SwePub
Sök i LIBRIS databas

  Utökad sökning

onr:"swepub:oai:gup.ub.gu.se/281063"
 

Sökning: onr:"swepub:oai:gup.ub.gu.se/281063" > Inferring rates of ...

Inferring rates of metastatic dissemination using stochastic network models

Gerlee, Philip, 1980 (författare)
Gothenburg University,Göteborgs universitet,Institutionen för matematiska vetenskaper,Department of Mathematical Sciences,Chalmers tekniska högskola,Chalmers University of Technology
Johansson, Mia, 1977 (författare)
Gothenburg University,Göteborgs universitet,Institutionen för kliniska vetenskaper, Avdelningen för onkologi,Institute of Clinical Sciences, Department of Oncology,University of Gothenburg
 (creator_code:org_t)
2019-04-01
2019
Engelska.
Ingår i: Plos Computational Biology. - : Public Library of Science (PLoS). - 1553-7358 .- 1553-734X. ; 15:4
  • Tidskriftsartikel (refereegranskat)
Abstract Ämnesord
Stäng  
  • The formation of metastases is driven by the ability of cancer cells to disseminate from the site of the primary tumour to target organs. The process of dissemination is constrained by anatomical features such as the flow of blood and lymph in the circulatory system. We exploit this fact in a stochastic network model of metastasis formation, in which only anatomically feasible routes of dissemination are considered. By fitting this model to two different clinical datasets (tongue & ovarian cancer) we show that incidence data can be modelled using a small number of biologically meaningful parameters. The fitted models reveal site specific relative rates of dissemination and also allow for patient-specific predictions of metastatic involvement based on primary tumour location and stage. Applied to other data sets this type of model could yield insight about seed-soil effects, and could also be used in a clinical setting to provide personalised predictions about the extent of metastatic spread. Author summary For most cancer patients the occurrence of metastases equals incurable disease. Despite this fact our quantitative knowledge about the process of metastatic dissemination is limited. In this manuscript we improve on a previously published mathematical model by incorporating known biological facts about metastatic spread and also consider the temporal dimension of dissemination. The model is fit to two different cancer types with very different patterns of spread, which highlights the versatility of our framework. Properly parametrised this type of model can be used for making personalised predictions about metastatic burden.

Ämnesord

MEDICIN OCH HÄLSOVETENSKAP  -- Klinisk medicin -- Cancer och onkologi (hsv//swe)
MEDICAL AND HEALTH SCIENCES  -- Clinical Medicine -- Cancer and Oncology (hsv//eng)
NATURVETENSKAP  -- Data- och informationsvetenskap -- Bioinformatik (hsv//swe)
NATURAL SCIENCES  -- Computer and Information Sciences -- Bioinformatics (hsv//eng)
NATURVETENSKAP  -- Biologi -- Bioinformatik och systembiologi (hsv//swe)
NATURAL SCIENCES  -- Biological Sciences -- Bioinformatics and Systems Biology (hsv//eng)

Nyckelord

circulating tumor-cells
ovarian-cancer
hematogenous metastasis
lung-cancer
neck
blood
head
identification
carcinoma
patterns
Biochemistry & Molecular Biology
Mathematical & Computational Biology

Publikations- och innehållstyp

ref (ämneskategori)
art (ämneskategori)

Hitta via bibliotek

Till lärosätets databas

Sök utanför SwePub

Kungliga biblioteket hanterar dina personuppgifter i enlighet med EU:s dataskyddsförordning (2018), GDPR. Läs mer om hur det funkar här.
Så här hanterar KB dina uppgifter vid användning av denna tjänst.

 
pil uppåt Stäng

Kopiera och spara länken för att återkomma till aktuell vy