(IDH) Mutations in Gliomas

Author Manuscript Published OnlineFirst on February 18, 2019; DOI: 10.1158/1078-0432.CCR-18-3205 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited.

Tissue 2-hydroxyglutarate as a biomarker for isocitrate dehydrogenase (IDH) mutations in gliomas

Hao-Wen Sim1 Romina Nejad1 Wenjiang Zhang Farshad Nassiri Warren Mason Ken Aldape Gelareh Zadeh2 Eric Chen2

Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada 1: Both authors contributed equally to the manuscript 2: Co-corresponding authors

Corresponding authors:

Dr. Gelareh Zadeh MacFeeters Hamilton Centre for Neuro-Oncology Research, Princess Margaret Cancer Centre, University Health Network 101 College St Toronto, Ontario, Canada M5G 1Z7 Tel: (416) 634-8728; Fax: (416) 603-5298 [email protected]

Dr. Eric Chen Department of Medical Oncology and Hematology Princess Margaret Cancer Centre, University Health Network 610 University Avenue Tel (416) 946-2263; Fax: (416) 946-4467 Toronto, Ontario, Canada M5G 2M9 [email protected]

Running title:

Tissue 2-hydroxyglutarate as a biomarker for IDH mutation

Keywords: 2-hydroxyglutarate, cancer metabolism, glioma, HPLC-MS, isocitrate dehydrogenase mutation

Financial Support:

Financial support for this study was provided by the Princess Margaret Cancer Center Foundation.

The Authors have no conflicts of interest to declare.

Downloaded from clincancerres.aacrjournals.org on September 29, 2021. © 2019 American Association for Cancer Research. Author Manuscript Published OnlineFirst on February 18, 2019; DOI: 10.1158/1078-0432.CCR-18-3205 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited.

1 Statement of translational relevance 2 3 Isocitrate dehydrogenase (IDH) 1 and 2 mutations are common in low grade gliomas, and mutated IDH enzymes 4 lead to the accumulation of R-2-hydroxyglutarate (R-2-HG) over S-2-hydroxyglutarate (S-2-HG). We describe a 5 HPLC-mass spectrometry based method to quantitate R-2-HG and S-2-HG individually in glioma tissues and 6 blood samples from glioma patients. We demonstrate that the ratio of tissue R-2-HG/S-2-HG (rRS), but not blood 7 rRS, is a sensitive and specific biomarker for IDH mutations. Patients with higher rRS may have worse prognosis 8 than those with lower rRS. The analytical method described in this report has a turnaround time of 60 minutes, 9 and it can potentially be applied in real time for IDH mutation status determination at the time of surgical 10 resection.

11 ABSTRACT 12 Background 13 Isocitrate dehydrogenase (IDH) mutations are common in low grade gliomas and the IDH mutation status is now 14 integrated into the WHO classification of gliomas. IDH mutations lead to preferential accumulation of the R- 15 relative to the S- enantiomer of 2-hydroxyglutarate (2-HG). We investigated the utility of tissue total 2-HG, R-2- 16 HG and the R-2-HG/S-2-HG ratio (rRS) as diagnostic and prognostic biomarkers for IDH mutations in gliomas. 17 18 Methods 19 Glioma tissue and blood samples from 87 patients were analyzed with HPLC-MS/MS coupled with a 20 CHIROBIOTIC column to quantify both enantiomers of 2-HG. Receiver operator curve (ROC) analysis was 21 conducted to evaluate the sensitivity and specificity of 2-HG, R-2-HG and rRS. The feasibility of real-time 22 determination of IDH status was evaluated in 11 patients intra-operatively. The prognostic value of rRS was 23 evaluated using the Kaplan-Meier method. 24 25 Results 26 The rRS in glioma tissues clearly distinguished patients with IDH mutant versus wildtype tumors (p<0.001). 27 Sensitivity and specificity using an rRS cut-off value of 32.26 were 97% and 100% respectively. None of total 2- 28 HG, R-2-HG or rRS was elevated in serum samples. Among patients with IDH mutant tumors, tissue rRS 29 stratifies overall survival. The duration of tissue analysis is approximately 60 minutes. 30 31 Conclusions 32 Our study demonstrates that rRS is a reliable biomarker of IDH mutation status. This technique can be used to 33 determine IDH mutation status intra-operatively, and to guide treatment decisions based on IDH mutation status 34 in real time. Lastly, rRS values may provide additional prognostic information and further validation is required. 35

