REVIEWS
Adrenocortical carcinoma - towards genomics guided clinical care
Joakim Crona1 * and Felix Beuschlein2,3*
Abstract | Adrenocortical carcinoma (ACC) is an aggressive and rare neoplasm that originates in the cortex of the adrenal gland. The disease is associated with heterogeneous but mostly poor outcomes and lacks effective pharmaceutical treatment options. Multi-omics studies have defined the landscape of molecular alterations in ACC. Specific molecular signatures can be detected in body fluids, potentially enabling improved diagnostic applications for patients with adrenal tumours. Importantly, pan-molecular data sets further reveal a spectrum within ACC, with three major subgroups that have different disease outcomes. These new subgroups have value as prognostic biomarkers. Research has revealed that the p53-RB and the WNT-ß-catenin pathways are common disease drivers in ACC. However, these pathways remain difficult to target by therapeutic interventions. Instead, a unique characteristic of ACC is steroidogenic differentiation, which has emerged as a potential treatment target, with several agents undergoing preclinical or clinical investigations. Finally, a large proportion of ACC tumours have genetic profiles that are associated with promising therapeutic responsiveness in other cancers. All these opportunities now await translation from the laboratory into the clinical setting, thereby offering a real potential of improved survival outcomes and increased quality of life for patients with this serious condition.
Adrenocortical carcinoma (ACC) is a rare malignancy that originates in the cortex (the outer layer) of the adre- nal gland. Diagnostic approaches and available treatment options have remained unchanged for this entity since the introduction of surgery (1914) and mitotane plus platinum-based therapy (1998). Surgery is currently the only available curative treatment option, and the disease can often be associated with severe morbidity owing to endocrine disturbances and local or metastatic tumour growth (BOX 1). Advances in the understanding of ACC pathophysiology, together with the formation of interna- tional ACC research networks, have sparked optimism for future improvements in patient care (FIG. 1).
‘Department of Medical Sciences, Uppsala Universitet, Uppsala, Sweden.
2Medizinische Klinik und Poliklinik IV, Klinikum der Universität München, Munich, Germany.
3 Klinik für Endokrinologie, Diabetologie und Klinische Ernährung, UniversitätsSpital Zurich, Zurich, Switzerland.
*e-mail: Joakim.crona@ medsci.uu.se; Felix. Beuschlein @usz.ch
https://doi.org/10.1038/ s41574-019-0221-7
In this Review, we discuss the current state of the art on ACC pathophysiology and patient care. Molecular information is summarized from three relevant perspec- tives: first, within the ACC entity with a focus on relevant subgroups; second, in a comparative approach between ACC and adrenocortical adenomas; and third, in a pan- cancer context (FIG. 2). The third perspective is based on novel data from The Cancer Genome Atlas (TCGA) data- base, which includes clinical and molecular data from >10,000 tumours of 33 different disease types. Finally, we explore how the TCGA database and other data sets can be used to develop novel diagnostic, prognostic and therapeutic tools.
Disease overview
Epidemiology and outcomes. ACC is an ultra-rare malignancy that accounts for only a minor fraction of primary adrenal neoplasms. Specifically, data from the United States and the Netherlands show that the inci- dence of ACC is ~1 case per 1 million person-years in the general population and 0.21 cases per 1 million person-years in children and young adults1,2. By contrast, in the United States, the age-standardized general can- cer incidence is ~4,500 cases per 1 million person-years in adults and ~150 cases per 1 million person-years in children3. The incidence of ACC follows a bimodal age distribution, with a peak in childhood and a plateau occurring between 40 and 60 years of age. The median overall survival is ~3-4 years and the overall 5-year sur- vival for paediatric patients is <60%1,2. Furthermore, the 5-year survival is ~60-80% for ACC localized to the adrenal cortex, 35-50% for ACC with locally advanced disease and 0-28% for patients with distant metastases, highlighting the prognostic relevance of tumour staging4.
From a pan-cancer perspective, the outcome of ACC ranks intermediate with respect to overall survival. However, the relative difference between survival in localized versus advanced disease stages seems to be larger in ACC than in most other cancers5,6. When com- paring outcomes within the TCGA cohort, we identified
Key points
· Adrenocortical carcinoma (ACC) is an ultra-rare disease that is associated with poor outcomes; surgery, mitotane-based and platinum-based chemotherapy remain the only effective therapeutic strategies.
· Ongoing clinical trials include two phase III trials (ADIUVO and ADIUVO-2) as well as multiple phase Il studies.
. Two large consortia have characterized the landscape of molecular alterations in ACC, which included high chromosomal aneuploidy, and the most common driver genes are TP53 and CTNNB1.
· Three molecular subtypes of ACC have been defined that correlate with prognosis; related surrogate biomarkers that are adopted for clinical use have been described.
· Up to 50% of metastatic ACCs might harbour genetic aberrations associated with treatment efficacy in other diseases; evaluating a precision oncology approach based on these features will require implementation of new clinical trial designs.
RO resection
Absence of cancer cells at the resection margin by microscopic analysis.
Neoadjuvant treatment
Ancillary therapy administered before main therapy.
Adjuvant therapy Ancillary therapy administered after main therapy.
that the overall survival in advanced ACC was similar to that of advanced bladder carcinoma or advanced squamous cell lung cancer, which are both considered to have a poor prognosis. For localized ACC, overall sur- vival seemed to be closer to diseases with high cure rates, such as localized renal clear cell carcinoma or localized rectal carcinoma. Discouragingly, epidemiological data suggest that no substantial improvement in the survival of patients with ACC was achieved between the years 1993-1998 and 2005-2010 (REF.2).
Current diagnosis and clinical investigation. The 2017 WHO classification on tumours of the adrenal cortex recognizes ACC as a malignant epithelial tumour of adrenocortical cells7,8. Histopathology is the primary determinant of malignancy and is based on the Weiss scoring system, established in 1984 (REF.9).
Early diagnosis of ACC remains a challenge owing to the rarity of this disorder, together with the lack of distinct and specific alarm symptoms. Instead, patients often present with nonspecific complaints that are related to tumour mass effect or endocrine disturbances10. As such, clinical investigation and endocrine laboratory
Box 1 | Overview of ACC
· Epidemiology: the annual incidence of adult adrenocortical carcinoma (ACC) in the United States and the Netherlands is 0.7-2.0 cases per million individuals, with a peak in incidence between 40 and 60 years of age2.
· Diagnosis: the WHO recognizes ACC as a malignant epithelial tumour of adrenocortical origin. Malignancy is primarily determined by histopathological criteria (the Weiss scoring system)8.
