Evidence map›Paper›PMID 26883775›Full record

ArticleActa biomaterialia2016

Extracellular matrix microarrays to study inductive signaling for endoderm specification.

D F Braga Malta, N E Reticker-Flynn, C L da Silva, J M S Cabral, H E Fleming, K S Zaret, S N Bhatia, G H Underhill

Abstract read
In one paragraph

Article in Acta biomaterialia, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Review
  6. Observational
  7. Article
  8. Microrheology for biomaterial design.APL bioengineering · 2020
    Review
  9. Review
  10. Article
  11. Article
  12. Article
  13. Article
  14. Organoids: fundamentals, present and future.Revista peruana de medicina experimental y salud publica
    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

8 authors.

D F Braga MaltaMassachusetts Institute of Technology, Cambridge, MA, United States; Department of Bioengineering and IBB-Institute for Bioengineering and Biosciences, Instituto Superior Técnico, Universidade de Lisboa, Portugal.
N E Reticker-FlynnMassachusetts Institute of Technology, Cambridge, MA, United States.
C L da SilvaDepartment of Bioengineering and IBB-Institute for Bioengineering and Biosciences, Instituto Superior Técnico, Universidade de Lisboa, Portugal.
J M S CabralDepartment of Bioengineering and IBB-Institute for Bioengineering and Biosciences, Instituto Superior Técnico, Universidade de Lisboa, Portugal.
H E FlemingMassachusetts Institute of Technology, Cambridge, MA, United States.
K S ZaretUniversity of Pennsylvania, Philadelphia, PA, United States.
S N BhatiaMassachusetts Institute of Technology, Cambridge, MA, United States; The Howard Hughes Medical Institute, Cambridge, MA, United States; Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 021392, United States; Institute for Medical Engineering & Science, Massachusetts Institute of Technology, Cambridge, MA 02139, United States.
G H UnderhillUniversity of Illinois at Urbana-Champaign, Urbana, IL, United States. Electronic address: gunderhi@illinois.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 CA014051NCI NIH HHS P30-CA14051
6 · The paper itself

Abstract

During tissue development, stem and progenitor cells are faced with fate decisions coordinated by microenvironmental cues. Although insights have been gained from in vitro and in vivo studies, the role of the microenvironment remains poorly understood due to the inability to systematically explore combinations of stimuli at a large scale. To overcome such restrictions, we implemented an extracellular matrix (ECM) array platform that facilitates the study of 741 distinct combinations of 38 different ECM components in a systematic, unbiased and high-throughput manner. Using embryonic stem cells as a model system, we derived definitive endoderm progenitors and applied them to the array platform to study the influence of ECM, including the interactions of ECM with growth factor signaling, on the specification of definitive endoderm cells towards the liver and pancreas fates. We identified ECM combinations that influence endoderm fate decisions towards these lineages, and demonstrated the utility of this platform for studying ECM-mediated modifications to signal activation during liver specification. In particular, defined combinations of fibronectin and laminin isoforms, as well as combinations of distinct collagen subtypes, were shown to influence SMAD pathway activation and the degree of hepatic differentiation. Overall, our systematic high-throughput approach suggests that ECM components of the microenvironment have modulatory effects on endoderm differentiation, including effects on lineage fate choice and cell adhesion and survival during the differentiation process. This platform represents a robust tool for analyzing effects of ECM composition towards the continued improvement of stem cell differentiation protocols and further elucidation of tissue development processes. STATEMENT OF SIGNIFICANCE: Cellular microarrays can provide the capability to perform high-throughput investigations into the role of microenvironmental signals in a variety of cell functions. This study demonstrates the utility of a high-throughput cellular microarray approach for analyzing the effects of extracellular matrix (ECM) in liver and pancreas differentiation of endoderm progenitor cells. Despite an appreciation that ECM is likely involved in these processes, the influence of ECM, particularly combinations of matrix proteins, had not been systematically explored. In addition to the identification of relevant ECM compositions, this study illustrates the capability of the cellular microarray platform to be integrated with a diverse range of cell fate measurements, which could be broadly applied towards the investigation of cell fate regulation in other tissue development and disease contexts.

Indexed as

Body PatterningSignal TransductionAnimalsBiomarkersCell AdhesionCell CountCell DifferentiationCell LineageEndodermExtracellular MatrixLamininLiverMiceMicroarray AnalysisPancreasPhosphorylationBiomarkersLamininSmad ProteinsExtracellular matrixHigh-throughputLiverMicroarrayPancreas

Identifiers

PMID26883775
PMCPMC5588684

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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.