The Potential of Steroid Profiling by Mass Spectrometry in the Management of Adrenocortical Carcinoma

An untargeted metabolomics approach to evaluate enzymatically deconjugated steroids and intact steroid conjugates in urine as diagnostic biomarkers for adrenal tumors

OBJECTIVES

Urinary steroid profiling after hydrolysis of conjugates is an emerging tool to differentiate aggressive adrenocortical carcinomas (ACC) from benign adrenocortical adenomas (ACA). However, the shortcomings of deconjugation are the lack of standardized and fully validated hydrolysis protocols and the loss of information about the originally conjugated form of the steroids. This study aimed to evaluate the quality of the deconjugation process and investigate novel diagnostic biomarkers in urine without enzymatic hydrolysis.

METHODS

24 h urine samples from 40 patients with ACC and 40 patients with ACA were analyzed by untargeted metabolomics using liquid chromatography-high-resolution mass spectrometry both unmodified and after hydrolysis with arylsulfatase/glucuronidase from Helix pomatia. Both approaches were compared regarding the differentiation of ACC vs. ACA via ROC analyses and to evaluate the hydrolyzation efficiency of steroid conjugates.

RESULTS

Steroid glucuronides were fully deconjugated, while some disulfates and all monosulfates were still largely detectable after enzymatic hydrolysis, suggesting incomplete and variable deconjugation. In unhydrolyzed urine, steroid monosulfates showed the best differentiation between ACC and ACA (highest AUC=0.983 for C21H32O6S, followed by its isomer and two isomers with the molecular formula C21H32O7S). Moreover, several disulfates were highly abundant and increased in ACC compared to ACA.

CONCLUSIONS

This work highlights the limitations of hydrolyzing steroid conjugates before analysis and shows a possible superiority of a direct analysis approach compared to a hydrolysis approach from a methodological point of view and regarding diagnostic accuracy. Several steroid conjugates were found as promising diagnostic biomarkers for differentiation between ACC and ACA.

Unmasking primary aldosteronism: Transforming disease management with advanced steroid profiling

Primary aldosteronism (PA) is traditionally thought to result from the overproduction of aldosterone which is unregulated by the renin-angiotensin system. It leads to a significantly increased risk of cardiovascular and metabolic complications as compared to primary hypertension. However, approximately one-third of patients diagnosed with PA according to the traditional guidelines have been found to exhibit low aldosterone levels and other steroid hormones may also play a potentially critical role in PA development. Early diagnosis of PA remains challenging due to low screening rates and the complex diagnostic procedures. The need for invasive adrenal vein sampling for PA subtyping also leads to a dilemma in therapeutic strategy selection. With advances in techniques, an increasing number of steroid hormones have been discovered to be associated with PA, potentially optimizing the PA diagnostic procedures. Herein, we review the cutting-edge advances in steroid hormones, including aberrant hormone synthesis and metabolism related to the pathophysiological development of PA, quantitative assays, and potential clinical value. Mass spectrometry provides a robust technical foundation for the simultaneous profiling of a panel of steroid hormones. Steroid hormone profiling combined with machine learning algorithms holds great research promise for facilitating early diagnosis and minimally invasive subtyping of PA. Thus, current progress and future expectations in combining steroid hormones with advanced technologies for early disease diagnosis and management are also reviewed. Research Agenda. 1) Identify changes in steroid hormones and the underlying biochemical mechanisms associated with PA. 2) Investigate the role of advanced mass spectrometry techniques in steroid hormone profiling. 3) Discuss current advances and future expectations in combining machine learning algorithms with MS-based steroid hormone profiling for PA's systematic and practical management.

Steroid profiling in adrenal disease

The measurement of steroid hormones in blood and urine, which reflects steroid biosynthesis and metabolism, has been recognized as a valuable tool for identifying and distinguishing steroidogenic disorders. The application of mass spectrometry enables the reliable and simultaneous analysis of large panels of steroids, ushering in a new era for diagnosing adrenal diseases. However, the interpretation of complex hormone results necessitates the expertise and experience of skilled clinicians. In this scenario, machine learning techniques are gaining worldwide attention within healthcare fields. The clinical values of combining mass spectrometry-based steroid profiles analysis with machine learning models, also known as steroid metabolomics, have been investigated for identifying and discriminating adrenal disorders such as adrenocortical carcinomas, adrenocortical adenomas, and congenital adrenal hyperplasia. This promising approach is expected to lead to enhanced clinical decision-making in the field of adrenal diseases. This review will focus on the clinical performances of steroid profiling, which is measured using mass spectrometry and analyzed by machine learning techniques, in the realm of decision-making for adrenal diseases.

