For a study, it was determined that non–small cell lung cancer was no longer seen as a single illness, but rather as a collection of cancer forms that respond differently to different therapies. Specific Food and Drug Administration–regulated molecular tests for identifying driver mutations have been approved for matching the correct medicine to the right patient. Because of their capacity to inform treatment decisions and predict clinical response, the biomarkers, known as theranostic biomarkers, were transforming the way oncologists developed non–small cell lung cancer treatment regimens. Researchers investigated current literature suggestions for maximizing the collection and processing of cytology material for biomarker assessment, as well as determining which cytology samples produced the highest yields. As the capacity to properly individualize lung cancer therapy improved, it became crucial to screen and treat patients based on biomarker analyses.

Fluorescence in situ hybridization testing for genetic rearrangements and reverse-transcriptase polymerase chain reaction testing for genetic mutations were the authorized biomarker tests for lung cancer. As molecular medicine became more widely used, another therapeutic hurdle in lung cancer was relying on limited cytologic material to correctly evaluate the important theranostic indicators. The majority of newly diagnosed patients with lung cancer had advanced disease at the time of presentation, and thus frequently received the least intrusive biopsy possible to determine a diagnosis and stage of the illness. 

As less intrusive diagnostic procedures became increasingly popular, it became vital to maximize cancer tissue collection and reduce loss during processing. The physicians doing these operations are required to understand the tissue needs for molecular testing based on tumor type and must devise collection techniques to enhance molecular biomarker testing.

Reference:journals.lww.com/clinpulm/Abstract/2015/01000/Challenges_and_Opportunities_for_Identifying.6.aspx

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