CXCR4 serves as a new pathological biomarker for cortisol-producing adenomas

CXCR4 serves as a new pathological biomarker for cortisol-producing adenomas | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article CXCR4 serves as a new pathological biomarker for cortisol-producing adenomas Xinyue Yang, Yi Yang, Jiayu Li, Wenwen Li, Yue Wang, Chunxue He, and 9 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8269823/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Cortisol-producing adenomas (CPA) lack specific pathological markers. This study aims to investigate the expression levels and diagnostic value of CXC chemokine receptor 4 (CXCR4), 11β-hydroxylase (CYP11B1), and aldosterone synthase (CYP11B2) for CPA. We retrospectively included 25 non-functional adrenocortical adenomas (NACA) and 102 functional adrenocortical adenomas (FACA), which comprising 45 CPAs and 57 aldosterone-producing adenomas (APA). Immunohistochemical staining of CXCR4, CYP11B1 and CYP11B2 was performed and quantified by the H-score system. Receiver operating characteristic (ROC) curve analysis was applied to evaluate the diagnostic performance. CXCR4 H-score was significantly higher in FACA compared to NACA (78 vs. 7, P < 0.001). CYP11B1 H-score was significantly higher in CPA than APA (109 vs. 28; P < 0.001), but was not significantly different between CPA and NACA (109 vs. 81, P = 0.202). Notably, CYP11B2 H-score in APA was significantly higher compared to both CPA and NACA. Area under the ROC curve (AUC) of CXCR4 for distinguishing NACA from FACA was 0.982, with an optimal cutoff value of CXCR4 > 18. In FACA group, CYP11B2 demonstrated higher AUC in differentiating CPA from APA compared to CYP11B1 (1.000 vs. 0.782), with an optimal cutoff of CYP11B2 > 76. A dual-marker strategy (CXCR4 > 18 + CYP11B2 ≤ 76) for distinguishing CPA from other adrenocortical adenomas achieved an AUC of 0.983, with a sensitivity of 97.78% and a specificity of 93.90%. Thus, CXCR4 could effectively discriminates FACA from NACA. A dual-marker strategy combined CXCR4 and CYP11B2 represents a promising novel approach for CPA pathological diagnosis. Adrenocortical adenoma cortisol-producing adenoma CXC chemokine receptor 4 11β-hydroxylase aldosterone synthase Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction The widespread use of advanced imaging techniques has led to a significant increase in the detection rate of adrenocortical adenomas (ACA). Retrospective studies indicate a ten-fold rise in the detection rate of ACA between 1995 and 2017 [1] . A cross-sectional study based on a Chinese community population demonstrated that the prevalence of ACA among adults is approximately 1.4% [2] . ACA is classified as either non-functional or functional based on their hormone secretion status. Non-functional ACA (NACA) represents the majority of cases, comprising 50-85% of all ACA [2-4] . Based on their endocrine profiles, functional ACA (FACA) can be further categorized into aldosterone-producing adenomas (APA) and cortisol-producing adenomas (CPA). Post-operative histopathological evaluation of adrenal tissue remains essential for determining the pathological type of ACA, guiding treatment decisions, and prognostic evaluation. However, conventional morphological assessment fails to provide functional characterization. The steroidogenic enzymes 11β-hydroxylase (CYP11B1) and aldosterone synthase (CYP11B2) represent the rate-limiting enzymes in cortisol and aldosterone biosynthesis pathways, respectively. Recent studies have demonstrated that CYP11B2 immunohistochemical staining serves as a valuable pathological marker for both localizing aldosterone-producing lesions and histopathological classification in unilateral primary aldosteronism (UPA), which facilitating differentiate APA from other ACAs [5,6] . Although elevated CYP11B1 expression has been observed in CPA compared to adjacent adrenal tissue, it is also expressed in NACA at varying levels [7,8] . Therefore, reliable pathological markers for CPA are still lacking. CXC chemokine receptor type 4 (CXCR4), a G protein-coupled receptor with seven transmembrane domains, is widely expressed across various tissues and plays crucial roles in numerous physiological and pathological processes [9] .Heinze B et al. conducted a comprehensive analysis of 117 APAs, 54 CPAs, and 49 nonfunctioning adenomas (NFA), revealing distinct CXCR4 expression profiles: high expression of CXCR4 was observed in 71% of APAs and 26% of CPAs, compared to only 4% of NFAs [10] . However, the potential utility of CXCR4 as a pathological marker for differentiating CPA from other ACAs remains uncertain. This study aims to systematically evaluate the immunohistochemical expression levels of CXCR4, CYP11B1 and CYP11B2 in APA, CPA, and NACA, and to explore the diagnostic efficacy of these pathological markers for the diagnosis of CPA. Methods Study design and participants This study retrospectively enrolled 127 patients with various ACA subtypes who underwent adrenal surgery at the First Affiliated Hospital of Chongqing Medical University from January 2019 to September 2024, based on data from the CONPASS (Chongqing Primary Aldosteronism Study) and CONACSS (Cohort Study of Adrenogenic Autonomic Cortisol Secretion) databases. The cohort included 25 cases of NACA, 45 cases of CPA, and 57 cases of APA. The study was approved by the Ethics Committee of the First Affiliated Hospital of Chongqing Medical University, and all participants in both CONPASS and CONACSS provided written informed consent. The diagnosis of APA required fulfillment of all the following criteria [ 6 , 11 ] : (1) A positive screening test for primary aldosteronism (defined as a morning upright plasma aldosterone-to-renin ratio [ARR] > 20 pg·mL⁻¹/mIU·L⁻¹ ) combined with at least one positive confirmatory test (intravenous saline infusion test: plasma aldosterone concentration (PAC) post-test > 80 pg/mL; captopril challenge test: PAC post-test > 110 pg/mL [ 12 ] ), or meeting criteria for confirmatory test exemption (PAC > 200 pg/mL, plasma renin concentration (PRC) < 2.5 µIU/mL, and conccurent with hypokalemia) [ 13 ] ; (2) 1 mg dexamethasone suppression test (DST) with serum cortisol < 50 nmol/L at 8 a.m.; (3) Adrenal CT demonstrating a unilateral adrenal nodule; (4) Pathological confirmation of adrenocortical adenoma or nodule with positive CYP11B2 immunohistochemical staining; (5) Postoperative complete biochemical remission according to Primary Aldosteronism Surgical Outcome (PASO) criteria [ 14 ] . The diagnosis of CPA required fulfillment of the following criteria [ 15 ] : (1) Abnormal 1 mg DST with serum cortisol > 50 nmol/L at 8 a.m. with 24-hour urinary cortisol exceeding the upper limit of normal; (2) morning plasma adrenocorticotropic hormone (ACTH) 20 pg·mL⁻¹/mIU·L⁻¹ with post-saline infusion test plasma aldosterone < 60 pg/mL; (4) Unilateral adrenal nodule on adrenal CT; (5) Pathological confirmation of adrenocortical adenoma; and (6) postoperative serum cortisol < 50 nmol/L after 1 mg DST. The diagnosis of NACA was established based on the following criteria [ 16 ] : (1) Imaging evidence of unilateral adrenal nodule; (2) Normal biochemical profile, including ARR ≤ 20 pg·mL⁻¹/mIU·L⁻¹ (or ARR > 20 with post-saline infusion aldosterone < 60 pg/mL), 1 mg DST serum cortisol < 50 nmol/L at 8 a.m., and negative for catecholamine metabolites; (3) Postoperative histopathological confirmation of adrenocortical adenoma. Surgical intervention was indicated for patients with large tumor size or strong surgical desire. Immunohistochemistry Immunohistochemical staining for CXCR4, CYP11B1, and CYP11B2 was performed following established protocols [ 17 ] . Adrenal tissue specimens were fixed in 4% paraformaldehyde, paraffin-embedded, and sectioned at 6µm thickness. Following deparaffinization and hydrogen peroxide treatment, antigen retrieval was performed using citrate buffer (pH = 6.0). Tissue sections were incubated overnight at 4 ℃ with primary antibodies: including rabbit anti-human CXCR4 (abcam, ab124824), rat anti-human CYP11B1 (1:500; Millipore, MABS502), and mouse anti-human CYP11B2 (1: 200; Millipore, MABS1251). After incubation with biotinylated secondary antibodies for 60 minutes at room temperature, sections were treatmented with DAB and counterstained with hematoxylin, followed by dehydration and mounting. The positive control for CXCR4 immunohistochemical staining was the tissue section of human cervical cancer (refer to the antibody manual). Aldosterone-producing micronodule in adrenal tissue was used as the positive control for CYP11B2 immunohistochemical staining. Adrenal Zona fascicularis was used as the positive control for CYP11B1 immunohistochemical staining, and staining without primary antibody was used as the negative control. H- score analysis The scoring method refers to previously published studies [ 17 ] . Stained sections were subjected to image acquisition using the VS200 Research-grade whole-slide scanning system (Olympus). Quantitative H-score analysis was performed by randomly capturing 10 high-power fields per section. Staining intensity was graded as: 0 (negative), 1 (The cytoplasm of tumor parenchymal cells expresses faint but visible brown-yellow staining), 2 (The cytoplasm of tumor parenchymal cells expressed obvious brown-yellow staining), or 3 (The cytoplasm of tumor parenchymal cells expressed brown staining). The proportion of cells corresponding to different staining intensity was also quantified. The final H-score is the staining intensity multiplied by the percentage of cells with the corresponding staining intensity and summed. The total score corresponds to the strength of the immunohistochemical staining. The H-score analysis was carried out independently by two researchers who were blinded to the final clinical diagnosis of all cases studied. A third researcher would review the score when there was an inconsistency between the two researchers. Biochemical measurements The automated chemiluminescence immunoassay was used to measure PRC and PAC (LIAISON, DiaSorin, Italy), and serum cortisol and ACTH levels (DXI800, Beckman, America). The intra-assay and inter-assay coefficients of variation for PRC ranged from 1.2 to 3.7% and from 2.9 to 12.8%, respectively. The analytical sensitivity (lower detection limit) for