OncoProteomics
To better understand cancer in all its facets and work towards improved diagnostics and treatment, the OncoProteomics Laboratory (OPL) focuses on the comprehensive analysis of proteins, the functional building blocks of life, whose activities and functions are highly altered in cancer cells.
Through unbiased (phospho)protein profiling using mass spectrometry-based proteomics, we can quantify the biochemical impact of cancer-related genomic abnormalities, and thereby can bridge the gap between cancer genome information and observed cancer phenotype.
Our multi-disciplinary OPL team includes core members with expertise in mass spectrometry, biology, biochemistry, and bioinformatics, alongside post-docs and PhD students with life science and clinical backgrounds. In collaboration with cancer researchers and clinicians of Cancer Center Amsterdam (Medical Oncology, Urology, Hematology, Pulmonology, Surgery, Neurosurgery, Pathology, LEXOR) and external collaborators, our studies encompass the full spectrum of analyses in cancer cell lines, organoids, mouse models (both genetic and patient-derived xenografts), and clinical samples.
Cutting-edge mass spectrometry
We have implemented next generation quantitative proteomics based on data-independent acquisition. DIA-MS uses parallel peptide fragmentation and less complex biochemical workflows, together reducing missing values, processing time and costs, thereby enabling large scale clinical proteomics. DIA-MS will be key for phosphoproteomics for precision oncology. After implementing and bench-marking DIA-MS at the OPL, we participated in a multi-center study conducted in nine countries. We showed that harmonized MS with standardized data acquisition can yield highly reproducible data (Xuan et al., Nature Communications, 2020).
OncoProteomics research lines
Our OncoProteomics research can be divided into methodological research (sample preparation and data analysis contexts) and two broad cancer research lines:
1. Analysis of tumor microenvironment, via secretome, exosome and proximal fluid proteomics to develop non-invasive biomarker applications.
2. Analysis of cancer signalling pathways via cell and tissue lysate (phospho)proteomics to enable target discovery, patient stratification and response prediction.
These cancer research lines have been successfully applied in many collaborative projects in various tumor types, including colorectal cancer, breast cancer, lung cancer, pancreatic cancer, prostate cancer, and leukemias. The obtained (phospho)proteome data provide a valuable addition to the existing large collections of DNA and RNA datasets, thereby contributing to the multi-omics perspective of cancer and its precursors, and have revealed novel candidate biomarkers and drug targets that are in different phases of validation.
Biofluid proteomics
A highlight of research line 1 is the discovery and validation of novel stool markers for colorectal cancer screening using stool proteomics (Bosch et al., Ann. Intern. Med. 2017). Antibody assays for the top 10 protein stool markers have been being tested in prospective validation cohorts with positive results (De Klaver et al., Ann. Intern. Med. 2021). Cancer tissue secretome analyses in colorectal cancer have proven useful in identifying markers for non-invasive detection in plasma. These studies have also revealed the importance of non-conventional secretion in cancer. Another highlight is the urinary exosome proteomics work that reveals the potential for non-invasive stratification of progression risk in prostate cancer. Interestingly, distant cancers can also be detected in the urinary extracellular vesicle proteome.
Cancer cell and tumor tissue (phospho)proteomics
A highlight of research line 2 is the in-house developed computer algorithms that can pinpoint highly active protein kinases in single biological samples on the basis of label-free phosphoproteomic data (Integrative Inferred Kinase Activity (INKA) analysis, Beekhof et al., Mol. Syst. Biol. 2019). Its value for (combination) therapy selection was recently shown in the preclinical setting in several published studies (AML: Van Alphen, et al., MCP 2020; Cucchi et al., Hemasphere 2021; Renal Cancer: Van Beijnum et al., Cancers 2020; tALL: Cordo, et al., Nat Commun. 2022; PDAC: Valles et al., Cell Reports 2023; CRC: Beekhof et al., Science Transl. Med. 2023). Importantly, phosphoproteomics of clinical samples including needle biopsies is feasible as shown in several recent studies (Labots et al., Cancers 2020; Van Linde et al., Clin. Cancer Res. 2022; Wijngaart et al., Clin Proteomics. 2023).
Other highlights of research line 2 include the identification of protein biomarkers for prediction of response to platinum-based treatment regimens in patients with non-small cell lung cancer (Bottger et al., Mol. Oncol. 2023) and the generation of a large pan-cancer proteome landscape of >1000 tumors in an international collaborative effort.
A combined multi-omics view of the tumor of a patient, that includes not only the genome but also the functionally relevant proteome and phosphoproteome, is essential for advancing molecular cancer therapy and fulfilling the promise of personalized medicine.
For more information contact Connie Jimenez (c.jimenez@amsterdamumc.nl ).
Team members:
Core-group:
Thang Pham (staff scientist, focus data analysis) Berend Gagestein (staff scientist, focus mass spectrometry)
Jaco Knol (research technician, focus bioinformatics) Richard de Goeij- de Haas (research technician)
Irene Bijnsdorp (Associate member, staff scientist Dept. Urology)
Connie Jimenez (PI)
Franziska Bottger (post-doctoral fellow)
Alex Henneman (post-doctoral fellow)
Madalena Nunes Monteiro (PhD student)
Catarina Marques (PhD student)
Lijie Xu (PhD student)
Jianing Liu (PhD student)
Former PhD students working on their thesis:
Andrea Valles
Ayse Erozenci
Robin Beekhof
Financial support:
KWF
Health Holland
NWO
EU-ITN
Interested in proteomics?
As the proteomics core facility of the Amsterdam UMC, we provide support in all the steps of a proteomics experiment: study design (discussed at project intake with Jimenez), sample preparation (De Haas), mass spectrometry (Gagestein), and dedicated analysis (Pham). The results of our analysis are submitted in a user-friendly Excel file to end-users. Data management is in compliance with FAIR. Optional support in functional data mining is provided by Knol. The latest highthroughput mass spectrometer was installed in April 2023 with support of Amsterdam UMC.
For more information, see our website https://oncoproteomics.nl/
Text by Prof. Connie Jimenez.
This article was created for Cancer Center Amsterdam.