Diagnostic and prognostic utility of INSM1, ISL1 and secretagogin in pheochromocytoma

Diagnostic and prognostic utility of INSM1, ISL1 and secretagogin in pheochromocytoma | 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 Diagnostic and prognostic utility of INSM1, ISL1 and secretagogin in pheochromocytoma Mehmet Sözen, Gupse Turan, Zeynep Cantürk, Berrin Çetinarslan, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4322745/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 Background: To assess immunohistochemical expression of the second generation neuroendocrine immunohistochemical markers such as insulin gene enhancer protein 1 (ISL1), insulinoma-associated protein 1 (INSM1) and secretagogin (SECG) in pheochromocytoma (PCC) and prognostic value. Methods: The study included 30 operated PCC patients. The tissue preparations were re-evaluated by two pathologists and PASS score and GAPP score were given. 4 µm thick paraffin block sections were stained with INSM1, ISL1 and SECG antibodies to obtain staining intensity score, staining percentage and H-score. Results: Mean age at the diagnosis was 50.5 (±15.9) years. Eight patients were asymptomatic. The most common complaint was high blood pressure. 4 patients (13.3%) had nonfunctioning adenoma. The lesions were mostly localized in the right adrenal gland and median tumor size was 45.0 (35.0-54.2) mm. Median Ki67 was 2.0 % (0.9-3.0). According to the PASS score, 9 (30.0%) patients showed in the benign clinical behavior (score <4), while according to the GAPP score, only 4 (13.3%) patients in the well differentiated type (0-2 points) group. INSM1 and ISL1 were positive in 21 (70%) and 26 (86.7%) of the patients, respectively. However, SECG was positive only in 6 patients (20%). Among the second generation neuroendocrine immunohistochemical markers, ISL1 had the highest H-score. Correlation analysis showed a negative correlation between ISL1 and tumor HU and a positive correlation between INSM1 and Ki67. Conclusion: INSM1, ISL1 and SECG, which are second generation neuroendocrine immunohistochemical markers, can be used in the differential diagnosis of pheochromocytoma. In addition, especially ISNM1 may have prognostic significance. INSM1 ISL1 Secretagogin Pheochromocytoma Figures Figure 2 Introduction Pheochromocytomas (PCCs) are rare neuroendocrine tumors originating from chromaffin cells of the adrenal medulla and producing catecholamines. PCCs can occur at any age and peak in the 3rd and 4th decades. It's estimated prevalence between 0.1–0.6% and incidence 3–8 cases per million population per year. PCCs most commonly present with catecholamine excess symptoms such as headache, tremor, diaphoresis, hypertension, palpitations. However, approximately 4–5% of cases detected incidentally on radiological methods while screening other causes [ 1 ]. Pathologists can recognize the PCCs easily when typical morphology is present however it can be challenging in atypical cases. Immunohistochemistry (IHC) play important confirmatory role in diagnosis of PCCs. Classically, PCCs chromaffin cells are positive for chromogranin A (CgA) and synaptophysin and sustentacular cells are positive for S100. The general opinion is that the most specific neuroendocrine marker is CgA [ 2 ]. However, due to some limitations of these markers, new markers such as GATA3, cyclooxygenase 2, heat-shock protein 90, cell surface glycoprotein CD44 are recommended for diagnosis and risk stratification [ 2 – 4 ]. PCC can occur with metastases even a quarter of a century after the initial surgery [ 5 ]. In the 2022 World Health Organization (WHO) classification, PCC are defined as malignant neoplasms with variable metastatic potential [ 6 , 7 ]. Before the idea that all PCCs should be considered malignant, a number of scoring systems were used to predict the risk of metastasis [ 8 , 9 ]. However, recent studies have shown that high scores may lead to an overestimation of the risk of metastasis [ 10 ]. Therefore, it is undeniable fact that stronger arguments are needed to predict the risk of metastasis. In recent years, new IHC markers with high diagnostic accuracy have been used for neuroendocrine neoplasms such as insulin gene enhancer protein 1 (ISL1), insulinoma-associated protein 1 (INSM1) and secretagogin (SECG). These molecules are involved in the neuroendocrine cell differentiation steps, and many studies have reported that they are highly sensitive markers in the diagnosis of neuroendocrine neoplasms [ 11 – 13 ]. In this study; we investigated immunohistochemical expression of ISL1, INSM1 and SECG in PCC tissues in order to define their diagnostic and prognostic value. Materials and methods This study was approved by the local ethics committee (Project number: 2021/271). All data of PCC patients who were operated between 2010–2021, were retrieved from hospital archive system. After eliminating patients with missing data, 30 patients were included in the study. patients without preparations suitable for staining and patients with mixed tumors were excluded. The preoperative clinical status, symptoms and comorbidities and postoperative follow-up results of these patients were recorded. Radiological reevaluation was performed by a single radiologist on archived images, via the communication system (PACS) (Sectra IDS 7, Sectra, Linköping, Sweden). Computed tomography (CT) scans had been performed with 64 multidetector computed tomography (MDCT) scanner (Aquilion, Toshiba Healthcare), and magnetic resonance imaging (MRI) with 1.5 or 3-T systems (Philips Achieva Netherlands). The tissue preparations of the study cases were re-evaluated by two pathologists, PASS score and GAPP score were given. A PASS of < 4 accurately identified all histologically benign and clinically benign tumors [ 8 ]. The total GAPP points were then classified into follows: Well-differentiated type (0–2 points), Moderately differentiated type (3–6 points) and Poorly differentiated type (7–10 points) [ 9 ]. After this subclassification, 4 µm thick paraffin block sections were prepared from all cases and stained using INSM1, ISL1 and SECG antibodies. Staining was performed on a Ventana automatic staining device (Roche Ventana) using Ventana Optiview and Ultraview DAB kits. Immunohistochemical study preparations were evaluated simultaneously by two pathologists. Both staining intensity score (Strong = 3, Moderate = 2, Weak = 1, Absent = 0) and staining percentage (0-100) were obtained. The H-score (0-300) was obtained by multiplying the staining percentages and staining intensity score. Afterwards, The H-score expression level was categorized as follows; low (H-score, 0-100), moderate (H-score, 100–200), and high (H-score, 200–300). Ki67 and CgA were re-evaluated on previously stained immunohistochemistry preparations obtained from archive. Statistical Analysis All statistical analyses were performed using SPSS 20.0 (IBM Corp., Armonk, NY, USA). Shapiro-Wilk’s test was used to assess the assumption of normality. Continuous variables were presented with mean ± standard deviation or (in the case of non-normal distribution) median (interquartile range (IQR)). Categorical variables were summarized as counts and percentages. Associations between continuous variables were determined by Spearman's correlation analysis. Comparisons of continuous variables between groups were carried out using Mann-Whitney U test and Kruskal-Wallis test. Dependent group comparisons were performed by Friedman's two-way analysis of variance. Dunn's test was used for the multiple comparisons. A p-value < 0.05 was considered statistically significant. Results The male-to-female ratio in the PCC group was 1:2.75 and the mean age at the diagnosis was 50.5 (± 15.9) years and during study was 56.8 (± 16.4) years. Eight patients were asymptomatic and diagnosed incidentally. The most common complaint in symptomatic patients was high blood pressure, most of which was permanent. 6 patients had history of malignancy which were Prostate cancer (n = 1), lip cancer (n = 1), colon cancer (n = 1), endometrium cancer (n = 1), papillary thyroid cancer (n = 1) and medullary thyroid cancer (n = 1). The patient with medullary thyroid cancer had a RET proto-oncogene mutation caused to MEN2A syndrome. 17 patients (56.7%) had norepinephrine dominant catecholamine elevation, while 3 patients (10.0%) had epinephrine dominant, 6 patients (20.0%) had both catecholamine secretion. We couldn’t detect any increase in catecholamine secretion of the remaining 4 patients (13.3%) although several times of testing. Genetic analysis could be performed in ten patients (33.3%), of whom 7 (23.3%) had no pathogenic mutation. Of the remaining patients, one patient had SDHD, one had NF and one had RET mutation. The lesions were mostly localized to the right adrenal gland and were mostly mixed-characterized lesions with cystic areas, calcifications and necrosis. The minimum tumor size was 11 mm, while the maximum tumor size was 135 mm. HU values of all lesions were > 10 HU (min HU:18, max HU:56). All demographic, clinical and radiological characteristics were given in Table 1 . Table 1 Demographic and clinical characteristics Variable Value Age (years) 56.8 (± 16.4) Diagnosis age (years) 50.5 (± 15.9) Sex Female 22 (73.3%) Male 8 (26.7%) Incidental diagnosis 8 (26.7%) Symptoms Palpitation 18 (60.0%) Headache 12 (40.0%) Excessive sweating 10 (33.3%) Flushing 9 (30.0%) Dyspeptic disorder 8 (26.7%) Psychiatric state disorder 1 (3.3%) Tremor 1 (3.3%) Dyspnea 1 (3.3%) Hypertension 24 (80%) Hypertension pattern Sustained 13 (54.2%) Paroxysmal 11 (45.8%) Other diseases Diabetes mellitus 12 (40.0%) Cancer 6 (20.0%) Coronary artery disease 5 (16.7) Cerebrovascular disease 3 (10.0%) Hepatitis B 1 (3.3%) Asthma 1 (3.3%) Dyslipidemia 1 (3.3%) Syndromic cases 2 (6.7%) Biochemical parameters Preoperative urine-free metanephrine (µg/24 h) 239.0 (157.0-1019.5) Preoperative urine-free normetanephrine (µg/24 h) 2026.0 (1051.0-4592.5) Postoperative urine-free metanephrine (µg/24 h) 103.0 (53.2–126.0) Postoperative urine-free normetanephrine (µg/24 h) 316.5 (250.7–383.0) Radiological findings Diagnostic method CT 7 (23.3%) MR 13 (43.3) CT + MR 10 (33.4%) Tumor size (mm) 45.0 (35.0-54.2) Location Right 20 (66.7%) Left 10 (33.3%) Structure Solid 11 (36.7%) Cystic 6 (20.0%) Solid + cystic 13 (43.3%) Irregular Border 1 (3.3%) Shape Oval 23 (76.7%) Round 7 (23.3%) Peripheral tissue invasion 1 (3.3%) Peripheral rim 11 (36.7%) Calcification 3 (10.0%) Necrosis 18 (60.0%) Tumor HU 33.06 (± 8.75) All patients mean Ki67 was 2.17 ± 1.46. According to the PASS score, most patients were in the potentially aggressive behavior group (score ≥ 4), while according to the GAPP score, most of them were in the moderately differentiated type (3–6 points) group. All cases were positive for CgA neuroendocrine tumor marker. INSM1 and ISL1, which are novel second generation neuroendocrine immunohistochemical markers, were positive in 21 (70%) and 26 (86.7%) of the patients, respectively. However, SECG was positive only in 6 patients (20%) (Table 2 ). INSM1 and ISL1 staining intensity was mostly weak to moderate, whereas SECG did not show a very large amount of staining (Fig. 1). Table 2 Pathological features and IHC staining intensities Ki67 (%) 2.0 (0.9-3.0) 3 6 (20.0%) PASS score 4.8 (± 2.6) Benign clinical behavior (score < 4) 9 (30.0%) Potential aggressive behaviour (score ≥ 4) 21 (70.0%) GAPP score 4.4 (± 1.9) Well differentiated type (0–2 points) 4 (13.3%) Moderately differentiated type (3–6 points) 22 (73.4%) Poorly differentiated type (7–10 points) 4 (13.3%) CgA staining intensity Negative 0 (0.0%) Weak 2 (6.7%) Moderate 9 (30.0%) Strong 19 63.3%) ISNM1 staining intensity Negative 9 (30.0%) Weak 11 (36.7%) Moderate 9 (30.0%) Strong 1 (3.3%) ISL1 staining intensity Negative 4 (13.3%) Weak 6 (20.1%) Moderate 13 (43.3%) Strong 7 (23.3%) SECG staining intensity Negative 24 (80.0%) Weak 5 (16.7%) Moderate 0 (0.0%) Strong 1 (3.3%) The mean H-score of all cases was positive for CgA at the highest expression level. Among the second generation neuroendocrine immunohistochemical markers, ISL1 had the highest H-score. Their H-score expression levels are summarized in Table 3 and expression variations are better illustrated in a H-score plot graphic (Fig. 2). Table 3 Expression of traditional and second generation neuroendocrine IHC markers p value CgA ISNM1 ISL1 SECG CgA vs INSM1 CgA vs ISL1 CgA vs SECG H-score 300 (200–300) 10 (3.75-80) 120 (20-202.5) 0 (0–0) 0.000 0.075 0.000 Low expression 2 (6.7%) 25 (83.3%) 12 (40.0%) 29 (96.7%) Moderate expression 10 (33.3%) 4 (13.3%) 11 (36.7%) 0 (0.0%) High expression 18 (60.0%) 1 (3.3%) 7 (23.3%) 1 (3.3%) Correlation analysis revealed a negative correlation between ISL1 and tumor HU and a positive correlation between INSM1 and Ki67 (Table 4 ). Table 4 Correlation analysis of traditional and second generation neuroendocrine IHC markers CgA ISL1 INSM1 SECG Age r -,148 ,039 -,049 ,161 p ,436 ,838 ,795 ,395 Diagnosis age r -,176 ,231 ,098 ,134 p ,351 ,220 ,607 ,480 Preoperative urine-free metanephrine r ,166 -,016 ,078 -,123 p ,379 ,935 ,683 ,517 Preoperative urine-free normetanephrine r -,113 -,272 -,141 -,082 p ,551 ,145 ,457 ,666 Postoperative urine-free metanephrine r ,019 -,134 -,185 -,007 p ,921 ,479 ,328 ,970 Postoperative urine-free normetanephrine r -,157 ,097 ,030 -,116 p ,408 ,608 ,876 ,542 Tumor HU r ,021 -,803 ** -,378 -,049 p ,935 ,000 ,135 ,851 Tumor size r -,100 -,162 -,209 -,106 p ,601 ,392 ,268 ,576 GAPP score r -,074 ,008 ,008 -,221 p ,697 ,968 ,965 ,242 PASS score r -,019 ,019 -,046 -,222 p ,921 ,920 ,809 ,239 Ki67 r -,011 ,157 ,475 ** -,014 p ,956 ,406 ,008 ,942 None of the patients had metastases at the time of diagnosis and surgical remission was achieved in all patients. The follow-up period of the patients included in the study was 69 (32.25–106.0) months. In one patient, new liver metastases were detected approximately 24 months after the initial surgery. This patient underwent 8 cycles of 177 Lu treatment. But the patient died due to progressive disease Discussion The diagnosis of neuroendocrine tumors (NETs) is based on histopathological confirmation of neuroendocrine differentiation. Chromogranin A (CgA) is an acidic, monomeric protein released by exocytosis from neuroendocrine secretory granules. CgA is a sensitive but non-specific IHC marker for NETs [ 14 ]. CgA usually shows strong positive staining in NETs but is focal and weak or absent in most neuroendocrine carcinomas (NECs) [ 15 ]. Pheochromocytomas (PCCs) showing a nested growth pattern (zellballen appearance) of chief cells with basophilic cytoplasm are strongly positive for the CgA [ 16 ]. Elevated serum CgA has been associated with large tumor tissue and metastasis in small studies [ 17 , 18 ]. However, tissue expression of CgA has not been shown to distinguish between malignant and benign tumors or to predict prognosis [ 8 ]. Meanwhile, downregulation of chromogranin B (CgB), which belongs to the same family as CgA, was observed in PCCs with high PASS score and was associated with shorter survival [ 19 ]. Due to the limitations of well-known NET markers in the diagnosis and determining prognosis, several new markers have emerged, such as INSM1, ISL1 and SECG, which have high sensitivity and specificity levels for diagnosis. These markers have been evaluated in small groups of PCCs in a few NET studies in the literature, but no large PCC-specific studies have been conducted. Therefore, we investigated the clinicopathologic significance of second generation neuroendocrine immunohistochemical markers in PCC patients. In this study, we showed that INSM1 and ISL1 can be used to diagnose PCC, but not SECG. Furthermore, INSM1 expression was positively correlated with higher Ki67 proliferative index levels. And moreover, ISL1 expression showed an inverse correlation with tumor HU on CT imaging INSM1 is a transcription factor involved in the differentiation of embryonic neuroendocrine cells. Subsequent studies show that INSM1 expression is a highly specific marker for NETs in lung, gastrointestinal tract, pancreas and breast, medullary thyroid carcinoma, pheochromocytoma and pituitary adenoma [ 20 – 22 ]. Rosenbaum et al. found INSM1 expression in 88.3% of neoplastic NET tissue detected by IHC [ 22 ]. In the study by Fujino et al., INSM1 was found to be positive in 71.4% (5/7) of PCC patients and staining intensity rates varied between 5–50% and conventional NET markers mean H-score were superior to INSM1 [ 23 ]. In another study, INSM1 staining was found in all 7 PCC patients [ 22 ]. Beyond its diagnostic significance, it confirmed that INSM1 is an independent prognostic factor in small cell lung cancer [ 24 ]. Similarly, in pulmonary high-grade neuroendocrine carcinoma patients, overall survival and recurrence-free survival were significantly poorer in the INSM1 positive group [ 25 ]. Conversely, INSM1 expression in luminal B breast cancers was associated with significantly better survival [ 26 ]. INSM1 was demonstrated by IHC in the majority of cases in this study. In addition, it was found to be associated with Ki67, which has been proposed as a reliable marker to identify cases with a high risk of metastatic spread and poor prognosis in PCC. This result suggests that INSM1 may be a marker that can predict prognosis as well as diagnosis in PCC patients. ISL1 is a homeobox-gene–related transcription factor involved in pancreatic exocrine and endocrine differentiation and regulates insulin gene expression [ 27 ]. Initially, researchers suggested that from a diagnostic point of view, ISL1 immunoreactivity would indicate that the primary site of a metastatic NET was the pancreas [ 28 ]. Subsequent studies have also shown ISL1 expression in duodenal, rectal, colonic and ileal NET, Merkel cell carcinomas, pulmonary small cell NET, medullary thyroid carcinomas and pheochromocytomas [ 12 , 29 , 30 ]. In the study by Agaimy et al., ISL1 showed strong (> 50%) staining intensity in all six PCC patients [ 12 ]. Similarly, Hattori et al. have shown that the expression of ISL1 genes is upregulated in human PCC tissue [ 31 ]. In a preclinical study, ISL1 immunoreactivity was widely distributed in PCC cell line [ 32 ]. In this study, ISL1 immunoreactivity was examined in a large group of PCCs and a high rate of positivity was observed in accordance with the literature. Moreover, it was also similar to CgA in terms of H-score. However, no correlation was observed between ISL1 expression and prognostic markers beyond diagnosis. We found a negative association between ISL1 and tumor HU, but this has never been studied before in the literature. The diagnostic or prognostic significance of this may be improved by further research. Secretagogin is a 32 kDa hexa-EF-el Ca2þ-binding protein with homology to calbindin D28k and calretinin, encoded by genes located on chromosome 6 and is involved in cell growth, differentiation and replication through calcium signaling modulation [ 33 ]. In subsequent studies, SECG immunoreactivity has been demonstrated in many neuroendocrine tumors such as well-differentiated neuroendocrine tumors of pancreas, ovarian carcinoid, pituitary adenoma, medullary thyroid cancer, small cell lung cancer, large cell neuroendocrine carcinoma [ 34 , 35 ]. However in most PCC patients, SECG showed negative or weak immunoreactivity [ 35 ]. Juhlin et al. similarly showed negative SECG immunoreactivity in 83.3% (5/6) of PCC cases [ 11 ]. In metastatic NETs of unknown primary, they suggested that PCC or paraganglioma should be investigated in a tumor exhibiting ISL1 (+), INSM1 (+) and SECG (-) according to second-generation neuroendocrine immunohistochemical marker results. The present study supports the literature data and SECG was found to be negative or weakly positive in the majority of cases and could not be associated with prognostic markers. Our study has several limitations. First, this is a retrospective study and the small case population may reduce statistical power. Second, we included cases over a 12-year period, so some antigens may have been lost to different degrees or have reduced power. Third, since the genetic background of all patients is unknown, it is not clear how second generation neuroendocrine immunohistochemical markers work in different genotypes. Conclusion Our study demonstrated that INSM1, ISL1 and SECG, which are second generation neuroendocrine immunohistochemical markers, can be used in the differential diagnosis of pheochromocytoma. Since CgA is sensitive but non-specific, these markers can be used supportively to reveal the nature of a mass. Furthermore, the second generation IHC NET markers may also have prognostic significance beside their diagnostic role, but further larger studies with longer follow-up period are needed because metastatic disease may be diagnosed even after 20 years. Abbreviations Insulin gene enhancer protein 1 (ISL1) Insulinoma-associated protein 1 (INSM1) Secretagogin (SECG) Pheochromocytoma (PCC) Chromogranin A (CgA) Declarations Ethics approval: This study was approved by Kocaeli University Non-Interventional Clinical Research Ethics Committee with project number 2021/271. Consent for publication: Not applicable Availability of data and material: The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request. Competing interests: The authors declare that they have no competing interests. Funding: This project was supported by Kocaeli University Scientific Research Projects Coordination Unit with project number 2756. Author contribution: MS: Study conception, material preparation, data collection, analysis and manuscript writing; GT: Pathological interpretation and critical review of manuscript; ZC: Interpretation of results and statistical analysis; BC: Data interpretation and critical review of manuscript; AS: Study conception and critical review of manuscript; MT: Radiological data interpretation; AHC: Pathological interpretation and data collection; BC, EG, DK: Critical review of literature, material preparation, data collection. All authors have read and approved the manuscript final version. Acknowledgments: None References Sbardella E, Grossman AB. Pheochromocytoma: An approach to diagnosis. Best Pract Res Clin Endocrinol Metab. Baillière Tindall; 2020;34:101346. Cheung VKY, Gill AJ, Chou A. Old, New, and Emerging Immunohistochemical Markers in Pheochromocytoma and Paraganglioma. Endocr Pathol [Internet]. Humana Press Inc.; 2018 [cited 2023 Jul 11];29:169–75. Available from: https://link.springer.com/article/10.1007/s12022-018-9534-7 Salmenkivi K, Haglund C, Ristimäki A, Arola J, Heikkilä P. Increased Expression of Cyclooxygenase-2 in Malignant Pheochromocytomas. J Clin Endocrinol Metab [Internet]. Oxford Academic; 2001 [cited 2023 Jul 11];86:5615–9. Available from: https://dx.doi.org/10.1210/jcem.86.11.8052 Asa SL, Ezzat S, Mete O. The Diagnosis and Clinical Significance of Paragangliomas in Unusual Locations. J Clin Med 2018, Vol 7, Page 280 [Internet]. Multidisciplinary Digital Publishing Institute; 2018 [cited 2023 Jul 11];7:280. Available from: https://www.mdpi.com/2077-0383/7/9/280/htm Thai E, Gnetti L, Gilli A, Caruana P, Valle RD, Buti S. Very late recurrence of an apparently benign pheochromocytoma. J Cancer Res Ther [Internet]. Medknow Publications; 2015 [cited 2023 Aug 10];11:1226–9. Available from: https://journals.lww.com/cancerjournal/Fulltext/2015/11040/Very_late_recurrence_of_an_apparently_benign.143.aspx Mete O, Asa SL, Gill AJ, Kimura N, de Krijger RR, Tischler A. Overview of the 2022 WHO Classification of Paragangliomas and Pheochromocytomas. Endocr Pathol 2022 331 [Internet]. Springer; 2022 [cited 2023 Aug 10];33:90–114. Available from: https://link.springer.com/article/10.1007/s12022-022-09704-6 WHO Classification of Tumours Editorial Board: Endocrine and Neuroendocrine tumours, vol. 8. 