36 INTRODUCTION 37 Since its initial discovery in 2009, isocitrate dehydrogenase 1/2 (IDH1/2) mutations have been found in a diverse 38 group of cancers such as glioma (1-3), acute myeloid leukemia (AML)(4,5), intrahepatic cholangiocarcinoma 39 (6,7), chondrosarcoma (8), angioimmunoblastic T cell lymphoma (9) and others (10-12). IDH1/2 mutations 40 are reported in approximately 70-90% of low grade diffuse gliomas and secondary glioblastomas 41 (GBM), and are associated with younger age at diagnosis and significantly improved overall survival 42 (1-3,13,14). Given the prognostic significance of IDH and its implicated role in gliomagenesis, IDH 43 mutation status and other molecular markers have recently been integrated into the World Health 44 Organization (WHO) classification of gliomas (15). 45 46 IDH1 and IDH2 are nicotinamide adenine dinucleotide phosphate (NADP+)-dependent enzymes and function in 47 the tricarboxylic acid cycle to catalyze the oxidative decarboxylation of isocitrate to α-ketoglutarate (αKG) (16). 48 IDH1 and IDH2 enzymes share 70% sequence similarity, but are encoded by different genes (IDH1, 2q33; IDH2, 49 15q26) and localize to different cellular compartments (17). In gliomas, over 90% of IDH mutations involve 50 IDH1 codon 132 with substitution of arginine by histidine (R132H) (18). Accordingly, immunohistochemistry 51 (IHC) with an antibody specific for this canonical mutation has greater than 90% sensitivity. The high sensitivity 52 and relatively low cost of IHC makes it the most common method of determining IDH mutation status clinically. 53 Of course, this method will not be sensitive to non-canonical IDH1 or IDH2 mutations (19). Direct sequencing is 54 being increasingly used, but it is associated with higher costs and a longer turnaround time. 55 56 Mutations in IDH1/2 confer neomorphic activities that convert αKG to 2-hydroxyglutarate (2-HG) (20), with 57 preferential accumulation of the R- relative to the S- enantiomer of 2-HG (21). Previous studies have investigated 58 the utility of using 2-HG as a biomarker for IDH mutation status in gliomas without conclusive results (21-26). 59 These studies have been limited by measuring levels of total 2-HG, and by measuring 2-HG in blood or urine as 60 opposed to tumor tissue. Only one study investigated the utility of R-2-HG, but in cerebrospinal fluid (CSF) (26). 61 The use of proton magnetic resonance spectroscopy (MRS) has been advocated by several groups, but it is also 62 limited by its ability to detect total 2-HG only (27,28). In the current study, we evaluated the utility of 63 quantitating the relative abundance of R-2-HG and S-2-HG using a novel high pressure liquid chromatography 64 tandem mass spectrometry (HPLC-MS/MS) technique as a surrogate for IDH mutation status. 65 66 67 MATERIALS AND METHODS 68 Tissue and serum samples

