blood samples and tumour tissues were obtained from 117 operated lung cancer patients admitted to oslo university hospitalrikshospitalet in the period 20062011 . the collected tumor samples consisted of 93 adenocarcinomas , 2 large cell carcinomas and 22 squamous cell carcinomas .
one patient was diagnosed with metastases based on pathology report , and was omitted from survival analyses .
tumour tissue was snap frozen in liquid nitrogen and stored at 80c until dna isolation .
dna was extracted using maxwell16 dna purification kits and a maxwell16 instrument according to technical manual ( literature # tm284)(http://www.promega.com ) .
dna from blood was isolated using the master pure dna purification kit for blood according to the dna purification protocol ( http://www.epicentre.com ) .
targeted resequencing was performed using the sureselect human kinome kit ( agilent technologies ) , with capture probes targeting 3.2 mb of the human genome , including exons and untranslated regions ( utrs ) of all known kinases and selected cancerrelated genes ( 612 ) .
library construction and in solution capturing was performed following agilent 's sureselectxt library construction kit and sureselect target enrichment protocol , respectively .
sequencing was performed on an illumina genome analyzer using truseq sbs kit v5 generating pairedend reads of 75 bp in length .
base calling , demultiplexing and quality filtering was performed using illumina 's software packages scs2.8/rta1.8 and offline basecallerv1.8 .
the raw sequencing reads derived from tumour and control samples were subsequently processed in a computational pipeline to identify and functionally annotate somatic dna changes .
a variant calling pipeline was established to identify somatic mutations in each tumour / control sample pair .
this included several steps : ( i ) alignment of sequence reads toward the reference genome ( grch37  including unlocalised / unplaced contigs and decoy sequences ) using bwamem,9 ( ii ) marking of potential pcrderived duplicate reads using picard ( http://broadinstitute.github.io/picard/ ) , ( iii ) local realignment around indel sites using gatk realignertargetcreator and indelrealigner,10 ( iv ) base quality recalibration using gatk baserecalibrator , and ( v ) somatic single nucleotide variant ( snv ) and short insertion / deletion ( indel ) calling using strelka and mutect algorithms.11 , 12 for snvs , we only considered calls designated as somatic by both mutect and strelka ( indels were called by strelka only ) .
our pipeline was recently part of a wholegenome benchmarking exercise organized through icgc , in which our performance was assessed for snv ( precision  =  0.90 , recall  =  0.73 ) and indel calling ( precision  =  0.71 , recall  = 0.70).13 
  to understand the functional role of identified variants , all variants were subject to a computational annotation workflow including a modified version of annovar ( release 2015dec14 , using ensembl as the gene model ) , cosmic ( known somatic cancer variants and cancer gene census , v76 february 2016 ) , pfam ( protein domain information , v27.0 ) , uniprot kb ( functional protein properties , release 2016_02 ) , the drug gene interaction database ( druggable targets , version 2.0 ) , database of curated mutations ( release january 2016 ) , and database of computational predictions of effects of nonsynonymous variants , v2.1.13 , 14 , 15 , 16 , 17 , 18 
  we used intogen ( integrative onco genomics ) to identify cancer driver genes in our sample cohort .
considering that a frequencybased approach to discover significantly mutated genes is suboptimal in samples with low mutation counts , intogen uses an approach by which a clustering and functional bias among gene mutations ( across the sample cohort ) indicates driver candidates.19 
  we have previously reported on the survival impact of stromal cd8 expression ( cytotoxic tcells ) including most of the patients in this study ( n  =  107).7 in short , tissue microarrays were used for determination of an immunoscore by immunohistochemistry cd8 staining by ventana benchmark , xt automated slide stainer ( ventana medical system ) . by light microscopy , the tissue cores were scored for the degree of infiltration of cd8 + lymphocytes .
the percentages of cd8 + lymphocytes among all nucleated cells in the stromal compartments were assessed .
scoring cutoff points at 5% , 25% , or 50% were used for each core .
all samples were anonymized and independently scored by two pathologists . the mean score for duplicate cores from each individual was calculated and the median stromal cd8 score was used as cutoff .
time to relapse was calculated from the date of diagnosis to the date of diagnosed local relapse , distant metastasis , or lung cancer death with a maximum followup time of 80 months after surgery .
the survival analyses were performed using spss ( pasw statistics for windows , version 18.0 , chicago : spss ) .
survival curves and estimation of statistical significance between the survival curves utilized the kaplanmeier method and log rank test , respectively .
a cox regression model was applied for the multivariate survival analysis using spss ( v. 18 ) .
probes that targeted the human kinome were captured and sequenced at 5060 coverage in 117 tumourcontrol sample pairs .
the medians for allelic fraction and read depth at confident variant sites were 0.2 and 84 , respectively .
