PCa Commentary | Volume 195 – November 2024
PCa Commentary | Volume 195 – November 2024 Posted by Edward Weber | November 2024 NEW...
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Topic: Biomarkers
Biomarkers for Radiation Therapy
Peter F. Orio III, DO, MS, focuses on the evolving role of biomarkers in radiation oncology, particularly for prostate cancer. He asserts that biomarkers serve as biological indicators that help predict and monitor responses to treatment, thereby optimizing therapeutic outcomes and reducing toxicity.
In this 12-minute presentation, Dr. Orio categorizes radiation biomarkers into diagnostic, predictive, prognostic, and monitoring types, emphasizing their distinct roles in disease prediction, treatment response, and patient prognosis. Orio provides examples and discusses how these tools influence radiation planning and decision-making across various medical disciplines, including radiation oncology, medical oncology, and surgery.
The presentation underscores that while many biomarkers are prognostic, the future lies in their predictive capabilities, which are crucial for truly personalized treatment.
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Cardiometabolic Health for Men with Advanced Prostate Cancer: Lessons Learned and Future Directions
Andrew W. Hahn, MD, addresses cardiometabolic health in men with advanced prostate cancer, focusing on the impacts of hormone therapy and strategies for managing cardiovascular risks.
In this 10-minute talk, Dr. Hahn highlights the common overlap of prostate cancer and cardiometabolic risk factors and underscores the necessity of evaluating cardiovascular risk in prostate cancer patients. He reviews data indicating that androgen deprivation therapy (ADT) can indirectly increase cardiovascular risks by altering body composition and intensifying metabolic syndrome. Adding androgen receptors nearly doubles cardiovascular event risk. Despite FDA advisories, guidelines, and the availability of cardiovascular risk assessments, many patients undergoing ADT lack appropriate cardiovascular monitoring.
Dr. Hahn highlights future directions in identifying men at heightened risk for cardiovascular events using imaging and genomic biomarkers. Promising approaches include myocardial perfusion PET scans and exploring genomic markers that correlate with cardiovascular toxicity in hormone therapy. Managing cardiometabolic health in advanced prostate cancer requires careful risk assessment and personalized approaches. Biomarkers are needed to effectively predict cardiovascular complications from hormone therapy.
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Advances and Controversies in Theranostic Approaches to Prostate Cancer
Eric M. Rohren, MD, PhD, analyzes how theranostics—combining therapeutic and diagnostic processes—are reshaping prostate cancer management. For example, prostate-specific membrane antigen (PSMA), used as a biomarker for both imaging and targeted therapy in PSMA-targeted PET scans, offers precise tumor localization, significantly enhancing diagnostic accuracy. PSMA-targeted radiopharmaceuticals such as 68Ga-PSMA-11 for PET imaging and 177Lu-PSMA-617 for therapy have been shown to improve detection rates and treatment outcomes, particularly in metastatic and castration-resistant prostate cancer.
Despite these advancements, Dr. Rohren acknowledges the challenges in theranostic approaches. The variability in PSMA expression among patients can impact the effectiveness of both imaging and therapy. Additionally, he discusses the potential side effects and toxicity associated with radioligand therapy, emphasizing the need for careful patient selection and monitoring.
Dr. Rohren also explores the ethical and regulatory considerations in the adoption of theranostics. He highlights the need for standardized protocols and guidelines to ensure consistent application and patient safety.
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KEYNOTE LECTURE: Too Little or Just Enough? The Role of Focal Therapy in ProtecT Era
Freddie Hamdy, MD, presents an insightful analysis of the role of focal therapy in the treatment of prostate cancer within the ProtecT era. He explores the balance between overtreatment and undertreatment, emphasizing the need for tailored approaches that maximize patient outcomes while minimizing unnecessary interventions.
Dr. Hamdy discusses the ProtecT trial’s findings, which highlight the benefits and limitations of active monitoring, surgery, and radiotherapy for localized prostate cancer. Focal therapy emerges as a promising middle ground. His presentation covers various focal therapy techniques, including high-intensity focused ultrasound (HIFU), cryotherapy, and focal laser ablation.
Dr. Hamdy stresses the importance of accurate patient selection, including diagnostic evaluations, multiparametric MRI, and targeted biopsies, for focal therapy. He also addresses the necessity of follow-up protocols including regular PSA testing and imaging.
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Optimizing BPH Clinical Pathway: Navigating the Next 20 Years
Ilya Sobol, MD provides a forward-looking analysis on optimizing the clinical pathway for benign prostatic hyperplasia (BPH) over the next 20 years. He emphasizes the integration of emerging technologies, personalized medicine, and patient-centered care to enhance treatment outcomes and patient satisfaction.
