As demand for the molecular profiling of solid tumors increases, so too does the need for H&E sample review, annotation and tumor content assessment. This is placing extra workload on already stretched pathology departments.
As demand for the molecular profiling of solid tumors increases, so too does the need for H&E sample review, annotation and tumor content assessment. This is placing extra workload on already stretched pathology departments.
General pathology workflows can be complicated and fragmented and molecular pathology workflows are often no different. Additionally, molecular pathology faces other fundamental challenges, including the provision of accurate tumor assessment for downstream molecular tests that is well documented in literature.1
All molecular tests (such as EGFR or NGS) require a minimum percentage of tumor cells due to their minimal sensitivity levels. Accurate information on tumor cell percentage therefore, is essential in having confidence in the selection for personalized medicine.
Without sufficient tumor cells and associated tumor DNA, the chances of finding important molecular test outcomes are significantly reduced and some molecular tests may deliver a false negative result.
Similarly, insufficient total cell numbers, may result in a failed sample run leading to extra consumable and staff costs. In fact, evidence shows that molecular biomarker trials are failing, in some cases by as much as 38%, due to the inability to reliably perform molecular testing after poorly chosen tissue samples.2
Analyze solid tumor tissue samples therefore, quickly to enhance the quality and accuracy of macrodissection, nucleic acid extraction, and molecular profiling using Philips TissueMark.3
TissueMark is a key offering in Philips computational pathology portfolio that assists the user to examine the region of interest (ROI) for Macrodissection by utilizing artificial intelligence through deep learning programs in order to:
Improve the quality of molecular tests with accurate ROI and cellularity guidance
Oncotarget PDF - Automated tumor analysis for molecular profiling in lung cancer - Download now