5th edn. (International Agency for Research on Cancer, Lyon, France, 2022) [Internet]. [cited 2023 Aug 10]. Available from: https://tumourclassification.iarc.who.int/welcome/# Thompson LDR. Pheochromocytoma of the Adrenal gland Scaled Score (PASS) to separate benign from malignant neoplasms: a clinicopathologic and immunophenotypic study of 100 cases. Am J Surg Pathol [Internet]. 2002 [cited 2023 Aug 2];26:551–66. Available from: https://europepmc.org/article/med/11979086 Kimura N, Takayanagi R, Takizawa N, Itagaki E, Katabami T, Kakoi N, et al. Pathological grading for predicting metastasis in phaeochromocytoma and paraganglioma. Endocr Relat Cancer [Internet]. Bioscientifica Ltd; 2014 [cited 2023 Aug 2];21:405–14. Available from: https://erc.bioscientifica.com/view/journals/erc/21/3/405.xml Stenman A, Zedenius J, Juhlin CC. Over-diagnosis of potential malignant behavior in MEN 2A-associated pheochromocytomas using the PASS and GAPP algorithms. Langenbeck’s Arch Surg [Internet]. Springer Verlag; 2018 [cited 2023 Aug 10];403:785–90. Available from: https://link.springer.com/article/10.1007/s00423-018-1679-9 Juhlin CC, Zedenius J, Höög A. Clinical Routine Application of the Second-generation Neuroendocrine Markers ISL1, INSM1, and Secretagogin in Neuroendocrine Neoplasia: Staining Outcomes and Potential Clues for Determining Tumor Origin. Endocr Pathol [Internet]. Springer; 2020 [cited 2023 Jul 11];31:401–10. Available from: https://link.springer.com/article/10.1007/s12022-020-09645-y Agaimy A, Erlenbach-Wünsch K, Konukiewitz B, Schmitt AM, Rieker RJ, Vieth M, et al. ISL1 expression is not restricted to pancreatic well-differentiated neuroendocrine neoplasms, but is also commonly found in well and poorly differentiated neuroendocrine neoplasms of extrapancreatic origin. Mod Pathol 2013 267 [Internet]. Nature Publishing Group; 2013 [cited 2023 Jul 11];26:995–1003. Available from: https://www.nature.com/articles/modpathol201340 Maleki Z, Nadella A, Nadella M, Patel G, Patel S, Kholová I. INSM1, a Novel Biomarker for Detection of Neuroendocrine Neoplasms: Cytopathologists’ View. Diagnostics [Internet]. Multidisciplinary Digital Publishing Institute (MDPI); 2021 [cited 2023 Jul 11];11. Available from: /pmc/articles/PMC8700458/ Modlin IM, Gustafsson BI, Moss SF, Pavel M, Tsolakis A V., Kidd M. Chromogranin A-biological function and clinical utility in neuro endocrine tumor disease. Ann Surg Oncol [Internet]. Springer; 2010 [cited 2023 Aug 4];17:2427–43. Available from: https://link.springer.com/article/10.1245/s10434-010-1006-3 Rindi G, Klimstra DS, Abedi-Ardekani B, Asa SL, Bosman FT, Brambilla E, et al. A common classification framework for neuroendocrine neoplasms: an International Agency for Research on Cancer (IARC) and World Health Organization (WHO) expert consensus proposal. Mod Pathol [Internet]. Elsevier; 2018 [cited 2023 Aug 4];31:1770–86. Available from: http://www.modernpathology.org/article/S0893395222011322/fulltext Juhlin CC. Challenges in Paragangliomas and Pheochromocytomas: from Histology to Molecular Immunohistochemistry. Endocr Pathol 2021 322 [Internet]. Springer; 2021 [cited 2023 Aug 4];32:228–44. Available from: https://link.springer.com/article/10.1007/s12022-021-09675-0 Szalat A, Fraenkel M, Doviner V, Salmon A, Gross DJ. Malignant pheochromocytoma: Predictive factors of malignancy and clinical course in 16 patients at a single tertiary medical center. Endocrine [Internet]. Humana Press Inc.; 2011 [cited 2023 Aug 4];39:160–6. Available from: https://link.springer.com/article/10.1007/s12020-010-9422-5 D’Herbomez M, Gouze V, Huglo D, Nocaudie M, Pattou F, Proye C, et al. Chromogranin A Assay and 131I-MIBG Scintigraphy for Diagnosis and Follow-Up of Pheochromocytoma. J Nucl Med [Internet]. Society of Nuclear Medicine; 2001 [cited 2023 Aug 4];42:993–7. Available from: https://jnm.snmjournals.org/content/42/7/993 Stenman A, Svahn F, Hojjat-Farsangi M, Zedenius J, Söderkvist P, Gimm O, et al. Molecular Profiling of Pheochromocytoma and Abdominal Paraganglioma Stratified by the PASS Algorithm Reveals Chromogranin B as Associated with Histologic Prediction of Malignant Behavior. Am J Surg Pathol. Lippincott Williams and Wilkins; 2019;43:409–21. Lan MS, Breslin MB. Structure, expression, and biological function of INSM1 transcription factor in neuroendocrine differentiation. FASEB J [Internet]. The Federation of American Societies for Experimental Biology; 2009 [cited 2023 Aug 5];23:2024. Available from: /pmc/articles/PMC2704596/ Tanigawa M, Nakayama M, Taira T, Hattori S, Mihara Y, Kondo R, et al. Insulinoma-associated protein 1 (INSM1) is a useful marker for pancreatic neuroendocrine tumor. Med Mol Morphol [Internet]. Springer Tokyo; 2018 [cited 2023 Aug 5];51:32–40. Available from: https://link.springer.com/article/10.1007/s00795-017-0167-6 Rosenbaum JN, Guo Z, Baus RM, Werner H, Rehrauer WM, Lloyd R V. INSM1: A Novel Immunohistochemical and Molecular Marker for Neuroendocrine and Neuroepithelial Neoplasms. Am J Clin Pathol [Internet]. Oxford Academic; 2015 [cited 2023 Aug 5];144:579–91. Available from: https://dx.doi.org/10.1309/AJCPGZWXXBSNL4VD Kosuke Fujino1, 2 KY, Kudoh1 S, Motooka1 Y, Sato1 Y, Wakimoto3 J, Kubota3 I, et al. INSM1 is the best marker for the diagnosis of neuroendocrine tumors: comparison with CGA, SYP and CD56. Int J Clin Exp Pathol. 2017;10(5):5393–405. Xu X, Wang G, Duan Y, Huo Z. Prognostic value and non-neuroendocrine role of INSM1 in small cell lung cancer. Pathol - Res Pract. Urban & Fischer; 2022;229:153693. Minami K, Jimbo N, Tanaka Y, Ogawa H, Hokka D, Nishio W, et al. Insulinoma-associated protein 1 is a prognostic biomarker in pulmonary high-grade neuroendocrine carcinoma. J Surg Oncol [Internet]. John Wiley & Sons, Ltd; 2020 [cited 2023 Aug 5];122:243–53. Available from: https://onlinelibrary.wiley.com/doi/full/10.1002/jso.25960 Razvi H, Tsang JY, Poon IK, Chan SK, Cheung SY, Shea KH, et al. INSM1 is a novel prognostic neuroendocrine marker for luminal B breast cancer. Pathology. Elsevier; 2021;53:170–8. Jensen J. Gene regulatory factors in pancreatic development. Dev Dyn [Internet]. John Wiley & Sons, Ltd; 2004 [cited 2023 Aug 5];229:176–200. Available from: https://onlinelibrary.wiley.com/doi/full/10.1002/dvdy.10460 Schmitt AM, Riniker F, Anlauf M, Schmid S, Soltermann A, Moch H, et al. Islet 1 (Isl1) expression is a reliable marker for pancreatic endocrine tumors and their metastases. Am J Surg Pathol [Internet]. 2008 [cited 2023 Aug 5];32:420–5. Available from: https://journals.lww.com/ajsp/Fulltext/2008/03000/Islet_1__Isl1__Expression_is_a_Reliable_Marker_for.10.aspx Hermann G, Konukiewitz B, Schmitt A, Perren A, Klöppel G. Hormonally defined pancreatic and duodenal neuroendocrine tumors differ in their transcription factor signatures: Expression of ISL1, PDX1, NGN3, and CDX2. Virchows Arch [Internet]. Springer; 2011 [cited 2023 Aug 5];459:147–54. Available from: https://link.springer.com/article/10.1007/s00428-011-1118-6 Graham RP, Shrestha B, Caron BL, Smyrk TC, Grogg KL, Lloyd R V., et al. Islet-1 is a sensitive but not entirely specific marker for pancreatic neuroendocrine neoplasms and their metastases. Am J Surg Pathol [Internet]. 2013 [cited 2023 Aug 5];37:399–405. Available from: https://journals.lww.com/ajsp/Fulltext/2013/03000/Islet_1_Is_a_Sensitive_But_Not_Entirely_Specific.10.aspx Hattori Y, Kanamoto N, Kawano K, Iwakura H, Sone M, Miura M, et al. Molecular characterization of tumors from a transgenic mouse adrenal tumor model: Comparison with human pheochromocytoma. Int J Oncol [Internet]. Spandidos Publications; 2010 [cited 2023 Aug 6];37:695–705. Available from: http://www.spandidos-publications.com/10.3892/ijo_00000719/abstract Dong J, Asa SL, Drucker DJ. Islet Cell and Extrapancreatic Expression of the LIM Domain Homeobox Gene isl-1. Mol Endocrinol [Internet]. Oxford Academic; 1991 [cited 2023 Aug 6];5:1633–41. Available from: https://dx.doi.org/10.1210/mend-5-11-1633 Zierhut B, Daneva T, Gartner W, Brunnmaier B, Mineva I, Berggård T, et al. Setagin and secretagogin-R22: Posttranscriptional modification products of the secretagogin gene. Biochem Biophys Res Commun. Academic Press; 2005;329:1193–9. Dong Y, Li Y, Liu R, Li Y, Zhang H, Liu H, et al. Secretagogin, a marker for neuroendocrine cells, is more sensitive and specific in large cell neuroendocrine carcinoma compared with the markers CD56, CgA, Syn and Napsin A. Oncol Lett [Internet]. Spandidos Publications; 2020 [cited 2023 Aug 6];19:2223–30. Available from: http://www.spandidos-publications.com/10.3892/ol.2020.11336/abstract Lai M, Lü B, Xing X, Xu E, Ren G, Huang Q. Secretagogin, a novel neuroendocrine marker, has a distinct expression pattern from chromogranin A. Virchows Arch [Internet]. Springer; 2006 [cited 2023 Aug 6];449:402–9. Available from: https://link.springer.com/article/10.1007/s00428-006-0263-9 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. