Molecular classification and prognostication of adrenocortical tumors by transcriptome profiling

Multi-omics profiling highlights karyopherin subunit alpha 2 as a promising biomarker for prognosis and immunotherapy respond in pediatric and adult adrenocortical carcinoma

PURPOSE

Adrenocortical carcinoma (ACC) afflicts both pediatric and adult populations and is characterized by dismal prognosis and elevated mortality. Given the inconsistent therapeutic benefits and significant side effects associated with the conventional chemotherapy agent, mitotane, and the nascent stage of immunotherapy and targeted treatments, there is an urgent need to identify novel prognostic biomarkers and therapeutic targets in ACC.

METHODS

Utilizing multi-omic datasets from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO), we employed Weighted Gene Co-expression Network Analysis (WGCNA), Cox regression, Receiver Operating Characteristic (ROC) curves, and survival analyses to sift for potential prognostic biomarkers. We subsequently validated these findings through immunohistochemistry and cell assays, and delved into the biological role of KPNA2 in ACC through functional enrichment analysis, mutational landscape, and immune cell infiltration.

RESULTS

A total of 77 progression-associated genes with aberrant chromosomal accessibility were discerned within the TCGA-ACC dataset. By integrating ROC and Cox regression from GEO datasets, KPNA2 emerged as an independent risk factor portending poor outcomes in ACC. ATAC-seq analysis revealed attenuated chromatin accessibility of KPNA2 in cases with unfavorable prognosis. Immunohistochemistry corroborated elevated KPNA2 expression, which was linked to enhanced proliferation and invasion. Elevated KPNA2 levels were found to activate oncogenic pathways while simultaneously suppressing immunological responses. Immune infiltration analysis further revealed a decrement in CD8+ T-cell infiltration in KPNA2-high cohorts.

CONCLUSION

This study demonstrates the clinical and biological significance of KPNA2 in ACC and suggests that KPNA2 could serve as a promising biomarker for predicting prognosis and immunotherapeutic responses in pediatric and adult ACC patients.

Targeted multiplex proteomics for the development and validation of biomarkers in primary aldosteronism subtyping

OBJECTIVE

Primary aldosteronism (PA), a significant cause of secondary hypertension affecting ∼10% of patients with severe hypertension, exacerbates cardiovascular, and cerebrovascular complications even after blood pressure control. PA is categorized into two main subtypes: unilateral aldosterone-producing adenomas (APA) and bilateral hyperaldosteronism (BHA), each requiring distinct treatment approaches. Accurate subtype classification is crucial for selecting the most effective treatment. The goal of this study was to develop novel blood-based proteomic biomarkers to differentiate between APA and BHA subtypes in patients with PA.

DESIGN AND METHODS

Five subtyping differential protein biomarker candidates (APOC3, CD56, CHGA, KRT5, and AZGP1) were identified through targeted proteomic profiling of plasma. The subtyping efficiency of these biomarkers was assessed at both the tissue gene expression and blood protein expression levels. To explore the underlying biology of APA and BHA, significant differential pathways were investigated.

RESULTS

The five-protein panel proved highly effective in distinguishing APA from BHA in both tissue and blood samples. By integrating these five protein biomarkers with aldosterone and renin, our blood-based predictive methods achieved remarkable receiver operating characteristic (ROC) area under the ROC curves of 0.986 (95% CI: 0.963-1.000) for differentiating essential hypertension from PA, and 0.922 (95% CI: 0.846-0.998) for subtyping APA versus BHA. These outcomes surpass the performance of the existing Kobayashi score subtyping system. Furthermore, the study validated differential pathways associated with the pathophysiology of PA, aligning with current scientific knowledge and opening new avenues for advancing PA care.

CONCLUSIONS

The new blood-based biomarkers for PA subtyping hold the potential to significantly enhance clinical utility and advance the practice of PA care.

Identification of DLK1, a Notch ligand, as an immunotherapeutic target and regulator of tumor cell plasticity and chemoresistance in adrenocortical carcinoma

