FICAN Research Professor (1/2021-12/2023) Matti Nykter has not always worked with cancer. During the Master’s studies, he studied computer science and signal processing focusing more on topics related to mobile phones than on biology. However, Matti got exposed to biomedical research and data when he started his doctoral studies. This was the early days of the microarray technology and there were a lot of opportunities for developing and applying computational analysis to these high throughout data. Quite soon Matti got involved in projects related to cancer research.
High-throughput technologies for tumor characterization
Matti’s research group Nykter Lab aims is to uncover the molecular basis of human cancers and to generate new avenues for treatment and diagnostics. They use various high throughput sequencing and imaging technologies to characterize tumors on multiple levels. Moreover, the Lab develop computational approaches to integrate and dissect these data to gain insight into the biological mechanisms that drive the tumor evolution, treatment response or other aspects that make the disease aggressive. Nykter Lab focuses on prostate cancer where they have a strong multidisciplinary research center at Tampere.
Datasets to study prostate cancer on a novel resolution
Currently, Nykter Lab is working towards their aim with multiple approaches. They study tumor evolution of prostate cancer in anatomical context to understand the evolution of cancer genomes and how this is reflected on epigenetic and transcriptomic levels in tumors and liquid biopsies. The Lab uses various sequencing technologies to study epigenetic state of tumors and are starting to understand how the chromatin structure is organized and regulated during the disease development. They are also generating new single cell and spatial transcriptomics datasets from prostate cancer tissues, that allow to study tissue organization, evolution, and gene regulation on a resolution that has not been possible before.
Tumor evolution analysis to guide personalized medicine
In a study hot off the press, Matti showed in collaboration with Prof. Steven Bova, how tumor evolution analysis can be used to track the tumor evolution within the prostate in detail. They identified and characterized the tumor initiating and metastasizing subclones as well as anatomical locations and timing of those events. The study was published in Genome Medicine with a title Cancer origin tracing and timing in two high risk prostate cancers using multisample whole genome analysis: prospects for personalized medicine.
In another recent study (Ketola et al. Cancer Research, 2021), Matti and his colleagues proposed a new concept of subclone eradication analysis that can be used to link specific treatments to eradication of specific subclones in solid tumors. Taken together, these studies build ground for clinical trials aiming to test the benefit of tumor evolution guided treatment strategies for patients of selected cancer types.