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Individualized Breast Cancer Characterization through Single-Cell Analysis of Tumor and Adjacent Normal Cells.
- Source :
-
Cancer research [Cancer Res] 2017 May 15; Vol. 77 (10), pp. 2759-2769. Date of Electronic Publication: 2017 Mar 01. - Publication Year :
- 2017
-
Abstract
- There is a need to individualize assays for tumor molecular phenotyping, given variations in the differentiation status of tumor and normal tissues in different patients. To address this, we performed single-cell genomics of breast tumors and adjacent normal cells propagated for a short duration under growth conditions that enable epithelial reprogramming. Cells analyzed were either unselected for a specific subpopulation or phenotypically defined as undifferentiated and highly clonogenic ALDH <superscript>+</superscript> /CD49f <superscript>+</superscript> /EpCAM <superscript>+</superscript> luminal progenitors, which express both basal cell and luminal cell-enriched genes. We analyzed 420 tumor cells and 284 adjacent normal cells for expression of 93 genes that included a PAM50-intrinsic subtype classifier and stemness-related genes. ALDH <superscript>+</superscript> /CD49f <superscript>+</superscript> /EpCAM <superscript>+</superscript> tumor and normal cells clustered differently compared with unselected tumor and normal cells. PAM50 gene-set analyses of ALDH <superscript>+</superscript> /CD49f <superscript>+</superscript> /EpCAM <superscript>+</superscript> populations efficiently identified major and minor clones of tumor cells, with the major clone resembling clinical parameters of the tumor. Similarly, a stemness-associated gene set identified clones with divergent stemness pathway activation within the same tumor. This refined expression profiling technique distinguished genes truly deregulated in cancer from genes that identify cellular precursors of tumors. Collectively, the assays presented here enable more precise identification of cancer-deregulated genes, allow for early identification of therapeutically targetable tumor cell subpopulations, and ultimately provide a refinement of precision therapeutics for cancer treatment. Cancer Res; 77(10); 2759-69. ©2017 AACR .<br /> (©2017 American Association for Cancer Research.)
- Subjects :
- Biomarkers, Tumor
Breast Neoplasms diagnosis
Breast Neoplasms metabolism
Cell Line, Tumor
Cluster Analysis
Epithelial Cells metabolism
Female
Flow Cytometry
Gene Expression Profiling
Gene Expression Regulation, Neoplastic
Gene Regulatory Networks
Humans
Phenotype
Real-Time Polymerase Chain Reaction
Breast Neoplasms genetics
Genomics methods
Precision Medicine methods
Single-Cell Analysis methods
Subjects
Details
- Language :
- English
- ISSN :
- 1538-7445
- Volume :
- 77
- Issue :
- 10
- Database :
- MEDLINE
- Journal :
- Cancer research
- Publication Type :
- Academic Journal
- Accession number :
- 28249895
- Full Text :
- https://doi.org/10.1158/0008-5472.CAN-16-3308