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PDF file - 636KB, Supplemental Table S1: information of the GBM lines used in this paper. Supplemental Table S2: information of the patient clinical data for Figure 1. Supplemental Table S3: Percentage of cells positive for staining with PRMT5 in spontaneous high grade astrocytoma from Mut3 strain (GFAP-cre; cisNf1-/+; P53-/-) and normal brain tissue from wild-type control mouse stained by PRMT5 and ki-67 antibody. Supplemental table S4. GBM cell line (U251) was transfected by scramble control or si-PRMT5. Affymetrix microarray genechip was performed in three independent experiments to evaluate genes up-regulated with PRMT5 silencing.

PDF file - 1690KB, Supplemental Figure S1. PRMT5 is over-expressed in human GBM cell lines. Supplemental Figure S2: High grade astrocytomas Supplemental Figure S3: efficacy and specificity of PRMT5 knock-down by lead siRNA. Supplemental Figure S4: PRMT5 Knockdown promotes cell death of human GBM cells Supplemental Figure S5: si-PRMT5 induced cell death is P53-independent Supplemental Figure S6: Decreased ST7 expression correlates with worse survival in all glioma patients (grade I-IV). Supplemental Figure S7: Over-expression of ST7 in three GBM cell lines was confirmed by real-time PCR and western blot (top panels).

Glioblastoma is the most common and aggressive histologic subtype of brain cancer with poor outcomes and limited treatment options. Here, we report the selective overexpression of the protein arginine methyltransferase PRMT5 as a novel candidate theranostic target in this disease. PRMT5 silences the transcription of regulatory genes by catalyzing symmetric dimethylation of arginine residues on histone tails. PRMT5 overexpression in patient-derived primary tumors and cell lines correlated with cell line growth rate and inversely with overall patient survival. Genetic attenuation of PRMT5 led to cell-cycle arrest, apoptosis, and loss of cell migratory activity. Cell death was p53-independent but caspase-dependent and enhanced with temozolomide, a chemotherapeutic agent used as a present standard of care. Global gene profiling and chromatin immunoprecipitation identified the tumor suppressor ST7 as a key gene silenced by PRMT5. Diminished ST7 expression was associated with reduced patient survival. PRMT5 attenuation limited PRMT5 recruitment to the ST7 promoter, led to restored expression of ST7 and cell growth inhibition. Finally, PRMT5 attenuation enhanced glioblastoma cell survival in a mouse xenograft model of aggressive glioblastoma. Together, our findings defined PRMT5 as a candidate prognostic factor and therapeutic target in glioblastoma, offering a preclinical justification for targeting PRMT5-driven oncogenic pathways in this deadly disease. Cancer Res; 74(6); 1752–65. ©2014 AACR.

Gliomas are the most common primary intracranial neoplasms, which cause significant mortality and morbidity that is disproportionate to their relatively rare incidence. Many potential risk factors for glioma have been studied to date, but only few provide explanation for the number of brain tumor cases identified. The most significant findings include increased risk due to exposure to ionizing radiation and decreased risk with the history of allergy or atopic diseases. The potential effect of the cellular phone usage has been evaluated extensively, but the results remain inconclusive. A very small proportion of gliomas can be attributed to inherited genetic disorders. Additionally, recent analyses using the genome-wide association study design have identified several inherited genomic risk variants.

Gliomas are the most common primary intracranial neoplasms, which cause significant mortality and morbidity that is disproportionate to their relatively rare incidence. Many potential risk factors for glioma have been studied to date, but only few provide explanation for the number of brain tumor cases identified. The most significant findings include increased risk due to exposure to ionizing radiation and decreased risk with the history of allergy or atopic diseases. The potential effect of the cellular phone usage has been evaluated extensively, but the results remain inconclusive. A very small proportion of gliomas can be attributed to inherited genetic disorders. Additionally, recent analyses using the genome-wide association study design have identified several inherited genomic risk variants.