· Staging: the widely adopted staging system designed by the European Network for the Study of Adrenal Tumours (ENS@T) uses information obtained from anatomical imaging and histopathological examinations4.
· Prognosis: tumour stage, resection status, Ki-67 index (or mitotic count), autonomous cortisol secretion and the patient’s general condition are validated prognostic factors14.
· Management: surgical resection should always be attempted. Systemic therapy with mitotane and/or platinum-combination chemotherapy is recommended in nonresectable ACC10.
. Recommendations for ACC clinical management are available from the European Society of Endocrinology and ENS@T (2018) and the European Society for Medical Oncology (2012)10,111.
· Ongoing phase III clinical trials: ADIUVO22 and ADIUVO-2 (REF.108) for adjuvant treatment. Currently, there are no active phase III studies on the treatment of advanced ACC.
assessment are recommended to document steroid hormone excess, which occurs in 50-60% of patients with ACC11. Clinically, hypercortisolism (Cushing syn- drome; observed in 50-60% of patients) and/or hyper- androgenism (female virilization; observed in 20-30% of female patients) are commonly found in patients with ACC, with a small fraction of patients having oestro- gen and/or mineralocorticoid excess10,12. In addition, 30-40% of patients experience space-occupying effects of the tumour mass12; however, systemic symptoms, including weight loss, fatigue, night sweats or fever are less commonly observed.
The WHO recommends using the European Network for the Study of Adrenal Tumours (ENS@T) staging sys- tem, which is based on the size and extent of ACC4. The second most important prognostic factor is the prolifer- ation rate of tumour cells, which can be assessed through mitotic counts or the Ki-67 index13-15. Additional clinico- pathological parameters with prognostic value include tumour grade, resection status, age and cancer-related or hormone-related symptoms16.
Current treatments. Complete surgical removal of the tumour remains the only curative treatment option for patients with ACC. However, even after RO resection the cumulative recurrence rate is high (~30-75%17).
Mitotane is the only drug formally approved (by the European Medicines Agency and the FDA) for the treat- ment of patients with advanced and inoperable ACC18. This agent is an adrenolytic dichlorodiphenyltrichloroethane (DDT) derivative with an incompletely understood mode of action. Neoadjuvant treatment with mitotane or other compounds is not yet part of the ACC treatment algorithm. By contrast, adjuvant therapy with mitotane is recommended by most experts regardless of ACC risk profile19. This recommendation, however, is based on retrospective data that showed long-term recurrence- free survival upon mitotane treatment in patients with radically resected ACC20,21. A risk-stratification approach is currently being evaluated in a randomized phase III trial to assess whether adjuvant mitotane is superior to observation alone in low-risk ACC (ADIUVO; Efficacy of Adjuvant Mitotane Treatment)22. In this Review, low-risk ACC is defined as stage I-III disease with a Ki-67 index <10% and RO resection.
In the palliative setting, monotherapy with mitotane can also be considered in patients with low tumour bur- den and/or slow tumour growth kinetics23. Otherwise, platinum-based chemotherapy, in combination with mitotane, is recommended as first-line treatment in the palliative setting. This recommendation is based on data from the FIRM-ACT (First International Randomized Trial in Locally Advanced and Metastatic ACC Treatment) trial that demonstrated superior effi- cacy in the etoposide, doxorubicin and cisplatin plus mitotane (EDP-M) arm (35 of 151 patients showing a radiological response, 23.2% response rate) compared with the streptozotocin plus mitotane (14 responders out of 153 patients, 9.2% response rate) arm24. In this trial, 15-20% of patients in the EDP-M arm and 5-10% in the streptozotocin plus mitotane arm remained alive after 5 years.
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ENS@T staging system
A5
Weiss score
ENS@T
Ki-67
TCGA
1984
2002
FIRM-ACT
2019
ADIUVO
GALACCTIC
JAVELIN
ADIUVO-2
Limited evidence exists supporting the efficacy of other anticancer agents in a second-line setting. Studied agents include streptozotocin (unknown response rate)24, insulin-like growth factor 1 receptor (IGF1R)-mTOR pathway inhibitors (7 responders out of 181 patients, 3.9% response rate)25, tyrosine kinase inhibitors (1 responder out of 72 patients, 1.4% response rate)25, anti-PD-L1 antibody (immune checkpoint inhibi- tor; 3 responders out of 50 patients, 6% response rate)26 and gemcitabine-based chemotherapy (7 responders out of 145 patients, 4.9% response rate)27.
The GALACCTIC (A Study of OSI-906 in Patients with Locally Advanced or Metastatic Adrenocortical Carcinoma) trial was a phase II study of linsitinib (an inhibitor of IGF1R and insulin receptors) versus pla- cebo for advanced ACC that had been treated with at least one but fewer than three previous drug regimens28. This trial failed to show improved survival of the exper- imental arm in comparison with placebo28. However, the placebo arm of this trial provided invaluable data on the morbidity and mortality in patients with advanced ACC that remained under surveillance only: among 49 patients who received placebo, the frequency of pro- gressive disease was 61% at 50 days, 90% at 100 days and 100% at 150 days28. In addition, 44% of patients in the placebo arm experienced an adverse event.
The JAVELIN (Avelumab in Metastatic or Locally Advanced Solid Tumours) trial was a phase Ib, single- arm study of avelumab (an anti-PD-L1 antibody) in 1,758 patients with different types of advanced solid tumour. A subgroup analysis reported data on 50 patients with advanced ACC treated with an anti-PD-L1 anti- body who had previously been treated with platinum- based chemotherapy26. The median time from disease progression to study baseline was 0.9 months (range 0.3-8.6 months). In addition 50% of these patients received concomitant treatment with mitotane. A par- tial response was observed in three patients (6%, 95% CI 1.3-16.5%), two of whom had received concom- itant mitotane. Median progression-free survival in
the 50 patients with advanced ACC tumours was 2.6 months. Only 8.7% (95% CI 2.6-19.6%) of the 50 patients remained free of disease progression at 12 months26. Notably, ACC tumour expression of PD-L1 did not correlate with treatment efficacy. However, data on important ACC pathological signatures (see subse- quent section), such as mismatch repair status or corti- sol secretion, were not reported. A subgroup of patients with ACC might still be considered for treatment with an alternative immune checkpoint inhibitor (an anti-PD-1 antibody) on the basis of the FDA approval of pem- brolizumab for solid tumours with high microsatellite instability or mismatch-deficient solid tumours29.
On the basis of this evidence from the recent liter- ature, many unresolved problems remain that should be addressed to decrease ACC-related morbidity and mortality. These issues include disease prevention, earlier detection, improved risk stratification, control- ling tumour growth and invasiveness and suppressing hormone production and secretion.