Immunotherapeutic targeting of cell surface proteins is an increasingly effective cancer therapy. However, given the limited number of current targets, the identification of new surface proteins, particularly those with biological importance, is critical. Here, we uncover delta-like non-canonical Notch ligand 1 (DLK1) as a cell surface protein with limited normal tissue expression and high expression in multiple refractory adult metastatic cancers including small cell lung cancer (SCLC) and adrenocortical carcinoma (ACC), a rare cancer with few effective therapies. In ACC, ADCT-701, a DLK1 targeting antibody-drug conjugate (ADC), shows potent in vitro activity among established cell lines and a new cohort of patient-derived organoids as well as robust in vivo anti-tumor responses in cell line-derived and patient-derived xenografts. However, ADCT-701 efficacy is overall limited in ACC due to high expression and activity of the drug efflux protein ABCB1 (MDR1, P-glycoprotein). In contrast, ADCT-701 is extremely potent and induces complete responses in DLK1+ ACC and SCLC in vivo models with low or no ABCB1 expression. Genetic deletion of DLK1 in ACC dramatically downregulates ABCB1 and increases ADC payload and chemotherapy sensitivity through NOTCH1-mediated adrenocortical de-differentiation. Single cell RNA-seq of ACC metastatic tumors reveals significantly decreased adrenocortical differentiation in DLK low or negative cells compared to DLK1 positive cells. This works identifies DLK1 as a novel immunotherapeutic target that regulates tumor cell plasticity and chemoresistance in ACC. Our data support targeting DLK1 with an ADC in ACC and neuroendocrine neoplasms in an active first-in-human phase I clinical trial (NCT06041516).

Cellular landscape of adrenocortical carcinoma at single-nuclei resolution

Adrenocortical carcinoma (ACC) is a rare yet devastating tumour of the adrenal gland with a molecular pathology that remains incompletely understood. To gain novel insights into the cellular landscape of ACC, we generated single-nuclei RNA sequencing (snRNA-seq) data sets from twelve ACC tumour samples and analysed these alongside snRNA-seq data sets from normal adrenal glands (NAGs). We find the ACC tumour microenvironment to be relatively devoid of immune cells compared to NAG tissues, consistent with known high tumour purity values for ACC as an immunologically "cold" tumour. Our analysis identifies three separate groups of ACC samples that are characterised by different relative compositions of adrenocortical cell types. These include cell populations that are specifically enriched in the most clinically aggressive and hormonally active tumours, displaying hallmarks of reorganised cell mechanobiology and dysregulated steroidogenesis, respectively. We also identified and validated a population of mitotically active adrenocortical cells that strongly overexpress genes POLQ, DIAPH3 and EZH2 to support tumour expansion alongside an LGR4+ progenitor-like or cell-of-origin candidate for adrenocortical carcinogenesis. Trajectory inference suggests the fate adopted by malignant adrenocortical cells upon differentiation is associated with the copy number or allelic balance state of the imprinted DLK1/MEG3 genomic locus, which we verified by assessing bulk tumour DNA methylation status. In conclusion, our results therefore provide new insights into the clinical and cellular heterogeneity of ACC, revealing how genetic perturbations to healthy adrenocortical renewal and zonation provide a molecular basis for disease pathogenesis.

LncRNA ZFHX4-AS1 as a novel biomarker in adrenocortical carcinoma

Background

Adrenocortical carcinoma (ACC) is a rare and highly aggressive malignant tumor. Currently, there is a lack of reliable prognostic markers in clinical practice. Extensive research has shown that long non-coding RNA (lncRNA) are critical factors in the initiation and progression of cancer, closely associated with early diagnosis and prognosis. Previous studies have identified that ZFHX4 antisense RNA 1 (ZFHX4-AS1) is aberrantly expressed in various cancers and is associated with poor outcomes. This study investigates whether ZFHX4-AS1 affects the prognosis of ACC patients and, if so, the potential mechanisms involved.

Methods

In this study, utilizing four multi-center cohorts from The Cancer Genome Atlas (TCGA) program and Gene Expression Omnibus (GEO), we validated the prognostic capability of ZFHX4-AS1 in ACC patients through Kaplan-Meier survival analysis, cox regression models, and nomograms. Then, we explored the biological functions of ZFHX4-AS1 using gene set enrichment analysis (GSEA), competing endogenous RNA (ceRNA) networks, and analyses of somatic mutations and copy number variation (CNV). Finally, in vitro experiments were conducted to further validate the impact of ZFHX4-AS1 on proliferation and migration capabilities of ACC cell lines.

Results

Survival analysis indicated that patients in the high ZFHX4-AS1 expression group of ACC had worse prognosis. Cox regression analyses suggested that ZFHX4-AS1 levels were independent risk factors for prognosis. Subsequently, we constructed nomograms based on clinical features and ZFHX4-AS1 levels, demonstrating good predictive performance under the time-dependent receiver operating characteristic (ROC) curve. Analysis based on somatic mutations and CNV revealed that CTNNB1 and 9p21.3-Del drove the expression of ZFHX4-AS1. Cell Counting Kit-8 (CCK-8), colony formation, and Transwell assays confirmed that knockdown of ZFHX4-AS1 inhibited proliferation and migration of ACC cells.

Conclusions

This study demonstrates that ZFHX4-AS1 has a reliable predictive value for the prognosis of ACC patients and is a promising biomarker.

