Single-cell Copy Number Variation Research Articles

Abstract P3-01-09: Tracing clonal evolution of circulating tumor cells and cell-free DNA in a metastatic breast cancer patient

Abstract Background: Copy number variation analysis has been shown as a valuable tool to infer clonal evolution of tumor cells. While bulk genomic analysis of FFPE tissue can provide information about the characteristics of a primary tumor or a metastatic nodule, these biopsies are rarely repeated due to their invasive nature. Liquid biopsies on the other hand, provide minimally invasive access to tumor derived cells and DNA and can therefore be used to monitor genomic changes of the tumor longitudinally and in real time. Here we evaluate the kinetics of liquid biopsy biomarkers and monitor genomic changes in single circulating tumor cells (CTCs) and cell-free DNA (cfDNA) from 17 longitudinal blood draws collected from a metastatic breast cancer patient over seven treatment regimes. FFPE tissue from the primary tumor and two metastatic sites in liver and bone are available for comparative analysis. Methods: We used the high definition – single cell assay (HD-SCA) platform to detect and enumerate CTCs of the blood of one metastatic breast cancer patient followed for 4 years. CTCs were characterized morphometrically and single CTCs of each draw were sequenced for copy number variation (CNV). cfDNA was extracted from plasma and tissue samples of the primary breast, bone and liver metastasis were micro-dissected. Extracted DNA from tissue samples and plasma underwent CNV analysis and were compared with CNV data of CTCs. Results: CTCs were identified in 14/17 draws and varied from 0 to >3000 cells/ml, spiking at two different times concordant with clinical progression. Changes in cell free tumor DNA fraction (ctDNA) correlated strongly with CTC count. Comparative CNV analysis of CTCs, cfDNA and FFPE tissue confirmed the tumorous origin of both cells and cfDNA. Single cell CNV analysis found four genomically related sub-clones in the patient's blood, three of which were present at time of enrollment, while the fourth clone emerged 3.5 years later concordant with the decline in the patient's health. Genomic copy number losses included tumor suppressor genes such as ARID1A, FOXP1, ATM, BRCA2, RB1, CDH11 and CDH1. Genomic gains were limited but included the proto-oncogenes BCL9, ABL2 and MDM4. It is striking that the sub-clonal structure persisted nearly unchanged for 3.5 years throughout various hormone and cytotoxic treatments, indicating high genomic stability. Despite their genomic differences, cells from the different clones are indistinguishable by immunofluorescence or morphometric analysis. CNV profiles of cfDNA reflect the most abundant CTC clone at each time-point. Conclusion: Using the HD-SCA assay cellular (CTC), and soluble (cfDNA) fractions of liquid biopsies can be compared at the molecular level over a long time course, and verified by comparison with tissue biopsy. This work confirms that liquid biopsies can be used to access the molecular state of a patient's cancer in near real-time and provide insight into the response to treatment years after the original characterization of the primary tissue. Here we show in a single patient example the power of single CTC analysis and highlight how CNV analysis of liquid biopsies could serve as minimally invasive tool to monitor tumor evolution longitudinally. Citation Format: Welter L, Xu L, McKinley D, Dago AE, Restrepo-Vassalli S, Rodriguez Lee M, Kolatkar A, Nieva J, Hicks J, Kuhn P. Tracing clonal evolution of circulating tumor cells and cell-free DNA in a metastatic breast cancer patient [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P3-01-09.

Abstract AP06: SUBCLINICAL SIGNIFICANCE OF CIRCULATING TUMOR CELLS IN EPITHELIAL OVARIAN CANCER AS AN EARLY INDICATEOR OF RECURRENCE