Pathophysiology
ACC arises from cells within the adrenal cortex, but on a group level, the tumour retains a variable degree of adrenocortical differentiation. This characteristic results in a pathological steroidogenic signature (that is, the presence of specific steroid pattern not found in other conditions) that differs from that of more differ- entiated adrenocortical adenomas30-32. In addition, ACC can be separated from benign adrenocortical neoplasms on the basis of genomic, epigenomic and/or transcrip- tomic landscapes (the genetics and genomics of adreno- cortical tumours are reviewed in REF.33,34). The drivers of the differences between ACC and other types of adrenocortical tumour are unclear and cannot currently be attributed to a separate cell of origin and/or specific pathological mechanisms.
Two consortia have now performed comprehensive pan-molecular characterizations of a large number of ACC tumours: ENS@T (n = 45)35 and TCGA (n = 91)30. These two projects provide information on ACC biol- ogy with an unprecedented level of detail. However, the TCGA and ENS@T data sets were generated from selected populations of patients and are therefore not without limitations. Compared with patients with ACC in the Surveillance, Epidemiology, and End Results Program (SEER) database, the ENS@T and TCGA ACC cohorts included younger patients (mean age: ENS@T 46.9 years and TCGA 47.2 years versus SEER 52.5 years) and a lower percentage of advanced stage IV disease (ENS@T 31.8% and TCGA 20% versus SEER 50.9%)5,30,35. In addition, the ENS@T and TCGA data were generated exclusively from primary tumour specimens obtained from adult patients. As such, paediatric ACC as well as aggressive forms (including metastatic disease) of adult ACC are therefore less well characterized and represent areas for future exploration.
Pan-molecular studies (mRNA, DNA methylation, microRNA (miRNA) and protein) have clearly demon- strated that ACC can be separated into different sub- groups with distinct biological signatures and different clinical outcomes. For example, a study from the ENS@T
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ACC and its subgroups relative to other cancers
| Signature | pan-ACC | ACC-CoCI | ACC-CoC II | ACC-CoC III |
|---|---|---|---|---|
| Chromosomal aneuploidy | 34 | 35 | 32 | 31 |
| TGCT, UCS | LUAD, LUSC | |||
| Whole-genome doubling | 26 | 24 | 21 | 29 |
| SARC, STAD | BRCĄ, SKCM | LUAD, ESCA | ||
| Proportion germline mutations | 30 | 30 | 30 | 30 |
| LAML, HNSC | ||||
| Somatic mutation burden | 10 | 7 | 12 | 12 |
| MESO | TGCT, THYM | SARC, PAAD | ||
| Number of somatic driver genes | 6 | 1 | 6 | 6 |
| THCA, PPGL | KICH | THCA, PPGL | ||
| Steroid differentiation score | 35 | 33 | 34 | 35 |
| Unique to ACC | ||||
| Proliferation signature (MKI67) | 9 | 7 | 12 | 12 |
| KIRC, UVM | PRAD, KIRC | GBM, CHOL | ||
| Immune signature - lymphocyte depleted | 34 | 33 | 34 | 34 |
| GBM, UVM, LIHC | ||||
| Immune signature - inflammatory | 20 | 27 | 17 | 17 |
| SARC | LUAD, CHOL | BRCĄ, SKCM | ||
Relative difference between ACC: CoC I and CoC II-CoC III
Relative difference between ACC and adrenal adenoma
☒
☒
☒
☒
☒
☒
☒
☒
☒
☒
☒
☒
☒
☒
☒
Unknown
☒
Unknown
Relative to other cancers
Higher in CoCI
Higher in CoC II- CoC III
Higher in ACC
Higher in adrenal adenoma
35 Highest ranking
1
Lowest ranking
Fig. 2 | Biology of ACC from different perspectives. Left: pathological signatures of adrenocortical carcinoma (ACC) and its molecular subgroups observed from a pan-cancer perspective based on estimations as well as raw data. For each pathological signature, the pan-cancer ranking of ACC as well as molecular subgroups Cluster of Cluster (CoC) I-III are provided and examples of cancers with a similar profile are shown. Middle: the table shows the estimated relative differences for specific pathological signatures within the molecular subgroups of ACC (CoC I versus CoC II-III). Right: table shows the estimated differences in specific pathological signatures between ACC and adrenal adenomas. BRCA, breast-invasive carcinoma; CHOL, cholangiocarcinoma; ESCA, oesophageal carcinoma; GBM, glioblastoma multiforme; HNSC, head and neck squamous cell carcinoma; KICH, kidney chromophobe; KIRC, kidney renal clear cell carcinoma; LAML, acute myeloid leukaemia; LIHC, liver hepatocellular carcinoma; LUAD, lung adenocarcinoma; LUSC, lung squamous cell carcinoma; MESO, mesothelioma; PAAD, pancreatic adenocarcinoma; PPGL, pheochromocytoma and/or paraganglioma; PRAD, prostate adenocarcinoma; SARC, sarcoma; SF1, steroidogenic factor 1; SKCM, skin cutaneous melanoma; SOAT1, sterol-O-acyltransferase 1; STAD, stomach adenocarcinoma; TGCT, testicular germ cell tumours; THCA, thyroid carcinoma; THYM, thymoma; UCS, uterine carcinosarcoma; UVM, uveal melanoma.
network identified two main subgroups of ACC, C1A and C1B, whereas the more comprehensive TCGA data set allowed discrimination of three subgroups, Cluster of Cluster (CoC) I, II and III30 (TABLE 1). When these molecular signatures were compared with those of other diseases, ACCs could be clearly separated from adreno- cortical adenomas, and when compared with 10,000 tumours in the TCGA database, all ACC clustered into a distinct homogeneous group that was separated from other cancer forms36,37.
