- Email: [email protected]
Steroid biomarkers and the diagnosis of adrenal cortical carcinoma
Available online at www.sciencedirect.com
ScienceDirect
Current Opinion in
Endocrine and Metabolic Research
Review
Steroid biomarkers and the diagnosis of adrenal cortical carcinoma Irina Bancos1 and Wiebke Arlt2,3 Abstract
Adrenal cortical carcinomas (ACCs) are rare adrenal tumors with a poor prognosis when diagnosed at an advanced stage. Early diagnosis is the key to assure prompt management and improve the prognosis. Surgery is the mainstay of therapy in patients with operable ACC, with R0 resection being the only curative intervention. Diagnosis of ACC is currently based on imaging phenotype and standard-of-care hormonal workup and may present a diagnostic dilemma when imaging characteristics and the hormonal workup are insufficient to make an accurate diagnosis. Noninvasive biomarkers that accurately distinguish ACC from other tumors could aid in making an earlier diagnosis and lead to a better overall prognosis. This review summarizes the current diagnostic approach to ACC including the emerging role of steroid biomarkers in the diagnosis of ACC. Addresses 1 Division of Endocrinology, Diabetes, Metabolism and Nutrition, Mayo Clinic, Rochester, MN, USA 2 Institute of Metabolism and Systems Research, University of Birmingham, Birmingham, UK 3 Centre for Endocrinology, Diabetes and Metabolism, Birmingham Health Partners, Birmingham, UK Corresponding author: Bancos, Irina ([email protected])
Current Opinion in Endocrine and Metabolic Research 2019, 8:167–173 This review comes from a themed issue on Adrenal Cortex Edited by André Lacroix and Enzo Lalli For a complete overview see the Issue and the Editorial Available online 30 August 2019 https://doi.org/10.1016/j.coemr.2019.08.013 2451-9650/© 2019 Elsevier Ltd. All rights reserved.
Keywords ACC, Adrenal mass, Diagnosis, Steroid, Prognosis, Imaging, Biopsy.
Introduction Adrenal cortical carcinomas (ACCs) are rare adrenal tumors with an incidence of circa 1 per million population per year [1,2]. ACCs present with a slight female predominance (55e65%) and can affect individuals of all ages, with a peak between the 5th and 6th decade [1e4]. The majority of ACCs are sporadic but may also occur as a part of LieFraumeni syndrome, Lynch www.sciencedirect.com
syndrome, multiple endocrine neoplasia type 1, neurofibromatosis type 1, and familial adenomatous polyposis [5e7]. At the time of diagnosis, early-stage disease (ENSAT stage I or II) is diagnosed in 30e59% of patients, advanced ENSAT stage III in 10e19% of patients, and metastatic ENSAT stage IV in 21e40% of patients [1,2,8,9]. Early-stage disease demonstrates a five-year overall survival of 62e100% [1e3]. Advancedstage ACC (ENSAT II and IV) is associated with a poor prognosis, with a recent multicenter study documenting a median overall survival of 24 months in 444 patients with ACC ENSAT stages III and IV [10]; in the same study, a further modification of the classification (modified ENSAT classification) that considered stage, R status, age, and symptoms provided superior prognostic prediction. This classification was recently extended by the inclusion of molecular and genetic parameters [11,12]. Surgery is the mainstay of therapy in patients with operable ACC, with R0 resection being the only curative intervention and the Ki67 index being the most important histopathological predictor of probability of recurrence [13]. Diagnosis of ACC is currently based on imaging phenotype and standard-of-care hormonal workup and may present a diagnostic dilemma when imaging characteristics and the hormonal workup are insufficient to make an accurate diagnosis. In patients diagnosed with ACC and undergoing surgical resection, monitoring for recurrence is cumbersome and relies on frequent imaging that may delay management. Early diagnosis is the key to assure prompt management and improve the prognosis. It is also equally important to accurately exclude ACC in the large number of patients with incidentally discovered adrenal tumors, which in the majority represent harmless adenomas. Noninvasive biomarkers that accurately distinguish ACC from other tumors could aid in making an earlier diagnosis and lead to a better overall prognosis. This review summarizes the current diagnostic approach to ACC including the emerging role of steroid biomarkers in the diagnosis of ACC.
Diagnosis of ACC Imaging
Imaging phenotype, including tumor size and other imaging characteristics, provides key information in Current Opinion in Endocrine and Metabolic Research 2019, 8:167–173
168 Adrenal cortex
making the initial diagnosis of ACC. At the time of presentation, ACCs are usually unilateral large tumors with a median size of 10 cm [1,2,4]. Based on a large series of more than 1000 patients, tumor size cutoff of >4 cm has a sensitivity of 93% but a poor specificity of 42% in distinguishing ACC from other adrenal tumors [14]. In a more recent study of 705 large adrenal tumors of >4 cm, the overall rate of malignancy was 31%, with 13% of patients being diagnosed with ACC [4]. Although ACCs usually present as large tumors, diagnosis at an earlier stage and smaller size has been reported in some instances, especially when discovered incidentally on cross-sectional imaging performed for reasons other than suspicion of an adrenal mass [2]. In a consecutive cohort of 47 patients evaluated between 2002 and 2018 in a single center in Finland, authors reported that 19% of patients were diagnosed with stage I ACC and 40.5% patients with stage II, with the smallest ACC described at only 2 cm in size [2]. Data on the natural history of ACC are scarce; however, a slower growth and initial discovery at a smaller size is possible and represents a challenge when imaging characteristics are indeterminate. ACCs have low lipid content and thus present with increased attenuation on unenhanced computed tomography (CT) and absence of chemical shift on magnetic resonance imaging. The median unenhanced Hounsfield unit (HU) of ACCs on CTwas reported at around 35 HU, with a minimum of 18e21 HU [2,4]. Recently, Dinnes et al. [15] summarized data on accuracy of imaging characteristics for the diagnosis of malignant adrenal mass in a systematic review and meta-analysis. Unenhanced CT attenuation cutoff equal to or higher than 10 HU demonstrated a 100% sensitivity but a lower specificity of 72% in diagnosing adrenal malignancy. A subsequent study of 353 patients at high risk of malignancy confirmed that unenhanced attenuation of >10 HU diagnosed malignancy with a sensitivity of 100% but with a specificity of 33% [16]. The relatively poor specificity in diagnosing ACC is explained by the fact that while a high lipid content reliably indicates a benign adrenal tumor, a large proportion of adrenal adenomas and other benign adrenal masses also have a low lipid content as ACC. Limited data from patients with adrenal tumors who underwent the FDG-PET scan demonstrated that a FDG-PET/CT adrenal:liver ratio of >1.8 indicates malignancy with a sensitivity of 87% and specificity of 84% and could be additive in value when the adrenal mass is indeterminate on CT [16]. There is no good quality evidence to support the differential diagnostic value of CT washout studies [15], despite its often widespread use in clinical practice. Adrenal biopsy
Adrenal biopsy is not recommended in patients with ACC as the limited amount of tissue obtained at biopsy makes Current Opinion in Endocrine and Metabolic Research 2019, 8:167–173
the differentiation of benign from malignant adrenocortical tissue often impossible; in addition, there is concern of risk of needle track tumor dissemination [17e19]. In a systematic review and meta-analysis of performance in diagnosis of adrenal malignancy, adrenal biopsy was reported to have a sensitivity of only 70% in diagnosing ACC [18]. Moreover, adrenal biopsy has a nondiagnostic rate of 5e8.7% and complication rate of 2.5e4% and should be reserved for patients with high pretest suspicion of adrenal metastasis as recommended by the 2016 European Society for Endocrinology (ESE)-ENSAT guidelines for evaluation of adrenal tumors [17e19]. Adrenal hormonal excess
Patients with ACC may present with clinical signs and symptoms of hormone excess (31e50%), with mass effect (14e30%), incidentally (42e79%), or very rarely with B symptoms (<1%) [2e4]. Regardless of the mode of discovery, the workup for hormonal excess should be performed in any patient with an adrenal mass. A thorough workup reveals biochemical evidence of hormonal excess in 63e73% of patients with ACC [2,20] (Table 1). Cortisol excess is the most common hormone overproduction in ACC, documented in 41e67% of patients, isolated androgen excess is found in 19e52% of female patients, estrogen excess, in 5e7% of male patients, and aldosterone excess, in 2e20% of patients [2,3,20,21]. A presentation with mixed adrenal hormone excess, most commonly glucocorticoid and androgen excess (seen in around 20e27% of patients), is strongly indicative of ACC and not seen in benign adrenal adenomas [2,3,20,21]. The only exception is the concurrent presentation with glucocorticoid and mineralocorticoid excess, which is regularly seen in benign tumors, including a large proportion of patients with primary aldosteronism [22].