PRC was 0.53 mIU/L, with a functional sensitivity of 1.60 mIU/L. The PAC assay had a measurement range of 2.2–100 ng/dL (analytical sensitivity), with a functional sensitivity of 3.0 ng/dL. The intra-assay coefficient of variation for PAC was from 2.4 to 4.8% and the inter-assay coefficient of variation was from 4.4 to 6.7%. The cortisol assay has a measuring range from 11 nmol/L (analytical sensitivity) to 1655 nmol/L. High-performance liquid chromatography-tandem mass spectrometry (LC-MS/MS) was used to measure MNs (AB SCIEX Triple Quad™ 4500MD). The measurement ranges were 12.0-900.0 pg/mL for MN and 23.04–1728.0 pg/mL for NMN, with all correlation coefficients (R) > 0.995. The recovery rates ranged from 91.8% to 114% for MN and 85.3% to 105.0% for NMN, with relative standard deviations (RSD) < 10.6%. The inter-assay and intra-assay coefficients of variation for MN and NMN were both < 15%. Statistical analysis Statistical analysis was performed using SPSS 29.0, MedCalc for Receiver operating characteristic (ROC) curve generation, and GraphPad Prism 8.0 for graphical presentation. Data distribution was assessed using the Kolmogorov-Smirnov test. Normally distributed continuous variables were expressed as mean ± standard deviation and compared by using t-tests, while non-normally distributed variables were presented as median (interquartile range) and analyzed with non-parametric tests. Categorical variables were described as frequencies (percentages) and analyzed by using Chi-square or Fisher's exact tests (for 2×2 tables with n < 40 or expected values < 5). All tests were two-tailed, with statistical significance set at P < 0.05. Results Clinical and biochemical characteristics of patients The clinical and biochemical characteristics of the 127 ACA patients included in this study were presented in Table 1 . Compared with the CPA group, the NACA group showed a significantly lower incidence of hypokalemia and shorter duration of hypertension (P < 0.05), while the APA group exhibited significantly higher levels in these two parameters (P < 0.05). The systolic blood pressure (SBP) and diastolic blood pressure (DBP) in the CPA group were significantly higher than those in the NACA group (P < 0.05), but no significant differences were noted between the CPA and APA group (SBP: 147.27 ± 19.77 mmHg vs. 150.46 ± 16.55 mmHg, P = 0.38; DBP: 93.27 ± 16.81 mmHg vs. 98.07 ± 10.67 mmHg, P = 0.10). The ARR in the CPA group showed no significant difference compared to the NACA group (P = 0.22), but it was significant lower than that in the APA group (P < 0.001). Additionally, both the cortisol levels at 8 a.m. and post-1mg DST cortisol levels in the CPA group were significantly higher than those in the NACA and APA groups. Conversely, the ACTH levels at 8 a.m. in the CPA group were markedly lower than those observed in both the NACA and APA groups. Table 1 Clinical and biochemical characteristics of patients with ACAs NACA(n = 25) CPA(n = 45) APA(n = 57) Male (n/%) 12/48 6/13* 22/38 # Age (year) 51.3 ± 11.1 44.8 ± 11.8* 47.8 ± 11.5 History of hypokalemia (%) 4 47* 89* # Duration of HT (year) 0.00(0.00,2.00) 2.00(0.08,5.00)* 6.00(2.00,10.00)* # BMI (kg/m 2 ) 26.14 ± 3.64 25.40 ± 3.04 24.45 ± 3.04* SBP (mmHg) 126.92 ± 19.07 147.27 ± 19.77* 150.46 ± 16.55* DBP (mmHg) 79.40 ± 11.70 93.27 ± 16.81* 98.07 ± 10.67* Serum Potassuim (mmol/L) 4.01 ± 0.36 3.43 ± 0.53* 2.78 ± 0.58* # ARR (pg·mL − 1 /mIU·L − 1 ) 6.22(3.37,10.61) 8.05(3.93,19.11) 106.40(45.92,269.03)* # Cortisol at 8am. (nmol/L) 302.20(250.20,395.37) 496.57(329.15,598.91)* 295.20(213.63,383.41) # ACTH at 8am. (pg/mL) 23.48(13.99,32.07) 3.98(1.52,9.60)* 24.36(16.59,38.65) # Cortisol post 1mg DST (nmol/L) 24.19(17.71,30.48) 478.32(130.50,579.49)* 23.40(18.42,34.57) # MN (ng/L) 98.60(45.70,108.70) 48.40(21.00,101.05)* 28.10(22.20,74.10)* Data were expressed as mean ± SD or median (interquartile range) and number of patients. Abbreviations, HT: hypertension, BMI: body mass index, SBP: systolic blood pressure, DBP: diastolic blood pressure, ARR: aldosterone to rennin ratio, ACTH: adrenocorticotropic hormone, DST: dexamethasone suppression test, MN: Metanephrine, NACA: non-functional adrenocortical adenoma, CPA: cortisol-producing adenoma, APA: aldosterone-producing adenoma. *significantly different from NACA group (P < 0.05). # significantly different from CPA group (P < 0.05) Immunohistochemical findings of studied cases Representative immunohistochemical staining results for CXCR4, CYP11B1, and CYP11B2 in each ACA groups were shown in Fig. 1 . We quantitatively assessed the immunohistochemical staining of CXCR4, CYP11B1 and CYP11B2 using the H-score system in all study subjects (Fig. 2 ). The FACA groups (comprising CPA and APA) showed significantly elevated CXCR4 H-scores compared to the NACA group (CPA vs NACA: median 65 vs 7, P < 0.001; APA vs NACA: median 85 vs 7, P < 0.001) (Fig. 2 a). The CPA group exhibited significantly higher CYP11B1 H-scores compared to the APA group (median values: 109 vs 28, P < 0.001), while no statistically significant difference was observed between CPA and NACA groups (median values: 109 vs 81, P = 0.202) (Fig. 2 b). Notably, the H-score of CYP11B2 in APA group were approximately 24-fold and 71-fold greater than those of the CPA and NACA groups, respectively (Fig. 2 c). Diagnostic accuracy of the H-score of CXCR4 and CYP11B1/2 in ACAs ROC curve analysis showed that the area under the ROC curve (AUC) for distinguishing NACA from FACA by the H-score of CXCR4 was 0.982 (95% CI: 0.941–0.997)(Fig. 3 a). The optimal H-score cutoff value of CXCR4 for diagnosis of FACA was > 18, yielding a sensitivity of 99.02% (95% CI: 94.7%-100.0%) and specificity of 92.00% (95% CI: 74.0%-99.0%) at maximum Youden index. Furthermore, we evaluated the diagnostic performance of CYP11B1 and CYP11B2 in discriminating CPA from APA. The AUC for differentiating these two FACA subtypes using the H-score of CYP11B2 was significantly higher than that of CYP11B1 (1.000 [95% CI: 0.964-1.000] vs 0.782 [95% CI: 0.689–0.858], P < 0.001) (Fig. 3 c and 3 b). At the optimal cutoff (H-score ≤ 76), CYP11B2 demonstrated a sensitivity of 98.25% [95% CI: 90.6%-100.0%] and a specificity of 100.0% [95% CI: 92.1%-100.0%]) for diagnosis of CPA, determined by maximal Youden index. The efficacy of CXCR4 combined with CYP11B1/2 in diagnosing CPA Based on the above results, a dual-marker strategy using CXCR4 and CYP11B2 for the diagnosis of CPA was established (Fig. 4 ). The first step involved utilizing CXCR4 to differentiate NACA from FACA: a positive CXCR4 expression (defined as the H-score > 18) indicated a diagnosis of FACA. The second step, following confirmation of FACA, further classified the functional subtypes via CYP11B2: CPA was diagnosed when CYP11B2-negative (defined as the H-score ≤ 76) and APA was verified when CYP11B2-positive (H-score > 76). The AUC was 0.983, with a sensitivity of 97.78% (95% CI: 88.2%-99.9%) and a specificity of 93.90% (95% CI: 86.3%-98.0%) when diagnosing CPA using CXCR4 combined with CYP11B2. When CPA was diagnosed using CXCR4 combined with CYP11B1, the model showed an AUC of only 0.728, with a sensitivity of 77.78% (95% CI: 62.9%-88.8%) and a specificity of 67.07% (95% CI: 55.8%-77.1%). Furthermore, when diagnosis of CPA was made using CXCR4 combined with CYP11B2, the addition of CYP11B1 did not further improve diagnostic accuracy (AUC = 0.983). Discussion In this study, we investigated the expression levels of CXCR4 and CYP11B1/2 in adrenal tissues among 127 patients with different types of ACA, and explored the diagnostic efficacy of CXCR4 combined with CYP11B2 for the diagnosis of CPA. We found that CXCR4 was highly expressed in FACA (APA and CPA), and the quantitative H-score of CXCR4 could effectively distinguish NACA from FACA. Furthermore, the two types of FACA (CPA and APA) could be differentiated by CYP11B2 staining. Based on these results, we proposed a dual-marker strategy of using CXCR4 in combination with CYP11B2 for the diagnosis of CPA. Our findings enriched the understanding of CXCR4 expression patterns in ACAs, and provided new insights into the pathological diagnosis of CPA. Currently, conventional morphological assessment struggles to achieve functional diagnosis of ACAs, and accurate functional typing of ACA still relies on specific pathological markers. CYP11B1 and CYP11B2 are key enzymes involved in the synthesis of adrenal cortisol and aldosterone, respectively, among which CYP11B2 is a well-recognized pathological marker for APA [ 6 ] . The present study demonstrated that the APA group exhibited significantly higher CYP11B2 H-scores compared to both CPA and NACA groups. The AUC of CYP11B2 for differentiating APA from CPA achieved 1.000, with a sensitivity of 98.25% and a specificity of 100.00%, suggesting that CYP11B2 is a highly reliable marker for the pathological diagnosis of APA. However, although CYP11B1 is the key enzyme for cortisol synthesis, its expression in adrenal lesions of patients with hypercortisolism often shows no significant upregulation compared to normal adrenal tissue. This phenomenon may be attributed to two factors: first, normal adrenal glands exhibit a certain baseline level of CYP11B1 expression; second, zona fasciculata cells are widely distributed within the adrenal glands. Consequently, even a mild upregulation of CYP11B1 expression could result in a substantial increase in cortisol synthesis [ 18 – 20 ] . Previous studies have reported that APA and NACA also express CYP11B1 to varying degrees, which consequently limits its diagnostic utility for distinguishing CPA from other ACA subtypes [ 17 , 20 , 21 ] . Our study similarly indicate that CYP11B1 expression is detectable across NACA, CPA and APA subtypes, exhibiting limited diagnostic specificity and suboptimal discriminatory performance (AUC = 0.782). Consequently, for CYP11B2-negative ACAs, additional biomarkers are required to reliably differentiate between CPA and NACA. CXCR4, a widely expressed G protein-coupled receptor, plays crucial roles in diverse physiological and pathological processes, including embryogenesis, cell migration, organ vascularization, immunity, tumorigenesis, and inflammation [ 22 ] . Previous studies have investigated the expression profile of CXCR4 in ACAs. Heinze B et al. conducted a comprehensive analysis of 117 