Quantitative assessment of copy number changes in tumor cells by single cell aCGH.

<p>A) Vertical aCGH profiles of chromosome 17 of four breast cancer cell lines with increasing copy number of ERBB2 locus (MDA-MB-453, MDA-MB-361, SKBR3 and BT474) generated using unamplified DNA (upper row) or single-cell WGA products (lower row). Red brackets indicate the position of the ERBB2 locus. Corresponding FISH ratios (ERBB2 vs. CEP17) of all cell lines are indicated in blue brackets. B) Correlation of average log2 values of ERBB2 specific probes obtained in single-cell aCGH experiments (Y-axis) vs. corresponding values obtained with unamplified DNA (X-axis). DNA samples from four breast cancer cell lines (MDA-MB-453, MDA-MB-361, SKBR3, BT474) have been included in the analysis. Pearson’s correlation coefficient 0.94. C) Correlation of average log2 values specific for ERBB2 locus obtained in single-cell aCGH experiments (Y-axis) vs. FISH ratios (ERBB2/CEP17) calculated for four breast cancer cell lines: MDA-MB-453, MDA-MB-361, SKBR3, BT474. Pearson’s correlation coefficient 0.97.</p

Molecular findings in individual DCCs over the course of systemic treatment.

<p>A) Chemotherapy regime: first patient was subjected to three cycles of 75 mg/m² Taxotere® (T) and 50 mg/m² Doxorubicin (D) in three week intervals. Subsequently followed two cycles of high dose chemotherapy treatment with an intermediate interval of 4-6 weeks. In the first cycle 500 mg/m² of Vepesid (V), 4000 mg/m² of Isofamid (I) and 500 mg/m² of Carboplatin (C) was administered. The last cycle consisted of 1500 mg/m2 of Cyclophosphamid (Cy) and 200 mg/m2 of Thiotepa (T). Both cycles of high dose chemotherapeutic treatment were accompanied by addition of granulocyte colony-stimulating factor (G-CSF), and autologous transplant of peripheral blood stem cells (PBSCs). B) The course and outcome of bone marrow sampling. DCC count indicated the number of identified DCCs in 1.0×10⁶ mononuclear cells. C) Venn diagram depicting distribution of MRAs (gains and losses) across three types of clinical samples. D) Hierarchical clustering (distance: Euclidian; linkage: average) of samples including DCCs, the primary tumor and a metastatic lesion. E) Table depicting core MRAs that were found in all DCCs, the primary tumor and the metastatic lesion or in the metastatic compartments (DCCs and the lymph metastasis) only.</p

PCR-based PCR-T2 labeling technique vs. RP labeling.

<p>A) Chromosome specific aCGH profiles of chromosome 8. B) Chromosome specific aCGH profiles of 17. Each panel represents aCGH profiles generated with unamplified and single-cell gDNA (PCR-T2 labeling) – left and middle plot, respectively. The right plot of each panel represents magnified graphical overview of genes within loci recognized as aberrant. C) ROC-curves (corresponding to profiles presented in panel A) depicting the accuracy of single cell aCGH assay for PCR-T2 or RP labeling. The array CGH profile generated using unamplified gDNA of OE-19 cells was taken as reference for the comparison. ROC analysis was performed on a genome-wide basis. D) Genome wide aCGH profiles of OE-19 cells generated using unamplified gDNA (upper panel) and a single-cell WGA product labeled with PCR-T2 (middle panel) or RP labeling approach.</p

Experimental approach.

<p>Overview of the single cell aCGH procedure: single cells were isolated by micromanipulation and subjected to <i>Ampli1™</i> WGA protocol. Primary WGA product can be re-amplified for further downstream applications (optional step). DNA was labeled by RP labeling or PCR-based approaches (PCR-T1 and PCR-T2). Subsequent hybridization was carried out on Agilent SurePrint G3 Human 4×180k arrays resulting data was evaluated with Agilent Genomic Workbench Software.</p

PCR results of corresponding transcripts in Sca-1+/CD31- and cells CD34+/CD45- cells.

<p>PCR results of corresponding transcripts in Sca-1+/CD31- and cells CD34+/CD45- cells.</p

Gene expression microarray analysis of isolated single cells.

