Identification of two cancer stem cell-like populations in triple-negative breast cancer xenografts.
Jun NakayamaHiroko MatsunagaKoji ArikawaTakuya YodaMasahito HosokawaHaruko TakeyamaYusuke YamamotoKentaro SembaPublished in: Disease models & mechanisms (2022)
Gene expression analysis at the single-cell level by next-generation sequencing has revealed the existence of clonal dissemination and microheterogeneity in cancer metastasis. The current spatial analysis technologies can elucidate the heterogeneity of cell-cell interactions in situ. To reveal the regional and expressional heterogeneity in primary tumors and metastases, we performed transcriptomic analysis of microtissues dissected from a triple-negative breast cancer (TNBC) cell line MDA-MB-231 xenograft model with our automated tissue microdissection punching technology. This multiple-microtissue transcriptome analysis revealed three cancer cell-type clusters in the primary tumor and axillary lymph node metastasis, two of which were cancer stem cell (CSC)-like clusters (CD44/MYC-high, HMGA1-high). Reanalysis of public single-cell RNA-sequencing datasets confirmed that the two CSC-like populations existed in TNBC xenograft models and in TNBC patients. The diversity of these multiple CSC-like populations could cause differential anticancer drug resistance, increasing the difficulty of curing this cancer.
Keyphrases
- single cell
- rna seq
- papillary thyroid
- lymph node metastasis
- high throughput
- cancer stem cells
- gene expression
- squamous cell
- healthcare
- end stage renal disease
- squamous cell carcinoma
- newly diagnosed
- machine learning
- ejection fraction
- emergency department
- peritoneal dialysis
- prognostic factors
- childhood cancer
- transcription factor
- neoadjuvant chemotherapy
- deep learning
- genome wide
- radiation therapy
- cell death