A first-generation classification model for lung cancer has now been developed and is performing well. The model is based on gene expression data and is already available for use within Qlucore Insights. The initial model facilitates a division into two main groups, lung adenocarcinoma and lung squamous cell carcinoma, as well as three further groups based on whether the tumor profile corresponds to metastases from breast, colorectal, or kidney cell cancer. The model is designed to utilize tissue fixed with formalin (FFPE), which is a common sample form in the pathological workflow for solid tumors. It is clinically important to distinguish between primary lung cancer tumors and tumors that have metastasized to the lung in order to optimize next step investigations and treatment. Additional model generations are planned with improvements and expansion to support more forms of metastases. The goal is to further develop the solution into
In late 2021,
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The new classification model is based on
Precision diagnostics for cancer have advanced rapidly in recent years, driven by next-generation sequencing (NGS). Up until now, the focus has been on mutations and variants in the genetic code, which have been used for patient stratification and decisions on cancer treatment. However, there has been increasing interest in techniques based on measurements of gene activity levels (gene expression) as it provides additional opportunities to describe the type of treatment a patient should receive.
Qlucore Insights is intended for research and enables early testing and evaluation. Qlucore Insights is provided to hospitals, clinics, and laboratories via Qlucore's European sales force.
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