WO2011002649A1 - Analyse de microparticules liées à une tumeur circulante - Google Patents

Analyse de microparticules liées à une tumeur circulante Download PDF

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Publication number
WO2011002649A1
WO2011002649A1 PCT/US2010/039628 US2010039628W WO2011002649A1 WO 2011002649 A1 WO2011002649 A1 WO 2011002649A1 US 2010039628 W US2010039628 W US 2010039628W WO 2011002649 A1 WO2011002649 A1 WO 2011002649A1
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WIPO (PCT)
Prior art keywords
tmp
ctc
labeled
cells
blood
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PCT/US2010/039628
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English (en)
Inventor
Frank Coumans
Leon W.M.M. Terstappen
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Veridex, Llc
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Publication of WO2011002649A1 publication Critical patent/WO2011002649A1/fr

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/53—Immunoassay; Biospecific binding assay; Materials therefor
    • G01N33/574—Immunoassay; Biospecific binding assay; Materials therefor for cancer
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/53—Immunoassay; Biospecific binding assay; Materials therefor
    • G01N33/543—Immunoassay; Biospecific binding assay; Materials therefor with an insoluble carrier for immobilising immunochemicals
    • G01N33/54313—Immunoassay; Biospecific binding assay; Materials therefor with an insoluble carrier for immobilising immunochemicals the carrier being characterised by its particulate form
    • G01N33/54326—Magnetic particles

