OncoProteomics Laboratory

Research aims

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.

Connie Jimenez

Cutting-edge mass spectrometry and bioinformatics

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. Dedicated statistics and bioinformatic solutions are contineously being developed (IQ, INKA and more).

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 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 (see references below). 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 (submitted).

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.

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 (Piersma), and dedicated analysis (Pham). The results of our analysis are submitted in a user-friendly Excel file to end-users (Knol). 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/

Group members

PostDocs/senior researchers:

  • Dr. Thang Pham
  • Dr. Sander Piersma
  • Dr. Irene Bijnsdorp (Dept. Urology)
  • Dr. Alex Henneman
  • Dr. Franziska Böttger

Research technicians

  • Dr. Jaco Knol
  • Dr. Richard de Goeij de Haas

Current PhD students:

  • Catarina de Almeida Marques
  • Lijie Xu
  • Jianing Liu

PhD students writing thesis:

  • Madalena Nunes Monteiro
  • Ayse Erözenci
  • Robin Beekhof

        Key publications

        Novel Stool-Based Protein Biomarkers for Improved Colorectal Cancer Screening: A Case-Control Study
        Bosch LJW, de Wit M, Pham TV, Coupé VMH, Hiemstra AC, Piersma SR, Oudgenoeg G, Scheffer GL, Mongera S, Sive Droste JT, Oort FA, van Turenhout ST, Larbi IB, Louwagie J, van Criekinge W, van der Hulst RWM, Mulder CJJ, Carvalho B, Fijneman RJA, Jimenez CR, Meijer GA.
        Ann Intern Med. 2017 Dec 19;167(12):855-866.

        Feasibility of urinary extracellular vesicle proteome profiling using a robust and simple, clinically applicable isolation method
        Bijnsdorp IV, Maxouri O, Kardar A, Schelfhorst T, Piersma SR, Pham TV, Vis A, van Moorselaar RJ, Jimenez CR.
        J Extracell Vesicles. 2017 Apr 28;6(1):1313091.

        Longitudinal stability of urinary extracellular vesicle protein patterns within and between individuals
        Erozenci LA, Piersma SR, Pham TV, Bijnsdorp IV, Jimenez CR.
        Sci Rep. 2021 Aug 2;11(1):15629. doi: 10.1038/s41598-021-95082-8. PMID: 34341426; PMCID: PMC8329217.

        INKA, an integrative data analysis pipeline for phosphoproteomic inference of active kinases.
        Beekhof R, van Alphen C, Henneman AA, Knol JC, Pham TV, Rolfs F, Labots M, Henneberry E, Le Large TY, de Haas RR, Piersma SR, Vurchio V, Bertotti A, Trusolino L, Verheul HM, Jimenez CR.
        Mol Syst Biol. 2019 May 24;15(5):e8981.

        Phosphoproteomic profiling of T cell acute lymphoblastic leukemia reveals targetable kinases and combination treatment strategies
        Cordo V, Meijer MT, Hagelaar R, de Goeij-de Haas RR, Poort VM, Henneman AA, Piersma SR, Pham TV, Oshima K, Ferrando AA, Zaman GJR, Jimenez CR, Meijerink JPP.
        Nat Commun. 2022 Feb 25;13(1):1048.

        Phosphotyrosine-based Phosphoproteomics for Target Identification and Drug Response Prediction in AML Cell Lines
        van Alphen C, Cloos J, Beekhof R, Cucchi DGJ, Piersma SR, Knol JC, Henneman AA, Pham TV, van Meerloo J, Ossenkoppele GJ, Verheul HMW, Janssen JJWM, Jimenez CR.
        Mol Cell Proteomics. 2020 May;19(5):884-899.

        Phosphoproteomics guides effective low-dose drug combinations against pancreatic ductal adenocarcinoma
        Vallés-Martí A, Mantini G, Manoukian P, Waasdorp C, Sarasqueta AF, de Goeij-de Haas RR, Henneman AA, Piersma SR, Pham TV, Knol JC, Giovannetti E, Bijlsma MF, Jiménez CR.
        Cell Rep. 2023 Jun 27;42(6):112581.

        Phosphoproteomics of patient-derived xenografts identifies targets and markers associated with sensitivity and resistance to EGFR blockade in colorectal cancer
        Beekhof R, Bertotti A, Böttger F, Vurchio V, Cottino F, Zanella ER, Migliardi G, Viviani M, Grassi E, Lupo B, Henneman AA, Knol JC, Pham TV, de Goeij-de Haas R, Piersma SR, Labots M, Verheul HMW, Trusolino L, Jimenez CR.
        Sci Transl Med. 2023 Aug 16;15(709):eabm3687.

        Kinase activities in pancreatic ductal adenocarcinoma with prognostic and therapeutic avenues
        Vallés-Martí A, de Goeij-de Haas RR, Henneman AA, Piersma SR, Pham TV, Knol JC, Verheij J, Dijk F, Halfwerk H, Giovannetti E, Jiménez CR, Bijlsma MF.
        Mol Oncol. 2024 Apr 22.

        Identification of protein biomarkers for prediction of response to platinum-based treatment regimens in patients with non-small cell lung cancer
        Böttger F, Radonic T, Bahce I, Monkhorst K, Piersma SR, Pham TV, Dingemans AC, Hillen LM, Santarpia M, Giovannetti E, Smit EF, Burgers SA, Jimenez CR.
        Mol Oncol. 2024 Jun;18(6):1417-1436.

        Standardization and harmonization of distributed multi-center proteotype analysis supporting precision medicine studies
        Xuan Y, Bateman NW, Gallien S, Goetze S, Zhou Y, Navarro P, Hu M, Parikh N, Hood BL, Conrads KA, Loosse C, Kitata RB, Piersma SR, Chiasserini D, Zhu H, Hou G, Tahir M, Macklin A, Khoo A, Sun X, Crossett B, Sickmann A, Chen YJ, Jimenez CR, Zhou H, Liu S, Larsen MR, Kislinger T, Chen Z, Parker BL, Cordwell SJ, Wollscheid B, Conrads TP.
        Nat Commun. 2020 Oct 16;11(1):5248.

        Contact

        c.jimenez@amsterdamumc.nl
        www.oncoproteomics.nl

        Keywords

        (Phospho) Proteomics | Mass Spectrometry | Biomarker / Target Discovery | Kinase Activty | Extracellular Vesicle | Microbiome | Biofluids/ Secretome