Qlucore newsletter: Improved molecular classification of lung lesions available

The new Qlucore Insights model provides a comprehensive overview of the lesion that is being analyzed. The model assigns a sample to one of 18 subgroups, where the subgroups include the major primary lung cancer subtypes, twelve subgroups for metastatic cancer such as breast, colorectal, or kidney cell cancer and two subtypes for infections/inflammatory conditions, i.e. Sarcoidosis and TBC. 

The Qlucore Insights lung cancer model is based on RNA-seq data from more than 300 carefully selected samples (FFPE). The model is developed using modern and tailored AI-based machine learning techniques. Gene fusions are also detected and reported. Data processing and results are easy and fast to generate with the foundation in standard RNA-seq kits, standard workflows and NGS-instruments. 

Although there have been major advancements in the treatment of lung cancer over the past decades, it remains the major cause of cancer death worldwide. To further improve outcomes, the scientific community favours RNA analysis which unlike DNA, fluctuates considerably both in presence and relative concentrations reflecting the cellular characteristics of a tumor. RNA analysis gives a snapshot of the current state of a potential tumor sample. Qlucore uses this snapshot to assign a sample to the correct subgroup. 

The lung cancer model is available and integrated into the Qlucore Insights software for research purposes. An IVDR compliant solution is under development. The lung cancer model is one of several supported by the software platform which also includes leukemia and bladder cancer models, making it easier for an organization to work with several types of cancer.

Contact us today to start a trial or, sign up for the upcoming webinar “Identify the tissue of origin for lung lesions”.  

UPCOMING FREE WEBINAR:

Qlucore Insights: Identify the tissue of origin for lung lesions

August 29th, 2024

at 11:00 CET.

Sign up here