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Mutational profiling of glioblastoma

Bleeker, F.E.

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Citation for published version (APA):Bleeker, F. E. (2009). Mutational profiling of glioblastoma.

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Mutational profiling of kinases in glioblastoma

F.E. Bleeker1,2 • S. Lamba2 • C. Zanon2 • T.J. Hulsebos3

D. Troost4 • C.J.F. Van Noorden5 • W.P. Vandertop1,6 S. Leenstra7,8 • A.A. van Tilborg9 • A. Bardelli2,10

1Neurosurgical Center Amsterdam, Location Academic Medical Center, Amsterdam, The Netherlands;

2Laboratory of Molecular Genetics, The Oncogenomics Center, Institute for Cancer Research and Treatment,

University of Torino Medical School, Candiolo, Italy;

Departments of 3Neurogenetics, 4Neuropathology and 5Cell Biology and Histology, Academic Medical Center,

University of Amsterdam, Amsterdam, The Netherlands;

6Neurosurgical Center Amsterdam, Location VU University Medical Center, Amsterdam, The Netherlands;

7Department of Neurosurgery, Sint Elisabeth Ziekenhuis, Tilburg, The Netherlands;

Departments of 8Neurosurgery and 9Pathology, Erasmus Medical Center, Rotterdam, The Netherlands;

10FIRC Institute of Molecular Oncology, Milan, Italy.

Manuscript in preparation

Proefschrift Bleeker.indd 27 21-5-2009 15:03:40

28

AbstractGlioblastoma is a highly malignant brain tumor for which no cure is available. To identify new therapeutic targets, we performed a mutation analysis of kinase genes in glioblastoma. Database mining and a literature search identified 76 kinases that have been found to be mutated at least twice in multiple cancer types before. Among those we selected 34 kinase genes for detailed mutation analysis in glioblastoma. We also included PTEN, TP53 and NRAS, genes that are known to be mutated at high frequency in glioblastoma. In total, we sequenced 170 exons of 37 genes in 113 glioblastoma samples from 109 patients and 16 high-grade glioma (HGG) cell lines. Our analysis led to the identification of 125 non-synonymous somatic mutations, of which 30 have not been reported before in glioblastoma. Somatic mutations were found in TP53, PTEN, PIK3CA, EGFR, BRAF, EPHA3, NRAS, TGFRB2, FLT3 and RPS6KC1. When the mutated genes were mapped into known signaling pathways it became clear that the large majority of them plays central roles in the PI3K-AKT pathway. The knowledge that at least 50% of glioblastoma tumors display mutational activation of the PI3K-AKT pathway offers new opportunities for the rational development of therapeutic approaches for glioblastomas.

IntroductionCancer is a multi-step, polygenic disease, caused by accumulation of genetic alterations in oncogenes and/or tumor suppressor genes resulting in neoplastic transformation. The first transforming somatic mutation was described in the HRAS gene in human bladder cancer.1 Since then, transforming somatic mutations have been identified in numerous genes in various types of malignant tumors. In the last decade, sequencing of the human genome and development of high-throughput technologies have enabled the systematic analysis of the cancer genome.2-8 Genes encoding kinases are overrepresented in the group of cancer genes that have been found to be mutated.9 They form effective therapeutic targets in various types of cancer.10,11 The description of the 518 protein kinases constituting the ‘kinome’12 enabled systematic mutation analysis of protein and lipid kinases in colon cancer.2,6 Subsequently, mutational profiling studies were performed on the protein kinome in other cancer types,4 including glioblastoma.5,13

Glioblastoma is the most frequently occurring and most aggressive type of primary brain cancer in human. Glioblastomas are histopathologically characterized by nuclear atypia, high mitotic activity, microvascular proliferation (angiogenesis), necrosis and remarkable heterogeneity of histological and genetic features throughout the tumor and are classified as WHO grade IV.14 Glioblastoma is preferentially located in the cerebral hemispheres and is known for its widespread invasion, which makes complete resection virtually impossible. Treatment is intensive and consists of, if possible, a combination of surgical resection, radiotherapy and chemotherapy (temozolomide). However, the median survival remains limited to 15 months.15 Therefore, novel therapies are urgently needed. For rational drug design, it is essential to unravel the etiology of glioblastoma. Different genes have been found to be involved in glioblastoma, by changes in expression, methylation, copy number alterations or mutations. The best characterized mutation affects EGFR and codes for a

