Abstract: 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.

Abstract: The disclosure provides methods for analyzing rare circulating cells (RCCs) at cellular and molecular level following their detection in non-enriched blood samples, methods of this disclosure serve as diagnostic methods for several disease conditions, including cardiovascular diseases and cancer.

Abstract: 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.

Abstract: The disclosure provides methods for analyzing rare circulating cells (RCCs) at cellular and molecular level following their detection in non-enriched blood samples, methods of this disclosure serve as diagnostic methods for several disease conditions, including cardiovascular diseases and cancer.

Abstract: The present invention describes a method for detecting castration-resistant prostate cancer (CRPC) in a patient afflicted with prostate cancer comprising (a) performing a direct analysis comprising immunofluorescent staining and morphological characterization of nucleated cells in a blood sample obtained from the patient to detect circulating tumor cells (CTC), (b) determining prevalence of a CTC subpopulation associated with CRPC comprising detecting a measurable feature of each biomarker in a panel of morphological and protein biomarkers, and (c) comparing the prevalence of said CTC subpopulation to a predetermined threshold value, wherein the prevalence of the CTC subpopulation associated with CRPC above said predetermined threshold value is indicative of CRPC. In some embodiments, the CTC subpopulation associated with CRPC comprises CK? CTCs. In some embodiments, the CTC subpopulation associated with CRPC comprises small CTCs.

Abstract: Methods are provided for detecting 5T4-positive circulating tumor cells in a mammalian subject. Methods of diagnosing 5T4-positive cancer in a mammalian subject are provided. The methods of detection or diagnosis indicate the presence of 5T4-positive metastatic cancer or early stage 5T4-positive cancer.

Abstract: The disclosure provides a method of predicting de novo resistance to androgen receptor (AR) targeted therapy in a tumor of a prostate cancer patient comprising (a) performing a direct analysis comprising immunofluorescent staining and morphological characteristization of nucleated cells in a blood sample obtained from the patient to generate circulating tumor cell (CTC) data, wherein the analysis comprises determining a measurable feature of a panel of traditional and non-traditional CTC biomarkers for de novo resistance to androgen receptor (AR) targeted therapy, and (b) evaluating the CTC data to determine the probability of de novo resistance to the AR targeted therapy in the tumor of the prostate cancer patient. Further disclosed are the panel of traditional and non-traditional CTC biomarkers for the methods.

Abstract: The present application provides methods for obtaining single cells from a sample. Methods for isolating and analyzing molecular features obtained from a single cell are also disclosed herein. For example, individual circulating tumor cells (CTCs) from a sample such as a patient's blood sample can be identified and obtained using methods disclosed herein, and picked for further analysis.