Evidence map›Paper›PMID 26417077›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2015

Mathematical framework for activity-based cancer biomarkers.

Gabriel A Kwong, Jaideep S Dudani, Emmanuel Carrodeguas, Eric V Mazumdar, Seyedeh M Zekavat, Sangeeta N Bhatia

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.

0numbers the graph read from it
0cells of the map it votes in
33citing 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

33 citing papers in PubMed.

  1. Article
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  4. Targeting and monitoring ovarian cancer invasion with an RNAi and peptide delivery system.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  5. Article
  6. Liquid biopsies for early diagnosis of brain tumours:Journal of the Royal Society, Interface · 2022
    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

6 authors.

Gabriel A KwongInstitute for Medical Engineering and Science, Harvard-MIT Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA 02139; Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139;
Jaideep S DudaniKoch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139; Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139;
Emmanuel CarrodeguasInstitute for Medical Engineering and Science, Harvard-MIT Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA 02139; Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139;
Eric V MazumdarInstitute for Medical Engineering and Science, Harvard-MIT Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA 02139; Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139;
Seyedeh M ZekavatInstitute for Medical Engineering and Science, Harvard-MIT Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA 02139; Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139;
Sangeeta N BhatiaInstitute for Medical Engineering and Science, Harvard-MIT Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA 02139; Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139; Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA 02139; Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115; Howard Hughes Medical Institute, Chevy Chase, MD 20815 sbhatia@mit.edu.

Funding

VIRUS PRODUCTION COREP30CA014051 · NCI · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI MATTHEW G. VANDER HEIDEN · 1985 to 2026
$93.9M
Howard Hughes Medical InstituteNCI NIH HHS P30 CA014051
6 · The paper itself

Abstract

Advances in nanomedicine are providing sophisticated functions to precisely control the behavior of nanoscale drugs and diagnostics. Strategies that coopt protease activity as molecular triggers are increasingly important in nanoparticle design, yet the pharmacokinetics of these systems are challenging to understand without a quantitative framework to reveal nonintuitive associations. We describe a multicompartment mathematical model to predict strategies for ultrasensitive detection of cancer using synthetic biomarkers, a class of activity-based probes that amplify cancer-derived signals into urine as a noninvasive diagnostic. Using a model formulation made of a PEG core conjugated with protease-cleavable peptides, we explore a vast design space and identify guidelines for increasing sensitivity that depend on critical parameters such as enzyme kinetics, dosage, and probe stability. According to this model, synthetic biomarkers that circulate in stealth but then activate at sites of disease have the theoretical capacity to discriminate tumors as small as 5 mm in diameter-a threshold sensitivity that is otherwise challenging for medical imaging and blood biomarkers to achieve. This model may be adapted to describe the behavior of additional activity-based approaches to allow cross-platform comparisons, and to predict allometric scaling across species.

Indexed as

Models, BiologicalAnimalsBiomarkers, TumorHumansMiceMice, NudeMolecular ImagingNanomedicineNeoplasms, ExperimentalBiomarkers, Tumoractivity-based probescancer diagnosticscompartmental modelingnanomedicineurine biomarkers

Identifiers

PMID26417077
PMCPMC4611621

What OpenQuestion holds

Textmetadata
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.