Molecular profiling of single circulating tumor cells with diagnostic intention

Several hundred clinical trials currently explore the role of circulating tumor cell (CTC) analysis for therapy decisions, but assays are lacking for comprehensive molecular characterization of CTCs with diagnostic precision. We therefore combined a workflow for enrichment and isolation of pure CTCs with a non-random whole genome amplification method for single cells and applied it to 510 single CTCs and 189 leukocytes of 66 CTC-positive breast cancer patients. We defined a genome integrity index (GII) to identify single cells suited for molecular characterization by different molecular assays, such as diagnostic profiling of point mutations, gene amplifications and whole genomes of single cells. The reliability of >90% for successful molecular analysis of high-quality clinical samples selected by the GII enabled assessing the molecular heterogeneity of single CTCs of metastatic breast cancer patients. We readily identified genomic disparity of potentially high relevance between primary tumors and CTCs. Microheterogeneity analysis among individual CTCs uncovered pre-existing cells resistant to ERBB2-targeted therapies suggesting ongoing microevolution at late-stage disease whose exploration may provide essential information for personalized treatment decisions and shed light into mechanisms of acquired drug resistance

Molecular profiling of single circulating tumor cells with diagnostic intention

Several hundred clinical trials currently explore the role of circulating tumor cell (CTC) analysis for therapy decisions, but assays are lacking for comprehensive molecular characterization of CTCs with diagnostic precision. We therefore combined a workflow for enrichment and isolation of pure CTCs with a non-random whole genome amplification method for single cells and applied it to 510 single CTCs and 189 leukocytes of 66 CTC-positive breast cancer patients. We defined a genome integrity index (GII) to identify single cells suited for molecular characterization by different molecular assays, such as diagnostic profiling of point mutations, gene amplifications and whole genomes of single cells. The reliability of >90% for successful molecular analysis of high-quality clinical samples selected by the GII enabled assessing the molecular heterogeneity of single CTCs of metastatic breast cancer patients. We readily identified genomic disparity of potentially high relevance between primary tumors and CTCs. Microheterogeneity analysis among individual CTCs uncovered pre-existing cells resistant to ERBB2-targeted therapies suggesting ongoing microevolution at late-stage disease whose exploration may provide essential information for personalized treatment decisions and shed light into mechanisms of acquired drug resistance

A novel workflow for isolation and multi-omic profiling of DCCs derived from cerebrospinal fluid of patients with pediatric brain cancer

Background: Clinical management of cancers of the central nevus system (CNS) is very challenging as they often exhibit low responsiveness to radiation and chemotherapy resulting in overall poor survival. Moreover, analysis of mechanisms driving cancer progression and selection of targeted therapies in CNS tumors is hindered by the limited availability to tumor tissues accessible only though surgical biopsies. A potential source of cancer material in patients with CNS is cerebrospinal fluid (CSF). Analysis of CSF-derived disseminated cancer cells (csfDCCs) holds a promise for improvement of diagnostics and monitoring of CNS tumors. For this reason, we developed a novel workflow allowing detection, isolation and multi-omic analysis of csfDCCs. Methods: In a proof of concept study a new workflow was used to analyze CSF samples from two patients with medulloblastoma and pineoblastoma. CSF-derived cells were stained for CD45 to allow identification of infiltrating immune cells. Putative csfDCCs (CD45-negative) and control cells (CD45-positive) were subjected to a multi-omic workflow allowing parallel sequencing of genomes and transcriptomes of the same cells. Single-cell mRNA was physically separated from DNA, amplified by means of whole transcriptome amplification (Ampli1 WTA) and analyzed using endpoint PCR and a proprietary single-cell RNA-Seq approach. In parallel, DNA was subjected to whole genome amplification (Ampli1 WGA) and analyzed for the presence of copy number variations as well as point mutations (Ampli1 LowPass Kit and targeted sequencing of actionable hot-spots). Results: We analyzed seven CNS-derived single cells and five cell clusters from the medulloblastoma patient and further eight cell clusters and eight single cells obtained from the pineoblastoma patient. Transcriptome analysis revealed that expression of neural lineage markers (e.g. CD133, SYP, OTX2, MSI1, MAP2, NEUROG1 and NEUROD1) is present almost exclusively in CD45-negative cells. Only two samples collected from medulloblastoma patient co-expressed CD45 and GFAP. However, DNA analysis revealed that CD45-positive and CD45/GFAP double-positive samples showed non-aberrant genomic profiles, thus these cells were classified as non-malignant. In contrast, all CD45-negative cells harbored genetic alterations confirming their malignant origin. Conclusion: Our proof of concept study shows a novel workflow allowing identification, isolation as well as parallel genome and transcriptome analysis csfDCCs of patients with pediatric CNS tumors

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

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

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

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

Catch and release: Rare cell analysis from a functionalised medical wire

Enumeration and especially molecular characterization of circulating tumour cells (CTCs) holds great promise for cancer management. We tested a modified type of an in vivo enrichment device (Catch&Release) for its ability to bind and detach cancer cells for the purpose of single-cell molecular downstream analysis in vitro. The evaluation showed that single-cell analysis using array comparative genome hybridization (array-CGH) and next generation sequencing (NGS) is feasible. We found array-CGH to be less noisy when whole genome amplification (WGA) was performed with Ampli1 as compared to GenomePlex (DLRS values 0.65 vs. 1.39). Moreover, Ampli1-processed cells allowed detection of smaller aberrations (median 14.0 vs. 49.9 Mb). Single-cell NGS data obtained from Ampli1-processed samples showed the expected non-synonymous mutations (deletion/SNP) according to bulk DNA. We conclude that clinical application of this refined in vivo enrichment device allows CTC enumeration and characterization, thus, representing a promising tool for personalized medicine