Molecular Pathology of Adrenal Cortical Tumors: Separating Adenomas from Carcinomas
Thomas J. Giordano, MD, PHD
Abstract
Adrenal cortical carcinoma is a rare but interesting endocrine tumor. Its diagnosis is usu- ally straightforward using morphologic assessment and supplemental immunohistochem- istry. However, diagnostically challenging cases exist and pathologic evaluation would benefit from the availability of adjunctive molecular testing. Here, the relevant molecu- lar pathology of adrenal cortical tumors is reviewed with special reference to those meth- ods (e.g., DNA microarrays) that hold promise for improved diagnosis and prognosis, and prediction of therapeutic response.
Key Words: Adrenal cancer; genotyping; DNA microarray; molecular profiling.
Introduction
Adrenal cortical tumors (ACTs) are rela- tively rare with an incidence of one or two cases per million per year. Nonetheless, these tumors deserve attention for several important reasons. First, the incidence of adrenal tumors incidentally discovered during medical investigation (the so-called “adrenal incidentaloma”) has risen over the last decade owing to improved and more frequent imaging studies [1]. Second, these tumors are clinically and pathologically interesting due to their associated hor- monal [2] and genetic syndromes [3]. Finally, the available therapeutic choices for adrenal cortical carcinoma are quite lim- ited [4] and, thus, there is a significant clinical need for new, more effective, and less toxic therapies. Many of these aspects, as well as others, were discussed at an international meeting held in Ann Arbor in September 2003 [5].
Histopathology combined with immuno- histochemistry (IHC) of ACTs is often adequate to provide highly informed diag-
noses. However, there are diagnostically challenging cases in which adjunctive molecular methods would be useful. Furthermore, as the fields of surgical pathology and oncology becomes more molecularly oriented in general, it is both interesting and relevant to ask how reliably and accurately do molecular approaches separate benign and malignant ACTs. Here, the molecular pathology relevant to the distinction of benign and malignant ACTs is presented.
Department of Pathology, University of Michigan Medical School, Ann Arbor, Michigan.
Address correspondence to Dr. Thomas J. Giordano, Associate Professor, Department of Pathology, UH 2G332/0054, Ann Arbor, MI 48109-0054. E-mail: Giordano@umich.edu
Endocrine Pathology, vol. 17, no. 4, 355-364, Winter 2006 @ Copyright 2006 by Humana Press Inc. All rights of any nature whatsoever reserved. 1046-3976/1559-0097 (Online)/ 06/17:355-364/$30.00
Immunohistochemical Approaches
While molecular approaches are the focus of this review, it is also relevant to discuss the use of immunohistochemistry (IHC) as a diagnostic aid in the evaluation of ACTs, especially as many of the molecu- lar markers discovered by molecular pro- filing are likely to be converted in the future into IHC assays. Many of the studies per- formed to date have focused on rates of tumor cell proliferation, an approach
| Locus of gain or loss | Sidhu [14] (n = 13) | Kjellman [13] (n = 8) | Zhao [15] (n = 12) | Dohna [12] (n = 14) |
|---|---|---|---|---|
| 1p loss | 62% | 13% | 67% | 14% |
| 2q loss | 31% | 38% | 42% | 0% |
| 4p gain | 31% | 38% | 25% | 21% |
| 4q gain | 31% | 50% | 0% | 7% |
| 5p gain | 46% | 50% | 25% | 57% |
| 5q gain | 38% | 50% | 33% | 50% |
| 11q loss | 31% | 50% | 42% | 0% |
| 12p gain | 38% | 13% | 17% | 43% |
| 12q gain | 38% | 13% | 50% | 86% |
| 17p loss | 54% | 50% | 8% | 0% |
| 19 gain | 31% | 38% | 0% | 43% |
| 19 loss | 23% | 0% | 0% | 0% |
| 22 loss | 38% | 38% | 0% | 7% |
supported by the subsequent molecular profiling studies. These studies revealed comparatively high expression of many proliferation-related genes in adrenal cor- tical carcinomas (ACCs) (see below). The mib1/Ki-67 labeling index was shown to possess diagnostic value in most studies [6- 8], as well as the corresponding topo- isomerase 2 alpha labeling index [9]. Both of these markers were subsequently shown to correlate at the protein and mRNA levels, providing further support for their use [10].
In addition to markers of proliferation, some studies have investigated the use of IGF2 protein as an IHC marker of ACC, given its important role in pathogenesis. Expression of IGF2 protein was associated with ACC in a statistically significant man- ner [11], prompting the authors to sug- gest that IGF2 IHC is a useful tool that could be added to the multifactorial evalu- ation of ACTs.
