Evidence map›Paper›PMID 34693081›Full record

ArticleCurrent opinion in systems biology2021

Cell-Cell Communication Networks in Tissue: Toward Quantitatively Linking Structure with Function.

Gaurav Luthria, Douglas Lauffenburger, Miles A Miller

Abstract read
In one paragraph

Article in Current opinion in systems biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Review
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.

Gaurav LuthriaCenter for Systems Biology, Massachusetts General Hospital Research Institute, Boston, MA, 02114, USA.
Douglas LauffenburgerDepartment of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02181, USA.
Miles A MillerCenter for Systems Biology, Massachusetts General Hospital Research Institute, Boston, MA, 02114, USA.

Funding

Training Program in Bioinformatics and Integrative GenomicsT32HG002295 · NHGRI · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI Peter J Park · 2001 to 2026
$15.8M
Quantitative and functional characterization of therapeutic resistance in cancerU54CA217377 · NCI · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI LAUFFENBURGER, DOUGLAS A, MANALIS, SCOTT R · 2017 to 2021
$10.2M
Systems approaches to understanding the relationships between genotype, signaling, and therapeutic efficacyU01CA215798 · NCI · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI HAAS, WILHELM, HAIGIS, KEVIN · 2017 to 2021
$3.7M
Dissection of in situ myeloid signaling using image-guided synthetic controlDP2CA259675 · NCI · MASSACHUSETTS GENERAL HOSPITAL · PI MILLER, MILES A · 2020 to 2023
$2.7M
Single Cell In Vivo Imaging Technology to Analyze Taxane Nano Formulations in Breast CancerR00CA207744 · NCI · MASSACHUSETTS GENERAL HOSPITAL · PI MILLER, MILES A · 2018 to 2020
$747k
NCI NIH HHS DP2 CA259675NCI NIH HHS R00 CA207744NCI NIH HHS U01 CA215798NCI NIH HHS U54 CA217377NHGRI NIH HHS T32 HG002295
6 · The paper itself

Abstract

Forefront techniques for molecular interrogation of mammalian tissues, such as multiplexed tissue imaging, intravital microscopy, and single-cell RNA sequencing (scRNAseq), can combine to quantify cell-type abundance, co-localization, and global levels of receptors and their ligands. Nonetheless, it remains challenging to translate these various quantities into a more comprehensive understanding of how cell-cell communication networks dynamically operate. Therefore, construction of computational models for network-level functions - including niche-dependent actions, homeostasis, and multi-scale coordination - will be valuable for productively integrating the battery of experimental approaches. Here, we review recent progress in understanding cell-cell communication networks in tissue. Featured examples include ligand-receptor dissection of immunosuppressive and mitogenic signaling in the tumor microenvironment. As a future direction, we highlight an unmet potential to bridge high-level statistical approaches with low-level physicochemical mechanisms.

Identifiers

PMID34693081
PMCPMC8530179

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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.