Evidence map›Paper›PMID 39155781›Full record

ArticleJournal of Zhejiang University. Science. B2024

Single-cell transcriptomics reveals tumor landscape in ovarian carcinosarcoma.

Junfen Xu, Mengyan Tu

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Article in Journal of Zhejiang University. Science. B, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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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

1 citing paper in PubMed.

  1. 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

2 authors.

Junfen XuDepartment of Gynecologic Oncology, Women's Hospital, Zhejiang University School of Medicine, Hangzhou 310006, China. xjfzu@zju.edu.cn.
Mengyan TuDepartment of Gynecologic Oncology, Women's Hospital, Zhejiang University School of Medicine, Hangzhou 310006, China.

Funding

the Fundamental Research Funds for the Central Universities of China 2023QZJH54the National Natural Science Foundation of China 82072855
6 · The paper itself

Abstract

objectivesThe present study used single-cell RNA sequencing (scRNA-seq) to characterize the cellular composition of ovarian carcinosarcoma (OCS) and identify its molecular characteristics.

methodsscRNA-seq was performed in resected primary OCS for an in-depth analysis of tumor cells and the tumor microenvironment. Immunohistochemistry staining was used for validation. The scRNA-seq data of OCS were compared with those of high-grade serous ovarian carcinoma (HGSOC) tumors and other OCS tumors.

resultsBoth malignant epithelial and malignant mesenchymal cells were observed in the OCS patient of this study. We identified four epithelial cell subclusters with different biological roles. Among them, epithelial subcluster 4 presented high levels of breast cancer type 1 susceptibility protein homolog (

conclusionsThis study provides the single-cell transcriptomics signature of human OCS, which constitutes a new resource for elucidating OCS diversity.

Indexed as

CarcinosarcomaDNA Topoisomerases, Type IIOvarian NeoplasmsSingle-Cell AnalysisTranscriptomeBRCA1 ProteinCarrier ProteinsCystadenocarcinoma, SerousCytokinesDNA-Binding ProteinsFemaleGene Expression Regulation, NeoplasticHumansMiddle AgedPoly-ADP-Ribose Binding ProteinsSequence Analysis, RNABRCA1 ProteinBRCA1 protein, humanCarrier ProteinsCytokinesDNA-Binding ProteinsDNA Topoisomerases, Type IIpleiotrophinPoly-ADP-Ribose Binding ProteinsTOP2A protein, humanOvarian carcinosarcomaSingle-cell RNA sequencing (scRNA-seq)Tumor heterogeneity

Identifiers

PMID39155781
PMCPMC11337087

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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.