Genotyping Methods
As with other types of human tumors, ACTs acquire changes in their DNA (mutations) that manifest in the usual forms, ranging from gross chromosomal abnormalities, such as rearrangements, to
the most minimal type of change, single nucleotide substitutions (point mutation). Many types of mutations have been exam- ined in an effort to better understand the pathogenesis of ACTs, but it was also hoped that they could be exploited to develop robust and objective ways to dif- ferentiate benign [adrenal cortical adenoma (ACA)] and malignant tumors (ACC).
Comparative Genomic Hybridization
The experimental methods used to examine mutations in ACTs include “com- parative genomic hybridization” (CGH), which identifies large regions of chromo- somes that have either undergone deletion or amplification. By examining a large cohort of ACTs with CGH, it is possible to identify regions that have consistently been altered. Recurrent chromosomal alterations are likely to be related to patho- genesis and not simply a consequence of genomic instability. Thus, CGH poten- tially identifies regions that contain either oncogenes (regions of copy number gain) or tumor suppressor genes (regions of copy number loss). To date, there have been four CHG studies performed on adult ACTs [12-15], and the results are summarized in Table 1.
While CGH is a powerful chromosomal alteration discovery tool with the resulting CGH data in ACTs supporting a general model in which ACA progresses to ACC in a stepwise fashion, CGH studies have not yet yielded a reliable and accurate geno- type that can be clinically exploited to assist in the diagnosis of these tumors. Moreover, it is highly unlikely, especially given the promising prospects of assessing gene expression by microarrays (see below), that CGH will be clinically implemented for ACTs.
Single Marker Genotyping
One of the most successful approaches for the identification of cancer-related genes has been to isolate the genes respon- sible for familial cancer syndromes. There are two such syndromes in which ACC is a common manifestation; Beckwith- Wiedemann syndrome (BWS) [Online Mendelian Inheritance in Man (OMIM) entry 130650] and Li-Fraumeni syndrome (OMIM entry 151623). BWS is an over- growth disorder associated several tumor types. The mutations causing BWS have been tightly linked to the chromosomal region 11p15.5, which is a complex and imprinted region that contains several genes including H19, KIP2, and IGF2. Based on numerous studies, the role of IGF2 in sporadic and familial ACC has been well established [10,11,16-26]. IGF2 can undergo a variety of rearrangements, the most common being paternal isodisomy (loss of maternal allele and duplication of paternal allele), that result in increased IGF2 expression. These rearrangements are essentially restricted to ACCs [21], an observation that lends support to the notion of using these changes for clinical diagnosis, although I am not aware of a CLIA-approved laboratory that performs these tests for ACTs.
The Li-Fraumeni syndrome has been linked to mutations of the TP53 gene [27]. Many studies have examined TP53 muta- tions in ACTs with highly variable results [27-41]. Generally TP53 mutations were found in 20-67% of ACCs and were rare in ACAs. While the highest mutation fre- quency reported in ACCs was 67%, this is not high enough to be used clinically to accurately separate benign and malignant tumors. Loss of heterozygosity (LOH) studies hold the greatest diagnostic poten- tial [19]. However, the same is true for TP53 LOH genotyping in that there are no labs offering this testing for ACTs.
Other mutations have been associated with ACTs (reviewed in ref. 42) such as mutations of the MEN1 [43-45] and PRKARIA [46-49] genes, but they have not been demonstrated to have utility in separating ACAs from ACCs. Recent mutational work on the beta-catenin gene (CTNNB1) revealed similar mutations frequencies in ACAs and ACCs [50]. Thus, while interesting and important to patho- biology, there is no diagnostic utility in examining ACTs for CTNNB1 mutations.
Molecular Profiling Studies
One of the difficulties and limitations of using genotyping in a clinical setting is that several different types of mutations can inactivate (or activate) the same gene. Point mutations can be distributed across large genes (i.e., point mutations of MEN1) making their identification technically dif- ficult. Furthermore, it is also possible to mutate a single gene via distinct mutational mechanisms, thereby requiring different types of assays for the different types of mutations. For example, the most common type of BRAF mutation in papillary thy- roid carcinoma is a point mutation, but much less common translocations and
A
70
First two principal components using 2913 probe-sets (mean>200, CV>0.5)
B
Normals
C7
C14
C19
Second Principal Component
☐ Adenoma
C14
50
Carcinoma
C11
C18
C33
C15
30
C8
C4
☐
C17
10
☐
C13
A22
☐
A21
☐
☐
H29
-10
A28
C19
C13
A30
N6
N10
-30
N9
-70
-50
First Principal Component
-30
-10
10
30
C
6
First two principal components using 91 probe-sets (p <. 01, FC>3)
D
Normal
C13
C19
Second Principal Component
4
C13
☐ Adenoma
C14
Carcinoma
C17
2
C4
C18
C15
0
C14
☐
C8
C33
C11
-2
C7
A22
A21
-4
A28
H29
A30
-6
C19
N10
N9
N6
-8
-10
-8
-6
-4
First Principal Component
-2
0
2
4
6
8
10
amplifications have also been reported [51- 53]. Thus, a method based on DNA sequencing for point mutations will fail to identify the other mutations. For this rea- son, as well as others, there is much excite- ment over high-throughput methods to examine gene expression in tissues [54-58]. The development of commercially avail- able DNA microarrays has permitted their use in a variety of clinicopathologic stud-
ies and the first such studies of adrenal cor- tical tumors have been published [10,59].
