Targeted Assessment of G0S2 Methylation Identifies a Rapidly Recurrent, Routinely Fatal Molecular Subtype of Adrenocortical Carcinoma.

Purpose: Adrenocortical carcinoma (ACC) is a rare, aggressive malignancy with few therapies; however, patients with locoregional disease have variable outcomes. The Cancer Genome Atlas project on ACC (ACC-TCGA) identified that cancers of patients with homogeneously rapidly recurrent or fatal disease bear a unique CpG island hypermethylation phenotype, “CIMP-high.” We sought to identify a biomarker that faithfully captures this subgroup. Experimental Design: We analyzed ACC-TCGA data to characterize differentially regulated biological processes, and identify a biomarker that is methylated and silenced exclusively in CIMP-high ACC. In an independent cohort of 114 adrenocortical tumors (80 treatment-naive primary ACC, 22 adrenocortical adenomas, and 12 non-naive/nonprimary ACC), we evaluated biomarker methylation by a restriction digest/qPCR-based approach, validated by targeted bisulfite sequencing. We evaluated expression of this biomarker and additional prognostic markers by qPCR. Results: We show that CIMP-high ACC is characterized by upregulation of cell cycle and DNA damage response programs, and identify that hypermethylation and silencing of G0S2 distinguishes this subgroup. We confirmed G0S2 hypermethylation and silencing is exclusive to 40% of ACC, and independently predicts shorter disease-free and overall survival (median 14 and 17 months, respectively). Finally, G0S2 methylation combined with validated molecular markers (BUB1B-PINK1) stratifies ACC into three groups, with uniformly favorable, intermediate, and uniformly dismal outcomes. Conclusions: G0S2 hypermethylation is a hallmark of rapidly recurrent or fatal ACC, amenable to targeted assessment using routine molecular diagnostics. Assessing G0S2 methylation is straightforward, feasible for clinical decision-making, and will enable the direction of efficacious adjuvant therapies for patients with aggressive ACC.


Introduction
Adrenocortical carcinoma (ACC) is a rare cancer of the adrenal cortex affecting 0.5 to 2 individuals/million/year globally (1,2). Though rare, ACC is frequently aggressive with 35% 5-year survival (3). Therapies for metastatic ACC are primarily palliative, limited to administration of adrenolytic drug mitotane and/or cytotoxic chemotherapy (3). Patients with locoregional ACC routinely receive surgery and adjuvant mitotane, but 50% to 70% recur and develop metastases even after complete (R0) resection (4,5). Retrospective studies suggest adjuvant mitotane prolongs recurrence-free survival (6,7), but its efficacy is limited by its poor pharmacokinetic properties and dose-limiting toxicities. Obtaining therapeutic serum levels of mitotane may take several months to achieve if at all (8). Furthermore, there is a substantial proportion of ACC patients who experience rapid recurrence (<12 months; refs. 4,5,9), whose aggressive disease course may preclude response to mitotane. These patients may instead benefit from more rapidly acting therapies; however, prospectively identifying this subgroup remains challenging.
Histologic grade based on cellular proliferation is the strongest predictor of recurrence following R0 resection in ACC; high-grade disease is associated with higher risk of recurrence (10)(11)(12). Despite its clinical utility, significant caveats complicate interpretation of grade on an individual basis. Evaluation of grade is prone to high interrater variability (13), and outcomes of patients with low-and high-grade disease remain heterogeneous, with rapidly recurrent patients in both strata (10,14). Although some studies indicate clinical factors may be predictive of recurrence (9,15), molecular profiling studies suggest biomarkers may better resolve this heterogeneity by identifying patients with homogeneously dismal outcomes.
We and others have shown that transcriptomes of aggressive ACC are characterized by pronounced cell-cycle activation (16), and a score based on mRNA levels of mitotic regulator BUB1B (BUB1 Mitotic Checkpoint Serine/Threonine Kinase B) and mitochondrial kinase PINK1 (PTEN Induced Putative Kinase 1) discriminates uniformly favorable from poor clinical outcomes (17,18). Recent studies have implicated aberrant epigenetic patterning in ACC pathogenesis, highlighting that aggressive carcinomas bear widespread promoter CpG island hypermethylation (19,20). Notably, the most comprehensive molecular study on ACC to date, The Cancer Genome Atlas project on ACC (ACC-TCGA), similarly identified that rapidly recurrent ACC is distinguished by a CpG island hypermethylation phenotype, "CIMP-high" (21).
Although these studies have illuminated molecular programs core to aggressive ACC biology, clinical translation of "big data"derived biomarkers remains challenging. Thresholds for continuous data, for example mRNA-based biomarkers, vary across patient cohorts (17,18), compromising biomarker utility for prospective clinical management of a rare malignancy. Furthermore, while targeted assessment of DNA methylation appears promising for prognosticating ACC (20,22), measurement strategies frequently rely on several genomic loci, complicated data normalization procedures, and reference benign lesions (22). Finally, it remains unclear if validated biomarkers identify uniform ACC molecular subtypes amenable to clinical assessment of subtype-specific therapeutic approaches. It is therefore not surprising that mRNA and DNA methylation-based biomarkers have yet to be successfully translated clinically to prognosticate ACC, and highlights a strong need for identifying novel biomarkers with simplified, binary readouts and therapeutic import.