APAs, 54 CPAs, and 49 NFAs, revealing distinct CXCR4 expression profiles: high expression was observed in 71% of APAs and 26% of CPAs, compared to only 4% of NFAs [ 10 ] . Ding et al. reported that CXCR4 is expressed in 96% of APA cases (24/25), which is significantly higher than that in NFA [ 23 ] . Another study revealed that 82% out of 62 PA patients exhibited positive CXCR4 expression by using immunohistochemistry [ 24 ] . In recent years, multiple studies have reported the application of CXCR4-targeted radionuclide imaging for APA localization [ 10 , 23 , 25 – 27 ] . Additionally, research by Ding J et al. demonstrated that CXCR4-based radionuclide imaging can fassist in the localization of CPA [ 28 ] . However, it remains unclear whether CXCR4 serves as a valid pathological diagnostic indicator for ACAs. Our study demonstrates significant upregulation of CXCR4 expression in both APA and CPA compared to NACA. We assessed the diagnostic performance of the H-score of CXCR4 for discriminating NACA from FACA through ROC curve analysis, revealing exceptional diagnostic accuracy with an AUC of 0.982, accompanied by a sensitivity of 99.02% and a specificity of 92.00%. These findings indicate that the H-score of CXCR4 serves as an effective pathological marker for distinguishing NACA from FACA. In this study, a dual-marker strategy of using CXCR4 in combination with CYP11B2 was proposed to accurately distinguish the functional status and subtypes of ACAs (Fig. 4 ). The first step involves using CXCR4 for screening the functional status of ACA to differentiate NACA from FACA. The second step, on the basis of confirmed FACA, further classifies the functional subtypes through CYP11B2. Notably, the combined quantitative scoring of CXCR4 and CYP11B2 demonstrated outstanding diagnostic performance in distinguishing CPA from other ACA subtypes (NACA and APA), achieving an AUC of 0.983. These findings suggest that the combination of CXCR4 and CYP11B2 can serve as a pathological diagnostic tool for CPA identification. This study has the following strengths: Firstly, the H-score scoring system was used in this study, which has a clear quantitative standard to improve the accuracy and objectivity of CXCR4 and CYP11B1/2 evaluation. Secondly, this study proposes a novel dual-marker immunohistochemical model combining CXCR4 and CYP11B2 for functional classification and subtyping of ACAs. This approach optimizes the pathological diagnostic workflow for ACAs and provides a new diagnostic paradigm for identifying CPAs. However, certain limitations should also be acknowledged: The retrospective design of the present study may introduce potential selection bias. Meanwhile, the sample size is relatively small, with only 127 patients enrolled. Therefore, the results of this study need to be validated by multi-center prospective cohort studies with larger sample sizes. Conclusions CXCR4 could effectively discriminates FACA from NACA. A dual-marker strategy combined CXCR4 with CYP11B2 represents a promising new route for the pathological diagnosis of CPA. Declarations Acknowledgments We thank other members of the Cohort Study of Adrenogenic Autonomic Cortisol Secretion(CONACSS) Group: Yunfeng He, MD, PhD and Yao Zhang, MD, PhD for suggestions of study design and revision. Funding This work was supported by Chongqing Municipal Collaborative Medical Research Initiative (2025GGXM004, recipient: Qifu Li); Chongqing Technology Innovation and Application Development Special Program (CSTB2024TIAD-KPX0039, recipient: Qifu Li) the National Key Research and Development Project (2022YFC2505300, sub-project 2022YFC2505301, recipient: Qifu Li); the National Natural Science Foundation of China (82100833, recipient: Yi Yang and U21A20355, recipient: Qifu Li); Joint Medical Research Project of Chongqing Science and Technology Commission & Chongqing Health and Family Planning Commission (Major Project, 2022ZDXM003, recipient: Jinbo Hu). The Natural Science Foundation of Chongqing, China (CSTB2025NSCQ-GPX1230, recipient: Yi Yang and CSTB2024NSCQ-MSX0543, recipient: Jiayu Li). Author contributions Conception and design: Qifu Li, Shumin Yang and Jinbo Hu; Analysis and interpretation of the data: Xinyue Yang, Yi Yang, Jiayu Li, Ying Song and Linqiang Ma; Funding acquisition: Qifu Li, Jinbo Hu, Yi Yang and Jiayu Li; Administrative, technical, or logistic support: Jiayu Li, Wenwen Li, Yue Wang and Junlong Li; Acquisition and assembly of data: Xinyue Yang, Chunxue He, Xiangshuang Zhang, Ying Jing and Hang Shen; All authors read and approved the final paper. Competing interests The authors declare that they have no conflict of interest. Ethics approval This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Ethics Committee of the First Affiliated Hospital of Chongqing Medical University. Informed consent Informed consent was obtained from all individual participants included in the study. Data availability Some or all datasets generated during and/or analyzed during the current study are not publicly available but are available from the corresponding author on reasonable request. References A. Ebbehoj, D. Li, R.J. Kaur et al., Epidemiology of adrenal tumours in Olmsted County, Minnesota, USA: a population-based cohort study. The lancet. Diabetes Endocrinol. 8 (11), 894–902 (2020). https://doi.org/10.1016/S2213-8587(20)30314-4 Y. Jing, J. Hu, R. Luo et al., Prevalence and Characteristics of Adrenal Tumors in an Unselected Screening Population: A Cross-Sectional Study. Ann. Intern. Med. 175 (10), 1383–1391 (2022). https://doi.org/10.7326/M22-1619 T. Ichijo, H. Ueshiba, H. Nawata, T. Yanase, A nationwide survey of adrenal incidentalomas in Japan: the first report of clinical and epidemiological features. Endocr. J. 67 (2), 141–152 (2020). https://doi.org/10.1507/endocrj.EJ18-0486 J. Patrova, I. Jarocka, H. Wahrenberg, H. Falhammar, IN ADRENAL INCIDENTALOMA: EXPERIENCE FROM ONE CENTER, (2015) CLINICAL OUTCOMES. Endocrine practice: official journal of the American College of Endocrinology and the American Association of Clinical Endocrinologists, 21(8), 870–877. https://doi.org/10.4158/EP15618.OR K. Nanba, M. Tsuiki, K. Sawai et al., Histopathological diagnosis of primary aldosteronism using CYP11B2 immunohistochemistry. J. Clin. Endocrinol. Metab. 98 (4), 1567–1574 (2013). https://doi.org/10.1210/jc.2012-3726 T.A. Williams, C.E. Gomez-Sanchez, W.E. Rainey et al., International Histopathology Consensus for Unilateral Primary Aldosteronism. J. Clin. Endocrinol. Metab. 106 (1), 42–54 (2021). https://doi.org/10.1210/clinem/dgaa484 M. Kometani, T. Yoneda, M. Demura et al., Cortisol overproduction results from DNA methylation of CYP11B1 in hypercortisolemia. Sci. Rep. 7 (1), 11205 (2017). https://doi.org/10.1038/s41598-017-11435-2 C.H. Ahn, H.Y. Na, S.Y. Park et al., Expression of CYP11B1 and CYP11B2 in adrenal adenoma correlates with clinical characteristics of primary aldosteronism. Clin. Endocrinol. 96 (1), 30–39 (2022). https://doi.org/10.1111/cen.14628 N. Kawaguchi, T.T. Zhang, T. Nakanishi, Involvement of CXCR4 in Normal and Abnormal Development. Cells. 8 (2), 185 (2019). https://doi.org/10.3390/cells8020185 B. Heinze, C.T. Fuss, P. Mulatero et al., (2018) Targeting CXCR4 (CXC Chemokine Receptor Type 4) for Molecular Imaging of Aldosterone-Producing Adenoma. Hypertension (Dallas, Tex.: 1979), 71(2), 317–325. https://doi.org/10.1161/HYPERTENSIONAHA.117.09975 J.W. Funder, R.M. Carey, F. Mantero et al., The Management of Primary Aldosteronism: Case Detection, Diagnosis, and Treatment: An Endocrine Society Clinical Practice Guideline. J. Clin. Endocrinol. Metab. 101 (5), 1889–1916 (2016). https://doi.org/10.1210/jc.2015-4061 Y. Song, S. Yang, W. He et al., (2018) Confirmatory Tests for the Diagnosis of Primary Aldosteronism: A Prospective Diagnostic Accuracy Study. Hypertension (Dallas, Tex.: 1979), 71(1), 118–124. https://doi.org/10.1161/HYPERTENSIONAHA.117.10197 K. Wang, J. Hu, J. Yang et al., Development and Validation of Criteria for Sparing Confirmatory Tests in Diagnosing Primary Aldosteronism. J. Clin. Endocrinol. Metab. 105 (7), dgaa282 (2020). https://doi.org/10.1210/clinem/dgaa282 T.A. Williams, J.W.M. Lenders, P. Mulatero et al., Outcomes after adrenalectomy for unilateral primary aldosteronism: an international consensus on outcome measures and analysis of remission rates in an international cohort. The lancet. Diabetes Endocrinol. 5 (9), 689–699 (2017). https://doi.org/10.1016/S2213-8587(17)30135-3 L.K. Nieman, B.M. Biller, J.W. Findling et al., The diagnosis of Cushing's syndrome: an Endocrine Society Clinical Practice Guideline. J. Clin. Endocrinol. Metab. 93 (5), 1526–1540 (2008). https://doi.org/10.1210/jc.2008-0125 M. Terzolo, A. Stigliano, I. Chiodini et al., AME position statement on adrenal incidentaloma. Eur. J. Endocrinol. 164 (6), 851–870 (2011). https://doi.org/10.1530/EJE-10-1147 Y. Yang, M. Xiao, Y. Song et al., H-score of 11β-hydroxylase and aldosterone synthase in the histopathological diagnosis of adrenocortical tumors. Endocrine. 65 (3), 683–691 (2019). https://doi.org/10.1007/s12020-019-02022-8 U. Enberg, L.O. Farnebo, A. Wedell et al., In vitro release of aldosterone and cortisol in human adrenal adenomas correlates to mRNA expression of steroidogenic enzymes for genes CYP11B2 and CYP17. World J. Surg. 25 (7), 957–966 (2001). https://doi.org/10.1007/s00268-001-0035-2 C.E. Gomez-Sanchez, X. Qi, C. Velarde-Miranda et al., Development of monoclonal antibodies against human CYP11B1 and CYP11B2. Mol. Cell. Endocrinol. 383 (1–2), 111–117 (2014). https://doi.org/10.1016/j.mce.2013.11.022 K. Nishimoto, K. Nakagawa, D. Li et al., Adrenocortical zonation in humans under normal and pathological conditions. J. Clin. Endocrinol. Metab. 95 (5), 2296–2305 (2010). https://doi.org/10.1210/jc.2009-2010 F. Kubota-Nakayama, Y. Nakamura, S. Konosu-Fukaya et al., Expression of steroidogenic enzymes and their transcription factors in cortisol-producing adrenocortical adenomas: immunohistochemical analysis and quantitative real-time polymerase chain reaction studies. Hum. Pathol. 54 , 165–173 (2016). https://doi.org/10.1016/j.humpath.2016.03.016 T. Pozzobon, G. Goldoni, A. Viola, B. Molon, CXCR4 signaling in health and disease. Immunol. Lett. 177 , 6–15 (2016). https://doi.org/10.1016/j.imlet.2016.06.006 J. Ding, Y. Zhang, J. Wen et al., Imaging CXCR4 expression in patients with suspected primary hyperaldosteronism. Eur. J. Nucl. Med. Mol. Imaging. 