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Cancer remains one of the leading causes of death worldwide, accounting for nearly 10 million deaths in 2020 alone. One of the main challenges posed by the disease is that each individual cancer has a unique combination of genetic mutations, so no two cancers are the same. As such, the historical one-size-fits-all treatment approach doesn’t work for many patients.
In the search for more appropriate anti-cancer drugs, many believe a personalized treatment approach is needed, where the optimal therapy for each individual patient is determined. However, there are several challenges that need to be addressed before this becomes a reality.
For example, over the past decade we have seen a rise in targeted treatment approaches to cancer, which exploit the specific molecules and pathways involved in the growth, progression, and spread of the disease. Despite the initial success of these therapies, many patients with advanced cancers become resistant to treatment. This acquired resistance is a major bottleneck in cancer treatment, and one of the main reasons for poor overall survival.
Functional Drug Sensitivity Testing
Drug sensitivity testing is a process by which patient cells are examined experimentally in response to various drugs. This approach is showing great potential for the treatment of cancer patients where previous therapeutics have either failed or for those who have recurrence.
The process begins with fresh tissue samples being acquired from the patient. These are then processed, cultured and, once the researchers have enough cells, perturbed with freshly made drug plates. The effect of the drugs on cell health can then be examined.
Once drug sensitivity has been determined, the information can be passed to the physician responsible for the patient who can design a personalized scheme of treatment for the patient. The process also gathers valuable information on the cellular mechanisms of the cancer type studied.
This approach has recently been adopted by researchers at the Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki. “Our aim is to characterize the phenotypic alterations or actions of the small molecules at the single cell level,” explained Senior Scientist Vilja Pietiäinen. “These might be morphological changes, or they might be changes in the localization of a certain protein. By profiling these perturbations in the cells, we can get a better overview of how these drugs are acting.”
The team uses microscopic image-based solutions to investigate the response of 3D patient-derived cancer cells to a panel of anti-cancer compounds. They also utilize AI and machine learning models to help quantify the treatment effects on the cells.
The drug sensitivity testing and image-based analysis being conducted by the team at FIMM can provide clinicians with a more comprehensive picture of an individual’s cancer, and potentially improve outcomes for patients that have already exploited other treatment options.
In addition, the team is currently part of the ERA PerMed-funded project on clinical implementation of multidimensional phenotypical drug sensitivities in pediatric precision oncology (COMPASS). One of the goals of the project is to build an international, standardized, and validated platform for drug testing based on image analysis and accompanying molecular analysis that characterizes and classifies different types of tumors for their response to different drugs.
To find out more about the FIMM researchers’ work, read the full whitepaper.