Patient classification

Details Patient classification Patient classification

2001-09-13

2004-07-13

Brusca, John S. (Department: 1631)

Data processing: measuring, calibrating, or testing

Measurement system in a specific environment

Biological or biochemical

C435S006120, C435S007100, C435S007240

Reexamination Certificate

active

06763307

ABSTRACT:

BACKGROUND OF THE INVENTION
In disease, as in health, there is a complex and changing cast of cells playing different roles. Functional capabilities of these cells can be altered, depending on the course of disease; as a result of underlying genetic differences; or due to drug exposure or other treatments. Even cancers, sometimes characterized as simple overgrowths of a single cell type, frequently show progression from one cell type to another. For example, in cancers of the breast and prostate there is a clear distinction between the steroid dependent and steroid independent cells, where the latter can emerge from the course of drug treatments. Similarly, the use of chemotherapeutics can select for resistant tumor cells, which are then able to persist through treatment. In other diseases, such as degenerative diseases, the loss of specific cell types is observed. For example, a key indicator of the severity of diabetes is the number of functioning islet cells that remain.
Apart from these diseased cells, normal cells in the body may be present, including the mobile cells of the immune system and angiogenic cells of the vascular system. Inflammatory diseases, as well as responses to infections, tumors and the like, are characterized by the presence of a variety of leukocytes, including B cells, T cells, polymorphonuclear cells (eosinophils, basophils and neutrophils), macrophages, natural killer cells, megakaryocytes, and the like. Even within one of these groups, there can be substantial variation in the function of the involved cells, for example a Th1 type T cells and a Th2 type T cells can have opposite effects on the course of a disease; and genetic and environmental effects can determine the onset and course of T cell-mediated diseases.
Angiogenesis is a process critical to both tumor growth and metastasis, and can be characterized by the presence of functionally distinct endothelial cells, which can vary in their responsiveness to cytokines and other growth and regulatory factors. Although angiogenesis is a continuous process, different consecutive steps can be identified, including release of pro-angiogenic factors and proteolytic enzymes, and endothelial cell migration, morphogenesis and proliferation. Under normal circumstances, the microvasculature is maintained in a quiescent state. The acquisition of the angiogenic phenotype depends on the outcome of stimulatory and inhibitory regulation by the tumur and its microenvironment, features which are modified by genetic differences.
In addition to the development and localization of cells, there is also genotypic variation, which can have important ramifications in an individuals response to therapy. Pharmacogenetics seeks to determine the linkage between an individual's genotype and that individual's ability to metabolize or react to a therapeutic agent. The use of pharmacogenetics is reviewed in
Annu Rev Pharmacol Toxicol
(2001);41:101-121. Differences in metabolism or target sensitivity can lead to severe toxicity or therapeutic failure by altering the relation between bioactive dose and blood concentration of the drug. However, given the complex networks of interacting elements that confer an individuals responses to environmental or therapeutic or pathologic influences, simply predicting responses from genotype may be difficult. Thus, more direct means of assessing relevant patient phenotypes are required.
A need exists for methods that give detailed information about the “physiotype”, embodying cellular events that occur in response to differences in cell's genetic makeup, changes in a cell, its environment, and other events that influence the biology of the host. The present invention satisfies this need and provides additional advantages.
Related Literature
Cell based assays include a variety of methods to measure metabolic activities of cells including: uptake of tagged molecules or metabolic precursors, receptor binding methods, incorporation of tritiated thymidine as a measure of cellular proliferation, uptake of protein or lipid biosynthesis precursors, the binding of radiolabeled or otherwise labeled ligands; assays to measure calcium flux, and a variety of techniques to measure the expression of specific genes or their gene products.
Compounds have also been screened for their ability to inhibit the expression of specific genes in gene reporter assays. For example, Ashby et al. U.S. Pat. No. 5,569,588; Rine and Ashby U.S. Pat. No. 5,777,888 describe a genome reporter matrix approach for comparing the effect of drugs on a panel of reporter genes to reveal effects of a compound on the transcription of a spectrum of genes in the genome.
Methods utilizing genetic sequence microarrays allow the detection of changes in expression patterns in response to stimulus. A few examples include U.S. Pat. No. 6,013,437; Luria et al., “Method for identifying translationally regulated genes”; U.S. Pat. No. 6,004,755, Wang, “Quantitative microarray hybridization assays”; and U.S. Pat. No. 5,994,076, Chenchik et al., “Methods of assaying differential expression”. U.S. Pat. No. 6,146,830, Friend et al. “Method for determining the presence of a number of primary targets of a drug”.
Proteomics techniques have potential for application to pharmaceutical drug screening.
These methods require technically complex analysis and comparison of high resolution two-dimensional gels or other separation methods, often followed by mass spectrometry (for reviews see Hatzimanikatis et al. (1999)
Biotechnol Prog
15(3):312-8; Blackstock et al. (1999)
Trends Biotechnol
17(3):121-7. A discussion of the uses of proteomics in drug discovery may be found in Mullner et al. (1998)
Arzneimittelforschung
48(1):93-5.
SUMMARY OF THE INVENTION
Methods and compositions are provided for the classification of clinical samples, e.g. patient tissue samples, according to the physiological status of cells or constituents present in the sample. The information thus derived is useful in prognosis and diagnosis, and can further be used develop surrogate markers for disease states, and to investigate the effect of genetic polymorphisms in the responsiveness and state of cells involved in disease. In some embodiments of the invention, such cells are classified according to their ability to respond to therapeutic agents and treatments. In other embodiments, the cells are classified according to their status with respect to the activity of pathways of interest. In another embodiment, patient tissue samples are evaluated for the presence of biologically active molecules, e.g. secreted factors and the like, by adding the patient sample to a cell culture responsive to the molecules.
Patient samples are cultured in a panel of environments, where each environment can comprise combinations of factors, cells and therapeutically active agents. Generally at least one environment contains multiple factors that affect pathways of interest. The effect of altering the culture environment is assessed by monitoring multiple output parameters. The cells may also be treated with therapeutic agents in the presence or absence of factors, and the profile of output parameters determined. A sufficient number of markers are selected to provide a high confidence level that the pathways of interest are being monitored. When factors are employed, a sufficient number of factors are used to involve one or a plurality of pathways and a sufficient number of markers are determined to insure the cellular status is accurately being monitored.


REFERENCES:
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patent: 5631153 (1997-05-01), Capecchi et al.
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patent: 5994076 (1999-11-01), Chenchik et al.
patent: 6004755 (1999-12-01), Wang
patent: 6013437 (2000-01-01), Luria et al.
patent: 6146830 (2000-11-01), Friend et al.
patent: 6656695 (2003-12-01), Berg et al.
Altschul et al. , Issues in Searching Molecular Sequence Databases. Nature Genetics, vol. 6, pp. 119-129 (1994).*
Blackstock et al. Proteomics: Q

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