Dr. Sobol discusses the evolving landscape of BPH management, highlighting advances in diagnostic tools, such as improved imaging techniques and biomarker identification, and minimally invasive therapies, such as transurethral water jet ablation and laser enucleation, should be incorporated into standard practice.
Telemedicine and digital health technologies are highlighted as key components of the future clinical pathway. Dr. Sobol envisions the integration of telehealth services for routine follow-ups and monitoring. He also advocates for comprehensive patient education programs that empower individuals to make informed decisions about their care.
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Imaging and Biomarkers in Patient Selection for Focal Ablation
Ezequiel Becher, MD, discusses the critical role of imaging and biomarkers in selecting patients for focal ablation in prostate cancer treatment.
He highlights the advancements in imaging technologies that have revolutionized prostate cancer diagnostics, particularly multiparametric MRI (mpMRI). In addition to imaging, Dr. Becher underscores the significance of biomarkers in patient selection. While prostate-specific antigen (PSA) levels are traditionally used, they are complemented by more specific biomarkers such as PCA3, TMPRSS2-ERG, and genomic tests that provide a deeper understanding of tumor biology and aggressiveness.
Dr. Becher also addresses the challenges and limitations of current imaging and biomarker techniques. He advocates for continuous refinement of these technologies and the development of standardized protocols to enhance diagnostic accuracy. Looking forward, he points to the potential of artificial intelligence and machine learning in improving diagnostic precision and patient selection processes.
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The When and How of Post-Ablation Surveillance
Soroush Rais-Bahrami, MD, provides a detailed examination of the timing and methodologies for post-ablation surveillance in prostate cancer care. His discussion emphasizes the critical importance of effective monitoring to ensure the success of ablative therapies and the early detection of any recurrence or progression of the disease.
Dr. Rais-Bahrami outlines the primary goals of post-ablation surveillance, including assessing treatment efficacy, identifying complications, and detecting residual or recurrent disease. He discusses various imaging modalities used in post-ablation surveillance, with multiparametric MRI (mpMRI) playing a central role. Dr. Rais-Bahrami also addresses the utility of PET-CT scans, particularly PSMA PET-CT. In addition to imaging, Dr. Rais-Bahrami highlights serum biomarkers, such as prostate-specific antigen (PSA), in surveillance protocols. He also discusses the timing of surveillance to ensure the detection of any issues and allow for prompt intervention.
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PSMA Imaging as a Biomarker for Early Stage Prostate Cancer
Robert E. Reiter, MD, discusses PSMA imaging’s potential as a biomarker for early-stage prostate cancer. In this 11-minute presentation, Dr. Reiter compares PSMA PET and MRI. PSMA PET imaging, more sensitive than MRI, can detect cancer presence, tumor size, and potential spread beyond MRI’s capability, offering a possible advantage in early and focal disease management.
PSMA’s prognostic value is explored. Data indicate a correlation between high PSMA uptake (SUV) and higher Gleason scores. Low PSMA expression is linked with more aggressive cancer markers.
Additionally, Dr. Reiter asserts that PSMA’s potential as a guide in surgical procedures, such as radio-guided lymph node removal, could enhance surgical precision and reduce the chance of residual disease.
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Diagnostic and Prognostic Biomarkers for Prostate Cancer
Ericka Bagi, BSN, RN, discusses diagnostic and prognostic biomarkers in prostate cancer, emphasizing their pivotal role in guiding personalized treatment decisions and improving patient outcomes.
Bagi analyzes biomarker tests, such as prostate-specific antigen (PSA) and its derivatives, PSA density, and PSA velocity. Further, she discusses biomarkers such as the Gleason score, genomic classifiers (e.g., Oncotype DX, Prolaris), and molecular markers (e.g., TMPRSS2-ERG fusion). Information from these tests is instrumental in tailoring treatment plans to individual patient profiles, optimizing therapeutic strategies, and minimizing unnecessary interventions for low-risk patients.
Novel biomarkers, including circulating tumor cells (CTCs), exosome-based markers, and genetic mutations (e.g., BRCA mutations), hold promise for further refining risk assessment and treatment selection. These biomarkers provide complementary information to traditional clinical and imaging evaluations, enabling a comprehensive understanding of disease biology and response to therapy.
Ericka Bagi underscores the importance of integrating biomarker testing into routine clinical practice to enhance diagnostic accuracy, prognostic certainty, and therapeutic efficacy in prostate cancer management. Standardized protocols for biomarker assessment and interpretation ensure consistency across healthcare settings, facilitating evidence-based decision-making and improving patient care outcomes.
