Evidence map›Paper›PMID 39334440›Full record

ReviewStem cell research & therapy2024

Dissecting human adipose tissue heterogeneity using single-cell omics technologies.

Giuliana Di Rocco, Angelo Trivisonno, Giovanni Trivisonno, Gabriele Toietta

Abstract readReview
In one paragraph

Review in Stem cell research & therapy, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Review
  5. Article
  6. 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.

Giuliana Di Rocco *Unit of Cellular Networks and Molecular Therapeutic Targets, IRCCS Regina Elena National Cancer Institute, 00144, Rome, Italy.
Angelo Trivisonno *Fondazione Policlinico Universitario Agostino Gemelli IRCCS, 00168, Rome, Italy.
Giovanni TrivisonnoSchool of Medicine, University of Rome Campus Biomedico, 00128, Rome, Italy.
Gabriele ToiettaTumor Immunology and Immunotherapy Unit, IRCCS Regina Elena National Cancer Institute, Via E. Chianesi, 53, 00144, Rome, Italy. gabriele.toietta@ifo.it.ORCID 0000-0003-4182-2468

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Single-cell omics technologies that profile genes (genomic and epigenomic) and determine the abundance of mRNA (transcriptomic), protein (proteomic and secretomic), lipids (lipidomic), and extracellular matrix (matrisomic) support the dissection of adipose tissue heterogeneity at unprecedented resolution in a temporally and spatially defined manner. In particular, cell omics technologies may provide innovative biomarkers for the identification of rare specific progenitor cell subpopulations, assess transcriptional and proteomic changes affecting cell proliferation and immunomodulatory potential, and accurately define the lineage hierarchy and differentiation status of progenitor cells. Unraveling adipose tissue complexity may also provide for the precise assessment of a dysfunctional state, which has been associated with cancer, as cancer-associated adipocytes play an important role in shaping the tumor microenvironment supporting tumor progression and metastasis, obesity, metabolic syndrome, and type 2 diabetes mellitus. The information collected by single-cell omics has relevant implications for regenerative medicine because adipose tissue is an accessible source of multipotent cells; alternative cell-free approaches, including the use of adipose tissue stromal cell-conditioned medium, extracellular vesicles, or decellularized extracellular matrix, are clinically valid options. Subcutaneous white adipose tissue, which is generally harvested via liposuction, is highly heterogeneous because of intrinsic biological variability and extrinsic inconsistencies in the harvesting and processing procedures. The current limited understanding of adipose tissue heterogeneity impinges on the definition of quality standards appropriate for clinical translation, which requires consistency and uniformity of the administered product. We review the methods used for dissecting adipose tissue heterogeneity and provide an overview of advances in omics technology that may contribute to the exploration of heterogeneity and dynamics of adipose tissue at the single-cell level.

Indexed as

Adipose TissueSingle-Cell AnalysisAdipocytesCell DifferentiationGenomicsHumansProteomicsAdipose tissueOmics technologiesRegenerative medicineSingle-cell sequencingTissue heterogeneity

Identifiers

PMID39334440
PMCPMC11437900

What Socratic 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 Socratic graph.