69 The study was approved by the Research Ethics Board at University Health Network, Toronto, Canada and 70 conducted in accordance with the Declaration of Helsinki. Fresh frozen glioma tissues from 87 patients were 71 obtained from the University of Toronto Brain Tumor Biobank. Matched pre-operative serum samples were 72 available for 29 patients. Patient and disease characteristics such as age, sex, tumor histology, tumor grade, 73 clinically reported IDH1 mutation status, 1p/19q co-deletion status, treatment details and survival outcomes were 74 determined by retrospective chart review. 75 76 Separately, glioma tissues were obtained from 11 patients at the time of surgical resection. A written informed 77 consent was obtained from each patient. 78 79 Quantification of 2-HG 80 Tissue and serum samples were analyzed for R-2-HG and S-2-HG utilizing HPLC-MS/MS. Tissue or serum 81 samples were thawed, weighted or measured and homogenized with 500 l of double distilled water. Protein was 82 precipitated using acetonitrile, and samples were then centrifuged at room temperature (24C) for 10 minutes at a 83 speed of 10000 rpm. The resulting supernatants were transferred to polypropylene tubes and evaporated under 84 vacuum. The residues were reconstituted with 100-200 l of methanol water (90%:10%; v/v) and 10 µl was 85 injected into a Shimadzu CBM-20A System coupled with a triple quadrupole mass spectrometer (API 3200, 86 Applied Biosystems MDS SCIEX, Foster City, USA). Chromatographic separation was achieved through an 87 Astec® CHIROBIOTIC® Chiral HPLC analytical column (250×4.6 mm, 5 µm particles, Sigma Co, St Louis, 88 USA). Data collection, peak integration and processing were performed with Analyst® 1.6.2 (Applied Biosystems 89 MDS SCIEX, Foster City, USA). Assays were performed blinded to clinically reported IDH mutation status. The 90 lower limit of quantitation was 10.0 ng/g of tissue for both R-2-HG and S-2-HG. 91 92 IDH1 mutation and 1p/19q codeletion status 93 For 75 of the 87 patients in our cohort, IDH1 status was determined via IHC using an IDH1 antibody as per 94 standard clinical practices in a CLIA certified clinical pathology laboratory (18). For the remaining 12 patients, 95 DNA was isolated from fresh frozen tissue and PCR amplified using primer pairs specific for exon 4 of the IDH1 96 gene. The amplified products were then sequenced by Sanger Sequencing at the Center of Applied Genomics 97 (The Hospital for Sick Children, Toronto, Canada). For patients with discordant IHC and 2-HG results, IDH 98 status was determined through sequencing in the genome diagnostics/cancer cytogenetics laboratory in the 99 Department of Clinical Laboratory Genetics (University Health Network, Toronto, Canada). IDH mutation status 100 was further confirmed by 450K methylation array tumor profiling, using G-CIMP status as a readout (29). The 101 1p19q co-deletion status, determined either by PCR analysis and/or fluorescence in-situ hybridization (FISH) 102 analysis, was available for 53 patients. 5

103 104 Statistical analysis 105 Descriptive statistics were used to report the baseline patient and disease characteristics. Categorical variables 106 between groups were compared using Fisher’s exact test, and continuous variables were compared using the 107 Mann-Whitney-Wilcoxon test. Univariable and multivariable regression analyses were undertaken to identify 108 potential predictors of 2-HG levels, including age, gender, tumor grade, tumor recurrence, treatment latency 109 (defined as the duration between diagnosis and first surgery), IDH1 status and 1p/19q co-deletion status. Receiver 110 operator curve (ROC) analysis evaluated the utility of total 2-HG, R-2-HG alone and the ratio of R- to S- 111 enantiomers of 2-HG (rRS) as potential biomarkers of IDH status, based on the area under the ROC curve and the 112 Youden index, which identifies the cut-off maximizing the sum of sensitivity and specificity. 113 114 The Kaplan-Meier method was used to estimate survival rates. Overall survival (OS) was defined as the time from 115 diagnosis to death from any cause. Progression-free survival (PFS) was defined as the time from diagnosis to first 116 recurrence or death from any cause. Patients without documented evidence of an event were censored at the date 117 of last follow-up. The Cox proportional hazards regression analysis was used to explore the relationship between 118 groups and survival. Median study follow-up was calculated using the reverse Kaplan-Meier estimator. 119 120 Significance level was set at alpha of 0.05 for inferential analyses. All analyses were performed using R version 121 3.5.0 (R Foundation for Statistical Computing, Vienna, Austria). 122 123 RESULTS 124 Patient characteristics 125 Of the 87 patients included, 61 patients were IDH1 mutant tumors and 26 patients had IDH1 wildtype tumors. 126 Matched glioma tissue and serum samples were available for a subset of 29 patients. There were a total of 55 male 127 and 32 female patients, with a median age at diagnosis of 41 years (range: 20-75 years). Baseline patient and 128 disease characteristics stratified by IDH mutation status are summarized in Table 1. In keeping with previous 129 reports, patients with IDH1 mutations were significantly younger than those with IDH1 wild type tumors, had 130 lower grade tumors, longer treatment latency and tumors were more likely to harbor a 1p/19q co-deletion. Median 131 follow-up was 9.8 years (range: 1.3 – not reached). 132 133 Tissue and serum 2-HG and IDH mutation status 134 In glioma tissues, total 2-HG was significantly higher in IDH1 mutant tumors (median total 2-HG = 2.92×105 135 ng/g) compared to that in IDH1 wildtype tumors (median total 2-HG = 4.00×103 ng/g, p < 0.001, Figure 1(a)).

