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Method of using non-rare cells to detect rare cells

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Method of using non-rare cells to detect rare cells

The invention provides seminal computational approaches utilizing data from non-rare cells to detect rare cells, such as circulating tumor cells (CTCs). The invention is applicable at two distinct stages of CTC detection; the first being to make decisions about data collection parameters and the second being to make decisions during data reduction and analysis. Additionally, the invention utilizes both one and multi-dimensional parameterized data in a decision making process.
Related Terms: Circulating Tumor Cells

Inventors: Peter Kuhn, Anand Kolatkar, Joshua Kunken, Dena Marrinucci, Xing Yang, John R. Stuelpnagel
USPTO Applicaton #: #20120276555 - Class: 435 723 (USPTO) - 11/01/12 - Class 435 
Chemistry: Molecular Biology And Microbiology > Measuring Or Testing Process Involving Enzymes Or Micro-organisms; Composition Or Test Strip Therefore; Processes Of Forming Such Composition Or Test Strip >Involving Antigen-antibody Binding, Specific Binding Protein Assay Or Specific Ligand-receptor Binding Assay >Involving A Micro-organism Or Cell Membrane Bound Antigen Or Cell Membrane Bound Receptor Or Cell Membrane Bound Antibody Or Microbial Lysate >Animal Cell >Tumor Cell Or Cancer Cell

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The Patent Description & Claims data below is from USPTO Patent Application 20120276555, Method of using non-rare cells to detect rare cells.

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1. Field of the Invention

The invention relates generally to medical diagnostics and more specifically to detection and categorization of rare cells, such as circulating tumor cells (CTCs).

2. Background Information

Significant unmet medical need exists for the longitudinal disease monitoring in patients with epithelial cancers at the cellular level. Predicting and monitoring therapy response and disease progression are particularly important in epithelial cancer patients due to the natural history of the disease and the selective selection process in response to the therapeutic pressure. While progress has been made in understanding the primary and metastatic tumors in their respective microenvironments, a substantial barrier exists in understanding carcinoma behavior during the fluid phase, as it spreads within and occupies the bloodstream. The circulating component of cancer contains within it the cells giving rise to future metastases, and as such, represents a compelling target for investigation.

Research to fully characterize the clinical significance of this fluid phase of solid tumors has been hindered by the lack of easily accessible and reliable experimental tools for the identification of CTCs. The unknown character and low and unknown frequency of CTCs in the blood, combined with the difficulty of distinguishing between cancerous versus normal epithelial cells, has significantly impeded research into how the fluid phase might be clinically important. The ideal fluid phase biopsy should find significant numbers of a specific CTC population in most epithelial cancer patients and preserve and present CTCs to a pathologist and/or researcher in a format that enables not only enumeration but further molecular, morphologic and/or phenotypic analysis. In addition, it should preserve the remaining rare populations for further analysis.

CTCs are generally, although not exclusively, epithelial cells that originate from a solid tumor in very low concentration and enter into the blood stream of patients with various types of cancer. CTCs are also thought to be capable of originating in the blood, forming small colonies throughout the body. The shedding of CTCs by an existing tumor or metastasis often results in formation of secondary tumors. Secondary tumors typically go undetected and lead to 90% of all cancer deaths. Circulating tumor cells provide the link between the primary and metastatic tumors. This leads to the promise of using the identification and characterization of circulating tumor cells for the early detection and treatment management of metastatic epithelial malignancies. Detection of CTCs in cancer patients offers an effective tool in early diagnosis of primary or secondary cancer growth and determining the prognosis of cancer patients undergoing cancer treatment because number and characterization of CTCs present in the blood of such patients has been correlated with overall prognosis and response to therapy. Accordingly, CTCs serve as an early indicator of tumor expansion or metastasis before the appearance of clinical symptoms.

While the detection of CTCs has important prognostic and potential therapeutic implications in the management and treatment of cancer, because of their occult nature in the bloodstream, these rare cells are not easily detected. CTCs were first described in the 1800s, however only recent technological advances have allowed their reliable detection. The challenge in the detection of circulating tumor cells is that they are present in relatively low frequency compared to other nucleated cells, commonly less than 1:100,000. To compensate for this challenge, most conventional approaches for detecting circulating tumor cells rely on experimental enrichment methods, whereby the CTCs are preferentially separated from the other cellular components (e.g., non-CTCs), most importantly other nucleated cells that are the most similar to CTCs.

