Methods and compositions of molecular profiling for disease diagnostics

Abstract

The present invention relates to compositions, kits, and methods for molecular profiling and cancer diagnostics, including but not limited to gene expression product markers, alternative exon usage markers, and DNA polymorphisms associated with cancer. In particular, the present invention provides molecular profiles associated with thyroid cancer, methods of determining molecular profiles, and methods of analyzing results to provide a diagnosis.

1 - 78 . (canceled) 
     
     
         79 . A method of detecting a thyroid condition in a patient comprising the steps of
 a. obtaining a sample of thyroid tissue from said patient;   b. assaying a level of expression of one or more gene expression products in said sample of thyroid tissue; and   c. classifying said sample of thyroid tissue as benign or normal by applying a trained algorithm to data from step b, wherein said method has a negative predictive value (NPV) of at least 95% for independent samples.   
     
     
         80 . (canceled) 
     
     
         81 . The method of  claim 79 , wherein said method has a specificity greater than 70%. 
     
     
         82 . The method of  claim 79 , wherein an overall classification error rate of said method is less than 6%. 
     
     
         83 . The method of  claim 79 , wherein said sample of thyroid tissue is obtained by needle aspiration, fine needle aspiration, core needle biopsy, vacuum assisted biopsy, large core biopsy, incisional biopsy, excisional biopsy, punch biopsy, shave biopsy, or skin biopsy. 
     
     
         84 . The method of  claim 79 , wherein said sample of thyroid tissue comprises thyroid cells and said sample of thyroid tissue is obtained by fine needle aspiration. 
     
     
         85 . The method of  claim 79 , wherein said gene expression product is an RNA expression product. 
     
     
         86 . The method of  claim 85 , wherein a level of said RNA expression product is measured by microarray, SAGE, blotting, RT-PCR, quantitative PCR, or sequencing. 
     
     
         87 . The method of  claim 79 , wherein said trained algorithm is trained with at least three training samples, each of which exhibits a different malignant pathology. 
     
     
         88 . The method of  claim 79 , wherein said trained algorithm is trained with a training set comprising a training sample with a pathology selected from the group consisting of: metastatic melanoma, metastatic renal carcinoma, metastatic breast carcinoma, and metastatic B cell lymphoma. 
     
     
         89 . The method of  claim 79 , wherein said trained algorithm is trained with a training set comprising a training sample with a tissue type selected from the group consisting of: normal thyroid, follicular adenoma, parathyroid, follicular carcinoma, lymphocytic thyroiditis, follicular variant papillary thyroid carcinoma, papillary thyroid carcinoma, nodular hyperplasia, medullary thyroid carcinoma, Hurthle cell carcinoma, Hurthle cell adenoma, or anaplastic thyroid carcinoma. 
     
     
         90 . The method of  claim 79 , wherein said trained algorithm is trained with a training set comprising a training sample obtained by fine needle aspiration. 
     
     
         91 . The method of  claim 79 , wherein said trained algorithm is trained with a training set comprising a training sample obtained by fine needle aspiration and a training sample obtained by surgical biopsy. 
     
     
         92 . The method of  claim 79 , wherein said classifying is based on a level of expression in said sample of thyroid tissue of at least two of the following genes or corresponding Transcript Cluster ID Nos:
 CALCA, CEACAM5, SCG3, SCN9A, SYT4, FABP7, FXYD2, HAVCR1, LOC100101266, NR1H4, PREPL, SLC3A1, DMRT2, GCM2, KIDINS220, KL, PTH, SYCP2L, AGR3, C10orf81, MYB, SYCP2, VTCN1, CDH19, MLANA, S100B, SILV, TYR, TYRL, ALDHIB1, CD44, CPE, DEFB1, EGF, FRMD3, HSD17B6, IGF2BP2, IQCA1, ITGB3, LOC100129258, NUPR1, ODZ1, PVALB, PVRL2, RPL3, SLC16A1, ST3GAL5, ZBED2, ABCD2, AIM2, ARSG, AUTS2, C11orf72, C4orf7, CCL19, CCND1, CD36, CD52, CD96, CFH, CFHR1, CLDN1, CLDN16, CR2, CXCL13, DAB2, DPP4, DPP6, EAF2, EMR3, FABP4, FBXO2, FLJ42258, FN1, FPR2, FXYD6, GOS2, GABRB2, GIMAP2, GPR174, GZMK, HCG11, IL7R, ITGB1, KCNA3, KLRG1, LCP1, LIPH, LOC100131599, LOC647979, LRP1B, MAPK6, MATN2, MDK, MPPED2, MT1F, MT1G, MT1H, MT1P2, MYEF2, NRCAM, P2RY13, P1GN, PKHDIL1, PLA2G16, PLCB1, PLEK, PROS1, PTPRC, PTPRE, PYGL, PYHIN1, RGS13, RIMS2, ROS1, RXRG, SCEL, SEMA3D, SERGEF, SERPINA1, SERPINA2, SLC24A5, SLC34A2, SLC4A4, SNCA, STK32A, TIMP1, TIMP2, TMSB10, TNFRSF17, WIPI1, ZFYVEI6, ACSL1, AHNAK, ASPN, BCL2L1, CC2D2B, DDI2, DNAJC13, DYNLT1, FAH, FREM2, GMFG, HNRNPA3, IGHG1, LRP12, MAGI3, NDUFC2, OR10D1P, PDE8A, PDHA1, PFKFB2, PHYH, PPP2R2B, PRKG1, PZP, RNF24, RRAGD, SCN2A, SCUBE3, SDHALP2, SHC1, SLC43A3, THRSP, TNFRSF1A, TXNDC12, or VWA5A.   
     
