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US 8,557,520 B2Granted
Methods for diagnosing prostate cancer using MicroRNAs
AssigneeThe Ohio State University
InventorsCarlo M. Croce, George A. Calin, Stefano Volinia
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Abstract
The present invention provides novel methods and compositions for the diagnosis and treatment of solid cancers. The invention also provides methods of identifying inhibitors of tumorigenesis.
Claims20
A method to identify a human subject has prostate cancer, comprising:
- measuring in a test sample of prostate tissue from the subject a level of at least one let-7d gene product and at least one miR-128a prec gene product;
- comparing the level of the at least one let-7d gene product and the least one miR-128a prec gene product in the test sample from a subject to a control level of at least one corresponding let-7d gene product and at least one miR-128a prec gene product;
- correlating an increase in the test sample level of let-7d gene product compared to the control level of let-7d gene product, and a decrease in the test sample level of miR-128a prec gene product compared to the control level of miR-128a prec gene product, with a human subject having prostate cancer;
- and
- identifying the subject has prostate cancer, if the level of the at least one let-7d gene product in the test sample from the subject is greater than the control level of let-7d gene product, and if the level of the at least one miR-128a prec gene product in the test sample from the subject is less than the control level of miR-128a prec gene product.
2 more elements
A method of diagnosing whether a human subject has prostate cancer, comprising:
- a.) reverse transcribing at least one miR gene product from a test sample of prostate tissue from the subject to provide at least one corresponding miR gene product target oligonucleotides;
- b.) hybridizing at least one miR target oligodeoxynucleotides to a microarray comprising miRNA-specific probe oligonucleotides that include at least one corresponding miRNA-specific probe oligonucleotides to provide a hybridization profile for the test sample;
- c.) comparing the test sample hybridization profile to at least one control hybridization profile;
- d.) correlating an increase in the test sample level of miR gene product compared to the control level of miR gene product with a human subject having prostate cancer;
- and
- e.) diagnosing whether the subject has prostate cancer, wherein the diagnosing is based on the correlating of step d.);
- wherein the miR gene product is let-7d.
4 more elements
A method of diagnosing whether a human subject has prostate cancer, comprising:
- measuring in a test sample of prostate tissue from the subject a level of at least a let-7d gene product;
- comparing the level of at least let-7d gene product in the test sample from the subject to a control level of at least one let-7d gene product;
- correlating an increase in the test sample level of let-7d gene product compared to the control level of let-7d gene product with a human subject having prostate cancer;
- and
- diagnosing whether the subject has prostate cancer, wherein the diagnosing is based on the correlating.
2 more elements
A method of diagnosing whether a human subject has prostate cancer, comprising:
- a.) reverse transcribing at least let-7d gene product from a test sample of prostate tissue from a subject to provide at least one corresponding miR gene product target oligonucleotides;
- b.) hybridizing at least let-7d target oligodeoxynucleotides to a microarray comprising miRNA-specific probe oligonucleotides that include at least one corresponding let-7d RNA specific probe oligonucleotides to provide a hybridization profile for the test sample;
- c.) comparing the test sample hybridization profile to at least one control hybridization profile;
- d.) correlating an increase in the test sample level of miR gene product compared to the control level of miR gene product with a human subject having prostate cancer;
- and
- e.) diagnosing whether the subject has prostate cancer, wherein the diagnosing is based on the correlating of step d.)
3 more elements
Dependencies are inferred from the claim text.