Our research
Proteomics is a collective name of several techniques and methods for global analysis of proteins in biological samples such as cells and tissues. Proteins are vital for any living organism and are involved in virtually all biological functions from accelerating chemical reactions as enzymes to cellular signaling, and serve as hormonal signaling molecules, providing recognition sites for the immune system, and serving as building blocks responsible for maintaining the cell's form and structure.
The Cancer Proteomics Mass Spectrometry group headed by Professor Janne Lehtiö is continuously developing mass spectrometry-based methods to improve proteome analysis. We use omics methods to obtain detailed pictures of the molecular phenotype of cancer cells, tumors and plasma proteome on systems level. One fundamental question we currently address is how cancer genome aberrations influence the functional proteome. This emerging field is known as cancer proteogenomics (Branca, Nature Methods 2014; Zhu elt al., Mol. Cell. Prot. 2014; Boekel et al., Nature Biotechnol 2015; Zhu et al., Nature Commun., 2018). With this method we can also detect cancer cell specific protein variants, which open up the possibility to use proteogenomics to discover novel immunotherapy targets and to define predictive biomarkers for immunotherapy. Another focus of ours is to gain knowledge of how targeted cancer drugs affect the proteome and how this information can be used to select most effective treatment for an individual patient. Our efforts are currently focused on lung cancer (Orre et al., Molecular Cell 2019, Zhu et al. Mol. Cell. Proteomics 2020, Arslan et al., Nature Protocols 2022), breast cancer (Johansson, Nature Commun 2013; Nature Commun 2019; Johansson, Clinical Proteomics 2015) and leukemia (Yang, Nature Commun 2019).
Our group are encouraging team science and embraces diversity. We are engaged in translational research within our group and via large collaborative networks, in Sweden and globally, from tech development to implementation of omics in clinical use (Tamborero D, Nature Medicine 2020).
Proteomics and Proteogenomics Methods
Team leader: Dr. Rui Branca
In our group, we are focused on developing and applying mass spectrometry (MS)-based methods to enhance human proteome analysis. We have pioneered a prefractionation method known as high-resolution peptide isoelectric focusing (HiRIEF) (Branca et al., Nature Methods 2014). This technique enables reproducible fractionation, reducing sample complexity before MS analysis. As a result, it improves analytical depth, increases peptide and protein sequence coverage, enhances the overlap of detected peptides and proteins between samples, and provides an additional data point for each peptide—the peptide isoelectric point. This allows for novel applications, such as using MS data in unbiased genome-wide searches for protein-coding DNA sequences in the human genome (proteogenomics) (Branca et al., Nature Methods 2014; Boekel et al., Nature Biotechnology 2015; Zhu et al., Nature Communications 2018).
More recently, we have applied our proteogenomics methods and immunopeptidomics (the identification of peptides presented by the MHC complex) to discover tumor-specific antigens in cancer samples. Additionally, we are developing PRM (parallel reaction monitoring) targeted quantitative analysis of proteins for clinical applications. Over the past year, we have also implemented single-cell and low-cell number proteomics with high analytical depth. This advancement enables comprehensive proteome analysis of samples (>7000 proteins) from as few as 200 cells obtained through FACS (Fluorescence Activated Cell Sorting) or LCM (Laser Capture Microdissection).
Lung cancer research
Team leader: Dr. Lukas Orre
The Lung Cancer proteomics team has a strong focus on the application of proteomics methods in lung cancer research. Our general aim is to identify novel biomarkers and targets for cancer therapy to improve the treatment of non-small cell lung cancer (NSCLC). For state-of-the-art analytical depth, quantitative accuracy and proteome specific information we rely on in house developed methods (Branca et al., Nature Methods 2014, Panizza et al., Scientific Reports 2017, Zhu et al., Nature Com. 2018, Orre et al., Molecular Cell 2019, Zhu et al. Mol. Cell. Proteomics 2020, Arslan et al., Nature Protocols 2022).
In our clinical lung cancer proteomics projects primary tissue/biopsies from lung cancer are analysed in order to identify and characterize molecular subgroups of lung cancer. The gained knowledge of lung cancer subgroups is subsequently used for hypothesis driven projects where cancer drivers and corresponding therapeutic strategies are investigated in model systems. A current focus is also to understand the immune landscape of lung cancer in order to better target cancer cell escape from the immune system. In addition, translational projects are performed where discoveries from clinical samples are further investigated in model systems (Lehtiö et al., Nature Cancer 2021).
Further, pre-clinical research is performed where model systems are used to understand the molecular response to cancer therapy, with the aim to identify potential treatment predictive biomarkers and combination therapies (Orre et al., Oncogene 2013, Zhou et al., Oncogene 2017, Fotouhi et al., Oncogene 2019, Zhou Tran et al., Mol Cell Proteomics 2020). By analyzing the molecular response of cancer cells to different drugs we can identify the determinants of drug response or drug resistance, allowing us to suggest biomarkers and drug combinations for improved lung cancer therapy. Primary methods used are MS-based proteomics, transcriptomics, functional genomics, high-throughput drug screening as well as a range of classical molecular biology techniques.
The knowledge generated in different projects is used in concert to understand why cells from different tumors respond differently to cancer drugs, and what combinations of cancer therapies we should select for each patient. Ultimately this knowledge will help us tailor the best therapy for each lung cancer patient.
Breast cancer research
Team leader: Dr. Henrik Johansson
Our overall aim is to increase the biological understanding of the breast tumor proteome to define clinical subgroups, identify therapeutic targets and biomarkers for personalized therapy.
To aid this goal, we take part in development of MS-based proteomics methods in the group to obtain deep proteome coverage and identify novel protein coding protein regions (Branca et al., Nature Methods, 2014; Zhu et al., Nature Commun 2018).
