Hiring in life sciences? Share your open positions with our professional community. Read more Close

Advertisement

Single-cell transcriptomics and whole-genome sequencing reveal the tumor landscape in breast carcinosarcoma.

Created on 19 Jul 2026

Authors

Meiling Wang, Luhan Xie, Guangze Sun, Yue Huang, Jiping Xie, Weipeng Lv, Shilin Zhao, Yi Wan, Min Zhang, Zhantian Zhang, Shiyu Yang, Xiaomin Fu, Jingfan Xia, Zuowei Zhao, Yongqiang Yao, Ruoyu Wang

Published in

Scientific reports. Jul 19, 2026. Epub Jul 19, 2026.

Abstract

Breast carcinosarcoma is a rare and highly aggressive subtype of metaplastic breast carcinoma. It is typically negative for estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2 (HER2), and displays greater invasiveness and metastatic potential than triple-negative breast cancer (TNBC). This exploratory single-case study analyzed one individual breast carcinosarcoma sample via single-cell RNA sequencing, which revealed that the tumor was predominantly composed of epithelial cells and fibroblasts, with four distinct subpopulations identified for each cell type. In this case, critical crosstalk between malignant epithelial cells and mesenchymal cells may be mediated by the LAMININ, MK, and APP signaling pathways. Comparative analysis of single-cell sequencing data from this sample with publicly available TNBC single-cell datasets revealed notable differences in cellular composition between this breast carcinosarcoma case and TNBC samples. Whole-genome sequencing of the sample identified complex genomic alterations, including potential germline susceptibility-related candidate genes and candidate driver mutations associated with the tumor in this case. This study presents single-cell transcriptomic and whole-genomic profiling data for a single case of breast carcinosarcoma, deepens understanding of the biological characteristics of this tumor in the studied case, and provides a novel exploratory resource for investigating the heterogeneity of breast carcinosarcoma.

PMID:
42471398
Bibliographic data and abstract were imported from PubMed on 19 Jul 2026.

Read full publication at:
Please sign in to see all details.

Advertisement

Stats

  • Community rating n/a 0 votes
  • Reviewers' rating n/a 0 votes
  • Your rating

1-terrible, 9-excellent. How would you rate this publication? Sign in in to submit your rating.

  • Recommendations n/a n/a positive of 0 vote(s)
  • Views 5
  • Comments 0

Recommended by

  • No recommendations yet.

Post a comment

You need to be signed in to post comments. You can sign in here.

Comments

There are no comments yet.

Advertisement