Currently, the most utilized methods of positive enrichment for enumeration/characterization of CTCs are immunomagnetic enrichment methods targeting the surface protein EpCAM and the “CTC chip”. The most widely used methodology to detect CTCs, J&J\'s Veridex technology, utilizes immunomagnetic enrichment. The technology relies upon immunomagnetic enrichment of tumor cell populations using magnetic ferrofluids linked to an antibody which binds epithelial cell adhesion molecule (EpCAM), expressed only on epithelial derived cells. This methodology requires 7.5 mL of blood for analysis and finds greater than 2 CTCs in only some metastatic cancer patients.

Microfluidic or “CTC-Chip” technology, is another positive enrichment method for enumeration/characterization of CTCs. The methods utilizes 1-3 mL of blood in which whole blood flows past 78,000 EpCAM-coated microposts. EpCAM+ cells stick to the posts and are subsequently stained with cytokeratin, CD45, and DAPI. With this methodology, CTCs are found in virtually all metastatic cancer patients at a relatively high purity and not in healthy controls. Additionally, CTC-chip technology identifies CTCs in all patients and in higher numbers than other technologies by a factor of approximately 10 to 100 fold as reported in two recent publications.

The only routinely used technology for CTC detection is based on immunomagnetic enrichment. This current “gold standard” and FDA approved test is called CellSearch® and employs an immunomagnetic enrichment step to isolate cells that express the epithelial cells adhesion molecule (EpCAM). Additionally, to be identified as a CTC, the cell must contain a nucleus, express cytoplasmic cytokeratin, and have a diameter larger than five microns. This system has uncovered the prognostic utility of enumerating and monitoring CTC counts in patients with metastatic breast, prostate, and colorectal cancers; however, the sensitivity of this system is low, finding no or few CTCs in most patients. Most follow-on CTC technologies have reported higher sensitivity and are pursuing variations of the enrichment strategy, however this directly biases the detectable events towards those that have sufficient expression of the protein selected for the initial enrichment step.

A standardized microscope based approach has also been previously utilized to identify and morphologically characterize and credential CTCs in case studies of breast, colorectal, and lung cancer patients.

Although many CTC detection approaches are currently in use, significant limitations have been identified with the current approaches. For example, one significant limitation of positive selection methods to enumerate/characterize CTCs is that positive physical selection invariably leads to loss of CTCs and is less than 100% efficient. Thus the number of CTCs detected per sample using current methods is often too low to provide robust interpretation or clinically meaningful content of a particular sample. Additional limitations of current methods include low CTC detection due to CTC heterogeneity. For example, differences in individual CTC features within the CTC population of interest further hinder the number of CTCs detected using current methodologies. Such differences may include size variations between individual CTCs, and variable or down regulated expression between individual CTCs of the cell surface markers used to detect CTCs. A further limitation of existing methodologies includes limitations in purity levels and variable purity. Any enrichment will have a certain number of false positives, for instance other nucleated blood cells that stick to the enrichment. For example, the Veridex magnet has typically 5,000 to 10,000 false positives on top of the 5 to 10 positives.



The present invention is based in part on the discovery of innovative methods for analyzing samples to detect, enumerate and characterize rare cells, such as CTCs. Accordingly, the present invention provides methods for improved detection and characterization allowing for clinically meaningful analysis of samples for use in clinical, research and development settings.

Accordingly, the present invention provides methods for the improved detection and characterization of rare cells in a sample by utilizing data from non-rare cells (cells present at a concentration of 10, 50, 100, 200, 300, 400, 500, 1,000, 5,000, 10,000 times or greater as compared to the rare cell) in the sample. Thus the method of the invention utilizes similarity measures to assess non-similarity of cells, requiring both the biggest distance exclusion, e.g., events that are clearly non-rare cell related and the fine distinction of a cutoff based on similarities of surrounding non-rare cells.

The method includes providing a sample suspected of having at least one rare cell and at least one cell that is present at a concentration that is at least 10 times that of the rare cell; contacting the sample with at least one detectable agent, such as an agent that binds a cell marker; performing cell imaging on the sample to generate an image; and detecting the at least one rare cell as compared with other cells in the sample by analyzing the cell from the image, thereby detecting the rare cell in the sample. In various aspects of the invention, the method further includes plating of the suspected rare cell and at least one cell on a solid support, such as a slide, to facilitate contacting the cells with the detectable agent and cell imaging. In various aspects of the invention, the detectable agent is any agent used to stain the cells, such as an agent that binds a cell marker, including, but not limited to, a positive marker, negative marker, nuclear marker, content marker, or any combination thereof.