47 (11), 2656–2665 (2020). https://doi.org/10.1007/s00259-020-04722-0 Y. Zheng, T. Long, N. Peng et al., The Value of Targeting CXCR4 With 68Ga-Pentixafor PET/CT for Subtyping Primary Aldosteronism. J. Clin. Endocrinol. Metab. 109 (1), 171–182 (2023). https://doi.org/10.1210/clinem/dgad421 J. Hu, T. Xu, H. Shen et al., Accuracy of Gallium-68 Pentixafor Positron Emission Tomography-Computed Tomography for Subtyping Diagnosis of Primary Aldosteronism. JAMA Netw. open. 6 (2), e2255609 (2023). https://doi.org/10.1001/jamanetworkopen.2022.55609 X. Zhang, Y. Song, Y. Jing et al., Comparison of Different Diagnostic Criteria of 68Ga-Pentixafor PET/CT for the Classification of Primary Aldosteronism. J. Clin. Endocrinol. Metab. 110 (8), e2583–e2590 (2025). https://doi.org/10.1210/clinem/dgae747 Y. Gao, J. Ding, Y. Cui et al., Functional nodules in primary aldosteronism: identification of CXCR4 expression with 68Ga-pentixafor PET/CT. Eur. Radiol. 33 (2), 996–1003 (2023). https://doi.org/10.1007/s00330-022-09058-x J. Ding, A. Tong, M. Hacker, M. Feng, L. Huo, X. Li, Usefulness of 68 Ga-Pentixafor PET/CT on Diagnosis and Management of Cushing Syndrome. Clin. Nucl. Med. 47 (8), 669–676 (2022). https://doi.org/10.1097/RLU.0000000000004244 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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1","display":"","copyAsset":false,"role":"figure","size":875534,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRepresentative histopathological findings among patients with ACA\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAbbreviations, HE: hematoxylin-eosin, CYP11B1: 11β-hydroxylase, CYP11B2: aldosterone synthase, CXCR4: CXC chemokine receptor 4, NACA: non-functional adrenocortical adenoma, CPA: cortisol-producing adenoma, APA: aldosterone-producing adenoma\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8269823/v1/2366639c0f3d6f3605fcb7b7.png"},{"id":100684877,"identity":"96737ea1-e744-437e-998f-308a0b396722","added_by":"auto","created_at":"2026-01-20 12:47:22","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":51139,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eH-score of CXCR4 and CYP11B1/2 in adrenal tissues among patients with ACA\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFig. 2a: H-score of CXCR4 across different groups of ACA; Fig. 2b: H-score of\u0026nbsp; CYP11B1 across different groups of ACA; Fig. 2c: H-score of CYP11B2 across different groups of ACA. Abbreviations, CXCR4: CXC chemokine receptor 4, CYP11B1: 11β-hydroxylase, CYP11B2: aldosterone synthase, NACA: non-functional adrenocortical adenoma, CPA: cortisol-producing adenoma, APA: aldosterone-producing adenoma. *significantly different from NACA group (P \u0026lt; 0.05) , **significantly different from NACA group (P \u0026lt; 0.01). \u003csup\u003e#\u003c/sup\u003esignificantly different from CPA group (P \u0026lt; 0.05), \u003csup\u003e##\u003c/sup\u003e significantly different from CPA group (P \u0026lt; 0.01)\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8269823/v1/6edb5772bbce0d80342a5ddf.png"},{"id":100685100,"identity":"dca29f4a-757c-4d04-af83-c09376eeebbd","added_by":"auto","created_at":"2026-01-20 12:49:15","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":87669,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe diagnostic efficacy of the H-score of CXCR4 and CYP11B1/2 in ACAs\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFig. 3a: ROC curve of CXCR4 in differentiating the NACA group from the FACA group; Fig. 3b: ROC curve of CYP11B1 in differentiating the CPA group from the APA group; Fig. 3c: ROC curve of CYP11B2 in differentiating the CPA group from the APA group. Abbreviations, CXCR4: CXC chemokine receptor 4, CYP11B1: 11β-hydroxylase, CYP11B2: aldosterone synthase, NACA: non-functional adrenocortical adenoma, FACA: functinal adrenocortical adenoma, CPA: cortisol-producing adenoma, APA: aldosterone-producing adenoma\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8269823/v1/8e7c2c718a793fe12e25573a.png"},{"id":100684899,"identity":"a9b05a57-dfa1-4723-8ea7-c22f249de5ad","added_by":"auto","created_at":"2026-01-20 12:48:01","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":54312,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDual-marker Strategies for pathological diagnosis of CPA\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAbbreviations, NACA: non-functional adrenocortical adenoma, FACA: functinal adrenocortical adenoma, CPA: cortisol-producing adenoma, APA: aldosterone-producing adenoma, CYP11B2: aldosterone synthase, CXCR4: CXC chemokine receptor 4\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-8269823/v1/9aff9d8c6b490caba1f35f15.png"},{"id":101437019,"identity":"c2db3565-cafd-4a4e-8293-29a0ef35131c","added_by":"auto","created_at":"2026-01-29 16:27:05","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1928952,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8269823/v1/35e6460f-4775-4b7d-be41-633e94cd4f1c.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"CXCR4 serves as a new pathological biomarker for cortisol-producing adenomas","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe widespread use of advanced imaging techniques has led to a significant increase in the detection rate of adrenocortical adenomas (ACA). Retrospective studies indicate a ten-fold rise in the detection rate of ACA between 1995 and 2017\u003csup\u003e[1]\u003c/sup\u003e. A cross-sectional study based on a Chinese community population demonstrated that the prevalence of ACA among adults is approximately 1.4%\u003csup\u003e[2]\u003c/sup\u003e. ACA is classified as either non-functional or functional based on their hormone secretion status. Non-functional ACA (NACA) represents the majority of cases, comprising 50-85% of all ACA\u003csup\u003e[2-4]\u003c/sup\u003e. Based on their endocrine profiles, functional ACA (FACA) can be further categorized into aldosterone-producing adenomas (APA) and cortisol-producing adenomas (CPA).\u003c/p\u003e\n\u003cp\u003ePost-operative histopathological evaluation of adrenal tissue remains essential for determining the pathological type of ACA, guiding treatment decisions, and prognostic evaluation. However, conventional morphological assessment fails to provide functional characterization. The steroidogenic enzymes 11β-hydroxylase (CYP11B1) and aldosterone synthase (CYP11B2) represent the rate-limiting enzymes in cortisol and aldosterone biosynthesis pathways, respectively.\u0026nbsp;Recent studies have demonstrated that CYP11B2 immunohistochemical staining serves as a valuable pathological marker for both localizing aldosterone-producing lesions and histopathological classification in unilateral primary aldosteronism (UPA), which facilitating differentiate APA from other ACAs\u003csup\u003e[5,6]\u003c/sup\u003e. Although elevated CYP11B1 expression has been observed in CPA compared to adjacent adrenal tissue, it is also expressed in NACA at varying levels\u003csup\u003e[7,8]\u003c/sup\u003e. Therefore, reliable pathological markers for CPA are still lacking.\u003c/p\u003e\n\u003cp\u003eCXC chemokine receptor type 4 (CXCR4), a G protein-coupled receptor with seven transmembrane domains, is widely expressed across various tissues and plays crucial roles in numerous physiological and pathological processes\u003csup\u003e[9]\u003c/sup\u003e.Heinze B et al. conducted a comprehensive analysis of 117 APAs, 54 CPAs, and 49 nonfunctioning adenomas (NFA), revealing distinct CXCR4 expression profiles: high expression of CXCR4 was observed in 71% of APAs and 26% of CPAs, compared to only 4% of NFAs\u003csup\u003e[10]\u003c/sup\u003e. However, the potential utility of CXCR4 as a pathological marker for differentiating CPA from other ACAs remains uncertain.\u003c/p\u003e\n\u003cp\u003eThis study aims to systematically evaluate the immunohistochemical expression levels of CXCR4, CYP11B1 and CYP11B2 in APA, CPA, and NACA, and to explore the diagnostic efficacy of these pathological markers for the diagnosis of CPA.\u003c/p\u003e"},{"header":"Methods","content":"\n\u003ch3\u003eStudy design and participants\u003c/h3\u003e\n\u003cp\u003eThis study retrospectively enrolled 127 patients with various ACA subtypes who underwent adrenal surgery at the First Affiliated Hospital of Chongqing Medical University from January 2019 to September 2024, based on data from the CONPASS (Chongqing Primary Aldosteronism Study) and CONACSS (Cohort Study of Adrenogenic Autonomic Cortisol Secretion) databases. The cohort included 25 cases of NACA, 45 cases of CPA, and 57 cases of APA. The study was approved by the Ethics Committee of the First Affiliated Hospital of Chongqing Medical University, and all participants in both CONPASS and CONACSS provided written informed consent.\u003c/p\u003e \u003cp\u003eThe diagnosis of APA required fulfillment of all the following criteria\u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e: (1) A positive screening test for primary aldosteronism (defined as a morning upright plasma aldosterone-to-renin ratio [ARR]\u0026thinsp;\u0026gt;\u0026thinsp;20 pg\u0026middot;mL⁻\u0026sup1;/mIU\u0026middot;L⁻\u0026sup1; ) combined with at least one positive confirmatory test (intravenous saline infusion test: plasma aldosterone concentration (PAC) post-test\u0026thinsp;\u0026gt;\u0026thinsp;80 pg/mL; captopril challenge test: PAC post-test\u0026thinsp;\u0026gt;\u0026thinsp;110 pg/mL\u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e), or meeting criteria for confirmatory test exemption (PAC\u0026thinsp;\u0026gt;\u0026thinsp;200 pg/mL, plasma renin concentration (PRC)\u0026thinsp;\u0026lt;\u0026thinsp;2.5 \u0026micro;IU/mL, and conccurent with hypokalemia) \u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/sup\u003e; (2) 1 mg dexamethasone suppression test (DST) with serum cortisol\u0026thinsp;\u0026lt;\u0026thinsp;50 nmol/L at 8 a.m.; (3) Adrenal CT demonstrating a unilateral adrenal nodule; (4) Pathological confirmation of adrenocortical adenoma or nodule with positive CYP11B2 immunohistochemical staining; (5) Postoperative complete biochemical remission according to Primary Aldosteronism Surgical Outcome (PASO) criteria\u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe diagnosis of CPA required fulfillment of the following criteria\u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e: (1) Abnormal 1 mg DST with serum cortisol\u0026thinsp;\u0026gt;\u0026thinsp;50 nmol/L at 8 a.m. with 24-hour urinary cortisol exceeding the upper limit of normal; (2) morning plasma adrenocorticotropic hormone (ACTH)\u0026thinsp;\u0026lt;\u0026thinsp;10 pg/mL at 8 a.m.; (3) ARR\u0026thinsp;\u0026le;\u0026thinsp;20 pg\u0026middot;mL⁻\u0026sup1;/mIU\u0026middot;L⁻\u0026sup1; or ARR\u0026thinsp;\u0026gt;\u0026thinsp;20 pg\u0026middot;mL⁻\u0026sup1;/mIU\u0026middot;L⁻\u0026sup1; with post-saline infusion test plasma aldosterone\u0026thinsp;\u0026lt;\u0026thinsp;60 pg/mL; (4) Unilateral adrenal nodule on adrenal CT; (5) Pathological confirmation of adrenocortical adenoma; and (6) postoperative serum cortisol\u0026thinsp;\u0026lt;\u0026thinsp;50 nmol/L after 1 mg DST.