     
         93 . The method of  claim 79 , wherein said sample of thyroid tissue has not previously received a definitive diagnosis. 
     
     
         94 . The method of  claim 79 , wherein said sample of thyroid tissue is subjected to cytological testing that indicates the sample is ambiguous or suspicious. 
     
     
         95 . The method of  claim 79 , wherein said sample is a formalin-fixed-paraffin-embedded sample. 
     
     
         96 . The method of  claim 88 , wherein said pathology of said training sample is metastatic B cell lymphoma. 
     
     
         97 . The method of  claim 89 , wherein said tissue type of said training sample is selected from the group consisting of: follicular adenoma, follicular carcinoma, and papillary thyroid carcinoma. 
     
     
         98 . The method of  claim 89 , wherein said tissue type of said training sample is Hurthle cell carcinoma. 
     
     
         99 . The method of  claim 89 , wherein said tissue type of said training sample is selected from the group consisting of: follicular adenoma, follicular carcinoma, papillary thyroid carcinoma, Hurthle cell carcinoma, and follicular variant papillary thyroid carcinoma. 
     
     
         100 . The method of  claim 79 , further comprising treating the patient on the basis of step (c). 
     
     
         101 - 135 . (canceled) 
     
     
         136 . A method of evaluating a sample of thyroid tissue from a patient comprising the steps of:
 (a) obtaining said sample of thyroid tissue from said patient;   (b) assaying an expression level for two or more gene expression products in said sample of thyroid tissue to generate test data;   (c) applying an algorithm to said expression level of step (b), wherein said algorithm correlates the expression level of step (b) with expression data obtained from a plurality of samples, wherein said plurality of samples comprises a sample obtained by surgical biopsy of thyroid tissue and a sample obtained by fine needle aspiration of thyroid tissue; and   (d) based on said correlating, (i) identifying said sample of thyroid tissue as malignant, (ii) identifying said sample of thyroid tissue as benign, (iii) identifying said sample of thyroid tissue as non-cancerous, (iv) identifying said sample of thyroid tissue as non-malignant, or (v) identifying said sample of thyroid tissue as normal.   
     
     
         137 . The method of  claim 136 , wherein said algorithm is a trained algorithm trained by said expression data obtained from said plurality of samples. 
     
     
         138 . The method of  claim 137 , wherein said plurality of samples comprises at least 200 training samples. 
     
     
         139 . The method of  claim 137 , wherein said plurality of samples comprises at least 400 training samples. 
     
     
         140 . The method of  claim 137 , wherein one or more of said plurality of samples has a pathology selected from the group consisting of: metastatic melanoma, metastatic renal carcinoma, metastatic breast carcinoma, and metastatic B cell lymphoma. 
     
     
         141 . The method of  claim 137 , wherein one or more of said plurality of samples has a pathology selected from the group consisting of: normal thyroid, follicular adenoma, parathyroid, follicular carcinoma, lymphocytic thyroiditis, follicular variant papillary thyroid carcinoma, papillary thyroid carcinoma, nodular hyperplasia, medullary thyroid carcinoma, Hurthle cell carcinoma, Hurthle cell adenoma, or anaplastic thyroid carcinoma. 
     
