Relying solely on Next-Generation Sequencing (NGS) is insufficient for HER2 testing in biliary tract cancers. Data shows NGS misses up to 15% of patients with HER2 overexpression detected by immunohistochemistry (IHC). Performing both tests is essential to avoid denying patients effective targeted therapies.

To reduce treatment delays, pathologists should initiate biomarker testing reflexively. Waiting for a medical oncologist to order tests at a first visit is a system failure, wasting critical time and risking the need to retrieve archived samples.

Unlike rare biomarkers that necessitate a 'test-and-wait' approach, IB6 is expressed in over 80-90% of NSCLC tumors. This ubiquity could make pre-screening unnecessary for drugs like Sigvotatug Vedotin, allowing clinicians to initiate targeted therapy much faster and for a broader patient population.

An individual tumor can have hundreds of unique mutations, making it impossible to predict treatment response from a single genetic marker. This molecular chaos necessitates functional tests that measure a drug's actual effect on the patient's cells to determine the best therapy.

Data shows an average two-week delay occurs between a lung cancer patient's biopsy and the ordering of essential biomarker tests. This administrative gap, separate from the diagnostic process itself, is a major bottleneck that postpones critical treatment decisions.

The progress of AI in predicting cancer treatment is stalled not by algorithms, but by the data used to train them. Relying solely on static genetic data is insufficient. The critical missing piece is functional, contextual data showing how patient cells actually respond to drugs.

The success of perioperative osimertinib means oncologists cannot choose the optimal strategy (targeted therapy vs. chemoimmunotherapy) for resectable lung cancer without first knowing the patient's EGFR, ALK, and PD-L1 status. This elevates biomarker profiling from a metastatic-setting tool to a critical first step in early-stage disease.

The RSClin tool integrates a patient's Oncotype DX score with their unique clinical-pathologic features, such as tumor size and grade. This provides a more accurate and personalized risk assessment, as the same genomic score can represent significantly different prognoses for patients who have low versus high clinical risk factors.

The panel suggests AKT inhibitor trials in prostate cancer have been disappointing due to suboptimal biomarker selection (e.g., PTEN IHC). A similar drug in breast cancer showed significant survival benefit when using a more precise NGS-based strategy, indicating a potential path forward if the right patient population is identified genetically.