Here, we present a new analysis of ACC-TCGA data in which we demonstrate that CIMP-high ACC is a unique, rapidly recurrent ACC molecular subtype, bearing upregulation of cell cycle-and DNA damage-associated cellular programs. We identify that uniform hypermethylation and silencing of the gene G0S2 (G 0 -G 1 Switch 2) is largely exclusive to CIMP-high ACC. We show in an independent cohort that targeted assessment of G0S2 methylation using an overnight assay independently identifies a subgroup of patients with rapidly progressive or fatal disease course. Our data demonstrates that G0S2 methylation status is essentially binary, and thereby has high potential to enable clinicians to prospectively identify ACC patients unlikely to exhibit durable response to standard adjuvant therapy. We also propose that rapidly acting adjuvant cytotoxic agents may benefit patients with this ACC subtype. Finally, our study demonstrates the utility of comprehensive databases like TCGA, and illustrates a pipeline to identify and test clinically relevant biomarkers for ACC that may be extended to other cancers.

Data mining from ACC-TCGA
We downloaded the ACC-TCGA RNA-seq count table and raw data (IDAT files) from the Infinium HumanMethylation450 BeadChip ("450k") platform from the GDC legacy archive (https://portal.gdc.cancer.gov/legacy-archive). We used R (23)/ Bioconductor packages limma (24) and minfi (25) to obtain log2normalized counts per million (CPM) values for gene expression and b and M values for methylation arrays. We used limma to nominate differentially expressed genes (Benjamini-Hochberg FDR-corrected P-value <0.05) between CIMP-high and non-CIMP-high ACC. We used goana (24,26) to identify gene ontology terms enriched among differentially expressed genes in CIMP-high versus non-CIMP-high ACC. REVIGO (27) is an online tool that enables nonredundant visualization of large sets of GO terms based on semantic similarity. We used REVIGO with SimRel semantic similarity algorithm to plot the 200 most significant biological processes up (ranked by increasing P.Up, P.UP <0.05) or down (ranked by increasing P.Down, P.Down <0.05) in Fig. 1C. We used DMRcate (28) to interrogate differentially methylated regions (Stouffer-corrected P-value <0.05) across groups. We used logistic regression on the RNA-seq data to identify transcripts predictive of CIMP-high status. We used pheatmap (29) to perform unsupervised complete hierarchical clustering, and caret (30) to perform k-fold cross-validation.

Patients
Our study includes 114 adrenocortical tumors evaluated from 1989 to 2017. A total of 42 treatment-naive primary

Translational Relevance
Adrenocortical carcinoma (ACC) is a rare, frequently aggressive malignancy with few therapies. Standard of care for patients with locoregional disease is surgery with adjuvant mitotane, but response is variable and unpredictable. The Cancer Genome Atlas project on ACC (ACC-TCGA) revealed that aberrant promoter CpG island hypermethylation ("CIMP-high") independently predicts rapidly recurrent or fatal disease course. In this study, we analyze ACC-TCGA data and identify that uniform hypermethylation and silencing of G0S2 is a hallmark of CIMP-high ACC. We demonstrate in an independent cohort that G0S2 hypermethylation is exclusive to ACC, amenable to binary targeted assessment, and independently predictive of recurrence and death. We also show that CIMP-high ACC exhibit upregulation of pharmacologically targetable cell cycle and DNA damage response programs. Taken together, we demonstrate that evaluation of tumor G0S2 methylation identifies a subgroup of patients with rapidly progressive disease course who may benefit from aggressive adjuvant and surveillance approaches.