Genetic risk factors for ACC. ACC can occur either in the context of a genetic syndrome or as sporadic dis- ease38 (TABLE 2). Cases in children are frequently asso- ciated with the Li-Fraumeni syndrome, and germline TP53 mutations could be detected in 50% of 88 children
with ACC39,40. Moreover, ~10% of patients in the TCGA cohort of adult ACC had a pathogenetic or probable pathogenetic TP53 variant30. We estimate that these frequencies place ACC among the top ten of the most heritable neoplasms41 (FIG. 2). In adult patients with ACC, 4-6% harbour a germline mutation in TP53 (REFS42,43) and ~3% have a germline mutation in genes associ- ated with Lynch syndrome44 (TABLE 2). Some paediatric ACCs are also associated with Beckwith-Wiedemann syndrome (mutation or deletion of imprinted genes at chromosome 11p15.5)45. Although ACC occurs in ~1% of patients with multiple endocrine neoplasia type 1 REF.46,47, the exact frequency of germline MEN1 muta- tions in any ACC cohort is unknown but is probably very low (TABLE 2). In addition, adrenocortical tumours have also been identified in some patients with familial
| Subgroup | Chromosomal aneuploidy | Driver genes (ACC prevalence >10%) | Methylation CIMP | mRNA profile | Clinical outcomes |
|---|---|---|---|---|---|
| ENS@T (n=45) | |||||
| C1A | NA | CTNNB1, TP53 and ZNRF3 | Intermediate-high | C1A | Intermediate-inferior |
| C1B | NA | None reported | Low | C1B | Superior |
| TCGA (n = 91) | |||||
| CoCI | Chromosomal pattern | ZNRF3, MEN1 and MMR-related genes | Low | Majority steroid phenotype low pattern | Superior |
| CoC II | Majority chromosomal pattern | CDKN2A, CTNNB1,NF1, PRKAR1A, TP53 and ZNRF3 | Intermediate | Majority steroid phenotype high pattern ± proliferation pattern | Intermediate |
| CoC III | Majority noisy pattern | CDK4, CDKN2A, CTNNB1, MLL4, RB1, TERT, TP53 and ZNRF3 | High | Steroid phenotype high pattern ± proliferation pattern | Inferior |
ACC, adrenocortical carcinoma; CIMP, CpG island methylator phenotype; CoC, Cluster of Cluster; ENS@T, European Network for the Study of Adrenal Tumours; MMR, mismatch repair; NA, not available; TCGA, The Cancer Genome Atlas.
adenomatous polyposis 1 as well as MutY homologue (MUTYH)-associated polyposis48,49. Finally, there are individual case reports of ACC occurring in patients with Carney complex50.
Acquired genetic disturbances in ACC. High chro- mosomal aneuploidy is a hallmark of ACC that clearly separates it from adrenocortical adenomas51,52. Three subgroups were identified among ACCs in the TCGA cohort: ‘chromosomal’ (54 of 89 cases, 61%), with gains or deletions of chromosomes or chromosomal arms; ‘noisy’ (27 of 89 cases, 30%), with a high number of chro- mosomal breaks; and ‘quiet’ (8 of 89 cases, 9%), with few somatic copy number alterations30 (TABLE 1). From a pan- cancer perspective, we estimate that ACC ranks among the top five cancers with the highest levels of chromo- somal aneuploidy53 (FIG. 2). Of note, whole-genome doubling is also frequently observed and occurred in a majority (48 of 89 cases, 54%) of ACC cases. We esti- mate that this proportion ranks ACC in the top ten can- cers having the highest proportion of whole-genome doubling from the pan-cancer perspective53 (FIG. 2).
The TCGA and ENS@T ACC cohorts identified recurrent high-level amplifications of TERT (5p15.33) and CDK4 (12q14) as well as homozygous deletions of CDKN2A (9p21.3), RB1 (13q14), ZNRF3 (22q12.1) and long non-coding RNA LINC00290 (4q34.3)30,35. In addition, amplifications of TERF2 (16q22.1) and CCNE1 (19q12) as well as homozygous deletions of 3q13.1 have been reported. Preserving telomere length is an impor- tant mechanism for cell immortalization and different mutually exclusive mechanisms have been observed in ACC: increased TERT (encoding telomerase reverse transcriptase) expression (through promoter mutations or copy number gains) as well as alternative lengthen- ing of telomeres (through loss-of-function mutations in ATRX or DAXX)30,35,54-57.
Overall, ACC has relatively few single-nucleotide mutations (0.6-0.9 per megabase), thereby ranking it in the bottom ten on the pan-cancer background58,59
(FIG. 2). Although >30% of ACC within the TCGA data- base have somatic variances of the DNA mismatch repair system59, only a few cases displayed a very high rate of somatic mutations30,35,55, and a total of 4% were classi- fied as microsatellite instability-high58. Notably, three genes were reported to have recurrent somatic muta- tions in both the TCGA and ENS@T cohorts: CTNNB1, MEN1 and TP53 (REFS30,35) (TABLES 1,3). Additional genes with lower frequencies of somatic mutations include APC, ATM, ATRX, BRAF, BRCA1, BRCA2, CDK4, DAXX, GNAS, KMT2B, MED12, NF1, NF2, NOTCH1, RB1, RPL22, PRKAR1A, SETD2, TSC1, TSC2, TERT (promoter) and ZNRF3 (REFS30,35,55,60-65) (TABLE 3). Of note, a spectrum exists regarding the level of evidence that supports the pathogenetic effect of these alleles.
Compared with localized ACC, fewer genetic data are available on advanced forms of this disease. The most relevant data were presented in a study that inves- tigated the genetic landscape of 33 ACC metastases66. Importantly, this study revealed that ACC metastases have a 2.8 times higher somatic mutation rate com- pared with primary tumours and confirmed the pres- ence of genetic heterogeneity at relevant disease driver genes in both recurrent and metastatic ACC66. Of note, paediatric ACC is also less well characterized. However, one study performed genome or exome sequencing of 37 ACC tumours from children67. Of these, 25 had germline TP53 mutations, 2 cases were associated with Beckwith-Wiedemann syndrome and 10 were found to be sporadic. Moreover, in paediatric ACC, chromosomes 11p and 17 showed copy-neutral loss of heterozygosity early during tumorigenesis. This event was followed by mutations in ATRX (n = 6) and CTNNB1 (n = 3) as well as integration of human herpesvirus 6 (REF.67).