Abstract BACKGROUND: After diagnosis of cancer and subsequent treatment, a fraction of epithelial ovarian cancer (EOC) patients relapse with distant metastatic disease. While the fraction of the treated population that will relapse is predictable, there is not yet a way to determine the specific cases that will become metastatic. This transition between localized and disseminated cancer is clinically identified by the appearance of the patient's original cancer in a new anatomic location by various imaging methodologies or the increase of surrogate serum biomarkers. The actual biologic transition point, however, clearly occurs at some point prior to the time when metastasis becomes clinically evident. This becomes relevant during periods when disease is not clinically evident, where more sensitive identification methods of relapsing cancer may offer opportunities for therapy before tumor burden rises to an incurable level. PURPOSE: With the observation that circulating tumor cells (CTCs) are found in cancer patients with no clinical evidence of disseminated disease prior to clinically evident relapse, we sought to investigate whether the presence of CTCs in the circulatory compartment could possibly indicate tumor dissemination at its earliest time point and whether that could be leveraged to develop predictive models and markers that identify patients prior to clinical evidence of recurrent disease. METHODS: Peripheral blood samples collected after chemotherapy from 18 patients diagnosed with serous EOC were evaluated using the High Definition– Single Cell Assay (HD–SCA) for HD–CTCs enumeration, cytomorphological analysis and DNA copy number variation (CNV) profiling. RESULTS: HD–CTCs (≥1 CTC/mL) were detected in 9 (50%) of these patients, 3 of whom relapsed. Despite the genomic heterogeneity of the CTCs analyzed, single cell CNV profiles from one of these recurrent patients showed clonal cyclin E1 amplification on chromosome 19 and ARID1A tumor suppressor gene deletion on chromosome 1, genomic alterations consistent with EOC. CONCLUSION: The data suggests malignancy of multiple, single CTCs in recurrent patients, and further analysis of CTCs from non–recurrent patients could provide the means to determine the subclinical significance of CTCs in ovarian cancer. Earlier diagnosis of relapse, and subsequent personalized treatment, could eventually lead to more favorable prognoses in EOC patients. Citation Format: Carmen Ruiz, Serena Zheng, Bridgette Duggan, James Hicks and Peter Kuhn. SUBCLINICAL SIGNIFICANCE OF CIRCULATING TUMOR CELLS IN EPITHELIAL OVARIAN CANCER AS AN EARLY INDICATEOR OF RECURRENCE [abstract]. In: Proceedings of the 11th Biennial Ovarian Cancer Research Symposium; Sep 12-13, 2016; Seattle, WA. Philadelphia (PA): AACR; Clin Cancer Res 2017;23(11 Suppl):Abstract nr AP06.

Single-Cell-Based Platform for Copy Number Variation Profiling through Digital Counting of Amplified Genomic DNA Fragments.

We develop a novel single-cell-based platform through digital counting of amplified genomic DNA fragments, named multifraction amplification (mfA), to detect the copy number variations (CNVs) in a single cell. Amplification is required to acquire genomic information from a single cell, while introducing unavoidable bias. Unlike prevalent methods that directly infer CNV profiles from the pattern of sequencing depth, our mfA platform denatures and separates the DNA molecules from a single cell into multiple fractions of a reaction mix before amplification. By examining the sequencing result of each fraction for a specific fragment and applying a segment-merge maximum likelihood algorithm to the calculation of copy number, we digitize the sequencing-depth-based CNV identification and thus provide a method that is less sensitive to the amplification bias. In this paper, we demonstrate a mfA platform through multiple displacement amplification (MDA) chemistry. When performing the mfA platform, the noise of MDA is reduced; therefore, the resolution of single-cell CNV identification can be improved to 100 kb. We can also determine the genomic region free of allelic drop-out with mfA platform, which is impossible for conventional single-cell amplification methods.

Chromosomal Instability Estimation Based on Next Generation Sequencing and Single Cell Genome Wide Copy Number Variation Analysis.

Genomic instability is a hallmark of cancer often associated with poor patient outcome and resistance to targeted therapy. Assessment of genomic instability in bulk tumor or biopsy can be complicated due to sample availability, surrounding tissue contamination, or tumor heterogeneity. The Epic Sciences circulating tumor cell (CTC) platform utilizes a non-enrichment based approach for the detection and characterization of rare tumor cells in clinical blood samples. Genomic profiling of individual CTCs could provide a portrait of cancer heterogeneity, identify clonal and sub-clonal drivers, and monitor disease progression. To that end, we developed a single cell Copy Number Variation (CNV) Assay to evaluate genomic instability and CNVs in patient CTCs. For proof of concept, prostate cancer cell lines, LNCaP, PC3 and VCaP, were spiked into healthy donor blood to create mock patient-like samples for downstream single cell genomic analysis. In addition, samples from seven metastatic castration resistant prostate cancer (mCRPC) patients were included to evaluate clinical feasibility. CTCs were enumerated and characterized using the Epic Sciences CTC Platform. Identified single CTCs were recovered, whole genome amplified, and sequenced using an Illumina NextSeq 500. CTCs were then analyzed for genome-wide copy number variations, followed by genomic instability analyses. Large-scale state transitions (LSTs) were measured as surrogates of genomic instability. Genomic instability scores were determined reproducibly for LNCaP, PC3, and VCaP, and were higher than white blood cell (WBC) controls from healthy donors. A wide range of LST scores were observed within and among the seven mCRPC patient samples. On the gene level, loss of the PTEN tumor suppressor was observed in PC3 and 5/7 (71%) patients. Amplification of the androgen receptor (AR) gene was observed in VCaP cells and 5/7 (71%) mCRPC patients. Using an in silico down-sampling approach, we determined that DNA copy number and genomic instability can be detected with as few as 350K sequencing reads. The data shown here demonstrate the feasibility of detecting genomic instabilities at the single cell level using the Epic Sciences CTC Platform. Understanding CTC heterogeneity has great potential for patient stratification prior to treatment with targeted therapies and for monitoring disease evolution during treatment.