Steroid biomarkers of ACC In addition to the standard-of-care workup for adrenal hormonal excess (Table 1), multisteroid profiling in serum, plasma, and 24-h urine has been suggested as valuable diagnostic biomarker approaches for the diagnosis of ACC [20,21,23e26] (Table 2). Physiologically, adrenal steroid secretion is affected by sex, age, and the body mass index [20,27e30]; however, in the context of excess steroid production in ACC, the variability of these physiological parameters is much lower than typically observed steroid concentrations. Serum steroids are affected by the diurnal variation and circulate in relatively low concentrations. Measurement of steroids in a 24-h urine sample represents a more accurate and representative estimate of the daily net steroid production [20,31] and, therefore, likely holds superior diagnostic potential for the assessment of www.sciencedirect.com
www.sciencedirect.com
Overt hormonal excess or subclinical hormonal excess. a
ACTH, corticotropin; DHEAS, Dehydroepiandrosterone sulfate.
5 Estrogen
2 Aldosterone
30% Androgen
169
adrenal hormonal excess. The collection of a 24-h urine sample is noninvasive but may be slightly more cumbersome for patients than collection of a blood sample, and the accuracy of urine steroid quantification may be affected by an incomplete 24-h urine collection. Androgens and glucocorticoids contribute to the majority of urinary steroids, whereas mineralocorticoids and steroid precursors represent a smaller part of steroid metabolome [1,20,23,26].
Uterine bleeding (postmenopausal women) Gynecomastia, sexual dysfunction in men
Abdominal fat redistribution, proximal myopathy, striae, moon facies, hyperglycemia, hypertension, osteoporosis Hirsutism, virilization in women, secondary amenorrhea Resistant hypertension, edema
Abnormal dexamethasone suppression test, increased 24-h urine cortisol, suppressed plasma ACTH Elevated serum DHEAS, androstenedione, testosterone Elevated plasma aldosterone and suppressed plasma renin Elevated estradiol 50–70% Glucocorticoid
Biochemical findings Prevalencea,[3,4] Steroid excess
Workup for adrenal hormonal excess.
Table 1
Clinical manifestations
Steroids in ACC Bancos and Arlt
The diagnostic value of multisteroid profiling in ACC is based on the finding of immature steroidogenesis with highly increased excretion of steroid hormone precursors rather than end products of steroid hormone biosynthesis. This was first demonstrated and systematically explored by Arlt et al. [20] in a proof-of-concept study of 45 patients with ACC and 102 patients with benign adrenocortical adenomas (ACAs), using gas chromatographyemass spectrometry (GCeMS) for analysis of 24h urine samples. This included concurrent identification and quantitation of 32 distinct steroid metabolites in a single GCeMS run, with the resulting steroid data subsequently analyzed by a machine learningebased algorithm. This approach revealed a distinct pattern of steroid hormone precursors, that is, a malignant ‘steroid fingerprint,’ that diagnosed ACC with a 90% sensitivity and 90% specificity (Table 3). A subsequent study by Kerkhofs et al. [21] in 27 patients with ACC and 107 patients with ACA, GCeMS profiling of 22 steroids revealed high sensitivity but a variable specificity of 2e 83%, but that study did not use a computational algorithm for data analysis and interpretation (Table 3). Another study of 31 patients with ACC and 108 patients with ACA using a 32-steroid GCeMS method by Velikanova et al. [26] demonstrated again that patients with ACC have significantly higher steroid precursor output than patients with ACC (Table 3). While steroid profiling by GCeMS showed promise, this method is time-consuming and technically demanding and, as such, only available in specialized centers. A highthroughput method using liquid chromatography (LC)ehigh-resolution accurate mass spectrometry was subsequently developed by Hines et al. [23] and tested in a small cohort of patients, including 5 patients with ACC and 61 patients with ACA. The authors demonstrated similar findings to those of previous studies, with 11 steroids significantly higher in patients with ACC (Table 3). All studies examining 24-h urine steroid profiling in patients with ACC agree that tetrahydro-11deoxycortisol derived from 11-deoxycortisol and the adrenal androgen precursor metabolites pregnanediol (5-PD) and pregnanetriol (5-PT), derived from pregnenolone and 17-hydroxypregnenolone, respectively, present the highest diagnostic value. In addition, other steroids of diagnostic value include the progesterone metabolite pregnanediol, the 17OHP metabolite Current Opinion in Endocrine and Metabolic Research 2019, 8:167–173
170 Adrenal cortex
Table 2 Serum and urinary steroids. Serum steroid
Cortisol
Cortisone
21-Deoxycortisol 17-Hydroxyprogesterone Progesterone 11-Deoxycortisol Corticosterone Corticosterone and 11-dehydrocorticosterone 11-Deoxycorticosterone Androstenedione, testosterone 17-Hydroxypregnenolone Pregnenolone Dehydroepiandrosterone and Dehydroepiandrosterone sulfate Dihydrotestosterone
Urinary steroid metabolite
In ACC
Full name
Abbreviation
Cortisol А-cortol В-cortol 6b-Hydroxycortisol 5a-Tetrahydrocortisol Tetrahydrocortisol Cortisone А-cortolone B-cortolone Tetrahydrocortisone Pregnanetriolone Pregnanetriol 17-Hydroxypregnenolone Pregnanediol Tetrahydro-11-deoxycortisol Tetrahydro-11-corticosterone 5a-Tetrahydro-11-corticosterone 5a-Tetrahydro-11-dehydrocorticosterone Tetrahydro-11-dehydrocorticosterone Tetrahydro-11-deoxycorticosterone 5a-Tetrahydro-11-deoxycorticosterone Androsterone Etiocholanolone Pregnanetriol Pregnanediol Dehydroepiandrosterone 16a-Hydroxydehydroepiandrosterone Androsterone
F a-cortol В-cortol 6b –OH–Cortisol 5a-THF THF E a-cortolone b-cortolone THE PTONE PT 17-HP PD THS THB 5a-THB 5a-THA THA THDOC 5a-THDOC An Etio 5-PT 5-PD DHEA 16a-DHEA An
-/[ -/[ -/[ -/[ -/[ -/[ -/[ -/[ -/[ -/[ -/[ [ [[ [[ [[[ [ [ [ -/[ -/[ -/[ [[ [[ [[[ [[[ [[ [[ [[
ACC, adrenal cortical carcinoma.
