18 research outputs found

    A microfluidic-based filtration system to enrich for bone marrow disseminated tumor cells from breast cancer patients

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    Disseminated tumors cells (DTCs) present in the bone marrow (BM) are believed to be the progenitors of distant metastatic spread, a major cause of mortality in breast cancer patients. To better understand the behavior and therapeutic vulnerabilities of these rare cell populations, unbiased methods for selective cell enrichment are required. In this study, we have evaluated a microfluidic-based filtration system (ParsortixR, Angle PLC), previously demonstrated for use in circulating tumor cell (CTC) capture, to capture BM DTCs. Performance using BM samples was also compared directly to enrichment of CTCs in the peripheral blood (PB) from both metastatic and non-metastatic breast cancer patients. Although the non-specific capture of BM immune cells was significant, the device could routinely achieve significant cytoreduction of BM and PB WBCs and at least 1,000-fold enrichment of DTCs, based on labeled tumor cell spike-in experiments. Detection of previously characterized DTC-associated gene expression biomarkers was greatly enhanced by the enrichment method, as demonstrated by droplet digital PCR assay. Cells eluted from the device were viable and suitable for single cell RNA sequencing experiments. DTCs in enriched BM samples comprised up to 5% of the total cell population, allowing for effective single cell and population-based transcriptional profiling of these rare cells. Use of the Parsortix instrument will be an effective approach to enrich for rare BM DTCs in order to better understand their diverse molecular phenotypes and develop approaches to eradicate these cells to prevent distant disease development in breast cancer patients

    Gene expression analysis to detect disseminated tumor cells in the bone marrow of triple-negative breast cancer patients predicts metastatic relapse

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    PURPOSE: Disseminated tumor cells (DTCs) in the BM of breast cancer patients predict early disease relapse, but the molecular heterogeneity of these cells is less well characterized. Expression of a 46-gene panel was used to detect DTCs and classify patient BM samples to determine whether a composite set of biomarkers could better predict metastatic relapse. METHODS: Using a high-throughput qRT-PCR assay platform, BM specimens collected from 70 breast cancer patients prior to neoadjuvant therapy were analyzed for the expression of 46 gene transcripts. Gene expression was scored positive (detectable) relative to a reference pool of 16 healthy female control BM specimens. To validate findings from a subset of 28 triple-negative breast cancer (TNBC) patients in the initial 70 patient cohort, an independent set of pre-therapeutic BM specimens from 16 TNBC patients was analyzed. RESULTS: Expression of each of the 46 gene transcripts was highly variable between patients. Individual gene expression was detected in 0-84% of BM specimens analyzed and all but two patient BM specimens expressed at least one transcript. Among a subset of 28 patients with TNBC, positivity of one or more of eight transcripts correlated with time to distant relapse (p = 0.03). In an independent set of 16 triple-negative patient BM samples, detection of five of these same eight gene transcripts also correlated with time to distant relapse (p = 0.03) with a positive predictive value of 89%. CONCLUSIONS: We identified a set of gene transcripts whose detection in the BM of TNBC patients, prior to any treatment intervention, predicts time to first distant relapse, thus identifying a TNBC patient population which requires additional treatment intervention. Because these genes are presumably expressed in populations of DTCs and many encode proteins that are known therapeutic targets (e.g., ERBB2), these results also suggest a potential approach for targeted DTC therapy to mitigate distant metastases in TNBC

    Gene expression analysis to detect disseminated tumor cells in the bone marrow of triple-negative breast cancer patients predicts metastatic relapse

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    PURPOSE: Disseminated tumor cells (DTCs) in the BM of breast cancer patients predict early disease relapse, but the molecular heterogeneity of these cells is less well characterized. Expression of a 46-gene panel was used to detect DTCs and classify patient BM samples to determine whether a composite set of biomarkers could better predict metastatic relapse. METHODS: Using a high-throughput qRT-PCR assay platform, BM specimens collected from 70 breast cancer patients prior to neoadjuvant therapy were analyzed for the expression of 46 gene transcripts. Gene expression was scored positive (detectable) relative to a reference pool of 16 healthy female control BM specimens. To validate findings from a subset of 28 triple-negative breast cancer (TNBC) patients in the initial 70 patient cohort, an independent set of pre-therapeutic BM specimens from 16 TNBC patients was analyzed. RESULTS: Expression of each of the 46 gene transcripts was highly variable between patients. Individual gene expression was detected in 0-84% of BM specimens analyzed and all but two patient BM specimens expressed at least one transcript. Among a subset of 28 patients with TNBC, positivity of one or more of eight transcripts correlated with time to distant relapse (p = 0.03). In an independent set of 16 triple-negative patient BM samples, detection of five of these same eight gene transcripts also correlated with time to distant relapse (p = 0.03) with a positive predictive value of 89%. CONCLUSIONS: We identified a set of gene transcripts whose detection in the BM of TNBC patients, prior to any treatment intervention, predicts time to first distant relapse, thus identifying a TNBC patient population which requires additional treatment intervention. Because these genes are presumably expressed in populations of DTCs and many encode proteins that are known therapeutic targets (e.g., ERBB2), these results also suggest a potential approach for targeted DTC therapy to mitigate distant metastases in TNBC