Chapter 3


29

truncated constitutively activated form which is known as EGFRv3. The question is whether other kinases could play a role as well by mutational activation in glioblastoma. Limited numbers of glioblastoma samples have been sequenced in kinase mutational screenings, without identification of frequently mutated kinases. This may be due to the limited number of samples.5,13 Therefore, we decided to perform a kinase mutation analysis in a large number of glioblastoma samples. Thirty-eight genes were sequenced in 113 glioblastoma tumors and 16 high-grade glioma (HGG) cell lines.

Materials and methodsSelection of genesA search strategy was performed by database mining for kinase mutations in cancer. This search included the Online Mendelian Inheritance in Man (OMIM) database of human genes and genetic disorders16 and the Catalogue of Somatic Mutations in Cancer (COSMIC).17 In addition, a literature search was performed using the key words ‘kinase*’ and ‘mutation*’ in Pubmed. In silico, 217 kinases were identified to be mutated in cancer and 76 had been reported to contain non-synonymous somatic mutations in at least two independent tumor samples in the literature. We selected 34 of these 76 kinases for mutation analysis. In addition, we included NRAS, PTEN and TP53. Specifically, we examined 170 exons in which mutations have been previously described for the following genes: AKT2, ATM, ATR, BRAF, BRD2, DDR1, DYRK2, EGFR, EPHA3, EPHA5, EPHA6, EPHB2, ERBB2, ERBB4, FGFR1, FGFR2, FGFR3, FGFR4, FLT1, FLT3, FRAP1, KDR, KIT, MAP2K4, MET, NRAS, NTRK2, NTRK3, PAK4, PDGRA, PDPK1, PIK3CA, PTEN, RPS6KC1, STK11, TGFBR2 and TP53.

Patients, tumor samples and DNA extractionOne hundred and thirteen glioblastoma samples were obtained from 109 patients from the tumor bank maintained by the Departments of Neurosurgery and Neuropathology at the Academic Medical Center (Amsterdam, The Netherlands). The samples have been collected from patients treated at the Academic Medical Center with brain tumor surgery, according to protocols approved by the institutional ethical committee. In addition, 16 high-grade glioma cell lines were included: the cell lines CCF-STTG1, Hs683, U87MG, U118MG, U251MG, U373MG, T98G (ATCC, Middlesex, United Kingdom), GAMG (Deutsche Sammlung von Mikroorganismen und Zellkulturen, Braunschweig, Germany), SKMG-3 (a gift of Dr C.Y. Thomas, University of Virginia Division of Hematology/Oncology, Charlottesville, VA), D384MG, SF763 (gifts of Dr M.L. Lamfers, Department of Neurosurgery, VU University, Amsterdam, The Netherlands), SF126 (a gift of Dr C. Van Bree, Department of Radiotherapy, Academic Medical Center) and the xenograft cell line IGRG121 (a gift of Dr B. Geoerger, Institut Gustave Roussy, Villejuif, France). A58, A60 and Gli-6 cell lines were derived from our own laboratory.18,19 Genomic DNA was isolated as previously described.20 Matching between germline and tumor DNA was verified by direct sequencing of 26 single nucleotide polymorphisms (SNPs) at 24 loci (data not shown). Sample details are shown in Figure 1.



