Diagnostics-in-3D progress update 2021

About 7,000 rare hereditary diseases affect ±8% of the EU population, which translates to ±36 million people. Identification of causative mutations of such diseases thus, forms an essential step towards diagnosis as well as towards development of treatment. At CMBI, along with a multidisciplinary team of experts from BioProdict and Vartion, we are making efforts to predict (and eventually explain) functional effects of variants of unknown clinical significance.

Our EFRO funded project Diagnostics-in-3D uses an advanced deep learning framework known as DeepRank where we leverage information on protein structural features surrounding missense variants, coupled with the evolutionary significance of variant positions, and allow neural networks to learn from such variant environments. This exercise produces a probability estimate classifying whether a variant is disease-causing or not.

We have tailored DeepRank's 3D-CNN framework to help address our problem statement. One of the key aspects of this project is the diversity in variant environments captured from protein structures that differ depending on various protein families they belong to. Taking this aspect into account, we are now in the process of performance evaluation of our tool.

Research Departments Center for Molecular and Biomolecular Informatics

Center for Molecular and Biomolecular Informatics

The Center for Molecular and Biomolecular Informatics (CMBI) does research and education, and provides services in bioinformatics and cheminformatics.

Contact Head of the CMBI

Peter-Bram 't Hoen
head of department

+31 (0)24 361 93 90
contact


Mission & vision

Our mission

Our mission is to add value to personal health data by their translation into integrative knowledge and actionable information.

Our vision 

  • CMBI develops bioinformatics approaches that contribute to the understanding of disease mechanisms, personalized therapies and interventions, and a learning health care system
  • CMBI is committed to the reusability of their data, tools, and services
  • CMBI provides  bioinformatics researchers in Radboudumc with a platform for exchange of knowledge and expertise
  • CMBI contributes to the education of BMW, MLW, and MMD students so that they can apply and understand the principles behind (existing) bioinformatics tools

Radboudumc Technology Center Bioinformatics

The Bioinformatics technology center aims to raise and solve biological questions using the most recent computer technologies and big data solutions. read more

Education

Our mission is to provide a basic understanding in Bioinformatic principles. Follow-up courses are available for those who want to gain greater insight in our field. read more

Education

Researchers at the CMBI contribute to several courses at both the Faculty of Science and the Medical Faculty. We provide courses in Structural Bioinformatics, Comparative Genomics, Data Analysis, and programming courses such as Java. We specifically focus on the Molecular Life Science students, Biomedical Sciences students and participants in the master Molecular Mechanisms of Disease, although some of our courses can be chosen by Biology, Chemistry or Medical students as well. 

Our mission is to provide a basic understanding in Bioinformatic principles for bachelor students as this was shown to be beneficial for those who want to pursue a career in Life Sciences. Follow-up courses are available for those who want to gain greater insight in our field. 

For MLS/Biology students it is even possible to follow the B-track by choosing a combination of (master) Bioinformatics courses and internships at Bioinformatics departments. 

Our researchers also teach in special interest courses and summer schools here at the Radboudumc, the Radboud University and elsewhere.

 

For more information, you can contact dr. Hanka Venselaar, education coordinator at the CMBI.

 

 


Internships

The CMBI offers a wide range of possibilities for internships. read more

Internships

Both bachelor and master students from studies such as Molecular Life Sciences, Biomedical Sciences, Chemistry and MMD are welcome. In general, we are flexible in terms of internship length, type of internship and type of research. 

Below you can find our internship projects:


  • Deeper understanding of the immune system’s intricacies has led to clinical breakthroughs of personalized cancer vaccines in eliminating tumors in advanced-stage cancer patients1-4. Formulated with fragments from a patient’s tumor DNA, cancer vaccines train a patient’s own immune system to recognize a patient’s mutated cancer proteins as ‘foreign’ and wage a lethal attack against tumors (see key concepts in Box 1). The major puzzle in this field is: which of a patient’s hundreds of tumor mutations can trigger the immune system to attack tumors? Complementary to costly and time-consuming wet-lab screenings (e.g., Sipuleucel-T was priced at $93,0005), predictive algorithms that can quickly pinpoint neoantigens from a patient’s tumor DNA are urgently needed, if personalized cancer vaccines are to be applied on a large scale.

    Box 1. The TCR:peptide:MHC complex, neoantigens, and their pivotal role in the immune surveillance system and T-cell-mediated immune attacks on tumor cells6Cells constantly break down proteins into peptides. The major histocompatibility complex (MHC) proteins present some of these peptides on the cell surface. T cells are fired up when their T-cell receptor (TCR) recognizes tumor-specific peptides presented on the tumor cell surface by MHC proteins forming the TCR:peptide:MHC (TCR:pMHC) complex1,2 (Figure 1). MHC class I presents on the surface of every cell, while MHC II only presents on specific immune cells, e.g., dendritic cells. Tumor peptides presented by MHC-I can activate CD8+ T cells, which can directly kill tumor cells that present the peptides on their surface. Peptides presented by MHC-II can activate CD4+ T cells, which stimulate the production of antibodies and can provide help to CD8+ T cells.​ Such tumor-mutation derived peptides that are recognized by T cells as 'foreign' (i.e., immunogenic) are called neoantigens7. MHC epitopes: MHC-binding peptides. TCR epitopes: peptides that bind both MHC and TCR.

