Dataset Information

Integrated Workflow for the Label-Free Isolation and Genomic Analysis of Single Circulating Tumor Cells in Pancreatic Cancer.

ABSTRACT: As pancreatic cancer is the third deadliest cancer in the U.S., the ability to study genetic alterations is necessary to provide further insight into potentially targetable regions for cancer treatment. Circulating tumor cells (CTCs) represent an especially aggressive subset of cancer cells, capable of causing metastasis and progressing the disease. Here, we present the Labyrinth-DEPArray pipeline for the isolation and analysis of single CTCs. Established cell lines, patient-derived CTC cell lines and freshly isolated CTCs were recovered and sequenced to reveal single-cell copy number variations (CNVs). The resulting CNV profiles of established cell lines showed concordance with previously reported data and highlight several gains and losses of cancer-related genes such as FGFR3 and GNAS. The novel sequencing of patient-derived CTC cell lines showed gains in chromosome 8q, 10q and 17q across both CTC cell lines. The pipeline was used to process and isolate single cells from a metastatic pancreatic cancer patient revealing a gain of chromosome 1q and a loss of chromosome 5q. Overall, the Labyrinth-DEPArray pipeline offers a validated workflow combining the benefits of antigen-free CTC isolation with single cell genomic analysis.

SUBMITTER: Rupp B

PROVIDER: S-EPMC9316651 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Circulating tumor cells (CTCs) have significant implications in both basic cancer research and clinical applications. To address the limited availability of viable CTCs for fundamental and clinical investigations, effective separation of extremely rare CTCs from blood is critical. Ferrohydrodynamic cell separation (FCS), a label-free method that conducted cell sorting based on cell size difference in biocompatible ferrofluids, has thus far not been able to enrich low-concentration CTCs from cancer patients' blood because of technical challenges associated with processing clinical samples. In this study, we demonstrated the development of a laminar-flow microfluidic FCS device that was capable of enriching rare CTCs from patients' blood in a biocompatible manner with a high throughput (6 mL h-1) and a high rate of recovery (92.9%). Systematic optimization of the FCS devices through a validated analytical model was performed to determine optimal magnetic field and its gradient, ferrofluid properties, and cell throughput that could process clinically relevant amount of blood. We first validated the capability of the FCS devices by successfully separating low-concentration (?100 cells per mL) cancer cells using six cultured cell lines from undiluted white blood cells (WBCs), with an average 92.9% cancer cell recovery rate and an average 11.7% purity of separated cancer cells, at a throughput of 6 mL per hour. Specifically, at ?100 cancer cells per mL spike ratio, the recovery rates of cancer cells were 92.3 ± 3.6% (H1299 lung cancer), 88.3 ± 5.5% (A549 lung cancer), 93.7 ± 5.5% (H3122 lung cancer), 95.3 ± 6.0% (PC-3 prostate cancer), 94.7 ± 4.0% (MCF-7 breast cancer), and 93.0 ± 5.3% (HCC1806 breast cancer), and the corresponding purities of separated cancer cells were 11.1 ± 1.2% (H1299 lung cancer), 10.1 ± 1.7% (A549 lung cancer), 12.1 ± 2.1% (H3122 lung cancer), 12.8 ± 1.6% (PC-3 prostate cancer), 11.9 ± 1.8% (MCF-7 breast cancer), and 12.2 ± 1.6% (HCC1806 breast cancer). Biocompatibility study on H1299 cell line and HCC1806 cell line showed that separated cancer cells had excellent short-term viability, normal proliferation and unaffected key biomarker expressions. We then demonstrated the enrichment of CTCs in blood samples obtained from two patients with newly diagnosed advanced non-small cell lung cancer (NSCLC). While still at its early stage of development, FCS could become a complementary tool for CTC separation for its high recovery rate and excellent biocompatibility, as well as its potential for further optimization and integration with other separation methods.

Project description:Cancer cells metastasize through the bloodstream either as single migratory circulating tumor cells (CTCs) or as multicellular groupings (CTC-clusters). Existing technologies for CTC enrichment are designed primarily to isolate single CTCs, and while CTC-clusters are detectable in some cases, their true prevalence and significance remain to be determined. Here, we developed a microchip technology (Cluster-Chip) specifically designed to capture CTC-clusters independent of tumor-specific markers from unprocessed blood. CTC-clusters are isolated through specialized bifurcating traps under low shear-stress conditions that preserve their integrity and even two-cell clusters are captured efficiently. Highly parallel architecture of the chip allows deterministic screening of clinically relevant volumes of blood samples at slow, and hence, non-damaging flow rates. Using the Cluster-Chip, we identify CTC-clusters in 30-40% of patients with metastatic cancers of the breast, prostate and melanoma. RNA sequencing of CTC-clusters confirms their tumor origin and identifies leukocytes within the clusters as being tissue-derived macrophages. Together, the development of a device for efficient capture of CTC-clusters will enable detailed characterization of their biological properties and role in cancer metastasis. We used the Cluster-Chip to capture CTC-clusters from the blood of a breast cancer patient with high CTC counts, released CTC-clusters in solution, stained them with TexasRed-conjugated antibodies against the leukocyte cell surface markers CD45, CD14 and CD16, and then isolated intact CTC-clusters individually using a micromanipulator. From a single time point, we retrieved 15 CTC-clusters, and each of those clusters was individually subjected to RNA-sequencing analysis using a next generation platform (SOLiD 5500). In addition, two leukocytes were isolated from the blood of a healthy donor were individually subjected to RNA-sequencing analysis using the same platform.

Dataset Information

Integrated Workflow for the Label-Free Isolation and Genomic Analysis of Single Circulating Tumor Cells in Pancreatic Cancer.

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