Glenn Deng

Single Cell Profiling of Circulating Tumor Cells: Transcriptional Heterogeneity and Diversity from Breast Cancer Cell Lines

Background To improve cancer therapy, it is critical to target metastasizing cells. Circulating tumor cells (CTCs) are rare cells found in the blood of patients with solid tumors and may play a key role in cancer dissemination. Uncovering CTC phenotypes offers a potential avenue to inform treatment. However, CTC transcriptional profiling is limited by leukocyte contamination; an approach to surmount this problem is single cell analysis. Here we demonstrate feasibility of performing high dimensional single CTC profiling, providing early insight into CTC heterogeneity and allowing comparisons to breast cancer cell lines widely used for drug discovery. Methodology/Principal Findings We purified CTCs using the MagSweeper, an immunomagnetic enrichment device that isolates live tumor cells from unfractionated blood. CTCs that met stringent criteria for further analysis were obtained from 70% (14/20) of primary and 70% (21/30) of metastatic breast cancer patients; none were captured from patients with non-epithelial cancer (n = 20) or healthy subjects (n = 25). Microfluidic-based single cell transcriptional profiling of 87 cancer-associated and reference genes showed heterogeneity among individual CTCs, separating them into two major subgroups, based on 31 highly expressed genes. In contrast, single cells from seven breast cancer cell lines were tightly clustered together by sample ID and ER status. CTC profiles were distinct from those of cancer cell lines, questioning the suitability of such lines for drug discovery efforts for late stage cancer therapy. Conclusions/Significance For the first time, we directly measured high dimensional gene expression in individual CTCs without the common practice of pooling such cells. Elevated transcript levels of genes associated with metastasis NPTN, S100A4, S100A9, and with epithelial mesenchymal transition: VIM, TGFß1, ZEB2, FOXC1, CXCR4, were striking compared to cell lines. Our findings demonstrate that profiling CTCs on a cell-by-cell basis is possible and may facilitate the application of ‘liquid biopsies’ to better model drug discovery.

Linear mRNA amplification from as little as 5 ng total RNA for global gene expression analysis.

Gene expression analysis has become an invaluable tool for understanding gene function and regulation. However, global expression analysis requires large RNA quantities or RNA preamplification. We describe an isothermal messenger RNA (mRNA) amplification method, Ribo-SPIA, which generates micrograms of labeled cDNA from 5 ng of total RNA in 1 day for analysis on arrays or by PCR quantification. Highly reproducible GeneChip array performance (R2 > 0.95) was achieved with independent reactions starting with 5-100 ng Universal Human Reference total RNA. Targets prepared by the Ribo-SPIA procedure (20 ng total RNA input) or the Affymetrix Standard Protocol (10 microg total RNA) perform similarly, as indicated by gene call concordance (86%) and good correlation of differential gene expression determination (R2 = 0.82). Accuracy of transcript representation in cDNA generated by the Ribo-SPIA procedure was also demonstrated by PCR quantification of 33 transcripts, comparing differential expression in amplified and nonamplified cDNA (R2 = 0.97 over a range of nearly 10(6) infold change). Thus Ribo-SPIA amplification of mRNA is rapid, robust, highly accurate and reproducible, and sensitive enough to allow quantification of very low abundance transcripts.

Patient-derived xenografts of triple-negative breast cancer reproduce molecular features of patient tumors and respond to mTOR inhibition

