Researchers at SciLifeLab have harnessed the latest technologies to map the molecular landscape of lung cancer on the protein level. In-depth analysis revealed novel molecular subtypes associated with cancer drug targets, and the developed high-throughput proteomics method paves the way for introducing proteomics to the clinic.
If you want to know if the food is too salty, do you read the recipe or taste it? Similarly, when designing an effective anti-cancer treatment targeting proteins, a protein-level readout can serve as a direct taste of the cancer subtype, in addition to today’s practice of consulting the recipe, a genome.
In a recent study, published in Nature Cancer, researchers from SciLifeLab and Karolinska Institutet have used multi-omics analysis of cancer and thereby combined both. This extensive proteogenomics analysis revealed novel molecular subtypes of lung cancer that can support the design and selection of not only the most suitable drugs but also their effective combinations.
Lung cancer represents a hallmark disease of unmet clinical need with a dismal 5-year survival of patients diagnosed with advanced-stage lung cancers. However, many new cancer drugs have been developed targeting cancer driver proteins and activating the body’s own immune system to fight cancer. The challenge is to find effective combinations of these drugs and to match these combinations to individual patients. This hurdle of personalizing diagnosis and treatment hinders rapid translation of drug development advances to patient benefits.
By harnessing the latest mass spectrometry-based technologies for cancer research, SciLifeLab researcher Janne Lehtiö (KI) and his group analyzed over 400 lung cancer samples. In collaboration with researchers from Lund, Oslo, and Edinburgh, the team achieved a remarkably in-depth molecular mapping of lung cancer on protein level that revealed new subtypes of lung cancer with interesting associations to proteins, i.e., candidate drug targets.
“This information is a crucial readout when forming a hypothesis on how to combine anti-cancer drugs for individual patients”, says last author, Lukas Orre (KI), who has been dedicated to the project for several years.
Based on the in-depth proteogenomics analysis, the researchers designed a method for rapid proteome analysis that could, in the future, be used in hospitals to add protein-level information to support clinical decision-making. This method was tested and validated using a large cohort collected by colleagues from Oslo and with the help of unique biopsy material on late-stage lung cancers from Lund.
“Particularly intriguing is the finding on the mechanism of how a single well-known cancer mutation can activate proteins leading to both tumor growth and its escape from the body’s immune surveillance at the same time”, states first author Janne Lehtiö.
This and the other findings presented in the study form a strong foundation for the team’s future work on bringing proteomics to the clinic.