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4322745","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":296608019,"identity":"890e3520-34d4-4967-bfce-651efe3c3ea8","order_by":0,"name":"Mehmet Sözen","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA90lEQVRIiWNgGAWjYFACHgTz8J8KIMnM3ECElgQwi/EBzxmQFkbitTAb8LaBteLXotvee3TDxx91cvLtvcckJOfVRvO3A7X8qNiGU4vZmXNpN2ckHDZm7DmXJmG47XjujMOMDYw9Z27j1nIjx+w2T8KBxGaJHDOJxG3HchuAWpgZ2/Bouf/G7PafhLrENvk3ZhIH5xzLnU9Qyw0es9sMCcyJPRI8xoaNDTW5GwhqOZNjdrMn7bCxBE+O4WOGYwdyNwK1HMTrl+NnzG78sAGF2BmDwww1dbnzzh8++OBHBW4t6OAwmDxAtHogqCNF8SgYBaNgFIwQAAAIR17etE4fuAAAAABJRU5ErkJggg==","orcid":"","institution":"Kocaeli University Faculty of Medicine","correspondingAuthor":true,"prefix":"","firstName":"Mehmet","middleName":"","lastName":"Sözen","suffix":""},{"id":296608020,"identity":"943f96dc-4c4b-453a-a471-c8efc56bba84","order_by":1,"name":"Gupse Turan","email":"","orcid":"","institution":"Kocaeli University Faculty of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Gupse","middleName":"","lastName":"Turan","suffix":""},{"id":296608021,"identity":"3bf8f197-fd7e-47ef-b8b9-e55abe6bc670","order_by":2,"name":"Zeynep Cantürk","email":"","orcid":"","institution":"Kocaeli University Faculty of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Zeynep","middleName":"","lastName":"Cantürk","suffix":""},{"id":296608022,"identity":"7ae11acc-1794-494a-8789-8ad7a7ce9b43","order_by":3,"name":"Berrin Çetinarslan","email":"","orcid":"","institution":"Kocaeli University Faculty of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Berrin","middleName":"","lastName":"Çetinarslan","suffix":""},{"id":296608023,"identity":"c908b9cb-1638-4900-8450-4c209568f8ce","order_by":4,"name":"Alev Selek","email":"","orcid":"","institution":"Kocaeli University Faculty of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Alev","middleName":"","lastName":"Selek","suffix":""},{"id":296608024,"identity":"4db799f9-9c2f-472e-8719-942d1f9176ad","order_by":5,"name":"Mesude Tosun","email":"","orcid":"","institution":"Kocaeli University Faculty of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Mesude","middleName":"","lastName":"Tosun","suffix":""},{"id":296608026,"identity":"f4958eaf-72be-4b48-ae34-b59ea9d2f184","order_by":6,"name":"Aziz Hakkı Civriz","email":"","orcid":"","institution":"Kocaeli University Faculty of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Aziz","middleName":"Hakkı","lastName":"Civriz","suffix":""},{"id":296608028,"identity":"3e928a10-ab37-444e-87ea-468e66277185","order_by":7,"name":"Burcu Sevinç","email":"","orcid":"","institution":"Kocaeli University Faculty of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Burcu","middleName":"","lastName":"Sevinç","suffix":""},{"id":296608029,"identity":"2c4cff26-fe6d-4ba5-952c-6f052dd33517","order_by":8,"name":"Emre Gezer","email":"","orcid":"","institution":"Kocaeli University Faculty of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Emre","middleName":"","lastName":"Gezer","suffix":""},{"id":296608030,"identity":"75daeea3-4fc2-490e-a102-48ccf3855475","order_by":9,"name":"Damla Köksalan","email":"","orcid":"","institution":"Kocaeli University Faculty of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Damla","middleName":"","lastName":"Köksalan","suffix":""}],"badges":[],"createdAt":"2024-04-25 08:38:24","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4322745/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4322745/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":56036215,"identity":"eebec6b8-2d8a-4f99-b0d7-4fbb5ef0c5b8","added_by":"auto","created_at":"2024-05-07 18:43:17","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":18421,"visible":true,"origin":"","legend":"\u003cp\u003eH-scores box plot of CgA, INSM1, ISL1 and SECG expression in PCCs.\u003c/p\u003e","description":"","filename":"figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4322745/v1/1c7ac9b33c4492f1e0f5f94e.jpg"},{"id":68780539,"identity":"0d4976fc-eb6f-4cba-a789-f11071e37339","added_by":"auto","created_at":"2024-11-12 02:38:42","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":585240,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4322745/v1/b3950a48-e1fe-47ef-9305-774c4bc3ff30.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eDiagnostic and prognostic utility of INSM1, ISL1 and secretagogin in pheochromocytoma\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003ePheochromocytomas (PCCs) are rare neuroendocrine tumors originating from chromaffin cells of the adrenal medulla and producing catecholamines. PCCs can occur at any age and peak in the 3rd and 4th decades. It's estimated prevalence between 0.1\u0026ndash;0.6% and incidence 3\u0026ndash;8 cases per million population per year. PCCs most commonly present with catecholamine excess symptoms such as headache, tremor, diaphoresis, hypertension, palpitations. However, approximately 4\u0026ndash;5% of cases detected incidentally on radiological methods while screening other causes [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePathologists can recognize the PCCs easily when typical morphology is present however it can be challenging in atypical cases. Immunohistochemistry (IHC) play important confirmatory role in diagnosis of PCCs. Classically, PCCs chromaffin cells are positive for chromogranin A (CgA) and synaptophysin and sustentacular cells are positive for S100. The general opinion is that the most specific neuroendocrine marker is CgA [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. However, due to some limitations of these markers, new markers such as GATA3, cyclooxygenase 2, heat-shock protein 90, cell surface glycoprotein CD44 are recommended for diagnosis and risk stratification [\u003cspan additionalcitationids=\"CR3\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePCC can occur with metastases even a quarter of a century after the initial surgery [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. In the 2022 World Health Organization (WHO) classification, PCC are defined as malignant neoplasms with variable metastatic potential [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Before the idea that all PCCs should be considered malignant, a number of scoring systems were used to predict the risk of metastasis [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. However, recent studies have shown that high scores may lead to an overestimation of the risk of metastasis [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Therefore, it is undeniable fact that stronger arguments are needed to predict the risk of metastasis. In recent years, new IHC markers with high diagnostic accuracy have been used for neuroendocrine neoplasms such as insulin gene enhancer protein 1 (ISL1), insulinoma-associated protein 1 (INSM1) and secretagogin (SECG). These molecules are involved in the neuroendocrine cell differentiation steps, and many studies have reported that they are highly sensitive markers in the diagnosis of neuroendocrine neoplasms [\u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. In this study; we investigated immunohistochemical expression of ISL1, INSM1 and SECG in PCC tissues in order to define their diagnostic and prognostic value.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003e This study was approved by the local ethics committee (Project number: 2021/271). All data of PCC patients who were operated between 2010\u0026ndash;2021, were retrieved from hospital archive system. After eliminating patients with missing data, 30 patients were included in the study. patients without preparations suitable for staining and patients with mixed tumors were excluded. The preoperative clinical status, symptoms and comorbidities and postoperative follow-up results of these patients were recorded.\u003c/p\u003e \u003cp\u003eRadiological reevaluation was performed by a single radiologist on archived images, via the communication system (PACS) (Sectra IDS 7, Sectra, Link\u0026ouml;ping, Sweden). Computed tomography (CT) scans had been performed with 64 multidetector computed tomography (MDCT) scanner (Aquilion, Toshiba Healthcare), and magnetic resonance imaging (MRI) with 1.5 or 3-T systems (Philips Achieva Netherlands).\u003c/p\u003e \u003cp\u003eThe tissue preparations of the study cases were re-evaluated by two pathologists, PASS score and GAPP score were given. A PASS of \u0026lt;\u0026thinsp;4 accurately identified all histologically benign and clinically benign tumors [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. The total GAPP points were then classified into follows: Well-differentiated type (0\u0026ndash;2 points), Moderately differentiated type (3\u0026ndash;6 points) and Poorly differentiated type (7\u0026ndash;10 points) [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. After this subclassification, 4 \u0026micro;m thick paraffin block sections were prepared from all cases and stained using INSM1, ISL1 and SECG antibodies. Staining was performed on a Ventana automatic staining device (Roche Ventana) using Ventana Optiview and Ultraview DAB kits. Immunohistochemical study preparations were evaluated simultaneously by two pathologists. Both staining intensity score (Strong\u0026thinsp;=\u0026thinsp;3, Moderate\u0026thinsp;=\u0026thinsp;2, Weak\u0026thinsp;=\u0026thinsp;1, Absent\u0026thinsp;=\u0026thinsp;0) and staining percentage (0-100) were obtained. The H-score (0-300) was obtained by multiplying the staining percentages and staining intensity score. Afterwards, The H-score expression level was categorized as follows; low (H-score, 0-100), moderate (H-score, 100\u0026ndash;200), and high (H-score, 200\u0026ndash;300). Ki67 and CgA were re-evaluated on previously stained immunohistochemistry preparations obtained from archive.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eAll statistical analyses were performed using SPSS 20.0 (IBM Corp., Armonk, NY, USA). Shapiro-Wilk\u0026rsquo;s test was used to assess the assumption of normality. Continuous variables were presented with mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation or (in the case of non-normal distribution) median (interquartile range (IQR)). Categorical variables were summarized as counts and percentages. Associations between continuous variables were determined by Spearman's correlation analysis. Comparisons of continuous variables between groups were carried out using Mann-Whitney U test and Kruskal-Wallis test. Dependent group comparisons were performed by Friedman's two-way analysis of variance. Dunn's test was used for the multiple comparisons. A p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eThe male-to-female ratio in the PCC group was 1:2.75 and the mean age at the diagnosis was 50.5 (\u0026plusmn;\u0026thinsp;15.9) years and during study was 56.8 (\u0026plusmn;\u0026thinsp;16.4) years. Eight patients were asymptomatic and diagnosed incidentally. The most common complaint in symptomatic patients was high blood pressure, most of which was permanent. 6 patients had history of malignancy which were Prostate cancer (n\u0026thinsp;=\u0026thinsp;1), lip cancer (n\u0026thinsp;=\u0026thinsp;1), colon cancer (n\u0026thinsp;=\u0026thinsp;1), endometrium cancer (n\u0026thinsp;=\u0026thinsp;1), papillary thyroid cancer (n\u0026thinsp;=\u0026thinsp;1) and medullary thyroid cancer (n\u0026thinsp;=\u0026thinsp;1). The patient with medullary thyroid cancer had a RET proto-oncogene mutation caused to MEN2A syndrome. 17 patients (56.7%) had norepinephrine dominant catecholamine elevation, while 3 patients (10.0%) had epinephrine dominant, 6 patients (20.0%) had both catecholamine secretion. We couldn\u0026rsquo;t detect any increase in catecholamine secretion of the remaining 4 patients (13.3%) although several times of testing.\u003c/p\u003e \u003cp\u003eGenetic analysis could be performed in ten patients (33.3%), of whom 7 (23.3%) had no pathogenic mutation. Of the remaining patients, one patient had SDHD, one had NF and one had RET mutation.