In various aspects of the invention, the methods described herein are performed on an apparatus for efficiently imaging a slide containing a detectable signal, such as a fluorescent signal. The apparatus may typically include a computer having at least one system processor with image processing capability, a computer monitor, an input device, a power supply and a microscope subsystem. Thus the apparatus includes a computer having executable code for performing the various analysis required to practice the invention. The microscope subsystem includes an optical sensing array for acquiring images. A two-dimensional motion stage for sample movement and for focus adjustment, and input and output mechanisms for multiple sample analysis and storage. The apparatus may also include a transmitted light source as well as an illuminating/fluorescent excitation light source for fluorescing samples.

In one embodiment of the invention, the method includes establishing optimal exposure limits for performing the cell imaging that facilitate detection of rare cells present. In one aspect, the exposure limit for the detectable agent is determined using a signal from at least one cell. In various aspects, the detectable marker may be a positive marker, negative marker, nuclear marker or content marker. In a related aspect, the exposure limits may be set using data relating to the cells and/or suspected rare cells gathered from a first image, to re-image the slide.

In another embodiment, the method includes minimizing exposure settings to minimize data collection time and maximize throughput to facilitate detection of rare cells.

In another embodiment, the method includes utilizing data associated with non-rare cells to generate a quality control parameter that facilitates detection of rare cells. In various aspects, the quality control parameter is distribution of at least one non-rare cell on the slide, alignment of multiple cell images via alignment of non-rare cell markers, quality of cell staining, distribution of a positive marker throughout the non-rare cells, or cell loss from repeated processing.

In another embodiment, the method includes determining intensity cut-off limits to minimize false negatives, as well as false positives and to facilitate rare cell detection. In one aspect, the detectable agent is a positive marker and the intensity limits are determined using mean, standard deviation, coefficient of variation, other statistical parameters or any combination thereof, for a background signal of the positive marker. In another aspect, the detectable agent is a positive marker and the intensity limits are determined within a single image, or portions of that image, by identifying the highest signal event from a positive marker and comparing the highest signal to the mean and standard deviation calculated from signals of all, or a subset of events. In yet another aspect, the detectable agent is a negative marker and the intensity limit for the negative marker is determined using mean and standard deviation of signals from the negative markers from non-rare cells (either all non-rare cells or a specific subset).

In another embodiment, cytological features of non-rare cells, such as cellular and nuclear size (absolute and relative; overall and apparent) and distribution, are utilized to facilitate detection of non-rare cells.

In another embodiment, the method includes utilizing data associated with non-rare cells to enumerate rare cells, thus facilitating their detection. In various embodiments, data may include, but is not limited to, total intensity, mean intensity, segmented intensity, fixed circle, variable circle, or any combination thereof.

In another embodiment, the method includes determination of the expression level of a content marker in rare cells and non-rare cells to facilitate detection of rare cells.

In various aspects of the invention, a rare cell is a CTC or subpopulation thereof.

As such, in another embodiment, the invention provides a method for diagnosing or prognosing cancer in a subject. The method includes performing the method of improved detection and characterization of CTCs as described herein and analyzing detected CTCs and provide a diagnosis or prognosis based on analysis of the CTCs, thereby diagnosing or prognosing cancer in a subject.

In another embodiment, the invention provides a method for determining responsiveness of a subject to a therapeutic regime. The method includes performing the method of improved detection and characterization of CTCs as described herein and analyzing the CTCs, thereby determining the responsiveness of the subject to a therapeutic regime.

In another embodiment, the invention provides a method for determining a candidate subject for a clinical trial. The method includes performing the method of improved detection and characterization of CTCs as described herein and analyzing the CTCs, thereby determining a candidate subject for a clinical trial.


FIG. 1 is a graphical representation of mean observed SKBR3s plotted against expected SKBR3s. Four aliquots of normal control blood were spiked with varying numbers of SKBR2 cells to produce 4 slides with approximately 10, 30, 100, and 300 cancer cells per slide. The mean of each quadruplicate is displayed as well as error bars noting standard deviation.