ACC, one primary ACC from a patient who received neoadjuvant etoposide/doxorubicin/cisplatinþmitotane, three nonprimary ACC, and 14 cortisol-secreting adrenocortical adenomas (ACA) are from Faculdade de Medicina da Universidade de São Paulo (FMUSP), São Paulo, Brazil; 38 primary ACC, eight non-primary ACC, four aldosterone-secreting ACA, and four cortisol-secreting ACA are from the University of Michigan (UM), Ann Arbor, MI. Diagnosis of ACA/ACC was established by expert pathologic assessment (M.C.N.Z., T.J.G.) of surgical specimen using Weiss criteria (12). Diagnosis of ACA or ACC was assigned to samples with Weiss score <3 or !3, respectively. Informed consent was obtained from all participants, and  ACC-TCGA demonstrates that rapidly recurrent, CIMP-high carcinomas are a unique molecular subtype associated with upregulation of pharmacologically targetable cell cycle-and DNA damage-associated processes. A, ACC-TCGA reveals that DFS of ACC patients with locoregional disease following R0/RX resection can be stratified by CpG island methylator phenotype ("CIMP") status. Patients with CIMP-high carcinoma status have dismal outcomes, with median DFS of 13.6 months compared to failure to achieve median DFS in CIMP-low + CIMP-intermediate group. B, ACC-TCGA reveals that CIMP-high ACC is a unique molecular subtype, associated with "Steroid-high + prolif" transcriptional program (mRNA group), "Noisy" chromosomal landscape with frequent focal copy number gains and losses (SCNA group), and higher incidence of somatic alterations leading to constitutive cell cycle activation. Notably, CIMP-high ACC is not associated with an increased incidence of somatic alterations leading to activation of the Wnt pathway.  ND-2000). cDNA was synthesized (High-Capacity cDNA Reverse Transcription Kit with RNase Inhibitor; Applied Biosciences/Thermo Fisher Scientific; 4374966) from high integrity and high-quality RNA (visual 28S:18S rRNA ratio 2:1 and 260/280 ratio !2.00). qPCR was performed in the QuantStudio 3 Real-Time PCR System (Applied Biosciences/Thermo Fisher Scientific; A28136), using TaqMan Fast Advanced Master Mix (Applied Biosciences/Thermo Fisher Scientific; 4444557) and FAM-MGB-labeled TaqMan Gene Expression Assays (Applied Biosciences/Thermo Fisher Scientific) to evaluate expression of G0S2 (Hs00274783_s1), BUB1B (Hs01084828_m1), PINK1 (Hs00260868_m1), and housekeeping gene GUSB (Hs00939627_m1). TaqMan Gene Expression Assays were performed in triplicate. Gene expression levels were calculated using the DC t method where DC t (X) ¼ C t (X) -C t (GUSB), and BUB1B-PINK1 score calculated as DC t (BUB1B) -DC t (PINK1).

Measurement of G0S2 methylation
Targeted bisulfite sequencing. Assessment of G0S2 methylation by targeted bisulfite sequencing in physiologic tissues, ACA, and ACC was performed by Zymo Research Corporation. Zymo Research Co. designed/validated primers to amplify the G0S2 locus, chr1:209,848,443-chr1:209,848,900 (hg19), using a proprietary pipeline. Submitted gDNA with 260/280 !1.7, intact genomic band (!5 kb) by gel electrophoresis, and sufficient quantity (!100 ng) was subject to bisulfite conversion, targeted amplification, next-generation sequencing library indexing, and sequencing on Illumina MiSeq. Sequence data were demultiplexed and assessed for bisulfite conversion rate, read coverage, mapping efficiency, and CpG coverage. Bisulfite conversion rate was !99% for all samples. Average CpG coverage ranged from 5,000 to 50,000Â. Methylation at each CpG was calculated from the ratio of methylated to total CpG count.
Methylation-sensitive restriction digest/qPCR. Available gDNA from ACC and ACA was subject to methylation-sensitive restriction digestion using EpiTect II DNA Methylation Enzyme Kit To measure intact gDNA following overnight restriction digestion, gDNA was amplified by qPCR using the EpiTect Methyl II PCR Primer Assay for Human G0S2 (Qiagen; Catalog No. EPHS101235-1A) and RT 2 SYBR Green ROX qPCR Mastermix (Qiagen; 330521). Percent G0S2 methylation was calculated arithmetically from M o , M s , M d , and M sd C t values according to manufacturer instructions, using a Microsoft Excel spreadsheet provided by Qiagen.

Statistical analysis
We used Chi-square test to evaluate associations between categorical variables, Mann-Whitney test or Pearson correlation to compare continuous data from two groups, and Kruskal-Wallis with Dunn's multiple comparisons test to compare continuous data from >2 groups. We used pheatmap (29) to perform unsupervised complete hierarchical clustering. We used caret (30) to perform k-fold cross validation. We used receiver operating characteristic (ROC) curve analysis to estimate a cutoff of G0S2 expression that predicts methylation. We used Kaplan-Meier analysis with pairwise log-rank test to compare overall survival (OS) and disease-free survival (DFS), and Cox proportional hazards regression models to estimate hazard ratios for clinical/molecular variables. P-value <0.05 was significant for all analyses. Statistical analyses were performed in GraphPad Prism, MedCalc, and R (23).

ACC-TCGA reveals CIMP-high defines a rapidly recurrent molecular subtype
In ACC-TCGA, comprehensive DNA methylome profiling of 79 treatment-naive primary ACC using the 450k platform clustered ACC into three DNA-methylation-based subtypes: "CIMP-low," "CIMP-intermediate," and "CIMP-high" (21). Although patients with CIMP-low and CIMP-intermediate carcinomas exhibited indistinguishable disease course (log-rank P ¼ 0.22 for DFS of CIMP-low vs. CIMP-intermediate; Supplementary Fig. S1A), patients with CIMP-high carcinomas characteristically exhibited rapidly recurrent or deadly disease course with median DFS following R0/RX resection of 13.6 months (Fig. 1A) and median OS of 36 months ( Supplementary Fig. S1B). Given the striking clinical phenotype associated with the CIMP-high signature, we sought to determine if other molecular classes and somatic alterations identified by ACC-TCGA were associated with this epigenetic program. We performed association tests between CIMP status and ACC-TCGA-defined transcriptome class (mRNA group), somatic copy number alteration profile (SCNA group), or somatic alterations. We observed that CIMP-high carcinomas were distinguished by a transcriptional signature featuring increased expression of steroidogenic and proliferative machinery ("Steroid-high þ prolif." transcriptional program), and a chromosomally "noisy" genomic landscape with numerous arm-level breaks and focal copy number gains and losses (Fig. 1B). CIMP-high ACC also frequently bore somatic alterations leading to activation of the cell cycle; however, CIMP-high status was not associated with an increased incidence of alterations leading to activation of Wnt signaling, present in $40% of ACC ( Fig. 1B; ref. 21).