Background To elucidate molecular features associated with disproportionate survival of glioblastoma (GB) patients, we conducted deep genomic comparative analysis of a cohort of patients receiving standard therapy (surgery plus concurrent radiation and temozolomide); "GB outliers" were identified: long-term survivor of 33 months (LTS; n = 8) versus short-term survivor of 7 months (STS; n = 10). Methods We implemented exome, RNA, whole genome sequencing, and DNA methylation for collection of deep genomic data from STS and LTS GB patients. Results LTS GB showed frequent chromosomal gains in 4q12 (platelet derived growth factor receptor alpha and KIT) and 12q14.1 (cyclin-dependent kinase 4), and deletion in 19q13.33 (BAX, branched chain amino-acid transaminase 2, and cluster of differentiation 33). STS GB showed frequent deletion in 9p11.2 (forkhead box D4-like 2 and aquaporin 7 pseudogene 3) and 22q11.21 (Hypermethylated In Cancer 2). LTS GB showed 2-fold more frequent copy number deletions compared with STS GB. Gene expression differences showed the STS cohort with altered transcriptional regulators: activation of signal transducer and activator of transcription (STAT)5a/b, nuclear factor-kappaB (NF-κB), and interferon-gamma (IFNG), and inhibition of mitogen-activated protein kinase (MAPK1), extracellular signal-regulated kinase (ERK)1/2, and estrogen receptor (ESR)1. Expression-based biological concepts prominent in the STS cohort include metabolic processes, anaphase-promoting complex degradation, and immune processes associated with major histocompatibility complex class I antigen presentation; the LTS cohort features genes related to development, morphogenesis, and the mammalian target of rapamycin signaling pathway. Whole genome methylation analyses showed that a methylation signature of 89 probes distinctly separates LTS from STS GB tumors. Conclusion We posit that genomic instability is associated with longer survival of GB (possibly with vulnerability to standard therapy); conversely, genomic and epigenetic signatures may identify patients where up-front entry into alternative, targeted regimens would be a preferred, more efficacious management.

Glioblastoma (GBM) is an aggressive, malignant brain tumor typically resulting in death of the patient within one year following diagnosis; and those who survive beyond this point usually present with tumor recurrence within two years (5-year survival is 5%). The genetic heterogeneity of GBM has made the molecular characterization of these tumors an area of great interest and has led to identification of molecular subtypes in GBM. The availability of sequencing platforms that are both fast and economical can further the adoption of tumor sequencing in the clinical environment, potentially leading to identification of clinically actionable genetic targets. In this pilot study, comprised of triplet samples of normal blood, primary tumor, and recurrent tumor samples from three patients; we compared the ability of Illumina whole exome sequencing (ExomeSeq) and the Ion AmpliSeq Comprehensive Cancer Panel (CCP) to identify somatic variants in patient-paired primary and recurrent tumor samples. Thirteen genes were found to harbor variants, the majority of which were exclusive to the ExomeSeq data. Surprisingly, only two variants were identified by both platforms and they were located within the PTCH1 and NF1 genes. Although preliminary in nature, this work highlights major differences in variant identification in data generated from the two platforms. Additional studies with larger samples sizes are needed to further explore the differences between these technologies and to enhance our understanding of the clinical utility of panel based platforms in genomic profiling of brain tumors.

Glioblastoma (GBM) is a prototypical heterogeneous brain tumor refractory to conventional therapy. A small residual population of cells escapes surgery and chemoradiation, resulting in a typically fatal tumor recurrence ∼7 mo after diagnosis. Understanding the molecular architecture of this residual population is critical for the development of successful therapies. We used whole-genome sequencing and whole-exome sequencing of multiple sectors from primary and paired recurrent GBM tumors to reconstruct the genomic profile of residual, therapy resistant tumor initiating cells. We found that genetic alteration of the p53 pathway is a primary molecular event predictive of a high number of subclonal mutations in glioblastoma. The genomic road leading to recurrence is highly idiosyncratic but can be broadly classified into linear recurrences that share extensive genetic similarity with the primary tumor and can be directly traced to one of its specific sectors, and divergent recurrences that share few genetic alterations with the primary tumor and originate from cells that branched off early during tumorigenesis. Our study provides mechanistic insights into how genetic alterations in primary tumors impact the ensuing evolution of tumor cells and the emergence of subclonal heterogeneity.