Methylome, transcriptome and microRNA. One of the methods that can discriminate the different sub- groups of ACC (TABLE 1) is based on the analysis of mRNA expression. In the ENS@T study, gene expres- sion profiles separated ACC into two subgroups: C1A
| Genetic alteration | Syndrome | Frequency paediatricª | Frequency adultª | Syndrome manifestations | Refs |
|---|---|---|---|---|---|
| TP53 | Li-Fraumeni syndrome | 50% | 4-6% | Soft tissue sarcomas and osteosarcomas, breast cancer, brain tumours and leukaemia | 39,40,43 |
| Mutation or deletion of imprinted genes at 11p15.5 | Beckwith-Wiedemann | NA | NA | Wide spectrum of phenotypic features including exomphalos, macroglossia and gigantism | Reviewed in REF. 45 |
| MLH1, MSH2, MSH6 and PMS2 | Lynch syndrome | NA | 3% | Endometrial, ovary, stomach, small intestine, hepatobiliary tract, upper urinary tract, brain and skin cancers | 44 |
| MEN1 | Multiple endocrine neoplasia type 1 | NA | Low | Parathyroid adenoma, pituitary tumour and pancreatic neuroendocrine tumour | 46,47 |
ACC, adrenocortical carcinoma; NA, not available. ªRefers to the proportion of ACC cases in this population that can be attributed to the syndrome.
with aggressive disease and C1B representing slower growing tumours35. TCGA further refined this classifi- cation by stratifying ACC into four groups on the basis of differences in adrenocortical differentiation and cell proliferation30. Genome-wide gene expression profiles can also discriminate ACC from adrenal adenomas68,69, with thousands of genes deregulated in ACC. Many of these genes are related to malignant transformation, for example, genes involved in DNA maintenance, cell-cycle regulation, apoptosis and inflammation34. Key deregu- lated and overexpressed transcripts in ACC include IGF2 and SF1. The latter has a key role in both adrenocortical development and tumorigenesis70.
Good evidence now exists in the literature suggesting that the most robust biomarker to identify ACC pan- molecular subgroups could be targeted DNA methyl- ation analysis. Using high-throughput methods, ACCs can be separated into at least three different subgroups on the basis of different CpG island methylator pheno- type (CIMP) status: CIMP-high, CIMP-low and non- CIMP35,71. Similar findings were reported in the TCGA study, which also categorized ACC into three groups: CIMP-high, CIMP-intermediate and CIMP-low30. This classification based on DNA methylation showed a sat- isfactory overlap with the pan-molecular subgroups (TABLE 1). DNA methylation at selected loci has now been confirmed to provide clinically meaningful information on prognosis by two independent studies72,73.
Molecular hallmarks of ACC. Pan-molecular data sets of ACC biology show that ACCs are characterized by a few key molecular hallmarks (FIG. 3): deregulated cell-cycle and apoptosis pathways (p53 and RB); impaired chro- matin and DNA maintenance (mismatch and double- stranded DNA repair as well as TERT overexpression or alternative lengthening of telomeres); altered adren- ocortical differentiation; and signalling pathway acti- vation (most commonly WNT-ß-catenin signalling74 but also cAMP and the mitogen-activated protein
kinase pathways30,35). These hallmarks are unequally dis- tributed among the different pan-molecular subgroups of ACC30,35: the slow-growing group of ACC (ENS@T C1B or TCGA CoC I; FIG. 2; TABLE 1) has substantially fewer driver events. Although ACCs show heterogene- ous molecular profiles, from a pan-cancer perspective, ACC remained a homogeneous category with a unique biology, including steroid differentiation36,37 (FIG. 2).
From bench to bedside
ACC is an aggressive cancer with typically poor out- comes, which necessitates the translation of preclinical research into more effective management strategies. Important research targets include more accurate pre- operative diagnosis, earlier detection of recurrences, improved disease monitoring and the identification of new treatment targets and therapies. The detection and quantification of disease-specific molecules in body fluids has thus far been the most active research direction.
Diagnostic biomarkers. A need exists for non-invasive methods to detect ACC early in the course of the disease. Preliminary data suggest that circulating tumour DNA can be detected in the serum of a subset of patients with ACC, predominantly those with metastatic disease75,76. The detection and characterization of circulating tumour cells might represent a more promising, yet technically challenging, biomarker. For example, a single study con- firmed that circulating tumour cells could be detected in all (n = 14) investigated patients with ACC77. In addition, ACC-specific miRNAs also show promise as biomarkers for improved diagnosis78,79. However, owing to methodo- logical difficulties, the diagnostic accuracy of ACC- specific miRNAs is too low for clinical applications80. A promising alternative could be analysis of miRNAs in circulating extracellular vesicles81,82. Finally, the altered adrenocortical differentiation of ACC leads to a patho- logical steroidogenic profile that can be detected using liquid-chromatography mass spectrometry of serum31,32.
Adrenal adenomas Benign tumour lesions of the adrenal cortex.
| Gene | Mutation frequency in adult ACC (n = 176)30,3 | Mutation frequency in paediatric ACC (n = 32)67 | Mutation frequency in adult ACC metastasesª (n = 6)60 | Mutation frequency in adult ACC metastasesb (n = 264)61-65 | Biomarker-drug evidence levelc (OncoKB)114 |
|---|---|---|---|---|---|
| APC | 4 (2%) | 0 (0%) | 0 (0%) | 21 (9%) | NA |
| ATM | 6 (3%) | 0 (0%) | 2 (33%) | 12 (6%) | IV |
| ATRX | 6 (3%) | 4 (13%) | 0 (0%) | 22 (10%) | NA |
| BRAF | 1 (1%) | 0 (0%) | 0 (0%) | 2 (2%) | I |
| BRCA1 | 0 (0%) | 0 (0%) | 0 (0%) | 3 (2%) | I |
| BRCA2 | 0 (0%) | 1 (3%) | 0 (0%) | 4 (3%) | I |
| CDK4mut | 0 (0%) | 0 (0%) | 0 (0%) | 4 (3%) | NA |
| CDK4amp | 13 (8%) | NA | NA | 7 (10%) | IIA |
| CTNNB1 | 26 (15%) | 1 (3%) | 0 (0%) | 46 (17%) | NA |
| DAXX | 7 (4%) | 1 (3%) | 1 (17%) | 14 (6%) | NA |
| GNAS | 6 (3%) | 0 (0%) | 0 (0%) | 8 (5%) | NA |
| KMT2A | 5 (3%) | 0 (0%) | 0 (0%) | 3 (12%) | NA |
| KMT2B | 3 (2%) | 2 (6%) | 1 (17%) | NA | NA |
| KMT2C | 5 (3%) | 0 (0%) | 0 (0%) | 0 (0%) | NA |
| KMT2D | 6 (3%) | 0 (0%) | 1 (17%) | 2 (8%) | NA |
| MEN1 | 9 (5%) | 0 (0%) | 1 (17%) | 21 (9%) | NA |
| NF1 | 6 (3%) | 0 (0%) | 2 (33%) | 20 (12%) | IV |
| NOTCH1 | 2 (1%) | 0 (0%) | 0 (0%) | 5 (5%) | NA |
| PTCH1 | 3 (2%) | 0 (0%) | 0 (0%) | 10 (4%) | IIIA |
| RB1 | 4 (2%) | 1 (3%) | 0 (0%) | 4 (2%) | NA |
| SETD2 | 3 (2%) | 0 (0%) | 1 (17%) | 3 (2%) | NA |
| TSC1 | 0 (0%) | 0 (0%) | 0 (0%) | 2 (2%) | I |
| TSC2 | 2 (1%) | 0 (0%) | 0 (0%) | 3 (2%) | I |
| TP53 | 29 (16%) | 3 (9%) | 1 (17%) | 64 (24%) | NA |
| ZNRF3 | 8 (5%) | 0 (0%) | 1 (17%) | 18 (11%) | NA |
| Actionable mut (OncoKB) | 17 (10%) | 1 (3%) | 3 (50%) | NA | NA |
ACC, adrenocortical carcinoma; amp, amplification; mut, mutation; NA, not available. ªSix ACC metastases were analysed by exome sequencing. bTwenty-seven ACC metastases were analysed by targeted sequencing. “Evidence level of biomarker-drug associations were acquired from the OncoKB Precision Oncology Knowledge Database114.