\u003c/p\u003e \u003cp\u003eThe lesions were mostly localized to the right adrenal gland and were mostly mixed-characterized lesions with cystic areas, calcifications and necrosis. The minimum tumor size was 11 mm, while the maximum tumor size was 135 mm. HU values of all lesions were \u0026gt;\u0026thinsp;10 HU (min HU:18, max HU:56). All demographic, clinical and radiological characteristics were given in Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\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\u003eDemographic and clinical characteristics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eValue\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e56.8 (\u0026plusmn;\u0026thinsp;16.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiagnosis age (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50.5 (\u0026plusmn;\u0026thinsp;15.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22 (73.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 (26.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIncidental diagnosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 (26.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSymptoms\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePalpitation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18 (60.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeadache\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12 (40.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExcessive sweating\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 (33.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFlushing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9 (30.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDyspeptic disorder\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 (26.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePsychiatric state disorder\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (3.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTremor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (3.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDyspnea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (3.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24 (80%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension pattern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSustained\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13 (54.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParoxysmal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11 (45.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther diseases\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes mellitus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12 (40.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (20.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCoronary artery disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (16.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCerebrovascular disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (10.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHepatitis B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (3.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAsthma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (3.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDyslipidemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (3.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSyndromic cases\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (6.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBiochemical parameters\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePreoperative urine-free metanephrine (\u0026micro;g/24 h)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e239.0 (157.0-1019.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePreoperative urine-free normetanephrine (\u0026micro;g/24 h)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2026.0 (1051.0-4592.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePostoperative urine-free metanephrine (\u0026micro;g/24 h)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e103.0 (53.2\u0026ndash;126.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePostoperative urine-free normetanephrine (\u0026micro;g/24 h)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e316.5 (250.7\u0026ndash;383.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRadiological findings\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiagnostic method\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (23.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13 (43.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCT\u0026thinsp;+\u0026thinsp;MR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 (33.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTumor size (mm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45.0 (35.0-54.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLocation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20 (66.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLeft\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 (33.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStructure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSolid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11 (36.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCystic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (20.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSolid\u0026thinsp;+\u0026thinsp;cystic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13 (43.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIrregular Border\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (3.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eShape\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOval\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23 (76.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRound\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (23.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePeripheral tissue invasion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (3.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePeripheral rim\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11 (36.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCalcification\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (10.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNecrosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18 (60.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTumor HU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33.06 (\u0026plusmn;\u0026thinsp;8.75)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAll patients mean Ki67 was 2.17\u0026thinsp;\u0026plusmn;\u0026thinsp;1.46. According to the PASS score, most patients were in the potentially aggressive behavior group (score\u0026thinsp;\u0026ge;\u0026thinsp;4), while according to the GAPP score, most of them were in the moderately differentiated type (3\u0026ndash;6 points) group. All cases were positive for CgA neuroendocrine tumor marker. INSM1 and ISL1, which are novel second generation neuroendocrine immunohistochemical markers, were positive in 21 (70%) and 26 (86.7%) of the patients, respectively. However, SECG was positive only in 6 patients (20%) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). INSM1 and ISL1 staining intensity was mostly weak to moderate, whereas SECG did not show a very large amount of staining (Fig.\u0026nbsp;1).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePathological features and IHC staining intensities\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKi67 (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.0 (0.9-3.0)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7 (23.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u0026ndash;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e17 (56.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6 (20.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePASS score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4.8 (\u0026plusmn;\u0026thinsp;2.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBenign clinical behavior (score\u0026thinsp;\u0026lt;\u0026thinsp;4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9 (30.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePotential aggressive behaviour (score\u0026thinsp;\u0026ge;\u0026thinsp;4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e21 (70.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGAPP score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4.4 (\u0026plusmn;\u0026thinsp;1.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWell differentiated type (0\u0026ndash;2 points)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4 (13.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModerately differentiated type (3\u0026ndash;6 points)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e22 (73.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoorly differentiated type (7\u0026ndash;10 points)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4 (13.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCgA staining intensity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeak\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2 (6.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9 (30.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStrong\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e19 63.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eISNM1 staining intensity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9 (30.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeak\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11 (36.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9 (30.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStrong\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1 (3.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eISL1 staining intensity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4 (13.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeak\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6 (20.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13 (43.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStrong\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7 (23.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSECG staining intensity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e24 (80.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeak\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5 (16.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStrong\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1 (3.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe mean H-score of all cases was positive for CgA at the highest expression level. Among the second generation neuroendocrine immunohistochemical markers, ISL1 had the highest H-score. Their H-score expression levels are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and expression variations are better illustrated in a H-score plot graphic (Fig.\u0026nbsp;2).