\u003c/p\u003e \u003cp\u003eThe diagnosis of NACA was established based on the following criteria\u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e: (1) Imaging evidence of unilateral adrenal nodule; (2) Normal biochemical profile, including ARR\u0026thinsp;\u0026le;\u0026thinsp;20 pg\u0026middot;mL⁻\u0026sup1;/mIU\u0026middot;L⁻\u0026sup1; (or ARR\u0026thinsp;\u0026gt;\u0026thinsp;20 with post-saline infusion aldosterone\u0026thinsp;\u0026lt;\u0026thinsp;60 pg/mL), 1 mg DST serum cortisol\u0026thinsp;\u0026lt;\u0026thinsp;50 nmol/L at 8 a.m., and negative for catecholamine metabolites; (3) Postoperative histopathological confirmation of adrenocortical adenoma. Surgical intervention was indicated for patients with large tumor size or strong surgical desire.\u003c/p\u003e\n\u003ch3\u003eImmunohistochemistry\u003c/h3\u003e\n\u003cp\u003eImmunohistochemical staining for CXCR4, CYP11B1, and CYP11B2 was performed following established protocols\u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e. Adrenal tissue specimens were fixed in 4% paraformaldehyde, paraffin-embedded, and sectioned at 6\u0026micro;m thickness. Following deparaffinization and hydrogen peroxide treatment, antigen retrieval was performed using citrate buffer (pH\u0026thinsp;=\u0026thinsp;6.0). Tissue sections were incubated overnight at 4 ℃ with primary antibodies: including rabbit anti-human CXCR4 (abcam, ab124824), rat anti-human CYP11B1 (1:500; Millipore, MABS502), and mouse anti-human CYP11B2 (1: 200; Millipore, MABS1251). After incubation with biotinylated secondary antibodies for 60 minutes at room temperature, sections were treatmented with DAB and counterstained with hematoxylin, followed by dehydration and mounting. The positive control for CXCR4 immunohistochemical staining was the tissue section of human cervical cancer (refer to the antibody manual). Aldosterone-producing micronodule in adrenal tissue was used as the positive control for CYP11B2 immunohistochemical staining. Adrenal Zona fascicularis was used as the positive control for CYP11B1 immunohistochemical staining, and staining without primary antibody was used as the negative control.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eH- score analysis\u003c/h2\u003e \u003cp\u003eThe scoring method refers to previously published studies\u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e. Stained sections were subjected to image acquisition using the VS200 Research-grade whole-slide scanning system (Olympus). Quantitative H-score analysis was performed by randomly capturing 10 high-power fields per section. Staining intensity was graded as: 0 (negative), 1 (The cytoplasm of tumor parenchymal cells expresses faint but visible brown-yellow staining), 2 (The cytoplasm of tumor parenchymal cells expressed obvious brown-yellow staining), or 3 (The cytoplasm of tumor parenchymal cells expressed brown staining). The proportion of cells corresponding to different staining intensity was also quantified. The final H-score is the staining intensity multiplied by the percentage of cells with the corresponding staining intensity and summed. The total score corresponds to the strength of the immunohistochemical staining. The H-score analysis was carried out independently by two researchers who were blinded to the final clinical diagnosis of all cases studied. A third researcher would review the score when there was an inconsistency between the two researchers.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eBiochemical measurements\u003c/h3\u003e\n\u003cp\u003eThe automated chemiluminescence immunoassay was used to measure PRC and PAC (LIAISON, DiaSorin, Italy), and serum cortisol and ACTH levels (DXI800, Beckman, America). The intra-assay and inter-assay coefficients of variation for PRC ranged from 1.2 to 3.7% and from 2.9 to 12.8%, respectively. The analytical sensitivity (lower detection limit) for PRC was 0.53 mIU/L, with a functional sensitivity of 1.60 mIU/L. The PAC assay had a measurement range of 2.2\u0026ndash;100 ng/dL (analytical sensitivity), with a functional sensitivity of 3.0 ng/dL. The intra-assay coefficient of variation for PAC was from 2.4 to 4.8% and the inter-assay coefficient of variation was from 4.4 to 6.7%. The cortisol assay has a measuring range from 11 nmol/L (analytical sensitivity) to 1655 nmol/L.\u003c/p\u003e \u003cp\u003eHigh-performance liquid chromatography-tandem mass spectrometry (LC-MS/MS) was used to measure MNs (AB SCIEX Triple Quad\u0026trade; 4500MD). The measurement ranges were 12.0-900.0 pg/mL for MN and 23.04\u0026ndash;1728.0 pg/mL for NMN, with all correlation coefficients (R)\u0026thinsp;\u0026gt;\u0026thinsp;0.995. The recovery rates ranged from 91.8% to 114% for MN and 85.3% to 105.0% for NMN, with relative standard deviations (RSD)\u0026thinsp;\u0026lt;\u0026thinsp;10.6%. The inter-assay and intra-assay coefficients of variation for MN and NMN were both \u0026lt;\u0026thinsp;15%.\u003c/p\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eStatistical analysis was performed using SPSS 29.0, MedCalc for Receiver operating characteristic (ROC) curve generation, and GraphPad Prism 8.0 for graphical presentation. Data distribution was assessed using the Kolmogorov-Smirnov test. Normally distributed continuous variables were expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation and compared by using t-tests, while non-normally distributed variables were presented as median (interquartile range) and analyzed with non-parametric tests. Categorical variables were described as frequencies (percentages) and analyzed by using Chi-square or Fisher's exact tests (for 2\u0026times;2 tables with n\u0026thinsp;\u0026lt;\u0026thinsp;40 or expected values\u0026thinsp;\u0026lt;\u0026thinsp;5). All tests were two-tailed, with statistical significance set at P\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eClinical and biochemical characteristics of patients\u003c/h2\u003e \u003cp\u003eThe clinical and biochemical characteristics of the 127 ACA patients included in this study were presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Compared with the CPA group, the NACA group showed a significantly lower incidence of hypokalemia and shorter duration of hypertension (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05), while the APA group exhibited significantly higher levels in these two parameters (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The systolic blood pressure (SBP) and diastolic blood pressure (DBP) in the CPA group were significantly higher than those in the NACA group (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05), but no significant differences were noted between the CPA and APA group (SBP: 147.27\u0026thinsp;\u0026plusmn;\u0026thinsp;19.77 mmHg vs. 150.46\u0026thinsp;\u0026plusmn;\u0026thinsp;16.55 mmHg, P\u0026thinsp;=\u0026thinsp;0.38; DBP: 93.27\u0026thinsp;\u0026plusmn;\u0026thinsp;16.81 mmHg vs. 98.07\u0026thinsp;\u0026plusmn;\u0026thinsp;10.67 mmHg, P\u0026thinsp;=\u0026thinsp;0.10). The ARR in the CPA group showed no significant difference compared to the NACA group (P\u0026thinsp;=\u0026thinsp;0.22), but it was significant lower than that in the APA group (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Additionally, both the cortisol levels at 8 a.m. and post-1mg DST cortisol levels in the CPA group were significantly higher than those in the NACA and APA groups. Conversely, the ACTH levels at 8 a.m. in the CPA group were markedly lower than those observed in both the NACA and APA groups.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eClinical and biochemical characteristics of patients with ACAs\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNACA(n\u0026thinsp;=\u0026thinsp;25)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCPA(n\u0026thinsp;=\u0026thinsp;45)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAPA(n\u0026thinsp;=\u0026thinsp;57)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMale (n/%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12/48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6/13*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22/38\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge (year)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e51.3\u0026thinsp;\u0026plusmn;\u0026thinsp;11.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44.8\u0026thinsp;\u0026plusmn;\u0026thinsp;11.8*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e47.8\u0026thinsp;\u0026plusmn;\u0026thinsp;11.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHistory of hypokalemia (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e89*\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDuration of HT (year)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.00(0.00,2.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.00(0.08,5.00)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.00(2.00,10.00)*\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBMI (kg/m\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26.14\u0026thinsp;\u0026plusmn;\u0026thinsp;3.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25.40\u0026thinsp;\u0026plusmn;\u0026thinsp;3.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24.45\u0026thinsp;\u0026plusmn;\u0026thinsp;3.04*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSBP (mmHg)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e126.92\u0026thinsp;\u0026plusmn;\u0026thinsp;19.