30

PCR and sequencing detailsPCR and sequencing primers were designed using Primer 321 and synthesized by InvitrogenTM

(Life Technologies, Paisley, UK). PCR primers were designed to amplify the selected 170 exons and the flanking intronic sequences (including splicing donor and acceptor regions) of the genes. PCR products were approximately 400 bp in length with multiple overlapping amplimers for larger exons. For each sample, 185 PCRs were performed. PCRs were performed in both 384- and 96-well formats in 5 or 10 µl reaction volumes, respectively, containing 0.25 mM deoxynucleotide triphosphates (dNTPs), 1 mM each of forward and reverse primer, 6% dimethylsulfoxide (DMSO), 1X PCR buffer, 0.05 U/µl Platinum Taq InvitrogenTM and 1 ng/µl DNA. A touchdown PCR program was used for PCR amplification (Peltier Thermocycler PTC-200; MJ Research, Bio-Rad Laboratories, Milan, Italy). PCR conditions were: 94°C for 2 min; 3 cycles of 94°C for 15 sec; 64°C for 30 sec, 70°C for 30 sec, 3 cycles of 94°C for 15 sec, 61°C for 30 sec, 70°C for 30 sec, 3 cycles of 94°C for 15 sec, 58°C for 30 sec, 70°C for 30 sec, and 35 cycles of 94°C for 15 sec, 57°C for 30 sec and 70°C for 30 sec, followed by 70°C for 5 min and 12°C forever. PCR products were purified using AMPure® (Agencourt Bioscience Corporation, Beckman Coulter, Milan, Italy) and eluted in distilled water. Sequencing PCRs were carried out at 97°C for 3 min, and 29 cycles of 97°C for 10 sec, 50°C for 20 sec and 60°C for 2 min. Sequencing PCR products were purified using CleanSeq® (Agencourt Bioscience Corporation). Direct sequencing was performed using BigDye® Terminator v3.1 Cycle Sequencing Kit (Applied Biosystems, Foster City, CA) with a 3730 DNA Analyzer, ABI capillary electrophoresis system (Applied Biosystems). Sequence traces were analyzed using Mutation Surveyor software (Version 2.02; SoftGenetics, State College, PA).

Figure 1. Mutation analysis screen details

Chapter 3

217 Kinases mutated in cancer

~ 550 Kinases

76 Kinases mutated in cancer:≥ 1 Non-synonymous

somat ic mutat ion≥ in 2 samples

Selec�on of 34 kinases & NRAS & PTEN & TP53

(185 amplicons for 170 exons)

129 Glioblastoma samples

- 16 HGG cell lines

- 113 Glioblastoma tumors

•17 Secondary

•11 Recurrent (4 with primary)

Sequencing of 37 genes in 129 samples

Total of 23.865 PCRs covering 9.5 Mb of coding tumor DNA


31

CloningFor cloning of the PCR products the pcDNA™3.3-TOPO® TA Cloning Kit (Invitrogen) was used according to the manufacturer’s guidelines. The TOPO ligation reaction (containing 2 µl of fresh PCR product and 1 µl TOPO vector) was incubated for 5 min at room temp. Competent E. coli were transformed with the TOPO cloning reaction and spread on a pre-warmed selective plate (ampicillin). Plates were incubated at 37°C overnight. White colonies were picked for PCR analysis and sequencing, using the protocol described above.

Statistical analysisStatistical processing of data was performed using Excel 2002 (Microsoft, San Jose, CA) and SPSS 16.02 for Windows (SPSS, Chicago, IL). Associations between the different mutations were assessed by the Fisher’s exact test. Mutation rates were compared by means of the binomial test. A retrospective survival analysis was performed on 98 newly diagnosed adult glioblastoma patients of whom follow-up was available. Characteristics of these patients are displayed in Table 1. The primary end point of this analysis was survival. Overall survival time was calculated as time from surgery to death. Event times were censored if the patient was alive at the time of last follow-up. Follow-up for included patients ranged from 15 to 2722 days. Additional therapies, besides irradiation, include chemoradiation (radiotherapy with concomitant and adjuvant temozolomide), brachytherapy, Gliadel, PCV, temozolomide, MTX and nicotinamine. The association between mutations and survival time was tested with Cox proportional hazard models. After the individual tests, factors with P values less than 0.10 were included in the multivariate Cox model to determine the factors that are associated with survival time after adjustment for the other factors.

