Roskilde University Entrance

The Cancitis research group

About Us

Cancitis – an abbreviation of Cancer and the Latin word itis for inflammation - is part of the National Center for Mathematical Modeling - Human Health and Disease (COMMAND) at RUC. The Center for Mathematical Modeling - Health and Disease collaborates with the PandemiX Center, Center for Big Data and Center for Sundhedsfremmeforskning at RUC.

Nationally we have a well established collaboration with Hospitals in Region Copenhagen and in particular Dept. of Hematology, Region Zealand, Roskilde. The collaboration includes co-financed PhD students/postdocs focusing on educating and recruiting young researchers. We are member of the Danish Life Science Cluster “Center for (Early) Diagnosis and Treatment/Clinical Health Data Science” and Key member of the Greater Copenhagen CAG (Clinical Academic Group) initiative “ZIRI: The Zealand Inflammation Research Initiative. Chronic Inflammation, Vascular Diseases, and Cancer. Mutations in Blood Cells - a Common Link?”.

The Cancitis group and the Center for Mathematical Modeling - Health and Disease at RUC host a recent Lundbeck-Foundation’s Fellowship led by Prof. Thomas Stiehl. The Fellowship project on “Mathematical modeling of Acute Leukemia” (2021-2025) is a five-year and 10 Mill DKK grant in collaboration with Zealand University Hospital, Department of Hematology. The team members have successfully been investigating ways to work with Region Zealand and Region Copenhagen blood bank data and the Statens Serum Institute to create a brand new natural observatory for disease protection (antibodies, mutations, etc.) in Danish population age cohorts.

Our Team

Morten Andersen

Associate Professor

RUC Research Profile.

Johanne Gudmand-Høyer

Assistant Professor

RUC Research Profile.

Jordan Andrew Snyder

Assistant Professor

RUC Research Profile.

Tobias Idor Boklund

Ph.D. student

RUC Research Profile.

Previous members

Marc John Bordier Dam

Ph.D. student

RUC Research Profile.

Rasmus K. Pedersen

Ph.D. graduate, 2020

RUC Research Profile.

Personal Website.

Zamra Sajid

Ph.D. graduate, 2021

RUC Research Profile.

Published articles and other work

System dynamics of cancer in erythropoiesis with multiple EPO feedbacks

Published in System Dynamics Review, 2021, 36(4)

DOI: 10.1002/sdr.1670

Zamra Sajid, Morten Andersen and Johnny T. Ottesen

Link to journal

Mathematical modelling of the hematopoietic stem cell-niche system: Clonal dominance based on stem cell fitness

Published in Journal of Theoretical Biology, 2021, 518

DOI: 10.1016/j.jtbi.2021.110620

Rasmus Kristoffer Pedersen, Morten Andersen, Thomas Stiehl and Johnny T. Ottesen

Link to journal

Dynamics of competing heterogeneous clones in blood cancers explains multiple observations - a mathematical modeling approach

Published in Mathematical Biosciences and Engineering, 2020, 17(6)

DOI: 10.3934/mbe.2020389

Katrine O. Bangsgaard, Morten Andersen, Vibe Skov, Lasse Kjær, Hans C. Hasselbalch and Johnny T. Ottesen

Link to journal View PDF

Global dynamics of healthy and cancer cells competing in the hematopoietic system

Published in Mathematical Biosciences, 2020, 326

DOI: 10.1016/j.mbs.2020.108372

Morten Andersen, Hans C. Hasselbalch, Lasse Kjær, Vibe Skov and Johnny T. Ottesen

Link to journal View PDF

Data-driven analysis of JAK2V617F kinetics during interferonalpha2 treatment of patients with polycythemia vera and related neoplasms

Published in Cancer Medicine, January 2020

DOI: 10.1002/cam4.2741

Rasmus K. Pedersen, Morten Andersen, Trine A. Knudsen, Zamra Sajid, Johanne Gudmand-Hoeyer, Marc J. B. Dam, Vibe Skov, Lasse Kjær, Christina Ellervik, Thomas S. Larsen, Dennis Hansen, Niels Pallisgaard, Hans C. Hasselbalch and Johnny T. Ottesen

Link to journal View PDF View supplementary material

Mathematical Analysis of the Cancitis model and the role of inflammation in blood cancer progression.

