Evidence map›Paper›PMID 37938367›Full record

ArticleCancer immunology, immunotherapy : CII2023

Unraveling intratumoral complexity in metastatic dermatofibrosarcoma protuberans through single-cell RNA sequencing analysis.

Ling-Ling Ge, Zhi-Chao Wang, Cheng-Jiang Wei, Jing-Xuan Huang, Jun Liu, Yi-Hui Gu, Wei Wang, Qing-Feng Li

Abstract read
In one paragraph

Article in Cancer immunology, immunotherapy : CII, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
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  5. 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

8 authors.

Ling-Ling Ge *Department of Plastic and Reconstructive Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, 639 Zhizaoju Road, Shanghai, 200011, People's Republic of China.ORCID http://orcid.org/0000-0003-0544-1238
Zhi-Chao Wang *Department of Plastic and Reconstructive Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, 639 Zhizaoju Road, Shanghai, 200011, People's Republic of China.ORCID http://orcid.org/0000-0002-5859-4193
Cheng-Jiang Wei *Department of Plastic and Reconstructive Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, 639 Zhizaoju Road, Shanghai, 200011, People's Republic of China.ORCID http://orcid.org/0000-0002-1431-3986
Jing-Xuan HuangDepartment of Plastic and Reconstructive Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, 639 Zhizaoju Road, Shanghai, 200011, People's Republic of China.ORCID http://orcid.org/0009-0005-4472-8372
Jun LiuDepartment of Plastic and Reconstructive Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, 639 Zhizaoju Road, Shanghai, 200011, People's Republic of China.ORCID http://orcid.org/0009-0007-2299-8800
Yi-Hui GuDepartment of Plastic and Reconstructive Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, 639 Zhizaoju Road, Shanghai, 200011, People's Republic of China.ORCID http://orcid.org/0000-0002-9321-1768
Wei WangDepartment of Plastic and Reconstructive Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, 639 Zhizaoju Road, Shanghai, 200011, People's Republic of China.ORCID http://orcid.org/0000-0002-6180-2301
Qing-Feng LiDepartment of Plastic and Reconstructive Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, 639 Zhizaoju Road, Shanghai, 200011, People's Republic of China. dr.liqingfeng@shsmu.edu.cn.ORCID http://orcid.org/0000-0002-6954-2583

Funding

Clinical Research Plan of SHDC SHDC2020CR1019BInnovative Research Team of High-level Local University in Shanghai SSMU-ZDCX20180700National Natural Science Foundation of China 82102344National Natural Science Foundation of China 82172228Natural Science Foundation of Shanghai Municipality 22ZR1422300Science and Technology Commission of Shanghai Municipality 22MC1940300
6 · The paper itself

Abstract

Dermatofibrosarcoma protuberans (DFSP) stands as a rare and locally aggressive soft tissue tumor, characterized by intricated molecular alterations. The imperative to unravel the complexities of intratumor heterogeneity underscores effective clinical management. Herein, we harnessed single-cell RNA sequencing (scRNA-seq) to conduct a comprehensive analysis encompassing samples from primary sites, satellite foci, and lymph node metastases. Rigorous preprocessing of raw scRNA-seq data ensued, and employing t-distributed stochastic neighbor embedding (tSNE) analysis, we unveiled seven major cell populations and fifteen distinct subpopulations. Malignant cell subpopulations were delineated using infercnv for copy number variation calculations. Functional and metabolic variations of diverse malignant cell populations across samples were deciphered utilizing GSVA and the scMetabolism R packages. Additionally, the exploration of differentiation trajectories within diverse fibroblast subpopulations was orchestrated through pseudotime trajectory analyses employing CytoTRACE and Monocle2, and further bolstered by GO analyses to elucidate the functional disparities across distinct differentiation states. In parallel, we segmented the cellular components of the immune microenvironment and verified the presence of SPP1

Indexed as

DermatofibrosarcomaSkin NeoplasmsDNA Copy Number VariationsHumansLymphatic MetastasisSequence Analysis, RNATumor MicroenvironmentDermatofibrosarcoma protuberansIntratumoral heterogeneityMetastasisSingle-cell RNA sequencing analysis

Identifiers

PMID37938367
PMCPMC10992304

What OpenQuestion holds

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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 OpenQuestion graph.