    Figure 1. TCR nomenclature and the TCR:pMHC complex. A TCR has two chains (α  and β ) and each chain has 3 loops (CDR1-3). It mainly uses CDR3 to interact with the peptide. Source: Leem et al. for 20188 for sub-figure a. and La Gruta et al. 20189 for b.

    Our overall aim is to improve the efficacy, safety and development time of existing T cell based cancer vaccine approaches. In this project, we aim to predict 3D peptide:MHC structures using a neural network simulator. 3D peptide:MHC structures bear crucial information for predicting effective cancer vaccine candidates, the major challenge of this field.

    You will learn:

    1. Advanced 3D modelling techniques for protein-protein complexes
    2. Advanced deep learning algorithms (dynamic GNN) on protein structures
    3. Basic knowledge of T cell based immunotherapy
    4. You will have opportunity to learning deep learning on these elegant molecules by joining our lab meetings and discussions with our collaborators - world-class deep learning experts at UvA.  
    5. Present your work
    6. Summarize your work in manuscript (and potential opportunities to be included in our publications)

    Your contributions:

    1. Develop, train and validate a dynamic graph network for modelling 3D peptide:MHC complexes.
    2. GitHub contribution to our 3D-Vac project.

    Requirements:

    1. Master students in MMD (molecular mechanism of diseases), MLS (molecular life sciences) program, Bioinformatics or related programs are welcome.
    2. Basic structural biology and biochemistry knowledge is required.
    3. Good programming skills (ideally python) is required.
    4. Basic deep learning knowledge is preferred.

    Time to start:

    As early as possible.

    Time last:

    6-12 months

    Contact:

    Li Xue: Li.Xue@radboudumc.nl

    References:

    1.        Ott, P. A. et al. An immunogenic personal neoantigen vaccine for patients with melanoma. Nature 547, 217–221 (2017).

    2.        Sahin, U. et al. Personalized RNA mutanome vaccines mobilize poly-specific therapeutic immunity against cancer. Nature 547, 222–226 (2017).

    3.        Harjes, U. Personal training by vaccination. Nature Reviews Cancer 17, 451

    4.        Sahin, U. & Türeci, Ö. Personalized vaccines for cancer immunotherapy. Science 359, 1355–1360 (2018).

    5.        Jaroslawski, S., Drugs, T. S.-T. B.2015. Autopsy of an innovative paradigm change in cancer treatment: Why a single-product Biotech company failed to capitalize on its breakthrough Invention.

    6.        Neefjes, J., Jongsma, M. L. M., Paul, P. & Bakke, O. Towards a systems understanding of MHC class I and MHC class II antigen presentation. Nature Reviews Immunology 2018 18:7 11, 823–836 (2011).

    7.        Schumacher, T. N. & Schreiber, R. D. Neoantigens in cancer immunotherapy. Science 348, 69–74 (2015).

    8.        Leem, J., de Oliveira, S. H. P., Krawczyk, K. & Deane, C. M. STCRDab: the structural T-cell receptor database. Nucleic Acids Res. 46, D406–D412 (2018).

    9.        La Gruta, N. L., Gras, S., Daley, S. R., Thomas, P. G. & Rossjohn, J. Understanding the drivers of MHC restriction of T cell receptors. Nature Reviews Immunology 2018 18:7 18, 467–478 (2018).

    10.     Renaud, N., Geng, C., Georgievska, S., Ambrosetti, F., Ridder, L., Marzella, D. F., ... & Xue, L. C. (2021). DeepRank: a deep learning framework for data mining 3D protein-protein interfaces. Nature communications, 12(1), 1-8.

     

     

     


Bioinformatics Services

We maintain computational facilities, databases, and software packages in bioinformatics. read more

Diagnostics-in-3D progress update 2021

Update on the EFRO funded project Diagnostics-in-3D. read more

Organization


Our researchers CMBI

A list of researchers connected to this department. read more

Getting there

Entrance: Radboud Institute for Molecular Life Sciences
Route: 260

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Getting there

Visiting address

Radboud Institute for Molecular Life Sciences
Geert Grooteplein 28
6525 GA Nijmegen

Directions

Enter building at: Radboud Institute for Molecular Life Sciences
Follow route 260

Contact Business manager

Nicolai Giling
Business manager

+31 (0)24 3686538
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Contact Operational manager

Barbara van Kampen
Operational manager

+31 (0)24 361 93 90
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Contact Management assistent

Sandra de Leeuw
Management assistent

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Research themes

Affiliated institutes

Radboud Institute for Health Sciences

This department is affiliated with RIHS. The research at this institute aims to improve clinical practice and public health. institute pages

Radboud Institute for Molecular Life Sciences

This department is affiliated with RIMLS. Their main aim is to achieve a greater understanding of the molecular mechanisms of disease. institute pages