We next analyzed RNA-seq data (n ¼ 78) from ACC-TCGA to identify differentially expressed genes in CIMP-high compared with non-CIMP-high (CIMP-low þ CIMP-intermediate) carcinomas (Supplementary Table S1). We performed gene ontology analysis on differentially expressed genes and identified that CIMP-high ACC exhibited transcriptional upregulation of numerous cell cycle-and DNA damage-associated biological processes, consistent with the enrichment of cell cycle-activating somatic alterations and chromosomal "noisiness" in this subgroup (Fig. 1C, left). Intriguingly, CIMP-high carcinomas exhibited transcriptional downregulation of a wide array of immunological processes (Fig. 1C, right), suggesting that CIMP-high ACC are relatively immune poor. The convergence of this unique transcriptional program, somatic alterations targeting the cell cycle, and "noisy" chromosomal landscape in CIMP-high carcinomas demonstrates that CIMP-high status defines a distinct molecular subtype of ACC characterized by rapidly recurrent or fatal disease course. Therefore, prospectively identifying CIMP-high carcinomas using targeted molecular markers may have strong clinical utility.

Analysis of ACC-TCGA nominates G0S2
We sought to identify a single biomarker with strong discriminatory power between CIMP-high and non-CIMP-high ACC, straightforward to measure and interpret without reference samples or extensive data manipulation. We were therefore interested in genomic loci that are methylated and silenced exclusively in CIMP-high ACC. We analyzed DNA methylation data from ACC-TCGA to identify regions hypermethylated in CIMP-high compared with non-CIMP-high carcinomas (Supplementary Table  S2). Among the top 10 most hypermethylated regions in our analysis was a 2kb region on chromosome 1 (chr1:209847618-209849445, hg19; Supplementary Fig. S2), encompassing 13 contiguous 450k probes and spanning the G0S2 gene locus (non-CIMP-high vs. CIMP-high: max b fold-change À0.709, mean b fold-change À0.508, Stouffer-corrected P-value 4.32 Â 10 À134 ). Our analysis of differentially expressed genes in CIMP-high compared with non-CIMP-high ACC also revealed G0S2 was among the top five downregulated genes, nearly silenced in CIMP-high carcinomas (CIMP-high vs. non-CIMP-high: log2 fold change À5.21, Benjamini-Hochberg FDR-corrected P-value 2.31 Â 10 À10 ), and highly predictive of CIMP-high status (logistic regression coefficient À0.925, P-value 2.10 Â 10 À5 ; Supplementary Table S1). These results suggested G0S2 is silenced by hypermethylation in a subgroup of ACC as reported in a smaller ACC cohort (20), and that low G0S2 expression and hypermethylation predict CIMP-high status. This observation was particularly intriguing as analysis of GTEx RNA-seq data (31) revealed G0S2 is highly expressed in the physiologic adrenal gland (Supplementary Fig. S3).
We then plotted all 450k probes spanning the G0S2 locus in each tumor sample from ACC-TCGA, ranked by decreasing G0S2 expression. Strikingly, tumors exhibited an "all or none," binary pattern of methylation, with uniform hypermethylation (probe b value >0.5) across the gene locus nearly restricted to CIMP-high carcinomas, and associated with reduced G0S2 expression ( Fig. 2A). Indeed, average methylation level of probes residing in the G0S2 CpG island is significantly higher in CIMP-high compared with non-CIMP-high ACC (P < 0.0001, Kruskal-Wallis with Dunn's multiple comparisons test; Fig. 2B), expression of G0S2 is significantly lower in CIMP-high compared with non-CIMP-high ACC (P < 0.0001, Kruskal-Wallis with Dunn's multiple comparisons test; Fig. 2C), and both metrics are strongly inversely correlated (P < 2.2 Â 10 À16 , r ¼ À0.82, R 2 ¼ 0.68, Pearson correlation; Fig. 2D). The inverse correlation between G0S2 methylation and expression in ACC-TCGA suggested that measurement of G0S2 methylation (or expression in the absence of genomic DNA) can enable identification of CIMP-high ACC.