Single cell copy number variation analysis of circulating tumor cells in gastrointestinal cancer patients for study of intra-patient genomic heterogeneity.

e23122Background: Tumor heterogeneity represents a key hallmark of cancer which complicates anti-cancer treatments. Presence of sub-clonal tumor population may be undetected through bulk tumor sequ...

Abstract 371: Longitudinal genetic characterization of circulating tumor cells in metastatic breast cancer patients

Abstract 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

Abstract 4599: Sequential monitoring of single-cell copy number variation in metastatic prostate cancer.

Abstract The high-definition circulating tumor cell (HD-CTC) assay provides for an enrichment-free approach to CTC identification. Here, we utilized the HD-CTC approach to study androgen receptor (AR) expression combined with single-nucleus sequencing for genome-wide analysis of copy number variation (CNV) in sequential CTCs samples obtained from a patient with metastatic prostate cancer treated with abiraterone acetate (an androgen synthesis inhibitor). At baseline, before initiation of abiraterone treatment, we observed a balanced proportion of AR-negative and AR-positive CTCs. During a brief period of clinical response (marked with a decreased serum PSA and decreased pain) the proportion of AR-positive CTCs declined followed by a rapid increase associated with clinical progression (increased PSA and pain). CNV analysis of single CTCs revealed multiple genomic rearrangements, such as AR amplification along with the chromosomal gains and losses typical of prostate cancer, in multiple cells at baseline. During treatment response, the frequency of CNV alterations significantly declined, followed by a reemergence to a pattern of multiple, complex alterations associated with clinical progression. Detailed analysis of the CNV profiles revealed that many abnormalities were commonly shared between the CTC populations, but a number were unique to the AR+ resistant/hormone refractory CTC population including increased MYC amplification alteration and the AR amplicon that include additional adjacent genes. Remarkably, the reconstruction of tumor lineage history based on the CTC genomic profiles enables us to trace and identify the precise treatment time point where the putative therapy-resistant CTC clone emerges, under therapeutic pressure, until it eventually expanded to become the AR+ resistant CTC population at the point of therapeutic relapse. Overall, our results demonstrated that the integration of the HD-CTC enumeration technology with protein expression and single cell genomic analyses could successfully be applied to real time monitoring of ADT therapy emergent change in a prostate cancer patient, and may provide a direct roadmap for personalized cancer medicine in the near future. Citation Format: Peter Kuhn, Angel E. Dago, Asya Stepansky, Anders Carlsson, Natalie Felch, Madelyn Luttgen, Anand Kolatkar, James Hicks, Mitchell E. Gross. Sequential monitoring of single-cell copy number variation in metastatic prostate cancer. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 4599. doi:10.1158/1538-7445.AM2013-4599

A Single Cell Level Based Method for Copy Number Variation Analysis by Low Coverage Massively Parallel Sequencing

Copy number variations (CNVs), a common genomic mutation associated with various diseases, are important in research and clinical applications. Whole genome amplification (WGA) and massively parallel sequencing have been applied to single cell CNVs analysis, which provides new insight for the fields of biology and medicine. However, the WGA-induced bias significantly limits sensitivity and specificity for CNVs detection. Addressing these limitations, we developed a practical bioinformatic methodology for CNVs detection at the single cell level using low coverage massively parallel sequencing. This method consists of GC correction for WGA-induced bias removal, binary segmentation algorithm for locating CNVs breakpoints, and dynamic threshold determination for final signals filtering. Afterwards, we evaluated our method with seven test samples using low coverage sequencing (4∼9.5%). Four single-cell samples from peripheral blood, whose karyotypes were confirmed by whole genome sequencing analysis, were acquired. Three other test samples derived from blastocysts whose karyotypes were confirmed by SNP-array analysis were also recruited. The detection results for CNVs of larger than 1 Mb were highly consistent with confirmed results reaching 99.63% sensitivity and 97.71% specificity at base-pair level. Our study demonstrates the potential to overcome WGA-bias and to detect CNVs (>1 Mb) at the single cell level through low coverage massively parallel sequencing. It highlights the potential for CNVs research on single cells or limited DNA samples and may prove as a promising tool for research and clinical applications, such as pre-implantation genetic diagnosis/screening, fetal nucleated red blood cells research and cancer heterogeneity analysis.

Single-cell copy number variation detection

Detection of chromosomal aberrations from a single cell by array comparative genomic hybridization (single-cell array CGH), instead of from a population of cells, is an emerging technique. However, such detection is challenging because of the genome artifacts and the DNA amplification process inherent to the single cell approach. Current normalization algorithms result in inaccurate aberration detection for single-cell data. We propose a normalization method based on channel, genome composition and recurrent genome artifact corrections. We demonstrate that the proposed channel clone normalization significantly improves the copy number variation detection in both simulated and real single-cell array CGH data.