Evidence map›Paper›PMID 30890944›Full record

ArticleFrontiers in physiology2019

Dynamic Targeting in Cancer Treatment.

Zhihui Wang, Thomas S Deisboeck

Open access · goldAbstract read
In one paragraph

Article in Frontiers in physiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
1.7field-weighted citation impact, top 18% 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

17 citing papers in PubMed, 31 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Review
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  7. Review
  8. Article
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  12. Article
  13. Image-guided mathematical modeling for pharmacological evaluation of nanomaterials and monoclonal antibodies.Wiley interdisciplinary reviews. Nanomedicine and nanobiotechnology · 2020
    Review
  14. A Multiscale Agent-Based Model of Ductal Carcinoma In Situ.IEEE transactions on bio-medical engineering · 2020
    Article
  15. Review
  16. Mathematical Modeling to Address Challenges in Pancreatic Cancer.Current topics in medicinal chemistry · 2020
    Article
  17. Development of a Physiologically-Based Mathematical Model for Quantifying Nanoparticle Distribution in Tumors.Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference · 2019
    Article
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

2 authors at 2 institutions in 1 country.

Zhihui WangMathematics in Medicine Program, Houston Methodist Research Institute, Houston, TX, United States.
Thomas S DeisboeckDepartment of Radiology, Harvard-MIT (HST) Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, United States.
Massachusetts General Hospital · USThe University of Texas MD Anderson Cancer Center · US

Funding

Transport Oncophysics CoreU54CA210181 · NCI · METHODIST HOSPITAL RESEARCH INSTITUTE · PI SHEN, HAIFA · 2016 to 2020
$9.3M
Imaging and Molecular Correlates of Progression in Cystic Neoplasms of the PancreasU01CA196403 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI MAITRA, ANIRBAN · 2015 to 2020
$5.8M
A Targeted Nanomedicine Prototype Against Enzalutamide-resistant Prostate CancerR01CA226537 · NCI · RBHS -CANCER INSTITUTE OF NEW JERSEY · PI ARAP, WADIH, BRINKER, C JEFFREY · 2018 to 2022
$3.2M
miR-155 targeted therapeutics for precision medicine in lung cancerR01CA222007 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI CALIN, GEORGE A., CRISTINI, VITTORIO · 2018 to 2022
$2.6M
Targeted therapeutics for ovarian cancer and its microenvironment - treatment and theoretical modelingU01CA213759 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI LOPEZ-BERESTEIN, GABRIEL · 2017 to 2021
$2.5M
NCI NIH HHS R01 CA222007NCI NIH HHS R01 CA226537NCI NIH HHS U01 CA196403NCI NIH HHS U01 CA213759NCI NIH HHS U54 CA210181
6 · The paper itself

Abstract

With the advent of personalized medicine, design and development of anti-cancer drugs that are specifically targeted to individual or sets of genes or proteins has been an active research area in both academia and industry. The underlying motivation for this approach is to interfere with several pathological crosstalk pathways in order to inhibit or at the very least control the proliferation of cancer cells. However, after initially conferring beneficial effects, if sub-lethal, these artificial perturbations in cell function pathways can inadvertently activate drug-induced up- and down-regulation of feedback loops, resulting in dynamic changes over time in the molecular network structure and potentially causing drug resistance as seen in clinics. Hence, the targets or their combined signatures should

Indexed as

drug discoverymathematical modelingnetwork medicinesignaling pathwaytherapeutic targettranslational research

Identifiers

PMID30890944
PMCPMC6413712
OpenAlexW2912919165

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.