Somatic copy number alterations, or CNAs, are frequent occurrences in the tumor landscape and can present in the form of focal alterations or as chromosome level events. Reliable detection of CNAs is crucial to understanding the impact of these events on a wide range of factors including tumor progression and treatment outcomes. The clinical use of NGS panels, and more recently exomes, continues to expand in cancer but the reliable detection of CNAs remains a challenge. A major factor contributing to the challenge is the availability of reliable tools that have been well tested and validated. We sought to characterize the sensitivity and specificity of multiple CNA detection tools with a focus on clinically relevant genes in NGS panel and whole-exome. Our approach utilized a variety of publicly available CNA tools to identify whole gene amplifications and deletions in a set clinically relevant genes identified in the Catalogue of Somatic Mutations in Cancer (COSMIC) database. The tested CNA tools included two that supported both whole exome and panel NGS data, allowing cross platform in addition to cross tool comparisons. This work involved more than 20 well characterized cell lines derived from a broad spectrum of tumor types, including breast, lung, melanoma, and prostate cancers. The cell lines were analyzed in both tumor/normal and tumor only (which utilizes a proxy normal) modes. Analyses of patient-matched and proxy-normal data were performed with both assays. Using our approach, we were able to identify clinically relevant CNAs on both platforms. The performance of the tools tested varied, with some tools performing best on either amplification or deletion events. These results represent a comprehensive comparison of recent copy number alteration tools and provides data that can be utilized to make the tools even more robust and reliable. Citation Format: Selene M. Virk, Sean Michael Boyle, Ravi Alla, Jennifer Yen, Richard Chen. Comparative analysis of multiple copy number alteration tools in the detection of amplifications and deletions on both whole-exome and targeted NGS panel platforms [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 5368. doi:10.1158/1538-7445.AM2017-5368

Gliomas are the most common type of primary intracranial tumors. Some glioma subtypes cause significant mortality and morbidity that are disproportionate to their relatively rare incidence. A very small proportion of glioma cases can be attributed to inherited genetic disorders. Many potential risk factors for glioma have been studied to date, but few provide explanation for the number of brain tumors identified. The most significant of these factors includes increased risk due to exposure to ionizing radiation, and decreased risk with history of allergy or atopic disease. The potential effect of exposure to cellular phones has been studied extensively, but the results remain inconclusive. Recent genomic analyses, using the genome-wide association study (GWAS) design, have identified several inherited risk variants that are associated with increased glioma risk. The following chapter provides an overview of the current state of research in the epidemiology of intracranial glioma.

To evaluate evolutionary patterns of GBM recurrence, we analyzed whole genome sequencing (WGS) and multi-sector exome sequencing data from pairs of primary and posttreatment GBM. WGS on ten primary-recurrent pairs detected a median number of 12,214 mutations which we utilized to uncover clonal structures, by analyzing the distribution of mutation cellular frequencies (the fraction of tumor cells harboring a mutation). On average, 41 % of the mutations were shared by primary and recurrence. The majority of shared mutations were clonal in both primary and recurrence, but we also observed many clonal mutations that were uniquely detected in either the primary or the recurrence. This raises the intriguing possibility that major tumor clones in the primary tumor and disease relapse both evolved from a shared ancestral tumor cell population. At least one subclone was identified in the majority of WGS samples, and we observed groups of mutations that were at low cancer cell fractions in both primary and recurrence, suggesting that both subclones evolved from the same ancestral tumor cells separate from the major clone ancestral cells. To address the possibility that the lack of overlap between subsequent tumors was due to intratumoral heterogeneity, we analyzed exome sequencing from a second tumor sector of seven primary and six recurrent tumors. We found that the majority of "second biopsy" mutations were not conserved between time points, suggesting that intratumoral heterogeneity did not explain the large number of mutations uniquely detected in primary and recurrence. The limited overlap of mutations in primary and recurrence provides evidence for ancestral tumor cell populations that could not be eradicated by therapy, while offspring cell populations contained unique mutations, were selectively killed by treatment and could therefore no longer be detected after disease relapse. This study has provided new insights into patterns and dynamics of tumor evolution.

