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BACKGROUND: Lower-grade gliomas (WHO grade II and III gliomas) are usually slowly progressive but rarely curable brain caners, for which optimal therapy is still controversial. Recently, we have delineated a comprehensive picture of genetic alterations in lower-grade gliomas and revealed that they could be clearly classified into three genetic subtypes characterized by distinct genetic and clinical features: IDH1/2 mutated tumors with 1p/19q co-deletion (Type−I), IDH1/2 mutated tumors without 1p/19q co-deletion (Type−II) and IDH1/2 wild-type tumors (Type−III). Median survival of each genetic subtype is 16.4, 7.77, and 2.12 years in Type−I, −II, and −III tumors, respectively. Given a higher layer of inter-tumor heterogeneity inferred from the presence of additional genetic lesions on each subtype, there still remains a possibility that within each subtype, we could find one or more subgroups showing distinct biological behaviors and clinical outcomes. In the current study, we analyzed a large data set of patients with lower-grade gliomas fully genotyped for major genetic lesions to determine the prognostic significance of additional genetic alterations.. METHODS: We analyzed genetic alterations detected by exome and/or targeted sequencing as well as SNP-array karyotyping obtained from clinically well-annotated 724 patients aged ≥18 years with supratentorial lower-grade gliomas from the Japan and The Cancer Genome Atlas (TCGA) cohorts. We performed univariate and multivariate Cox hazard proportional analyses for overall survival; multivariate models incorporated age at the time of surgery (≥60 vs. RESULTS: In the multivariate Cox proportional-hazards regression analysis, we revealed that several genetic alterations have subtype-specific prognostic significance: NOTCH1 mutation in Type-I [hazard ratio (HR) = 2.57, 95% confidence interval (CI) = 1.40-4.70], high-level focal amplification of CDK4 [HR = 9.40, 95% CI = 3.08-28.7], PIK3R1 mutation [HR = 8.13, 95% CI = 2.70-24.52], and loss of chromosome 9p [HR = 1.98, 95% CI = 1.16-3.38] in Type-II, and loss of chromosome 10 [HR = 2.26, 95% CI = 1.28-3.97] in Type-III tumors. In Type-III tumors, WHO grade [HR = 5.79, 95% CI = 2.79-12.0] showed a much higher prognostic value than other prognostic factors. Most of these genetic alterations are components of three major signaling pathways or copy number variations frequently affected in glioblastomas, suggesting a close link of disease progression to glioblastoma pathophysiology. CONCLUSIONS: Subtype-specific genetic lesions can be used to further stratify patients in each genetic subtype for overall survival to improve management of lower-grade gliomas. Citation Format: Kosuke Aoki, Hiromichi Suzuki, Hideo Nakamura, Keitaro Matsuo, Kazuya Motomura, Fumiharu Ohka, Masahiro Mizoguchi, Yasutomo Momii, Yasuhiro Muragaki, Satoru Miyano, Toshihiko Wakabayashi, Atsushi Natsume, Seishi Ogawa. Genetic subtype-specific prognostic significance of genetic alterations in lower-grade gliomas. [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 4751.

Lower grade gliomas (LGGs, WHO grade II/III gliomas) account for approximately one third of all gliomas. Although LGGs are typically slowly progressive, their clinical course is invariably indolent and most patients ultimately succumb to death. In contrast to glioblastoma (GBM), our knowledge about the genetic lesions and clonal evolution in LGG is still incomplete. So, to obtain a complete registry of gene mutations involved in LGG pathogenesis and their role in clonal evolution, we performed whole exome sequencing (WES) and/or targeted sequencing of 335 LGG cases. Clonal evolution in LGG was investigated using paired primary/relapsed tumor specimens from 10 cases as well as multiple tumor specimens (median 5) from 4 cases. Massive parallel sequencing revealed LGGs were clearly grouped into three subgroups with or without IDH1/2 mutation and 1p19q loss of heterozygous (LOH). Type I tumor with IDH1/2 mutation and 1p19q LOH had a most favorable survival and harbored mutations in TERT promoter, CIC, FUBP1 and NOTCH1. Type II tumor with IDH1/2 mutant/1p19q intact subtype represented TP53 bialleleic inactivation and/or ATRX mutations. Type III tumor with IDH1/2 intact showed GBM like mutation profile and poor prognosis. Large scale samples allowed to obviously detect strong positive/negative correlations with each other driver genes. Extensive analysis of variant allele frequencies among co-existing mutations revealed temporal orders of gene mutations in each subtypes. Multi regional/time-points sampling analysis suppoted mutational order and revealed regional and special heterogeneity with tumor evolution in LGGs. LGG contiguously developed and generated heterogeneity through acquiring new mutations in a complex but ordered fashion. In conclusion, our findings delineated the landscape of gene mutations in LGG. LGG had mutually exclusive mutational patterns with hierarchical order in discrete subtypes. IDH1/2 and TERT promoter mutations and 1p19q LOH were thought to exist in the major clone and important role in tumor initiation. In contrast, common occurrence of parallel mutations found in TP53, ATRX, CIC, FUBP1 and NOTCH1 genes indicated central roles of these mutations in LGG development. Citation Format: Hiromichi Suzuki, Kosuke Aoki, Kenichi Chiba, Yusuke Sato, Yusuke Shiozawa, Yuichi Shiraishi, Atsushi Niida, Teppei Shimamura, Masashi Sanada, Satoru Miyano, Toshihiko Wakabayashi, Atsushi Natsume, Seishi Ogawa. The landscape and clonal architecture in lower grade glioma. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 3933. doi:10.1158/1538-7445.AM2015-3933

