Evidence map›Paper›PMID 35445686›Full record

ReviewSoft matter2022

Materials-driven approaches to understand extrinsic drug resistance in cancer.

Justin R Pritchard, Michael J Lee, Shelly R Peyton

Abstract readReview
In one paragraph

Review in Soft matter, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

3 authors.

Justin R PritchardDepartment of Biomedical Engineering, Pennsylvania State University, State College PA, USA.
Michael J LeeDepartment of Systems Biology, University of Massachusetts Chan Medical School, Worcester, MA, USA.
Shelly R PeytonDepartment of Chemical Engineering, University of Massachusetts Amherst, 240 Thatcher Way, Life Sciences Laboratory N531, Amherst, MA 01003, USA. speyton@umass.edu.ORCID http://orcid.org/0000-0002-7364-8727

Funding

Personalization and Failure Testing of Dual Switch Gene Drives in Lung CancerU01CA265709 · NCI · PENNSYLVANIA STATE UNIVERSITY, THE · PI PRITCHARD, JUSTIN · 2021 to 2025
$2.6M
Model Driven Construction of Dual-switch Selection Gene Drives to Combat Drug ResistanceR21EB026617 · NIBIB · PENNSYLVANIA STATE UNIVERSITY, THE · PI PRITCHARD, JUSTIN · 2019 to 2021
$628k
NCI NIH HHS U01 CA265709NIBIB NIH HHS R21 EB026617
6 · The paper itself

Abstract

Metastatic cancer has a poor prognosis, because it is broadly disseminated and associated with both intrinsic and acquired drug resistance. Critical unmet needs in effectively killing drug resistant cancer cells include overcoming the drug desensitization characteristics of some metastatic cancers/lesions, and tailoring therapeutic regimens to both the tumor microenvironment and the genetic profiles of the resident cancer cells. Bioengineers and materials scientists are developing technologies to determine how metastatic sites exclude therapies, and how extracellular factors (including cells, proteins, metabolites, extracellular matrix, and abiotic factors) at metastatic sites significantly affect drug pharmacodynamics. Two looming challenges are determining which feature, or combination of features, from the tumor microenvironment drive drug resistance, and what the relative impact is of extracellular signals

Indexed as

NeoplasmsDrug ResistanceExtracellular MatrixHumansTumor Microenvironment

Identifiers

PMID35445686
PMCPMC9380814

What OpenQuestion holds

Textmetadata
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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.