Systems and Methods For RNA Analysis In Functional Confirmation Of Cancer Mutations

Abstract

Contemplated systems and methods integrate genomic/exomic data with transcriptomic data by correlating a cancer associated mutation in the genome/exome with the transcription level of the affected gene carrying the mutation, particularly where the mutation is a 3-terminal nonsense mutation.

What is claimed is: 
     
         1 . A computer-assisted method of treating a patient having a tumor, comprising:
 obtaining or generating a genomic data set and a transcriptomic data set;
 wherein the genomic data set includes DNA sequence data that is representative of a mutation in at least one tumor-associated gene of a diseased tissue of the patient, and wherein the mutation is relative to a normal tissue of the patient; 
 wherein the transcriptomic data set includes 1) RNA sequence data that is representative of the mutation in the at least one tumor-associated gene and 2) RNA expression level data of the at least one tumor-associated gene of the diseased tissue of the patient, and wherein the mutation and expression level are relative to the normal tissue of the patient; 
   using a sequence analysis engine to:
 (a) associate the transcriptomic data set with the genomic data set using the mutation; 
 (b) identify the mutation as a nonsense mutation, and upon identification of the mutation as nonsense mutation to: 
 (c) identify the expression level of the at least one gene as being higher than the normal tissue of the patient; and 
   treating the patient having the tumor where the tumor is related to the at least one gene having the nonsense mutation and higher expression level.   
     
     
         2 . The method of  claim 1  further comprising informationally coupling a sequence database or a sequencing device with the sequence analysis engine, and using the sequence analysis engine to generate the transcriptomic data set and the genomic data set. 
     
     
         3 . The method of  claim 1  wherein the transcriptomic data set and the genomic data set are differential sequence objects. 
     
     
         4 . The method of  claim 1  wherein the diseased tissue is a cancerous tissue. 
     
     
         5 . The method of  claim 1  wherein the transcriptomic data set is associated with the genomic data set when the mutation is in the same position. 
     
     
         6 . The method of  claim 1  wherein the transcriptomic data are obtained from cDNA or polyA + -RNA. 
     
     
         7 . The method of  claim 1 , wherein the mutation in the at least one gene in the genomic data set is patient specific. 
     
     
         8 . The method of  claim 1 , wherein the sequence analysis engine is further used to identify a position of the mutation in the at least one gene. 
     
     
         9 . The method of  claim 8 , wherein the position of the mutation is within the 3′-end portion of the at least one gene. 
     
     
         10 . The method of  claim 8 , wherein the position of the mutation is within last two exons of the at least one gene. 
     
     
         11 . The method of  claim 1 , wherein the at least one mutated gene is mutated in at least two distinct cancers. 
     
     
         12 . The method of  claim 1 , wherein the at least one mutated gene is mutated in at least four distinct cancers. 
     
     
         13 . The method of  claim 1  wherein the gene is selected from the group consisting of CDKN2A, ARID1A, FAT1, TP53, PTEN, AHNAK, SRRM2, RASA1, PIK3R1, and MRPL32. 
     
     
         14 . The method of  claim 1 , wherein the transcriptomic data set of the at least one mutated gene and the genomic data set of the at least one mutated gene are associated by alignment such that corresponding sequences or locations can be compared between the genomic data set and the transcriptomic data set. 
     
     
         15 . The method of  claim 1 , wherein the transcriptomic data set of the at least one mutated gene and the genomic data set of the at least one mutated gene are associated by combining the genomic data set and the transcriptomic data set. 
     
     
         16 . The method of  claim 1 , further comprising updating or generating, by the sequence analysis engine, the omics record using the position of the mutation and the expression level when the identified mutation is the nonsense mutation and the identified expression level is above expression level relative to the normal tissue. 
     
     
         17 . The method of  claim 16 , wherein the omics record further indicates use of the at least one mutated gene to determine presence, treatment or prevention of the tumor.