Glioblastoma is the most common and aggressive histologic subtype of brain cancer with poor outcomes and limited treatment options. Here, we report the selective overexpression of the protein arginine methyltransferase PRMT5 as a novel candidate theranostic target in this disease. PRMT5 silences the transcription of regulatory genes by catalyzing symmetric dimethylation of arginine residues on histone tails. PRMT5 overexpression in patient-derived primary tumors and cell lines correlated with cell line growth rate and inversely with overall patient survival. Genetic attenuation of PRMT5 led to cell-cycle arrest, apoptosis, and loss of cell migratory activity. Cell death was p53-independent but caspase-dependent and enhanced with temozolomide, a chemotherapeutic agent used as a present standard of care. Global gene profiling and chromatin immunoprecipitation identified the tumor suppressor ST7 as a key gene silenced by PRMT5. Diminished ST7 expression was associated with reduced patient survival. PRMT5 attenuation limited PRMT5 recruitment to the ST7 promoter, led to restored expression of ST7 and cell growth inhibition. Finally, PRMT5 attenuation enhanced glioblastoma cell survival in a mouse xenograft model of aggressive glioblastoma. Together, our findings defined PRMT5 as a candidate prognostic factor and therapeutic target in glioblastoma, offering a preclinical justification for targeting PRMT5-driven oncogenic pathways in this deadly disease. Cancer Res; 74(6); 1752–65. ©2014 AACR.

Despite the general poor prognosis for patients with GBM, a proportion survives well beyond the median survival of 12-14 months following diagnosis. To elucidate molecular features associated with disproportionately protracted survival, we conducted deep genomic comparative analysis of a cohort of patients receiving standard therapy (surgery plus concurrent radiation and temozolomide) wherein “GBM outliers” were identified: patients who responded (long-term survivor, LTS) versus those who failed rapidly (short-term survivor, STS). The datasets enabled interrogation for signatures indicative of tumor vulnerability. Whole genomic, transcriptomic and epigenetic analyses of 18 patients, including 8 LTS with an average 30 months overall survival (OS) and 10 STS with an average of 7 months OS were performed to capture single nucleotide variants (SNVs), indels, translocations, intra-chromosomal rearrangements, copy number variants, along with DNA methylation and mRNA expression. LTS and STS cases showed equal proportion of 7p11.2 (EGFR) amplification and 9p21.3 (CDKN2A) deletion. However, LTS GBM showed frequent chromosomal gains in 4q12 (PDGFRA and KIT) and 12q14.1 (CDK4) and deletion in 19q13.33 (BAX, BCAT2 and CD33), whereas, STS GBM showed frequent deletion in 9p11.2 (FOXD4L2 and AQP7P3) and 22q11.21 (HIC2). In addition, LTS GBM showed a 2-fold increased copy number alteration (specifically deletion) as compared to STS GBM. By gene expression analysis, supervised clustering using the CIN70 signature (prognostic) showed an increased expression in STS GBM. Overall, whole genome methylation analyses showed that STS GBM tumors harbor more hypomethylation in probes situated in -200 bp of transcription start site (TSS) and both exon 1 and 5’UTR region. A methylation signature consist of 89 probes distantly separate LTS from STS GBM tumors. We posit that genomic instability (broadly inclusive) is associated with vulnerability of GBM to standard therapy; conversely, genomic instability coupled with genetic and epigenetic signatures may identify patients where up-front entry into alternative, targeted regimens would be a preferred, more-efficacious management. Supported by a grant from the Ben & Catherine Ivy Foundation. Citation Format: Sen Peng, Harshil Dhurv, Brock Armstrong, Jeffrey Kiefer, Bodour Salhia, Julianna Ross, Christophe Legendre, Selene Virk, Andrew E. Sloan, Quinn T. Ostrom, Jill Barnholtz-Sloan, Nhan L. Tran, Michael E. Berens. Integrated genomic analysis of survival outliers in glioblastoma. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 129.