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e147.27\u0026thinsp;\u0026plusmn;\u0026thinsp;19.77*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e150.46\u0026thinsp;\u0026plusmn;\u0026thinsp;16.55*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDBP (mmHg)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e79.40\u0026thinsp;\u0026plusmn;\u0026thinsp;11.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e93.27\u0026thinsp;\u0026plusmn;\u0026thinsp;16.81*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e98.07\u0026thinsp;\u0026plusmn;\u0026thinsp;10.67*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSerum Potassuim (mmol/L)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.01\u0026thinsp;\u0026plusmn;\u0026thinsp;0.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.43\u0026thinsp;\u0026plusmn;\u0026thinsp;0.53*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.78\u0026thinsp;\u0026plusmn;\u0026thinsp;0.58*\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eARR (pg\u0026middot;mL\u003c/b\u003e\u003csup\u003e\u003cb\u003e\u0026minus;\u0026thinsp;1\u003c/b\u003e\u003c/sup\u003e \u003cb\u003e/mIU\u0026middot;L\u003c/b\u003e\u003csup\u003e\u003cb\u003e\u0026minus;\u0026thinsp;1\u003c/b\u003e\u003c/sup\u003e \u003cb\u003e)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.22(3.37,10.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.05(3.93,19.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e106.40(45.92,269.03)*\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCortisol at 8am. (nmol/L)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e302.20(250.20,395.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e496.57(329.15,598.91)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e295.20(213.63,383.41)\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eACTH at 8am. (pg/mL)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23.48(13.99,32.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.98(1.52,9.60)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24.36(16.59,38.65)\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCortisol post 1mg DST (nmol/L)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24.19(17.71,30.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e478.32(130.50,579.49)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23.40(18.42,34.57)\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMN (ng/L)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e98.60(45.70,108.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48.40(21.00,101.05)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28.10(22.20,74.10)*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eData were expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD or median (interquartile range) and number of patients. Abbreviations, HT: hypertension, BMI: body mass index, SBP: systolic blood pressure, DBP: diastolic blood pressure, ARR: aldosterone to rennin ratio, ACTH: adrenocorticotropic hormone, DST: dexamethasone suppression test, MN: Metanephrine, NACA: non-functional adrenocortical adenoma, CPA: cortisol-producing adenoma, APA: aldosterone-producing adenoma. *significantly different from NACA group (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). \u003csup\u003e#\u003c/sup\u003esignificantly different from CPA group (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05)\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eImmunohistochemical findings of studied cases\u003c/h2\u003e \u003cp\u003eRepresentative immunohistochemical staining results for CXCR4, CYP11B1, and CYP11B2 in each ACA groups were shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. We quantitatively assessed the immunohistochemical staining of CXCR4, CYP11B1 and CYP11B2 using the H-score system in all study subjects (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The FACA groups (comprising CPA and APA) showed significantly elevated CXCR4 H-scores compared to the NACA group (CPA vs NACA: median 65 vs 7, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001; APA vs NACA: median 85 vs 7, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003ea). The CPA group exhibited significantly higher CYP11B1 H-scores compared to the APA group (median values: 109 vs 28, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), while no statistically significant difference was observed between CPA and NACA groups (median values: 109 vs 81, P\u0026thinsp;=\u0026thinsp;0.202) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003eb). Notably, the H-score of CYP11B2 in APA group were approximately 24-fold and 71-fold greater than those of the CPA and NACA groups, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003ec).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eDiagnostic accuracy of the H-score of CXCR4 and CYP11B1/2 in ACAs\u003c/h3\u003e\n\u003cp\u003eROC curve analysis showed that the area under the ROC curve (AUC) for distinguishing NACA from FACA by the H-score of CXCR4 was 0.982 (95% CI: 0.941\u0026ndash;0.997)(Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e3\u003c/span\u003ea). The optimal H-score cutoff value of CXCR4 for diagnosis of FACA was \u0026gt;\u0026thinsp;18, yielding a sensitivity of 99.02% (95% CI: 94.7%-100.0%) and specificity of 92.00% (95% CI: 74.0%-99.0%) at maximum Youden index. Furthermore, we evaluated the diagnostic performance of CYP11B1 and CYP11B2 in discriminating CPA from APA. The AUC for differentiating these two FACA subtypes using the H-score of CYP11B2 was significantly higher than that of CYP11B1 (1.000 [95% CI: 0.964-1.000] vs 0.782 [95% CI: 0.689\u0026ndash;0.858], P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e3\u003c/span\u003ec and \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e3\u003c/span\u003eb). At the optimal cutoff (H-score\u0026thinsp;\u0026le;\u0026thinsp;76), CYP11B2 demonstrated a sensitivity of 98.25% [95% CI: 90.6%-100.0%] and a specificity of 100.0% [95% CI: 92.1%-100.0%]) for diagnosis of CPA, determined by maximal Youden index.\u003c/p\u003e\n\u003ch3\u003eThe efficacy of CXCR4 combined with CYP11B1/2 in diagnosing CPA\u003c/h3\u003e\n\u003cp\u003eBased on the above results, a dual-marker strategy using CXCR4 and CYP11B2 for the diagnosis of CPA was established (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The first step involved utilizing CXCR4 to differentiate NACA from FACA: a positive CXCR4 expression (defined as the H-score\u0026thinsp;\u0026gt;\u0026thinsp;18) indicated a diagnosis of FACA. The second step, following confirmation of FACA, further classified the functional subtypes via CYP11B2: CPA was diagnosed when CYP11B2-negative (defined as the H-score\u0026thinsp;\u0026le;\u0026thinsp;76) and APA was verified when CYP11B2-positive (H-score\u0026thinsp;\u0026gt;\u0026thinsp;76). The AUC was 0.983, with a sensitivity of 97.78% (95% CI: 88.2%-99.9%) and a specificity of 93.90% (95% CI: 86.3%-98.0%) when diagnosing CPA using CXCR4 combined with CYP11B2. When CPA was diagnosed using CXCR4 combined with CYP11B1, the model showed an AUC of only 0.728, with a sensitivity of 77.78% (95% CI: 62.9%-88.8%) and a specificity of 67.07% (95% CI: 55.8%-77.1%). Furthermore, when diagnosis of CPA was made using CXCR4 combined with CYP11B2, the addition of CYP11B1 did not further improve diagnostic accuracy (AUC\u0026thinsp;=\u0026thinsp;0.983).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, we investigated the expression levels of CXCR4 and CYP11B1/2 in adrenal tissues among 127 patients with different types of ACA, and explored the diagnostic efficacy of CXCR4 combined with CYP11B2 for the diagnosis of CPA. We found that CXCR4 was highly expressed in FACA (APA and CPA), and the quantitative H-score of CXCR4 could effectively distinguish NACA from FACA. Furthermore, the two types of FACA (CPA and APA) could be differentiated by CYP11B2 staining. Based on these results, we proposed a dual-marker strategy of using CXCR4 in combination with CYP11B2 for the diagnosis of CPA. Our findings enriched the understanding of CXCR4 expression patterns in ACAs, and provided new insights into the pathological diagnosis of CPA.\u003c/p\u003e \u003cp\u003eCurrently, conventional morphological assessment struggles to achieve functional diagnosis of ACAs, and accurate functional typing of ACA still relies on specific pathological markers. CYP11B1 and CYP11B2 are key enzymes involved in the synthesis of adrenal cortisol and aldosterone, respectively, among which CYP11B2 is a well-recognized pathological marker for APA\u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e. The present study demonstrated that the APA group exhibited significantly higher CYP11B2 H-scores compared to both CPA and NACA groups. The AUC of CYP11B2 for differentiating APA from CPA achieved 1.000, with a sensitivity of 98.25% and a specificity of 100.00%, suggesting that CYP11B2 is a highly reliable marker for the pathological diagnosis of APA. However, although CYP11B1 is the key enzyme for cortisol synthesis, its expression in adrenal lesions of patients with hypercortisolism often shows no significant upregulation compared to normal adrenal tissue. This phenomenon may be attributed to two factors: first, normal adrenal glands exhibit a certain baseline level of CYP11B1 expression; second, zona fasciculata cells are widely distributed within the adrenal glands. Consequently, even a mild upregulation of CYP11B1 expression could result in a substantial increase in cortisol synthesis \u003csup\u003e[\u003cspan additionalcitationids=\"CR19\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/sup\u003e. Previous studies have reported that APA and NACA also express CYP11B1 to varying degrees, which consequently limits its diagnostic utility for distinguishing CPA from other ACA subtypes\u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/sup\u003e. Our study similarly indicate that CYP11B1 expression is detectable across NACA, CPA and APA subtypes, exhibiting limited diagnostic specificity and suboptimal discriminatory performance (AUC\u0026thinsp;=\u0026thinsp;0.782). Consequently, for CYP11B2-negative ACAs, additional biomarkers are required to reliably differentiate between CPA and NACA.