Improved analysis of derivatized steroid hormone isomers using ion mobility-mass spectrometry (IM-MS)

Over the last decade, applications of ion mobility-mass spectrometry (IM-MS) have exploded due primarily to the widespread commercialization of robust instrumentation from several vendors. Unfortunately, the modest resolving power of many of these platforms (~40-60) has precluded routine separation of constitutional and stereochemical isomers. While instrumentation advances have pushed resolving power to >150 in some cases, chemical approaches offer an alternative for increasing resolution with existing IM-MS instrumentation. Herein we explore the utility of two reactions, derivatization by Girard's reagents and 1,1-carbonyldiimidazole (CDI), for improving IM separation of steroid hormone isomers. These reactions are fast (≤30 min), simple (requiring only basic lab equipment/expertise), and low-cost. Notably, these reactions are structurally selective in that they target carbonyl and hydroxyl groups, respectively, which are found in all naturally occurring steroids. Many steroid hormone isomers differ only in the number, location, and/or stereochemistry of these functional groups, allowing these reactions to "amplify" subtle structural differences and improve IM resolution. Our results show that resolution was significantly improved amongst CDI-derivatized isomer groups of hydroxyprogesterone (two-peak resolution of Rpp = 1.10 between 21-OHP and 11B-OHP), deoxycortisone (Rpp = 1.47 between 11-DHC and 21-DOC), and desoximetasone (Rpp = 1.98 between desoximetasone and fluocortolone). Moreover, characteristic collision cross section (DTCCSN2) measurements can be used to increase confidence in the identification of these compounds in complex biological mixtures. To demonstrate the feasibility of analyzing the derivatized steroids in complex biological matrixes, the reactions were performed following steroid extraction from urine and yielded similar results. Additionally, we applied a software-based approach (high-resolution demultiplexing) that further improved the resolving power (>150). Overall, our results suggest that targeted derivatization reactions coupled with IM-MS can significantly improve the resolution of challenging isomer groups, allowing for more accurate and efficient analysis of complex mixtures.

Recent Updates on the Management of Adrenal Incidentalomas

Adrenal incidentalomas represent an increasingly common clinical conundrum with significant implications for patients. The revised 2023 European Society of Endocrinology (ESE) guideline incorporates cutting-edge evidence for managing adrenal incidentalomas. This paper provides a concise review of the updated contents of the revised guideline. In the 2023 guideline, in patients without signs and symptoms of overt Cushing's syndrome, a post-dexamethasone cortisol level above 50 nmol/L (>1.8 μg/dL) should be considered as mild autonomous cortisol secretion. Regarding the criteria of benign adrenal adenomas, a homogeneous adrenal mass with ≤10 Hounsfield units on non-contrast computed tomography requires no further follow-up, irrespective of its size. The updated guideline also discusses steroid metabolomics using tandem mass spectrometry to discriminate malignancy. It underscores the importance of high-volume surgeons performing adrenalectomy and emphasizes the pivotal role of a multidisciplinary team approach in deciding the treatment plan for indeterminate adrenal masses. The guideline advocates for more proactive surgical treatment for indeterminate adrenal masses in young patients (<40 years) and pregnant women. This review of the 2023 ESE guideline underscores the ongoing evolution of the adrenal incidentaloma management landscape, emphasizing the need for further research and adaptation of diagnostic and therapeutic strategies.

Applications of spatially resolved omics in the field of endocrine tumors

Endocrine tumors derive from endocrine cells with high heterogeneity in function, structure and embryology, and are characteristic of a marked diversity and tissue heterogeneity. There are still challenges in analyzing the molecular alternations within the heterogeneous microenvironment for endocrine tumors. Recently, several proteomic, lipidomic and metabolomic platforms have been applied to the analysis of endocrine tumors to explore the cellular and molecular mechanisms of tumor genesis, progression and metastasis. In this review, we provide a comprehensive overview of spatially resolved proteomics, lipidomics and metabolomics guided by mass spectrometry imaging and spatially resolved microproteomics directed by microextraction and tandem mass spectrometry. In this regard, we will discuss different mass spectrometry imaging techniques, including secondary ion mass spectrometry, matrix-assisted laser desorption/ionization and desorption electrospray ionization. Additionally, we will highlight microextraction approaches such as laser capture microdissection and liquid microjunction extraction. With these methods, proteins can be extracted precisely from specific regions of the endocrine tumor. Finally, we compare applications of proteomic, lipidomic and metabolomic platforms in the field of endocrine tumors and outline their potentials in elucidating cellular and molecular processes involved in endocrine tumors.

