Evidence map›Paper›PMID 38798565›Full record

ArticlebioRxiv : the preprint server for biology2024

Determination of permissive and restraining cancer-associated fibroblast (DeCAF) subtypes.

Xianlu Laura Peng, Elena V Kharitonova, Yi Xu, Joseph F Kearney, Changfei Luan, Priscilla S Chan, Arthi Hariharan, Ian C McCabe, John R Leary, Ashley B Morrison and 13 more

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

23 authors.

Xianlu Laura PengORCID 0000-0002-8684-5762
Elena V Kharitonova
Yi Xu
Joseph F Kearney
Changfei Luan
Priscilla S Chan
Arthi Hariharan
Ian C McCabe
John R Leary
Ashley B Morrison
Hannah E Trembath
Michelle E LaBella
Silvia G Herera Loeza
Ashley Cliff
Hong Jin Kim
Brian A Belt
Roheena Z Panni
David C Linehan
Jeffrey S Damrauer
Alina C Iuga
William Y Kim
Naim U Rashid
Jen Jen Yeh

Funding

Integrating tumor and stroma to understand and predict treatment responseU01CA274298 · NCI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI Naim Ur Rashid, Susan Tsai · 2022 to 2026
$4.7M
UNC Integrated Translational Oncology Program (UNC-iTOP)T32CA244125 · NCI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI WILLIAM Y. KIM, Jen Jen Yeh · 2019 to 2026
$3.9M
NCI NIH HHS T32 CA244125
6 · The paper itself

Abstract

Cancer-associated fibroblast (CAF) subpopulations in pancreatic ductal adenocarcinoma (PDAC) have been identified using single-cell RNA sequencing (scRNAseq) with divergent characteristics, but their clinical relevance remains unclear. We translate scRNAseq-derived CAF cell-subpopulation-specific marker genes to bulk RNAseq data, and develop a single- sample classifier, DeCAF, for the classification of clinically rest raining and perm issive CAF subtypes. We validate DeCAF in 19 independent bulk transcriptomic datasets across four tumor types (PDAC, mesothelioma, bladder and renal cell carcinoma). DeCAF subtypes have distinct histology features, immune landscapes, and are prognostic and predict response to therapy across cancer types. We demonstrate that DeCAF is clinically replicable and robust for the classification of CAF subtypes in patients for multiple tumor types, providing a better framework for the future development and translation of therapies against permissive CAF subtypes and preservation of restraining CAF subtypes. Significance: We introduce a replicable and robust classifier, DeCAF, that delineates the significance of the role of permissive and restraining CAF subtypes in cancer patients. DeCAF is clinically tractable, prognostic and predictive of treatment response in multiple cancer types and lays the translational groundwork for the preclinical and clinical development of CAF subtype specific therapies.

Identifiers

PMID38798565
PMCPMC11118336

What Socratic holds

Textmetadata
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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.