Steroids and their metabolites are also excreted in the urine, therefore enabling urinary steroid profiling for the differential diagnosis of adrenal masses83. According to a 2017 meta-analysis, mass spectrometry-based 24 h urine steroid metabolome profiling provides a diagnostic sensitivity and specificity that exceeds the sensitivity and specificity of imaging84.
Prognostic markers. The classification of ACCs into distinct molecular subgroups (FIG. 2; TABLE 1) provides insight into differences in pathogenesis, but these sub- groups might also act as independent prognostic mark- ers. The following biomarkers have been associated with survival: chromosomal aneuploidy pattern (noisy versus quiet (HR = 4.0)); mutation status (TP53 (HR = 4.9) or ZNRF3 (HR = 2.4) mutation positive versus mutation negative); CIMP status (high versus low (HR = 8.9)); and mRNA features (steroid-high plus proliferation (HR = 29.5), steroid-low plus proliferation (HR = 16.9) and steroid-high versus steroid-low without proliferation
(HR = 10.8))30. These biomarkers were validated in a fairly large (n = 107) retrospective cohort63. This study incorporated relevant clinical (tumour stage, age and symptoms due to steroid secretion), histopathologi- cal (Ki-67 index and R-status) and molecular factors (genetic alterations in genes related to WNT-ß-catenin and/or p53-RB pathways as well as DNA promoter methylation) into a combined prognostic system, the COMBI score. This combination of clinicopathological and molecular data was superior to either of the two components independently for the estimation of overall survival as well as disease-free survival in patients with completely resected (RO) disease63.
Several studies have validated the use of targeted molecular analyses to stratify ACC into prognostic subgroups. These assays measure VAV2 (an angiogenic factor) expression85, CIMP or non-CIMP methylation status through analysis of four genes (PAX5, GSTP1, PYCARD and PAX6)72, methylation of GOS2 (an apop- totic factor)73 and quantification of miRNA-483-5p
Vismodegib
NOTCH inh
Sonidegib
Linsitinib
Jagged1
NOTCH1
PTCH1
SMO
IGF1R
ZNRF3
ACC cell
NF1
Menin
ß-Catenin
Durvalumab
Vemurafenib
APC
Avelumab
Nivolumab
PRKAR1A
BRAF
Dabrafenib
Atezolizumab
Pembrolizumab
Cobimetinib
CDKN2A
Trametinib
MEK1
Palbociclib
PD-L1
PD-1
T cell
Ribociclib
CDK4
Everolimus
Milciclib
CTLA4
mTOR
TSC1
MDM2
DS-3032b
TSC2
RG7112
Ipilimumab
RB
Tremelimumab
p53
KMT2A- KMT2D
Mitotane
Menin
Cell cycle
ATR-101
SETD2
ATM
SOAT1
Olaparib
VAV2
Chromatin
Niraparib
BRCA1
Steroidogenic enzymes
DNA
TERT
BRCA2
Talazoparib
SF1
PARP
Rucaparib
Abiraterone
M6620
ATR
DAXX
MMR
MUTYH
POLE
1311-MTO
AZD6738
ATRX
131|-MAZA
Nucleus
(promotes cell proliferation) and miRNA-195 (tumour suppressor; function poorly characterized)79. Of these assays, we believe that targeted DNA methylation anal- ysis could be the most promising surrogate biomarker for ACC pan-molecular subgroups.
The prognostic utility of molecular data for paedi- atric ACC is less clear. Although TP53 mutation status did not show any prognostic relevance, concomitant TP53 and ATRX mutations have been associated with worse prognosis67,86.
Predictive markers for treatment response. Some patients with ACC do not respond to treatment with mitotane; therefore, it is important that robust bio- markers are developed that might predict treatment response. Currently, the only validated predictive factor
for the effect of mitotane is plasma concentration of the compound and its metabolites87,88. A promising potential molecular biomarker is tumour cell expression of sterol- O-acyl-transferase 1 (SOAT1), a protein that normally functions in lipoprotein assembly and dietary cholesterol absorption, which correlated positively with response to mitotane treatment89. Interestingly, this study also sug- gested that SOAT1 might be the most relevant target for the adrenolytic effect of mitotane, which opens up ave- nues for the development of specific compounds with manageable pharmacokinetic properties89.
Biomarkers with predictive capability for the effect of chemotherapy have also been difficult to identify. Negative staining for ERCC1 was initially recognized to correlate with shorter survival after platinum-based chemotherapy in ACC and other diseases90. However,
as in other cancer types, validating studies provided contradictory results91,92. Of note, tumour expression of topoisomerase IIa and thymidylate synthase showed a correlation with the efficacy of EDP-M, but this remains to be validated93. Understanding the molecular rationale for treatment efficacy in those rare responders to targeted therapies is a priority but, to our knowledge, no data on this topic have yet surfaced in the literature.
Therapeutic targets. The discovery of novel therapeu- tics for ACC is among the major research goals for this disease. In theory, the unique biology of adrenocortical cells should open new vulnerabilities to targeted ther- apies that leave other cells unharmed. A key regulator for adrenocortical cells that could be suitable for such a targeted approach is the transcriptional activator steroidogenic factor 1 (SF1) and its downstream tar- gets. Promisingly, the inhibition of downstream factor VAV2, a guanine nucleotide exchange factor for small
GTPases, has shown efficacy in preclinical models94. A second drug target, which is related to steroidogenesis, is 17a-hydroxylase. Abiraterone acetate (a 17a-hydroxylase inhibitor) is approved for the treatment of prostate can- cer and has shown anti-secretory effects, with reduced secretion of cortisol and androgens, as well as a decrease in ACC viability in preclinical models95.
