Construction of repeat-free fluorescence in situ hybridization probes

FISH probes are generally made out of BAC clones with genomic DNA containing a variable amount of repetitive DNA that will need to be removed or blocked for FISH analysis. To generate repeat free (RF) Probes without loss in genomic coverage, a random library is made from BAC clones by whole-genome amplification (WGA). Libraries are denatured in the presence of excess C0t-1 DNA and allowed to re-anneal followed by digestion of all double-stranded elements by duplex-specific nuclease (DSN). Selective amplification of all elements not containing repetitive sequences is realized by a sequential amplification. The final RF products can be re-amplified and used as a stock for future probe production. The RF probes have a lower background, the signal intensity build up is faster and there is no need for blocking DNA. The signal to background ratio of the RF was higher as compared to repeat containing probes

Detection of cancer before distant metastasis

Background: To establish a distant metastasis (DM) cells must disseminate from the primary tumor and overcome a series of obstacles, the metastatic cascade. In this study we develop a mathematical model for this cascade to estimate the tumor size and the circulating tumor cell (CTC) load before the first metastasis has formed from a primary breast cancer tumor. Methods: The metastatic cascade is described in discrete steps: 1. local tumor growth; 2. dissemination into circulation; 3. survival in circulation; 4. extravasation into tissue; and 5. growth into a metastasis. The model was built using data and relationships described in the literature to predict the relationship between tumor size and probability of distant metastasis for 38715 patients with surgically removed TXNXM0 primary breast cancer from the Netherlands Cancer Registry. The model was calibrated using primary tumor size, probability of distant metastasis and time to distant metastasis for 1489 patients with stage T1BNXM0 (25% of total patients with T1BNXM0). Validation of the model was done with data for all patients. Results: From the time to distant metastasis of these 38715 breast cancer patients, we determined a tumor doubling time of 1.7 ± 0.9 months. Fitting the data for 25% of T1B patients estimates a metastatic efficiency of 1 metastasis formed per 60 million disseminated tumor cells. Validation of the model to data of patients in all T-stages shows good agreement between model and epidemiological data. To reduce the 5-year risk of distant metastasis for TXNXM0 from 9.2% to 1.0%, the primary tumor needs to be detected and removed before it reaches a diameter of 2.7 ± 1.6 mm. At this size, the model predicts that there will be 9 ± 6 CTC/L blood. Conclusions: To reduce the rate of distant metastasis in surgically treated TXNXM0 breast cancer to 1%, imaging technology will need to be able to detect lesions of 2.7 mm in diameter or smaller. Before CTC detection can be applied in the early disease setting, sensitivity will need to be improved by at least 15-fold and combined with technology that minimizes false positives

All patients with metastatic breast, colorectal and prostate carcinoma have circulating tumor cells

Background: Presence of EpCAM+ cytokeratin+ nucleated circulating tumor cells (CTC) in metastatic carcinoma patients is associated with poor survival and may be used to guide treatment. Assessment of treatment targets on these CTC holds the promise of a liquid biopsy. However the proportion of patients in which a sufficient number of CTC are detected in 7.5 mL of blood is not sufficient. In this study we estimate the number of CTC in blood of patients with metastatic disease, explore the relationship with survival and determine whether assay modifications and/or increases in sample volume are needed to achieve the required increase in number of CTC detected. Methods: EpCAM+CK+DNA+CD45- CTC enumeration was performed with the CellSearch® system in 7.5 mL of blood of 836 patients with metastatic breast, colorectal and prostate cancer patients (Cristofanilli, NEJM 2004, Cohen, JCO 2008, De Bono, CCR 2008). EpCAM+, CD45-, Nucleic acid+ CTC were enumerated in 100ul of NH4CL lysed blood from 140 metatatic cancer patients and compared to CTC as enumerated with the CellSearch system. Image analysis for automated CTC enumeration and modeling of CTC frequencies was performed in Matlab. Results: The median number of CTC in 7.5mL of blood metastatic breast, colorectal and prostate is 5 and in 39% of patients no CTC are detected. The best fit of the CTC frequency distribution was used to extrapolate the sample volume to 5 liters of blood and predicted that 99% (95% confidence interval, CI, 95-99.8%) of patients had at least 1 CTC before initiation of therapy, which decreased to 97% (95% CI 87-99.5%) after the first cycles of therapy. One hundred CTC per liter of blood are present in ∼80% of patients, 1 CTC per ml of blood in ∼40% of patients and 10 CTC per ml of blood in ∼20% of patients. The median survival of patients with CTC is reduced by 6.6 months for each tenfold CTC increase. CTC definitions that do not include a requirement for presence of DNA, EpCAM, cytokeratin 8,18,19 (CK) or absence of CD45 are less predictive of survival, than the strictest definition requiring a CTC to be EpCAM+CK+DNA+CD45-. Comparison of CTC detected by flow cytometry to the CellSearch CTC method on 140 patients shows that improvements in EpCAM recovery may increase the average number of detected CTC by 6.5 fold (95% CI 5.6-7.3), yet the fits predict that this will only reduce the number of patients with 0 CTC from 39% to 21% (95% CI 13-31%). Conclusions: EpCAM+CK+DNA+CD45- CTC are present in blood of all patients with metastatic breast, colorectal and prostate cancer. The predicted strong relation with survival suggests the importance of this phenotype for metastasis. To use CTC as a liquid biopsy for the majority of patients, the CTC yield needs to be improved 100-1000 fold. This requires a dramatic increase in sample volume which may be achieved by in vivo flow cytometry, or through processing an apheresis product