136 Similarly, the median R-2HG was 2.91 × 105 ng/g in IDH1 mutant tumors and 2.08 × 103 ng/g in IDH1 wildtype 137 tumors (p < 0.001). The rRS was significantly higher in IDH1 mutant tumors (median rRS = 567) compared to 138 IDH1 wildtype tumors (median rRS = 1.11, p < 0.001, Figure 1(b)). Initially, there were 4 samples that were 139 determined to be IDH1 wildtype based on IHC, but with unexpectedly high tissue rRS. Upon sequencing, 3 of 140 these samples were found to have non-canonical IDH1 mutations. The other sample was confirmed to be IDH1 141 wildtype. 142 143 In contrast to tissue measurements, total 2-HG, R-2-HG and rRS were not elevated in matched serum samples and 144 did not differentiate between IDH1 mutant and IDH1 wildtype status. Median rRS was 1.49 for IDH1 mutant 145 samples versus 1.22 for IDH1 wildtype samples (p = 0.08, Figure 1(c)). 146 147 Tissue 2-HG as a biomarker of IDH mutation status 148 The potential predictive value of tissue 2-HG was examined with univariable and multivariable analyses. The 149 sensitivity and specificity of rRS for IDH mutation was determined with ROC analysis. Based on univariable 150 analyses, the significant predictors of the rRS from glioma tissues included IDH1 mutation status (higher rRS for 151 IDH1 mutant tumors), age (higher rRS for patients under 40 years), tumor grade (higher rRS for low grade 152 tumors), treatment latency (higher rRS for longer latency) and 1p/19q codeletion status (higher rRS for codeleted 153 tumors). In multivariable analysis, the impact of IDH1 status persisted and it was clearly the most important 154 predictor of rRS from glioma tissues (p < 0.001, Table 2). In particular, the rRS from glioma tissues was 155 significantly associated with IDH1 status within both low-grade and high-grade glioma subgroups (Figures 1(d) 156 and (e)). This suggests that elevated rRS values are driven by IDH status, controlled for baseline patient and 157 disease characteristics. 158 159 ROC analysis showed that the tissue rRS was highly specific and sensitive for IDH mutation status (Figure 1(f)). 160 Using a rRS cut-off of 32.26, where higher values designate IDH1 mutant tumors and lower values designate 161 IDH1 wildtype tumors, the area under the ROC curve was greater than 0.99 and the sensitivity and specificity was 162 97% and 100% respectively. This discriminatory effect was greater than that with the use of total 2-HG or R- 163 2HG, consistent with the relative abundance of R-2-HG versus S-2-HG in IDH mutations. 164 165 For the group of 11 patients with intra-operative samples, these samples were processed fresh without freezing 166 and the time intervals from sample acquisition to results by HPLC-MS/MS were approximately 60 minutes. 167 There were 4 patients with rRS values above the cutoff of 32.26 (189.5, 223.6, 296.7, and 1054.2 respectively), 168 and 7 patients with rRS values below the cutoff ranging from 0.39 – 0.80 (Supplementary Materials, Table 2). 169 These results were in complete agreement with those of IHC.