the best covered variant sites ( read depth of 150 ) enabled detection of variants with allelic fraction as low as 34% .
in addition to coding exonic sequences , the targeted regions included canonical splice sites in introns , as well as utrs .
each tumour sample had an accompanying control sample ( blood ) , which allowed the detection of point mutations and insertions / deletions of somatic origin .
our pipeline for somatic mutation detection relied on a consensus between two different algorithms ( mutect and strelka ) , a strategy that performed well in a previous benchmarking exercise.20 only mutations called by both the algorithms were thus included in the further analysis .
the number of coding mutations varied extensively between tumours , ranging from 0 to 50 ( mean  =  11 , median  =  9 ) .
calculation of coding mutations in the same genes ( i.e. , kinome ) of tcga lung adenocarcinoma samples revealed similar numbers ( mean 13.2 , median 9).21 there was no significant difference in number of mutations between men and women or between tumours with different histological subtypes .
number of mutations was significantly associated with packyears of tobacco smoking ( p  =  0.009 ) .
the tp53 gene and the ttn gene were the most frequently mutated genes , the latter being a known artefact due to its large size ( fig . 1 
 a ) .
the tp53 mutations were all validated by sanger sequencing where the sequences were aligned and analysed using seqscape v.2.5 according to the project template [ tp53 accession nr .
( a ) recurrence of somatically mutated genes . shown are all mutated genes with a recurrence frequency > = 4% among all 117 samples .
ad  =  adenocarcinoma , scc  =  squamous cell carcinoma , lcc  =  large cell carcinoma .
genes defined by intogen as significant cancer drivers are indicated in red . through use of intogen , kras , egfr , tp53 and
kras was mutated in 28 samples ( 27 adenocarcinomas , one large cell carcinoma ) .
eight samples ( seven adenocarcinomas ) were mutated in the stk11 gene . only adenocarcinomas were egfrmutated , with mainly l858r mutations and exon 19 deletions .
twentyseven samples had mutations in known dna repair genes,1 including palb2 , atm , atr , brca1 , brca2 , fancl , chek1 , chek2 and clk2 .
there was a significant correlation between mutations in one of these genes and the total number of mutations ( p  <  0.001 ) .
tumours with a mutation in tp53 , atm or atr had an increased number of mutations when analysed separately ( fig .
2 ) , whereas tumours with mutations in the other repair genes did not show a significant increase by themselves ; however , the number of samples in these groups were small .
mutations in one of the dna repair genes were significantly associated with a higher number of mutations .
mutations in tp53 , atr and atm alone were associated with a higher number of mutations .
the tumours were divided in three separate groups based on an immunoscore reflecting the number of infiltrating cd8 + tlymphocytes , as defined by donnem et al.7 there was no significant association between immunoscore and the number of point mutations . however , when using the median stromal cd8score as cutoff ( high score n  =  58 , low score n  =  49 ) , there was a significant inverse correlation between the number of infiltrating stromal cd8 + lymphocytes and presence of egfr mutations ( r  =  0.21 , p  = 0.029 ) ( pearson  ) .
patients with more than the median number of mutations in their tumours had shorter relapsefree survival than patients with submedian mutation counts ( fig .
multivariate analysis of relapsefree survival was performed using cox regression to study the influence of known prognostic factors ( histology , stage , sex ) .
the number of mutations was not significantly associated with survival in a coxanalysis with number of mutations as a continuous variable ( p  =  0.60 ) .
however , the number of mutations ( over median ) was found to be significantly associated with time to progression after adjusting for clinical variables ( p  =  0.021 ) . there was a tendency toward increased relapsefree survival for patients with high cd8score ( p  =  0.10 ) .
twentyseven samples had mutations in known dna repair genes,1 including palb2 , atm , atr , brca1 , brca2 , fancl , chek1 , chek2 and clk2 .
there was a significant correlation between mutations in one of these genes and the total number of mutations ( p  <  0.001 ) .
tumours with a mutation in tp53 , atm or atr had an increased number of mutations when analysed separately ( fig .
2 ) , whereas tumours with mutations in the other repair genes did not show a significant increase by themselves ; however , the number of samples in these groups were small .
mutations in one of the dna repair genes were significantly associated with a higher number of mutations .
mutations in tp53 , atr and atm alone were associated with a higher number of mutations .
the tumours were divided in three separate groups based on an immunoscore reflecting the number of infiltrating cd8 + tlymphocytes , as defined by donnem et al.7 there was no significant association between immunoscore and the number of point mutations . however , when using the median stromal cd8score as cutoff ( high score n  =  58 , low score n  =  49 ) , there was a significant inverse correlation between the number of infiltrating stromal cd8 + lymphocytes and presence of egfr mutations ( r  =  0.21 , p  = 0.029 ) ( pearson  ) .
