Human pathology
September 22, 2026 · via Europe PMC
Clinical utilization of CYP17A1 and CYP11B2 in evaluating cortisol- and aldosterone-producing adrenal nodules.
Sarmadian PJ, Baraban EG, Lotan TL, +7 more, Li H.
AI summary — for doctors, generated from the abstract only
A study found that a specific immunohistochemistry stain (CYP17A1), when combined with an existing classification system, can help identify adrenal nodules that are secretly producing excess cortisol alongside aldosterone, but cautioned that this stain can be misleading in more typical cases and should not be used alone to assess cortisol production.
What was studied
A study investigating the clinical utility of CYP17A1 immunohistochemistry, combined with the established mHISTALDO classification system, for distinguishing cortisol-producing from aldosterone-producing adrenal nodules across patients with mild autonomous cortisol secretion only, primary aldosteronism only, or both conditions combined.
Key findings
- Normal adrenal tissue and non-functioning adrenal tumors showed expected, predictable CYP17A1 staining patterns, while adrenal nodules with mild autonomous cortisol secretion showed diffuse, mostly strong staining (though not exceeding background levels).
- In patients with both primary aldosteronism and mild cortisol secretion, nodules showed unusual ('non-classical') staining patterns, were positive for CYP17A1 but negative for the aldosterone marker CYP11B2, and showed no overlap between the two markers — findings that may provide supportive evidence for cortisol co-secretion in these specific patients.
- In contrast, patients with primary aldosteronism alone (without cortisol overproduction) showed 'classical' staining patterns with variable CYP17A1 positivity overlapping with the aldosterone marker in all cases, despite having no actual excess cortisol production, meaning CYP17A1 positivity in this classical pattern should not be misinterpreted as evidence of cortisol overproduction.
Clinical relevance
The findings suggest that combining CYP17A1 staining with the established classification system could provide a helpful diagnostic adjunct for identifying aldosterone-producing adrenal nodules that may also secretly be producing excess cortisol (which carries additional health risks and surgical considerations like postoperative adrenal insufficiency), but caution that CYP17A1 positivity in classical staining patterns should not be mistaken as evidence of cortisol overproduction without clinical and biochemical confirmation.
Who should care
Limitations
The authors explicitly describe these findings as preliminary and hypothesis-generating, requiring validation in larger, independent patient cohorts before being adopted into routine clinical practice.
A specific immunohistochemistry stain, when combined with an existing adrenal nodule classification system, may help identify hidden cortisol co-secretion in aldosterone-producing adrenal tumors, but the authors caution this preliminary finding needs further validation and should not be used alone to assess cortisol production.
This is an AI-generated summary of the published abstract, not a clinical recommendation. It may not reflect the full text or subsequent updates — verify against the original source before acting on it.
Abstract
Mild autonomous cortisol secretion (MACS) has been increasingly recognized as a risk factor for cardiometabolic comorbidities and increased mortality. While CYP11B2 immunohistochemistry (IHC) based HISTALDO classification is well established for evaluating primary aldosteronism (PA), the clinical utility of CYP17A1 IHC in assessing cortisol- and aldosterone-producing adrenal nodules remains underexplored. We investigated the clinical utility of CYP17A1 IHC, in combination with mHISTALDO patterns, to distinguish cortisol-producing adrenal lesions across a spectrum of adrenal pathologies, focusing on patients with MACS only, PA only, and PA + MACS. As expected, normal adrenal cortex demonstrated diffuse, strong (3+) CYP17A1 expression in the zona fasciculata and zona reticularis, whereas markedly reduced CYP17A1 was seen in secondary adrenal atrophy. Non-functional adenomas showed patchy, weak CYP17A1 expression, while functioning adrenocortical carcinomas demonstrated marked intratumoral heterogeneity with loss of zonation. MACS adenomas showed diffuse (≥90%) CYP17A1 labeling, predominantly of strong intensity, though not exceeding that of the background cortex. Non-classical mHISTALDO patterns were identified in all PA + MACS patients, in which the adenomas were CYP17A1-positive and CYP11B2-negative. No overlapping labeling of CYP17A1 and CYP11B2 was observed in MACS and PA + MACS. In contrast, classical mHISTALDO patterns were present in all PA-only patients, with variable colocalization of CYP17A1 positivity in all CYP11B2-positive adenomas, without autonomous cortisol secretion. The colocalization ranged from small focal to diffuse, with weak to strong CYP17A1 intensity. The lack of hypercortisolism in PA-only patients argued against the cortisol-producing action of CYP17A1 in classical mHISTALDO. In summary, diffuse CYP17A1 expression was associated with adrenal nodules in MACS and in PA + MACS with non-classical patterns, and may provide supportive histologic evidence for lesions associated with cortisol co-secretion. In patients with classical patterns, CYP17A1 positivity in CYP11B2-positive adenomas may be misleading and should not be interpreted as evidence of cortisol overproduction. The combined use of CYP17A1 IHC and the mHISTALDO classification in PA patients may provide a diagnostic adjunct for identifying lesions with potential hormone co-secretion; however, clinical and biochemical correlation is essential in determining functional impact. In patients with PA, a non-classical mHISTALDO pattern and a CYP17A1-positive, CYP11B2-negative nodule may warrant additional evaluation for cortisol co-secretion and consideration of postoperative adrenal insufficiency. Our findings are preliminary, hypothesis-generating, and require validation in larger, independent cohorts.
DOI
10.1016/j.humpath.2026.106272
PMID
42772699
Research metadata (titles, abstracts, authors, publication dates) is sourced from Europe PMC, which aggregates content from PubMed/MEDLINE, PubMed Central, and other providers under the U.S. National Library of Medicine (NLM/NCBI). NLM does not claim copyright on abstracts; the original journal publishers or authors may hold rights to the full articles. AI-generated summaries are derived only from the abstract, never the full text, and are always labeled as AI-generated.
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