IntroductionTriple-negative breast cancer (TNBC) is aggressive and lacks targeted therapies. Phosphatidylinositide 3-kinase (PI3K)/mammalian target of rapamycin (mTOR) pathways are frequently activated in TNBC patient tumors at the genome, gene expression and protein levels, and mTOR inhibitors have been shown to inhibit growth in TNBC cell lines. We describe a panel of patient-derived xenografts representing multiple TNBC subtypes and use them to test preclinical drug efficacy of two mTOR inhibitors, sirolimus (rapamycin) and temsirolimus (CCI-779).MethodsWe generated a panel of seven patient-derived orthotopic xenografts from six primary TNBC tumors and one metastasis. Patient tumors and corresponding xenografts were compared by histology, immunohistochemistry, array comparative genomic hybridization (aCGH) and phosphatidylinositol-4,5-bisphosphate 3-kinase, catalytic subunit alpha (PIK3CA) sequencing; TNBC subtypes were determined. Using a previously published logistic regression approach, we generated a rapamycin response signature from Connectivity Map gene expression data and used it to predict rapamycin sensitivity in 1,401 human breast cancers of different intrinsic subtypes, prompting in vivo testing of mTOR inhibitors and doxorubicin in our TNBC xenografts.ResultsPatient-derived xenografts recapitulated histology, biomarker expression and global genomic features of patient tumors. Two primary tumors had PIK3CA coding mutations, and five of six primary tumors showed flanking intron single nucleotide polymorphisms (SNPs) with conservation of sequence variations between primary tumors and xenografts, even on subsequent xenograft passages. Gene expression profiling showed that our models represent at least four of six TNBC subtypes. The rapamycin response signature predicted sensitivity for 94% of basal-like breast cancers in a large dataset. Drug testing of mTOR inhibitors in our xenografts showed 77 to 99% growth inhibition, significantly more than doxorubicin; protein phosphorylation studies indicated constitutive activation of the mTOR pathway that decreased with treatment. However, no tumor was completely eradicated.ConclusionsA panel of patient-derived xenograft models covering a spectrum of TNBC subtypes was generated that histologically and genomically matched original patient tumors. Consistent with in silico predictions, mTOR inhibitor testing in our TNBC xenografts showed significant tumor growth inhibition in all, suggesting that mTOR inhibitors can be effective in TNBC, but will require use with additional therapies, warranting investigation of optimal drug combinations.

Single Cell Isolation and Analysis

Individual cell heterogeneity within a population can be critical to its peculiar function and fate. Subpopulations studies with mixed mutants and wild types may not be as informative regarding which cell responds to which drugs or clinical treatments. Cell to cell differences in RNA transcripts and protein expression can be key to answering questions in cancer, neurobiology, stem cell biology, immunology, and developmental biology. Conventional cell-based assays mainly analyze the average responses from a population of cells, without regarding individual cell phenotypes. To better understand the variations from cell to cell, scientists need to use single cell analyses to provide more detailed information for therapeutic decision making in precision medicine. In this review, we focus on the recent developments in single cell isolation and analysis, which include technologies, analyses and main applications. Here, we summarize the historical background, limitations, applications, and potential of single cell isolation technologies.

Abstract 3528: Genotype discordance between circulating tumor cells in blood and disseminated tumor cells in bone marrow at single cell level in breast cancer patients

Proceedings: AACR Annual Meeting 2014; April 5-9, 2014; San Diego, CA Background: Circulating tumor cells (CTCs) in blood and disseminated tumor cells (DTCs) in bone marrow are being studied to monitor disease and guide therapy, but the relationship between CTCs and DTCs is weak and may confound clinical decision-making. Because blood sampling is easier than sampling bone marrow, CTC analyses are used more frequently than DTC analyses, although the relationship between CTCs and DTCs and the mutational heterogeneity within both populations at the single cell level are not usually examined simultaneously. Methods: We used the MagSweeper to immunomagnetically isolate single tumor cells from blood and bone marrow samples in breast cancer patients. Isolated tumor cells were used for immunohistochemical identification, PIK3CA gene mutation analysis, and to propagate cells in culture. In one patient, CTC and DTC single cell genotypes were compared during multiple treatment courses as the disease course progressed. Results: 242 individual tumor cells were isolated from 17 breast cancer patients. All tumor cells were assayed for single nucleotide mutations on exons 9 and 20 of the PIK3CA gene, and 48 mutated cells were identified in three patients. Heterogeneity and temporal discordance were observed in and between CTCs and DTCs in the same patient. All DTCs from bone marrow overgrown by tumor cells in a metastatic breast cancer patient carried the same PIK3CA single nucleotide mutation even though CTCs isolated within the same time period were wild type or heterogeneous for the mutation, providing evidence of both concordance and discordance of single cell PIK3CA genotype between CTCs and DTCs at different blood sampling time points. DTCs isolated by the MagSweeper could be directly cultured and consistently maintained the mutant PIK3CA genotype despite morphological changes over time in cell culture. Conclusions: DTCs isolated live by the MagSweeper can be propagated in culture, and a DNA single nucleotide mutation was maintained as a stable marker during cell culture multiple passages. This same mutation was used to monitor CTCs and DTCs at the single cell level. Although others have shown variable correlation between presence of CTCs and DTCs in the same patients, we show here potential discordance at the genotype level of single CTCs isolated from the same patient at different time points and between individual CTCs and DTCs. Our data support that CTCs and DTCs can have independent clinical value and suggest that it may be necessary to independently sample both during overall treatment course. Citation Format: Glenn Deng, Sujatha Krishnakumar, Marc A. Coram, Ashley A. Powell, Haiyu Zhang, Michael N. Mindrinos, Melinda L. Telli, Katharina E. Effenberger, Michael Herrler, Klaus Pantel, Ronald W. Davis, Stefanie S. Jeffrey. Genotype discordance between circulating tumor cells in blood and disseminated tumor cells in bone marrow at single cell level in breast cancer patients. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 3528. doi:10.1158/1538-7445.AM2014-3528