pregnanetriol, the 11-deoxycorticosterone metabolite tetrahydro-11-deoxycorticosterone, the corticosterone metabolite 5a-tetrahydrocortisol (5a-tetrahydro-11dehydrocorticosterone), the cortisol metabolite 5atetrahydrocortisol, and the androgen metabolites etiocholanolone and androsterone (Tables 2 and 3). Analyzing serum samples from patients with ACC, Taylor et al. [25] reported on performance of a 13steroid panel by LCetandem MS (LCeMS/MS), describing up to 7 highly increased steroids, in a very limited cohort comprising only 10 patients with ACC and 23 patients with ACA. Corresponding to 24-h urine results, they found that 11-deoxycortisol was the most discriminating steroid and increased in all 10 patients with ACC they examined. In addition, concentrations of Dehydroepiandrosterone sulfate (DHEAS), androstenedione, 17 OH -provesterone (17OHProg), 17 -OH pregnenolone (17OHPreg), 11-deoxycorticosterone, and cortisol were significantly increased in patients with ACC vs ACA (Table 3). In a larger study, albeit still limited in size, Schweitzer et al. [24] measured 15 plasma steroids by LCeMS/MS in 42 patients with ACC and 66 patients with ACA. In that study, they described Current Opinion in Endocrine and Metabolic Research 2019, 8:167–173
increased plasma concentrations of 11deoxycorticosterone, progesterone, 17-hydroxyprogesterone, 11-deoxycortisol, dehydroepiandrosterone (DHEA), DHEAS, and estradiol in patients with ACC. Discrimination between ACC and ACA was poor when single steroids were analyzed; however, a combination of 6 steroids achieved a receiver operating characteristic curve area under the curve (AUC) of 0.94 in men (11-deoxycortisol, DHEA, progesterone, androstenedione, corticosterone, and estradiol) and 0.95 in women (DHEAS, DHEA, androstenedione, dehydrotestosterone (DHT), 11deoxycorticosterone, and 17OHProg) (Table 3). The unanimous findings of increased serum/plasma concentrations of 11-deoxycortisol and urinary excretion of the 11-deoxycortisol metabolite tetrahydro-11deoxycortisol in patients with ACC indicate reduced activity or decreased expression of CYP11B1, the enzyme responsible for conversion of 11-deoxycortisol to cortisol, which may represent a consequence of the steroidogenic dedifferentiation and shift to immature steroidogenesis occurring in ACC. Similarly, the accumulation of pregnenolone and 17OHPreg, and in www.sciencedirect.com
www.sciencedirect.com
Table 3 Studies evaluating steroid profiling in patients with adrenocortical carcinoma (ACC) and patients with adrenocortical adenoma (ACA). Author, year
ACC (n)
ACA (n)
Biomaterial
Steroid profiling method
Findings
Arlt et al, 2011 [20]
Retrospective, 6 centers
45
102
24-h urine
GC–MS, 32 steroids + machine learning computation
Kerkhofs et al, 2015 [21]
Retrospective, 2 centers
27
107
24-h urine
GC–MS, 22 steroids
Velikanova et al, 2016 [26]
Retrospective, 3 centers
31
108
24-h urine
GC–MS, 32 steroids
Hines et al, 2017 [23]
Retrospective study of prospectively collected samples, single center NA
5
61
24-h urine
HRAM LC–MS, 26 steroids
Sensitivity = Specificity of 9 steroids, THS, 5-PT, 5-PD, PT, THDOC, 5a-THA, Etio, 5a-THF, and PD, to diagnose ACC: 88% Sensitivity = Specificity of 32 steroids to diagnose ACC: 90% ROC analysis demonstrated that 15 steroids had a sensitivity of >90% and specificity of 2–99% for detecting ACC; of which, 7 had a sensitivity of 100% and specificity of 4–99% (THS, 5-PT, 5-PD, Etio, An, THF, and THE) Patients with ACC have significantly higher THS, PD, 5-PT, and 5-PD than patients with ACA; however, increased THS was demonstrated only in 74% of patients with ACC. Patients with ACC (vs ACA) demonstrated significantly higher concentrations in 11 steroids (2- to 14-fold differences).
10
23
Serum
LC–MS/MS, 13 steroids
Retrospective study of prospectively collected samples, single center
42
66
Plasma
LC–MS/MS, 15 steroids + computational model
Taylor et al, 2017 [25]
Schweitzer et al, 2019 [24]
Patients with ACC (vs ACA) demonstrated significantly higher concentrations in 11deoxycortisol, DHEAS, androstenedione, 17OHProg, 17OHPreg, 11-deoxycorticosterone, and cortisol Combination of 6 steroids distinguished ACC from ACA: Men: AUC of 0.94 (11deoxycortisol, DHEA, progesterone, androstenedione, corticosterone, and estradiol) Women: AUC of 0.95 for women (DHEAS, DHEA, androstenedione, DHT, 11deoxycorticosterone, and 17OHProg)
5a-THA, 5a-tetrahydro-11-dehydrocorticosterone; 5a-THF, 5a-tetrahydrocortisol; An, androsterone; DHEA, dehydroepiandrosterone; Etio, etiocholanolone; GC, gas chromatography; HRAM, high-resolution accurate mass spectrometry; LC, liquid chromatography; MS, mass spectrometry; PD, pregnanediol; PT, pregnanetriol; ROC, receiver operating characteristic; THDOC, tetrahydro-11-deoxycorticosterone; THE, tetrahydrocortisone; THS, tetrahydro-11-deoxycortisol; DHEAS, dehydroepiandrosterone sulfate; AUC, area under the curve; 17OHProg, 17 OH -provesterone; 17OHpreg, 17 -OH pregnenolone.
Steroids in ACC Bancos and Arlt 171
Current Opinion in Endocrine and Metabolic Research 2019, 8:167–173
Type of study
172 Adrenal cortex
relatively much higher concentrations of their urinary metabolites 5-PT and 5-PD, indicates an inefficiency of CYP17A1 (17,20-lyase) activity in converting 17-hydroxypregnenolone to the major androgen precursor DHEA.
Conflict of interest W.A. is an inventor to a patent on the use of steroid profiling as a biomarker tool in the differential diagnosis of steroid-producing and steroid-dependent tumors (PCT/ GB2010/000274). I.B. reports advisory board participation with HRA Pharma outside the submitted work.
Clinical implications
Clinicians currently face the dilemma of struggling to accurately differentiate ACC from other tumors based on imaging alone. A large adrenal tumor with imaging characteristics suggestive of a lipid poor mass may represent a benign tumor (adrenal adenoma, ganglioneuroma, and so on) or other malignant adrenal mass (such as sarcoma, lymphoma, or metastasis of an extraadrenal primary tumor). However, the downstream therapeutic pathways for these three entities are very different, and accurate diagnosis would assure that the implemented therapy is appropriate, and unnecessary procedures or delay in management is avoided. Even in situations when adrenalectomy is considered, such as an adrenal mass with overt cortisol excess, the choice between laparoscopic versus open surgery may have significant implications for duration of surgery, recovery, rate of complications, and overall prognosis. Based on the retrospective studies available to date, significantly higher excretion of steroid precursor metabolites in ACCs compared with ACAs positions steroid profiling as an attractive noninvasive alternative to the current standard practice that relies heavily on imaging and invasive procedures. Urine steroid metabolomics, that is, the combination of multisteroid profiling MS in combination with machine learningebased computational data analysis, was recently taken forward in a prospective validation study that recruited more than 2000 patients with adrenal tumors (EURINE-ACT), which hopefully will pave the way for introduction of urine steroid metabolomics into the routine workup of patients with adrenal tumors.
Funding This work has been supported by the European Commission Horizon 2020 Program under grant agreement 633983 (ENSAT-HT, to W.A.), Robert and Elizabeth Strickland Career Development Award, James A. Ruppe Career Development Award in Endocrinology, and the Catalyst award for Advancing in Academics (Mayo Clinic, Rochester, to IB). This research was supported by the National Institute of Diabetes and Digestive and Kidney Diseases of the National Institutes of Health USA under award number K23DK121888 (to I.B.). I.B. was also supported by a Robert and Elizabeth Strickland Career Development Award, a James A. Ruppe Career Development Award in Endocrinology, and a Catalyst for Advancing in Academics Award from Mayo Clinic. The views expressed are those of the authors and not necessarily the official views of the National Institutes of Health USA. Current Opinion in Endocrine and Metabolic Research 2019, 8:167–173
References Papers of particular interest, published within the period of review, have been highlighted as: * of special interest * * of outstanding interest 1.
