Evidence map›Paper›PMID 38858612›Full record

ArticleBMC cancer2024

Pathomics and single-cell analysis of papillary thyroid carcinoma reveal the pro-metastatic influence of cancer-associated fibroblasts.

Yixian Wang, Xin Li, Qingwei Gang, Yinde Huang, Mingyu Liu, Han Zhang, Shikai Shen, Yao Qi, Jian Zhang

Abstract read
In one paragraph

Article in BMC cancer, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing 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

20 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Cancers · 2026
    Article
  7. Review
  8. Article
  9. Review
  10. Review
  11. Article
  12. Review
  13. Article
  14. Article
  15. Article
  16. Reprogramming of fatty acid metabolism in thyroid cancer: Potential targets and mechanisms.Chinese journal of cancer research = Chung-kuo yen cheng yen chiu · 2025
    Article
  17. Review
  18. Article
  19. Article
  20. Article
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

9 authors.

Yixian Wang *Department of Vascular and Thyroid Surgery, The First Hospital, China Medical University, Shenyang, Liaoning, 110001, China.
Xin Li *Department of Head and Neck Surgery, Liaoning Cancer Hospital & Institute, Shenyang, Liaoning, 110042, China.
Qingwei Gang *Department of Vascular and Thyroid Surgery, The First Hospital, China Medical University, Shenyang, Liaoning, 110001, China.
Yinde HuangDepartment of Breast and Thyroid Surgery, Chongqing General Hospital, Chongqing, 401147, China.
Mingyu LiuDepartment of Vascular and Thyroid Surgery, The First Hospital, China Medical University, Shenyang, Liaoning, 110001, China.
Han ZhangDepartment of Vascular and Thyroid Surgery, The First Hospital, China Medical University, Shenyang, Liaoning, 110001, China.
Shikai ShenDepartment of Vascular and Thyroid Surgery, The First Hospital, China Medical University, Shenyang, Liaoning, 110001, China.
Yao QiDepartment of Vascular and Thyroid Surgery, The First Hospital, China Medical University, Shenyang, Liaoning, 110001, China.
Jian ZhangDepartment of Vascular and Thyroid Surgery, The First Hospital, China Medical University, Shenyang, Liaoning, 110001, China. jianzhang@cmu.edu.cn.

Funding

National Natural Science Foundation of China 82170507
6 · The paper itself

Abstract

backgroundPapillary thyroid carcinoma (PTC) is globally prevalent and associated with an increased risk of lymph node metastasis (LNM). The role of cancer-associated fibroblasts (CAFs) in PTC remains unclear.

methodsWe collected postoperative pathological hematoxylin-eosin (HE) slides from 984 included patients with PTC to analyze the density of CAF infiltration at the invasive front of the tumor using QuPath software. The relationship between CAF density and LNM was assessed. Single-cell RNA sequencing (scRNA-seq) data from GSE193581 and GSE184362 datasets were integrated to analyze CAF infiltration in PTC. A comprehensive suite of in vitro experiments, encompassing EdU labeling, wound scratch assays, Transwell assays, and flow cytometry, were conducted to elucidate the regulatory role of CD36

resultsA significant correlation was observed between high fibrosis density at the invasive front of the tumor and LNM. Analysis of scRNA-seq data revealed metastasis-associated myoCAFs with robust intercellular interactions. A diagnostic model based on metastasis-associated myoCAF genes was established and refined through deep learning methods. CD36 positive expression in CAFs can significantly promote the proliferation, migration, and invasion abilities of PTC cells, while inhibiting the apoptosis of PTC cells.

conclusionThis study addresses the significant issue of LNM risk in PTC. Analysis of postoperative HE pathological slides from a substantial patient cohort reveals a notable association between high fibrosis density at the invasive front of the tumor and LNM. Integration of scRNA-seq data comprehensively analyzes CAF infiltration in PTC, identifying metastasis-associated myoCAFs with strong intercellular interactions. In vitro experimental results indicate that CD36 positive expression in CAFs plays a promoting role in the progression of PTC. Overall, these findings provide crucial insights into the function of CAF subset in PTC metastasis.

Indexed as

Cancer-Associated FibroblastsSingle-Cell AnalysisThyroid Cancer, PapillaryThyroid NeoplasmsApoptosisCD36 AntigensCell Line, TumorCell MovementCell ProliferationFemaleHumansLymphatic MetastasisMaleMiddle AgedNeoplasm InvasivenessCD36 AntigensCD36 protein, humanCancer-associated fibroblastsDeep learningPapillary thyroid carcinomaPathomicsSingle-cell RNA sequencing

Identifiers

PMID38858612
PMCPMC11163752

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.