Evidence map›Paper›PMID 34845273›Full record

ArticleScientific reports2021

Single cell imaging-based chromatin biomarkers for tumor progression.

Saradha Venkatachalapathy, Doorgesh S Jokhun, Madhavi Andhari, G V Shivashankar

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2021. 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
1.1field-weighted citation impact, top 26% of its field
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, 19 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Review
  14. 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 at 2 institutions in 3 countries.

Saradha VenkatachalapathyMechanobiology Institute and Department of Biological Sciences, National University of Singapore, Singapore, 117411, Singapore.
Doorgesh S JokhunMechanobiology Institute and Department of Biological Sciences, National University of Singapore, Singapore, 117411, Singapore.
Madhavi AndhariMechanobiology Institute and Department of Biological Sciences, National University of Singapore, Singapore, 117411, Singapore.
G V ShivashankarMechanobiology Institute and Department of Biological Sciences, National University of Singapore, Singapore, 117411, Singapore. shiva.gvs@gmail.com.
National University of Singapore · SGIndian Institute of Science Education and Research Kolkata · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Tumour progression within the tissue microenvironment is accompanied by complex biomechanical alterations of the extracellular environment. While histopathology images provide robust biochemical markers for tumor progression in clinical settings, a quantitative single cell score using nuclear morphology and chromatin organization integrated with the long range mechanical coupling within the tumor microenvironment is missing. We propose that the spatial chromatin organization in individual nuclei characterises the cell state and their alterations during tumor progression. In this paper, we first built an image analysis pipeline and implemented it to classify nuclei from patient derived breast tissue biopsies of various cancer stages based on their nuclear and chromatin features. Replacing H&E with DNA binding dyes such as Hoescht stained tissue biopsies, we improved the classification accuracy. Using the nuclear morphology and chromatin organization features, we constructed a pseudo-time model to identify the chromatin state changes that occur during tumour progression. This enabled us to build a single-cell mechano-genomic score that characterises the cell state during tumor progression from a normal to a metastatic state. To gain further insights into the alterations in the local tissue microenvironments, we also used the nuclear orientations to identify spatial neighbourhoods that have been posited to drive tumor progression. Collectively, we demonstrate that image-based single cell chromatin and nuclear features are important single cell biomarkers for phenotypic mapping of tumor progression.

Indexed as

BiomarkersBiomarkers, TumorBiophysicsBiopsyBreast NeoplasmsCell NucleusChromatinCollagenComputational BiologyDisease ProgressionDNAFibroblastsGenomicsHumansImage Processing, Computer-AssistedIn Vitro TechniquesBiomarkersBiomarkers, TumorChromatinCollagenDNA

Identifiers

PMID34845273
PMCPMC8630115
OpenAlexW3215914090

What OpenQuestion holds

Textmetadata
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.