TY - JOUR A1 - Detomas, Mario A1 - Pivonello, Claudia A1 - Pellegrini, Bianca A1 - Landwehr, Laura-Sophie A1 - Sbiera, Silviu A1 - Pivonello, Rosario A1 - Ronchi, Cristina L. A1 - Colao, Annamaria A1 - Altieri, Barbara A1 - De Martino, Maria Cristina T1 - MicroRNAs and long non-coding RNAs in adrenocortical carcinoma JF - Cells N2 - Non-coding RNAs (ncRNAs) are a type of genetic material that do not encode proteins but regulate the gene expression at an epigenetic level, such as microRNAs (miRNAs) and long non-coding RNAs (lncRNAs). The role played by ncRNAs in many physiological and pathological processes has gained attention during the last few decades, as they might be useful in the diagnosis, treatment and management of several human disorders, including endocrine and oncological diseases. Adrenocortical carcinoma (ACC) is a rare and aggressive endocrine cancer, still characterized by high mortality and morbidity due to both endocrine and oncological complications. Despite the rarity of this disease, recently, the role of ncRNA has been quite extensively evaluated in ACC. In order to better explore the role of the ncRNA in human ACC, this review summarizes the current knowledge on ncRNA dysregulation in ACC and its potential role in the diagnosis, treatment, and management of this tumor. KW - miRNA KW - lncRNA KW - adrenocortical tumor KW - ACC KW - adrenocortical adenoma KW - prognostic markers Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-281795 SN - 2073-4409 VL - 11 IS - 14 ER - TY - JOUR A1 - Fuss, Carmina Teresa A1 - Other, Katharina A1 - Heinze, Britta A1 - Landwehr, Laura-Sophie A1 - Wiegering, Armin A1 - Kalogirou, Charis A1 - Hahner, Stefanie A1 - Fassnacht, Martin T1 - Expression of the chemokine receptor CCR7 in the normal adrenal gland and adrenal tumors and its correlation with clinical outcome in adrenocortical carcinoma JF - Cancers N2 - Background: The chemokine receptor CCR7 is crucial for an intact immune function, but its expression is also associated with clinical outcome in several malignancies. No data exist on the expression of CCR7 in adrenocortical tumors. Methods: CCR7 expression was investigated by qRT-PCR and immunohistochemistry in 4 normal adrenal glands, 59 adrenocortical adenomas, and 181 adrenocortical carcinoma (ACC) samples. Results: CCR7 is highly expressed in the outer adrenocortical zones and medulla. Aldosterone-producing adenomas showed lower CCR7 protein levels (H-score 1.3 ± 1.0) compared to non-functioning (2.4 ± 0.5) and cortisol-producing adenomas (2.3 ± 0.6), whereas protein expression was variable in ACC (1.8 ± 0.8). In ACC, CCR7 protein expression was significantly higher in lymph node metastases (2.5 ± 0.5) compared to primary tumors (1.8±0.8) or distant metastases (2.0 ± 0.4; p < 0.01). mRNA levels of CCR7 were not significantly different between ACCs, normal adrenals, and adrenocortical adenomas. In contrast to other tumor entities, neither CCR7 protein nor mRNA expression significantly impacted patients' survival. Conclusion: We show that CCR7 is expressed on mRNA and protein level across normal adrenals, benign adrenocortical tumors, as well as ACCs. Given that CCR7 did not influence survival in ACC, it is probably not involved in tumor progression, but it could play a role in adrenocortical homeostasis. KW - CCR7 KW - chemokine receptor KW - adrenocortical carcinoma KW - adrenal tumors Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-250112 SN - 2072-6694 VL - 13 IS - 22 ER - TY - JOUR A1 - Marquardt, André A1 - Landwehr, Laura-Sophie A1 - Ronchi, Cristina L. A1 - di Dalmazi, Guido A1 - Riester, Anna A1 - Kollmannsberger, Philip A1 - Altieri, Barbara A1 - Fassnacht, Martin A1 - Sbiera, Silviu T1 - Identifying New Potential Biomarkers in Adrenocortical Tumors Based on mRNA Expression Data Using Machine Learning JF - Cancers N2 - Simple Summary Using a visual-based clustering method on the TCGA RNA sequencing data of a large adrenocortical carcinoma (ACC) cohort, we were able to classify these tumors in two distinct clusters largely overlapping with previously identified ones. As previously shown, the identified clusters also correlated with patient survival. Applying the visual clustering method to a second dataset also including benign adrenocortical samples additionally revealed that one of the ACC clusters is more closely located to the benign samples, providing a possible explanation for the better survival of this ACC cluster. Furthermore, the