Characteristic Mean or number

Age (years) 53 (27-80)KPS 76 (50-90)Irradiation dosage (Gy) 41 (0-78)Gender M 53 (54%)

F 45 (46%)Surgical procedure Biopsy or irradical resection 41 (42%)

Gross total removal 57 (59%)Other therapy No additional therapy 61 (62%)

Additional therapy 37 (38%)Tumor occurrence Primary glioblastoma 85 (87%)

Secondary glioblastoma 13 (13%)PIK3CA Wild-type 87 (89%)

Mutated 11 (11%)PTEN Wild-type 74 (75%)

Mutated 24 (25%)TP53 Wild-type 60 (61%)

Mutated 38 (39%)

Table 1. Baseline characteristics of 98 newly diagnosed adult glioblastoma patients in survival analysis Data are mean (range) or number (%). Abbreviations: F, Female; Gy, Gray; M, Male; KPS, Karnofsky performance score.



32

Results and discussionIn the present study, a total of 23.865 PCR products, covering 9.5 Mb of tumor genomic DNA, were generated and subjected to direct sequencing. Over 5.000 nucleotide changes were identified during this initial screening. Changes previously described as SNPs were excluded from further analyses. To ensure that the observed mutations were not PCR or sequencing artifacts, amplicons were independently re-amplified and resequenced in the corresponding tumors. All verified changes were resequenced in parallel with the matched normal DNA to distinguish between somatic mutations and SNPs not previously described. Mutational screening details are depicted in Figure 1.

This approach led to the identification of 125 somatic mutations in 129 samples. Somatic mutations were found in TP53 (60), PTEN (38), PIK3CA (12), EGFR (7), BRAF (3), EPHA3 (1), NRAS (1), TGFRB2 (1), FLT3 (1) and RPS6KC1 (1). Mutated genes and mutation frequencies are reported in Table 2. For PIK3CA and PTEN, genes mutated at considerable frequency in our study, the mutation frequencies are not different from previous reports22-24. The mutation frequency of TP53 is slightly higher than reported.22,23 Regarding TP53, we identified seven samples with two mutations in TP53. When corrected for mutated single samples, the mutation percentage is 41%, still slightly higher than reported. In contrast, for EGFR the mutation frequency is lower than reported,25 due to the fact that we only sequenced exons belonging to the kinase domain, whereas mutations were predominantly found in the extracellular domain.25

The observed mutation rate of all non-synonymous somatic mutations (13.2 mutation/Mb) was higher than the expected ‘passenger’ mutation rate26 (P < 1x10-15, binomial distribution), indicating that most of these mutations probably represent ‘driver’ mutations. Seventy-three out of 113 (65%) glioblastoma tumors displayed at least one somatic mutation; no mutation was identified in 39 glioblastoma tumors. In all cell lines at least one mutation in TP53 or PTEN was found. The maximum number of mutations in a single sample was three, occurring in both tumor and cell line samples. No differences in non-silent mutation rate between

Table 2. Mutated genes and mutation frequenciesMutated genes and mutation percentages identified in 129 glioblastoma samples and HGG cell lines

Gene Mutation number Mutation %

TP53 60 47PTEN 38 29PIK3CA 12 9EGFR 7 5BRAF 3 2EPHA3 1 1NRAS 1 1RPS6KC1 1 1FLT3 1 1TGFBR2 1 1

Chapter 3


33

Figure 2. Somatic mutation confirmed by cloning A, chromatogram of matched normal blood sample; B, chromatogram of tumor sample; C, chromatogram of cloned PCR product. Arrows, location of missense somatic mutations. Numbers above the sequences are part of the software output. PIK3CA, c.158A>G, p.M2V.


untreated samples and recurrent samples treated prior with temozolomide chemotherapy were found. Only non-silent mutations were further investigated to determine whether they were somatic or not. Therefore, it is impossible to conclude whether samples derived from patients that had been pretreated with temozolomide developed a hypermutator phenotype. This has been described for other glioblastoma samples after temozolomide treatment.5 Remarkably, no additional mutations were observed in the four recurrent tumors compared to their primary glioblastomas, which were included in the study as well. As of now, all analyses are performed on 109 single samples. Mutations in samples derived from 109 patients and 16 cell lines are shown in Table 3.