Comprehensive genomic analysis of adrenocortical carcinoma reveals genetic profiles associated with patient survival

BACKGROUND

Adrenocortical carcinoma (ACC) is one of the most lethal endocrine malignancies and there is a lack of clinically useful markers for prognosis and patient stratification. Therefore our aim was to identify clinical and genetic markers that predict outcome in patients with ACC.

METHODS

Clinical and genetic data from a total of 162 patients with ACC were analyzed by combining an independent cohort consisting of tumors from Yale School of Medicine, Karolinska Institutet, and Düsseldorf University (YKD) with two public databases [The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO)]. We used a novel bioinformatical pipeline combining differential expression and messenger RNA (mRNA)- and DNA-dependent survival. Data included reanalysis of previously conducted whole-exome sequencing (WES) for the YKD cohort, WES and RNA data for the TCGA cohort, and RNA data for the GEO cohort.

RESULTS

We identified 3903 significant differentially expressed genes when comparing ACC and adrenocortical adenoma, and the mRNA expression levels of 461/3903 genes significantly impacted survival. Subsequent analysis revealed 45 of these genes to be mutated in patients with significantly worse survival. The relationship was significant even after adjusting for stage and age. Protein-protein interaction showed previously unexplored interactions among many of the 45 proteins, including the cancer-related proteins DNA polymerase delta 1 (POLD1), aurora kinase A (AURKA), and kinesin family member 23 (KIF23). Furthermore 14 of the proteins had significant interactions with TP53 which is the most frequently mutated gene in the germline of patients with ACC.

CONCLUSIONS

Using a multiparameter approach, we identified 45 genes that significantly influenced survival. Notably, many of these genes have protein interactions not previously implicated in ACC. These findings may lay the foundation for improved prognostication and future targeted therapies.

Molecular pathology of endocrine gland tumors: genetic alterations and clinicopathologic relevance

Tumors of the endocrine glands are common. Knowledge of their molecular pathology has greatly advanced in the recent past. This review covers the main molecular alterations of tumors of the anterior pituitary, thyroid and parathyroid glands, adrenal cortex, and adrenal medulla and paraganglia. All endocrine gland tumors enjoy a robust correlation between genotype and phenotype. High-throughput molecular analysis demonstrates that endocrine gland tumors can be grouped into molecular groups that are relevant from both pathologic and clinical point of views. In this review, genetic alterations have been discussed and tabulated with respect to their molecular pathogenetic role and clinicopathologic implications, addressing the use of molecular biomarkers for the purpose of diagnosis and prognosis and predicting response to molecular therapy. Hereditary conditions that play a key role in determining predisposition to many types of endocrine tumors are also discussed.

Comprehensive analysis of the role of cuproptosis-related genes in the prognosis and immune infiltration of adrenocortical Carcinoma

Background

Cuproptosis is a recently discovered form of nonapoptotic programmed cell death. However, no research on cuproptosis in the context of adrenocortical carcinoma has been conducted, and the prognostic value of assessing cuproptosis remains unclear.

Methods

In this study, we established comprehensive models to assess gene expression changes, mutation status, and prognosis prediction and developed a prognostic nomogram for cuproptosis-related genes. Using data from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and Genotype-Tissue Expression (GTEx) databases, an analysis of 11 cuproptosis-related genes was performed. Additionally, a risk scoring method and nomogram were used to assess the relationships among cuproptosis-associated genes, transcript expression, clinical characteristics, and prognosis. The connections among tumors, immune checkpoints, and immune infiltration were also analyzed.

Results

The patterns observed in patients with adrenocortical carcinoma who were assessed using cuproptosis-associated risk scores provide useful information for understanding gene mutations, clinical outcomes, immune cell infiltration, and immune checkpoint analysis results. FDX1, LIPT1, MTF1, COX11, CYP2D6, DLAT, ATP7Band CDKN2A were differentially expressed in patients with adrenocortical carcinoma and normal controls. In addition, higher risk scores were significantly associated with poor overall survival and progression-free interval. The nomogram model subsequently developed to facilitate the clinical application of the analysis showed good predictive and calibration capabilities. GSE10927 and GSE33371 were used for independent cohort validation. Moreover, CDKN2A, FDX1, and other cuproptosis-related genes were significantly associated with immune infiltration and checkpoints.

Conclusion

We confirmed that our model had excellent predictive ability in patients with adrenocortical carcinoma. Therefore, an in-depth evaluation of patients using cuproptosis-related risk scores is clinically essential and can assist in therapy in the future.