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eExpression of traditional and second generation neuroendocrine IHC markers\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003ep value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCgA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eISNM1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eISL1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSECG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCgA vs INSM1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCgA vs ISL1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eCgA vs SECG\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eH-score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e300 (200\u0026ndash;300)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (3.75-80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e120 (20-202.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0 (0\u0026ndash;0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.075\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow expression\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (6.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25 (83.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12 (40.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e29 (96.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModerate expression\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 (33.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (13.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11 (36.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh expression\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18 (60.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (3.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7 (23.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1 (3.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eCorrelation analysis revealed a negative correlation between ISL1 and tumor HU and a positive correlation between INSM1 and Ki67 (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCorrelation analysis of traditional and second generation neuroendocrine IHC markers\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCgA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eISL1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eINSM1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSECG\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-,148\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e,039\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-,049\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e,161\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e,436\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e,838\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e,795\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e,395\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDiagnosis age\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-,176\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e,231\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e,098\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e,134\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e,351\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e,220\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e,607\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e,480\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePreoperative urine-free metanephrine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e,166\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-,016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e,078\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-,123\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e,379\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e,935\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e,683\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e,517\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePreoperative urine-free normetanephrine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-,113\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-,272\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-,141\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-,082\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e,551\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e,145\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e,457\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e,666\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePostoperative urine-free metanephrine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e,019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-,134\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-,185\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-,007\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e,921\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e,479\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e,328\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e,970\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePostoperative urine-free normetanephrine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-,157\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e,097\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e,030\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-,116\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e,408\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e,608\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e,876\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e,542\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTumor HU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e,021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-,803\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-,378\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-,049\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e,935\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e,000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e,135\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e,851\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTumor size\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-,100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-,162\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-,209\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-,106\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e,601\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e,392\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e,268\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e,576\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGAPP score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-,074\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e,008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e,008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-,221\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e,697\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e,968\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e,965\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e,242\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePASS score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-,019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e,019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-,046\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-,222\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e,921\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e,920\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e,809\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e,239\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eKi67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-,011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e,157\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e,475\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-,014\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e,956\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e,406\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e,008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e,942\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eNone of the patients had metastases at the time of diagnosis and surgical remission was achieved in all patients. The follow-up period of the patients included in the study was 69 (32.25\u0026ndash;106.0) months. In one patient, new liver metastases were detected approximately 24 months after the initial surgery. This patient underwent 8 cycles of \u003csup\u003e177\u003c/sup\u003eLu treatment. But the patient died due to progressive disease\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe diagnosis of neuroendocrine tumors (NETs) is based on histopathological confirmation of neuroendocrine differentiation. Chromogranin A (CgA) is an acidic, monomeric protein released by exocytosis from neuroendocrine secretory granules. CgA is a sensitive but non-specific IHC marker for NETs [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. CgA usually shows strong positive staining in NETs but is focal and weak or absent in most neuroendocrine carcinomas (NECs) [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Pheochromocytomas (PCCs) showing a nested growth pattern (zellballen appearance) of chief cells with basophilic cytoplasm are strongly positive for the CgA [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Elevated serum CgA has been associated with large tumor tissue and metastasis in small studies [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. However, tissue expression of CgA has not been shown to distinguish between malignant and benign tumors or to predict prognosis [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Meanwhile, downregulation of chromogranin B (CgB), which belongs to the same family as CgA, was observed in PCCs with high PASS score and was associated with shorter survival [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDue to the limitations of well-known NET markers in the diagnosis and determining prognosis, several new markers have emerged, such as INSM1, ISL1 and SECG, which have high sensitivity and specificity levels for diagnosis. These markers have been evaluated in small groups of PCCs in a few NET studies in the literature, but no large PCC-specific studies have been conducted. Therefore, we investigated the clinicopathologic significance of second generation neuroendocrine immunohistochemical markers in PCC patients. In this study, we showed that INSM1 and ISL1 can be used to diagnose PCC, but not SECG. Furthermore, INSM1 expression was positively correlated with higher Ki67 proliferative index levels. And moreover, ISL1 expression showed an inverse correlation with tumor HU on CT imaging\u003c/p\u003e \u003cp\u003eINSM1 is a transcription factor involved in the differentiation of embryonic neuroendocrine cells. Subsequent studies show that INSM1 expression is a highly specific marker for NETs in lung, gastrointestinal tract, pancreas and breast, medullary thyroid carcinoma, pheochromocytoma and pituitary adenoma [\u003cspan additionalcitationids=\"CR21\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Rosenbaum et al. found INSM1 expression in 88.3% of neoplastic NET tissue detected by IHC [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. In the study by Fujino et al., INSM1 was found to be positive in 71.4% (5/7) of PCC patients and staining intensity rates varied between 5\u0026ndash;50% and conventional NET markers mean H-score were superior to INSM1 [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. In another study, INSM1 staining was found in all 7 PCC patients [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Beyond its diagnostic significance, it confirmed that INSM1 is an independent prognostic factor in small cell lung cancer [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Similarly, in pulmonary high-grade neuroendocrine carcinoma patients, overall survival and recurrence-free survival were significantly poorer in the INSM1 positive group [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Conversely, INSM1 expression in luminal B breast cancers was associated with significantly better survival [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. INSM1 was demonstrated by IHC in the majority of cases in this study. In addition, it was found to be associated with Ki67, which has been proposed as a reliable marker to identify cases with a high risk of metastatic spread and poor prognosis in PCC. This result suggests that INSM1 may be a marker that can predict prognosis as well as diagnosis in PCC patients.