Some of the mutations were probably present in a small fraction of cancer cells since their mutated status could not be validated by an independent PCR. Cloning of the PCR product helped to confirm the mutation in all tested samples. An example is shown in Figure 2. For some amplicons, the PCR reaction failed twice, as occurred for example for exon 4 of PTEN in the SKMG-3 cell line. This cell-line is known for a deletion containing exon 4.27 Hence, in this case, the incapacity of amplification is probably caused by the deletion.

A

B

C


34

No new mutation hotspot was identified in the sequenced exons of the selected genes. However, we found 30 novel somatic mutations in glioblastoma. This supports the theory that tumor types may have their own mutated cancer candidate genes, and only a few of these genes are shared by different tumor types.28 Furthermore, the mutations themselves, rather than the genes, may be tumor-specific. Therefore, we cannot exclude that other exons of the genes may exhibit a more frequently mutated genotype. Notably, glioblastomas do exhibit different mutation spectra for some genes as compared to other tumor types. For example, most EGFR and ERBB2 mutations in lung cancer are found in the kinase domain29,30 and that is why we included those regions in our study. However, recent studies show that these genes are predominantly mutated in the extracellular domain in glioblastoma.25,31

Some of the mutations that we found do affect kinases, for example EPHA3. These are clearly amenable to pharmacologic intervention and represent potential novel therapeutic targets for glioblastoma. Functional analysis is required in order to assess their roles in cancer.

In the present study, heterozygous and homozygous mutations in both oncogenes and tumor suppressor genes have been identified. Various TP53 alleles (TP53R175H, TP53R248W and TP53R273C/H) showed both homozygous and heterozygous mutations in distinct samples. Proto-oncogenes are affected by heterozygous mutations to activate the oncogenic protein, and tumor suppressor genes need to lose both alleles before their suppressive function is diminished, according to the Knudson theory.32 This may explain why two heterozygous mutations were found affecting the tumor suppressor gene in a single sample, as we observed six times for TP53. The mutations were either located close to each other in the same exon, or in different exons. However, haplo-insufficient tumor suppressor genes have been described.33 Therefore, the loss of one allele can already stop the tumor suppressive function of some tumor suppressor proteins. The finding of both a homozygous and heterozygous mutation affecting TP53 in a single glioblastoma sample may be explained by the presence of both a passenger and a driver mutation.

Different mutation spectra were observed for the PTEN and TP53 tumor suppressor genes. In PTEN many mutations (13/37; insertions, deletions and point mutations) were leading to a premature stop codon. In TP53 most mutations consisted of missense mutations, and only eight were causing a premature stop codon (8/59) (P = 0.02, Fisher’s exact test). In PTEN, seven mutations affecting splice sites were identified; in TP53 only one (P = 0.005, Fisher’s exact test).

Identified mutations in cell lines were consistent with previous studies as far as reported by COSMIC.17 In all cell lines at least one mutation in TP53 or PTEN was found. No PIK3CA mutations were found in any of the cell lines examined. Compared to the mutation frequency (11%) that we found in 109 glioblastoma samples, the lack of PIK3CA mutations in our panel of 16 HGG cell lines is remarkable, because glioblastoma cell lines with PIK3CA mutations have been described.24 Two cell lines generated from glioblastoma samples included in our mutational screen were also subjected to the mutation analysis we performed. Surprisingly, mutations in the cell lines were found in homozygosity, whereas the same mutations in the

Chapter 3


35

original tumor were heterozygous. We included tumor samples only if at least 80% of the sample consisted of cancer cells, as verified by H&E staining. Therefore, we considered the chance of contamination by normal brain to be small. Established cell lines derived from glioblastoma resemble the original tumors in patients poorly when compared at the level of DNA alterations.18,34 Therefore, one allele of the genes might have been lost during the establishment of the cell lines or during cell culture afterwards.

