Evidence map›Paper›PMID 42010061›Full record

ReviewNature cancer2026

Heterogeneity and plasticity of cancer-associated fibroblasts.

Sneha Pramod, Hagar Lavon, Ruth Scherz-Shouval, Mara H Sherman

Abstract readReview
PubMed Publisher
In one paragraph

Review in Nature cancer, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Understanding and targeting the tumour matrisome.Nature reviews. Clinical oncology · 2026
    Review
  3. Review
  4. 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.

Sneha Pramod *Cancer Biology and Genetics Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Hagar Lavon *Department of Biomolecular Sciences, The Weizmann Institute of Science, Rehovot, Israel.ORCID http://orcid.org/0009-0008-5733-9642
Ruth Scherz-ShouvalDepartment of Biomolecular Sciences, The Weizmann Institute of Science, Rehovot, Israel. ruth.shouval@weizmann.ac.il.ORCID http://orcid.org/0000-0002-4570-121X
Mara H ShermanCancer Biology and Genetics Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA. shermam1@mskcc.org.ORCID http://orcid.org/0000-0001-7826-3888

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI SELWYN M VICKERS · 1985 to 2026
$347.4M
Origins and functions of pancreatic cancer-associated fibroblastsR01CA250917 · NCI · SLOAN-KETTERING INST CAN RESEARCH · PI Mara H. Sherman · 2021 to 2026
$2.3M
EC | EU Framework Programme for Research and Innovation H2020 | H2020 Priority Excellent Science | H2020 European Research Council (H2020 Excellent Science - European Research Council) 101043300NCI NIH HHS P30 CA008748NCI NIH HHS R01 CA250917
6 · The paper itself

Abstract

Fibroblasts sense and respond to contextual cues to support tissue structure and function. In cancer, they engage a dysregulated wound-healing response that profoundly shapes tumor composition and progression. Efforts to therapeutically target these cancer-associated fibroblasts (CAFs) have been complicated by their heterogeneity and plasticity. However, recent advances, particularly in single-cell and spatial technologies, have greatly improved the understanding of the phenotypic consequences of distinct CAF states and functions. Here we review the current understanding of CAFs as heterogeneous, instructive regulators of tumor microenvironments across anatomic sites and highlight key challenges for the future.

Indexed as

Cancer-Associated FibroblastsCell PlasticityNeoplasmsAnimalsHumansTumor Microenvironment

Identifiers

What OpenQuestion holds

Textmetadata
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.