Published in Mathematical Biosciences and Engineering, 2019, 16(6)

DOI: 10.3934/mbe.2019418

Zamra Sajid, Morten Andersen and Johnny T. Ottesen

Link to journal View PDF

Bridging blood cancers and inflammation: The reduced Cancitis model

Published in Journal of Theoretical Biology, 2019, Volume 465

DOI: 10.1016/j.jtbi.2019.01.001

Johnny T. Ottesen, Rasmus K. Pedersen, Zamra Sajid, Johanne Gudmand-Høyer, Katrine O. Bangsgaard, Vibe Skov, Lasse Kjær, Trine A. Knudsen, Niels Pallisgaard, Hans C. Hasselbalch, and Morten Andersen

Link to journal View PDF Additional info and figures

Mathematical Modelling as a Proof of Concept for MPNs as a Human Inflammation Model for Cancer Development

Published in PLoS One, 2017 12(8)

DOI: 10.1371/journal.pone.0183620

Morten Andersen, Zamra Sajid, Rasmus K. Pedersen, Johanne Gudmand-Hoeyer, Christina Ellervik, Vibe Skov, Lasse Kjær, Niels Pallisgaard, Torben A. Kruse, Mads Thomassen, Jesper Troelsen, Hans Carl Hasselbalch, Johnny T. Ottesen

Link to journal View PDF View supplementary material

Collaborators

  • Hans Hasselbalch, Lasse Kjær, Vibe Skov, Trine A. Knudsen and Morten K. Larsen
    Hematological Department, Zealand University Hospital, Denmark
  • Thomas Stiehl and Steffen Koschmieder
    Aachen University Medical Center, Germany
  • Mads Hall Andersen
    National Center for Cancer Immune therapy (CCIT-dk), University Hospital Herlev, Denmark
  • Lars Rønn Olesen
    Cancer Genomics, Section for Bioinformatics, DTU Health Technology & Center for Genomic Medicine, Copenhagen University Hospital
  • Claus Henrik Nielsen
    Rigshospitalet
  • Nina Øbro
    Dept of Clinical Immunology Copenhagen University Hospital, Rigshospitalet
  • Helen Byrne
    Applied Mathematics, Mathematical Institute University of Oxford
  • David Kent
    Department of Biology, York University, UK
  • Ann Mullally
    Department of Medicine Harvard University
  • Christina Ellervik
    Harvard Medical School, Boston, USA
  • Mette Olufsen
    Bio-mathematics, NCSU, USA
  • Aurelius de los Reyes V
    University of the Philippines, Philippines

Other things

Presentations, posters and seminars.

"Modelling Hematopoietic Stem Cells and their Interaction with the Bone Marrow Microenvironment"

Talk (Online) - Statistic and Biomathematics Seminar, Chalmers University of Technology, Gothenburg - April 21st 2020

Rasmus Kristoffer Pedersen

Slides

Stem Cell Modelling Day

Seminar at Roskilde University - September 18th 2019

Speakers: Rasmus Kristoffer Pedersen (Roskilde University), Thomas Stiehl (Heidelberg University), Jesper Troelsen (Roskilde University) and Peter Ashcroft (ETH Zurich)

"Hematopoiesis or inflammation driven blood cancer? Insights from mathematical modelling"

Talk - SMB 2019, Montreal

Morten Andersen

"Modelling Myeloproliferative Neoplasms - Dynamics of myeloid cell lin for Ph-negative MPNs"

Poster - SMB 2019, Montreal

Zamra Sajid

"Modelling the Dynamics of Hematopoietic Stem Cells"

Poster - SMB 2019, Montreal

Rasmus Kristoffer Pedersen

"The Cancitis model: a coupled leukemic-inflammatory response"

Talk - ECMTB 2018, Lisbon

Johnny T. Ottesen

"Mathematical modelling of blood cancer evolution"

Talk - ECMTB 2018, Lisbon

Morten Andersen

"Modelling the myeproliferative neoplasms (MPNs): Stability analysis & sensitivty analysis"

Poster - ECMTB 2018, Lisbon

Zamra Sajid

"Modelling of quiescent stem cells in relation to myeloproliferative neoplasms"

Poster - ECMTB 2018, Lisbon

Rasmus Kristoffer Pedersen

Outreach and dissemination

Hematologic Biomarker Index

Animation of the Hematologic Biomarker Index

Cohort of patients treated with either Hydroxyurea or Interferon-alpha animated over time from baseline (time of diagnoses) to 36 month after. First axis show percent changes in JAK2 allele burden and second axis shows the hematopoietic Biomarker Index (HBI), a weighted average of distance to normalized blood cell levels. Full remission corresponds to be at the lower left corner of the diagram. To calculate the HBI we determine the distance from the normal level for each of the three biomarkers (leucocyte count, platelet count and LDH). If a measurement lies above the normal level we calculate the distance to the upper limit of the normal level and if the measurement lies below the normal level we calculate the distance to the lower limit of the normal level. If a measurement falls within the normal level it adds zero to the HBI. To give each biomarker comparable weight we weigh the distances by the upper limit for the normal level of each biomarker. An example of the HBI calculation: The numbers indicate how far from the normal level each measurement is. The measurements which fall inside the normal levels do not contribute to the HBI. Taking the final measurement as an example the thrombocyte contribution is 264/390 ≈ 0.68, the leucocyte contribution is 4.0/8.8 ≈ 0.45 and the LDH contribution is 123/230 ≈ 0.53 and thus the HBI in this case is approximately 0.68 + 0.45 + 0.53 = 1.66. If the three cell counts were all in the normal range the HBI would be 0.