170 171 Survival and IDH status 172 Survival outcomes were compared between IDH mutant and IDH wildtype patients. The potential prognostic 173 effect of rRS was examined by quartiles. As expected, OS was significantly longer in patients with IDH1 mutant 174 versus IDH1 wildtype tumors (median OS: 131 vs. 18 months, HR 0.08 [95%CI 0.04-0.15], Figure 2(a)). 175 Similarly, PFS was significantly longer in patients with IDH1 mutant versus IDH1 wildtype tumors (median PFS: 176 43 vs. 13 months, HR 0.22 [95% CI 0.12-0.39], Figure 2(b)). For the subgroup of patients with IDH1 mutant 177 tumors, the 1p/19q co-deletion status did not differentiate survival. OS (HR 0.80 [95% CI 0.38-1.71], Figure 178 2(c)) and PFS were both similar (HR 0.73 [95% CI 0.38-1.44], Figure 2(d)). 179 180 Stratifying patients with IDH mutant tumors by rRS, median OS was 200 months for the lowest quartile of rRS 181 values (Q1) versus 66 months for the highest quartile of rRS values (Q4) (HR 0.33 [95% CI 0.13-0.86], p = 0.02. 182 Figure 2(e)). Similarly, median PFS was 58 months for the lowest quartile of rRS values versus 25 months for the 183 highest quartile of rRS values (HR 0.56 [95% CI 0.24-1.32], p = 0.18. Figure 2(f)). These results suggest that 184 higher rRS values may be associated with a worse prognosis. There was a similar but less conclusive trend when 185 stratifying by total 2-HG (OS: HR 0.63 [95% CI 0.25-1.62]; PFS: HR 0.66 [95% CI 0.29-1.50]). 186 187 DISCUSSION 188 In most patients with suspected gliomas, the diagnosis is based on pre-operative imaging and tissue acquired at 189 the time of surgical resection. IDH status is a key part of the integrated genotype-phenotype diagnosis of gliomas 190 and directs treatment decisions post-operatively. However, it is usually determined post-operatively using IHC for 191 the canonical IDH1 R132 mutation. An important limitation of this method is that the small number of other non- 192 canonical IDH1 mutations or mutations in IDH2 will not be detected. This is highlighted by the 3 patients in this 193 study who were deemed to be IDH wildtype by IHC, but were found to have high rRS ratios and subsequently 194 confirmed to have non-canonical IDH1 mutations by sequencing. In addition to IHC, many centres rely on 195 sequencing to determine IDH mutation status, however, the resources required and turnaround times can be 196 deterrents for routine clinical use. In addition, sequencing does not provide information on the activity of mutant 197 IDH enzymes. An evolving method for IDH determination is MRS, an imaging modality that can estimate the 198 tumor 2-HG levels non-invasively and in real-time based on the spectral pattern (27,28). MRS accuracy varies 199 widely depending on the tumor volume (sensitivity 8-91%), with very low sensitivity in smaller tumors. Another 200 technology, desorption electrospray ionization mass spectrometry (DESI-MS), was recently used to detect 2-HG 201 from tissue sections rapidly at the time of surgery (30,31). Furthermore, DESI-MS could be used to determine 202 surgical margins, thereby, assisting in the decision-making during surgery. Similarly matrix-assisted laser 203 desorption ionization-time of flight mass spectrometry (MALDI-TOF) was shown to be able to detect 2HG in 8

204 tissue sections rapidly (32). However, none of these methods can distinguish between R-2-HG and S-2-HG. In 205 contrast, the technique we present leverages the biochemical consequence of all mutant IDH mutations and uses 206 the ratio of R/S as a biomarker. 207 208 To date, several direct and quantitative 2-HG detection methods have been reported. Gross and colleagues (5) 209 were among the first to report higher 2-HG levels in the serum of patients with IDH1 R132H mutant AML 210 compared to wildtype AML. Similarly, in a cohort of 82 patients with de novo AML, median 2-HG levels were 211 significantly higher in serum samples from IDH1/2 mutant patients, in comparison to serum samples (21.2 vs. 1.2 212 μmol/L) from IDH wildtype patients (33). From these studies, serum 2-HG levels appear to be a reliable surrogate 213 of IDH1/2 mutations in AML patients. Significantly higher 2-HG has been reported in the serum of patients with 214 IDH mutant cholangiocarcinoma, breast cancer and colon cancer (11,12,34,35). However, current evidence does 215 not support the use of serum 2-HG for IDH mutation detection in gliomas. Capper et al (22) reported no 216 differences in preoperative serum 2-HG levels of WHO grade II and III IDH mutant versus wildtype glioma (1.6 217 vs. 1.3 mmol/L). Lombardi and colleagues (24) reported similar 2-HG levels in the serum of patients with IDH1 218 mutant versus wildtype glioma (97.2 vs. 97.0 ng/mL). Interestingly, when 2-HG testing was extended to urine 219 samples, patients with IDH wildtype glioma had a significantly higher concentration of 2-HG than those with IDH 220 mutant glioma (7.3 vs. 4.6 g/mg), contrary to expectation. Results from our study do not support the use of total 221 2-HG, R-2-HG or rRS as biomarkers for IDH mutation status from patient serum samples. This may be attributed 222 to the very low diffusion rate of 2-HG from glioma cells due to the blood-brain barrier, in comparison to AML 223 and cholangiocarcinoma where 2-HG is produced outside of the central nervous system (36). Kalinina et al used a 224 HPLC-MS method and found that R-2-HG in CSF of IDH mutant patients increased by > 17 folds compared to 225 IDH wildtype patients (26). However, sensitivity and specificity were 84% and 90% respectively. 226 227 Taken together, previous methods of 2-HG detection have reported inconsistent results and have mainly focused 228 on detection of total 2-HG or R-2-HG, as opposed to the abnormal accumulation of R-2-HG relative to S-2-HG as 229 a result of the neomorphic activity of IDH mutations. Our results revealed that assessment of tissue rRS reliably 230 determined IDH mutation status with very high sensitivity and specificity. Outlier values were predominantly due 231 to non-canonical IDH1 mutations, which were not detectable using conventional IHC but identified with 232 sequencing. IDH mutation status was the most important predictor of tissue rRS, after accounting for patient age, 233 gender, tumor grade, tumor recurrence, treatment latency and 1p/19q co-deletion status. 234 235 IDH mutant gliomas are associated with improved survivals compared to IDH wild type gliomas. Recent data 236 suggest that even IDH mutant gliomas are a heterogeneous group, and the extent of tumor DNA methylation is 237 associated with survival (37). The presumed mechanism of 2-HG associated tumorigenesis is through inhibiting

