressiveness at diagnosis, as well as the limitations of serum prostate-specific antigen (PSA) and imaging in detecting cancer spread until the disease reaches an advanced stage. Additionally, intra-tumoral heterogeneity, such as the presence of different prostate epithelial cell subtypes, complicates treatment, as current therapies do not target all cell subtypes.

To address this issue, researchers have explored the potential of stratifying prostate cancer patients through circulating genes in liquid biopsies. Liquid biopsy is a non-invasive method that reflects molecular changes in tumors through biomarkers such as circulating tumor cells (CTCs), extracellular vesicles (EVs), and cell-free DNA (cfDNA) in bodily fluids. This study aims to reveal tumor heterogeneity in prostate cancer patients by detecting specific gene expressions in blood and provide a basis for personalized treatment.

Source of the Paper

This paper was co-authored by Seta Derderian, Edouard Jarry, Arynne Santos, and others from institutions such as McGill University Health Center, McGill University, and Centre Hospitalier Régional et Universitaire de Lille. The paper was published in 2025 in the journal Molecular Oncology, titled Clinical Significance of Stratifying Prostate Cancer Patients Through Specific Circulating Genes.

Research Process and Results

1. Study Design and Gene Selection

The research team first constructed a panel of 57 genes representing different prostate cancer cell subtypes (e.g., luminal cells, neuroendocrine cells, and stem-like cells), drug targets, and genes associated with treatment resistance. These genes were selected based on systematic literature reviews and existing prostate cancer transcriptomic datasets. The team used quantitative reverse transcription polymerase chain reaction (RT-qPCR) to detect the expression levels of these genes in blood samples.

2. Sample Collection and Processing

The study included blood samples from 89 prostate cancer patients, comprising 16 patients before radical prostatectomy (RP), 26 patients who had undergone curative treatments without metastasis, and 28 metastatic patients (including 3 with hormone-sensitive prostate cancer and 25 with castration-resistant prostate cancer). Additionally, blood samples from 26 healthy controls were collected. Blood samples were collected in PAXgene tubes, and RNA was extracted and quality-checked before gene expression analysis using RT-qPCR.

3. Gene Expression Analysis and Results

The research team found that 44 out of the 57 genes were overexpressed in at least one patient’s blood sample. The expression patterns of these genes showed significant heterogeneity among patients at different disease stages. For example, patients with aggressive pathological features (e.g., intraductal carcinoma) at diagnosis exhibited more gene overexpression. In metastatic patients, specific cell subtype or resistance-related gene signatures were significantly associated with treatment, progression-free survival (PFS), and overall survival (OS).

4. Correlation Between Gene Expression and Clinical Features

The study revealed that the expression patterns of circulating genes in blood were closely related to patients’ clinical characteristics. For instance, patients with higher PSA levels at diagnosis were more likely to exhibit overexpression of multiple genes. Additionally, patients with intraductal carcinoma (IDC) at diagnosis showed overexpression of more neuroendocrine and stem-like genes, which correlated with poorer clinical outcomes.

5. Temporal Changes in Gene Expression

The study also tracked changes in gene expression over time in some patients during treatment. The results showed significant changes in gene expression patterns as treatment progressed and the disease advanced. For example, in one patient, genes that were overexpressed before radical prostatectomy disappeared 12 months post-surgery, while in another patient, gene expression patterns significantly changed after radiotherapy and androgen deprivation therapy (ADT).

6. Overexpression of Drug Target Genes

The study also found that 23 out of the 57 genes were drug target genes tested in clinical trials. These genes were overexpressed in 70% of the samples, suggesting their potential as targets for personalized therapy. For example, genes such as AURKA and KIF2C were significantly overexpressed in metastatic patients and associated with treatment resistance and disease progression.

Conclusions and Significance

This study demonstrates that stratifying prostate cancer patients by detecting specific circulating genes in blood can effectively guide personalized treatment. These genes not only reflect tumor heterogeneity but are also closely related to patients’ clinical characteristics, treatment responses, and prognosis. In particular, the overexpression of drug target genes provides potential opportunities for developing new targeted therapies.

Research Highlights

1. Non-Invasive Detection: The analysis of circulating gene expression in liquid biopsies offers a non-invasive method for stratifying prostate cancer patients.
2. Personalized Treatment: The study reveals correlations between specific genes and treatment responses or prognosis, providing new insights for personalized therapy.
3. Drug Target Discovery: The study identifies multiple potential drug target genes, offering a basis for future clinical trials and drug development.

Additional Valuable Information

The research team also validated the expression patterns of these genes in another cohort of 32 castration-resistant prostate cancer patients, with results consistent with the main study cohort, further supporting the clinical relevance of these genes. Additionally, the study emphasizes the importance of dynamically monitoring gene expression changes during treatment to better guide therapeutic decisions.

This research opens new avenues for precision medicine in prostate cancer. By analyzing circulating genes in liquid biopsies, it enables a better understanding of tumor heterogeneity and provides more personalized treatment options for patients.