Kerkhofs TM, Verhoeven RH, Van der Zwan JM, et al.: Adrenocortical carcinoma: a population-based study on incidence and survival in The Netherlands since 1993. Eur J Cancer 2013, 49:2579–2586.
2.
Kostiainen I, Hakaste L, Kejo P, Parviainen H, Laine T, Loyttyniemi E, et al.: Adrenocortical carcinoma: presentation and outcome of a contemporary patient series. Endocrine 2019;(65):166–174.
3. **
Fassnacht M, Dekkers O, Else T, et al.: European society of Endocrinology clinical practice guidelines on the management of adrenocortical carcinoma in adults, in collaboration with the european network for the study of adrenal tumors. Eur J Endocrinol 2018. This is a comprehensive review of current evidence and guidelines on management of adrenocortical carcinoma 4. *
Iniguez-Ariza NM, Kohlenberg JD, Delivanis DA, et al.: Clinical, biochemical, and radiological characteristics of a singlecenter retrospective cohort of 705 large adrenal tumors. Mayo Clin Proc Innov Qual Outcomes 2018, 2:30–39. Authors describe a large cohort of large adrenal tumors in regards to presentation, imaging phenotype and hormonal work up, as well as predictors of malignancy. 5.
Kaur RJ, Pichurin PN, Hines JM, Singh RJ, Grebe SK, Bancos I: Adrenal cortical carcinoma associated with Lynch syndrome: a case report and review of literature. J Endocr Soc 2019, 3: 784–790.
6.
Ballinger ML, Best A, Mai PL, et al.: Baseline surveillance in Lifraumeni syndrome using whole-body magnetic resonance imaging: a meta-analysis. JAMA Oncol 2017, 3:1634–1639.
7.
Else T: Association of adrenocortical carcinoma with familial cancer susceptibility syndromes. Mol Cell Endocrinol 2012, 351:66–70.
8.
Fassnacht M, Johanssen S, Quinkler M, et al.: Limited prognostic value of the 2004 International Union against Cancer staging classification for adrenocortical carcinoma: proposal for a Revised TNM Classification. Cancer 2009, 115:243–250.
9.
Lughezzani G, Sun M, Perrotte P, et al.: The European Network for the Study of Adrenal Tumors staging system is prognostically superior to the international union against cancerstaging system: a North American validation. Eur J Cancer 2010, 46:713–719.
10. Libe R, Borget I, Ronchi CL, et al.: Prognostic factors in stage III-IV adrenocortical carcinomas (ACC): an european network for the study of adrenal tumor (ENSAT) study. Ann Oncol 2015, 26:2119–2125. 11. Lippert J, Appenzeller S, Liang R, et al.: Targeted molecular analysis in adrenocortical carcinomas: a strategy toward improved personalized prognostication. J Clin Endocrinol Metab 2018, 103:4511–4523. 12. Assie G, Jouinot A, Fassnacht M, et al.: Value of molecular classification for prognostic assessment of adrenocortical carcinoma. JAMA Oncol 2019. 13. Beuschlein F, Weigel J, Saeger W, et al.: Major prognostic role of Ki67 in localized adrenocortical carcinoma after complete resection. J Clin Endocrinol Metab 2015, 100:841–849.
www.sciencedirect.com
Steroids in ACC Bancos and Arlt
173
14. Mantero F, Terzolo M, Arnaldi G, et al.: A survey on adrenal incidentaloma in Italy. Study group on adrenal tumors of the Italian society of Endocrinology. J Clin Endocrinol Metab 2000, 85:637–644.
23. Hines JM, Bancos I, Bancos C, et al.: High-resolution, accuratemass (HRAM) mass spectrometry urine steroid profiling in the diagnosis of adrenal disorders. Clin Chem 2017, 63: 1824–1835.
15. Dinnes J, Bancos I, Ferrante di Ruffano L, et al.: Management OF endocrine disease: imaging for the diagnosis of malignancy in incidentally discovered adrenal masses: a systematic review and meta-analysis. Eur J Endocrinol 2016, 175: R51–R64.
24. Schweitzer S, Kunz M, Kurlbaum M, et al.: Plasma steroid * metabolome profiling for the diagnosis of adrenocortical carcinoma. Eur J Endocrinol 2019, 180:117–125. In this study authors demonstrate a high diagnostic value of plasma steroid profiling in adrenocortical carcinoma.
16. Delivanis DA, Bancos I, Atwell TD, et al.: Diagnostic performance of unenhanced computed tomography and (18) Ffluorodeoxyglucose positron emission tomography in indeterminate adrenal tumours. Clin Endocrinol 2018, 88:30–36.
25. Taylor DR, Ghataore L, Couchman L, et al.: A 13-steroid serum panel based on LC-MS/MS: use in detection of adrenocortical carcinoma. Clin Chem 2017, 63:1836–1846.
17. Delivanis DA, Erickson D, Atwell TD, et al.: Procedural and clinical outcomes of percutaneous adrenal biopsy in a highrisk population for adrenal malignancy. Clin Endocrinol 2016, 85:710–716.
26. Velikanova LI, Shafigullina ZR, Lisitsin AA, et al.: Different types of urinary steroid profiling obtained by high-performance liquid chromatography and gas chromatography-mass spectrometry in patients with adrenocortical carcinoma. Horm Cancer 2016, 7:327–335.
18. Bancos I, Tamhane S, Shah M, et al.: Diagnosis OF endocrine disease: the diagnostic performance of adrenal biopsy: a systematic review and meta-analysis. Eur J Endocrinol 2016, 175:R65–R80.
27. O’Reilly MW, Taylor AE, Crabtree NJ, et al.: Hyperandrogenemia predicts metabolic phenotype in polycystic ovary syndrome: the utility of serum androstenedione. J Clin Endocrinol Metab 2014, 99:1027–1036.
19. Fassnacht M, Arlt W, Bancos I, et al.: Management of adrenal incidentalomas: european society of Endocrinology clinical practice guideline in collaboration with the european network for the study of adrenal tumors. Eur J Endocrinol 2016, 175: G1–G34.
28. Tomlinson JW, Finney J, Hughes BA, Hughes SV, Stewart PM: Reduced glucocorticoid production rate, decreased 5alphareductase activity, and adipose tissue insulin sensitization after weight loss. Diabetes 2008, 57:1536–1543.
20. Arlt W, Biehl M, Taylor AE, et al.: Urine steroid metabolomics as * a biomarker tool for detecting malignancy in adrenal tumors. J Clin Endocrinol Metab 2011, 96:3775–3784. First proof of concept large study on steroid profiling and computational analysis in patients with adrenocortical carcinoma. 21. Kerkhofs TM, Kerstens MN, Kema IP, Willems TP, Haak HR: Diagnostic value of urinary steroid profiling in the evaluation of adrenal tumors. Horm Cancer 2015, 6:168–175. 22. Arlt W, Lang K, Sitch AJ, et al.: Steroid metabolome analysis * * reveals prevalent glucocorticoid excess in primary aldosteronism. JCI Insight 2017, 2. Key study demonstrating high prevalence of glucocorticoid excess in patients with primary aldosteronism.
www.sciencedirect.com
29. Ackermann D, Groessl M, Pruijm M, et al.: Reference intervals for the urinary steroid metabolome: the impact of sex, age, day and night time on human adult steroidogenesis. PLoS One 2019, 14:e0214549. 30. de Jong WHA, Buitenwerf E, Pranger AT, et al.: Determination of reference intervals for urinary steroid profiling using a newly validated GC-MS/MS method. Clin Chem Lab Med 2017, 56: 103–112. 31. Kotlowska A, Malinski E, Sworczak K, Kumirska J, Stepnowski P: The urinary steroid profile in patients diagnosed with adrenal incidentaloma. Clin Biochem 2009, 42:448–454.