PLK1 inhibitors as a new targeted treatment for adrenocortical carcinoma

Adrenocortical carcinoma (ACC) is an aggressive malignancy with limited treatment options. Polo-like kinase 1 (PLK1) is a promising drug target; PLK1 inhibitors (PLK1i) have been investigated in solid cancers and are more effective in TP53-mutated cases. We evaluated PLK1 expression in ACC samples and the efficacy of two PLK1i in ACC cell lines with different genetic backgrounds. PLK1 protein expression was investigated by immunohistochemistry in tissue samples and correlated with clinical data. The efficacy of rigosertib (RGS), targeting RAS/PI3K, CDKs and PLKs, and poloxin (Pol), specifically targeting the PLK1 polo-box domain, was tested in TP53-mutated NCI-H295R, MUC-1, and CU-ACC2 cells and in TP53 wild-type CU-ACC1. Effects on proliferation, apoptosis, and viability were determined. PLK1 immunostaining was stronger in TP53-mutated ACC samples vs wild-type (P = 0.0017). High PLK1 expression together with TP53 mutations correlated with shorter progression-free survival (P= 0.041). NCI-H295R showed a time- and dose-dependent reduction in proliferation with both PLK1i (P< 0.05at 100 nM RGS and 30 µM Pol). In MUC-1, a less pronounced decrease was observed (P< 0.05at 1000 nM RGS and 100 µM Pol). 100 nM RGS increased apoptosis in NCI-H295R (P< 0.001), with no effect on MUC-1. CU-ACC2 apoptosis was induced only at high concentrations (P < 0.05 at 3000 nM RGS and 100 µM Pol), while proliferation decreased at 1000 nM RGS and 30 µM Pol. CU-ACC1 proliferation reduced, and apoptosis increased, only at 100 µM Pol. TP53-mutated ACC cell lines demonstrated better response to PLK1i than wild-type CU-ACC1. These data suggest PLK1i may be a promising targeted treatment of a subset of ACC patients, pre-selected according to tumour genetic signature.

A robust six-gene prognostic signature based on two prognostic subtypes constructed by chromatin regulators is correlated with immunological features and therapeutic response in lung adenocarcinoma

Accumulating evidence has demonstrated that chromatin regulators (CRs) regulate immune cell infiltration and are correlated with prognoses of patients in some cancers. However, the immunological and prognostic roles of CRs in lung adenocarcinoma (LUAD) are still unclear. Here, we systematically revealed the correlations of CRs with immunological features and the survival in LUAD patients based on a cohort of gene expression datasets from the public TCGA and GEO databases and real RNA-seq data by an integrative analysis using a comprehensive bioinformatics method. Totals of 160 differentially expressed CRs (DECRs) were identified between LUAD and normal lung tissues, and two molecular prognostic subtypes (MPSs) were constructed and evaluated based on 27 prognostic DECRs using five independent datasets (p =0.016, <0.0001, =0.008, =0.00038 and =0.00055, respectively). Six differentially expressed genes (DEGs) (CENPK, ANGPTL4, CCL20, CPS1, GJB3, TPSB2) between two MPSs had the most important prognostic feature and a six-gene prognostic model was established. LUAD patients in the low-risk subgroup showed a higher overall survival (OS) rate than those in the high-risk subgroup in nine independent datasets (p <0.0001, =0.021, =0.016, =0.0099, <0.0001, =0.0045, <0.0001, =0.0038 and =0.00013, respectively). Six-gene prognostic signature had the highest concordance index of 0.673 compared with 19 reported prognostic signatures. The risk score was significantly correlated with immunological features and activities of oncogenic signaling pathways. LUAD patients in the low-risk subgroup benefited more from immunotherapy and were less sensitive to conventional chemotherapy agents. This study provides novel insights into the prognostic and immunological roles of CRs in LUAD.

The diagnostic or prognostic values of FADD in cancers based on pan‑cancer analysis

Previous studies have determined that aberrant expression of the fas-associated death domain (FADD) contributes to the development of cancer. However, no pan-cancer analysis has been reported to explore the relationship between FADD and various cancers. Multiple databases were screened to identify cancer datasets for the present study and to validate the expression of FADD in various tumors. The association of FADD alteration with cancer prognosis, clinical features and tumor immunity was also evaluated. Reverse transcription-quantitative PCR (RT-qPCR) was utilized to confirm the expression of FADD in breast, colon, liver and gastric cancer cells. Analysis of Gene Expression Omnibus database and The Cancer Genome Atlas database indicated that FADD was highly expressed in breast invasive carcinoma (BRCA), cervical squamous cell carcinoma and endocervical adenocarcinoma, cholangiocarcinoma, colon adenocarcinoma (COAD), esophageal carcinoma (ESCA), kidney renal clear cell carcinoma, kidney renal papillary cell carcinoma, liver hepatocellular carcinoma (LIHC), lung adenocarcinoma (LUAD) and prostate adenocarcinoma, whereas RT-qPCR results revealed that FADD was highly expressed in breast cancer and colon cancer. Further analyses demonstrated that FADD expression was significantly altered in ESCA, head and neck squamous cell carcinoma (HNSC), lung squamous cell carcinoma and BRCA. FADD expression was observed to be a risk factor of the overall survival in patients with HNSC, LIHC and LUAD as demonstrated by Kaplan-Meier and Cox regression analyses. The results of the present study demonstrated that FADD is highly expressed in numerous malignancies and can be utilized as a biomarker for the diagnosis of BRCA, COAD, LIHC and stomach adenocarcinoma. Moreover, FADD expression is a predictive risk factor for the development of HNSC, LIHC and LUAD and can potentially be used as a prognostic marker for these cancers.