PCa Commentary | Volume 181 – September 2023
Background
The function of initial staging of prostate cancer is to accurately estimate the risk of progression in order to guide optimal therapy. The influential National Comprehensive Cancer Network (NCCN)
recommends a PSMA PET/CT as part of initial staging for men in the risk categories of intermediate- and high-risk cancer as defined by clinicopathologic features: PSA, Gleason score, clinical tumor stage and number of positive biopsy cores. For men with a life expectancy of >10 years molecular analysis (i.e., Decipher, Prolaris or OncotypeDx Prostate) is suggested by the NCCN.
PSMA PET/CT in advanced cancer identifies lesions that are missed on conventional CT and bone scans. Yaxley et al., BJU Int 2019 reported the results of primary staging by PSMA PET/CT in 1253 men, half and half with intermediate and high-risk disease in the largest published study on this subject. Metastases were identified in 12.1%; 8.2% in men with PSA values <10 ng/ml and 47% with PSA values > 20 ng/mL. Segregated by Gleason Grade, metastases were found in 6.4% with GG 2-3 (Gleason 3+3 and 3+4). Extra-pelvic lymph nodes occurred in 47%. Bone metastases were found in 5.2% in men with intermediate-risk and in 20% high-risk cancer.
Enter the Immune System — Its Influence on Cancer Behavior
The influence of immune cell infiltration within the tumor and from the surrounding microenvironment is not taken into account in assigning a Gleason score and therefore is not considered in the NCCN classifications of risk. The variety of promoter and suppressive lymphocytes and macrophages that comprise these infiltrations are not fully identified under the microscope and play no role in standard risk assessments.
The immune microenvironment of the primary tumor influences both the initiation and early progression (i.e., toward a higher Gleason score) of the developing cancer. Immune elements compete (i.e., pro-tumor and anti-tumor) to suppress malignant clones from progressing — while others promote disorganization and aggressiveness. Protective cells include immune enhancing CD8+T-cells, Killer T-cells, protective macrophages; immune suppressive cells include T-regulation cells and immune suppressive macrophages. In fact, recent studies reveal that the ratio of one particular gene in anti-tumor macrophages to a different gene in pro-tumor macrophages can by itself determine the outcome in a man’s cancer — and possibly all cancers. (Bill et al., SCIENCE, Aug 2023).
These immune cellular elements are not only found within and surrounding tumors but also can be identified in the blood to various amounts. Based on their presence in the blood, Chinese researchers have “developed and validated a machine-learning nomogram for the prediction of risk stratification of prostate cancer based on subsets of these lymphocytes in the blood.” This nomogram functioned better than the standard NCCN prognostic risk groups. (Yang et al., Journal of Translational Medicine 2023.)
The Predictive Power of Artificial Intelligence
The genomic classifier Decipher has been multiply validated to estimate prognosis based on its risk scale of 0 to 1.0. However, AI has the capability to derive a prediction — for example of an individual man’s response to a given treatment. When whole mount pathology slides, multiply stained, are digitized into a scanner, the AI process identifies standard histology but also detects the subtypes of immune cells infiltrating the tumor and the surrounding microenvironment. This comprehensive analysis presents a complete picture of a man’s cancer, its predicted behavior and supports individualized management.
Two Examples of Clinically Useful Applications of AI for Intensifying or De-intensifying
Therapy
Commentary #180 discusses a study assessing the relative benefits of adding ADT to
radiation therapy in men with advanced cancer based on a derived biomarker.
At the 2023 annual meeting of the American Society of Clinical Oncology, Armstrong and
colleagues from Duke University presented their abstract, “Development and validation of an
AI-derived digital pathology-based biomarker to predict benefit of long-term androgen deprivation therapy with radiotherapy in men with localized high-risk prostate cancer across
multiple phase III NRG/RTOG trials,” i.e., a goal “to guide ADT duration to maximize benefits
and minimize risks.”
“Pre-treatment prostate biopsy slides were digitized from six randomized trials evaluating the
benefit of radiation therapy +/- ADT” in men with localized high-risk prostate cancer with end
points of distant metastases (DM) and prostate cancer-specific mortality. The data from this
training set was then validated in a major trial comparing radiation plus 4 vs. 28 months of ADT and determined a distinguishing biomarker. Their study found that 28 months of ADT was 13% better than 4 months in the biomarker-positive group as compared to only 2% better in the biomarker-negative group, a finding that could influence clinical decision-making.
[A spokesman for Artera AI.com said the company is working on developing a test based on this
study for commercial availability.]
BOTTOM LINE
PSMA PET/CT scans and applications of AI in prostate cancer management are aiding individualized patient management.
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PCa Commentary | Volume 180 – August 2023
Background
Ever since 1675 when the Dutch lens maker, Leeuwenhoek, looked down the newly invented microscope at rainwater and reported seeing ‘animalcules – tiny dancing creatures” (bacteria), pathologists have been similarly looking down their scopes and guiding prostate management by applying their expertise in pattern recognition.
