Evidence map›Paper›PMID 35053177›Full record

ArticleBiomolecules2021

Transcriptomic-Based Quantification of the Epithelial-Hybrid-Mesenchymal Spectrum across Biological Contexts.

Susmita Mandal, Tanishq Tejaswi, Rohini Janivara, Syamanthak Srikrishnan, Pradipti Thakur, Sarthak Sahoo, Priyanka Chakraborty, Sukhwinder Singh Sohal, Herbert Levine, Jason T George and 1 more

Abstract read
In one paragraph

Article in Biomolecules, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
–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

11 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  7. Review
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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

11 authors.

Susmita MandalCentre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore 560012, India.
Tanishq TejaswiCentre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore 560012, India.
Rohini JanivaraDepartment of Biological Sciences, Georgia Institute of Technology, Atlanta, GA 30332, USA.ORCID 0000-0002-0634-2357
Syamanthak SrikrishnanDepartment of Biotechnology, Indian Institute of Technology, Kharagpur 721302, India.
Pradipti ThakurDepartment of Biotechnology, Indian Institute of Technology, Kharagpur 721302, India.ORCID 0000-0001-6597-8227
Sarthak SahooCentre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore 560012, India.
Priyanka ChakrabortyCentre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore 560012, India.
Sukhwinder Singh SohalRespiratory Translational Research Group, Department of Laboratory Medicine, School of Health Sciences, College of Health and Medicine, University of Tasmania, Launceston 7248, Australia.
Herbert LevineDepartments of Physics and Bioengineering, Northeastern University, Boston, MA 02115, USA.
Jason T GeorgeCenter for Theoretical Biological Physics, Rice University, Houston, TX 77030, USA.
Mohit Kumar JollyCentre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore 560012, India.ORCID 0000-0002-6631-2109

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Epithelial-mesenchymal plasticity (EMP) underlies embryonic development, wound healing, and cancer metastasis and fibrosis. Cancer cells exhibiting EMP often have more aggressive behavior, characterized by drug resistance, and tumor-initiating and immuno-evasive traits. Thus, the EMP status of cancer cells can be a critical indicator of patient prognosis. Here, we compare three distinct transcriptomic-based metrics-each derived using a different gene list and algorithm-that quantify the EMP spectrum. Our results for over 80 cancer-related RNA-seq datasets reveal a high degree of concordance among these metrics in quantifying the extent of EMP. Moreover, each metric, despite being trained on cancer expression profiles, recapitulates the expected changes in EMP scores for non-cancer contexts such as lung fibrosis and cellular reprogramming into induced pluripotent stem cells. Thus, we offer a scoring platform to quantify the extent of EMP in vitro and in vivo for diverse biological applications including cancer.

Indexed as

Induced Pluripotent Stem CellsTranscriptomeCell Line, TumorCellular ReprogrammingEpithelial-Mesenchymal TransitionHumanscellular reprogrammingEMT scoringhybrid epithelial/mesenchymalsingle-cell RNA-seq

Identifiers

PMID35053177
PMCPMC8773604

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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.