Most glioblastoma manifest rapidly de novo, without recognizable precursor lesions. In contrast, secondary glioblastomas are diagnosed in patients with a preceding low-grade glioma, which in years progress to glioblastoma.35,36 Both subtypes are considered to be histopathologically indistinguishable, but differences in molecular alterations are apparent. Primary glioblastomas have a high rate of EGFR alterations, MDM2 duplications, PTEN mutations and homozygous CDKN2A deletions, whereas TP53 mutations are most prevalent in secondary glioblastomas.22,35 In our set of 109 glioblastomas, mutations in PTEN were significantly more frequent in primary glioblastomas (P = 0.01, Fisher’s exact test). Although most secondary glioblastomas contained a TP53 mutation (10/12), no significant differences in mutation frequency in PIK3CA and TP53 mutations were observed between primary and secondary glioblastomas. This may be due to the relatively small set of secondary glioblastomas.

PIK3CA has been found to be mutated in various tumor types, particularly the exons 9 and 20, and to a lesser extent exon 1 has been found to contain mutations.7,37 In our glioblastoma set, five out of 12 mutations in PIK3CA were located in exon 1, two and three mutations in exon 9 and exon 20, respectively. Three of the five mutations in exon 1 have not been reported before, and one of these mutations was present in two independent tumor samples. PIK3CA and PTEN mutations were found mutually exclusive in our set of glioblastomas, as was previously observed in glioblastoma38,39 and other tumor lineages.40,41 This suggests that they exert overlapping cellular functions. Both the lipid kinase PI3K and the phosphatase PTEN act as central regulators of the PI3K-AKT pathway by controlling the cellular levels of phosphatidylinositol-3-phosphate. Mutations in the PIK3CA oncogene result in increased PI3K catalytic activity and constitutive downstream signaling. The tumor suppressor protein PTEN counteracts the effect of PI3K and acts as a negative regulator of PI3K signaling.42

We assessed whether any of the frequently identified mutations are an independent prognostic factor for survival in 98 glioblastoma patients (Table 1). When corrected for age, Karnofsky performance status (KPS), extent of surgery, received dosage of radiotherapy, chemotherapy or other treatment besides radiotherapy, mutations in PTEN and/or PIK3CA (Tables 4 and 5), mutations in TP53 were an independent prognostic factor for improved overall survival (P < 0.001; Figure 3 and Table 5). In previous studies, TP53 mutations were negatively associated with survival or not associated with survival at all.22,23 In one study, TP53 mutations had positive prognostic effects in younger patients and negative effects on prognosis in older patients.43 In general, TP53 is not acknowledged as a prognostic factor.14



36

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Chapter 3


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H

omU

118

IVS8

+1G

>T10

26+1

G>T

Hom

R213

Q63

8G>A

Hom

U25

1MG

E242

fs*1

572

3_72

4ins

TT

Hom

R273

H81

8G>A

Hom

U37

3MG

E242

fs*1

572

3_72

4ins

TT

Hom

R273

H81

8G>A

Hom

U87

IVS3

+1G

>T20

9+1G

>TH

omEP

HA

3 RP

S6KC

1K5

00N

Q

741*

1725

G>T

22

18C>

TH

et

Hom

SF12

6G

129R

385G

>AH

omSF

-763

R158

L47

3G>T

Hom

A58

T319

fs*2

957d

elC

Hom

R248

Q74

3G>A

Hom

A60

K13E

A37

GH

omCC

F-ST

TG1

L112

R33

5 T>

GH

om

D38

4A

159V

476C

>TH

omG

AM

GL2

65P

794T

>C

Hom

Hs6

83R2

48Q

743G

>AH

omIG

RG-1

21Y2

25*

675T

>GH

om

Tabl

e 3.