FIG. 2 is a pictorial representation of a gallery of a representative subpopulation of CTCs found in cancer patients. Each CTC of the subpopulation is cytokeratin positive, CD45 negative, contains a DAPI nucleus, and is morphologically distinct from surrounding white blood cells which are circular in shape.

FIG. 3 is a graphical representation comparing CTC counts between two separate processors on 9 different cancer patient samples. CTC/mL counts ranged from 0 to 203.

FIG. 4 is a graphical representation including four graphs plotting CTC and PSA levels of serial blood draws from 4 different prostate cancer patients over a three month time period. Two patients had increasing CTC and PSA levels and two patients had decreasing/stable CTC and PSA levels. PSA levels increased in patients that had increasing CTC counts and decreased in patients that had decreasing/stable CTC counts.

FIG. 5 is a graphical representation showing the incidence rate of a putative rare cell population across patients relative to a CTC subpopulation (HD-CTC).



The present invention provides a method which omits physical methods for positively enriching for rare cells, such as CTCs, from a mixed population, thereby minimizing the loss of rare cells. This methodology further allows for the capture/identification of subsets of cell populations, such as subpopulations of CTCs or other rare populations by detection of the same or different markers using different parameters, such as cutoff values, that allow for distinguishing between events and non-events. For example, as discussed in detail herein, different cutoffs may be utilized to characterize different cell subpopulations.

While the disclosure highlights CTCs and subpopulations thereof, the same methodologies may be used to find any other rare cell type in a background of non-rare cells. As used herein, a “rare cell” is intended to include a cell that is either 1) of a cell type that is less than about 5%, 4%, 3%, 2%, 1%, 0.1%, 0.01% or 0.001% of the total nucleated cell population in a fluid sample, or 2) of a cell type that is present at less than one million cells per milliliter of fluid sample. Exemplary rare cells include, but are not limited to CTCs, circulating endothelial cells (CECs), white blood cells in emboli, cancer stem cells, activated or infected cells, such as activated or infected blood cells, and fetal cells.

Accordingly, it will be understood by one in the art that references to CTCs throughout the specification include reference to rare cells and vice versa.

The present method allows for identification of rare cells, such as CTCs or subpopulations of CTCs from the background of other blood cells using microscopy, cytometry, automation, and computation. The present invention utilizes these components, individually and collectively, to identify rare cells. The benefits include the ability to find more rare cells, to present them in a way that enables subsequent analyses for content markers, and to do so in a time and resource efficient manner.

Further, the present disclosure is based in part on a next generation assay capable of identifying subpopulations of CTCs in cancer patients. One particular subpopulation identified was from a small cohort of cancer patients. In addition to using specific parameters defining subpopulations of CTCs, such as one referred to herein as the High-Definition-CTC (HD-CTC) subpopulation, the assay affords greater sensitivity with a smaller volume of blood than previous efforts. The key innovative aspects of this assay are driven by the need for simplicity and minimal processing of the blood specimen as well as conforming to the need to enable professional interpretation with diagnostic quality imagery.

The approach used to identify a rare cell population, such as CTCs, or subpopulation thereof, is distinct in that it does not rely on any single protein enrichment strategies. All nucleated blood cells are imaged in multiple colors to locate and morphologically evaluate rare events. This enrichment-free strategy results in an assay capable of ‘tunable specificity/sensitivity’ allowing high sensitivity and high specificity while still enabling the study of a rare cell population known to be heterogeneous. A key advantage and difference to physical enrichment is that one may ‘tune’ the outcome, while physical enrichment is ‘yes’ or ‘no’. Another key advantage of this approach is that one or multiple analysis parameters can be pursued to identify and characterize specific populations of interest.

Before the present compositions and methods are described, it is to be understood that this invention is not limited to particular compositions, methods, and experimental conditions described, as such compositions, methods, and conditions may vary. It is also to be understood that the terminology used herein is for purposes of describing particular embodiments only, and is not intended to be limiting, since the scope of the present invention will be limited only in the appended claims.

As used in this specification and the appended claims, the singular forms “a”, “an”, and “the” include plural references unless the context clearly dictates otherwise. Thus, for example, references to “the method” includes one or more methods, and/or steps of the type described herein which will become apparent to those persons skilled in the art upon reading this disclosure and so forth.

Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Although any methods and materials similar or equivalent to those described herein can be used in the practice or testing of the invention, the preferred methods and materials are now described.