Current Opinion in Endocrine and Metabolic Research 2019, 8:167–173
ScienceDirect
Current Opinion in
Endocrine and Metabolic Research
Review
Steroid biomarkers and the diagnosis of adrenal cortical carcinoma Irina Bancos1 and Wiebke Arlt2,3 Abstract
Adrenal cortical carcinomas (ACCs) are rare adrenal tumors with a poor prognosis when diagnosed at an advanced stage. Early diagnosis is the key to assure prompt management and improve the prognosis. Surgery is the mainstay of therapy in patients with operable ACC, with R0 resection being the only curative intervention. Diagnosis of ACC is currently based on imaging phenotype and standard-of-care hormonal workup and may present a diagnostic dilemma when imaging characteristics and the hormonal workup are insufficient to make an accurate diagnosis. Noninvasive biomarkers that accurately distinguish ACC from other tumors could aid in making an earlier diagnosis and lead to a better overall prognosis. This review summarizes the current diagnostic approach to ACC including the emerging role of steroid biomarkers in the diagnosis of ACC. Addresses 1 Division of Endocrinology, Diabetes, Metabolism and Nutrition, Mayo Clinic, Rochester, MN, USA 2 Institute of Metabolism and Systems Research, University of Birmingham, Birmingham, UK 3 Centre for Endocrinology, Diabetes and Metabolism, Birmingham Health Partners, Birmingham, UK Corresponding author: Bancos, Irina ([email protected])
Current Opinion in Endocrine and Metabolic Research 2019, 8:167–173 This review comes from a themed issue on Adrenal Cortex Edited by André Lacroix and Enzo Lalli For a complete overview see the Issue and the Editorial Available online 30 August 2019 https://doi.org/10.1016/j.coemr.2019.08.013 2451-9650/© 2019 Elsevier Ltd. All rights reserved.
Keywords ACC, Adrenal mass, Diagnosis, Steroid, Prognosis, Imaging, Biopsy.
Introduction Adrenal cortical carcinomas (ACCs) are rare adrenal tumors with an incidence of circa 1 per million population per year [1,2]. ACCs present with a slight female predominance (55e65%) and can affect individuals of all ages, with a peak between the 5th and 6th decade [1e4]. The majority of ACCs are sporadic but may also occur as a part of LieFraumeni syndrome, Lynch www.sciencedirect.com
syndrome, multiple endocrine neoplasia type 1, neurofibromatosis type 1, and familial adenomatous polyposis [5e7]. At the time of diagnosis, early-stage disease (ENSAT stage I or II) is diagnosed in 30e59% of patients, advanced ENSAT stage III in 10e19% of patients, and metastatic ENSAT stage IV in 21e40% of patients [1,2,8,9]. Early-stage disease demonstrates a five-year overall survival of 62e100% [1e3]. Advancedstage ACC (ENSAT II and IV) is associated with a poor prognosis, with a recent multicenter study documenting a median overall survival of 24 months in 444 patients with ACC ENSAT stages III and IV [10]; in the same study, a further modification of the classification (modified ENSAT classification) that considered stage, R status, age, and symptoms provided superior prognostic prediction. This classification was recently extended by the inclusion of molecular and genetic parameters [11,12]. Surgery is the mainstay of therapy in patients with operable ACC, with R0 resection being the only curative intervention and the Ki67 index being the most important histopathological predictor of probability of recurrence [13]. Diagnosis of ACC is currently based on imaging phenotype and standard-of-care hormonal workup and may present a diagnostic dilemma when imaging characteristics and the hormonal workup are insufficient to make an accurate diagnosis. In patients diagnosed with ACC and undergoing surgical resection, monitoring for recurrence is cumbersome and relies on frequent imaging that may delay management. Early diagnosis is the key to assure prompt management and improve the prognosis. It is also equally important to accurately exclude ACC in the large number of patients with incidentally discovered adrenal tumors, which in the majority represent harmless adenomas. Noninvasive biomarkers that accurately distinguish ACC from other tumors could aid in making an earlier diagnosis and lead to a better overall prognosis. This review summarizes the current diagnostic approach to ACC including the emerging role of steroid biomarkers in the diagnosis of ACC.
Diagnosis of ACC Imaging
Imaging phenotype, including tumor size and other imaging characteristics, provides key information in Current Opinion in Endocrine and Metabolic Research 2019, 8:167–173
168 Adrenal cortex
making the initial diagnosis of ACC. At the time of presentation, ACCs are usually unilateral large tumors with a median size of 10 cm [1,2,4]. Based on a large series of more than 1000 patients, tumor size cutoff of >4 cm has a sensitivity of 93% but a poor specificity of 42% in distinguishing ACC from other adrenal tumors [14]. In a more recent study of 705 large adrenal tumors of >4 cm, the overall rate of malignancy was 31%, with 13% of patients being diagnosed with ACC [4]. Although ACCs usually present as large tumors, diagnosis at an earlier stage and smaller size has been reported in some instances, especially when discovered incidentally on cross-sectional imaging performed for reasons other than suspicion of an adrenal mass [2]. In a consecutive cohort of 47 patients evaluated between 2002 and 2018 in a single center in Finland, authors reported that 19% of patients were diagnosed with stage I ACC and 40.5% patients with stage II, with the smallest ACC described at only 2 cm in size [2]. Data on the natural history of ACC are scarce; however, a slower growth and initial discovery at a smaller size is possible and represents a challenge when imaging characteristics are indeterminate. ACCs have low lipid content and thus present with increased attenuation on unenhanced computed tomography (CT) and absence of chemical shift on magnetic resonance imaging. The median unenhanced Hounsfield unit (HU) of ACCs on CTwas reported at around 35 HU, with a minimum of 18e21 HU [2,4]. Recently, Dinnes et al. [15] summarized data on accuracy of imaging characteristics for the diagnosis of malignant adrenal mass in a systematic review and meta-analysis. Unenhanced CT attenuation cutoff equal to or higher than 10 HU demonstrated a 100% sensitivity but a lower specificity of 72% in diagnosing adrenal malignancy. A subsequent study of 353 patients at high risk of malignancy confirmed that unenhanced attenuation of >10 HU diagnosed malignancy with a sensitivity of 100% but with a specificity of 33% [16]. The relatively poor specificity in diagnosing ACC is explained by the fact that while a high lipid content reliably indicates a benign adrenal tumor, a large proportion of adrenal adenomas and other benign adrenal masses also have a low lipid content as ACC. Limited data from patients with adrenal tumors who underwent the FDG-PET scan demonstrated that a FDG-PET/CT adrenal:liver ratio of >1.8 indicates malignancy with a sensitivity of 87% and specificity of 84% and could be additive in value when the adrenal mass is indeterminate on CT [16]. There is no good quality evidence to support the differential diagnostic value of CT washout studies [15], despite its often widespread use in clinical practice. Adrenal biopsy
Adrenal biopsy is not recommended in patients with ACC as the limited amount of tissue obtained at biopsy makes Current Opinion in Endocrine and Metabolic Research 2019, 8:167–173
the differentiation of benign from malignant adrenocortical tissue often impossible; in addition, there is concern of risk of needle track tumor dissemination [17e19]. In a systematic review and meta-analysis of performance in diagnosis of adrenal malignancy, adrenal biopsy was reported to have a sensitivity of only 70% in diagnosing ACC [18]. Moreover, adrenal biopsy has a nondiagnostic rate of 5e8.7% and complication rate of 2.5e4% and should be reserved for patients with high pretest suspicion of adrenal metastasis as recommended by the 2016 European Society for Endocrinology (ESE)-ENSAT guidelines for evaluation of adrenal tumors [17e19]. Adrenal hormonal excess
Patients with ACC may present with clinical signs and symptoms of hormone excess (31e50%), with mass effect (14e30%), incidentally (42e79%), or very rarely with B symptoms (<1%) [2e4]. Regardless of the mode of discovery, the workup for hormonal excess should be performed in any patient with an adrenal mass. A thorough workup reveals biochemical evidence of hormonal excess in 63e73% of patients with ACC [2,20] (Table 1). Cortisol excess is the most common hormone overproduction in ACC, documented in 41e67% of patients, isolated androgen excess is found in 19e52% of female patients, estrogen excess, in 5e7% of male patients, and aldosterone excess, in 2e20% of patients [2,3,20,21]. A presentation with mixed adrenal hormone excess, most commonly glucocorticoid and androgen excess (seen in around 20e27% of patients), is strongly indicative of ACC and not seen in benign adrenal adenomas [2,3,20,21]. The only exception is the concurrent presentation with glucocorticoid and mineralocorticoid excess, which is regularly seen in benign tumors, including a large proportion of patients with primary aldosteronism [22].