\u003c/p\u003e \u003cp\u003eISL1 is a homeobox-gene\u0026ndash;related transcription factor involved in pancreatic exocrine and endocrine differentiation and regulates insulin gene expression [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Initially, researchers suggested that from a diagnostic point of view, ISL1 immunoreactivity would indicate that the primary site of a metastatic NET was the pancreas [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Subsequent studies have also shown ISL1 expression in duodenal, rectal, colonic and ileal NET, Merkel cell carcinomas, pulmonary small cell NET, medullary thyroid carcinomas and pheochromocytomas [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. In the study by Agaimy et al., ISL1 showed strong (\u0026gt;\u0026thinsp;50%) staining intensity in all six PCC patients [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Similarly, Hattori et al. have shown that the expression of ISL1 genes is upregulated in human PCC tissue [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. In a preclinical study, ISL1 immunoreactivity was widely distributed in PCC cell line [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. In this study, ISL1 immunoreactivity was examined in a large group of PCCs and a high rate of positivity was observed in accordance with the literature. Moreover, it was also similar to CgA in terms of H-score. However, no correlation was observed between ISL1 expression and prognostic markers beyond diagnosis. We found a negative association between ISL1 and tumor HU, but this has never been studied before in the literature. The diagnostic or prognostic significance of this may be improved by further research.\u003c/p\u003e \u003cp\u003eSecretagogin is a 32 kDa hexa-EF-el Ca2\u0026thorn;-binding protein with homology to calbindin D28k and calretinin, encoded by genes located on chromosome 6 and is involved in cell growth, differentiation and replication through calcium signaling modulation [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. In subsequent studies, SECG immunoreactivity has been demonstrated in many neuroendocrine tumors such as well-differentiated neuroendocrine tumors of pancreas, ovarian carcinoid, pituitary adenoma, medullary thyroid cancer, small cell lung cancer, large cell neuroendocrine carcinoma [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. However in most PCC patients, SECG showed negative or weak immunoreactivity [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Juhlin et al. similarly showed negative SECG immunoreactivity in 83.3% (5/6) of PCC cases [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. In metastatic NETs of unknown primary, they suggested that PCC or paraganglioma should be investigated in a tumor exhibiting ISL1 (+), INSM1 (+) and SECG (-) according to second-generation neuroendocrine immunohistochemical marker results. The present study supports the literature data and SECG was found to be negative or weakly positive in the majority of cases and could not be associated with prognostic markers.\u003c/p\u003e \u003cp\u003eOur study has several limitations. First, this is a retrospective study and the small case population may reduce statistical power. Second, we included cases over a 12-year period, so some antigens may have been lost to different degrees or have reduced power. Third, since the genetic background of all patients is unknown, it is not clear how second generation neuroendocrine immunohistochemical markers work in different genotypes.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eOur study demonstrated that INSM1, ISL1 and SECG, which are second generation neuroendocrine immunohistochemical markers, can be used in the differential diagnosis of pheochromocytoma. Since CgA is sensitive but non-specific, these markers can be used supportively to reveal the nature of a mass. Furthermore, the second generation IHC NET markers may also have prognostic significance beside their diagnostic role, but further larger studies with longer follow-up period are needed because metastatic disease may be diagnosed even after 20 years.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eInsulin gene enhancer protein 1 (ISL1)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eInsulinoma-associated protein 1 (INSM1)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSecretagogin (SECG)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePheochromocytoma (PCC)\u003c/p\u003e\n\u003cp\u003eChromogranin A (CgA)\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval:\u003c/strong\u003e This study was approved by Kocaeli University Non-Interventional Clinical Research Ethics Committee with project number 2021/271.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u003c/strong\u003e Not applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and material:\u003c/strong\u003e The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u003c/strong\u003e The authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e This project was supported by Kocaeli University Scientific Research Projects Coordination Unit with project number 2756.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contribution:\u003c/strong\u003e MS: Study conception, material preparation, data collection, analysis and manuscript writing; GT: Pathological interpretation and critical review of manuscript; ZC: Interpretation of results and statistical analysis; BC: Data interpretation and critical review of manuscript; AS: Study conception and critical review of manuscript; MT: Radiological data interpretation; AHC: Pathological interpretation and data collection; BC, EG, DK: Critical review of literature, material preparation, data collection. All authors have read and approved the manuscript final version.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments:\u003c/strong\u003e None\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSbardella E, Grossman AB. Pheochromocytoma: An approach to diagnosis. Best Pract Res Clin Endocrinol Metab. Bailli\u0026egrave;re Tindall; 2020;34:101346. \u003c/li\u003e\n\u003cli\u003eCheung VKY, Gill AJ, Chou A. Old, New, and Emerging Immunohistochemical Markers in Pheochromocytoma and Paraganglioma. Endocr Pathol [Internet]. Humana Press Inc.; 2018 [cited 2023 Jul 11];29:169\u0026ndash;75. Available from: https://link.springer.com/article/10.1007/s12022-018-9534-7\u003c/li\u003e\n\u003cli\u003eSalmenkivi K, Haglund C, Ristim\u0026auml;ki A, Arola J, Heikkil\u0026auml; P. Increased Expression of Cyclooxygenase-2 in Malignant Pheochromocytomas. J Clin Endocrinol Metab [Internet]. Oxford Academic; 2001 [cited 2023 Jul 11];86:5615\u0026ndash;9. Available from: https://dx.doi.org/10.1210/jcem.86.11.8052\u003c/li\u003e\n\u003cli\u003eAsa SL, Ezzat S, Mete O. The Diagnosis and Clinical Significance of Paragangliomas in Unusual Locations. J Clin Med 2018, Vol 7, Page 280 [Internet]. Multidisciplinary Digital Publishing Institute; 2018 [cited 2023 Jul 11];7:280. Available from: https://www.mdpi.com/2077-0383/7/9/280/htm\u003c/li\u003e\n\u003cli\u003eThai E, Gnetti L, Gilli A, Caruana P, Valle RD, Buti S. Very late recurrence of an apparently benign pheochromocytoma. J Cancer Res Ther [Internet]. Medknow Publications; 2015 [cited 2023 Aug 10];11:1226\u0026ndash;9. Available from: https://journals.lww.com/cancerjournal/Fulltext/2015/11040/Very_late_recurrence_of_an_apparently_benign.143.aspx\u003c/li\u003e\n\u003cli\u003eMete O, Asa SL, Gill AJ, Kimura N, de Krijger RR, Tischler A. Overview of the 2022 WHO Classification of Paragangliomas and Pheochromocytomas. Endocr Pathol 2022 331 [Internet]. Springer; 2022 [cited 2023 Aug 10];33:90\u0026ndash;114. Available from: https://link.springer.com/article/10.1007/s12022-022-09704-6\u003c/li\u003e\n\u003cli\u003eWHO Classification of Tumours Editorial Board: Endocrine and Neuroendocrine tumours, vol. 8. 5th edn. (International Agency for Research on Cancer, Lyon, France, 2022) [Internet]. [cited 2023 Aug 10]. Available from: https://tumourclassification.iarc.who.int/welcome/#\u003c/li\u003e\n\u003cli\u003eThompson LDR. Pheochromocytoma of the Adrenal gland Scaled Score (PASS) to separate benign from malignant neoplasms: a clinicopathologic and immunophenotypic study of 100 cases. Am J Surg Pathol [Internet]. 