\u003c/p\u003e \u003cp\u003eCXCR4, a widely expressed G protein-coupled receptor, plays crucial roles in diverse physiological and pathological processes, including embryogenesis, cell migration, organ vascularization, immunity, tumorigenesis, and inflammation\u003csup\u003e[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/sup\u003e. Previous studies have investigated the expression profile of CXCR4 in ACAs. Heinze B et al. conducted a comprehensive analysis of 117 APAs, 54 CPAs, and 49 NFAs, revealing distinct CXCR4 expression profiles: high expression was observed in 71% of APAs and 26% of CPAs, compared to only 4% of NFAs\u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e. Ding et al. reported that CXCR4 is expressed in 96% of APA cases (24/25), which is significantly higher than that in NFA\u003csup\u003e[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/sup\u003e. Another study revealed that 82% out of 62 PA patients exhibited positive CXCR4 expression by using immunohistochemistry\u003csup\u003e[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/sup\u003e. In recent years, multiple studies have reported the application of CXCR4-targeted radionuclide imaging for APA localization\u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan additionalcitationids=\"CR26\" citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/sup\u003e. Additionally, research by Ding J et al. demonstrated that CXCR4-based radionuclide imaging can fassist in the localization of CPA\u003csup\u003e[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/sup\u003e. However, it remains unclear whether CXCR4 serves as a valid pathological diagnostic indicator for ACAs. Our study demonstrates significant upregulation of CXCR4 expression in both APA and CPA compared to NACA. We assessed the diagnostic performance of the H-score of CXCR4 for discriminating NACA from FACA through ROC curve analysis, revealing exceptional diagnostic accuracy with an AUC of 0.982, accompanied by a sensitivity of 99.02% and a specificity of 92.00%. These findings indicate that the H-score of CXCR4 serves as an effective pathological marker for distinguishing NACA from FACA.\u003c/p\u003e \u003cp\u003eIn this study, a dual-marker strategy of using CXCR4 in combination with CYP11B2 was proposed to accurately distinguish the functional status and subtypes of ACAs (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The first step involves using CXCR4 for screening the functional status of ACA to differentiate NACA from FACA. The second step, on the basis of confirmed FACA, further classifies the functional subtypes through CYP11B2. Notably, the combined quantitative scoring of CXCR4 and CYP11B2 demonstrated outstanding diagnostic performance in distinguishing CPA from other ACA subtypes (NACA and APA), achieving an AUC of 0.983. These findings suggest that the combination of CXCR4 and CYP11B2 can serve as a pathological diagnostic tool for CPA identification.\u003c/p\u003e \u003cp\u003eThis study has the following strengths: Firstly, the H-score scoring system was used in this study, which has a clear quantitative standard to improve the accuracy and objectivity of CXCR4 and CYP11B1/2 evaluation. Secondly, this study proposes a novel dual-marker immunohistochemical model combining CXCR4 and CYP11B2 for functional classification and subtyping of ACAs. This approach optimizes the pathological diagnostic workflow for ACAs and provides a new diagnostic paradigm for identifying CPAs. However, certain limitations should also be acknowledged: The retrospective design of the present study may introduce potential selection bias. Meanwhile, the sample size is relatively small, with only 127 patients enrolled. Therefore, the results of this study need to be validated by multi-center prospective cohort studies with larger sample sizes.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eCXCR4 could effectively discriminates FACA from NACA. A dual-marker strategy combined CXCR4 with CYP11B2 represents a promising new route for the pathological diagnosis of CPA.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank other members of the Cohort Study of Adrenogenic Autonomic Cortisol Secretion(CONACSS) Group: Yunfeng He, MD, PhD and Yao Zhang, MD, PhD for suggestions of study design and revision.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by Chongqing Municipal Collaborative Medical Research Initiative (2025GGXM004, recipient: Qifu Li); Chongqing Technology Innovation and Application Development Special Program (CSTB2024TIAD-KPX0039, recipient: Qifu Li) the National Key Research and Development Project (2022YFC2505300, sub-project 2022YFC2505301, recipient: Qifu Li); the National Natural Science Foundation of China (82100833, recipient: Yi Yang and U21A20355, recipient: Qifu Li); Joint Medical Research Project of Chongqing Science and Technology Commission \u0026amp; Chongqing Health and Family Planning Commission (Major Project, 2022ZDXM003, recipient: Jinbo Hu). The Natural Science Foundation of Chongqing, China (CSTB2025NSCQ-GPX1230, recipient: Yi Yang and CSTB2024NSCQ-MSX0543, recipient: Jiayu Li).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConception and design: Qifu Li, Shumin Yang and Jinbo Hu; Analysis and interpretation of the data: Xinyue Yang, Yi Yang, Jiayu Li, Ying Song and Linqiang Ma; Funding acquisition: Qifu Li, Jinbo Hu, Yi Yang and Jiayu Li; Administrative, technical, or logistic support: Jiayu Li, Wenwen Li, Yue Wang and Junlong Li; Acquisition and assembly of data: Xinyue Yang, Chunxue He, Xiangshuang Zhang, Ying Jing and Hang Shen; All authors read and approved the final paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003eThe authors declare that they have no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval\u0026nbsp;\u003c/strong\u003eThis study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Ethics Committee of the First Affiliated Hospital of Chongqing Medical University.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInformed consent\u0026nbsp;\u003c/strong\u003eInformed consent was obtained from all individual participants included in the study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSome or all datasets generated during and/or analyzed during the current study are not publicly available but are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eA. Ebbehoj, D. Li, R.J. Kaur et al., Epidemiology of adrenal tumours in Olmsted County, Minnesota, USA: a population-based cohort study. The lancet. Diabetes Endocrinol. \u003cb\u003e8\u003c/b\u003e(11), 894\u0026ndash;902 (2020). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/S2213-8587(20)30314-4\u003c/span\u003e\u003cspan address=\"10.1016/S2213-8587(20)30314-4\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eY. Jing, J. Hu, R. Luo et al., Prevalence and Characteristics of Adrenal Tumors in an Unselected Screening Population: A Cross-Sectional Study. Ann. Intern. Med. \u003cb\u003e175\u003c/b\u003e(10), 1383\u0026ndash;1391 (2022). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.7326/M22-1619\u003c/span\u003e\u003cspan address=\"10.7326/M22-1619\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eT. Ichijo, H. Ueshiba, H. Nawata, T. Yanase, A nationwide survey of adrenal incidentalomas in Japan: the first report of clinical and epidemiological features. Endocr. J. \u003cb\u003e67\u003c/b\u003e(2), 141\u0026ndash;152 (2020). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1507/endocrj.EJ18-0486\u003c/span\u003e\u003cspan address=\"10.1507/endocrj.EJ18-0486\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJ. Patrova, I. Jarocka, H. Wahrenberg, H. Falhammar, IN ADRENAL INCIDENTALOMA: EXPERIENCE FROM ONE CENTER, (2015) CLINICAL OUTCOMES. Endocrine practice: official journal of the American College of Endocrinology and the American Association of Clinical Endocrinologists, 21(8), 870\u0026ndash;877. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.4158/EP15618.OR\u003c/span\u003e\u003cspan address=\"10.4158/EP15618.OR\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eK. Nanba, M. Tsuiki, K. Sawai et al., Histopathological diagnosis of primary aldosteronism using CYP11B2 immunohistochemistry. J. Clin. Endocrinol. Metab. \u003cb\u003e98\u003c/b\u003e(4), 1567\u0026ndash;1574 (2013). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1210/jc.2012-3726\u003c/span\u003e\u003cspan address=\"10.1210/jc.2012-3726\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eT.A. Williams, C.E. Gomez-Sanchez, W.E. Rainey et al., International Histopathology Consensus for Unilateral Primary Aldosteronism. J. Clin. Endocrinol. Metab. \u003cb\u003e106\u003c/b\u003e(1), 42\u0026ndash;54 (2021). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1210/clinem/dgaa484\u003c/span\u003e\u003cspan address=\"10.1210/clinem/dgaa484\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eM. Kometani, T. Yoneda, M. Demura et al., Cortisol overproduction results from DNA methylation of CYP11B1 in hypercortisolemia. Sci. Rep. \u003cb\u003e7\u003c/b\u003e(1), 11205 (2017). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/s41598-017-11435-2\u003c/span\u003e\u003cspan address=\"10.1038/s41598-017-11435-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eC.H. Ahn, H.Y. Na, S.Y. Park et al., Expression of CYP11B1 and CYP11B2 in adrenal adenoma correlates with clinical characteristics of primary aldosteronism. Clin. Endocrinol. \u003cb\u003e96\u003c/b\u003e(1), 30\u0026ndash;39 (2022). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/cen.14628\u003c/span\u003e\u003cspan address=\"10.1111/cen.14628\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eN. Kawaguchi, T.T. Zhang, T. Nakanishi, Involvement of CXCR4 in Normal and Abnormal Development. Cells. \u003cb\u003e8\u003c/b\u003e(2), 185 (2019). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/cells8020185\u003c/span\u003e\u003cspan address=\"10.3390/cells8020185\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eB. Heinze, C.T. Fuss, P. Mulatero et al., (2018) Targeting CXCR4 (CXC Chemokine Receptor Type 4) for Molecular Imaging of Aldosterone-Producing Adenoma. Hypertension (Dallas, Tex.: 1979), 71(2), 317\u0026ndash;325. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1161/HYPERTENSIONAHA.117.09975\u003c/span\u003e\u003cspan address=\"10.1161/HYPERTENSIONAHA.117.09975\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJ.W. Funder, R.M. Carey, F. Mantero et al., The Management of Primary Aldosteronism: Case Detection, Diagnosis, and Treatment: An Endocrine Society Clinical Practice Guideline. J. Clin. Endocrinol. Metab. \u003cb\u003e101\u003c/b\u003e(5), 1889\u0026ndash;1916 (2016). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1210/jc.2015-4061\u003c/span\u003e\u003cspan address=\"10.1210/jc.2015-4061\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eY. Song, S. Yang, W. He et al., (2018) Confirmatory Tests for the Diagnosis of Primary Aldosteronism: A Prospective Diagnostic Accuracy Study. Hypertension (Dallas, Tex.: 1979), 71(1), 118\u0026ndash;124. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1161/HYPERTENSIONAHA.117.10197\u003c/span\u003e\u003cspan address=\"10.1161/HYPERTENSIONAHA.117.10197\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eK. Wang, J. Hu, J. Yang et al., Development and Validation of Criteria for Sparing Confirmatory Tests in Diagnosing Primary Aldosteronism. J. Clin. Endocrinol. Metab. \u003cb\u003e105\u003c/b\u003e(7), dgaa282 (2020). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1210/clinem/dgaa282\u003c/span\u003e\u003cspan address=\"10.1210/clinem/dgaa282\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eT.A. Williams, J.W.M. Lenders, P. Mulatero et al., Outcomes after adrenalectomy for unilateral primary aldosteronism: an international consensus on outcome measures and analysis of remission rates in an international cohort. The lancet. Diabetes Endocrinol. \u003cb\u003e5\u003c/b\u003e(9), 689\u0026ndash;699 (2017). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/S2213-8587(17)30135-3\u003c/span\u003e\u003cspan address=\"10.1016/S2213-8587(17)30135-3\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eL.K. Nieman, B.M. Biller, J.W. Findling et al., The diagnosis of Cushing's syndrome: an Endocrine Society Clinical Practice Guideline. J. Clin. Endocrinol. Metab. \u003cb\u003e93\u003c/b\u003e(5), 1526\u0026ndash;1540 (2008). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1210/jc.2008-0125\u003c/span\u003e\u003cspan address=\"10.1210/jc.2008-0125\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eM. Terzolo, A. Stigliano, I. Chiodini et al., AME position statement on adrenal incidentaloma. Eur. J. Endocrinol. \u003cb\u003e164\u003c/b\u003e(6), 851\u0026ndash;870 (2011). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1530/EJE-10-1147\u003c/span\u003e\u003cspan address=\"10.1530/EJE-10-1147\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eY. Yang, M. Xiao, Y. Song et al., H-score of 11β-hydroxylase and aldosterone synthase in the histopathological diagnosis of adrenocortical tumors. Endocrine. \u003cb\u003e65\u003c/b\u003e(3), 683\u0026ndash;691 (2019). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s12020-019-02022-8\u003c/span\u003e\u003cspan address=\"10.1007/s12020-019-02022-8\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eU. Enberg, L.O. Farnebo, A. Wedell et al., In vitro release of aldosterone and cortisol in human adrenal adenomas correlates to mRNA expression of steroidogenic enzymes for genes CYP11B2 and CYP17. World J. Surg. \u003cb\u003e25\u003c/b\u003e(7), 957\u0026ndash;966 (2001). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s00268-001-0035-2\u003c/span\u003e\u003cspan address=\"10.1007/s00268-001-0035-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eC.E. Gomez-Sanchez, X. Qi, C. Velarde-Miranda et al., Development of monoclonal antibodies against human CYP11B1 and CYP11B2. Mol. Cell. Endocrinol. \u003cb\u003e383\u003c/b\u003e(1\u0026ndash;2), 111\u0026ndash;117 (2014). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.mce.2013.11.022\u003c/span\u003e\u003cspan address=\"10.1016/j.mce.2013.11.022\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eK. Nishimoto, K. Nakagawa, D. Li et al., Adrenocortical zonation in humans under normal and pathological conditions. J. Clin. Endocrinol. Metab. \u003cb\u003e95\u003c/b\u003e(5), 2296\u0026ndash;2305 (2010). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1210/jc.2009-2010\u003c/span\u003e\u003cspan address=\"10.1210/jc.2009-2010\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eF. Kubota-Nakayama, Y. Nakamura, S. Konosu-Fukaya et al., Expression of steroidogenic enzymes and their transcription factors in cortisol-producing adrenocortical adenomas: immunohistochemical analysis and quantitative real-time polymerase chain reaction studies. Hum. Pathol. \u003cb\u003e54\u003c/b\u003e, 165\u0026ndash;173 (2016). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.humpath.2016.03.016\u003c/span\u003e\u003cspan address=\"10.1016/j.humpath.2016.03.016\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eT. Pozzobon, G. Goldoni, A. Viola, B. Molon, CXCR4 signaling in health and disease. Immunol. Lett. \u003cb\u003e177\u003c/b\u003e, 6\u0026ndash;15 (2016). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.imlet.2016.06.006\u003c/span\u003e\u003cspan address=\"10.1016/j.imlet.2016.06.006\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJ. Ding, Y. Zhang, J. Wen et al., Imaging CXCR4 expression in patients with suspected primary hyperaldosteronism. Eur. J. Nucl. Med. Mol. Imaging. \u003cb\u003e47\u003c/b\u003e(11), 2656\u0026ndash;2665 (2020). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s00259-020-04722-0\u003c/span\u003e\u003cspan address=\"10.1007/s00259-020-04722-0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eY. Zheng, T. Long, N. Peng et al., The Value of Targeting CXCR4 With 68Ga-Pentixafor PET/CT for Subtyping Primary Aldosteronism. J. Clin. Endocrinol. Metab. \u003cb\u003e109\u003c/b\u003e(1), 171\u0026ndash;182 (2023). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1210/clinem/dgad421\u003c/span\u003e\u003cspan address=\"10.1210/clinem/dgad421\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJ. Hu, T. Xu, H. Shen et al., Accuracy of Gallium-68 Pentixafor Positron Emission Tomography-Computed Tomography for Subtyping Diagnosis of Primary Aldosteronism. JAMA Netw. open. \u003cb\u003e6\u003c/b\u003e(2), e2255609 (2023). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1001/jamanetworkopen.2022.55609\u003c/span\u003e\u003cspan address=\"10.1001/jamanetworkopen.2022.55609\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eX. Zhang, Y. Song, Y. Jing et al., Comparison of Different Diagnostic Criteria of 68Ga-Pentixafor PET/CT for the Classification of Primary Aldosteronism. J. Clin. Endocrinol. Metab. \u003cb\u003e110\u003c/b\u003e(8), e2583\u0026ndash;e2590 (2025). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1210/clinem/dgae747\u003c/span\u003e\u003cspan address=\"10.1210/clinem/dgae747\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eY. Gao, J. Ding, Y. Cui et al., Functional nodules in primary aldosteronism: identification of CXCR4 expression with 68Ga-pentixafor PET/CT. Eur. Radiol. \u003cb\u003e33\u003c/b\u003e(2), 996\u0026ndash;1003 (2023). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s00330-022-09058-x\u003c/span\u003e\u003cspan address=\"10.1007/s00330-022-09058-x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJ. Ding, A. Tong, M. Hacker, M. Feng, L. Huo, X. Li, Usefulness of 68 Ga-Pentixafor PET/CT on Diagnosis and Management of Cushing Syndrome. Clin. Nucl. Med. \u003cb\u003e47\u003c/b\u003e(8), 669\u0026ndash;676 (2022). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1097/RLU.0000000000004244\u003c/span\u003e\u003cspan address=\"10.1097/RLU.0000000000004244\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Adrenocortical adenoma, cortisol-producing adenoma, CXC chemokine receptor 4, 11β-hydroxylase, aldosterone synthase","lastPublishedDoi":"10.21203/rs.3.rs-8269823/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8269823/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eCortisol-producing adenomas (CPA) lack specific pathological markers. This study aims to investigate the expression levels and diagnostic value of CXC chemokine receptor 4 (CXCR4), 11β-hydroxylase (CYP11B1), and aldosterone synthase (CYP11B2) for CPA. We retrospectively included 25 non-functional adrenocortical adenomas (NACA) and 102 functional adrenocortical adenomas (FACA), which comprising 45 CPAs and 57 aldosterone-producing adenomas (APA). Immunohistochemical staining of CXCR4, CYP11B1 and CYP11B2 was performed and quantified by the H-score system. Receiver operating characteristic (ROC) curve analysis was applied to evaluate the diagnostic performance. CXCR4 H-score was significantly higher in FACA compared to NACA (78 vs. 7, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). CYP11B1 H-score was significantly higher in CPA than APA (109 vs. 28; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), but was not significantly different between CPA and NACA (109 vs. 81, P\u0026thinsp;=\u0026thinsp;0.202). Notably, CYP11B2 H-score in APA was significantly higher compared to both CPA and NACA. Area under the ROC curve (AUC) of CXCR4 for distinguishing NACA from FACA was 0.982, with an optimal cutoff value of CXCR4\u0026thinsp;\u0026gt;\u0026thinsp;18. In FACA group, CYP11B2 demonstrated higher AUC in differentiating CPA from APA compared to CYP11B1 (1.000 vs. 0.782), with an optimal cutoff of CYP11B2\u0026thinsp;\u0026gt;\u0026thinsp;76. A dual-marker strategy (CXCR4\u0026thinsp;\u0026gt;\u0026thinsp;18\u0026thinsp;+\u0026thinsp;CYP11B2\u0026thinsp;\u0026le;\u0026thinsp;76) for distinguishing CPA from other adrenocortical adenomas achieved an AUC of 0.983, with a sensitivity of 97.78% and a specificity of 93.90%. Thus, CXCR4 could effectively discriminates FACA from NACA. A dual-marker strategy combined CXCR4 and CYP11B2 represents a promising novel approach for CPA pathological diagnosis.\u003c/p\u003e","manuscriptTitle":"CXCR4 serves as a new pathological biomarker for cortisol-producing adenomas","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-20 10:52:42","doi":"10.21203/rs.3.rs-8269823/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e113879c-b7f8-4e8c-8819-e275145f9b7d","owner":[],"postedDate":"January 20th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-01-29T16:26:16+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-20 10:52:42","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8269823","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8269823","identity":"rs-8269823","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}