Targeted sequencing assays are increasingly used to identify tumor mutations that guide therapeutic decisions. Interpretation of a cancer variant's origin and therapeutic impact poses analytical challenges. Recent studies have indicated that jointly analyzing a tumor with its matched normal can accurately discriminate between tumor-specific (somatic) and inherited (germline) mutations. Moreover, a NHGRI/NCI Clinical Sequencing Exploratory Research Consortium Tumor Working Group just released a set of guidelines recommending that laboratories performing cancer sequencing tests should include germline variants. However, procurement of a matched sample is often logistically impractical. In the absence of a matched normal, large databases and analytical techniques are currently used to identify cancer variants in tumor sequencing data. Whether the benefits outweigh the additional burden of sequencing the matched normal for accurate detection of cancer-relevant mutations remains an open question. To compare tumor-only and tumor/normal analysis of cancer samples, we collected a set of >100 formalin-fixed (FFPE) and fresh frozen cancer samples of various tumor types, where matched normal blood or adjacent tissue was available. We performed augmented target enrichment sequencing (exome and large cancer gene panel) of both DNA and RNA. The data was analyzed using cancer bioinformatics pipelines that detect base substitutions, small insertions/deletions, copy number alterations, and gene fusions in both tumor-only and tumor/normal modes. Variants were annotated using described clinical actionability filtering strategies. Analysis of germline variants for secondary findings was performed. We find that 67% of mutations detected in tumor-only mode are reclassified as germline variants when analyzed together with the matched normal sample. These include mutations in hereditary cancer predisposition genes, such as BRCA1, VHL, and other genes with ACMG guidelines that warrant germline variant classification and appropriate management. Clinically actionable mutations may be miscalled as somatic when a matched normal is not available; however, we find the definition of ‘actionable’ can greatly impact the results of this analysis. Finally, the use of newly available large datasets, such as ExAC, substantially decreases the number of miscalled somatic variants in the absence of a matched normal. The effects of administering targeted therapies to patients with germline mutations in the relevant gene are largely unknown. Mutations of putative germline origin may be important for hereditary cancer knowledge and tumor treatment, and should be reported as such. For NGS-based cancer interpretation to guide clinical decisions in a practical and cost-effective manner, highly optimized tumor-only and tumor/normal analyses must be available with proper attention to germline consent, classification and education. Citation Format: Elena Helman, Michael J. Clark, Ravi Alla, Sean M. Boyle, Shujun Luo, Selene Virk, Deanna Church, Parin Sripakdeevong, Jason Harris, Mirian karbelashvili, Christian Haudenschild, John West, Richard Chen. The benefits and burdens of assaying matched normal tissue when sequencing cancer genomes. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 3169.

11561Background: Interpretation of a cancer variant’s origin and therapeutic impact poses analytical challenges. Recent studies have indicated that analyzing a tumor with its matched normal can dis...

BACKGROUND: Glioblastoma is the most deadly and frequently occurring adult primary brain tumor. The characterization of genetic variants and molecular signatures in glioblastoma is heavily reliant upon genomic sequencing. The availability of rapid and economical sequencing platforms is necessary for the widespread adoption of high-throughput sequencing in the clinical environment. METHODS: Utilizing patient matched triplet samples consisting of normal blood and snap-frozen primary and recurrent glioblastoma tumor samples from the Ohio Brain Tumor Study, we compared whole exome sequencing data from TCGA to sequencing data obtained from Ion AmpliSeqTM Comprehensive Cancer Panel (CCP). RESULTS: As we anticipated, the number of variants identified from the exome sequencing data (n = 619) was greater than those identified from the Ion AmpliSeqTM CCP data (n = 22). Surprisingly, there were only six variants common across both data sets. In addition, none of the variants from the Ion AmpliSeqTM CCP data were shared across patient samples. CONCLUSIONS: Our pilot results suggest disparities in both the number and category of mutations identified from analysis of data generated from the Ion AmpliSeqTM CCP and whole exome sequencing. Future studies are needed to elucidate the nature of these differences and to determine the clinical relevance of variants that may be associated with glioblastoma recurrence and response to treatment. High-throughput sequencing based cancer panels may be improved by the development of brain tumor specific panels.

