248 results about "Hematological sample" patented technology

Described here is an automated robotic device that isolates circulating tumor cells (CTCs) or other biological structures with extremely high purity. The device uses powerful magnetic rods covered in removable plastic sleeves. These rods sweep through blood samples, capturing, e.g., cancer cells labeled with antibodies linked to magnetically responsive particles such as superparamagnetic beads. Upon completion of the capturing protocol, the magnetic rods undergo several rounds of washing, thereby removing all contaminating blood cells. The captured target cells are released into a final capture solution by removing the magnetic rods from the sleeves. Additionally, cells captured by this device show no reduced viability when cultured after capture. Cells are captured in a state suitable for genetic analysis. Also disclosed are methods for single cell analysis. Being robotic allows the device to be operated with high throughput.

1. A method for classifying and counting leukocytes, which comprises:(1) a step of staining cells in a sample obtained from a hematological sample by treatment with a hemolytic agent, with a fluorescent dye;(2) a step of introducing the sample containing the stained cells into a flow cytometer to measure first scattered light, second scattered light different from the first scattered light and fluorescence of the respective cells;(3) a step of obtaining scattered light peak intensities and scattered light widths of the respective cells based on the measured first scattered light, obtaining scattered light intensities of the respective cells based on the measured second scattered light, and obtaining fluorescece intensities of the respective cells based on the measured fluorescence light;(4) a step of classifying the cells into a first group and a second group based on the scattered light peak intensities and the scattered light widths, the first group including leukocytes and second group including platelet clumps;(5) a step of classifying the leukocytes included in the first group into at least lymphocytes, monocytes and granulocytes based on the scattered light intensities and the fluorescence intensities; and(6) a step of counting the classified lymphocytes, the classified monocytes and the classified granulocytes.

Methods using mass spectral data analysis and a classification algorithm provide an ability to determine whether a non-small-cell lung cancer patient, head and neck squamous cell carcinoma or colorectal cancer patient has likely developed a non-responsiveness to treatment with a drug targeting an epidermal growth factor receptor pathway. As the methods of this disclosure require only simple blood samples, the methods enable a fast and non-intrusive way of measuring when drugs targeting the EGFR pathway cease to be effective in certain patients. This discovery represents the first known example of true personalized selection of these types of cancer patients for treatment using these classes of drugs not only initially, but during the course of treatment.