Was It an Adrenocortical Adenoma or an Adrenocortical Carcinoma? Limitation of the Weiss Scoring System in Determining the Malignant Potential of Adrenocortical Tumor: Report on Two Cases

Background

Adrenocortical carcinoma (ACC) is a rare endocrine malignancy. An accurate diagnosis of ACC is of paramount importance as it greatly impacts the management and prognosis of a patient. However, the differentiation between early stage, low-grade ACC and adrenocortical adenoma (ACA) may not always be straightforward. The recommended classification system, namely, the Weiss scoring system, is not without flaws. We herein report two cases of ACC which were initially diagnosed as ACA according to the Weiss scoring system but developed distant metastases in subsequent years. Case Presentation. Case 1: A 60-year-old Chinese woman presented with a recent onset of worsening of blood pressure control and clinical features of Cushing's syndrome. Investigations confirmed ACTH-independent endogenous hypercortisolism, and a CT abdomen showed a 6 cm right adrenal mass. Twenty-four-hour urine steroid profiling revealed co-secretion of adrenal androgens and atypical steroid metabolites. Laparoscopic right adrenalectomy was performed, and pathology of the tumor was classified as an ACA by the Weiss scoring system. Four years later, the patient presented with an abrupt onset of severe hypercortisolism and was found to have a metastatic recurrence in the liver and peritoneum. The patient received a combination of mitotane, systemic chemotherapy, and palliative debulking surgery and succumbed 8.5 years after the initial presentation due to respiratory failure with extensive pulmonary metastases. Case 2: A 68-year-old Chinese woman presented with acute bilateral pulmonary embolism and was found to have a 3 cm left adrenal mass. Hormonal workup confirmed ACTH-independent endogenous hypercortisolism, and laparoscopic left adrenalectomy revealed an ACA according to the Weiss scoring system. Five years later, she presented with recurrent hypercortisolism due to hepatic and peritoneal metastases. The patient had progressive disease despite mitotane therapy and succumbed 7 years after initial presentation.

Conclusions

Although the Weiss scoring system is recommended as the reference pathological classification system to diagnose adrenocortical carcinoma, there remain tumors of borderline malignant potential which may escape accurate classification. Various alternative classification systems and algorithms exist but none are proven to be perfect. Clinicians should recognize the potential limitation of these histological criteria and scoring systems and incorporate other clinical parameters, such as the pattern of hormonal secretion, urinary steroid profiling, and radiographic features, to improve the prognostication and surveillance strategy of these tumors.

Urine steroid profile as a new promising tool for the evaluation of adrenal tumors. Literature review

PURPOSE

To review the literature assessing the diagnostic performance of urinary steroid profiling (USP) by high-performance liquid chromatography (LC-MS) or gas chromatography (GC) coupled to mass spectrometry (MS) in the evaluation of adrenal lesions, both in terms of functionality and malignancy.

RESULTS

The evaluation of adrenal incidentalomas (AI) aims to rule out malignancy and hormone excess. Current diagnostic protocols have several limitations and include time consuming and relatively complicated multi-step processes in most cases. On the contrary, USP by LC-MS/MS or LC-GC/MS offer an easy, comprehensive and non-invasive assessment of adrenal steroid secretion. USP complements current workups used in the evaluation of AIs by improving our ability to identify malignancy and/or autonomous hormone secretion.

CONCLUSIONS

Urine steroid profiling by LC-MS/MS and GC-MS allows a thorough, non-invasive, assessment of adrenal steroidogenesis as a whole which complement the current evaluation of AIs, and holds a promising role in the diagnosis of autonomous cortisol secretion, primary aldosteronism, and adrenal malignancy.

The Role of Biomarkers in Adrenocortical Carcinoma: A Review of Current Evidence and Future Perspectives

Adrenocortical carcinoma (ACC) is a rare endocrine malignancy arising from the adrenal cortex often with unexpected biological behavior. It can occur at any age, with two peaks of incidence: in the first and between fifth and seventh decades of life. Although ACC are mostly hormonally active, precursors and metabolites, rather than end products of steroidogenesis are produced by dedifferentiated and immature malignant cells. Distinguishing the etiology of adrenal mass, between benign adenomas, which are quite frequent in general population, and malignant carcinomas with dismal prognosis is often unfeasible. Even after pathohistological analysis, diagnosis of adrenocortical carcinomas is not always straightforward and represents a great challenge for experienced and multidisciplinary expert teams. No single imaging method, hormonal work-up or immunohistochemical labelling can definitively prove the diagnosis of ACC. Over several decades' great efforts have been made in finding novel reliable and available diagnostic and prognostic factors including steroid metabolome profiling or target gene identification. Despite these achievements, the 5-year mortality rate still accounts for approximately 75% to 90%, ACC is frequently diagnosed in advanced stages and therapeutic options are unfortunately limited. Therefore, imperative is to identify new biological markers that can predict patient prognosis and provide new therapeutic options.