ONCOLOGY


mortality and metastasis. This score has outperformed traditional risk tools and successfully reclassified a substantial proportion of intermediate- risk patients.4


This may help identify


By aligning clinical genomics with established expertise in cellular and digital pathology, Source BioScience is driving the adoption of multi-modal datasets into clinical practice.


on clinical services. Modern oncology increasingly blurs the boundary between screening and diagnostics, as both now rely on molecular and biomarker-based methods to improve accuracy. This shift includes the adoption of molecular reflex tests such as Proclarix (Proteomedix) and Stockholm3 (A3P Biomedical), which integrate protein biomarkers, genetics, and clinical variables to more accurately distinguish aggressive from indolent prostate cancers following an elevated PSA. Recognising their potential to reduce overdiagnosis and unnecessary intervention, the recent Prostate Cancer Research (PCR) report recommends Proclarix and Stockholm3 as reflex tools within a future national screening programme.3 At the same time, hereditary cancer testing is reshaping how risk is defined even before screening begins. Individuals with germline mutations such as BRCA1 and BRCA2 have significantly higher lifetime risks of breast, ovarian, pancreatic, and prostate cancers. Identifying these individuals allows screening to start earlier, occur more frequently, or be paired with preventive options. Although distinct from population screening, hereditary testing increasingly forms part of a continuum where genetics informs who to screen, when, and how.


Taken together, oncology is moving


from universal, one-size-fits-all screening to a more precise, biomarker and genomics informed approach, bridging screening and diagnostics into a unified, proactive model of early cancer detection.


Risk stratification: precision in diagnosis


When cancer is suspected, achieving diagnostic precision is essential, yet it remains a complex challenge in oncology. Traditional tools such as imaging, cytology, and histopathology remain central to diagnosis, but their interpretation can be limited by subjectivity, sampling variation, and tumour heterogeneity. As a result, patients with biologically distinct cancers may receive similar treatment recommendations despite vastly different prognoses.


Molecular assays are increasingly being used to complement traditional methods, providing quantitative insights into tumour biology that enable more accurate risk stratification. One example is the Prostatype Genomic Classifier (Prostatype Genomics), a prognostic tool that combines gene expression analysis from prostate biopsy tissue with clinical parameters to generate a molecular P-score. This score predicts long-term outcomes such as prostate cancer-specific


Modern oncology increasingly blurs the boundary between screening and diagnostics, as both now rely on molecular and biomarker-based methods to improve accuracy


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individuals suitable for less aggressive management strategies, including active surveillance or focal therapy. The adoption of focal therapy in the prostate cancer space remains limited by poorly defined selection criteria, with current parameters such as PSA, Gleason score, and mpMRI offering valuable information; but these are not always sufficient to predict long-term outcomes reliably. Genomic classifiers like Prostatype help fill this gap by providing a biologically informed assessment of tumour behaviour, supporting more confident and personalised treatment decisions. By refining diagnosis through risk stratification, clinicians can deliver more precise care, avoiding overtreatment in low-risk cases while ensuring that high- risk patients receive timely, potentially curative intervention.


Guiding therapeutic strategy Oncology diagnostics lies not only in detecting and characterising cancer, but in directing how it is treated. Historically, cancer treatment followed a ‘one-size- fits-all’ approach, where patients with the same tumour type often received the same therapy regardless of molecular differences. This approach overlooks the inherent heterogeneity of tumours, contributing to variable treatment outcomes, drug resistance, and avoidable toxicity. Today, therapeutic strategy is increasingly determined by the molecular profile of an individual’s tumour. Biomarker-guided treatment uses


predictive assays to identify which patients are most likely to benefit from a specific therapy. These assays identify patients whose tumours express the relevant molecular target, ensuring that only likely responders receive therapy, while sparing others from ineffective treatment. In breast cancer, MAF gene amplification testing (Inbiomotion) has emerged as a predictive biomarker to guide adjuvant bisphosphonate therapy in early stage, post-menopausal women.5 Clinical evidence demonstrates that patients without MAF amplification derive significant survival benefit from bisphosphonate treatment, whereas those with MAF amplification do not. This enables oncologists to personalise treatment decisions, not only improving outcomes while avoiding ineffective therapy and potential side effects but also leading to significant savings throughout the patient pathway.6


DECEMBER 2025 WWW.PATHOLOGYINPRACTICE.COM


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