Evidence map›Paper›PMID 32566069›Full record

ArticleBiomicrofluidics2020

The promise of single-cell mechanophenotyping for clinical applications.

Molly Kozminsky, Lydia L Sohn

Abstract read
In one paragraph

Article in Biomicrofluidics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
  4. Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. Mechanical Measurements of Cells Using AFM: 3D or 2D Physics?Frontiers in bioengineering and biotechnology · 2020
    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.

Molly KozminskyCalifornia Institute for Quantitative Biosciences, University of California, 174 Stanley Hall, Berkeley, California 94720, USA.ORCID 0000-0001-7040-1641

Funding

Mechanical Phenotyping of Random Periaerolar Fine Needle Aspiration-Collected Cells for Early Breast Cancer DetectionR01EB024989 · NIBIB · UNIVERSITY OF CALIFORNIA BERKELEY · PI Mark A LaBarge, Lydia L Sohn · 2017 to 2026
$4.8M
A Label-Free, Point-of-Care Platform to Diagnose Acute Promyelocytic LeukemiaR01CA190843 · NCI · UNIVERSITY OF CALIFORNIA BERKELEY · PI FEUSNER, JAMES, SOHN, LYDIA L · 2015 to 2019
$1.6M
DNA-Directed Micropatterning of Cells to Investigate Prostate Cancer Dormancy in the Bone MarrowF32CA243354 · NCI · UNIVERSITY OF CALIFORNIA BERKELEY · PI KOZMINSKY, MOLLY · 2019 to 2021
$195k
NCI NIH HHS F32 CA243354NCI NIH HHS R01 CA190843NIBIB NIH HHS R01 EB024989
6 · The paper itself

Abstract

Cancer is the second leading cause of death worldwide. Despite the immense research focused in this area, one is still not able to predict disease trajectory. To overcome shortcomings in cancer disease study and monitoring, we describe an exciting research direction: cellular mechanophenotyping. Cancer cells must overcome many challenges involving external forces from neighboring cells, the extracellular matrix, and the vasculature to survive and thrive. Identifying and understanding their mechanical behavior in response to these forces would advance our understanding of cancer. Moreover, used alongside traditional methods of immunostaining and genetic analysis, mechanophenotyping could provide a comprehensive view of a heterogeneous tumor. In this perspective, we focus on new technologies that enable single-cell mechanophenotyping. Single-cell analysis is vitally important, as mechanical stimuli from the environment may obscure the inherent mechanical properties of a cell that can change over time. Moreover, bulk studies mask the heterogeneity in mechanical properties of single cells, especially those rare subpopulations that aggressively lead to cancer progression or therapeutic resistance. The technologies on which we focus include atomic force microscopy, suspended microchannel resonators, hydrodynamic and optical stretching, and mechano-node pore sensing. These technologies are poised to contribute to our understanding of disease progression as well as present clinical opportunities.

Identifiers

PMID32566069
PMCPMC7286698

What OpenQuestion holds

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Registered trials

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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.