"SRP/SOP materiale"

High-school teaching material

Problem-statements and examples for use for danish high-school students working on either SRP or SOP assignments.

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"Gryende forskningsfelt: Matematikere og læger er et godt mathc"

"Ugeskriftet for Læger" article

Danish article about our collaboration with clinicians.

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"Matematik giver mere effektiv kræftbehandling"

"Tæt på Videnskaben" article

Danish article about blood cancers and our work.

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"Undervisningspakke - Matematisk modellering af cancer"

High-school teaching material (Only in danish)

Collection of various material, intended for use in danish high-school in collaboration with Roskilde University.

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Video (In danish)

"Så Vidt Vi Ved - P1"

Radio-interview (Only in danish)

Danish radio feature about mathematical modelling and blood cancers.

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Student projects

"Forudsigelser og beregninger i evolutionær spilteori og anvendelsen af dem i forbindelse med modellering af cancer"

Student project

2020

Malthe Frøkjær-Rubbås

"Investigating the Structural Identifiability Analysis by Extended Observability Method"

Bachelor Thesis and Subject Module

2019

Magnus Skjold Frederiksen, Uffe Bundesen, Karl Skovfoged Nordentoft, Kenny Haslund Andersen, Max Thrane Nielsen and Poul Thrane

"Modeling the interaction between the immune system and leukemia"

Bachelor 1st semester project

2019

Stine G. Fohrmann, Lukas Rasocha, Jūlija Tumanovska, Julien Hirsch and Kata M. Riegels

"Matematisk modellering af dynamikken mellem T-celler og cancerceller"

Bachelor 2nd semester project

2019

Ilayda Dilara Pusat, Emira Havkic and Kimmie Britoft

"Bag om Matematisk Modellering"

Bachelor 3rd semester project

2018

Bjørn Dan Orfang Nielsen, Frederik Vedel Gantzel, Karl Skovfoged Nordentoft, Kenny Haslund Andersen, Max Thrane Nielsen and Poul Thrane

"Matematisk modellering af non-hodgkins lymfoma"

Bachelor semester project

2018

Daniel Vestma Norén, Emely Overby, Kimmie Schäfferling Britoft, Mads Jens Køie Nielsen, Mette Michelle Unterborg Alempiew and Michelle Vigant Nielsen

"Mathematical Modeling of Blood Cancer"

Master semester project

2018

Katrine O. Bangsgaard

"How can a mathematical model aid in curing leukaemia?"

Bachelor semester project

2018

Mathis Brette Mortensen, Natalia Stati, Irida Gkouzou and Magnus Skjold Frederiksen

"Parameters estimation in a Myeloproliferative Neoplasm model"

Master semester project

2017

Jeannie Bøg Rasmussen, Maria Nørr and Mehmet Temizsoy

"Quasi-SteadyState assumption on a Mathematical Model of Leukemia"

Bachelor semester project

2017

Mikkel Zielinski Ajslev, Hasan M. M. Osman and Stefan Bisgaard

The Cancitis Model

Our main work concerns the Cancitis Model, as introduced in our 2017 PLOS One paper. Below is a schematic overview of the compartments of the model.

The corresponding system of ordinary differential equations is given as:

$$ \begin{align} \frac{dx_0}{dt} &= (r_x \phi_x s- a_x - d_{x0}) x_0 - r_m s x_0 \\ \frac{dx_1}{dt} &= a_x A_x x_0 - d_{x1} x_1 \\ \frac{dy_0}{dt} &= (r_y \phi_y - a_y - d_{y0}) y_0 + r_m s x_0 \\ \frac{dy_1}{dt} &= a_y A_y y_0 - d_{y1} y_1 \\ \frac{da}{dt} &= d_{x0} x_0 + d_{y0} y_0 + d_{x1} x_1 + d_{y1} y_1 -e_a a s\\ \frac{ds}{dt} &= r_s a - e_s s + I \end{align} $$
where \( \phi_x (x_0,y_0) = \frac{1}{1+c_{xx}x_0 + c_{xy}y_0} \) and \( \phi_y (x_0,y_0) = \frac{1}{1+c_{yx}x_0 + c_{yy}y_0} \)

In our 2019 JTB paper (Ottesen et al, 2019), we showed that a model reduction is possible. More information and additional figures can be found here.