2002 [cited 2023 Aug 2];26:551\u0026ndash;66. Available from: https://europepmc.org/article/med/11979086\u003c/li\u003e\n\u003cli\u003eKimura N, Takayanagi R, Takizawa N, Itagaki E, Katabami T, Kakoi N, et al. Pathological grading for predicting metastasis in phaeochromocytoma and paraganglioma. Endocr Relat Cancer [Internet]. Bioscientifica Ltd; 2014 [cited 2023 Aug 2];21:405\u0026ndash;14. Available from: https://erc.bioscientifica.com/view/journals/erc/21/3/405.xml\u003c/li\u003e\n\u003cli\u003eStenman A, Zedenius J, Juhlin CC. Over-diagnosis of potential malignant behavior in MEN 2A-associated pheochromocytomas using the PASS and GAPP algorithms. Langenbeck\u0026rsquo;s Arch Surg [Internet]. Springer Verlag; 2018 [cited 2023 Aug 10];403:785\u0026ndash;90. Available from: https://link.springer.com/article/10.1007/s00423-018-1679-9\u003c/li\u003e\n\u003cli\u003eJuhlin CC, Zedenius J, H\u0026ouml;\u0026ouml;g A. Clinical Routine Application of the Second-generation Neuroendocrine Markers ISL1, INSM1, and Secretagogin in Neuroendocrine Neoplasia: Staining Outcomes and Potential Clues for Determining Tumor Origin. Endocr Pathol [Internet]. Springer; 2020 [cited 2023 Jul 11];31:401\u0026ndash;10. Available from: https://link.springer.com/article/10.1007/s12022-020-09645-y\u003c/li\u003e\n\u003cli\u003eAgaimy A, Erlenbach-W\u0026uuml;nsch K, Konukiewitz B, Schmitt AM, Rieker RJ, Vieth M, et al. ISL1 expression is not restricted to pancreatic well-differentiated neuroendocrine neoplasms, but is also commonly found in well and poorly differentiated neuroendocrine neoplasms of extrapancreatic origin. Mod Pathol 2013 267 [Internet]. Nature Publishing Group; 2013 [cited 2023 Jul 11];26:995\u0026ndash;1003. Available from: https://www.nature.com/articles/modpathol201340\u003c/li\u003e\n\u003cli\u003eMaleki Z, Nadella A, Nadella M, Patel G, Patel S, Kholov\u0026aacute; I. INSM1, a Novel Biomarker for Detection of Neuroendocrine Neoplasms: Cytopathologists\u0026rsquo; View. Diagnostics [Internet]. Multidisciplinary Digital Publishing Institute (MDPI); 2021 [cited 2023 Jul 11];11. Available from: /pmc/articles/PMC8700458/\u003c/li\u003e\n\u003cli\u003eModlin IM, Gustafsson BI, Moss SF, Pavel M, Tsolakis A V., Kidd M. Chromogranin A-biological function and clinical utility in neuro endocrine tumor disease. Ann Surg Oncol [Internet]. Springer; 2010 [cited 2023 Aug 4];17:2427\u0026ndash;43. Available from: https://link.springer.com/article/10.1245/s10434-010-1006-3\u003c/li\u003e\n\u003cli\u003eRindi G, Klimstra DS, Abedi-Ardekani B, Asa SL, Bosman FT, Brambilla E, et al. A common classification framework for neuroendocrine neoplasms: an International Agency for Research on Cancer (IARC) and World Health Organization (WHO) expert consensus proposal. Mod Pathol [Internet]. Elsevier; 2018 [cited 2023 Aug 4];31:1770\u0026ndash;86. Available from: http://www.modernpathology.org/article/S0893395222011322/fulltext\u003c/li\u003e\n\u003cli\u003eJuhlin CC. Challenges in Paragangliomas and Pheochromocytomas: from Histology to Molecular Immunohistochemistry. Endocr Pathol 2021 322 [Internet]. Springer; 2021 [cited 2023 Aug 4];32:228\u0026ndash;44. Available from: https://link.springer.com/article/10.1007/s12022-021-09675-0\u003c/li\u003e\n\u003cli\u003eSzalat A, Fraenkel M, Doviner V, Salmon A, Gross DJ. Malignant pheochromocytoma: Predictive factors of malignancy and clinical course in 16 patients at a single tertiary medical center. Endocrine [Internet]. Humana Press Inc.; 2011 [cited 2023 Aug 4];39:160\u0026ndash;6. Available from: https://link.springer.com/article/10.1007/s12020-010-9422-5\u003c/li\u003e\n\u003cli\u003eD\u0026rsquo;Herbomez M, Gouze V, Huglo D, Nocaudie M, Pattou F, Proye C, et al. Chromogranin A Assay and 131I-MIBG Scintigraphy for Diagnosis and Follow-Up of Pheochromocytoma. J Nucl Med [Internet]. Society of Nuclear Medicine; 2001 [cited 2023 Aug 4];42:993\u0026ndash;7. Available from: https://jnm.snmjournals.org/content/42/7/993\u003c/li\u003e\n\u003cli\u003eStenman A, Svahn F, Hojjat-Farsangi M, Zedenius J, S\u0026ouml;derkvist P, Gimm O, et al. Molecular Profiling of Pheochromocytoma and Abdominal Paraganglioma Stratified by the PASS Algorithm Reveals Chromogranin B as Associated with Histologic Prediction of Malignant Behavior. Am J Surg Pathol. Lippincott Williams and Wilkins; 2019;43:409\u0026ndash;21. \u003c/li\u003e\n\u003cli\u003eLan MS, Breslin MB. Structure, expression, and biological function of INSM1 transcription factor in neuroendocrine differentiation. FASEB J [Internet]. The Federation of American Societies for Experimental Biology; 2009 [cited 2023 Aug 5];23:2024. Available from: /pmc/articles/PMC2704596/\u003c/li\u003e\n\u003cli\u003eTanigawa M, Nakayama M, Taira T, Hattori S, Mihara Y, Kondo R, et al. Insulinoma-associated protein 1 (INSM1) is a useful marker for pancreatic neuroendocrine tumor. Med Mol Morphol [Internet]. Springer Tokyo; 2018 [cited 2023 Aug 5];51:32\u0026ndash;40. Available from: https://link.springer.com/article/10.1007/s00795-017-0167-6\u003c/li\u003e\n\u003cli\u003eRosenbaum JN, Guo Z, Baus RM, Werner H, Rehrauer WM, Lloyd R V. INSM1: A Novel Immunohistochemical and Molecular Marker for Neuroendocrine and Neuroepithelial Neoplasms. Am J Clin Pathol [Internet]. Oxford Academic; 2015 [cited 2023 Aug 5];144:579\u0026ndash;91. Available from: https://dx.doi.org/10.1309/AJCPGZWXXBSNL4VD\u003c/li\u003e\n\u003cli\u003eKosuke Fujino1, 2 KY, Kudoh1 S, Motooka1 Y, Sato1 Y, Wakimoto3 J, Kubota3 I, et al. INSM1 is the best marker for the diagnosis of neuroendocrine tumors: comparison with CGA, SYP and CD56. Int J Clin Exp Pathol. 2017;10(5):5393\u0026ndash;405. \u003c/li\u003e\n\u003cli\u003eXu X, Wang G, Duan Y, Huo Z. Prognostic value and non-neuroendocrine role of INSM1 in small cell lung cancer. Pathol - Res Pract. Urban \u0026amp; Fischer; 2022;229:153693. \u003c/li\u003e\n\u003cli\u003eMinami K, Jimbo N, Tanaka Y, Ogawa H, Hokka D, Nishio W, et al. Insulinoma-associated protein 1 is a prognostic biomarker in pulmonary high-grade neuroendocrine carcinoma. J Surg Oncol [Internet]. John Wiley \u0026amp; Sons, Ltd; 2020 [cited 2023 Aug 5];122:243\u0026ndash;53. Available from: https://onlinelibrary.wiley.com/doi/full/10.1002/jso.25960\u003c/li\u003e\n\u003cli\u003eRazvi H, Tsang JY, Poon IK, Chan SK, Cheung SY, Shea KH, et al. INSM1 is a novel prognostic neuroendocrine marker for luminal B breast cancer. Pathology. Elsevier; 2021;53:170\u0026ndash;8. \u003c/li\u003e\n\u003cli\u003eJensen J. Gene regulatory factors in pancreatic development. Dev Dyn [Internet]. John Wiley \u0026amp; Sons, Ltd; 2004 [cited 2023 Aug 5];229:176\u0026ndash;200. Available from: https://onlinelibrary.wiley.com/doi/full/10.1002/dvdy.10460\u003c/li\u003e\n\u003cli\u003eSchmitt AM, Riniker F, Anlauf M, Schmid S, Soltermann A, Moch H, et al. Islet 1 (Isl1) expression is a reliable marker for pancreatic endocrine tumors and their metastases. Am J Surg Pathol [Internet]. 2008 [cited 2023 Aug 5];32:420\u0026ndash;5. Available from: https://journals.lww.com/ajsp/Fulltext/2008/03000/Islet_1__Isl1__Expression_is_a_Reliable_Marker_for.10.aspx\u003c/li\u003e\n\u003cli\u003eHermann G, Konukiewitz B, Schmitt A, Perren A, Kl\u0026ouml;ppel G. Hormonally defined pancreatic and duodenal neuroendocrine tumors differ in their transcription factor signatures: Expression of ISL1, PDX1, NGN3, and CDX2. Virchows Arch [Internet]. Springer; 2011 [cited 2023 Aug 5];459:147\u0026ndash;54. Available from: https://link.springer.com/article/10.1007/s00428-011-1118-6\u003c/li\u003e\n\u003cli\u003eGraham RP, Shrestha B, Caron BL, Smyrk TC, Grogg KL, Lloyd R V., et al. Islet-1 is a sensitive but not entirely specific marker for pancreatic neuroendocrine neoplasms and their metastases. Am J Surg Pathol [Internet]. 2013 [cited 2023 Aug 5];37:399\u0026ndash;405. Available from: https://journals.lww.com/ajsp/Fulltext/2013/03000/Islet_1_Is_a_Sensitive_But_Not_Entirely_Specific.10.aspx\u003c/li\u003e\n\u003cli\u003eHattori Y, Kanamoto N, Kawano K, Iwakura H, Sone M, Miura M, et al. Molecular characterization of tumors from a transgenic mouse adrenal tumor model: Comparison with human pheochromocytoma. Int J Oncol [Internet]. Spandidos Publications; 2010 [cited 2023 Aug 6];37:695\u0026ndash;705. Available from: http://www.spandidos-publications.com/10.3892/ijo_00000719/abstract\u003c/li\u003e\n\u003cli\u003eDong J, Asa SL, Drucker DJ. Islet Cell and Extrapancreatic Expression of the LIM Domain Homeobox Gene isl-1. Mol Endocrinol [Internet]. Oxford Academic; 1991 [cited 2023 Aug 6];5:1633\u0026ndash;41. Available from: https://dx.doi.org/10.1210/mend-5-11-1633\u003c/li\u003e\n\u003cli\u003eZierhut B, Daneva T, Gartner W, Brunnmaier B, Mineva I, Bergg\u0026aring;rd T, et al. Setagin and secretagogin-R22: Posttranscriptional modification products of the secretagogin gene. Biochem Biophys Res Commun. Academic Press; 2005;329:1193\u0026ndash;9. \u003c/li\u003e\n\u003cli\u003eDong Y, Li Y, Liu R, Li Y, Zhang H, Liu H, et al. Secretagogin, a marker for neuroendocrine cells, is more sensitive and specific in large cell neuroendocrine carcinoma compared with the markers CD56, CgA, Syn and Napsin A. Oncol Lett [Internet]. Spandidos Publications; 2020 [cited 2023 Aug 6];19:2223\u0026ndash;30. Available from: http://www.spandidos-publications.com/10.3892/ol.2020.11336/abstract\u003c/li\u003e\n\u003cli\u003eLai M, L\u0026uuml; B, Xing X, Xu E, Ren G, Huang Q. Secretagogin, a novel neuroendocrine marker, has a distinct expression pattern from chromogranin A. Virchows Arch [Internet]. Springer; 2006 [cited 2023 Aug 6];449:402\u0026ndash;9. Available from: https://link.springer.com/article/10.1007/s00428-006-0263-9\u003c/li\u003e\n\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":"INSM1, ISL1, Secretagogin, Pheochromocytoma","lastPublishedDoi":"10.21203/rs.3.rs-4322745/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4322745/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eTo assess immunohistochemical expression of the second generation neuroendocrine immunohistochemical markers such as insulin gene enhancer protein 1 (ISL1), insulinoma-associated protein 1 (INSM1) and secretagogin (SECG) in pheochromocytoma (PCC) and prognostic value.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eThe study included 30 operated PCC patients. The tissue preparations were re-evaluated by two pathologists and PASS score and GAPP score were given. 4 µm thick paraffin block sections were stained with INSM1, ISL1 and SECG antibodies to obtain staining intensity score, staining percentage and H-score.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eMean age at the diagnosis was 50.5 (±15.9) years. Eight patients were asymptomatic. The most common complaint was high blood pressure. 4 patients (13.3%) had nonfunctioning adenoma. The lesions were mostly localized in the right adrenal gland and median tumor size was 45.0 (35.0-54.2) mm. Median Ki67 was 2.0 % (0.9-3.0). According to the PASS score, 9 (30.0%) patients showed in the benign clinical behavior (score \u0026lt;4), while according to the GAPP score, only 4 (13.3%) patients in the well differentiated type (0-2 points) group. INSM1 and ISL1 were positive in 21 (70%) and 26 (86.7%) of the patients, respectively. However, SECG was positive only in 6 patients (20%). Among the second generation neuroendocrine immunohistochemical markers, ISL1 had the highest H-score. Correlation analysis showed a negative correlation between ISL1 and tumor HU and a positive correlation between INSM1 and Ki67.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003eINSM1, ISL1 and SECG, which are second generation neuroendocrine immunohistochemical markers, can be used in the differential diagnosis of pheochromocytoma. In addition, especially ISNM1 may have prognostic significance.\u003c/p\u003e","manuscriptTitle":"Diagnostic and prognostic utility of INSM1, ISL1 and secretagogin in pheochromocytoma","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-05-07 18:43:12","doi":"10.21203/rs.3.rs-4322745/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":"c1d822b9-b78f-45a0-b323-ae5a74fb1b2b","owner":[],"postedDate":"May 7th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-11-12T02:38:09+00:00","versionOfRecord":[],"versionCreatedAt":"2024-05-07 18:43:12","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4322745","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4322745","identity":"rs-4322745","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}