Despite the general poor prognosis for patients with GBM, a proportion survives well beyond the median survival of 12-14 months following diagnosis. To elucidate molecular features associated with disproportionately protracted survival, we conducted deep genomic comparative analysis of a cohort of patients receiving standard therapy (surgery plus concurrent radiation and temozolomide) wherein "GBM outliers" were identified: patients who responded (long-term survivor, LTS) versus those who failed rapidly (short-term survivor, STS). The datasets enabled interrogation for signatures indicative of tumor vulnerability. Whole genomic, epigenetic and transcriptomic analyses of 18 patients, including 8 LTS with an average 30 months overall survival (OS) and 10 STS with an average of 7 months OS were performed to capture single nucleotide variants (SNVs), indels, translocations, intra-chromosomal rearrangements, copy number variants, along with DNA methylation and mRNA expression. LTS and STS cases showed equal proportion of 7p11.2 (EGFR) amplification and 9p21.3 (CDKN2A) deletion. However, LTS GBM showed frequent chromosomal gains in 4q12 (PDGFRA and KIT) and 12q14.1 (CDK4) and deletion in 19q13.33 (BAX, BCAT2 and CD33), whereas, STS GBM showed frequent deletion in 9p11.2 (FOXD4L2 and AQP7P3) and 22q11.21 (HIC2). In addition, LTS GBM showed a 2-fold increased chromosomal instability as compared to STS GBM. By gene expression analysis, supervised clustering using the CIN70 chromosomal instability signature showed a decreased expression of these markers in LTS GBM, corroborating the genomic analysis. Finally, integrating DNA methylation data with gene expression revealed in STS GBM hypermethylation and downregulation of EPHA3, MEG, and PPP1R9A, linked to defective cell migration and adhesion. In contrast, LTS GBM showed hypomethylation and an increased gene expression of KIT. We posit that genomic instability predicts vulnerability of GBM to standard therapy and coupled with genetic and epigenetic signatures may identify patients where front-line entry into alternative, targeted regimens would be a preferred, more-efficacious management.

To evaluate evolutionary patterns in progression and therapy-resistance of GBM, we analyzed the genomic profiles of 252 GBM samples from The Cancer Genome Atlas (TCGA)1, including 48 multi-sector and recurrent tumor biopsies taken from 17 pairs of pre- and post-treatment GBMs, to understand 1) the intratumoral heterogeneity of GBM and 2) how GBM responds to therapeutic intervention. We integrated variant allele fraction, DNA copy number and genotype information to determine clonality of all mutations and found that 69.5% of mutations (median across samples 70.1% ± 19.6%) were classified as clonal and 30.5% as subclonal. To verify our classification approach, we classified mutations detected in two non-overlapping biopsies from 11 tumors into clonal and subclonal categories. Of mutations detected in both tumor sectors 86.2% were classified as clonal and 45.2% of sample-private mutations were categorized as clonal, which was a strongly significant difference (P = 1.8×10-87). Separating patients into discrete age groups by an interval of 10 years, we found a significant linear correlation between clonal mutations and age (P < 0.001). This observation supports the notion that clonal mutations predominantly accumulated over the life span of the cell population that gave rise to the cell of origin before neoplastic onset2. No correlation with age was found for subclonal mutations. In contrast, the frequency of subclonal mutations was strongly correlated with the presence of alterations related to the p53 pathway (P < 0.001), particularly TP53 point mutation or amplification of MDM2. This observation raises the possibility that p53 pathway alterations stimulate subclonal evolution, possibly by providing greater tolerance to DNA damage and/or suppression of apoptosis3. To evaluate the effects of clonal heterogeneity on disease recurrence, we analyzed matched pairs of primary and recurrent GBM, including five pairs with mutated TP53 and nine pairs with wildtype TP53. Recurrent TP53 mutant GBM showed a further and significant increase in the subclonal mutation frequency. In contrast, TP53 wildtype tumors showed an increase in the frequency of clonal mutations compared to their matched primary tumor. These data suggest that TP53 mutant GBM became increasingly clonally complex at time of recurrence, whereas TP53 wildtype GBM showed a reduced level of intratumoral heterogeneity. We observed an ultramutator phenotype in three recurrent tumors, associated with temozolomide treatment. Our results suggest that mutations in the p53 pathway affect the response to therapy by supporting greater intratumoral heterogeneity. Paradoxically we observe a trend towards improved event free survival in samples with high subclonal mutation frequency. Further research is needed to assess whether the level of intratumoral heterogeneity is a reflection of the molecular portrait of GBM progression. Citation Format: Hoon Kim, Siyuan Zheng, Seyed S. Amini, Selene M. Virk, Tom Mikkelsen, Daniel J. Brat, Jonna Grimsby, Carrie Sougnez, Andrew E. Sloan, Mark L. Cohen, Erwin G. Van Meir, Lisa Scarpace, The Cancer Genome Research Network, Peter W. Laird, John N. Weinstein, Eric Lander, Stacey Gabriel, Gad Getz, Matthew Meyerson, Lynda Chin, Jill S. Barnholtz-Sloan, Roel G.w. Verhaak. Alteration of the p53 pathway is associated with subclonal tumor progression in glioblastoma. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 984. doi:10.1158/1538-7445.AM2014-984