Pan-Cancer Analysis Reveals CENPI as a Potential Biomarker and Therapeutic Target in Adrenocortical Carcinoma

Background

Centromere protein I (CENPI) has been shown to affect the tumorigenesis of breast and colorectal cancers. However, its biological role and prognostic value in other kinds of cancer, especially adrenocortical carcinoma (ACC), remained to be further investigated.

Methods

Various bioinformatics tools were adopted for exploring the significance of differential expression of CENPI in several malignant tumors from databases such as Depmap portal, GTEx, and TCGA. ACC was selected for further analyzed, and information such as clinicopathological features, the prognostic outcome of diverse subgroups, differentially expressed genes (DEGs), co-expression genes, as well as levels of tumor-infiltrating immune cells (TIIC), was extracted from multiple databases. To verify the possibility of CENPI as a therapeutic target in ACC, drug sensitivity assay and si-RNA mediate knockdown of CENPI were carried out.

Results

The pan-cancer analyses showed that the CENPI mRNA expression levels differed significantly among most cancer types. Additionally, a high precision in cancer prediction and close relation with cancer survival indicated that CENPI could be a potential candidate biomarker to diagnose and predict cancer prognosis. In ACC, CENPI was closely related to multiple clinical characteristics, such as pathological stage and primary therapy outcome. High CENPI levels predicted poor overall survival (OS), progression-free interval (PFI), and disease-specific survival (DSS) of ACC patients, particularly for different clinical subgroups. Moreover, the expression of CENPI showed positive relationship to Th2 cells but negatively related to most of the TIICs. Furthermore, drug sensitivity assay showed that vorinostat inhibit CENPI expression and ACC cell growth. Additionally, si-RNA mediated knockdown of CENPI inhibited ACC cell growth and invasion and showed synergistic anti-proliferation effect with AURKB inhibitor barasertib.

Conclusion

Pan-cancer analysis demonstrated that CENPI is a potential diagnostic and prognostic biomarker in various cancers as well as an anti-ACC therapeutic target.

Transcriptome Profile of the Rat Adrenal Gland: Parenchymal and Interstitial Cells

The homeostasis of the adrenal gland plays a decisive role in its proper functioning, both in non-stressful conditions and under the influence of various types of stress. This consists of interactions between all types of cells that make up the organ, including parenchymal and interstitial cells. The amount of available information on this subject in the rat adrenal glands under non-stressful conditions is insufficient; the aim of the research was to determine the expression of marker genes for rat adrenal cells depending on their location. The material for the study consisted of adrenal glands taken from intact adult male rats that were separated into appropriate zones. Transcriptome analysis by means of Affymetrix^® Rat Gene 2.1 ST Array was used in the study, followed by real-time PCR validation. Expression analysis of interstitial cell marker genes revealed both the amount of expression of these genes and the zone in which they were expressed. The expression of marker genes for fibroblasts was particularly high in the cells of the ZG zone, while the highest expression of specific macrophage genes was observed in the adrenal medulla. The results of this study, especially with regard to interstitial cells, provide a so far undescribed model of marker gene expression of various cells, both in the cortex and medulla of the sexually mature rat adrenal gland. The interdependence between parenchymal and interstitial cells creates a specific microenvironment that is highly heterogeneous within the gland with respect to some of the interstitial cells. This phenomenon most likely depends on the interaction with the differentiated parenchymal cells of the cortex, as well as the medulla of the gland.