In a study from our laboratory [10], we used oligonucleotide arrays and a small cohort of normal adrenal cortex, ACAs, and ACCs to identify gene expression pro- files that robustly separated benign and ma- lignant tumors, including one low-grade tumor. Using a large group of variably expressed genes selected without reference
Steroidogenesis
IGF-2
319
320
317
319
81% = carcinomas (Weiss≥4)
316
90% = adenomas (Weiss≤3)
212
311
205
103
202
320
103
308
206
307
111
325
106
306
118
104
219
203
107
Molecular Diagnosis of Adrenal Cancer
204
217
315
117
324
110
303
113
304
208
314
109
302
105
312
218
313
210
305
207
322
307
321
204
201
104
318
101
301
115
213
114
102
203
202
323
93% = adenomas (Weiss≤3)
101
112
117
75% = carcinomas (Weiss≥4)
301
215
102
216
324 312
210
115
116
208
213
206
322
212
304
109
305
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302
205
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106
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321
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306
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315
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201
113
314
107
310
114
313
CYP21A2
INHA
CYP17
GPC3
S100B
TGFBR3
HSD 3B1
NME1
STAR
CYP11A
CYP11B1
PPM1A
RB1
CREM
KCN10T1
NST 1R
TGFB2
FGER1
TGEBR1
FGFR4
IGF 2
GAPD
Fig. 2. Hierarchical clustering of gene expression in adrenal cortical tumors. The top panel shows division of tumors into two clusters based on gene expression of genes related to /GF2 expression. The bottom panel shows a similar division of tumor based on expression of genes
related to steroidogenesis. Reproduced with permission from ref. 59.
to pathologic diagnosis, separation of ACCs from the other cortical tissues was observed. The one low-grade ACC (desig- nated C13) was intermediate in its classification. When a reduced gene list of 91 differentially expressed genes was used, C13 clearly segregated with the other ACCs. This was observed when both prin-
cipal component analysis (PCA) and hier- archical clustering was performed (Fig. 1). Consistent with the IGF2 genotyping work described above, IGF2 expression was greatly increased in the ACCs compared to the other tissues, along with many other genes related to increased proliferation. While limited to a small cohort of tumors,
this study revealed distinct gene expression profiles of ACAs and ACCs and derived a short yet robust list of differentially expressed genes.
A second microarray paper used a larger set of tumors but a much smaller set of 230 genes [59]. The real power of this study comes not from the depth of its array but from their ability to correlate gene expres- sion and patient outcome. Combining these variables, a 22-gene set was developed and shown to possess predictive diagnos- tic power (Fig. 2). In addition, a 14-gene set was shown to correlate with outcome. These gene expression signatures are excit- ing and await further validation.
Collectively, these DNA microarray studies demonstrated clear differences in gene expression between benign and malignant ACTs and strikingly illustrate the power of molecular profiling approaches for tumor classification and gene discovery.
Future Directions
Many vitally important questions remain unanswered. For instance, just as other endocrine tumors have biologically and molecularly distinct subgroups (e.g., papillary thyroid carcinoma), can ACC be classified into clinically meaning- ful groups? Stated more plainly: Is adrenal cancer one disease or several morphologi- cally related diseases? Furthermore, can molecular profiling studies identify addi- tional therapeutic targets? The existing studies suggest that increased IGF2 gene expression is the dominant cause of ACC and thus a valid therapeutic target. Is IGF2 the whole story or are other factors, yet undiscovered, of equal importance? Despite the rare nature of adrenal cancer, many groups are actively trying to address these questions.
It is quite difficult to predict the spe- cific path this field will take in the coming years, especially given the rapid evolution of high-throughput genomic and pro- teomic technologies to comprehensively examine various aspects of tumor cell biology. However, it is unmistakably clear that the disciplines of oncology and pathol- ogy are poised to undergo a transforma- tion in which more molecularly targeted therapies become available and more intelligent therapeutic choices are made, largely driven by molecular profiling-based assessments of individual patient’s tumors. It will be exciting to witness and partici- pate in this transformation as it is applied to the diagnosis, prognosis, and treatment of adrenal cortical carcinoma.
Acknowledgments
This work was originally presented at the Endocrine Pathology Society Compan- ion Meeting at the 2006 Annual Meeting of the United States Academy of Patholo- gists (USCAP). The author thanks the organizers for the opportunity to present and Donita Sanders for editorial assistance.
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