Evidence map›Paper›PMID 24408919›Full record

ArticleCancer research2014

Bridging population and tissue scale tumor dynamics: a new paradigm for understanding differences in tumor growth and metastatic disease.

Jill Gallaher, Aravind Babu, Sylvia Plevritis, Alexander R A Anderson

Abstract read
In one paragraph

Article in Cancer research, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
2.0field-weighted citation impact, top 13% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed, 19 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Review
  5. The viable circulating tumor cells with cancer stem cells feature, where is the way out?Journal of experimental & clinical cancer research : CR · 2018
    Review
  6. Article
  7. Article
  8. Tissue-scale, personalized modeling and simulation of prostate cancer growth.Proceedings of the National Academy of Sciences of the United States of America · 2016
    Article
  9. Article
  10. Article
  11. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 2 institutions in 1 country.

Jill GallaherIntegrated Mathematical Oncology, Moffitt Cancer Center, Tampa, FL 33612.
Aravind BabuInstitute for Computational and Mathematical Engineering, Stanford University, Stanford, CA 94305.
Sylvia Plevritis *Department of Radiology, Stanford University School of Medicine, Stanford, CA 94305.
Alexander R A Anderson *Integrated Mathematical Oncology, Moffitt Cancer Center, Tampa, FL 33612.
Moffitt Cancer Center · USStanford University · US

Funding

TrainingU54CA113007 · NCI · VANDERBILT UNIVERSITY · PI QUARANTA, VITO · 2004 to 2014
$19.2M
MODELING THE ROLE OF PROGRESSION IN FOLLICULAR LYMPHOMAU54CA149145 · NCI · STANFORD UNIVERSITY · PI PLEVRITIS, SYLVIA KATINA · 2010 to 2014
$12.1M
Comparative Modeling of Lung Cancer Control PoliciesU01CA152956 · NCI · MASSACHUSETTS GENERAL HOSPITAL · PI DE KONING, HARRY J, KONG, CHUNG YIN · 2010 to 2014
$7.4M
Predicting Prostate Cancer AggressivenessU01CA151924 · NCI · H. LEE MOFFITT CANCER CTR & RES INST · PI ANDERSON, ALEXANDER ROBERTSON ALLAN, AYALA, GUSTAVO ENRIQUE · 2011 to 2015
$2.8M
Breast Cancer Trend Analysis Using Stochastic Stimulati*U01CA088248 · NCI · STANFORD UNIVERSITY · PI PLEVRITIS, SYLVIA KATINA · 2000 to 2009
$2.0M
Cost Effectiveness Analysis of Lung Cancer ScreeningR01CA105366 · NCI · STANFORD UNIVERSITY · PI PLEVRITIS, SYLVIA KATINA · 2004 to 2006
$976k
NCI NIH HHS 1R01CA105366NCI NIH HHS 1U01CA088248NCI NIH HHS R01 CA105366NCI NIH HHS U01 CA088248NCI NIH HHS U01 CA151924NCI NIH HHS U01CA151924NCI NIH HHS U01 CA152956NCI NIH HHS U01CA159256NCI NIH HHS U54 CA113007NCI NIH HHS U54CA113007NCI NIH HHS U54 CA149145NCI NIH HHS U54CA149145
6 · The paper itself

Abstract

To provide a better understanding of the relationship between primary tumor growth rates and metastatic burden, we present a method that bridges tumor growth dynamics at the population level, extracted from the SEER database, to those at the tissue level. Specifically, with this method, we are able to relate estimates of tumor growth rates and metastatic burden derived from a population-level model to estimates of the primary tumor vascular response and the circulating tumor cell (CTC) fraction derived from a tissue-level model. Variation in the population-level model parameters produces differences in cancer-specific survival and cure fraction. Variation in the tissue-level model parameters produces different primary tumor dynamics that subsequently lead to different growth dynamics of the CTCs. Our method to bridge the population and tissue scales was applied to lung and breast cancer separately, and the results were compared. The population model suggests that lung tumors grow faster and shed a significant number of lethal metastatic cells at small sizes, whereas breast tumors grow slower and do not significantly shed lethal metastatic cells until becoming larger. Although the tissue-level model does not explicitly model the metastatic population, we are able to disengage the direct dependency of the metastatic burden on primary tumor growth by introducing the CTC population as an intermediary and assuming dependency. We calibrate the tissue-level model to produce results consistent with the population model while also revealing a more dynamic relationship between the primary tumor and the CTCs. This leads to exponential tumor growth in lung and power law tumor growth in breast. We conclude that the vascular response of the primary tumor is a major player in the dynamics of both the primary tumor and the CTCs, and is significantly different in breast and lung cancer.

Indexed as

AlgorithmsBreast NeoplasmsChemotaxisFemaleHumansHypoxiaLung NeoplasmsModels, StatisticalModels, TheoreticalMonte Carlo MethodNecrosisNeoplasm MetastasisNeoplastic Cells, CirculatingOxygenPopulation DynamicsSEER ProgramOxygenVascular Endothelial Growth Factor AVEGFA protein, human

Identifiers

PMID24408919
PMCPMC3913019
OpenAlexW2142826053

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.