Finally, we sought to evaluate the ability of G0S2 methylation alone to classify ACC-TCGA samples by CIMP status. We performed unsupervised hierarchical clustering analysis using the logit-transformed b values of 450k probes lying within the G0S2 CpG island ( Supplementary Fig. S4A). This analysis identified two distinct clusters of samples: one cluster with samples bearing either no or low levels of G0S2 methylation ("G0S2 unmethylated") corresponding to 2/3 of ACC-TCGA, and one with samples bearing high levels of uniform or heterogeneous G0S2 methylation ("G0S2 methylated") corresponding to 1/3 of ACC-TCGA. The G0S2 methylated cluster was strongly enriched for CIMP-high ACC (P < 0.0001, Fisher exact test), capturing 18/19 CIMP-high samples. To evaluate the performance of a logistic regression model utilizing G0S2 methylation to discriminate CIMP-high from non-CIMPhigh ACC, we performed an internal k-fold cross validation (k ¼ 5, 20 repeats) on the average of the logit-transformed b values of probes residing in the G0S2 CpG island. Our fitted logistic regression model is described in Supplementary Table S3, and the ROC curve (ROC AUC ¼ 0.928; 95% CI, 0.8235-1) is depicted in Supplementary Fig. S4B. At average G0S2 methylation >0.5200819 (measured by 450k array), we can predict assignment to CIMP-high using G0S2 methylation alone at 94.87% accuracy, with 94.74% sensitivity, 94.92% specificity, 85.71% positive predictive value, and 98.25% negative predictive value. This analysis demonstrates that G0S2 hypermethylation has high discriminatory power to distinguish CIMP-high from non-CIMP-high ACC, and shows that unsupervised clustering of G0S2 CpG island methylation enables reliable identification of CIMP-high samples. Taken together, our analysis of ACC-TCGA suggests that assessment of G0S2 methylation and/or expression can reliably identify CIMP-high ACC without comprehensive DNA methylome data.

G0S2 hypermethylation and silencing is exclusive to ACC
We sought to evaluate G0S2 methylation in an independent ACC cohort, and determine if physiologic tissues and ACA exhibit G0S2 methylation. We collected gDNA and mRNA from a retrospective cohort of 80 treatment-naive primary ACC, 22 ACA, and 12 non-naive/non-primary ACC, summarized in Supplementary Table S4. We also collected gDNA from extra-adrenal tissues, microdissected adult adrenal cortex, and total adult adrenal cortex. We performed targeted bisulfite sequencing of G0S2 and determined that uniform hypermethylation throughout the locus is pathologic, exclusive to a subset of primary ACC and nonprimary/recurrent ACC ( Fig. 3A; Supplementary Table S5). These findings are supported by unsupervised hierarchical clustering analysis on logit-transformed targeted bisulfite sequencing data ( Supplementary Fig. S5A), in which we recapitulate G0S2 unmethylated and G0S2 methyl-ated clusters we identified in ACC-TCGA. We also demonstrate that physiologic tissue and benign adrenocortical tumors cluster with G0S2 unmethylated ACC, whereas only ACC with high levels of uniform or heterogeneous G0S2 methylation reside in the G0S2 methylated cluster. The association of physiologic adrenal cortex samples with G0S2 unmethylated ACC is consistent with the high expression of G0S2 in the physiologic adrenal gland (Supplementary Fig. S3).
The uniform pattern of G0S2 methylation in ACC-TCGA and our cohort indicated that locus methylation may be accurately measured by methylation-sensitive restriction digestion/qPCRbased methods instead of bisulfite-based approaches. We evaluated G0S2 methylation using one such approach, EpiTect (Qiagen). EpiTect and targeted bisulfite sequencing were highly concordant ( Fig. 3B; Supplementary Fig. S5C), demonstrating that ACA have no measurable G0S2 methylation, whereas ACC  Each row represents a sample, and samples are ranked in decreasing order of G0S2 expression (displayed as "Scaled Expression"; RNA-seq CPM scaled to fall in the range of 0-1), with assignment to CIMP status indicated right. Note that hypermethylation of the entire G0S2 locus is largely exclusive to CIMP-high ACC, and that hypermethylation is associated with reduced or absent expression of G0S2 transcript. Indicated by the pink bar at the bottom of the figure are probes lying within the G0S2-associated CpG island. B, Dot plot displaying average b value of probes indicated in pink from A in ACC-TCGA samples by CIMP group demonstrates that methylation of the G0S2 CpG island distinguishes CIMP-high ACC, and is significantly higher in CIMP-high ACC (clustered at >0.5) compared to CIMP-low or CIMP-intermediate ACC (clustered close to 0). C, Expression of G0S2 in ACC-TCGA samples by CIMP group demonstrates that reduced G0S2 expression is a striking feature of CIMP-high ACC. D, Scatterplot displaying the relationship between logit-transformed average b value from B and G0S2 expression from C demonstrates that G0S2 methylation and expression are inversely correlated, with CIMP-high ACC bearing the highest levels of G0S2 methylation and lowest levels of G0S2 expression. In B and C, mean and 95% CI of the mean are represented by bar and whiskers, respectively. have a bimodal distribution ( Fig. 3C; 40% of ACC in FMUSPþUM Primary ACC Cohort have G0S2 hypermethylation). We then sought to evaluate the concordance between EpiTect and binary G0S2 methylation status defined by unsupervised hierarchical clustering analysis (Supplementary Fig. S5A). For all samples with paired EpiTect and targeted bisulfite sequencing data (n ¼ 74; 60 ACC, 14 ACA), we performed an internal k-fold cross validation (k ¼ 5, 20 repeats) to evaluate a logistic regression model utilizing EpiTect measurements to discriminate these two classes. Our fitted logistic regression model is described in Supplementary  Table S6   Hypermethylation of the G0S2 locus is binary, exclusive to a subset of ACC, amenable to targeted assessment, and associated with decreased G0S2 expression. A, Heatmap depicting results of bisulfite sequencing of the G0S2 locus in physiologic tissues and adrenal tumors. Each row is a CpG position in the G0S2 locus, and any sequenced CpGs in positions corresponding to probes on the 450k array are indicated by arrowheads. Each column is a sample; "NON" refers to human extra-adrenal tissues (from left: kidney, lung, and corpus luteum); "zF" refers to the cortisol-secreting zona fasciculata layer of the adrenal cortex, microdissected from adult adrenal cortex; "zR" refers to the androgen-secreting zona reticularis layer of the adrenal cortex, microdissected from adult adrenal cortex; "cortex" refers to an entire adult adrenal cortex; "APA" refers to an aldosterone-producing adrenocortical adenoma (ACA) and "CPA" refers to a cortisol-producing ACA.
