Is Genomic Risk Stratification Overtaking Clinical Stage in Prostate Cancer?

Prostate cancer is one of the most common cancers among men, and treatment generally relies on clinical staging. However, cases showing unexpected biological behavior despite their clinical stage have always attracted scientists' attention. For example, patients with biologically aggressive early-stage disease, or advanced disease following a milder-than-expected course, were often not fully understood through traditional clinical assessments. These cases offer important insights into cancer's biological diversity and complexity.

In recent years, integrating genetic information into prostate cancer diagnosis and treatment has helped us better understand such cases. Advanced biomarkers, such as genomic risk stratification, are emerging as factors that complement clinical staging or may sometimes be more decisive. This article discusses the importance, definitions, and practical application of clinical staging and genomic risk stratification in prostate cancer.

Clinical Stage: Definition and Importance Clinical stage describes how far prostate cancer has spread in the body. The TNM system (Tumor, Node, Metastasis) assesses tumor size and extent within the prostate (T), spread to nearby lymph nodes (N), and the presence of distant metastases (M). Clinical staging is fundamental to treatment planning and predicting prognosis (disease course). Early-stage disease can generally be controlled with local treatments such as surgery or radiotherapy, whereas advanced disease requires more aggressive, systemic treatment.

Genomic Risk Stratification: Definition, Importance, and Procedure Genomic risk stratification analyzes the genetic makeup of prostate cancer cells to predict their behavior, aggressiveness, and treatment response. Genomic tests examine DNA from cancer cells to detect specific gene changes that may affect prognosis. This classification allows more precise prediction of disease course and the development of personalized treatment strategies. In particular, it shows that patients with high genomic risk may need more aggressive treatment even in early-stage prostate cancer. It therefore complements traditional clinical staging for more comprehensive patient management.

A Study Integrating Genomic and Clinicopathological Risk Groups

Society of Urologic Oncology Annual Meeting 2023 featured a study showing that genomic risk distributions among prostate cancer patients could vary widely across clinical stage groups. Researchers suggest that integrating genomic and clinicopathological risk categories may improve predictions of clinical outcomes.

The study used two large population-based tumor databases: the Decipher Genomics Resource for Intelligent Discovery (GRID; 50,981 people) and the Michigan Urological Surgery Improvement Collaborative (MUSIC; 1,584 people). The Decipher genomic classifier was used to examine genomic risk distributions in detail across these two prostate cancer cohorts. This highlights the importance of examining patients' genetic makeup and its effects on cancer risk.

Median age was 68 in GRID and 66 in MUSIC. Median prostate-specific antigen was 6.2 ng/mL in GRID and 10.5 ng/mL in MUSIC.

Study Details

In GRID, 31.4% of patients were classified as high genomic risk, 18.5% as intermediate, and 50.2% as low. MUSIC showed a similar distribution: 35.7%, 16.2%, and 47.9%, respectively.

Genomic risk varied across all STAR-CAP stages in both cohorts. For example, among stage IA-IC patients, 18.7% in GRID and 17.7% in MUSIC had high genomic risk.

Researchers also found wide variation in estimated prostate cancer-specific mortality (0.1% to 49.2%) and distant metastasis (0.3% to 73.4%) according to clinical-genomic risk.

Disease Stage Is Reclassified

Integrating Decipher risk estimates with STAR-CAP stages produced substantial stage reclassification. This included moving patients up or down at least one stage (25.6% and 45.5%, respectively), and up or down at least two stages (7.2% and 11.8%, respectively).

The researchers describe their work as follows: “We found wide variation in genomic risk distributions within and between clinical stage groups, suggesting that integrating genomic and clinicopathological risk groups may provide more differentiated predictions of relevant clinical outcomes. These findings may help individualize risk assessment by providing patients with more precise prognostic estimates.”

The study's importance lies in showing how integrating genomic risk factors beyond clinical stage may allow more accurate prediction of prostate cancer prognosis. By suggesting that genomic classification may be more important than clinical stage, it supports reassessing risk in patients with early-stage disease but high genomic risk. This may be an important step toward personalized treatment strategies, particularly in prostate cancer.

Another Important Study for Early-Stage Patients Under Active Surveillance

Another study discussed at the same meeting assessed the association between Decipher genomic classifier scores obtained from patients' initial prostate biopsies and their transition from active surveillance to active treatment. It found that Decipher score was an important, independent indicator of referral for treatment among patients under active surveillance.

The Decipher genomic classifier test is covered by Medicare for early-stage (localized) prostate cancer in the United States.  

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A New Era in Cancer Classification

The value of genomic risk stratification extends beyond prostate cancer to many other cancer types. Research shows that different cancers share some genetic changes, often involved in regulating gene expression. Such findings may help us better understand genetic relationships between cancer types and cancer development more broadly, shedding light on common genetic foundations.

The current research resembles gene signature studies because it analyzes genetic data to determine how genetic changes affect cancer risk and identify relationships across many cancer types. These studies offer detailed insights into cancer's molecular biology and genetic basis and may open new paths in diagnosis and treatment.

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