     
         142 . The method of  claim 137 , wherein said trained algorithm is trained by correlating a gene expression profile of a first sub-type of thyroid tissue with a gene expression profile of at least six sub-types of thyroid tissue that are not of said first sub-type. 
     
     
         143 . The method of  claim 137 , wherein said sample of thyroid tissue is obtained by needle aspiration, fine needle aspiration, core needle biopsy, vacuum assisted biopsy, large core biopsy, incisional biopsy, excisional biopsy, punch biopsy, shave biopsy, or skin biopsy. 
     
     
         144 . The method of  claim 137 , wherein said sample of thyroid tissue is subjected to cytological testing, a result of which is indeterminate. 
     
     
         145 . The method of  claim 137 , wherein said gene expression product is an RNA gene expression product. 
     
     
         146 . The method of  claim 137 , wherein said correlating uses gene expression data of at least two of the following genes or corresponding Transcript Cluster ID Nos:
 CALCA, CEACAM5, SCG3, SCN9A, SYT4, FABP7, FXYD2, HAVCR1, LOC100101266, NR1H4, PREPL, SLC3A1, DMRT2, GCM2, KIDINS220, KL, PTH, SYCP2L, AGR3, C10orf81, MYB, SYCP2, VTCN1, CDH19, MLANA, S100B, SILV, TYR, TYRL, ALDHIB1, CD44, CPE, DEFB1, EGF, FRMD3, HSD17B6, IGF2BP2, IQCA1, ITGB3, LOC100129258, NUPR1, ODZ1, PVALB, PVRL2, RPL3, SLC16A1, ST3GAL5, ZBED2, ABCD2, AIM2, ARSG, AUTS2, C11orf72, C4orf7, CCL19, CCND1, CD36, CD52, CD96, CFH, CFHR1, CLDN1, CLDN16, CR2, CXCL13, DAB2, DPP4, DPP6, EAF2, EMR3, FABP4, FBXO2, FLJ42258, FN1, FPR2, FXYD6, GOS2, GABRB2, GIMAP2, GPR174, GZMK, HCG11, IL7R, ITGB1, KCNA3, KLRG1, LCP1, LIPH, LOC100131599, LOC647979, LRP1B, MAPK6, MATN2, MDK, MPPED2, MT1F, MT1G, MT1H, MT1P2, MYEF2, NRCAM, P2RY13, PIGN, PKHD1L1, PLA2G16, PLCB1, PLEK, PROS1, PTPRC, PTPRE, PYGL, PYHIN1, RGS13, RIMS2, ROS1, RXRG, SCEL, SEMA3D, SERGEF, SERPINA1, SERPINA2, SLC24A5, SLC34A2, SLC4A4, SNCA, STK32A, TIMP1, TIMP2, TMSB10, TNFRSFI7, WIPI1, ZFYVE16, ACSL1, AHNAK, ASPN, BCL2L1, CC2D2B, DDI2, DNAJCI3, DYNLT1, FAH, FREM2, GMFG, HNRNPA3, IGHG1, LRP12, MAGI3, NDUFC2, OR10D1P, PDE8A, PDHA1, PFKFB2, PHYH, PPP2R2B, PRKG1, PZP, RNF24, RRAGD, SCN2A, SCUBE3, SDHALP2, SHC1, SLC43A3, THRSP, TNFRSF1A, TXNDC12, or VWA5A.   
     
     
         147 . The method of  claim 137 , wherein said sample of thyroid tissue is subjected to cytological testing that indicates the sample is ambiguous or suspicious. 
     
     
         148 . The method of  claim 137 , further comprising treating the patient on the basis of step (d). 
     
     
         149 . A method of detecting a thyroid condition in a patient comprising the steps of:
 a. obtaining a sample of thyroid tissue from said patient;   b. assaying a level of expression of one or more gene expression products in said sample of thyroid tissue; and   c. classifying said sample of thyroid tissue as benign by applying an algorithm to data from step b, wherein said algorithm correlates said data from step b with expression data obtained from a plurality of samples, wherein said plurality of samples comprises a sample with a pathology that is a metastatic cancer from a non-thyroid organ.   
     
     
         150 . The method of  claim 149 , wherein said algorithm is a trained algorithm trained with expression data obtained from a training set comprising a training sample with a pathology selected from the group consisting of: metastatic melanoma, metastatic renal carcinoma, metastatic breast carcinoma, and metastatic B cell lymphoma. 
     
     
         151 . The method of  claim 150 , wherein said pathology of said training sample is metastatic B cell lymphoma. 
     