<p><b>Panel A:</b> The comparison of microarray expression profiles of <i>Sca-1⁺/CD34⁺</i> cells and pulmonary reference (Sca-1^−/CD34^−/CD31^−/CD45⁻) cells showed 107 differentially expressed genes. <b>Panel B:</b> Pools of analyzed cells from <i>Sca-1⁺/CD34⁺</i> subpopulation (red), <i>Sca-1⁺/CD34</i>⁻ subpopulation (blue) and pulmonary reference cells (green) were analyzed by quantitative PCR against differentially expressed genes <i>Dcn</i>, <i>Esd</i> and <i>Gsn</i>. The selected genes not only show significant differences regarding to their expression, but also represent different subpopulations of proteins. Error bars indicate standard deviation of the mean calculated for analyzed triplicates. Expression values are calculated by relative quantification against housekeeping gene <i>Actb</i> and illustrated in comparison to pulmonary reference cells (expression value = 1.0) on a logarithmic scale. All comparisons between different groups, as determined by quantitative PCR, showed significantly different expression levels (student’s t-test, * indicating p<0.05).</p

Distribution of PCR-based <i>Sca-1/CD34</i> expression in isolated putative BASCs.

<p>Distribution of PCR-based <i>Sca-1/CD34</i> expression in isolated putative BASCs.</p

Expression of epithelial and mesenchymal markers in <i>Sca-1⁺/CD34^+,⁻</i> cells.

<p><b>Panel A:</b> The expression of epithelial and mesenchymal transcripts was tested by analytical PCR and is illustrated in a hierarchical cluster heatmap. The analysis shows that the majority of <i>Sca-1⁺/CD34⁺</i> cells (light grey) show similar marker expression as <i>Sca-1^−/CD34⁺</i> cells (white), while all <i>Sca-1⁺/CD34</i>⁻ cells (dark grey) are located in the second branch. Red squares indicate specific bands in analytical PCR, black squares indicate negative PCR results. <b>Panel B:</b> FACS analysis reveals EpCAM⁺/Pdgfrα⁺ subpopulation within Sca-1⁺/CD34^−/CD31^−/CD45⁻ cells. For each of 5 mice, 5×10⁶ murine lung cells were isolated from lung explants and stained with antibodies directed against Sca-1, CD34, CD31, CD45, Pdgfrα and Epcam. While Sca-1⁺/CD34⁻ cells consistently showed Epcam expression, Pdgfrα expression was predominantly found in Sca-1⁺/CD34⁺ cells. However, Sca-1⁺/CD34^−/Epcam⁺ cells could be divided in two major subpopulations defined by Pdgfrα expression. Relative quantification is given for corresponding selected subpopulation as indicated by arrows. <b>Panel C:</b> Scatter plots of the detected cell populations for mouse 5, only.</p

Non-erythrocytic cells, Sca-1⁺ and CD34⁺ cells per lung preparation.

<p>Non-erythrocytic cells, Sca-1⁺ and CD34⁺ cells per lung preparation.</p

Flowchart of the experimental setup.

<p>Simplified schematic overview on the workflow of single cell isolation and immunofluorescent staining strategy: Cells are divided into two groups after separation and stained with antibodies directed against CD31 and Sca-1 or CD34 and CD45, respectively. In order to gain appropriate reference cells for comparative gene expression analysis, additional lung cells are stained with antibodies directed against CD31 and CD45, and only CD31^−/CD45⁻ cells are isolated. Propidium iodide (PI) and GFP-Annexine (GFP-A) are applied to exclude apoptotic cells. Genes recently introduced in literature in order to differentiate between epithelial and mesenchymal cells are tested by specific PCR. PCR results enable further subdivision of analyzed cells (Sca-1⁺/CD34⁺ cells, Sca-1⁺/CD34⁻ cells, Sca-1^−/CD34⁺ cells). In a final step, selected Sca-1⁺/CD34⁺ cells, Sca-1⁺/CD34⁻ cells and Sca-1^−/CD34⁻ reference cells are subjected to comparative gene expression analysis. Results are validated by qPCR of pooled samples.</p