    Overexpression of BH3-Only Protein BNIP3 Leads to Enhanced Tumor Growth

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    BCL-2/E1B-19 kDa–interacting protein 3 (BNIP3) is a BH3-only mitochondrial protein. Expression of BNIP3 is strongly stimulated by hypoxia. Up-regulation of BNIP3 has been detected in several human carcinomas including carcinomas of the lung and breast. The significance of BNIP3 overexpression in these cancers is not known. To determine whether BNIP3 plays a role in tumor growth, we generated A549 lung carcinoma cells that overexpressed BNIP3 and examined their ability to form tumors in the mouse xenograft model. All cell lines that overexpressed BNIP3 formed larger tumors compared to the parental or vector-transformed A549 cells. Breast carcinoma cell lines that overexpressed BNIP3 also induced tumors in athymic mice in the absence of hormone administration, while the parental cell line did not. Stable shRNA-mediated knockdown of endogenous BNIP3 severely impaired the tumorigenic activity of A549 cells. The tumor growth-enhancing activity was reduced by deletion of the BH3 domain of BNIP3. Expression of a dominant-negative mutant of BNIP3 lacking the C-terminal transmembrane domain also inhibited the tumorigenic potential of A549 cells. These results suggest that BNIP3 plays a fundamental role in the development of certain solid tumors such as the lung and breast carcinomas

    Identifying biomarkers of breast cancer micrometastatic disease in bone marrow using a patient-derived xenograft mouse model

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    Abstract Background Disseminated tumor cells (DTCs) found in the bone marrow (BM) of patients with breast cancer portend a poor prognosis and are thought to be intermediaries in the metastatic process. To assess the clinical relevance of a mouse model for identifying possible prognostic and predictive biomarkers of these cells, we have employed patient-derived xenografts (PDX) for propagating and molecularly profiling human DTCs. Methods Previously developed mouse xenografts from five breast cancer patients were further passaged by implantation into NOD/SCID mouse mammary fat pads. BM was collected from long bones at early, serial passages and analyzed for human-specific gene expression by qRT-PCR as a surrogate biomarker for the detection of DTCs. Microarray-based gene expression analyses were performed to compare expression profiles between primary xenografts, solid metastasis, and populations of BM DTCs. Differential patterns of gene expression were then compared to previously generated microarray data from primary human BM aspirates from patients with breast cancer and healthy volunteers. Results Human-specific gene expression of SNAI1, GSC, FOXC2, KRT19, and STAM2, presumably originating from DTCs, was detected in the BM of all xenograft mice that also developed metastatic tumors. Human-specific gene expression was undetectable in the BM of those xenograft lines with no evidence of distant metastases and in non-transplanted control mice. Comparative gene expression analysis of BM DTCs versus the primary tumor of one mouse line identified multiple gene transcripts associated with epithelial-mesenchymal transition, aggressive clinical phenotype, and metastatic disease development. Sixteen of the PDX BM associated genes also demonstrated a statistically significant difference in expression in the BM of healthy volunteers versus the BM of breast cancer patients with distant metastatic disease. Conclusion Unique and reproducible patterns of differential gene expression can be identified that presumably originate from BM DTCs in mouse PDX lines. Several of these identified genes are also detected in the BM of patients with breast cancer who develop early metastases, which suggests that they may be clinically relevant biomarkers. The PDX model may also provide a clinically relevant system for analyzing and targeting these intermediaries of metastases

    Enrichment and Molecular Analysis of Breast Cancer Disseminated Tumor Cells from Bone Marrow Using Microfiltration.

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    PURPOSE:Molecular characterization of disseminated tumor cells (DTCs) in the bone marrow (BM) of breast cancer (BC) patients has been hindered by their rarity. To enrich for these cells using an antigen-independent methodology, we have evaluated a size-based microfiltration device in combination with several downstream biomarker assays. METHODS:BM aspirates were collected from healthy volunteers or BC patients. Healthy BM was mixed with a specified number of BC cells to calculate recovery and fold enrichment by microfiltration. Specimens were pre-filtered using a 70 μm mesh sieve and the effluent filtered through CellSieve microfilters. Captured cells were analyzed by immunocytochemistry (ICC), FISH for HER-2/neu gene amplification status, and RNA in situ hybridization (RISH). Cells eluted from the filter were used for RNA isolation and subsequent qRT-PCR analysis for DTC biomarker gene expression. RESULTS:Filtering an average of 14×106 nucleated BM cells yielded approximately 17-21×103 residual BM cells. In the BC cell spiking experiments, an average of 87% (range 84-92%) of tumor cells were recovered with approximately 170- to 400-fold enrichment. Captured BC cells from patients co-stained for cytokeratin and EpCAM, but not CD45 by ICC. RNA yields from 4 ml of patient BM after filtration averaged 135ng per 10 million BM cells filtered with an average RNA Integrity Number (RIN) of 5.3. DTC-associated gene expression was detected by both qRT-PCR and RISH in filtered spiked or BC patient specimens but, not in control filtered normal BM. CONCLUSIONS:We have tested a microfiltration technique for enrichment of BM DTCs. DTC capture efficiency was shown to range from 84.3% to 92.1% with up to 400-fold enrichment using model BC cell lines. In patients, recovered DTCs can be identified and distinguished from normal BM cells using multiple antibody-, DNA-, and RNA-based biomarker assays

    Expression of DTC associated transcripts in filtered and unfiltered BM specimens.

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    <p>Expression of 11 genes in normal BM samples spiked with 20 MDA-MB-231 cells per million nucleated BM cells compared to unspiked normal BM (NBM) as shown in x-axis. RNA expression was measured in either filtered (F) or unfiltered (UF) BM samples. Gene expression was determined by qRT-PCR on a Fluidigm platform. The actual fold values over normal BM are depicted.</p
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