     
         152 . The method of  claim 149 , further comprising treating the patient on the basis of step (c). 
     
     
         153 - 159 . (canceled) 
     
     
         160 . The method of any one of  claim 79  or  149 , wherein results from said classifying are sent to a party via a communication medium. 
     
     
         161 . The method of  claim 136 , wherein results from said identifying are sent to a party via a communication medium. 
     
     
         162 - 166 . (canceled) 
     
     
         167 . The method of  claim 79 , wherein said method has a negative predictive value (NPV) of at least 95% for at least 100 independent samples. 
     
     
         168 . The method of  claim 79 , wherein said method has a sensitivity of at least 90% for independent samples. 
     
     
         169 . The method of  claim 79 , further comprising treating said patient on the basis of step c. 
     
     
         170 . A method of detecting a thyroid condition in a patient comprising the steps of:
 a. obtaining a sample of thyroid tissue from said patient;   b. assaying a level of expression of one or more gene expression products in said sample of thyroid tissue; and   c. classifying said sample of thyroid tissue as benign or normal by applying a trained algorithm to data from step b, wherein said method has a negative predictive value (NPV) of at least 95% for at least 100 independent samples, and a sensitivity of at least 90 for at least 100 independent samples.   
     
     
         171 . The method of  claim 170 , wherein said gene expression product is an RNA expression product. 
     
     
         172 . The method of  claim 170 , wherein said trained algorithm is trained with at least three training samples, each of which exhibits a different malignant pathology. 
     
     
         173 . The method of  claim 170 , wherein said trained algorithm is trained with a training set comprising a training sample with a pathology selected from the group consisting of: metastatic melanoma, metastatic renal carcinoma, metastatic breast carcinoma, and metastatic B cell lymphoma. 
     
     
         174 . The method of  claim 170 , wherein said trained algorithm is trained with a training set comprising a training sample with a tissue type selected from the group consisting of: normal thyroid, follicular adenoma, parathyroid, follicular carcinoma, lymphocytic thyroiditis, follicular variant papillary thyroid carcinoma, papillary thyroid carcinoma, nodular hyperplasia, medullary thyroid carcinoma, Hurthle cell carcinoma, Hurthle cell adenoma, or anaplastic thyroid carcinoma. 
     
     
         175 . The method of  claim 170 , wherein said trained algorithm is trained with a training set comprising a training sample obtained by fine needle aspiration and a training sample obtained by surgical biopsy. 
     
     
         176 . The method of  claim 170 , wherein said sample of thyroid tissue has not previously received a definitive diagnosis. 
     
     
         177 . The method of  claim 170 , wherein said sample of thyroid tissue is subjected to cytological testing that indicates the sample is ambiguous or suspicious. 
     
     
         178 . The method of  claim 173 , wherein said pathology of said training sample is metastatic B cell lymphoma. 
     
     
         179 . The method of  claim 174 , wherein said tissue type of said training sample is selected from the group consisting of: follicular adenoma, follicular carcinoma, and papillary thyroid carcinoma. 
     
     
         180 . The method of  claim 174 , wherein said tissue type of said training sample is selected from the group consisting of: follicular adenoma, follicular carcinoma, papillary thyroid carcinoma, Hurthle cell carcinoma, and follicular variant papillary thyroid carcinoma. 
     
     
         181 . The method of  claim 170 , further comprising treating said patient on the basis of step c. 
     
     
         182 . The method of  claim 170 , wherein said sample of thyroid tissue is obtained by needle aspiration, fine needle aspiration, core needle biopsy, vacuum assisted biopsy, large core biopsy, incisional biopsy, excisional biopsy, punch biopsy, shave biopsy, or skin biopsy 
     
     
         183 . The method of  claim 170 , wherein said sample of thyroid tissue comprises thyroid cells and said sample of thyroid tissue is obtained by fine needle aspiration. 
     
     
         184 . The method of  claim 79 , wherein the sample is classified as not benign or not normal, and further comprising treating the patient. 
     
     
         185 . The method of  claim 79  or  170 , wherein prior to step (b), a cytological analysis of the tissue is performed, wherein if the tissue is ambiguous based on the cytological analysis, then steps (b) and (c) are performed. 
     
     
         186 . The method of  claim 79  or  170 , wherein prior to step (b), a cytological analysis of the tissue is performed, wherein (i) if the tissue is ambiguous based on the cytological analysis, then steps (b) and (c) are performed; and (ii) if the tissue is malignant or benign then steps (b) and (c) are not performed.