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.
Latest genotyping technologies allow to achieve a reliable genetic profile for the offender identification even from extremely minute biological evidence. The ultimate challenge occurs when genetic profiles need to be retrieved from a mixture, which is composed of biological material from two or more individuals. In this case, DNA profiling will often result in a complex genetic profile, which is then subject matter for statistical analysis. In principle, when more individuals contribute to a mixture with different biological fluids, their single genetic profiles can be obtained by separating the distinct cell types (e.g. epithelial cells, blood cells, sperm), prior to genotyping. Different approaches have been investigated for this purpose, such as fluorescent-activated cell sorting (FACS) or laser capture microdissection (LCM), but currently none of these methods can guarantee the complete separation of different type of cells present in a mixture. In other fields of application, such as oncology, DEPArray™ technology, an image-based, microfluidic digital sorter, has been widely proven to enable the separation of pure cells, with single-cell precision. This study investigates the applicability of DEPArray™ technology to forensic samples analysis, focusing on the resolution of the forensic mixture problem. For the first time, we report here the development of an application-specific DEPArray™ workflow enabling the detection and recovery of pure homogeneous cell pools from simulated blood/saliva and semen/saliva mixtures, providing full genetic match with genetic profiles of corresponding donors. In addition, we assess the performance of standard forensic methods for DNA quantitation and genotyping on low-count, DEPArray™-isolated cells, showing that pure, almost complete profiles can be obtained from as few as ten haploid cells. Finally, we explore the applicability in real casework samples, demonstrating that the described approach provides complete separation of cells with outstanding precision. In all examined cases, DEPArray™ technology proves to be a groundbreaking technology for the resolution of forensic biological mixtures, through the precise isolation of pure cells for an incontrovertible attribution of the obtained genetic profiles.
Background: We provide a solution of pressing needs in preparation of FFPE samples for genomic analysis: small sample size, unwanted admixture of normal cells, analysis of tumor rare-cell subpopulations present at low percentages in the tumor fraction. Methods: We disaggregated into cell suspensions archival FFPE samples from 12 ovarian, pancreatic and lung cancer patients, staining for Vimentin, Keratin and DNA. We sorted by DEPArray™ precise numbers (mean = 107, median 58, range = 5-600) of pure homogenous cells from the major population of tumor cells, the contaminant diploid stromal cells, and other minority tumor cell types indicative of epithelial-to-mesenchymal transition (EMT). Using IonTorrent AmpliSeq CHPv2, we generated sequencing libraries, after lysis of the pure cells recovered by DEPArray™ (n = 54), or unsorted samples (either QIAmp DNA columns or disaggregated cells). Libraries were sequenced with IonTorrent PGM (mean depth>2,000x), and analyzed using IonTorrent software. Results: On several loci, we detected somatic mutations with 100% variant frequency, only observable as heterozygous in the unsorted samples and as wild-type in stromal cells of same patient, confirming 100% purity of sorted cells. Moreover, in the EMT-phenotype subpopulations we identified clear somatic mutations, different from tumor cells majority and undetectable in unsorted samples. Frequently, for loci harboring germ-line heterozygous SNPs with variant frequency around 50% for pure stromal cells, we readily detected loss-of-heterozygosis in tumor cells subpopulations as binary (0%/100%) variants. Quantitative traits such as copy number gains and losses were also reproducibly identified in tumor cell replicates as deviations from the 50% variant frequency of germline SNPs of pure stromal cells. Furthermore, we observed an excellent coverage uniformity (mean = 96%) for recoveries (n = 27) in the range of 81-600 cells, even higher than the uniformity obtained with (n = 2) QIAmp-purified DNA (92%). Mean uniformity gradually decreased to 89% for cell recoveries (n = 13) in the range 21-80, and further decreased to 70% for lower cell numbers (n = 14). Highlights: Sorting tumor rare-cell subpopulations reveals their genetic characteristics, undetectable in unsorted samples. Analyzing homogenous cell subpopulations boosts signal-to-noise ratio working around inherent sensitivity/specifitiy trade-offs of rare-variant calls. The proposed workflow further enables reliable detection of quantitative traits such as CNVs. Sorting pure stromal cells yields internal controls for archival samples. Citation Format: Chiara Bolognesi, Anna Doffini, Genny Buson, Rossana Lanzellotto, Giulio Signorini, Valeria Sero, Alex Calanca, Francesca Fontana, Rita Romano, Stefano Gianni, Giulia Bregola, Gianni Medoro, Raimo Tanzi, Giuseppe Giorgini, Hans Morreau, Massimo Barberis, Willem E. Corver, Nicolo Manaresi. Image-based microchip sorting of pure, immuno-phenotypically defined subpopulations of tumor cells from tiny formalin-fixed paraffin embedded (FFPE) samples reveals their distinct genetic features. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 1552. doi:10.1158/1538-7445.AM2015-1552
Background: Little is known about the evolution of genetic aberrations during metastatic cancer progression and in response to systemic treatment. Obtaining repeated tissue biopsies is often impractical. On the other hand, it has been shown that circulating tumor cells (CTCs) can be easily followed during disease course and genetic characterization at the single cell level is possible with high reliability [1]. Methods: Individual CTCs of a ER+ and HER2- de novo metastatic breast cancer patient treated with weekly paclitaxel/gemcitabine as first line therapy, were collected at three different time points (before start, after one and two cycles of treatment). Whole peripheral blood was enriched using the CellSearch® system and CTCs were sorted by DEPArray™ device. The whole genome of single CTCs was amplified with Ampli1™ WGA kit and WGA quality was assessed by Ampli1™ QC Kit. Genome wide single cell copy number variation (CNV) profile was evaluated with Agilent SurePrint 180k array comparative genomic hybridization (aCGH). Results: CTCs count at CellSearch was 22, 75 and 15 at three time points respectively. A total of 25 single CTCs were collected and 23 (92%) showed high Genome Integrity Index (GII) as measured by Ampli1™ QC kit (GII = 3 or 4). For each time point multiple CTCs (3, 6 and 3 respectively) were selected for single cell aCGH analysis. The genomic profile was strikingly similar (1q gain, 12p, 13p, 16q and 17p losses) across individual cells of the same blood sample and throughout different time points evaluated. After 3 cycles of therapy a disease progression was documented by CAT-scan. Discussion: The observed high GII, low genetic heterogeneity and stable genome across different time points suggests the presence of an aggressive clone resistant to the treatment and cancer-associated genes analysis for sequence variants by NGS targeted sequencing is ongoing. Further patients with longitudinal follow-up will be enrolled in order to evaluate if the heterogeneity between aCGH profile at a given time point and longitudinal evolution of aCGH profiles can be associated with early treatment response. Results will be presented at the conference. [1] Polzer B, Medoro G, et al, EMBO Mol Med. 2014 Oct 30;6(11):1371-86. Citation Format: Valeria Sero, Francesca De Luca, Anna Doffini, Francesca Galardi, Marta Pestrin, Zbignew T. Czyz, Genny Buson, Giulia Bregola, Chiara Bolognesi, Francesca Fontana, Gianni Medoro, Bernhard Polzer, Angelo Di Leo, Christoph A. Klein, Nicolo Manaresi. Longitudinal genetic characterization of circulating tumor cells in metastatic breast cancer patients. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 371. doi:10.1158/1538-7445.AM2015-371
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