Definitions

  • CTCs are assessed as both live and dead cells, wherein "dead” includes the full range of damaged and fragmented cells as well as CTC-derived debris.
  • the conventional density gradients used in these studies would lose damaged CTC that would be located in the red blood cell (RBC) layer.
  • CTC debris that would be positively stained for cytokeratin may also have densities falling in the RBC, since most intracellular components have densities in the range of 1.15 to 1.3.
  • some damage to intact CTC cells may have occurred during cytospin or subsequent processing.
  • US patent application Ser No. 2005/0181463 describes the analysis of circulating tumor cells in conjunction with circulating clusters, fragments and debris.
  • the application focuses on minimizing in vitro damage to captured cells to assess the clusters, fragments and debris occurring as a consequence of apoptosis, necrosis or damage from the immune response.
  • the application does not consider a specific tumor cell related microparticles (TMP) as indicators of dissemination, based on size and labeled components.
  • TMP tumor cell related microparticles
  • TMPs provide a statistically more accurate and sensitive test in early detection of dissemination, especially when the CTC frequency is on an order below 1 cell per 7.5 ml of blood.
  • Analysis for TMP's can be performed with a number of platforms, including multiparameter flow cytometry, the Cellsearch® system (Veridex, LLC), or any appropriate fluorescent imaging system.
  • Figure 1 Circulating Tumor Cell identified by the CellSearch system.
  • Figure 2 Objects identified as Circulating tumor Cell candidates by the Cellsearch system.
  • the yellow box is 4 ⁇ m x 4 ⁇ m and serves to gauge the minimum size set as criteria for a CTC.
  • Objects 1 and 2 are clear CTCs. The majority of operators will classify objects 3-6 as CTCs and objects 7 and 8 are not classified as CTC. Green is Cytokeratin-PE, Purple is DAPI. Figure 3 Circulating Tumor Cells in 30 ml of blood before surgery of newly diagnosed colorectal cancer.
  • FIG. 4 Cytokeratin PE image of TMP candidates indicated with arrows for a patient (Panel A) and control (Panel B).
  • Figure 6 Kaplan Meier estimates of overall survival of metastatic prostate cancer patients with ⁇ 150 TMP's or >150 TMP's (Panel A) and ⁇ 5 CTCs or > 5 CTCs (Panel B).
  • FIG 10 Three images of the 8 CTC classes. Green represents the Cytokeratin-PE staining and the purple the DAPI staining. The black and white images show the corresponding CD45 staining. All classes except "CK+/CD45+" were CD45 negative. The top panel shows four classes that were assigned during review after the algorithm identified CK+ / DAPI+ events. The bottom panel shows classes assigned during review of CK+ events. For L-TCF the nucleus has to be larger than a 4 ⁇ m square, while for S-TCF the nucleus has to be smaller than a 4 ⁇ m square.
  • CK staining For L-TMP the CK staining has to be larger than 4 ⁇ m square, while for S-TCF the CK staining has to be smaller than a 4 ⁇ m square.
  • CK+/CD45+ are positive in both CK and CD45+ channels.
  • Focus Artifact (FA) images have the appearance of one or more out of focus balls, with a dot (partially) enclosed by a circle.
  • CTC circulating tumor cells
  • the CellSearch system consists of reagent kits, an automated sample preparation device (CellTracks Autoprep®, Veridex LLC) and a semi-automated fluorescence microscope
  • the fluorescence microscope is equipped with a 1OX objective (NA 0.45), a mercury arc lamp, a CCD camera, a computer controlled filter wheel and an X, Y, Z stage.
  • the set up takes a set of images of the DAPI, APC and PE fluorescence intensity that covers the complete surface of the analysis chamber.
  • a computer program is used to identify locations that show both DAPI and PE fluorescence. It presents the images to an operator who decides whether a detected event is a CTC or not, using a standard set of criteria.
  • An image of a CTC with a DAPI stained nucleus, cytoplamic Cytokeratin and no CD45 staining is illustrated in Figure 1.
  • a test volume of 7.5 ml of blood may not contain CTC otherwise present in the blood.
  • the present invention provides for a simple blood test using small tumor-related micro particles (TMP's) found in a patient's blood sample.
  • TMP's tumor-related micro particles
  • the test allows a clinician to rapidly assess treatment and decide whether to stop or change treatment.
  • the test will directly lead to an improvement of the treatment and thus quality of life of the patient. Further, the cost for medical care will be reduced.
  • TMP The enumeration of TMP provides a new system to detect disseminating tumors with a higher sensitivity, specificity and accuracy than CTC enumeration.
  • TMP Tumor cell related microparticles
  • TMP are defined as Cytokeratin+, CD45- and ⁇ 4 ⁇ m
  • application to a CellSearch dataset from a metastatic prostate clinical trial involving patients with no cancer versus metastatic patients with cancer and before initiation of therapy showed a correlation r of 0.66 with a slope of 17 and an intercept of 20 with the number of CTCs in the same patients.
  • Figure 5 shows the frequency of TMP' s and their correlation with CTCs. Thirty seven (37) of 176 patients (21%) had 0 CTCs detected, 27 of the 37 had TMP 's above the intercept suggesting that a substantial portion of the patients with O CTCs can be further subdivided based on their TMP number. The higher the frequency could result in a more sensitivity and accurate test when correlated with clinical outcome.
  • Kaplan Meier plots showed the relationship between TMP 's and survival of the prostate cancer patients. As shown in Figure 6, patients were divided into a Favorable and Unfavorable group using the median of the TMP counts and the presence of 5 or more CTC in a volume of 7.5 ml of blood. The Kaplan Meier plots surprisingly show as good or even better separation of the Favorable and Unfavorable groups when counting TMP 's. While there is a higher background observed in the blood of patients with no cancer, it is expected that this background is in part due to the definition used to count the TMP 's. The present invention considers other definitions, especially relating to size, in the enumeration of TMP's that would correlate with survival.
  • TMP's appear to be very heterogeneous, where some types may have clinical
  • the present invention considers microscopic, spectroscopic and cytometric means for characterizing TMPs and their clinical significance.
  • TMP detection together with patient history, provides a data base for correlating patient outcome and patient survival.
  • the present invention further considers algorithms based on this type of data which could be incorporated into software, designed to count TMP's in patients and provide patient information for clinical use.
  • TMP's While not meaning to limit the scope of the present invention, one hypothesis for the origin of TMP's and their generation is shown in Figure 7.
