Biomarkers in advanced prostate cancer: Liquid biopsy, ctDNA, and more

Nedim Ruhotina, MD

In this interview, Nedim Ruhotina, MD, outlines currently available as well as promising up-and-coming biomarkers for advanced prostate cancer. Dr Ruhotina is a urologist with Associated Medical Professionals and U.S. Urology Partners, based in Syracuse, New York.

Could you provide a concise overview of the current landscape of biomarkers used in the management of advanced prostate cancer?

The management of advanced prostate cancer has evolved significantly, driven in part by the integration of diverse biomarkers that guide treatment decisions from diagnosis through progression.

Historically, prostate specific antigen (PSA) has been the cornerstone of both screening and monitoring therapy. We not only track absolute PSA levels but can also assess features like PSA nadir and its kinetics, with lower nadir and longer time to nadir linked to better outcomes.

Alongside PSA genomic markers, mutations in the BRCA1 and BRCA2 genes have become increasingly important. These mutations, detected via germline, somatic tumor testing, or increasingly through liquid biopsies, help identify patients who may benefit from targeted therapy such as PARP inhibitors, ensuring that treatment options are tailored to the patient's genomic profile.

In addition to these well-established markers, prostate-specific membrane antigen [PSMA], has emerged as a critical biomarker for both staging and therapeutic targeting. PSMA testing, now often performed at the time of diagnosis, helps in not only accurately staging the disease but also in guiding the use of radioligand-based therapies in later stages. Similarly, the androgen receptor variant, AR-V7 splice variant, can be used as a predictive biomarker by identifying patients who are less likely to respond to AR guided therapies. For these patients, early transition to alternative treatments such as taxane-based chemotherapy may be more effective, highlighting the role of biomarkers in first-line treatment regimens.

What are the most promising emerging biomarkers for advanced prostate cancer, and what clinical impact are they expected to have?

Emerging biomarkers are poised to further refine patient management, with liquid biopsies and circulating tumor DNA (ctDNA) playing a pivotal role. ctDNA analysis is a noninvasive method that captures real-time genomic alterations in tumor cells, offering both predictive and prognostic insights. Beyond simply detecting actionable mutation, recent research has focused on ctDNA tumor fraction, the proportion of cell-free DNA that originates from tumor cells. This metric can serve as an indicator of tumor burden and has shown promise as a prognostic tool. Higher ctDNA fractions have been associated with worse overall survival and can signal emerging treatment resistance well before conventional markers like PSA or imaging revealed changes. By serially monitoring ctDNA tumor fractions, clinicians can potentially adjust therapeutic strategies in a timely manner, paving the way for more adaptive and personalized treatment approaches.

The loss of the PTEN tumor suppressor gene is another target of interest, as its absence activates downstream the PI3K/AKT/ mTOR signaling pathways, one of the most significant cell growth and pro survival pathways in cancer amenable to therapeutic intervention.

Additionally, other promising biomarkers include genomic signatures such as the homologous recombination deficiency or HRD signature, which extend the predictive power beyond BRCA mutation by identifying broader deficiency in DNA repair mechanisms. These emerging biomarkers are currently under investigation, and large-scale prospective studies are needed for validating their clinical utility and integrating them into comprehensive decision support tools.

How do ctDNA biomarkers contribute to the diagnosis, prognosis, and treatment of advanced prostate cancer?

ctDNA has become an increasingly valuable tool in the management of prostate cancer. As a noninvasive method for tumor genotyping, ctDNA can be used across the disease spectrum, from initial diagnosis to later stages, to detect genomic alterations. This capability is especially important when tissue samples for somatic tumor genotyping are unavailable or insufficient, ensuring that clinicians obtain a comprehensive molecular profile at any point along the treatment pathway. The predictive utility of ctDNA extends to personalizing treatment decisions; for example, it can help forecast responses with targeted therapy such as PARP inhibitors and immune checkpoint inhibitors as well as identify suitable candidate for clinical trials.

One particularly interesting aspect of ctDNA is a measurement of ctDNA tumor fraction (TF), which represents the proportion of circulating cell free DNA that originates from tumor cells. Research indicates that a higher TF is associated with a greater tumor burden and correlates with prognosis factors such as overall survival, particularly in patients with metastatic castrate resistant prostate cancer. Monitoring changes in TF over time can offer early insights into treatment response or emerging resistance. This dynamic monitoring may enable clinicians to adjust therapeutic strategies such as switching from a third-generation antiandrogen to taxane-based chemotherapy or alternative therapies well before conventional markers such as PSA or imaging indicate progression.

How do you see the role of liquid biopsies evolving in the management of advanced prostate cancer in the next several years?

There is considerable excitement about the potential for liquid biopsies to transform disease monitoring and treatment response evaluation. Currently, clinicians rely primarily on PSA levels and imaging, but both methods have limitations. PSA responses can be inconsistent, and imaging, especially in the presence of extensive bony metastatic disease, may not provide a complete picture of the disease. Emerging evidence suggests that ctDNA tumor fraction monitoring could complement or even surpass these traditional methods by providing a more sensitive and specific indicator of treatment efficacy. By detecting early signs of resistance of progression, liquid biopsies can enable a timelier adjustment of therapy, ultimately allowing for real-time treatment personalization.

What are some of the challenges and limitations of the currently available biomarkers in the advanced prostate cancer space?

Prostate cancer inherently is a heterogeneous disease at the molecular level, which poses a challenge in interpreting biomarker data. Additionally, there is a lack of standardization of assays and cutoff values used to assess these biomarkers, complicating their integration into routine clinical practice. Another significant hurdle is the difficulty of combining multiple biomarkers into a unified clinical decision-making tool. Addressing these changes will require large-scale, prospective studies to validate their utility and concerted effort to reduce the cost and availability of advanced molecular testing.

How can clinicians best integrate biomarker data into clinical decision making for patients with advanced prostate cancer?

Most importantly, I think, continuous medical education is crucial for urologists to keep up with the complex and rapid advancements in biomarker research as well as their clinical implications. A multidisciplinary approach is always helpful for effectively interpreting biomarker data. Furthermore, developing robust clinical decision support tools that integrate multiple biomarkers along with clinical factors will be key. Real-world evidence and outcome analyses based on biomarker guided treatment strategies will also play significant roles in refining these approaches.

How would you envision the role of artificial intelligence (AI) in the development interpretation of biomarker data for advanced prostate cancer?

AI, particularly large language models, offers promising opportunities for enhancing the interpretation of unstructured data hidden in electronic medical records. AI algorithms excel in pattern recognition and can integrate diverse sources of information, including genomic data, imaging, and clinical records which could be used to create predictive models. Moreover, AI can streamline the collection and analysis of real-world data from electronic health records and other sources, playing a crucial role in biomarker development and validation by uncovering trends and outcomes. These tools could serve as decision aids, tailoring treatment decisions to individualized patient profiles by identifying subtle patterns that may not be immediately apparent to clinicians.

Is there anything you would like to add?

The integration of advance biomarkers, particularly ctDNA and the dynamic measurement throughout the disease course, heralds an exciting era in the management of advanced prostate cancer.With new drugs, evolving biomarkers, and the advent of AI, the potential for more precise and personalized treatment strategies is greater than ever. Although challenges remain, particularly regarding standardization, accessibility, as well as cost, the ongoing evolution of biomarker technology promises to significantly enhance patient outcomes.