In the 1960s, Dr. Donald Gleason organized those patterns into doublets of 3, 4 (i.e., 3+4) and 5 to create the prognostic Gleason Score — now further refined. Anthony D’Amico, professor of Radiation Oncology at Harvard Medical School is credited for establishing prognostic categories segregating “risk of recurrence” into low-, intermediate- and high-risk prostate cancer (with intermediate-risk now subdivided into favorable” and “unfavorable.”)
[Google reminds us that “A prognostic biomarker provides information about the patient’s overall cancer outcome, regardless of therapy, whilst a predictive biomarker gives information about the effect of a therapeutic intervention.”]
Feng, Spratt et al., have now advanced the art by generating a personalized precision predictive model by utilizing large data sets, machine learning and the less human-dependent “deep learning” — both components of artificial intelligence. Their analysis was directed toward discovering a biomarker that can predict which men with intermediate-risk prostate cancer benefit from the addition of ADT to radiotherapy.
Their study found that some men gained much, but others only minimally. Previous data has found that only 60% of men with intermediate-risk cancer benefit from the addition of ADT to radiotherapy — although those with “unfavorable” intermediate-risk benefit more so. The challenge was identifying who benefits and who does not.
The Spratt AI Study
“Artificial Intelligence Predictive Model for Hormone Therapy Use in Prostate Cancer,” NEJM Evidence, June 29, 2023., by Dr. Daniel Spratt with many collaborators on behalf of NRG Prostate Cancer AI Consortium.
Dr. Spratt: “With the first-ever predictive biomarker of ADT benefit in prostate cancer, created with AI, we are able to further realize the ability to create a personalized approach for the treatment of cancer.” (Quoted in Precision Medicine News, 2023).
The study was based on “digitized pathology images of pretreatment prostate tissue and clinical data of 5727 patients enrolled in 5 phase 3 randomized trials in which treatment was radiotherapy with or without ADT.” The goal was to develop a binary model to predict the benefit from short-term ADT regarding the likelihood of developing distant metastases.
The article notes that androgen deprivation therapy (ADT) is customarily combined with radiation treatment in this setting. These were trials of radiation treatment for higher grades of prostate cancer, in which there are “no validated predictive models to guide its use.”
Spratt’s colleagues endeavored to establish such a guide – a binary determinant for men with localized intermediate-risk cancer predicting whether “a given patient will benefit from ADT or not“ based on the risk of time to developing distant metastases. They generated such a model by analyzing 4 major randomized clinical trials comparing radiation therapy alone or combined with ADT.
“Data from these trials were acquired and digitized and then were used to train a predictive AI model” to predict the differential benefit of ADT according to their biomarker status. Their image extraction method was described: “For each patient, the tissue across all available digital slides was divided into 256 x 256-pixel patches. … [and the] model was trained on image patches using self-supervised learning. Over 2.5 million tissue patches across four trials … were fed through the model 200 times to train the model.”
The next step was to take this predictive model and validate it using data from RTOG trial 9408 which randomized men with intermediate-risk cancer to radiation treatment plus or minus 4 months of ADT. By applying the AI-derived model, the 15-year estimate for developing distant metastases for biomarker-positive patients treated with ADT was 4% v 14.4% for biomarker-negative ADT patients. In developing their biomarker, they found the best cut-point was 67% for segregating biomarker-positive from biomarker-negative.
By applying the biomarker established in the development model, 543 men were biomarker-positive, indicating that ADT “significantly reduced (by 10.5 percentage points) the risk of distant metastases at 15 years compared to radiotherapy alone.” For 1051 biomarker-negative patients ADT conferred minimal benefit (percentage point benefit 0.5%). For prostate cancer-specific mortality, the comparison of benefits was 10.2% and 1.2%, respectively.
Dr. Spratt concluded, “Our AI-based predictive model was able to identify patients with a predominantly intermediate risk for prostate cancer likely to benefit from short-term ADT.” In an interview with ‘News Wise’ Dr. Spratt said: “We are fortunate to be already offering this test at UH Seidman Cancer Center, Case Western Reserve University, to our patients from Northwest Ohio, our nation, and around the world.” (Quoted in News Wise, June 2023)
BOTTOM LINE
The article reviewed in this Commentary is a prime example of how Artificial Intelligence can benefit the clinical management of prostate cancer.
From Artera.ai: “The ArteraAI Prostate Test is a Laboratory Developed Test that is now clinically available through a single CLIA-certified laboratory in Jacksonville, FL. Clinicians who would like to order the ArteraAI Prostate Test can contact us at support@artera.ai. Soon after, a member of our Customer Success team will reach out to set up an account in the ArteraAI Portal to enable order submission.”
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