Only treatment-naive primary ACC samples are shown here. All tumor samples in this panel are from FMUSP+UM ACA and Primary ACC Cohorts. The G0S2 locus is unmethylated in extra-adrenal tissues, the physiologic adrenal cortex and ACA evaluated here. Hypermethylation of the entire G0S2 locus is exclusive to a subset of ACC. B, Targeted assessment of G0S2 methylation by EpiTect (Qiagen, USA; upper panel) in treatment-naive primary ACC (n = 60) recapitulates results of bisulfite sequencing (lower panel; each dot represents the methylation level of a single CpG, and median and 95% CI are represented by bar and whiskers, respectively). We performed an internal k-fold cross-validation (k = 5, 20 repeats) on all samples with paired EpiTect and targeted bisulfite sequencing data (n = 74; 14 ACA, 60 ACC) to identify the appropriate EpiTect cutoff to classify a sample as bearing G0S2 hypermethylation (Supplementary Fig. S5 and Supplementary Table S6). This analysis established a threshold of >4.696% methylation by EpiTect as a cutoff for pathologic hypermethylation of the G0S2 locus, which is depicted here by the dotted line. C, Dot plot displaying distribution of G0S2 methylation as measured by EpiTect in FMUSP+UM Primary ACC and ACA Cohorts demonstrates that G0S2 methylation is clustered at 0% in ACA (n=14) and is bimodally clustered at 0% and >50% in ACC (n=70) with few intermediate values, consistent with ACC-TCGA. Mean of each group is indicated by the bar, and EpiTect cutoff is indicated by the dotted line. D, Evaluation of G0S2 methylation in ACA and primary ACC without methylation of the G0S2 locus ("G0S2 UM") or with hypermethylation of the G0S2 locus ("G0S2 M") demonstrates that G0S2 methylated tumors have lower expression of G0S2 compared to other adrenocortical tumors, consistent with ACC-TCGA. Note that plot depicts -DC t (G0S2), so a smaller value indicates lower expression. Mean and 95% CI of the mean are represented by bar and whiskers, respectively.
Together with ACC-TCGA, these data illustrate that uniform G0S2 hypermethylation and silencing is exclusive to a subset of ACC, and that G0S2 methylation can be accurately measured using restriction digest/qPCR-based methods or inferred from G0S2 expression when gDNA is unavailable.

G0S2 hypermethylation independently predicts rapid recurrence and death
High histologic grade is an established predictor of dismal outcomes in ACC (10)(11)(12). In the FMUSPþUM Primary ACC Cohort, patients with high-grade tumors accordingly exhibited rapidly recurrent disease following R0/RX resection (median DFS of 7.8 months). However, 3/10 of patients with high grade tumors remain disease free after >48 months follow-up and 11/32 patients with low-grade disease exhibited recurrence, demonstrating that proliferation-based grade alone stratifies patients into heterogeneous groups (Fig. 4A). In striking contrast, stratification by G0S2 methylation (measured by EpiTect or inferred from G0S2 expression when gDNA unavailable) demonstrates that patients with tumors bearing G0S2 hypermethylation homogeneously exhibited rapidly recurrent or fatal disease course (median DFS following R0/RX resection of 14 months and median OS of 17 months; Fig. 4B and C). Remarkably, G0S2 hypermethylation was identified at comparable frequency in low-and high-grade tumors (P ¼ 0.076, Fisher exact test), with G0S2 hypermethylation in 13/44 lowgrade tumors (Fig. 4D), suggesting that G0S2 hypermethylation identifies aggressive disease in tumors inadequately stratified by tumor grade. Finally, carcinomas with G0S2 hypermethylation were identified at comparable frequency in patients with localized ACC (ENSAT I-II), localized ACC with locoregional invasion or lymph node involvement (ENSAT III), and ACC with distal metastases (ENSAT IV) at diagnosis (P ¼ 0.31, Chi-square test; Fig. 4E). Notably, among 17 ENSAT I-III patients with R0/RX resection and G0S2 hypermethylation, only one patient remains disease free at >24 months.