We are mainly interested in 1) understanding and defining markers of endocrine resistance, 2) how the proteome defines breast tumor subgroups that can guide therapy and 3) how neoantigens shape the tumor and its response to therapy.
In our efforts to define antiestrogen responders from non-responders, we have identified a 13-protein panel and the nuclear receptor, RARA, as potential predictive markers of tamoxifen resistance (Johansson et al., Nature Commun 2013; Johansson et al., Clinical Proteomics 2015).
In a recent study, unbiased characterization of breast tumor proteomes recapitulates known BC subtypes and further subdivide by immune component infiltration, suggesting the current classification is incomplete (Johansson et al., Nature Commun 2019). The proteome profiles were used as a base to interpret multiple layers of data collected on the same tumors, including those of mRNA expression, genome copy-number alterations, single-nucleotide polymorphisms, phosphoprotein levels, and metabolite abundances. Proteins from part of the genome, not thought to be translated, were also identified. These novel proteins have the potential to function as tumor specific antigens in immunotherapy.
Acute lymphoblastic leukemia (ALL) and drug development research
Team leader. Rozbeh Jafari, PhD
We are utilizing and integrating state-of-the-art omics methods to obtain detailed molecular phenotypes of childhood and adult acute lymphoblastic leukemia (ALL), aiming to identify precision medicine candidates for improved therapy. Building on our recent studies (Leo, I.R. et al., Nat Commun 13, 1691 ,2022, Kurzawa, N. et al., Nat Chem Biol 19, 962–971, 2023), we are advancing the study and validation of precision medicine candidates, with a strong focus on their translational implementation.
A fundamental question we are currently addressing is how cancer genome aberrations influence the functional proteome by combining genomics with proteomics data, a field known as cancer proteogenomics. In addition to quantitative proteomics, we are enhancing our analysis by capturing the biophysical state of the proteome, regardless of its abundance, using thermal proteomics. This approach also allows us to identify functional proteoforms as well as their association with drug sensitivity.
Furthermore, we are investigating the target landscape of current and emerging targeted therapeutics using orthogonal chemical proteomics approaches to understand their mechanisms of action and potential toxicities. Our research also focuses on molecular and cellular biology, aiming to translate our findings into clinical applications that can significantly improve patient outcomes.
Translational cancer bioinformatics
Team leader. David Tamborero, PhD
Our objective is to support the clinical decision-making based on the interpretation of the molecular profile of each patient’s tumor. Precision oncology relies on the accurate identification and interpretation of molecular alterations developed during the onset and progression of the disease, and vast efforts are ongoing to better understand their relevance for diagnosis, prognosis and therapy selection. To help in this task, we have developed the Molecular Tumor Board (MTB) portal (), a clinical decision support tool that interprets tumor sequencing data and provides the infrastructure to harness the results. The MTB portal employs state-of-the-art biological, clinical and bioinformatics knowledge to annotate the functional significance of the molecular alterations observed in an individual tumor and their association with approved drugs and investigational therapies. The MTB portal also facilitates the discovery of new molecular biomarkers based on a systems biology approach and automates the detection of other events of clinical interest, such as allocation to available clinical trials and genetic counseling alerts, which support a more integrated care of the patients and their families. The MTB portal is currently used by the seven leading European comprehensive cancer centers forming the .
Infrastructure and funding
Mass spectrometry instrumentation
We use cutting edge mass spectrometry and chromatography instrumentation for our research. We have also developed the High Resolution Isoelectric Focusing (Branca et al., Nature Methods, 2014) for pre-fractionation to perform in-depth proteomics.
Instrumentation:
Mass spectrometers
- Two MS Orbitrap Astral, Thermo Scientific
- Two MS Orbitrap HF Q Exactive, Thermo Scientific
- MS timsTOF Pro 2, Bruker
- MS timsTOF HT, Bruker
- MS timsTOF SCP, Bruker
- MS Exploris 480, Thermo Scientific
- Acquity Premier Offline UPLC, Waters
Peptide separation technologies
- 1 HiRIEF (High Resolution Isoelectric Focusing)
- 1 Liquid Chromatography (nanoUPLC/HPLC/FPLC)
Robotic sample preparation
- Biomek i7 (Beckman Coulter) robot for automated sample preparation
- 1 Ettan Digester, GE Healthcare Life Science
Funding
Our method development and cancer research are made possible by grants from:
- AstraZeneca
- Cancer Research Foundations of Radiumhemmet
- Cancer Society in Stockholm
- Dr Åke Olsson Foundation for Hematological Research
- EU H2020 CCE-DART
- EU H2020 Oncobiome
- EU H2020 RESCUER
- GE Healthcare
- Horizon Europe EOSC4Cancer
- Horizon Europe PCM4EU
- Horizon Europe PRIME-ROSE
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- Knut and Alice Wallenberg Foundation
- Novartis
- Roche
- Stockholm County Council
- Swedish Cancer Society
- Swedish Childhood Cancer Foundation
- Swedish Research Council
- Swedish Foundation for Strategic Research
- Stiftelsen Sigurd och Elsa Goljes Minne
- Taiho Oncology
- The Erling-Persson Family Foundation
- The Sjöberg Foundation
- VINNOVA
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Doctoral courses
We arrange two doctoral courses every year:
"Proteomics by Mass Spectrometry: When and How" () given in November. Course responsible: Henrik Johansson, (henrik.johansson@ki.se)
"Omics data analysis: From quantitative data to biological information" () given in November/December. Course responsible: Haris Babačić (haris.babacic@ki.se) and Ioannis Siavelis (ioannis.siavelis@ki.se)