Abstract 4961: Analysis of genomic alterations in breast cancer using an automated aCGH workstation

The current sample preparation process for aCGH tests is tedious leading to errors that confound clinical results and increase re-test rates and costs. To overcome this problem, we have developed an aCGH workstation that automates the bench work from DNA labeling to array scanning. A robotic liquid handling and incubation system (ArrayPrep® Target Preparation System) automates the labeling and magnetic bead purification of 8-96 gDNA samples then loads them onto microarrays for hybridization using a rotating incubation system (Mai Tai® Hybridization System). Arrays are then post-processed using a robotic instrument (Little Dipper® Processor) for washing and drying. Previous studies have shown that the aCGH workstation generates high quality labeled gDNA and highly reproducible array data from batches of 8-96 samples. It requires less than 1hr hands-on technician time and can substantially enhance test reproducibility and lower cost (1). In this study, we examined the ability of the aCGH workstation to reproducibly detect genomic alterations in four well characterized breast cancer cell lines, MCF-7, SK-BR-3, BT-474 and MDA-MB-231 and in breast cancer tissue samples with known Her2/neu status. For each sample, replicate gDNA samples were processed using the aCGH workstation and Agilent 44K feature microarrays designed for genome-wide DNA copy number variation (CNV) profiling. The resulting array data were then analyzed for previously reported copy number alterations (CNAs) including loci within chromosomes 1q, 8q, 11q13, 17q and 20q13 (2, 3) and components of the epidermal growth factor receptor pathway affected by copy number changes (3). The results confirm that samples processed on the aCGH workstation reproducibly detect previously reported complex alterations involving multiple levels of change on chromosome arms 1p, 8q, 9p, 11q, 15q, 17q and 20q. Our data also confirmed that copy number alteration of multiple genetic loci involved in the EGF family of pathways is common in all four cell lines. The ERBB2 locus is highly amplified in the two known ERBB2-overexpressing cell lines (BT-474 and SK-BR-3). These two cell lines share amplifications at five additional gene loci, MAP2K6, CHN2, PRKCA, LIMK1 and cMYC, as previously reported (3). In summary, this initial study has shown the successful automation of the aCGH laboratory workflow for detection of genetic abnormalities at high resolution in breast cancer samples. This automated platform holds the potential to significantly improve test reliability and lower the cost of routine genetic analysis of clinical samples. References: 1. Herrler M, Ke W and Stanchfield J (2009). ASHG 59th Annual Meeting, Honolulu, Hawaii, Abstract 1442/W. 2. Pollack JR, Sorlie T, Perou CM, Rees CA, Jeffrey SS, Lonning PE, Tibshirani R, Botstein D, Borresen-Dale AL and Brown PO (2002). Proc Natl Acad Sci USA, 99(20):12963-8. 3. Shadeo A and Lam WL (2006). Breast Cancer Research, 8(1):R9. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 4961.