238 αKG-dependent dioxygenases including histone and DNA demethylases. It is reasonable to postulate that higher 239 2-HG levels are associated with increasing genomic abnormalities, hence poorer outcomes. Our results suggest 240 that tissue rRS appeared to stratify prognosis further for patients with IDH mutant tumors. Specifically, higher 241 rRS values were associated with a worse prognosis. The median OS was 200 months for the lowest rRS quartile 242 versus 66 months for the highest rRS quartile., These findings further argue for measuring both R-2-HG and S-2- 243 HG, rather than the total tissue 2-HG. 244 245 The method reported here has advantages over other methods of determining IDH mutation. An elevated rRS is 246 the biochemical consequence of all known IDH mutations, thereby avoiding sequencing each known mutation. 247 Tissue S-2-HG serves as an inherent internal control, and the use of tissue rRS can overcome limitations 248 associated with measuring total 2-HG only, such as cellularity and variable allele frequencies in the tissue tested 249 and differences in mutant IDH enzyme activities. Most importantly, rRS could potentially provide prognostic 250 information in addition to IDH status, and influence treatment decisions in these patients. For example, it is 251 possible that patients with low rRS can be monitored closely postoperatively to minimize treatment associated 252 toxicities and maintain quality of life for these patients, while those with high rRS may be considered for adjuvant 253 therapies or enrolled into clinical trials. However, our method is based on the availability of glioma tissues and is 254 not suitable for dynamic monitoring of changes in 2-HG as results of treatment or recurrence. 255 256 Another potential application of our HPLC-MS/MS based method is the real-time determination of IDH status at 257 the time of surgical resection. Current evidence suggests that aggressive resection may improve survival outcomes 258 in patients with gliomas; however, the extent of resection must be balanced against surgical risk and long-term 259 neurologic compromise. In a study of 335 glioma patients by Beiko and colleagues (38), 93% of patients with 260 IDH1 mutant tumors underwent complete resection of enhancing disease compared to 67% of patients with IDH1 261 wildtype tumors, suggesting that IDH1 mutant tumors were more amenable to resection. Moreover, complete 262 resection of IDH1 mutant tumors was associated with a significant OS improvement compared to incomplete 263 resection (19.6 vs. 10.7 months). Kanamori et al recently reported that tissue total 2-HG levels could be 264 determined within 10 minutes using HPLC-MS/MS (39). The current run-time for our method is approximately 265 60 minutes. We demonstrated that this technique could be applied intra-operatively to determine IDH status and 266 the result made available to the surgeon in real time to enable a personalized surgical approach for patients based 267 on IDH mutation status. This will not be achievable with the current sequencing technology. 268 269 In this study, we did not have IDH1 or IDH2 sequencing information for the majority of patients. This limitation 270 was mitigated by performing confirmatory 450K methylation analysis and by directly sequencing any tumor

271 tissue with discordant values. In follow-up to this study, the prognostic significance of rRS needs to be confirmed 272 in a larger cohort of patients. 273 274 In conclusion, we report a novel technique that can reliably detect both R-2-HG and S-2-HG in human glioma 275 tissues. The rRS from glioma tissues differentiated IDH1 mutant versus IDH1 wildtype tumors with high 276 sensitivity and specificity, whereas serum samples were unreliable. We demonstrated that this technique could be 277 used for the real-time determination of IDH status intra-operatively, and thus may potentially guide clinical 278 practice such as the extent of surgical resection. Most importantly, tissue rRS appears to stratify survival among 279 patients with IDH mutant tumors, suggesting that treatment decisions can be further individualized in these 280 patients. This technique is advantageous over other methods of IDH mutation determination, such as IHC, 281 sequencing or various MRS methods, in that it can provide all these information simultaneously.