We performed Cox proportional hazards regression analysis to evaluate the significance of G0S2 hypermethylation at predicting recurrence and death compared with other clinical metrics in the FMUSPþUM Primary ACC Cohort (Table 1) (Table 1). These observations demonstrate that G0S2 hypermethylation independently predicts rapidly recurrent disease course prior to detection of macroscopic disease spread, and routinely fatal disease course in the setting of disseminated disease.

G0S2 hypermethylation facilitates ACC stratification in combination with BUB1B-PINK1
Though G0S2 hypermethylation independently predicts uniformly dismal disease course, patients without G0S2 methylation exhibited heterogeneous outcomes ( Fig. 4B and C). We sought to determine if alternative molecular predictors could resolve this heterogeneity by separating patients with certain favorable prognosis from those with intermediate recurrence risk. We and others have shown that a score derived from expression of BUB1B and PINK1 (BUB1B-PINK1) can stratify ACC into "good prognosis" and "bad prognosis" groups (17,18). The disease course of "good prognosis" ACC has been likened to that of patients with ACA, as patients were primarily cured by surgery. Interestingly, "good prognosis" ACC had BUB1B-PINK1 indistinguishable from ACA (17).
ACA and ACC I tumors had no difference in BUB1B-PINK1 (P > 0.05, Kruskal-Wallis with Dunn's multiple comparisons test), whereas ACC II and ACC III had different BUB1B-PINK1 from ACA (P < 0.0001) and ACC I (II vs. I: P < 0.005, III vs. I: P < 0.0001). ACC II and ACC III had indistinguishable BUB1B-PINK1 (P > 0.05), suggesting BUB1B-PINK1 cannot further stratify G0S2 methylated carcinomas (Fig. 5A). Using this combination of BUB1B-PINK1 and G0S2 methylation status, we stratified the FMUSPþUM Primary ACC Cohort into three groups with variable risk of recurrence (Fig. 5B) and death (Fig. 5C). In patients with G0S2 unmethylated carcinomas, we could now distinguish those who remain disease free and alive (ACC I) from those with history of recurrence and death (ACC II). All clinical and molecular data are summarized in Supplementary Table S9.
These results demonstrate the combined utility of G0S2 methylation and BUB1B-PINK1 score in stratifying patients into three groups, two of which have uniformly favorable or dismal outcomes. These data illustrate a strategy for implementing molecular biomarkers in series to precisely define risk categories in ACC, with high potential to impact clinical management.

Discussion
ACC is a rare cancer with variable outcomes inadequately stratified by clinical and histologic metrics. ACC-TCGA identified three molecular subtypes of ACC and posited that clinical heterogeneity arises from unique transcriptional and epigenetic programs driving each class (21). We noted that the genomes of rapidly recurrent carcinomas are characterized by aberrant methylation directed to promoter CpG islands, "CIMP-high." In this study, we also identified that CIMPhigh carcinomas comprise a distinct molecular subtype of ACC, bearing upregulation of cell cycle-and DNA damageassociated cellular programs. However, prospective assessment of this complex signature is infeasible for routine molecular diagnostics. Hypermethylation of the G0S2 locus predicts rapid recurrence and death in an independent ACC cohort. A, Stratification of carcinomas from FMUSP+UM Primary ACC Cohort by grade (mitotic counts, where <20 mitotic counts/50 high-powered fields [HPF] is "low grade" and >20/50 HPF is "high grade") identifies two subgroups of carcinomas with failure to achieve median DFS (low grade) and median DFS of 7.8 mo (high grade) following R0/RX resection. B, Stratification of primary ACC by measured or inferred G0S2 methylation status demonstrates that patients with G0S2 methylated carcinomas have rapid recurrence and median DFS of 14 months following R0/RX resection. In contrast to patients with G0S2 unmethylated carcinomas that fail to achieve median DFS, only 1 patient in the G0S2 methylated group remains disease-free at >24 months, consistent with CIMP-high/G0S2 methylated carcinomas from ACC-TCGA. C, Stratification of primary ACC by measured or inferred G0S2 methylation status demonstrates that patients with G0S2 methylated carcinomas have dismal OS outcomes, with median OS of 17 months compared to failure to achieve median OS in the G0S2 unmethylated group. D, G0S2 methylated primary carcinomas were identified at statistically comparable frequency in patients with high grade disease (13/25) and in patients with low grade disease (13/44). E, G0S2 methylated primary carcinomas were identified in patients with ENSAT II-IV disease at diagnosis without predilection for late stage disease.