subsequent use of machine learning identified new possible biomarker genes with prognostic potential for this rare disease, that are significantly differentially expressed in the different survival clusters and should be further evaluated. Abstract Adrenocortical carcinoma (ACC) is a rare disease, associated with poor survival. Several “multiple-omics” studies characterizing ACC on a molecular level identified two different clusters correlating with patient survival (C1A and C1B). We here used the publicly available transcriptome data from the TCGA-ACC dataset (n = 79), applying machine learning (ML) methods to classify the ACC based on expression pattern in an unbiased manner. UMAP (uniform manifold approximation and projection)-based clustering resulted in two distinct groups, ACC-UMAP1 and ACC-UMAP2, that largely overlap with clusters C1B and C1A, respectively. However, subsequent use of random-forest-based learning revealed a set of new possible marker genes showing significant differential expression in the described clusters (e.g., SOAT1, EIF2A1). For validation purposes, we used a secondary dataset based on a previous study from our group, consisting of 4 normal adrenal glands and 52 benign and 7 malignant tumor samples. The results largely confirmed those obtained for the TCGA-ACC cohort. In addition, the ENSAT dataset showed a correlation between benign adrenocortical tumors and the good prognosis ACC cluster ACC-UMAP1/C1B. In conclusion, the use of ML approaches re-identified and redefined known prognostic ACC subgroups. On the other hand, the subsequent use of random-forest-based learning identified new possible prognostic marker genes for ACC. KW - adrenocortical carcinoma KW - in silico analysis KW - machine learning KW - bioinformatic clustering KW - biomarker prediction Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-246245 SN - 2072-6694 VL - 13 IS - 18 ER - TY - JOUR A1 - Landwehr, Laura-Sophie A1 - Altieri, Barbara A1 - Schreiner, Jochen A1 - Sbiera, Iuliu A1 - Weigand, Isabel A1 - Kroiss, Matthias A1 - Fassnacht, Martin A1 - Sbiera, Silviu T1 - Interplay between glucocorticoids and tumor-infiltrating lymphocytes on the prognosis of adrenocortical carcinoma JF - Journal for ImmunoTherapy of Cancer N2 - Background Adrenocortical carcinoma (ACC) is a rare endocrine malignancy. Tumor-related glucocorticoid excess is present in similar to 60% of patients and associated with particularly poor prognosis. Results of first clinical trials using immune checkpoint inhibitors were heterogeneous. Here we characterize tumor-infiltrating T lymphocytes (TILs) in ACC in association with glucocorticoids as potential explanation for resistance to immunotherapy. Methods We performed immunofluorescence analysis to visualize tumor-infiltrating T cells (CD3\(^+\)), T helper cells (CD3\(^+\)CD4\(^+\)), cytotoxic T cells (CD3\(^+\)CD8\(^+\)) and regulatory T cells (Tregs; CD3\(^+\)CD4\(^+\)FoxP3\(^+\)) in 146 ACC tissue specimens (107 primary tumors, 16 local recurrences, 23 metastases). Quantitative data of immune cell infiltration were correlated with clinical data (including glucocorticoid excess). Results 86.3% of ACC specimens showed tumor infiltrating T cells (7.7 cells/high power field (HPF)), including T helper (74.0%, 6.7 cells/HPF), cytotoxic T cells (84.3%, 5.7 cells/HPF) and Tregs (49.3%, 0.8 cells/HPF). The number of TILs was associated with better overall survival (HR for death: 0.47, 95% CI 0.25 to 0.87), which was true for CD4\(^+\)- and CD8\(^+\) subpopulations as well. In localized, non-metastatic ACC, the favorable impact of TILs on overall and recurrence-free survival was manifested even independently of ENSAT (European Network for the Study of Adrenal Tumors) stage, resection status and Ki67 index. T helper cells were negatively correlated with glucocorticoid excess (Phi=-0.290, p=0.009). Patients with glucocorticoid excess and low TILs had a particularly poor overall survival (27 vs. 121 months in patients with TILs without glucocorticoid excess). Conclusion Glucocorticoid excess is associated with T cell depletion and unfavorable prognosis. To reactivate the immune system in ACC by checkpoint inhibitors, an inhibition of adrenal steroidogenesis might be pivotal and should be tested in prospective studies. KW - immunity KW - immunotherapy KW - lymphocytes KW - tumor-infiltrating KW - t-lymphocytes KW - tumor microenvironment Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-229893 VL - 8 ER -