The Enhanced Expression of ZWILCH Predicts Poor Survival of Adrenocortical Carcinoma Patients

Zwilch kinetochore protein (ZWILCH) plays a key role in proper cell proliferation. The upregulation of the ZWILCH gene was observed in many types of cancers, but the association of ZWILCH with adrenocortical carcinoma (ACC) was not investigated so far. The main aim of the presented study was to verify if the enhanced level of the ZWILCH gene can be used as a diagnostic marker for ACC development and progression, as well as a predictor of survival time for ACC patients. The performed analyses included investigation of the ZWILCH expression profile in tumors with publicly available TCGA (The Cancer Genome Atlas) datasets and transcriptomic data from the Gene Expression Omnibus (GEO) database, as well as, in human biological samples of normal adrenal, adrenocortical carcinoma and in commercially available tissue microarrays. The findings demonstrate statistically significant higher ZWILCH gene expression in ACC tissue in comparison with normal adrenal glands. Furthermore, there is a strong correlation between ZWILCH upregulation and tumor mitotic rate and the probability of patient survival. The enhanced ZWILCH level is also connected with the activation of genes involved in cell proliferation and the inhibition of genes related to the immune system. This work contributes to a better understanding of the role of ZWILCH as an ACC biomarker and diagnostic tool.

Transcriptome sequencing reveals two subtypes of cortisol-secreting adrenocortical tumours in dogs and identifies CYP26B1 as a potential new therapeutic target

Cushing's syndrome (CS) is a serious endocrine disorder that is relatively common in dogs, but rare in humans. In ~15%-20% of cases, CS is caused by a cortisol-secreting adrenocortical tumour (csACT). To identify differentially expressed genes that can improve prognostic predictions after surgery and represent novel treatment targets, we performed RNA sequencing on csACTs (n = 48) and normal adrenal cortices (NACs; n = 10) of dogs. A gene was declared differentially expressed when the adjusted p-value was <.05 and the log₂ fold change was >2 or < -2. Between NACs and csACTs, 98 genes were differentially expressed. Based on the principal component analysis (PCA) the csACTs were separated in two groups, of which Group 1 had significantly better survival after adrenalectomy (p = .002) than Group 2. Between csACT Group G1 and Group 2, 77 genes were differentially expressed. One of these, cytochrome P450 26B1 (CYP26B1), was significantly associated with survival in both our canine csACTs and in a publicly available data set of 33 human cortisol-secreting adrenocortical carcinomas. In the validation cohort, CYP26B1 was also expressed significantly higher (p = .012) in canine csACTs compared with NACs. In future studies it would be interesting to determine whether CYP26B1 inhibitors could inhibit csACT growth in both dogs and humans.

Histopathologic Features of Adrenal Cortical Carcinoma

Adrenal cortical carcinoma (ACC) is a rare and aggressive malignancy that poses challenging issues regarding the diagnostic workup. Indeed, no presurgical technique or clinical parameters can reliably distinguish between adrenal cortical adenomas, which are more frequent and have a favorable outcome, and ACC, and the final diagnosis largely relies on histopathologic analysis of the surgical specimen. However, even the pathologic assessment of malignancy in an adrenal cortical lesion is not straightforward and requires a combined evaluation of multiple histopathologic features. Starting from the Weiss score, which was developed in 1984, several histopathologic scoring systems have been designed to tackle the difficulties of ACC diagnosis. Dealing with specific histopathologic variants (eg, Liss-Weiss-Bisceglia scoring system for oncocytic ACC) or patient characteristics (eg, Wieneke index in the pediatric setting), these scores remarkably improved the diagnostic workup of ACC and its subtypes. Nevertheless, cases with misleading features or discordant correlations between pathologic findings and clinical behavior still occur. Owing to multicentric collaborative studies integrating morphologic features with ancillary immunohistochemical markers and molecular analysis, ACC has eventually emerged as a multifaceted, heterogenous malignancy, and, while innovative and promising approaches are currently being tested, the future clinical management of patients with ACC will mainly rely on personalized medicine and target-therapy protocols. At the dawn of the new Fifth World Health Organization classification of endocrine tumors, this review will tackle ACC from the pathologist's perspective, thus focusing on the main available diagnostic, prognostic, and predictive tissue-tethered features and biomarkers and providing relevant clinical and molecular correlates.

Update on Biology and Genomics of Adrenocortical Carcinomas: Rationale for Emerging Therapies

The adrenal glands are paired endocrine organs that produce steroid hormones and catecholamines required for life. Adrenocortical carcinoma (ACC) is a rare and often fatal cancer of the peripheral domain of the gland, the adrenal cortex. Recent research in adrenal development, homeostasis, and disease have refined our understanding of the cellular and molecular programs controlling cortical growth and renewal, uncovering crucial clues into how physiologic programs are hijacked in early and late stages of malignant neoplasia. Alongside these studies, genome-wide approaches to examine adrenocortical tumors have transformed our understanding of ACC biology, and revealed that ACC is composed of distinct molecular subtypes associated with favorable, intermediate, and dismal clinical outcomes. The homogeneous transcriptional and epigenetic programs prevailing in each ACC subtype suggest likely susceptibility to any of a plethora of existing and novel targeted agents, with the caveat that therapeutic response may ultimately be limited by cancer cell plasticity. Despite enormous biomedical research advances in the last decade, the only potentially curative therapy for ACC to date is primary surgical resection, and up to 75% of patients will develop metastatic disease refractory to standard-of-care adjuvant mitotane and cytotoxic chemotherapy. A comprehensive, integrated, and current bench-to-bedside understanding of our field's investigations into adrenocortical physiology and neoplasia is crucial to developing novel clinical tools and approaches to equip the one-in-a-million patient fighting this devastating disease.