  • the generation of TMP's begins with an intact CTC having a cytoplasmic membrane, a cytoskeleton containing Cytokeratin and a nucleus containing DNA/RNA (Figure 7 Panel A).
  • the membrane loses its structure and the cytoskeleton and nucleus begin to crumble ( Figure 7 Panel B).
  • TMP's are formed in which portions of the cells are enclosed within pieces of the cell membrane (Figure 7 Panel C).
  • Plasma has been routinely discarded in the Cellsearch system before enrichment with the EpCAM labeled ferrofluids, the complete TMP count may not be determined from a sample taken for only CTC enumeration.
  • Plasma contains microparticles smaller than the TMP's found in the Cellsearch sample.
  • the present invention considers the relationship between the larger and smaller particles.
  • One method to address this is to stain blood from metastatic patients with fluorescently labeled antibodies directed against EpCAM, CDE45 nucleic acid and/or other membrane dyes and compare the two groups using flowcytometry or microscopic examination to provide information on their relationship.
  • a further embodiment of the present invention includes the apparatus for capturing and elucidating TMP.
  • TMP time tolive
  • a 20 fold higher frequency of TMP's compared to CTCs was observed in a preliminary study. Therefore, blood volumes smaller than 1 ml will not be sufficient to yield the numbers of TMPs needed for patient application across all stages of cancers.
  • a flow through device in which the input volume of blood can be varied to optimize the volume needed.
  • ferrofluids labeled with EpCAM for cell capture is one embodiment of the present invention
  • the present invention further considers capturing EpCAM positive events on a solid substrate followed by their release for analysis. An example is shown in Figure 8. Panels A, B, and C depict the making of a bead.
  • the first filter with a pore size of 5 ⁇ m contains approximately 0.25 x 10 6 pores and the released cells are trapped on the filter.
  • EpCAM capture from 7.5 ml of blood from healthy donors is between 500 and 5000 cells captured non-specifically. The excess of pores will avoid clogging of the filter.
  • the second filter with a pore size of 0.5 ⁇ m contains approximately 25 x 10 6 pores and the released TMP's are expected to be trapped on this filter. The captured events on the filters are then fluorescently labeled and examined by fluorescent microscopy.
  • positive identification candidates are fluorescently labeled streptavidin or fluorescently labeled EpCAM (different epitope), membrane dyes such as DiOC, or fluorescently labeled cytokeratins.
  • candidates for negative identification include fluorescently labeled monoclonal antibodies that recognize leukocytes (CD45), platelets (CD41), erythrocytes (CD235a) and endothelial and platelet derived microparticles (CD146, tissue factor).
  • the CellSearch system (Veridex LLC, Raritan, NJ) consists of a CellTracks Autoprep (Veridex LLC, Raritan, NJ) for sample preparation and a CellTracks Analyzer II (Veridex LLC, Raritan, NJ) for sample analysis.
  • the CellTracks Autoprep immunomagnetically enriches epithelial cells from 7.5mL of blood using ferrofluids coated with epithelial cell specific EpCAM antibodies and stain the CTC enriched samples with phycoerythrin conjugated antibodies directed against cytokeratins 8, 18 and 19, an allophycocyanin conjugated antibody to CD45 and the nuclear dye DAPI.
  • the CellTracks Analyzer II is a four color semi-automated fluorescence microscope that captures digital images covering the entire surface of the cartridge for four different fluorescence filter cubes. From the captured images, a gallery of objects meeting pre- determined criteria is automatically presented in a browser for interpretation by a trained operator who makes the final selection of cells. Results of cell enumeration are expressed as the number of cells per 7.5mL of blood. In this study the stored images were used to explore the role of alternative CTC definitions.
  • the automated algorithm in this software was used to identify events in the cytokeratin (CK) and or DAPI images.
  • the algorithm identifies events of at least 9 pixels in size of medium to high contrast in any selected channel. If more than one channel is selected for analysis events must be at least adjacent to each other before the algorithm presents the image to the user.
  • Two sets of analysis were performed where in one set thumbnails of events are presented to the reviewer with staining of both CK and DAPI and in the other set events are presented only staining with CK.
  • the operator reviews thumbnails of all events and is shown the maximum circumference of an event plus a boundary of at least 10 pixels around the event.
  • Monochrome thumbnails show the staining in DAPI, CK, CD45 channels as well as a false color overlay of DAPI and CK to show degree of overlap between channels.
  • the minimum size of the thumbnails is 40x40 pixels (25 ⁇ m 2 ).
  • CTC classes were defined using a training set of 63 samples that did not meet the inclusion criteria of having samples from both baseline and follow-up available. Statistical analysis was performed in SPSS 16.0. CTCs were subdivided into four groups of similar size Thirty-three baseline samples and 30 follow-up samples from the 63 samples were used to set the boundaries for each group on the 25 percentile, the median and the 75 percentile value. If there were more than 50% of samples with 0 events, the data was recoded into three groups. For all classes Kaplan Meier survival plots were generated and Cox regression was performed.
  • Age was included as a continuous variable in all Cox regressions, with a typical CH ratio of 1.02/year with a CI of 1.002 to 1.04 and significance of 0.029 (WaId test). Race, processing site and the time between first diagnosis of tumor and baseline sample were not statistically significant contributors to survival and therefore not included in the Cox regression.
  • the CTC classes were:
  • Intact CTC round or ellipsoid nucleus (DAPI) entirely surrounded by a uniform CK stain at least 4 ⁇ m squared in size and not staining with CD45.
  • DAPI ellipsoid nucleus
  • Granular CTC any shape nucleus connected to CK with at least 3 higher intensity dots, at least 4 ⁇ m squared in size and not staining with CD45.
  • L-TCF Large Tumor Cell Fragment
  • S-TCF Small Tumor Cell Fragment
  • the classes were:
  • L-TMP Large Tumor Micro Particle
  • CK staining area larger than 4 ⁇ m square DAPI + or DAPI-.
  • S-TMP Small Tumor Micro Particle
  • CK staining area smaller than 4 ⁇ m square DAPI + or DAPI-.
  • CK and CD45 positive fragment (CK+/CD45+), any DAPI + or DAPI- fragment that has CK and CD45 signal.
  • FA Focus Artifact
  • the TMP are easy to count, while CellSearch CTC L/S-TCF require the most operator training.
  • the present study shows that a fully automated system to identify CTC/TMP should eliminate the variability in the assignment of objects. CTC/TMP is more easily standardized to develop a fully automated image analysis.

