Methods for detecting mutation load from a tumor sample

Abstract

A targeted panel with low sample input requirements from a tumor only sample may be processed to estimate mutation load in a tumor sample. The method may include detecting variants in nucleic acid sequence reads corresponding to targeted locations in the tumor sample genome; annotating detected variants with an annotation information from a population database; filtering the detected variants, wherein the filtering rule set retains the somatic variants and removes germ-line variants; counting the identified somatic variants to give a number of somatic variants; determining a number of bases in covered regions of the targeted locations in the tumor sample genome; and calculating a number of somatic variants per megabase, provides an estimate of the mutation load per megabase in the tumor sample genome.

What is claimed is: 
     
         1 . A method of analyzing a tumor sample genome for a mutation load, comprising:
 amplifying nucleic acid sequences at targeted locations in the tumor sample genome by a targeted panel with a low sample input from the tumor sample to generate a plurality of nucleic acid sequence reads, wherein the tumor sample is a tumor only sample;   detecting variants in the plurality of nucleic acid sequence reads to produce a plurality of detected variants;   filtering the plurality of detected variants, wherein the filtering applies a rule set to the detected variants to retain somatic variants;   calculating a tumor mutation load in the tumor only sample by dividing a number of the somatic variants by a number of bases in covered regions of the targeted locations.   
     
     
         2 . The method of  claim 1 , wherein the low sample input comprises 1 ng to 40 ng of sample DNA. 
     
     
         3 . The method of  claim 1 , wherein the low sample input comprises 1 ng to 20 ng of sample DNA. 
     
     
         4 . The method of  claim 1 , wherein the low sample input comprises 10 ng to 20 ng of sample DNA. 
     
     
         5 . The method of  claim 1 , wherein the targeted panel covers approximately 1.7 Mb of the tumor sample genome. 
     
     
         6 . The method of  claim 1 , further comprising annotating one or more detected variants of the plurality of detected variants with an annotation information from one or more population databases, wherein the population databases include information associated with variants in a population. 
     
     
         7 . The method of  claim 6 , wherein the annotation information includes a minor allele frequency associated with a given variant. 
     
     
         8 . The method of  claim 1 , wherein the rule set includes retaining the detected variants whose minor allele frequency (MAF) is within a MAF range. 
     
     
         9 . The method of  claim 8 , wherein the MAF range is from 0 to 10 −6 . 
     
     
         10 . The method of  claim 8 , wherein the MAF range is from 0 to 0.01. 
     
     
         11 . The method of  claim 1 , wherein the rule set further comprises retaining the detected variants that are single nucleotide variants (SNVs). 
     
     
         12 . The method of  claim 1 , wherein the rule set further comprises retaining the detected variants that are SNVs, insertion variants and deletion variants (indels). 
     
     
         13 . The method of  claim 1 , wherein the rule set further comprises removing the detected variants that are SNVs corresponding to SNPs in a UCSC Common SNP database. 
     
     
         14 . The method of  claim 1 , wherein the rule set further comprises removing the detected variants in regions having homopolymer lengths greater than seven. 
     
     
         15 . The method of  claim 1 , wherein the step of detecting variants is configured by a variant caller parameter including a minimum coverage parameter. 
     
     
         16 . The method of  claim 15 , wherein the minimum coverage parameter is in a range from 20 to 60. 
     
     
         17 . The method of  claim 1 , wherein the step of detecting variants is configured by a variant caller parameter including a minimum allele frequency parameter. 
     
     
         18 . The method of  claim 1 , wherein the step of detecting variants is configured by a variant caller parameter including a strand bias parameter. 
     
     
         19 . The method of  claim 1 , wherein the step of detecting variants is configured by a variant caller parameter including a data quality stringency parameter. 
     
     
         20 . The method of  claim 1 , further comprising associating sources of somatic mutation damage with the somatic variants.