Evidence map›Paper›PMID 33028917›Full record

ArticleScientific reports2020

Multicompartment modeling of protein shedding kinetics during vascularized tumor growth.

Gautam B Machiraju, Parag Mallick, Hermann B Frieboes

Abstract read
In one paragraph

Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
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

4 citing papers in PubMed.

  1. AKR1B1 and AKR1B10 as Potential Prognostic Biomarkers of Endometrial Cancer.International journal of molecular sciences · 2026
    Article
  2. Article
  3. Review
  4. Review
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

3 authors.

Gautam B MachirajuBiomedical Informatics Training Program, Department of Biomedical Data Science, Stanford University, Stanford, CA, USA.
Parag MallickCanary Center at Stanford for Cancer Early Detection, Stanford University, Stanford, CA, USA. paragm@stanford.edu.
Hermann B FrieboesDepartment of Bioengineering, University of Louisville, Louisville, KY, USA. hbfrie01@louisville.edu.

Funding

POSTDOCTORAL TRAINING IN MEDICAL INFORMATION SCIENCEST15LM007033 · NLM · STANFORD UNIVERSITY · PI SYLVIA KATINA PLEVRITIS · 1985 to 2026
$25.5M
Biomedical Data Science Graduate Training at StanfordT32LM012409 · NLM · STANFORD UNIVERSITY · PI PLEVRITIS, SYLVIA KATINA · 2016 to 2020
$1.5M
Integrated framework to predict chemotherapy response post lung tumor resectionR15CA203605 · NCI · UNIVERSITY OF LOUISVILLE · PI FRIEBOES, HERMANN · 2016 to 2016
$462k
NCI NIH HHS R15 CA203605NIH HHS BD2K LM012409NLM NIH HHS T15 LM007033NLM NIH HHS T32 LM012409
6 · The paper itself

Abstract

Identification of protein biomarkers for cancer diagnosis and prognosis remains a critical unmet clinical need. A major reason is that the dynamic relationship between proliferating and necrotic cell populations during vascularized tumor growth, and the associated extra- and intra-cellular protein outflux from these populations into blood circulation remains poorly understood. Complementary to experimental efforts, mathematical approaches have been employed to effectively simulate the kinetics of detectable surface proteins (e.g., CA-125) shed into the bloodstream. However, existing models can be difficult to tune and may be unable to capture the dynamics of non-extracellular proteins, such as those shed from necrotic and apoptosing cells. The models may also fail to account for intra-tumoral spatial and microenvironmental heterogeneity. We present a new multi-compartment model to simulate heterogeneously vascularized growing tumors and the corresponding protein outflux. Model parameters can be tuned from histology data, including relative vascular volume, mean vessel diameter, and distance from vasculature to necrotic tissue. The model enables evaluating the difference in shedding rates between extra- and non-extracellular proteins from viable and necrosing cells as a function of heterogeneous vascularization. Simulation results indicate that under certain conditions it is possible for non-extracellular proteins to have superior outflux relative to extracellular proteins. This work contributes towards the goal of cancer biomarker identification by enabling simulation of protein shedding kinetics based on tumor tissue-specific characteristics. Ultimately, we anticipate that models like the one introduced herein will enable examining origins and circulating dynamics of candidate biomarkers, thus facilitating marker selection for validation studies.

Indexed as

Models, BiologicalHumansNeoplasmsNeovascularization, Pathologic

Identifiers

PMID33028917
PMCPMC7542472

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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.