The role of molecular profiling in adrenocortical carcinoma

Adrenocortical carcinoma (ACC) is a rare, aggressive cancer with still partially unknown pathogenesis, heterogenous clinical behaviour and no effective treatment for advanced stages. Therefore, there is an urgent clinical unmet need for better prognostication strategies, innovative therapies and significant improvement of the management of the individual patients. In this review, we summarize available studies on molecular prognostic markers and markers predictive of response to standard therapies as well as newly proposed drug targets in sporadic ACC. We include in vitro studies and available clinical trials, focusing on alterations at the DNA, RNA and epigenetic levels. We also discuss the potential of biomarkers to be implemented in a clinical routine workflow for improved ACC patient care.

Identification of core genes as potential biomarkers for predicting progression and prognosis in glioblastoma

Background: Glioblastoma is a common malignant neuroepithelial neoplasm with poor clinical outcomes and limited treatment options. It is extremely important to search and confirm diverse hub genes that are effective in the advance and prediction of glioblastoma.

Methods: We analyzed GSE50161, GSE4290, and GSE68848, the three microarray datasets retrieved from the GEO database. GO function and KEGG pathway enrichment analyses for differentially expressed genes (DEGs) were performed using DAVID. The PPI network of the DEGs was analyzed using the Search Tool for the Retrieval of Interacting Genes database and visualized by Cytoscape software. Hub genes were identified through the PPI network and a robust rank aggregation method. The Cancer Genome Atlas (TCGA) and the Oncomine database were used to validate the hub genes. In addition, a survival curve analysis was conducted to verify the correlation between the expression of hub genes and patient prognosis. Human glioblastoma cells and normal cells were collected, and then RT-PCR, Western blot, and immunofluorescence were conducted to validate the expression of the NDC80 gene. A cell proliferation assay was used to detect the proliferation of glioma cells. The effects of NDC80 expression on migration and invasion of GBM cell lines were evaluated by conducting scratch and transwell assays.

Results: A total of 716 DEGs were common to all three microarray datasets, which included 188 upregulated DEGs and 528 downregulated DEGs. Furthermore, we found that among the common DEGs, 10 hub genes showed a high degree of connectivity. The expression of the 10 hub genes in TCGA and the Oncomine database was significantly overexpressed in glioblastoma compared with normal genes. Additionally, the survival analysis showed that the patients with low expression of six genes (BIR5C, CDC20, NDC80, CDK1, TOP2A, and MELK) had a significantly favorable prognosis (p < 0.01). We discovered that NDC80, which has been shown to be important in other cancers, also has an important role in malignant gliomas. The RT-PCR, Western blot, and immunofluorescence results showed that the expression level of NDC80 was significantly higher in human glioblastoma cells than in normal cells. Moreover, we identified that NDC80 increased the proliferation and invasion abilities of human glioblastoma cells.

Conclusion: The six genes identified here may be utilized to form a panel of disease progression and predictive biomarkers of glioblastoma for clinical purposes. NDC80, one of the six genes, was discovered to have a potentially important role in GBM, a finding that needs to be further studied.

Comprehensive Multiomics Analysis Reveals Potential Diagnostic and Prognostic Biomarkers in Adrenal Cortical Carcinoma

Adrenal cortical carcinoma (ACC) is a severe malignant tumor with low early diagnosis rates and high mortality. In this study, we used a variety of bioinformatic analyses to find potential prognostic markers and therapeutic targets for ACC. Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) data sets were used to perform differential expressed analysis. WebGestalt was used to perform enrichment analysis, while String was used for protein-protein analysis. Our study first detected 28 up-regulation and 462 down-regulation differential expressed genes through the GEO and TCGA databases. Then, GO functional analysis, four pathway analyses (KEGG, REACTOME, PANTHER, and BIOCYC), and protein-protein interaction network were performed to identify these genes by WebGestalt tool and KOBAS website, as well as String database, respectively, and finalize 17 hub genes. After a series of analyses from GEPIA, including gene mutations, differential expression, and prognosis, we excluded one candidate unrelated to the prognosis of ACC and put the remaining genes into pathway analysis again. We screened out CCNB1 and NDC80 genes by three algorithms of Degree, MCC, and MNC. We subsequently performed genomic analysis using the TCGA and cBioPortal databases to better understand these two hub genes. Our data also showed that the CCNB1 and NDC80 genes might become ACC biomarkers for future clinical use.

