Landscape of Genomic Alterations in Pituitary Adenomas

Abstract

Purpose: Pituitary adenomas are the second most common primary brain tumor, yet their genetic profiles are incompletely understood.Experimental Design: We performed whole-exome sequencing of 42 pituitary macroadenomas and matched normal DNA. These adenomas included hormonally active and inactive tumors, ones with typical or atypical histology, and ones that were primary or recurrent.Results: We identified mutations, insertions/deletions, and copy-number alterations. Nearly one-third of samples (29%) had chromosome arm-level copy-number alterations across large fractions of the genome. Despite such widespread genomic disruption, these tumors had few focal events, which is unusual among highly disrupted cancers. The other 71% of tumors formed a distinct molecular class, with somatic copy number alterations involving less than 6% of the genome. Among the highly disrupted group, 75% were functional adenomas or atypical null-cell adenomas, whereas 87% of the less-disrupted group were nonfunctional adenomas. We confirmed this association between functional subtype and disruption in a validation dataset of 87 pituitary adenomas. Analysis of previously published expression data from an additional 50 adenomas showed that arm-level alterations significantly impacted transcript levels, and that the disrupted samples were characterized by expression changes associated with poor outcome in other cancers. Arm-level losses of chromosomes 1, 2, 11, and 18 were significantly recurrent. No significantly recurrent mutations were identified, suggesting no genes are altered by exonic mutations across large fractions of pituitary macroadenomas.Conclusions: These data indicate that sporadic pituitary adenomas have distinct copy-number profiles that associate with hormonal and histologic subtypes and influence gene expression. Clin Cancer Res; 23(7); 1841-51. ©2016 AACR.

Figure 1

Genomic disruption in pituitary adenomas. (A) Heatmap of copy-number alterations spanning the genome (y-axis) across 42 pituitary adenomas (x-axis). Features associated with each sample are indicated along the top. (B) Histogram of fraction of genome disrupted across these pituitary tumors. The red line indicates the threshold we use to distinguish the class of tumors with minimal to no genome disruption from those with extensive disruption. (C) Differences in fraction of genome disrupted between functional (ACTH, GH, PRL-expressing) and typical and atypical nonfunctional pituitary adenomas. * indicates p<0.05.

Figure 2

Genome disruption across cancers. (A) Extent of genomic disruption (y-axis) among minimally- and extensively-disrupted pituitary tumors (Pit_quiet and Pit_disrupted, respectively) and 12 other tumor types (x-axis). (B) Ratio between the fraction of the genome disrupted by focal copy-number alterations (involving less than half a chromosome arm) and the fraction disrupted by larger (arm-level) events (y-axis) across these same tumor types. Samples with ratios greater than two, typically resulting from lack of arm-level events and including all Pit_quiet samples, are not shown. Each dot indicates a single tumor; bars and whiskers indicate means and standard errors of the mean (SEMs). AML, acute myeloid leukemia; GBM, glioblastoma multiform; hg Meningioma, high grade meningioma; Lung sc, lung squamous cell.

Figure 3

Copy number alterations in pituitary tumors. Genome-wide profile of homologous copy ratios in 3 samples of pituitary adenoma processed using ABSOLUTE, demonstrating a (A) tetraploid (genome-doubled) and (B) haploid state. Color scheme indicates low (blue), high (red), and balanced (purple) levels of alleles, with homologous copy ratio histogram to the right of the plot. (C) Significance (as False Discovery Rate q-values; x-axis) of chromosomal gains (right, red) and losses (left, blue) across the genome (y-axis) among 41 pituitary adenomas from unique patients. The dotted line indicates q=0.1. (D) Copy neutral loss of heterozygosity (LOH) of chromosome 11 was also observed in an otherwise genomically quiet tumor, as illustrated by allelic copy number analysis.

Figure 4

Fluorescence in situ hybridization using probes to CDK4 (red) and the centromeres of chromosomes 2 and 12 (cen2 and cen12; aqua and green, respectively). (A) A pituitary tumor with chromosome 12 gains, as indicated by greater staining of CDK4 and cen12 relative to cen2. (B) A tumor sample without chromosome 12 gains, as indicated by equal staining of all probes.

Figure 5

Magnitude of differences (y-axis) within expression profiles from disrupted and quiet tumors (x-axis) (38, 40).

Figure 6

Characteristics of mutations in pituitary adenomas. (A) Mutation rates (y-axis) across pituitary-related and unrelated neoplasms (x-axis). (B) Power to detect mutations as recurrent in our cohort (y-axis) as a function of the fraction of pituitary adenomas that harbor the mutation (x-axis).