Another potential way to target the steroidogenic profile that is a hallmark of ACC is radionuclide therapy. For example, 131I-metomidate, which is a potent ligand of CYP11B1 and CYP11B2 (which are key enzymes in steroidogenesis), has been studied as a novel treatment strategy in 11 patients with ACC. All patients had met- astatic disease, and 8 of these patients had failed pre- vious treatment lines. Radiological evaluation revealed that one patient had a partial treatment response and five had stable disease96. As this compound had subop- timal pharmacokinetic properties, other radioligands are currently under development.
Box 2 | Examples of genetic biomarker-driven studies for targeted treatment
Amplification of CDK4 (CDK4/CDK6 inhibitors)
· CDK4 amplification has a prevalence in adrenocortical carcinoma (ACC) of ~19% (TABLE 3).
. Two studies demonstrated high expression of CDK4 in ACC primary cultures as well as NCI-H295R cells112,113.
· Both studies demonstrated efficacy of palbociclib (CDK4/CDK6 inhibitor approved for breast cancer114) in preclinical models112,113.
Loss-of-function in ATRX or DAXX (ATR inhibitors or agents inducing DNA double-strand breaks)
· Prevalence in ACC of ~15% (TABLE 3).
· Preclinical data from other diseases have demonstrated that tumours that acquired an alternative lengthening of telomeres phenotype owing to ATRX or DAXX deficiency are sensitive to serine/threonine-protein kinase ATR inhibitors as well as agents that induce double-strand DNA breaks115,116.
. Two different ATR inhibitors, M6620 and AZD6738, are undergoing early clinical studies, and phase I data suggest that M6620 plus topotecan is a tolerable treatment combination117.
Loss-of-function mutations in NF1 or MAP2K1 (MEK inhibitors)
· This genotype has a reported ACC prevalence of ~12% (TABLE 3).
. The activity of MEK inhibitors has been demonstrated in small studies or case reports of various NF1-driven or MEK-driven tumours, including plexiform neurofibromas, melanoma and glioma114,118.
Loss-of-function mutations in ATM, BRCA1 or BRCA2 (PARP inhibitors)
· This genotype has an ACC prevalence of ~4% (TABLE 3).
· Treatment with olaparib or niraparib is approved for BRCA1/BRCA2 mutated ovarian carcinoma119.
· Efficacy has been observed in other cancers with deficiency of the homologous DNA repair system114,120,121.
Microsatellite instability or hypermutator phenotype (anti-PD-1 or anti-PD-L1 antibodies)
· This genotype has a prevalence in ACC of ~4% (TABLE 3).
· Solid tumours classified as hypermutated or microsatellite instability-high have shown high response rates to treatment with anti-PD-1 antibody in small prospective trials29,114.
. The FDA has granted accelerated approval to pembrolizumab for this indication29.
Loss-of-function mutations in PTCH1 (Smoothened inhibitors)
· This genotype has a prevalence of ~2% in ACC (TABLE 3).
· Vismodegib is approved for basal cell carcinoma, and a small number of patients with other PTCH1-mutated tumours have responded to this therapy122.
JAG1 amplification or NOTCH1 loss-of-function mutations (NOTCH inhibitors)
. This phenotype has unknown prevalence in ACC.
. JAG1 is overexpressed in ACC and has been linked to increased cell proliferation123,124. NOTCH inhibition resulted in normalized proliferation124.
. In a phase I trial, four patients with ACC including three with JAG1 amplification and one with NOTCH1 truncation received a NOTCH inhibitor; there was one partial response125.
As previously mentioned, a 2015 study suggested that SOAT1 is the main target for the adrenolytic effect of mitotane89. ATR-101 is a selective SOAT1 inhibitor, which was initially developed as a cholesterol-lowering agent to prevent cardiovascular disease but failed to prove a positive effect for this purpose97. This inhibitor is now undergoing investigation as a potential therapy for ACC98. Proof of concept for the adrenolytic effect of ATR-101 was demonstrated in 2018 through the successful treatment of Cushing syndrome in dogs99.
Improved understanding of the adrenocortical hall- marks of ACC could also be relevant for the develop- ment of a potential new class of anti-ACC agents that are based on manipulation of the immune system. Indeed, tumour cells in ACC are known to express potential antigens, including 21-hydroxylase, the major autoan- tigen in Addison disease100. Discouragingly, a study reported that immunotherapy with the anti-PD-L1 antibody avelumab had low activity in ACC26. However, considering the molecular landscape of ACC, which has one of the lowest signals of infiltrating immune cells in any cancer type included in the TCGA database (FIG. 2), this limited efficacy of avelumab is unsurpris- ing101. Potential explanations for the limited efficacy of avelumab include very high chromosomal aneuploidy (demonstrated to enhance the ability of tumours to evade the immune system in melanoma)102, the excess of immunosuppressive corticosteroids103 and deregu- lated proliferative WNT-ß-catenin and anti-apoptotic p53 signalling pathways104. Several strategies might lead to the development of immunotherapies for ACC. First, patients might be selected with a molecular rationale for treatment response, for example, patients with Lynch syndrome or acquired deficiency in mismatch repair and/or DNA proofreading. Second, techniques could be developed to increase the immunogenicity of ACC, for example, by vaccination105. Third, research should focus on overcoming immune system tolerance, for example, by limiting cortisol secretion or by exploring new treat- ments (such as anti-CTLA4 antibody with an anti-PD-1 or anti-PD-L1 antibody).
Another potential anticancer treatment strategy that remains to be tested in ACC is whether genetic mutations can be used as predictive markers and/or druggable targets. The most common disease-driving
Box 3 | Focus points for future research in adrenocortical carcinoma
. Diagnostic setting: multi-analyte tests of body fluids to detect and quantify an adrenocortical carcinoma (ACC) metabolite and/or microRNA signature.
. Risk stratification for adjuvant therapy: single-analyte or multi-analyte tests of DNA copy number, mutation and/or methylation signatures as well as gene expression data.
· Preclinical research focus: development of drugs targeting the steroidogenic hallmarks of ACC as well as the identification of novel agents that target major ACC hallmarks, including the p53-RB and WNT-ß-catenin pathways.
· Treatment of advanced ACC: to recruit patients into ongoing phase II studies on immunotherapy (such as anti-PD-1 antibodies), tyrosine kinase inhibitors or chemotherapy and to evaluate the potential of a biomarker-driven umbrella trial to investigate drug repositioning based on the genetic profile of ACC.