Steroid biomarkers of ACC In addition to the standard-of-care workup for adrenal hormonal excess (Table 1), multisteroid profiling in serum, plasma, and 24-h urine has been suggested as valuable diagnostic biomarker approaches for the diagnosis of ACC [20,21,23e26] (Table 2). Physiologically, adrenal steroid secretion is affected by sex, age, and the body mass index [20,27e30]; however, in the context of excess steroid production in ACC, the variability of these physiological parameters is much lower than typically observed steroid concentrations. Serum steroids are affected by the diurnal variation and circulate in relatively low concentrations. Measurement of steroids in a 24-h urine sample represents a more accurate and representative estimate of the daily net steroid production [20,31] and, therefore, likely holds superior diagnostic potential for the assessment of www.sciencedirect.com
www.sciencedirect.com
Overt hormonal excess or subclinical hormonal excess. a
ACTH, corticotropin; DHEAS, Dehydroepiandrosterone sulfate.
5 Estrogen
2 Aldosterone
30% Androgen
169
adrenal hormonal excess. The collection of a 24-h urine sample is noninvasive but may be slightly more cumbersome for patients than collection of a blood sample, and the accuracy of urine steroid quantification may be affected by an incomplete 24-h urine collection. Androgens and glucocorticoids contribute to the majority of urinary steroids, whereas mineralocorticoids and steroid precursors represent a smaller part of steroid metabolome [1,20,23,26].
Uterine bleeding (postmenopausal women) Gynecomastia, sexual dysfunction in men
Abdominal fat redistribution, proximal myopathy, striae, moon facies, hyperglycemia, hypertension, osteoporosis Hirsutism, virilization in women, secondary amenorrhea Resistant hypertension, edema
Abnormal dexamethasone suppression test, increased 24-h urine cortisol, suppressed plasma ACTH Elevated serum DHEAS, androstenedione, testosterone Elevated plasma aldosterone and suppressed plasma renin Elevated estradiol 50–70% Glucocorticoid
Biochemical findings Prevalencea,[3,4] Steroid excess
Workup for adrenal hormonal excess.
Table 1
Clinical manifestations
Steroids in ACC Bancos and Arlt
The diagnostic value of multisteroid profiling in ACC is based on the finding of immature steroidogenesis with highly increased excretion of steroid hormone precursors rather than end products of steroid hormone biosynthesis. This was first demonstrated and systematically explored by Arlt et al. [20] in a proof-of-concept study of 45 patients with ACC and 102 patients with benign adrenocortical adenomas (ACAs), using gas chromatographyemass spectrometry (GCeMS) for analysis of 24h urine samples. This included concurrent identification and quantitation of 32 distinct steroid metabolites in a single GCeMS run, with the resulting steroid data subsequently analyzed by a machine learningebased algorithm. This approach revealed a distinct pattern of steroid hormone precursors, that is, a malignant ‘steroid fingerprint,’ that diagnosed ACC with a 90% sensitivity and 90% specificity (Table 3). A subsequent study by Kerkhofs et al. [21] in 27 patients with ACC and 107 patients with ACA, GCeMS profiling of 22 steroids revealed high sensitivity but a variable specificity of 2e 83%, but that study did not use a computational algorithm for data analysis and interpretation (Table 3). Another study of 31 patients with ACC and 108 patients with ACA using a 32-steroid GCeMS method by Velikanova et al. [26] demonstrated again that patients with ACC have significantly higher steroid precursor output than patients with ACC (Table 3). While steroid profiling by GCeMS showed promise, this method is time-consuming and technically demanding and, as such, only available in specialized centers. A highthroughput method using liquid chromatography (LC)ehigh-resolution accurate mass spectrometry was subsequently developed by Hines et al. [23] and tested in a small cohort of patients, including 5 patients with ACC and 61 patients with ACA. The authors demonstrated similar findings to those of previous studies, with 11 steroids significantly higher in patients with ACC (Table 3). All studies examining 24-h urine steroid profiling in patients with ACC agree that tetrahydro-11deoxycortisol derived from 11-deoxycortisol and the adrenal androgen precursor metabolites pregnanediol (5-PD) and pregnanetriol (5-PT), derived from pregnenolone and 17-hydroxypregnenolone, respectively, present the highest diagnostic value. In addition, other steroids of diagnostic value include the progesterone metabolite pregnanediol, the 17OHP metabolite Current Opinion in Endocrine and Metabolic Research 2019, 8:167–173
170 Adrenal cortex
Table 2 Serum and urinary steroids. Serum steroid
Cortisol
Cortisone
21-Deoxycortisol 17-Hydroxyprogesterone Progesterone 11-Deoxycortisol Corticosterone Corticosterone and 11-dehydrocorticosterone 11-Deoxycorticosterone Androstenedione, testosterone 17-Hydroxypregnenolone Pregnenolone Dehydroepiandrosterone and Dehydroepiandrosterone sulfate Dihydrotestosterone
Urinary steroid metabolite
In ACC
Full name
Abbreviation
Cortisol А-cortol В-cortol 6b-Hydroxycortisol 5a-Tetrahydrocortisol Tetrahydrocortisol Cortisone А-cortolone B-cortolone Tetrahydrocortisone Pregnanetriolone Pregnanetriol 17-Hydroxypregnenolone Pregnanediol Tetrahydro-11-deoxycortisol Tetrahydro-11-corticosterone 5a-Tetrahydro-11-corticosterone 5a-Tetrahydro-11-dehydrocorticosterone Tetrahydro-11-dehydrocorticosterone Tetrahydro-11-deoxycorticosterone 5a-Tetrahydro-11-deoxycorticosterone Androsterone Etiocholanolone Pregnanetriol Pregnanediol Dehydroepiandrosterone 16a-Hydroxydehydroepiandrosterone Androsterone
F a-cortol В-cortol 6b –OH–Cortisol 5a-THF THF E a-cortolone b-cortolone THE PTONE PT 17-HP PD THS THB 5a-THB 5a-THA THA THDOC 5a-THDOC An Etio 5-PT 5-PD DHEA 16a-DHEA An
-/[ -/[ -/[ -/[ -/[ -/[ -/[ -/[ -/[ -/[ -/[ [ [[ [[ [[[ [ [ [ -/[ -/[ -/[ [[ [[ [[[ [[[ [[ [[ [[
ACC, adrenal cortical carcinoma.