In general, reference to “a circulating tumor cell” is intended to refer to a single cell, while reference to “circulating tumor cells” or “cluster of circulating tumor cells” is intended to refer to more than one cell. However, one of skill in the art would understand that reference to “circulating tumor cells” is intended to include a population of circulating tumor cells including one or more circulating tumor cells.

The term “circulating tumor cell” (CTC) or CTC “cluster” is intended to mean any cancer cell or cluster of cancer cells that is found in a subject\'s sample. Typically CTCs have been exfoliated from a solid tumor. As such, CTCs are often epithelial cells shed from solid tumors found in very low concentrations in the circulation of patients with advanced cancers. CTCs may also be mesothelial from sarcomas or melanocytes from melanomas. CTCs may also be cells originating from a primary, secondary, or tertiary tumor. CTCs may also be circulating cancer stem cells. While the term “circulating tumor cell” (CTC) or CTC “cluster” includes cancer cells, it also is intended to include non-tumor cells that are not commonly found in circulation, for example, circulating epithelial or endothelial cells. Accordingly tumor cells and non-tumor epithelial cells are encompassed within the definition of CTCs.

The term “cancer” as used herein, includes a variety of cancer types which are well known in the art, including but not limited to, dysplasias, hyperplasias, solid tumors and hematopoietic cancers. Many types of cancers are known to metastasize and shed circulating tumor cells or be metastatic, for example, a secondary cancer resulting from a primary cancer that has metastasized. Additional cancers may include, but are not limited to, the following organs or systems: brain, cardiac, lung, gastrointestinal, genitourinary tract, liver, bone, nervous system, gynecological, hematologic, skin, breast, and adrenal glands. Additional types of cancer cells include gliomas (Schwannoma, glioblastoma, astrocytoma), neuroblastoma, pheochromocytoma, paraganlioma, meningioma, adrenalcortical carcinoma, medulloblastoma, rhabdomyoscarcoma, kidney cancer, vascular cancer of various types, osteoblastic osteocarcinoma, prostate cancer, ovarian cancer, uterine leiomyomas, salivary gland cancer, choroid plexus carcinoma, mammary cancer, pancreatic cancer, colon cancer, and megakaryoblastic leukemia; and skin cancers including malignant melanoma, basal cell carcinoma, squamous cell carcinoma, Karposi\'s sarcoma, moles dysplastic nevi, lipoma, angioma, dermatofibroma, keloids, sarcomas such as fibrosarcoma or hemangiosarcoma, and melanoma.

Using the methods described herein, rare cells, such as CTCs may be detected and characterized from any suitable sample type. As used herein, the term “sample” refers to any sample suitable for the methods provided by the present invention. The sample may be any sample that includes rare cells suitable for detection. Sources of samples include whole blood, bone marrow, pleural fluid, peritoneal fluid, central spinal fluid, urine, saliva and bronchial washes. In one aspect, the sample is a blood sample, including, for example, whole blood or any fraction or component thereof. A blood sample, suitable for use with the present invention may be extracted from any source known that includes blood cells or components thereof, such as veinous, arterial, peripheral, tissue, cord, and the like. For example, a sample may be obtained and processed using well known and routine clinical methods (e.g., procedures for drawing and processing whole blood). In one aspect, an exemplary sample may be peripheral blood drawn from a subject with cancer.

The term “blood component” is intended to include any component of whole blood, including red blood cells, white blood cells, platelets, endothelial cells, mesotheial cells or epithelial cells. Blood components also include the components of plasma, such as proteins, lipids, nucleic acids, and carbohydrates, and any other cells that may be present in blood, due to pregnancy, organ transplant, infection, injury, or disease.

As used herein, a “white blood cell” is a leukocyte, or a cell of the hematopoietic lineage that is not a reticulocyte or platelet. Leukocytes can include nature killer cells (“AK cells”) and lymphocytes, such as B lymphocytes (“B cells”) or T lymphocytes (“T cells”). Leukocytes can also include phagocytic cells, such as monocytes, macrophages, and granulocytes, including basophils, eosinophils and neutrophils. Leukocytes can also comprise mast cells.

As used herein, a “red blood cell” or “RBC” is an erythrocyte. Unless designated a “nucleated red blood cell” (“nRBC”) or “fetal nucleated red blood cell”, as used herein, “red blood cell” is used to mean a non-nucleated red blood cell.

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Circulating Tumor Cells

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