Glioblastoma multiforme (GBM) is the most prevalent malignant primary brain tumor in adults. GBM is classified as primary if it is assumed to have arisen de novo or as secondary if it progressed from lower grade astrocytoma. Previous studies have found that primary and secondary GBMs have distinct molecular and mutational profiles. Both have a grim prognosis with survival times of about a year with therapy. Although much progress in delineating the temporal order of mutations and copy number aberrations in the progression of lower grade gliomas was made in the past years, none of the studies have actively followed individual tumors through their progression. Whereas this method can detect aberrations that are prevalent in gliomas, it can miss events that are important in a subset of gliomas or are necessary for progression. The GlioMath-DD consortium is an interdisciplinary collaboration of several groups at the Technische Universität Dresden (TU-Dresden) aiming to study the progression of gliomas and to come up with a mathematical model for gliomagenesis. The work involves analyzing pairs of gliomas obtained from patients who had presented with a low grade glioma and who later had a recurrence of a higher grade glioma. All tumors were checked by pathologists and then high quality DNA and RNA material extracted and used for analysis. The tumors are analyzed for copy number variations (CNV) by array comparative genome hybridization (aCGH), while gene expression changes and small mutations are analyzed using high-throughput sequencing (RNA- and Exome-seq). The data gleaned from these experiments and from in vitro models of cell growth and spheroid formation will be used by bioinformaticians and mathematicians to infer key signaling networks and formulate a mathematical model of glioma progression. The ultimate aim of this work that spans two and a half years is to create a comprehensive model of glioma promotion and progression. Furthermore, it will pinpoint driver mutations and aberrations that contribute to this progression and eventually isolate biomarkers for diagnosis and therapy. During the conference, we will present preliminary genetic data of our ongoing study. Acknowledgements: The GlioMath-DD project (coordinator: Andreas Deutsch; SAB-Number 100098214) is funded by the European Social Fund (ESF) and the Free State of Saxony Citation Format: Evelin Schröck, Khalil Abou-El-Ardat, Ralf Wiedemuth, Michael Seifert, Alvaro Köhn-Luque, Mirjam Ingargiola, Kristin Stirnnagel, Alexander Krüger, Wolfgang Nagel, Kathrin Geiger, Andreas Beyer, Leoni A. Kunz-Schughart, Gabriele Schackert, Achim Temme, Barbara Klink, Andreas Deutsch. GlioMath-DD: A multidisciplinary approach to study glioma evolution and identify targets for individualized therapies. [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 5341. doi:10.1158/1538-7445.AM2014-5341

A critical component of the early development of anticancer agents is the assessment of the Maximum Tolerated Dose during Phase I. In practice, clinical toxicities are graded on a scale of severity, ranging from Grade 1 (least severe) to Grade 4. This categorical scale is also used for continuous readouts, such as neutropenia. As the underlying pathophysiology can be expected to remain the same, and vary by degree or intensity alone, the dose-response (or concentration- response) of lower-grade toxicities should foreshadow the incidence of higher-grade toxicities, which represent different thresholds on the same concentration-response curve. If the concentration- response of Grade 4 toxicity can be predicted from that of Grade 1 toxicity, then the accurate estimation of the MTD should be feasible from a careful estimation of the Grade 1 toxicity. In this work, we demonstrate the development of anticipatory toxicity models that are capable of predicting higher-grade toxicities during dose-escalation. First, we used a simple empirical approach that relies on a minimum of assumptions. We have previously shown that the nadir of neutropenia is strongly correlated with the maximum moving average concentration over the dosing window. Using this pharmacokinetic parameter as an independent variable, we developed a set of analytical expressions to connect the concentration- response of each lower grade of toxicity to the corresponding higher grades of toxicity. Next, we tested this family of anticipatory toxicity models on a simulated dataset of neutropenia generated from a previously published model of clinical neutropenia for a range of chemotherapeutics (Friberg et al., 2002). Finally, we validated our anticipatory toxicity models with in-house preclinical data. Next, we extended the development of anticipatory toxicity models to a model-based approach. We fitted the lower grades of toxicity from the simulated dataset described above to fit a semi-mechanistic model of neutropenia, showing that the model can predict higher grades of toxicity. Next, we again validated the anticipatory toxicity models built on a semi-mechanistic basis using in-house preclinical data. Each of the two approaches presented here may be better suited for different situations. The empirical approach is better suited for toxicities with a poorly understood mechanistic basis, while the semi-mechanistic approach is well suited for neutropenia and other hematological toxicities. In either case, the anticipatory toxicity models were able to accurately predict the incidence of higher-grade toxicities in the given datasets. Thus, a careful analysis of these lower-grade toxicities may provide the opportunity to accelerate clinical development through the design of alternative clinical dose-escalation schemes. Such alternative escalation schemes may also be safer, as they focus on the forward prediction of the MTD before it is reached. Citation Format: Ekta Kadakia, Snehal Samant, Christopher J. Zopf, Dean Bottino, Greg Hather, Santhosh Palani, Wen Chyi Shyu, Arijit Chakravarty. Predicting Maximum Tolerated Dose during Phase I using anticipatory toxicity models. [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 3747. doi:10.1158/1538-7445.AM2014-3747