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Abstract

L'invention porte sur des procédés, un appareil et des coffrets qui sont utilisés pour analyser des microparticules liées à une tumeur circulante. Une analyse peut être effectuée avec un certain nombre de plateformes, comprenant une cytométrie de flux ou le système Cellsearch. L'énumération des TMP a été montrée se corréler à un comptage de CPC et, par conséquent, fournir un moyen alternatif pour évaluer une maladie métastasique. En raison de leur fréquence dans le sang par comparaison aux CTC, les TMP fournissent un indicateur plus sensible de la dissémination et un moyen plus spécifique pour surveiller une maladie.
PCT/US2010/039628 2009-06-30 2010-06-23 Analyse de microparticules liées à une tumeur circulante WO2011002649A1 (fr)

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Cited By (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2012135560A1 (fr) * 2011-04-01 2012-10-04 Veridex, Llc Analyses de récepteurs de stéroïdes pour la détection de cellules cancéreuses
WO2013181532A1 (fr) 2012-06-01 2013-12-05 Creatv Microtech, Inc. Capture, identification et utilisation d'un nouveau biomarqueur de tumeurs solides dans des liquides organiques
CN105277697A (zh) * 2015-10-27 2016-01-27 上海芯超生物科技有限公司 一种测定血液中循环上皮肿瘤细胞数量的方法
US9739783B1 (en) 2016-03-15 2017-08-22 Anixa Diagnostics Corporation Convolutional neural networks for cancer diagnosis
US9934364B1 (en) 2017-02-28 2018-04-03 Anixa Diagnostics Corporation Methods for using artificial neural network analysis on flow cytometry data for cancer diagnosis
US10360499B2 (en) 2017-02-28 2019-07-23 Anixa Diagnostics Corporation Methods for using artificial neural network analysis on flow cytometry data for cancer diagnosis
US10871491B2 (en) 2014-08-25 2020-12-22 Creatv Microtech, Inc. Use of circulating cell biomarkers in the blood for detection and diagnosis of diseases and methods of isolating them
CN112730002A (zh) * 2017-03-31 2021-04-30 合度精密生物科技有限公司 使用图像分析识别候选细胞
US11156596B2 (en) 2012-06-01 2021-10-26 Creatv Microtech, Inc. Capture, identification and use of a new biomarker of solid tumors in body fluids
US11164082B2 (en) 2017-02-28 2021-11-02 Anixa Diagnostics Corporation Methods for using artificial neural network analysis on flow cytometry data for cancer diagnosis