. Improved infrastructure for clinical studies of an ultra-rare disease: a need exists for more efficient infrastructure to collect biomaterial and to study the association with clinical and therapeutic outcome.
mechanisms of ACC, which include the p53-RB and WNT-ß-catenin signalling pathways, still lack targeted treatment approaches. However, ~10% of ACC tumours included in exome sequencing studies harbour at least one genetic aberration that has been associated with a treatment effect in other cancers (TABLE 3). Indeed, such a pattern of actionable genetic alterations is not specific to ACC. Ongoing studies are investigating whether the concept of genetics-guided therapy can be bene- ficial across different cancer types (for example, NCI- MATCH106 and DRUP107). Although data is currently lacking that determines whether many of these genetic abberations contribute to ACC pathogenesis, our reviewed information60-65 suggests that the proportion of patients with advanced ACC with such markers might be as high as 50% (Table 3). Relevant examples of stud- ies on genetic markers for ACC therapy are described in BOX 2.
Future perspectives
From the reviewed data, we infer that translational and clinical ACC research should be focused on biomarker- driven clinical trials (BOX 3). Adjuvant strategies are currently being investigated in two clinical studies that utilize clinicopathological markers for patient risk stratification: ADIUVO (mitotane versus placebo for patients with low-risk ACC (ENS@T stage I-III, RO resection and Ki-67 index <10%))22, and ADIUVO-2 (Mitotane with or without Cisplatin and Etoposide after Surgery in Treating Participants with Stage I-III Adrenocortical Cancer with High Risk of Recurrence (ENS@T stage I-III, RO, R1 or Rx resection and Ki-67 index >10%))108. These studies are scheduled for comple- tion in 2020 (ADIUVO) and 2025 (ADIUVO-2). As pre- viously mentioned, there is now a rationale to evaluate whether the combined use of clinicopathological and molecular markers could improve the risk stratification of patients with ACC and R0 resection. However, the planning and design of such a clinical trial is advised to start after the results of ADIUVO become available.
Active clinical trials (ClinicalTrials.gov as of 1 April 2019) on systemic treatment for ACC are restricted to phase II studies and include immune checkpoint inhibi- tors (nivolumab, nivolumab and ipilimumab or pembroli- zumab), chemotherapy (cabazitaxel) and tyrosine kinase inhibitor (cabozantinib). In addition, ATR-101 is under investigation for the treatment of Cushing syndrome.
Merging our current understanding on advanced ACC with that of targeted therapy and predictive bio- markers in other cancers, we speculate that up to 50% of advanced ACC cases could have a novel druggable target and/or a predictive marker of treatment effect. On the basis of these data, we propose that there would be a rationale to investigate the repositioning of at least ten different classes of approved anticancer agents to ACC (FIG. 4). Encouragingly, aggregation of previous experiences from genetics-guided therapies in vari- ous cancers revealed ~25% objective response rates109. Nevertheless, a precision oncology approach should not be envisioned as a magic bullet for all ACCs but rather as a possibility to add effective therapies for a proportion of patients.
REVIEWS
ACC
Inclusion criteria
. Stage III or IV
· Nonresectable
· First line
Genetic test
Hedgehog inh
PTCH1
dMMR
Anti-PD-1 mAb
PARP inh
ATM, BRCA1-BRCA2
ALT
ATR inh
CDK4 inh
CDK4
NF1 or MAP2K1
MEK inh
mTOR inh
MTOR or TSC1-TSC2
BRAF
BRAF inh
NOTCH inh
JAG1 or NOTCH1
MDM2
MDM2 inh
No target
EPD-M
Recruiting patients with ACC for multiple biomarker- driven phase II trials, each with only ~1-20% of patients being eligible, would be challenging in the current infrastructure. As such, we argue that alternative clin- ical trial outlines need to be evaluated. We suggest that one such example could be the umbrella clinical trial design (FIG. 4). In this trial format, a distinct disease is selected for study and patients are stratified on the basis of molecular data towards different treatment baskets. This design would allow researchers to study the feasibil- ity and efficacy of the entire concept of genetics-guided therapy rather than only evaluating different agents separately, each with very low numbers of patients. We also speculate that such a clinical trial could be per- formed in a first-line setting (that is, without concom- itant mitotane), which would circumvent concerns on
pharmacokinetic disturbances caused by this drug110. Given the extraordinary clinical and molecular hetero- geneity of ACC, it should be of the upmost importance to perform detailed characterization of patients and tumours that are included in current and future clinical trials. Such information could improve our knowledge of disease biology in advanced and metastatic ACC. It would also allow researchers to study primary and secondary resistance to therapy as well as treatment sensitivity in rare patients who respond to therapy.
Conclusions
Multi-omics studies have defined the landscape of mole- cular alterations in ACC. Through these analyses, we are also able to compare the biology of ACC with that of other adrenal tumours as well as the entire pan-cancer cohort. Specific molecular signatures of ACC can be determined in body fluids, and several ongoing clinical studies are exploring the diagnostic utility of these biomarkers. The available pan-molecular data sets also revealed differ- ent subgroups of ACC, which share distinct molecular characteristics and correlate with different disease out- comes. These new prognostic biomarkers could poten- tially be used to identify patients who would benefit from adjuvant interventions or intensified surveillance.
Improved treatment of advanced disease is the high- est unmet medical need in ACC. Molecular studies provide evidence that ACC is a disease rich in drugga- ble molecular hallmarks. Steroidogenic differentiation represents perhaps the most promising vulnerability for therapy, whereas p53-RB and WNT-ß-catenin signal- ling pathways are still lacking a therapeutic solution. In addition, up to 50% of advanced ACC could harbour any of 20 different genetic biomarkers that have been linked to higher treatment efficacy in other cancers (TABLE 3). This fact offers researchers the chance to inves- tigate biomarker-directed drug repositioning in ACC. Together, these advances provide a unique opportunity to the newly consolidated ACC research community to perform novel clinical trials aiming at improving the outcome of this lethal disease.
Published online: 30 May 2019
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Acknowledgements
J.C. acknowledges the support of Akademiska Sjukhuset, Cancerfonden, Tore Nilsons Stiftelse and Wallenberg Stiftelsen. F.B. acknowledges the support of the Deutsche Forschungsgemeinschaft (DFG) within the CRC/Transregio 205/1 (‘The Adrenal: Central Relay in Health and Disease’).
Author contributions
The authors contributed equally to all aspects of the article.
Competing interests
J.C. received lecture honoraria from Novartis and honoraria for educational material from NET Connect (funded by Ipsen). F.B. has received funding from HRA Pharma and Ipsen.
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Reviewer information
Nature Reviews Endocrinology thanks R. Ribeiro and other, anonymous reviewer(s) for their contribution to the peer review of this work.
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