patients with more than the median number of mutations in their tumours had shorter relapsefree survival than patients with submedian mutation counts ( fig .
multivariate analysis of relapsefree survival was performed using cox regression to study the influence of known prognostic factors ( histology , stage , sex ) .
the number of mutations was not significantly associated with survival in a coxanalysis with number of mutations as a continuous variable ( p  =  0.60 ) .
however , the number of mutations ( over median ) was found to be significantly associated with time to progression after adjusting for clinical variables ( p  =  0.021 ) . there was a tendency toward increased relapsefree survival for patients with high cd8score ( p  =  0.10 ) .
by secondgeneration sequencing , we have confirmed that lung cancers are highly heterogeneous in terms of somatic mutation profiles , and that the number of mutations is associated with patient survival .
an improved understanding of tumour emergence relies on the identification of genes that drive carcinogenesis .
several bioinformatics approaches have been proposed to identify driver genes , all with shortcomings and particular biases.19 given the limited number of mutations per tumour kinome , we chose an approach ( intogen ) that emphasizes enrichment of clustered and functionally biased mutations .
this algorithm has previously demonstrated its capability of detecting cancer drivers.19 
  when applying the intogen algorithm on our dataset , tp53 , egfr , kras , and stk11 were identified as significant driver genes , as previously described.21 despite extensive efforts , no effective treatments targeting tp53 and kras have been presented up to now .
conversely , targeted treatment of mutated egfr has changed the prospects for the subset of patients with lung egfrmutationpositive lung cancers .
stk11 is a serine / threonine kinase and a tumour suppressor and has been ranked as the third most frequently mutated gene in lung cancers.22 it is implicated in cell polarity , energy metabolism , apoptosis , cell cycle arrest and proliferation .
the mutations observed were in the protein kinase domain , but are probably inactivating as stk11 is a tumour suppressor . other known genes involved in lung carcinogenesis , like alk and ros1 , were also mutated in a small subset of the tumours .
however , these genes are usually changed by inversions and translocations , not detected by our sequencing analysis .
they hamper tumour development , but unfortunately tumours can prevent sustained tcell responses via immune checkpoints .
unfortunately , good predictive biomarkers for response to checkpoint inhibitors are hitherto lacking.23 
  there have been several reports indicating that the effect of induced immuneresponse correlates with the number of mutations , with the novel immunotherapeutic checkpoint inhibitors having better efficacy on tumours with a high number of mutations.8 
 egfrmutated tumours generally have lower number of mutations.24 in our study , we found significantly more infiltrating stromal cd8 + tcells in tumours without egfr mutations .
this would be in accordance with a higher number of immunogenic antigens in tumours with a high number of mutations .
in addition , this is in accordance with the lack of cd8 + lymphocyte response in egfrmutant mice models and human tumours.25 
  mutations in dna repair genes would most often lead to repair defects , which would in turn allow certain types of mutations to accumulate . in our material , we find a significant association between number of mutations and mutated dna repair genes . whether the significantly higher number of mutations is a consequence of dysfunctional dna repair genes in these cases has not been determined .
clearly , our study is limited in size , so ruling out which genes in the dnarepair pathway are the most important should be studied more extensively , perhaps revealing a correlation of mutation signature to specific defects .
a total of only 28 samples were mutated in the dna repair genes . despite the modest number of samples in our cohort , we report a correlation between number of mutations and course of disease . in the present era of evolving immune therapies
, we believe this to be an important insight , which needs more attention in larger cohorts , and possibly with a further potential in the clinical setting .
 lung cancer is the leading cause of cancer related death , and the past years improved insight into underlying molecular events has significantly improved outcome for specific subsets of patients . in particular , several new therapies that target protein kinases have been implemented , and many more are becoming available . 
 we have investigated lung cancer specimens for somatic mutations in a targeted panel of 612 human genes , the majority being protein kinases . 
 the somatic mutation profiles were correlated to profiles of immune cell infiltration as well as relapsefree survival . targeted deep sequencing 
 was performed on 117 tumour / normal pairs using the sureselect human kinome kit ( agilent technologies ) , with capture probes targeting 3.2 mb of the human genome , including exons and untranslated regions of all known kinases , kinase receptors and selected cancerrelated genes ( 612 genes in total ) . 
 cd8 staining was determined using ventana benchmark . 
 survival analyses were performed using spss . 
 the number of mutations per sample ranged from 0 to 50 ( within the 612 genes tested ) , with a median of nine . 
 the prognosis was worse for patients with more than the median number of mutations . 
 a significant correlation was found between mutations in one of selected dnarepair genes and the total number of mutations in that tumour ( p  <  0.001 ) . there was a significant inverse correlation between the number of infiltrating stromal cd8 + lymphocytes and the presence of egfr mutations . 
Material and Methods
Results
Mutations in DNA repair genes
Immunoscore
Survival
Discussion