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JP2018021934A (ja) * 2011-04-01 2018-02-08 ヤンセン・ダイアグノスティックス・エルエルシーＪａｎｓｓｅｎ Ｄｉａｇｎｏｓｔｉｃｓ， ＬＬＣ 腫瘍細胞を検出するためのステロイド受容体アッセイ
WO2012135560A1 (fr) * 2011-04-01 2012-10-04 Veridex, Llc Analyses de récepteurs de stéroïdes pour la détection de cellules cancéreuses
CN103608681A (zh) * 2011-04-01 2014-02-26 詹森诊断器材有限责任公司 用于检测肿瘤细胞的类固醇受体测定
JP2018138042A (ja) * 2012-06-01 2018-09-06 クリエイティブ マイクロテック インコーポレイテッドＣ 体液中の固形腫瘍の新たなバイオマーカーの捕獲、特定及び使用
US10247725B2 (en) 2012-06-01 2019-04-02 Creatv Microtech Inc. Capture, identification and use of a new biomarker of solid tumors in body fluids
EP2855663A4 (fr) * 2012-06-01 2016-04-06 Creatv Microtech Inc Capture, identification et utilisation d'un nouveau biomarqueur de tumeurs solides dans des liquides organiques
US11156596B2 (en) 2012-06-01 2021-10-26 Creatv Microtech, Inc. Capture, identification and use of a new biomarker of solid tumors in body fluids
JP2015523559A (ja) * 2012-06-01 2015-08-13 クリエイティブ マイクロテック インコーポレイテッドＣ 体液中の固形腫瘍の新たなバイオマーカーの捕獲、特定及び使用
AU2013267253B2 (en) * 2012-06-01 2018-03-29 Creatv Microtech, Inc. Capture, identification and use of a new biomarker of solid tumors in body fluids
EP3400996A1 (fr) * 2012-06-01 2018-11-14 Creatv Microtech, Inc. Capture, identification et utilisation d'un nouveau biomarqueur de tumeurs solides dans des fluides corporels
WO2013181532A1 (fr) 2012-06-01 2013-12-05 Creatv Microtech, Inc. Capture, identification et utilisation d'un nouveau biomarqueur de tumeurs solides dans des liquides organiques
US10871491B2 (en) 2014-08-25 2020-12-22 Creatv Microtech, Inc. Use of circulating cell biomarkers in the blood for detection and diagnosis of diseases and methods of isolating them
JP2021170012A (ja) * 2014-08-25 2021-10-28 クリエイティブ マイクロテック インコーポレイテッドCreatv Microtech, Inc. 疾患の検出及び診断のための血液中の循環細胞バイオマーカーの使用並びにそれらを単離する方法
JP7215805B2 (ja) 2014-08-25 2023-01-31 クリエイティブ マイクロテック インコーポレイテッド 疾患の検出及び診断のための血液中の循環細胞バイオマーカーの使用並びにそれらを単離する方法
CN105277697A (zh) * 2015-10-27 2016-01-27 上海芯超生物科技有限公司 一种测定血液中循环上皮肿瘤细胞数量的方法
US9739783B1 (en) 2016-03-15 2017-08-22 Anixa Diagnostics Corporation Convolutional neural networks for cancer diagnosis
US9934364B1 (en) 2017-02-28 2018-04-03 Anixa Diagnostics Corporation Methods for using artificial neural network analysis on flow cytometry data for cancer diagnosis
US10360499B2 (en) 2017-02-28 2019-07-23 Anixa Diagnostics Corporation Methods for using artificial neural network analysis on flow cytometry data for cancer diagnosis
US11056236B2 (en) 2017-02-28 2021-07-06 Anixa Diagnostics Corporation Methods for using artificial neural network analysis on flow cytometry data for cancer diagnosis
US11164082B2 (en) 2017-02-28 2021-11-02 Anixa Diagnostics Corporation Methods for using artificial neural network analysis on flow cytometry data for cancer diagnosis
CN112730002A (zh) * 2017-03-31 2021-04-30 合度精密生物科技有限公司 使用图像分析识别候选细胞

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