Here, we identified that hypermethylation and silencing of G0S2 is a hallmark of ACC-TCGA CIMP-high carcinomas. In an independent cohort, we determined that G0S2 hypermethylation is restricted to 40% of ACC, absent from ACA and physiologic tissues. We then demonstrated that measurement of G0S2 methylation using a straightforward, overnight assay independently identifies a homogeneous subgroup of ACC patients with rapidly recurrent and fatal disease course. G0S2 methylation is essentially binary (carcinomas are either G0S2 methylated or G0S2 unmethylated), subverting a requirement for complicated analytical strategies and reference samples. G0S2 hypermethylation almost invariably predicts rapidly recurrent and fatal disease in patients with localized, locoregional, and disseminated ACC, including one third of patients with low-grade disease. Interestingly, we observed only one patient with tumor G0S2 hypermethylation who remains disease free >24 months following R0/RX resection. Given that adjuvant mitotane therapy is the standard of care at FMUSP and UM, our data suggest that G0S2 hypermethylation predicts short-lived remission regardless, reinforcing the need to develop improved adjuvant therapies for high-risk patients.
Expert opinion proposes that adjuvant cytotoxic chemotherapy should be considered as alternative to mitotane in high-risk patients (32,33). However, a precise definition of "high risk" is lacking, relying on histologic grade and subjective clinical assessment. Our study suggests that prospective assessment of G0S2 methylation would objectively identify uniformly high-risk patients. Additionally, we illustrated that G0S2 methylation can be combined in series with validated biomarkers (BUB1B-PINK1) to stratify ACC into three groups, with uniformly favorable (recurrence free), intermediate, and uniformly dismal (inevitable recurrence) clinical outcomes. Such a strategy could dramatically improve clinical management and direct future trials on adjuvant therapies (Fig. 5D). The major ongoing clinical trial evaluating the efficacy of adjuvant mitotane in low-intermediate risk ACC ("ADIUVO," NCT00777244) defines risk using grade; our study suggests this criterion is inadequate, as up to one third of these patients will have tumor G0S2 hypermethylation and likely recur on adjuvant mitotane. As new clinical trials are designed to evaluate adjuvant therapies in high-risk patients, we propose assessment of G0S2 methylation to determine risk as in Fig. 5D.
High-risk CIMP-high/G0S2 methylated ACC is associated with a unique transcriptional, copy number, and mutational landscape in ACC-TCGA, suggesting a common biological program underlies this aggressive ACC subtype (21). We demonstrated that CIMP-high carcinomas are chromosomally noisy, frequently bear somatic alterations leading to activation of cell cycle, and exhibit a transcriptional program characterized by increased expression of steroidogenic enzymes, proliferation machinery, and genes coordinating DNA damage-associated processes. Cell cycle and DNA damage-associated genes upregulated in CIMP-high ACC include MELK, AURKB, CDK6, PLK1, and TOP2A which have been successfully targeted in preclinical and translational models of ACC (34)(35)(36)(37)(38), and may even predict clinical responsiveness to combination therapy with etoposide, doxorubicin, cisplatin, and mitotane (39). Although there is currently little data to support a clinical trial evaluating utility of demethylating agents alone in   I  ACC II  ACC III   6  6  5  3  2  1  0  0  41 22 14  8  8  3  3  1  31  8  6  4  3   ACC (40,41), studies in other solid tumors demonstrate that epigenetic priming with demethylating agents may increase efficacy of cytotoxic therapies and targeted DNA repair inhibitors (42)(43)(44). Together, these observations suggest that therapies targeting the cell cycle, DNA repair, and epigenetics may be efficacious in patients with CIMP-high/G0S2 methylated ACC and warrant future study. The molecular mechanisms driving CpG island hypermethylation in IDH1/2-wild-type cancers including CIMP-high ACC are still poorly understood (45). Our data and studies identifying G0S2 hypermethylation in other cancer types (46,47) suggest that methylation of this locus is driven by the same unknown molecular programs supporting hypermethylation in other regions of the CIMP-high cancer genome. However, the high expression of G0S2 in lipid-rich tissues including the adrenal gland ( Supplementary Fig. S3) suggests that G0S2 may have tissue-specific tumor suppressor roles. Although G0S2 has been best characterized as a regulator of lipid metabolism (48), recent studies have demonstrated that methylation-dependent silencing of G0S2 in breast cancer augments oncogenic PI3K/mTOR signaling (49) and MYC transcriptional activity (50). These studies suggest that G0S2 may have important roles in adrenocortical biology, including a similar tumor suppressor function worthy of future investigation.
In conclusion, our study is the first to reduce the complex genome-wide CpG island hypermethylation signature from ACC-TCGA to a single, binary molecular marker, amenable to targeted assessment using routine molecular diagnostics. Assessing G0S2 methylation as we have here is inexpensive, straightforward, compatible with a timeline feasible for clinical decision-making, and will enable the direction of efficacious adjuvant therapies for patients with uniformly aggressive ACC. Future studies will be directed towards evaluating G0S2 methylation prospectively, in circulating tumor DNA, and in readily available clinical samples including formalin-fixed paraffin-embedded tissues.