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Table 1: Baseline patient and disease characteristics

IDH1 wildtype IDH1 mutant Characteristic p-value (n=26) (n=61) Age ≤ 40 years 5 (19%) 37 (61%) <0.001 > 40 years 21 (81%) 24 (39%)

Gender Male 18 (69%) 37 (61%) 0.48 Female 8 (31%) 24 (39%)

Tumor grade* ≤ 3 8 (31%) 52 (85%) <0.001 4 18 (69%) 9 (15%)

Primary vs Recurrent tumor Primary 15 (58%) 41 (67%) 0.47 Recurrent 11 (42%) 20 (33%)

Treatment latency# ≤ 3 months 26 (100%) 42 (69%) <0.001 > 3 months 0 (0%) 19 (31%)

1p/19q codeletion status Codeleted 0 (0%) 33 (54%) Non-codeleted 9 (35%) 20 (33%) <0.001 Unknown 17 (65%) 8 (13%)

* Tumor grade according to World Health Organization Classification of Tumors # Treatment latency denotes the duration between diagnosis and first surgery Abbreviations: IDH: isocitrate dehydrogenase

Table 2: Univariable and multivariable predictors of rRS from tissue samples

Univariable Multivariable Characteristic Coefficient Coefficient p-value p-value (95% CI) (95% CI) IDH1 status 2.56 2.12 <0.001 <0.001 mutant (vs. wildtype) (2.27 to 2.84) (1.50 to 2.74)

Age 1.03 0.40 <0.001 0.04 ≤ 40 years (vs. > 40) (0.51 to 1.55) (0.01 to 0.79)

Gender -0.17 0.22 0.57 0.17 male (vs. female) (-0.75 to 0.42) (-0.10 to 0.54)

Tumor grade* 1.45 0.49 <0.001 0.07 ≤ 3 (vs. 4) (0.92 to 1.98) (-0.04 to 1.02)

Primary vs Recurrent tumor 0.08 -0.33 0.80 0.07 primary tumor (vs. recurrent) (-0.51 to 0.67) (-0.67 to 0.02)

Treatment latency# -0.75 0.20 0.03 0.29 ≤ 3 months (vs. > 3) (-1.42 to -0.09) (-0.18 to 0.58)

1p/19q codeletion status 0.96 0.28 <0.001 0.15 codeleted (vs. non-codeleted) (0.45 to 1.48) (-0.10 to 0.67) * Tumor grade according to World Health Organization Classification of Tumors # Treatment latency denotes the duration between diagnosis and first surgery Abbreviations: CI: confidence interval; IDH: isocitrate dehydrogenase; rRS: ratio of R to S enantiomers of 2-hydroxyglutarate

Figure legends:

Figure 1: Comparison of 2-HG levels between IDH1 wildtype vs. mutant gliomas based on: (a) total 2- HG from tissue samples; (b) rRS from tissue samples; (c) rRS from serum samples; (d) for the subgroup with tumor grade ≤ 3, rRS from tissue samples; (e) for the subgroup with tumor grade 4, rRS from tissue samples; receiver-operator curve (ROC) analysis using rRS from tissue samples to differentiate between IDH1 wildtype vs. mutant gliomas, AUC: area under the curve .

Figure 2: Comparison of survival outcomes between patients with IDH1 wildtype vs. mutant gliomas for: (a) overall survival; (b) progression-free survival. For the subgroup of patients with IDH1 mutant gliomas, a comparison of survival outcomes for 1p19q codeleted vs. non-codeleted gliomas for: (c) overall survival; (d) progression-free survival; comparison between IDH mutant patients between lowest rRS vs highest rRS in (e) overall survival, (f) progression-free survival.

Tissue 2-hydroxyglutarate as a biomarker for isocitrate dehydrogenase (IDH) mutations in gliomas

Hao-Wen Sim, Romina Nejad, Wenjiang Zhang, et al.

Clin Cancer Res Published OnlineFirst February 18, 2019.

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