pregnanetriol, the 11-deoxycorticosterone metabolite tetrahydro-11-deoxycorticosterone, the corticosterone metabolite 5a-tetrahydrocortisol (5a-tetrahydro-11dehydrocorticosterone), the cortisol metabolite 5atetrahydrocortisol, and the androgen metabolites etiocholanolone and androsterone (Tables 2 and 3). Analyzing serum samples from patients with ACC, Taylor et al. [25] reported on performance of a 13steroid panel by LCetandem MS (LCeMS/MS), describing up to 7 highly increased steroids, in a very limited cohort comprising only 10 patients with ACC and 23 patients with ACA. Corresponding to 24-h urine results, they found that 11-deoxycortisol was the most discriminating steroid and increased in all 10 patients with ACC they examined. In addition, concentrations of Dehydroepiandrosterone sulfate (DHEAS), androstenedione, 17 OH -provesterone (17OHProg), 17 -OH pregnenolone (17OHPreg), 11-deoxycorticosterone, and cortisol were significantly increased in patients with ACC vs ACA (Table 3). In a larger study, albeit still limited in size, Schweitzer et al. [24] measured 15 plasma steroids by LCeMS/MS in 42 patients with ACC and 66 patients with ACA. In that study, they described Current Opinion in Endocrine and Metabolic Research 2019, 8:167–173
increased plasma concentrations of 11deoxycorticosterone, progesterone, 17-hydroxyprogesterone, 11-deoxycortisol, dehydroepiandrosterone (DHEA), DHEAS, and estradiol in patients with ACC. Discrimination between ACC and ACA was poor when single steroids were analyzed; however, a combination of 6 steroids achieved a receiver operating characteristic curve area under the curve (AUC) of 0.94 in men (11-deoxycortisol, DHEA, progesterone, androstenedione, corticosterone, and estradiol) and 0.95 in women (DHEAS, DHEA, androstenedione, dehydrotestosterone (DHT), 11deoxycorticosterone, and 17OHProg) (Table 3). The unanimous findings of increased serum/plasma concentrations of 11-deoxycortisol and urinary excretion of the 11-deoxycortisol metabolite tetrahydro-11deoxycortisol in patients with ACC indicate reduced activity or decreased expression of CYP11B1, the enzyme responsible for conversion of 11-deoxycortisol to cortisol, which may represent a consequence of the steroidogenic dedifferentiation and shift to immature steroidogenesis occurring in ACC. Similarly, the accumulation of pregnenolone and 17OHPreg, and in www.sciencedirect.com
www.sciencedirect.com
Table 3 Studies evaluating steroid profiling in patients with adrenocortical carcinoma (ACC) and patients with adrenocortical adenoma (ACA). Author, year
ACC (n)
ACA (n)
Biomaterial
Steroid profiling method
Findings
Arlt et al, 2011 [20]
Retrospective, 6 centers
45
102
24-h urine
GC–MS, 32 steroids + machine learning computation
Kerkhofs et al, 2015 [21]
Retrospective, 2 centers
27
107
24-h urine
GC–MS, 22 steroids
Velikanova et al, 2016 [26]
Retrospective, 3 centers
31
108
24-h urine
GC–MS, 32 steroids
Hines et al, 2017 [23]
Retrospective study of prospectively collected samples, single center NA
5
61
24-h urine
HRAM LC–MS, 26 steroids
Sensitivity = Specificity of 9 steroids, THS, 5-PT, 5-PD, PT, THDOC, 5a-THA, Etio, 5a-THF, and PD, to diagnose ACC: 88% Sensitivity = Specificity of 32 steroids to diagnose ACC: 90% ROC analysis demonstrated that 15 steroids had a sensitivity of >90% and specificity of 2–99% for detecting ACC; of which, 7 had a sensitivity of 100% and specificity of 4–99% (THS, 5-PT, 5-PD, Etio, An, THF, and THE) Patients with ACC have significantly higher THS, PD, 5-PT, and 5-PD than patients with ACA; however, increased THS was demonstrated only in 74% of patients with ACC. Patients with ACC (vs ACA) demonstrated significantly higher concentrations in 11 steroids (2- to 14-fold differences).
10
23
Serum
LC–MS/MS, 13 steroids
Retrospective study of prospectively collected samples, single center
42
66
Plasma
LC–MS/MS, 15 steroids + computational model
Taylor et al, 2017 [25]
Schweitzer et al, 2019 [24]
Patients with ACC (vs ACA) demonstrated significantly higher concentrations in 11deoxycortisol, DHEAS, androstenedione, 17OHProg, 17OHPreg, 11-deoxycorticosterone, and cortisol Combination of 6 steroids distinguished ACC from ACA: Men: AUC of 0.94 (11deoxycortisol, DHEA, progesterone, androstenedione, corticosterone, and estradiol) Women: AUC of 0.95 for women (DHEAS, DHEA, androstenedione, DHT, 11deoxycorticosterone, and 17OHProg)
5a-THA, 5a-tetrahydro-11-dehydrocorticosterone; 5a-THF, 5a-tetrahydrocortisol; An, androsterone; DHEA, dehydroepiandrosterone; Etio, etiocholanolone; GC, gas chromatography; HRAM, high-resolution accurate mass spectrometry; LC, liquid chromatography; MS, mass spectrometry; PD, pregnanediol; PT, pregnanetriol; ROC, receiver operating characteristic; THDOC, tetrahydro-11-deoxycorticosterone; THE, tetrahydrocortisone; THS, tetrahydro-11-deoxycortisol; DHEAS, dehydroepiandrosterone sulfate; AUC, area under the curve; 17OHProg, 17 OH -provesterone; 17OHpreg, 17 -OH pregnenolone.
Steroids in ACC Bancos and Arlt 171
Current Opinion in Endocrine and Metabolic Research 2019, 8:167–173
Type of study
172 Adrenal cortex
relatively much higher concentrations of their urinary metabolites 5-PT and 5-PD, indicates an inefficiency of CYP17A1 (17,20-lyase) activity in converting 17-hydroxypregnenolone to the major androgen precursor DHEA.
Conflict of interest W.A. is an inventor to a patent on the use of steroid profiling as a biomarker tool in the differential diagnosis of steroid-producing and steroid-dependent tumors (PCT/ GB2010/000274). I.B. reports advisory board participation with HRA Pharma outside the submitted work.
Clinical implications
Clinicians currently face the dilemma of struggling to accurately differentiate ACC from other tumors based on imaging alone. A large adrenal tumor with imaging characteristics suggestive of a lipid poor mass may represent a benign tumor (adrenal adenoma, ganglioneuroma, and so on) or other malignant adrenal mass (such as sarcoma, lymphoma, or metastasis of an extraadrenal primary tumor). However, the downstream therapeutic pathways for these three entities are very different, and accurate diagnosis would assure that the implemented therapy is appropriate, and unnecessary procedures or delay in management is avoided. Even in situations when adrenalectomy is considered, such as an adrenal mass with overt cortisol excess, the choice between laparoscopic versus open surgery may have significant implications for duration of surgery, recovery, rate of complications, and overall prognosis. Based on the retrospective studies available to date, significantly higher excretion of steroid precursor metabolites in ACCs compared with ACAs positions steroid profiling as an attractive noninvasive alternative to the current standard practice that relies heavily on imaging and invasive procedures. Urine steroid metabolomics, that is, the combination of multisteroid profiling MS in combination with machine learningebased computational data analysis, was recently taken forward in a prospective validation study that recruited more than 2000 patients with adrenal tumors (EURINE-ACT), which hopefully will pave the way for introduction of urine steroid metabolomics into the routine workup of patients with adrenal tumors.
Funding This work has been supported by the European Commission Horizon 2020 Program under grant agreement 633983 (ENSAT-HT, to W.A.), Robert and Elizabeth Strickland Career Development Award, James A. Ruppe Career Development Award in Endocrinology, and the Catalyst award for Advancing in Academics (Mayo Clinic, Rochester, to IB). This research was supported by the National Institute of Diabetes and Digestive and Kidney Diseases of the National Institutes of Health USA under award number K23DK121888 (to I.B.). I.B. was also supported by a Robert and Elizabeth Strickland Career Development Award, a James A. Ruppe Career Development Award in Endocrinology, and a Catalyst for Advancing in Academics Award from Mayo Clinic. The views expressed are those of the authors and not necessarily the official views of the National Institutes of Health USA. Current Opinion in Endocrine and Metabolic Research 2019, 8:167–173
References Papers of particular interest, published within the period of review, have been highlighted as: * of special interest * * of outstanding interest 1.
