Lung cancer, the leading cause of cancer death, is divided into several histological subtypes with large differences in molecular alterations, clinical presentation, and patient outcome. By a combined clinical and molecular approach the current project focuses on improving the molecular understanding of lung cancer and translate research findings into a clinical diagnostic setting.

By characterization of the genomic, transcriptional, and DNA methylation landscape in lung cancer subgroups defined by histology and other clinicopathological factors in both own and public cohorts we search for new molecular subgroups of potential clinical relevance, additional targets for synergistic treatment, and a deepened understanding of the molecular pathogenesis.

To identify operable lung cancer patients with risk for metastatic relapse we search for new prognostic biomarkers based on analysis of genome-wide gene expression data and conventional protein marker validation based on analysis of primary tumor tissue. By analysis of patient specific alterations in circulating tumor DNA in blood samples we aim to establish blood-based assays for early detection of lung cancer, treatment monitoring, and early detection of relapse in the primary and advanced setting.

Breast cancer is the most common malignancy in women and a heterogeneous disease at the molecular level. This heterogeneity translates into differences in clinical manifestation, patient therapies, and ultimately patient outcome. TNBC is a subgroup of breast cancer, representing ~10% of all cases (9% in Sweden 2015). To date, this patient subgroup has often had a poorer clinical outcome, early relapses, and without obvious available targeted therapies compared to other breast subgroups. Consequently, in TNBC there is a clear need of identifying new targets for selective inhibition to improve patient outcome.

The main aims of this project is to:

1) Characterize the molecular landscape in TNBC on the DNA, RNA, epigenetic and protein level, through broad high-dimensional analysis techniques and advanced bioinformatics.

2) Identify novel markers of DNA repair deficiency and neoantigens peptides in triple negative breast cancer  that may be relevant for future diagnostics and interpretation of response to current systemic therapies and emerging immune therapies.

3) Characterize the immunogenic landscape of TNBC through molecular data and in situ analyses.

4) Redefine the molecular taxonomy of TNBC through data integration of multiple -omics layers using advanced bioinformatics and machine-learning.

Based  on experiences and knowledge gained in TNBC we  are now expanding analyses of DNA repair deficiency to ER-positive and HER2-neegative disease,  representing   the largest subgroup of breast cancer. Here,  we  will use similar  techniques and multi-omics approaches.