Iden

tifie

d m

utati

ons

For

each

mut

ation

the

pro

tein

and

cD

NA

ann

otati

on a

nd z

ygos

ity a

re s

how

n. M

utat

ed p

atien

t sa

mpl

es a

re li

sted

. To

our

know

ledg

e, m

utati

ons

depi

cted

in re

d ar

e no

vel i

n ca

ncer

, mut

ation

s in

blu

e ha

ve b

een

repo

rted

in c

ance

r bu

t are

nov

el in

glio

blas

tom

a. A

bbre

viati

ons:

Hom

, hom

ozyg

ous;

Het

, het

eroz

ygou

s.



38

In conclusion, molecular profiling of tumor genomes has provided a comprehensive list of mutated cancer genes and of the signaling pathways they control. Among others, these efforts have led to the discovery that the PI3K-AKT pathway is more frequently activated by genomic aberrations than any other signaling pathway in many tumor types.28,44 Similarly, we found most mutations in genes belonging to the PI3K-AKT pathway; in at least 50% of glioblastomas, mutational activation of this pathway was observed. Therefore, the PI3K-AKT pathway represents an interesting therapeutic target for glioblastomas.

Characteristic HR 95% CI P value

Age, per year 1.028 1.012 to 1.045 0.001Sex (male vs female) 1.114 0.728 to 1.799 0.559KPS, per 10 points 0.969 0.949 to 0.989 0.002Resection (gross total removal vs biopsy or resection)

0.628 0.402 to 0.980 0.040

Irradiation dosage, per Gy 0.979 0.970 to 0.987 < 0.001Other therapy (additional therapy vs non-additional therapy)

0.415 0.261 to 0.660 < 0.001

Secondary vs primary glioblastoma 0.598 0.305 to 1.172 0.134TP53 mutated vs wild-type 0.520 0.322 to 0.840 0.007PIK3CA mutated vs wild-type 0.369 0.156 to 0.874 0.023PTEN mutated vs wild-type 1.824 1.101 to 3.022 0.020

Table 4. Univariate association between patient characteristics and survival Abbreviations: KPS, Karnofsky Performance Score; HR, Hazard Ratio; CI, Confidential Interval.

Table 5. Multivariate association between patient characteristics and survival Abbreviations: KPS, Karnofsky Performance Score; HR, Hazard Ratio; CI, Confidential Interval.

Characteristic HR 95% CI P value

Age, per year 1.027 1.008 to 1.046 0.006KPS, per 10 points 0.976 0.955 to 0.997 0.023Resection (biopsy or resection vs gross total removal)

1.318 0.776 to 2.239 0.306

Irradiation dosage, per Gy 0.981 0.970 to 0.992 0.001Other therapy (non-additional therapy vs additional therapy)

1.544 0.865 to 2.755 0.142

PIK3CA mutated vs wild-type 0.669 0.278 to 1.613 0.371PTEN mutated vs wild-type 1.518 0.865 to 2.663 0.146TP53 mutated vs wild-type 0.375 0.221 to 0.635 < 0.001

Chapter 3


39

AcknowledgementsThe authors like to thank Dr P.C. de Witt Hamer for his help with kinase selection, Prof Dr A. Zwinderman and Dr N. van Geloven for their advice on the statistical analyses. This work was supported by grants from ABC2 (AvT), Italian Association for Cancer Research (AIRC; AB), Italian Ministry of Health, Regione Piemonte (AB), Italian Ministry of University and Research, CRT Progetto Alfieri (AB), Association for International Cancer Research (AICR-UK; AB) and EU FP6 contract 037297 (AB). F.E. Bleeker is supported by a NWO travel grant and a Netherlands Genomic Initiative Fellowship.

Figure 3. Adjusted survival curves for TP53 wild-type and mutated glioblastoma patientsSurvival curves for TP53 wild-type and mutated glioblastoma patients constructed using multivariate Cox proportional hazards regression adjusted for age, Karnofsky performance score, resection, irradiation, additional treatments and mutations in PTEN and PIK3CA.

TP53 wild-typeTP53 mutated

Survival (days)

Ove

rall

surv

ival

(pro

babi

lity)



40

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