Tobias Sjöblom's projects on cancer-causing molecular alterations
Whole genome and transcriptome sequencing of colorectal cancers
Luís Nunes, Klara Hammarström, Emerik Österlund, Erik Osterman, Viktor Ljungström, Per-Henrik Edqvist, Emma Lundin
The aim of this project is to increase knowledge of colorectal cancer tumorigenesis through detailed characterisation of the somatic genomic and transcriptomic landscapes of colorectal tumours from Swedish patients. We have collected whole genome sequencing and transcriptome data for 1,063 tumours. These data sets are used for in-depth analyses of cancer-specific genomic and transcriptomic alterations and their associations to clinical characteristics and patient outcome. The study is possible through collaboration between the U-CAN colorectal cancer investigators at Uppsala University, Umeå University, and KTH.
Discovery and validation of cancer biomarkers in blood plasma
Joakim Ekström, Jim Åkerrén Ögren, Natallia Rameika, Klara Hammarström, Emma Lundin, Chatarina Larsson
A good diagnostic plasma biomarker should be specific for the cancer type and be able to accurately identify a patient at an early disease stage. However, most cancer types lack FDA-approved biomarkers for early detection, and the literature lacks strategies for how biomarker studies should be designed to maximize the chances of success.
We have developed a new study design framework for biomarker discovery based on regulatory authority requirements and novel statistical approaches. Here, we focus on discovery and validation of new diagnostic plasma biomarkers for colorectal, lung, and ovarian cancers by applying the statistical framework to large-scale proteomics and metabolomics data that we have generated from U-CAN patient samples. In the next step, we will extend the study to include e.g. breast cancer, prostate cancer and brain tumours. The aim is development of sensitive blood tests to detect cancer.
Exploiting loss of heterozygosity for a novel anti-cancer therapy
Xiaonan Zhang, Snehangshu Kundu, Natallia Rameika, Margus Veanes, Lei Zhong
Successful anti-cancer therapies selectively kill cancer cells, while normal tissues are spared. We have developed a concept based on frequent loss-of-function genetic variants that occur naturally in the human population, and cancer-specific loss of heterozygosity (LOH). As proof of principle for our approach, we have shown that loss-of-function variants of NAT2 make cancer cells sensitive to drugs that are metabolised by this enzyme if they have lost wild-type NAT2 activity through LOH (Rendo et al, Nat Commun., 2020; Rendo et al, Sci Rep., 2020; Conway et al, Angew Chem Int Ed Eng., 2020). Normal cells that retain at least one copy of the wild type NAT2 allele are not killed by these drugs as they can still metabolize them.
We are continuing our studies of NAT2-loss as target for anti-cancer therapy and have initiated studies of a second candidate gene for this novel type of therapy. Furthermore, we are also searching for additional novel LOH therapy targets in adult and pediatric cancers by informatics approaches.
Evaluation of clinical data parameters for prediction and prognosis in colorectal cancer
Klara Hammarström, Erik Osterman, Israa Imam, Emerik Österlund, Per-Henrik Edqvist, Sepehr Doroudian
We are studying the population of colorectal cancer patients from Uppsala, Dalarna and Gävleborg to evaluate e.g. how tumour and patient characteristics and given treatments affect progression and survival on a population level. The aim is to contribute towards improved predictive and prognostic tools in the clinic. We primarily base our research on clinical data from national registries, and also have access to molecular data generated in other projects in the research group. We collaborate closely with Professor Bengt Glimelius in this project.
Role of Ephrin receptors in metastasis
Snehangshu Kundu, Luís Nunes
Ephrin receptors have a role in tumour growth, invasiveness, and angiogenesis and have previously been associated with metastasis. We recently demonstrated a link between inactivating EPHB1 mutations and metastasis in colorectal cancer (Mathot et al, Cancer Res., 2017). To provide better insight into Ephrin receptor signalling in cancer and metastasis we aim to determine the phenotypes of the most frequently mutated positions in Ephrin receptors. To this end, mutational data from 10 000 TCGA tumours from 33 different cancers have been collated and ten hotspot mutations chosen for further functional analyses in cell models.
Computer-based image-analysis for medical imaging
Ali Teymur Kahraman, Sanhita Basu, Jim Åkerrén Ögren
The aim of the project is to support fast and accurate radiology evaluations through development of software and models for automated image analysis for medical images. In one study, we are developing methods for automatic interpretation of CT pulmonary angiography volume images to be able to segment structures of the thorax cavity in image stacks and detect emboli in segmented pulmonary arteries. In another study, we are developing models for automatic grading of knee osteoarthritis from plain radiographs using machine learning. This collaborative project includes radiologists Tomas Fröding and Dimitris Toumpanakis and is part of AIDA (Analytic Imaging Diagnostic Arena), a national arena at Linköping University for AI in medical diagnostics.