Evidence map›Paper›PMID 29795571›Full record

ArticlePLoS computational biology2018

The complex ecosystem in non small cell lung cancer invasion.

Seth Haney, Jessica Konen, Adam I Marcus, Maxim Bazhenov

Abstract read
In one paragraph

Article in PLoS computational biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Review
  2. Article
  3. Cancer metabolism and carcinogenesis.Experimental hematology & oncology · 2024
    Review
  4. Article
  5. Article
  6. Cell interactions in collective cell migration.Development (Cambridge, England) · 2019
    Review
  7. Therapeutic Targeting of Collective Invasion in Ovarian Cancer.International journal of molecular sciences · 2019
    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

4 authors.

Seth HaneyDepartment of Medicine, University of California, San Diego, La Jolla, California, United States of America.ORCID 0000-0002-4763-3548
Jessica KonenDepartment of Thoracic/Head and Neck Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America.
Adam I MarcusWinship Cancer Institute, Emory University, Atlanta, Georgia, United States of America.
Maxim BazhenovDepartment of Medicine, University of California, San Diego, La Jolla, California, United States of America.ORCID 0000-0002-1936-0570

Funding

Tumor Evolution and Metastasis ProgramP30CA016672 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Scott Kopetz · 1985 to 2026
$290.8M
Systems analysis of phenotypic switch in control of cancer invasionU54CA209992 · NCI · YALE UNIVERSITY · PI LEVCHENKO, ANDRE · 2016 to 2021
$10.1M
Developing a pharmacologic approach to treat LKB1 mutant NSCLC patientsR01CA194027 · NCI · EMORY UNIVERSITY · PI GILBERT-ROSS, MELISSA, MARCUS, ADAM I. · 2016 to 2020
$2.5M
Training in the Next Generation in Respiratory ScienceT32HL134632 · NHLBI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI MALHOTRA, ATUL, POWELL, FRANK L. · 2017 to 2021
$2.1M
CRCNS: Multiple roles of inhibition in the olfactory systemR01DC012943 · NIDCD · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI BAZHENOV, MAKSIM V · 2012 to 2016
$1.3M
Genomic and molecular dissection of the collective invasion packR21CA201744 · NCI · EMORY UNIVERSITY · PI MARCUS, ADAM I. · 2016 to 2017
$373k
NCI NIH HHS R01 CA194027NCI NIH HHS R21 CA201744NCI NIH HHS U54 CA209992NHLBI NIH HHS T32 HL134632NIDCD NIH HHS R01 DC012943
6 · The paper itself

Abstract

Many tumors are characterized by genetic instability, producing an assortment of genetic variants of tumor cells called subclones. These tumors and their surrounding environments form complex multi-cellular ecosystems, where subclones compete for resources and cooperate to perform multiple tasks, including cancer invasion. Our recent empirical studies revealed existence of such distinct phenotypes of cancer cells, leaders and followers, in lung cancer. These two cellular subclones exchange a complex array of extracellular signals demonstrating a symbiotic relationship at the cellular level. Here, we develop a computational model of the microenvironment of the lung cancer ecosystem to explore how the interactions between subclones can advance or inhibit invasion. We found that, due to the complexity of the ecosystem, invasion may have very different dynamics characterized by the different levels of aggressiveness. By altering the signaling environment, we could alter the ecological relationship between the cell types and the overall ecosystem development. Competition between leader and follower cell populations (defined by the limited amount of resources), positive feedback within the leader cell population (controlled by the focal adhesion kinase and fibronectin signaling), and impact of the follower cells to the leaders (represented by yet undetermined proliferation signal) all had major effects on the outcome of the collective dynamics. Specifically, our analysis revealed a class of tumors (defined by the strengths of fibronectin signaling and competition) that are particularly sensitive to manipulations of the signaling environment. These tumors can undergo irreversible changes to the tumor ecosystem that outlast the manipulations of feedbacks and have a profound impact on invasive potential. Our study predicts a complex division of labor between cancer cell subclones and suggests new treatment strategies targeting signaling within the tumor ecosystem.

Indexed as

Carcinoma, Non-Small-Cell LungLung NeoplasmsModels, BiologicalTumor MicroenvironmentCell Line, TumorComputational BiologyEcosystemHumansMicroscopy, FluorescenceSignal Transduction

Identifiers

PMID29795571
PMCPMC5991406

What OpenQuestion holds

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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.