Methods and algorithms for cell enumeration in low-cost cytometer

The enumeration of cells in fluids by flow cytometry is widely used across many disciplines such as assessment of leukocyte subsets in different bodily fluids or of bacterial contamination in environmental samples, food products and bodily fluids. For many applications the cost, size and complexity of the instruments prevents wider use, for example, CD4 analysis in HIV monitoring in resource-poor countries. The novel device, methods and algorithms disclosed herein largely overcome these limitations. Briefly, all cells in a biological sample are fluorescently labeled, but only the target cells are also magnetically labeled. In addition, non-magnetically labeled cells are imaged for viability in a modified slide configuration. The labeled sample, in a chamber or cuvet, is placed between two wedge-shaped magnets to selectively move the magnetically labeled cells to the observation surface of the cuvet. An LED illuminates the cells and a CCD camera captures the images of the fluorescent light emitted by the target cells. Image analysis performed with a novel algorithm provides a count of the cells on the surface that can be related to the target cell concentration of the original sample. The compact cytometer system provides a rugged, affordable and easy-to-use technique, which can be used in remote locations

Centrifugation affects the purity of liquid biopsy-based tumor biomarkers

Biomarkers in the blood of cancer patients include circulating tumor cells (CTCs), tumor-educated platelets (TEPs), tumor-derived extracellular vesicles (tdEVs), EV-associated miRNA (EV-miRNA), and circulating cell-free DNA (ccfDNA). Because the size and density of biomarkers differ, blood is centrifuged to isolate or concentrate the biomarker of interest. Here, we applied a model to estimate the effect of centrifugation on the purity of a biomarker according to published protocols. The model is based on the Stokes equation and was validated using polystyrene beads in buffer and plasma. Next, the model was applied to predict the biomarker behavior during centrifugation. The result was expressed as the recovery of CTCs, TEPs, tdEVs in three size ranges (1–8, 0.2–1, and 0.05–0.2 μm), EV-miRNA, and ccfDNA. Bead recovery was predicted with errors <18%. Most notable cofounders are the 22% contamination of 1–8 μm tdEVs for TEPs and the 8–82% contamination of <1 μm tdEVs for ccfDNA. A Stokes model can predict biomarker behavior in blood. None of the evaluated protocols produces a pure biomarker. Thus, care should be taken in the interpretation of obtained results, as, for example, results from TEPs may originate from co-isolated large tdEVs and ccfDNA may originate from DNA enclosed in <1 μm tdEVs

Surface plasmon resonance is an analytically sensitive method for antigen profiling of extracellular vesicles

BACKGROUND: Identification, enumeration, and characterization of extracellular vesicles (EVs) are hampered by the small size of EVs, a low refractive index, and low numbers of antigens on their surface. METHODS: We investigated the potential of a 48- multiplex surface plasmon resonance imaging (SPRi) system to perform EV phenotyping. Antigen surface density of 11 antigens was measured on the human breast cancer cell lines HS578T, MCF7, and SKBR3 and their EVs by use of both SPRi and the widely used flow cytometry (FCM). RESULTS: For cells, the SPRi andFCMsignals for antigen exposure correlated (R2 HS578T cells = 0.66, R2 MCF7 cells = 0.78, R2 SKBR3 cells = 0.60). With regard to EVs, SPRi detected 31 out of 33 tested antibody-EV pairs, whereas our flow cytometer detected 5 antibody-EV pairs because of high blank and isotype control signals. For HS578T-derived EVs, the SPRi and FCM signals correlated (R2 HS578T EVs = 0.98). However, on MCF7- and SKBR3-derived EVs, insufficient antigens were detected by our flow cytometer. To confirm that the SPRi responses correlated with mean antigen density on EVs, the SPRi responses of EVs were correlated with antigen density on parental cells as measured by FCM (R2 HS578T = 0.77, R2 MCF7 = 0.49, R2 SKBR3 = 0.52). CONCLUSIONS: SPRi responses correlate with mean antigen density. Moreover, SPRi detects lower antigenexposure levels than FCM because SPRi measures an ensemble of EVs binding to the sensor surface, whereas FCM detects antigens of single EV