Kerkhofs TM, Verhoeven RH, Van der Zwan JM, et al.: Adrenocortical carcinoma: a population-based study on incidence and survival in The Netherlands since 1993. Eur J Cancer 2013, 49:2579–2586.
2.
Kostiainen I, Hakaste L, Kejo P, Parviainen H, Laine T, Loyttyniemi E, et al.: Adrenocortical carcinoma: presentation and outcome of a contemporary patient series. Endocrine 2019;(65):166–174.
3. **
Fassnacht M, Dekkers O, Else T, et al.: European society of Endocrinology clinical practice guidelines on the management of adrenocortical carcinoma in adults, in collaboration with the european network for the study of adrenal tumors. Eur J Endocrinol 2018. This is a comprehensive review of current evidence and guidelines on management of adrenocortical carcinoma 4. *
Iniguez-Ariza NM, Kohlenberg JD, Delivanis DA, et al.: Clinical, biochemical, and radiological characteristics of a singlecenter retrospective cohort of 705 large adrenal tumors. Mayo Clin Proc Innov Qual Outcomes 2018, 2:30–39. Authors describe a large cohort of large adrenal tumors in regards to presentation, imaging phenotype and hormonal work up, as well as predictors of malignancy. 5.
Kaur RJ, Pichurin PN, Hines JM, Singh RJ, Grebe SK, Bancos I: Adrenal cortical carcinoma associated with Lynch syndrome: a case report and review of literature. J Endocr Soc 2019, 3: 784–790.
6.
Ballinger ML, Best A, Mai PL, et al.: Baseline surveillance in Lifraumeni syndrome using whole-body magnetic resonance imaging: a meta-analysis. JAMA Oncol 2017, 3:1634–1639.
7.
Else T: Association of adrenocortical carcinoma with familial cancer susceptibility syndromes. Mol Cell Endocrinol 2012, 351:66–70.
8.
Fassnacht M, Johanssen S, Quinkler M, et al.: Limited prognostic value of the 2004 International Union against Cancer staging classification for adrenocortical carcinoma: proposal for a Revised TNM Classification. Cancer 2009, 115:243–250.
9.
Lughezzani G, Sun M, Perrotte P, et al.: The European Network for the Study of Adrenal Tumors staging system is prognostically superior to the international union against cancerstaging system: a North American validation. Eur J Cancer 2010, 46:713–719.
10. Libe R, Borget I, Ronchi CL, et al.: Prognostic factors in stage III-IV adrenocortical carcinomas (ACC): an european network for the study of adrenal tumor (ENSAT) study. Ann Oncol 2015, 26:2119–2125. 11. Lippert J, Appenzeller S, Liang R, et al.: Targeted molecular analysis in adrenocortical carcinomas: a strategy toward improved personalized prognostication. J Clin Endocrinol Metab 2018, 103:4511–4523. 12. Assie G, Jouinot A, Fassnacht M, et al.: Value of molecular classification for prognostic assessment of adrenocortical carcinoma. JAMA Oncol 2019. 13. Beuschlein F, Weigel J, Saeger W, et al.: Major prognostic role of Ki67 in localized adrenocortical carcinoma after complete resection. J Clin Endocrinol Metab 2015, 100:841–849.
www.sciencedirect.com
Steroids in ACC Bancos and Arlt
173
14. Mantero F, Terzolo M, Arnaldi G, et al.: A survey on adrenal incidentaloma in Italy. Study group on adrenal tumors of the Italian society of Endocrinology. J Clin Endocrinol Metab 2000, 85:637–644.
23. Hines JM, Bancos I, Bancos C, et al.: High-resolution, accuratemass (HRAM) mass spectrometry urine steroid profiling in the diagnosis of adrenal disorders. Clin Chem 2017, 63: 1824–1835.
15. Dinnes J, Bancos I, Ferrante di Ruffano L, et al.: Management OF endocrine disease: imaging for the diagnosis of malignancy in incidentally discovered adrenal masses: a systematic review and meta-analysis. Eur J Endocrinol 2016, 175: R51–R64.
24. Schweitzer S, Kunz M, Kurlbaum M, et al.: Plasma steroid * metabolome profiling for the diagnosis of adrenocortical carcinoma. Eur J Endocrinol 2019, 180:117–125. In this study authors demonstrate a high diagnostic value of plasma steroid profiling in adrenocortical carcinoma.
16. Delivanis DA, Bancos I, Atwell TD, et al.: Diagnostic performance of unenhanced computed tomography and (18) Ffluorodeoxyglucose positron emission tomography in indeterminate adrenal tumours. Clin Endocrinol 2018, 88:30–36.
25. Taylor DR, Ghataore L, Couchman L, et al.: A 13-steroid serum panel based on LC-MS/MS: use in detection of adrenocortical carcinoma. Clin Chem 2017, 63:1836–1846.
17. Delivanis DA, Erickson D, Atwell TD, et al.: Procedural and clinical outcomes of percutaneous adrenal biopsy in a highrisk population for adrenal malignancy. Clin Endocrinol 2016, 85:710–716.
26. Velikanova LI, Shafigullina ZR, Lisitsin AA, et al.: Different types of urinary steroid profiling obtained by high-performance liquid chromatography and gas chromatography-mass spectrometry in patients with adrenocortical carcinoma. Horm Cancer 2016, 7:327–335.
18. Bancos I, Tamhane S, Shah M, et al.: Diagnosis OF endocrine disease: the diagnostic performance of adrenal biopsy: a systematic review and meta-analysis. Eur J Endocrinol 2016, 175:R65–R80.
27. O’Reilly MW, Taylor AE, Crabtree NJ, et al.: Hyperandrogenemia predicts metabolic phenotype in polycystic ovary syndrome: the utility of serum androstenedione. J Clin Endocrinol Metab 2014, 99:1027–1036.
19. Fassnacht M, Arlt W, Bancos I, et al.: Management of adrenal incidentalomas: european society of Endocrinology clinical practice guideline in collaboration with the european network for the study of adrenal tumors. Eur J Endocrinol 2016, 175: G1–G34.
28. Tomlinson JW, Finney J, Hughes BA, Hughes SV, Stewart PM: Reduced glucocorticoid production rate, decreased 5alphareductase activity, and adipose tissue insulin sensitization after weight loss. Diabetes 2008, 57:1536–1543.
20. Arlt W, Biehl M, Taylor AE, et al.: Urine steroid metabolomics as * a biomarker tool for detecting malignancy in adrenal tumors. J Clin Endocrinol Metab 2011, 96:3775–3784. First proof of concept large study on steroid profiling and computational analysis in patients with adrenocortical carcinoma. 21. Kerkhofs TM, Kerstens MN, Kema IP, Willems TP, Haak HR: Diagnostic value of urinary steroid profiling in the evaluation of adrenal tumors. Horm Cancer 2015, 6:168–175. 22. Arlt W, Lang K, Sitch AJ, et al.: Steroid metabolome analysis * * reveals prevalent glucocorticoid excess in primary aldosteronism. JCI Insight 2017, 2. Key study demonstrating high prevalence of glucocorticoid excess in patients with primary aldosteronism.
www.sciencedirect.com
29. Ackermann D, Groessl M, Pruijm M, et al.: Reference intervals for the urinary steroid metabolome: the impact of sex, age, day and night time on human adult steroidogenesis. PLoS One 2019, 14:e0214549. 30. de Jong WHA, Buitenwerf E, Pranger AT, et al.: Determination of reference intervals for urinary steroid profiling using a newly validated GC-MS/MS method. Clin Chem Lab Med 2017, 56: 103–112. 31. Kotlowska A, Malinski E, Sworczak K, Kumirska J, Stepnowski P: The urinary steroid profile in patients diagnosed with adrenal incidentaloma. Clin Biochem 2009, 42:448–454.
Current Opinion in Endocrine and Metabolic Research 2019, 8:167–173