Single cell gene expression for diagnosis, prognosis and identification of drug targets

• US 9,329,170 B2
• Filed: 01/20/2010
• Issued: 05/03/2016
• Est. Priority Date: 01/20/2009
• Status: Expired due to Fees

• Current Assignee: Board of Trustees of the Leland Stanford Junior University (Stanford Management Co.)
• Original Assignee: Board of Trustees of the Leland Stanford Junior University (Stanford Management Co.)
• Inventors: Clarke, Michael F., Quake, Stephen R., Dalerba, Piero D., Liu, Huiping, Leyrat, Anne, Kalisky, Tomer, Diehn, Maximilian, Wang, Jianbin
• Primary Examiner(s): Hibbert, Catherine S
• Application Number:
  US12/657,457
• Publication Number:
  US 20100255471A1
• Time in Patent Office: 2,295 Days
• Field of Search: None
• US Class Current: 1/1
• CPC Class Codes: C12Q 1/6886 for cancer immunoassay for cancer G01N33/574
• CPC Class Codes: C12Q 2600/106 Pharmacogenomics, i.e. genetic variability in individual responses to drugs and drug metabolism
• CPC Class Codes: C12Q 2600/112 Disease subtyping, staging or classification
• CPC Class Codes: C12Q 2600/118 Prognosis of disease development
• CPC Class Codes: C12Q 2600/136 Screening for pharmacological compounds
• CPC Class Codes: C12Q 2600/158 Expression markers
• CPC Class Codes: C12Q 2600/178 miRNA, siRNA or ncRNA
• CPC Class Codes: G01N 2800/52 Predicting or monitoring the response to treatment, e.g. for selection of therapy based on assay results in personalised medicine; Prognosis
• CPC Class Codes: G01N 33/5023 on expression patterns
• CPC Class Codes: G01N 33/57484 involving compounds serving as markers for tumor, cancer, neoplasia, e.g. cellular determinants, receptors, heat shock/stress proteins, A-protein, oligosaccharides, metabolites

Abstract

Methods are provided for diagnosis and prognosis of disease by analyzing expression of a set of genes obtained from single cell analysis. Classification allows optimization of treatment, and determination of whether on whether to proceed with a specific therapy, and how to optimize dose, choice of treatment, and the like. Single cell analysis also provides for the identification and development of therapies which target mutations and/or pathways in disease-state cells.

Claims

1. A method of identifying different cell populations in a heterogeneous cell sample, comprising:

randomly partitioning individual cells from said heterogeneous cell sample into discrete locations on a cell capture array with wells just large enough to fit a single cell;

identifying certain individually partitioned cells in the discrete locations on the cell capture array using one or more surface markers;

sorting the certain individually partitioned cells from the discrete locations using a microfluidic device;

performing transcriptome analysis on a plurality of genes of the individually sorted cells from the discrete locations; and

performing clustering analysis to identify different cell populations.

2. The method of claim 1, wherein said individual cells are not enriched prior to said partitioning.

3. The method of claim 1, wherein said transcriptome analysis is performed on at least 1000 individual cells in parallel.

4. The method of claim 1, wherein said transcriptome analysis is performed using nucleic acid analysis.

5. The method of claim 1, wherein said discrete locations are on a microarray.

6. The method of claim 1, wherein said transcriptome analysis comprises analyzing expressed RNA, non-expressed RNA, or both.

7. The method of claim 1, wherein said transcriptome analysis is whole transcriptome analysis.

8. The method of claim 1, wherein said transcriptome analysis comprises amplifying RNA using a set of at least five primer pairs.

9. The method of claim 8, wherein said at least five primer pairs are not nested primers.

10. The method of claim 1, wherein said transcriptome analysis is performed in parallel or substantially in real time on said individually sorted cells.

11. The method of claim 1, wherein said different cell populations are non-cancerous stem cells, non-cancerous progenitor cells, non-cancerous mature cells, inflammatory cells, cancer cells, cancer stem cells or non-tumorigenic cancer stem cells.