To investigate therapy induced evolutionary patterns in glioblastoma (GBM), we completed whole exome sequencing of all samples, as well as transcriptome sequencing, DNA copy number, DNA methylation, and mRNA from at least one primary sample, and one (post-therapy) recurrent sample. Sample collection was enabled through The Cancer Genome Atlas Research Network (TCGA). Multiple spatially distinct samples were available for five primary and six recurrent cases, allowing the integration of intratumoral heterogeneity with the evolutionary processes that shape the tumor recurrence after therapeutic intervention. Sample unique mutations were common, but most of the somatic variants in driver genes (like TP53 and EGFR) were preserved across the tumor and after therapy. We found that the therapeutic bottleneck resulted in proportionally higher numbers of (mostly clonal) mutations, reduced clonal complexity and changes in the mutation spectrum. GBM recurrence could be grouped into two categories, characterized by drastically different clonal evolution patterns. Our findings suggest that multi-sector sequencing sharpens the analysis but is not essential for precise delineation of the tumor progression process. Projecting our results on genomic data from 253 primary GBMs, we observed that the number of clonal, but not subclonal, mutations increased with age at diagnosis, and the two categories differed in their mutation spectrum. This study represents an important advance toward comprehensive characterization of the genomic alterations of GBM before and after cytotoxic treatment and surgery. Our analysis of spatially and temporally distinct samples provides new insights into the relevance of intratumoral heterogeneity on disease progression in GBM. Acknowledgements: This work is supported by Award Numbers 5 P50 CA127001 and 5 P50 CA083639-12 from the National Cancer Institute (NCI) to RGWV. H.K. is supported in part by the Odyssey Program and Theodore N. Law Endowment for Scientific Achievement at The University of Texas MD Anderson Cancer Center. The results published here are in whole or part based upon data generated by The Cancer Genome Atlas project established by the NCI and NHGRI. Citation Information: Mol Cancer Ther 2013;12(11 Suppl):B130. Citation Format: Hoon Kim, Siyuan Zheng, Seyed S. Amini, Selene Virk, Tom Mikkelsen, Daniel J. Brat, Jonna Grimsby, Carrie Sougnez, Andrew E. Sloan, Mark L. Cohen, Erwin G. Van Meir, Lisa Scarpace, Peter W. Laird, John N. Weinstein, Eric S. Lander, Stacey Gabriel, Gaddy Getz, Matthew Meyerson, Lynda Chin, Jill S. Barnholtz-Sloan, Roeland GW Verhaak. The intratumoral heterogeneity of glioblastoma suggests a pivotal role for clonal evolution. [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2013 Oct 19-23; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2013;12(11 Suppl):Abstract nr B130.