Evidence map›Paper›PMID 40950406›Full record

ArticleFrontiers in cell and developmental biology2025

Comprehensive analysis of the papillary thyroid carcinoma identifies CSGALNACT1 as a proliferation driver and prognostic biomarker.

Yu Zhao, Juan Zhang, Yong Yao, Linna Yu

Abstract read
In one paragraph

Article in Frontiers in cell and developmental biology, 2025. 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
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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

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.

Yu ZhaoPeople's Hospital of Qianxinan Prefecture, Xingyi, Guizhou, China.
Juan ZhangPeople's Hospital of Qianxinan Prefecture, Xingyi, Guizhou, China.
Yong YaoPeople's Hospital of Qianxinan Prefecture, Xingyi, Guizhou, China.
Linna YuPeople's Hospital of Qianxinan Prefecture, Xingyi, Guizhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Papillary thyroid carcinoma (PTC) is the most prevalent form of thyroid cancer, yet its cellular heterogeneity and prognostic determinants remain poorly defined. Here, we integrate two single-cell RNA sequencing datasets comprising 20 human thyroid samples to construct a high-resolution cellular atlas of PTC. We identify 29 distinct cellular subpopulations and delineate their composition, dynamics, and interactions in healthy versus tumor tissues. Notably, epithelial and monocyte populations were markedly expanded in PTC, whereas adaptive immune subsets such as B and T cells were diminished. Cell-cell communication analysis revealed enhanced intercellular signaling in the tumor microenvironment, with epithelial and endothelial cells receiving the strongest inputs. Among monocyte-specific transcriptional signatures, we identified 65 prognostic genes via univariate Cox analysis. A LASSO-derived 14-gene risk score robustly stratified patient outcomes, with CSGALNACT1 emerging as a key epithelial-specific, independent prognostic gene. Pseudotime analysis further supported its role in epithelial cell differentiation. Functional validation demonstrated that CSGALNACT1 promotes proliferation in PTC cell lines, suggesting a potential oncogenic function. Immune deconvolution across risk groups revealed substantial divergence in innate and adaptive immune infiltration, indicating a close interplay between tumor-intrinsic transcriptional programs and immune microenvironment remodeling. Collectively, our study provides a comprehensive single-cell framework for PTC, identifies a clinically relevant risk model, and highlights CSGALNACT1 as a potential therapeutic target.

Indexed as

bulk RNA-seqcell proliferationimmune infiltrationpapillary thyroid carcinomaScRNA-seq

Identifiers

PMID40950406
PMCPMC12426183

What Socratic holds

Textmetadata
LicenceCC BY
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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 Socratic graph.