Identification of Four Novel Prognostic Biomarkers and Construction of Two Nomograms in Adrenocortical Carcinoma: A Multi-Omics Data Study via Bioinformatics and Machine Learning Methods

Background: Adrenocortical carcinoma (ACC) is an orphan tumor which has poor prognoses. Therefore, it is of urgent need for us to find candidate prognostic biomarkers and provide clinicians with an accurate method for survival prediction of ACC via bioinformatics and machine learning methods.

Methods: Eight different methods including differentially expressed gene (DEG) analysis, weighted correlation network analysis (WGCNA), protein-protein interaction (PPI) network construction, survival analysis, expression level comparison, receiver operating characteristic (ROC) analysis, and decision curve analysis (DCA) were used to identify potential prognostic biomarkers for ACC via seven independent datasets. Linear discriminant analysis (LDA), K-nearest neighbor (KNN), support vector machine (SVM), and time-dependent ROC were performed to further identify meaningful prognostic biomarkers (MPBs). Cox regression analyses were performed to screen factors for nomogram construction.

Results: We identified nine hub genes correlated to prognosis of patients with ACC. Furthermore, four MPBs (ASPM, BIRC5, CCNB2, and CDK1) with high accuracy of survival prediction were screened out, which were enriched in the cell cycle. We also found that mutations and copy number variants of these MPBs were associated with overall survival (OS) of ACC patients. Moreover, MPB expressions were associated with immune infiltration level. Two nomograms [OS-nomogram and disease-free survival (DFS)-nomogram] were established, which could provide clinicians with an accurate, quick, and visualized method for survival prediction.

Conclusion: Four novel MPBs were identified and two nomograms were constructed, which might constitute a breakthrough in treatment and prognosis prediction of patients with ACC.

Synergistic effects of telomerase reverse transcriptase and regulator of telomere elongation helicase 1 on aggressiveness and outcomes in adrenocortical carcinoma

Adrenocortical carcinoma (ACC) is one of the deadliest endocrine malignancies and telomere maintenance by activated telomerase is critically required for ACC development and progression. Because telomerase reverse transcriptase (TERT) and regulator of telomere elongation helicase 1 (RTEL1) play key roles in telomere homeostasis, we determined their effect on ACC pathogenesis and outcomes. Analyses of TCGA and GEO datasets showed significantly higher expression of RTEL1 but not TERT in ACC tumors, compared to their benign or normal counterparts. Furthermore, gains/amplifications of both TERT and RTEL1 genes were widespread in ACC tumors and their expression correlated with their gene copy numbers. Higher expression of either TERT or RTEL1 was associated with shorter overall and progression-free survival (OS and PFS) in the TCGA ACC patient cohort, and higher levels of both TERT and RTEL1 mRNA predicted the shortest patient OS and PFS. However, multivariate analyses showed that only RTEL1 independently predicted patient OS and PFS. Gene set enrichment analysis further showed enrichments of wnt/β-catenin, MYC, glycolysis, MTOR, and DNA repair signaling pathways in ACC tumors expressing high TERT and RTEL1 mRNA levels. Taken together, TERT and RTEL1 promote ACC aggressiveness synergistically and may serve as prognostic factors and therapeutic targets for ACC.

Screening for Prognostic Biomarkers in Metastatic Adrenocortical Carcinoma by Tissue Micro Arrays Analysis Identifies P53 as an Independent Prognostic Marker of Overall Survival

Advanced adrenocortical carcinoma (ACC) has poor but heterogeneous prognosis. Apart from Ki67 index, no prognostic or predictive biomarker has been validated in advanced ACC, so far. We aimed at analyzing expression of a large panel of proteins involved in known altered pathways in ACC (cell cycle, Wnt/ß-catenin, methylation) to identify and prioritize potential prognostic or predictive parameters metastatic ACC population. We conducted a retrospective multicentric study. Overall survival (OS) and partial response according to RECIST 1.1 were primary endpoints. TMA was set up and 16 markers were analyzed. Modified ENSAT and GRAS parameters were characterized for prognostic adjustment. Results: We included 66 patients with a mean age at metastatic diagnosis of 48.7 ± 15.5 years. Median survival was 27.8 months. After adjustment to mENSAT-GRAS parameters, p53 and PDxK were prognostic of OS. No potential biomarker has been identified as predictive factor of response. We identified for the first time P53 as an independent prognostic marker of metastatic adrenocortical carcinoma after mENSAT-GRAS parameter adjustment. Prognostic impact of Wnt/ß-catenin alterations was not confirmed in this cohort of metastatic ACC.

Transcriptome in paraffin samples for the diagnosis and prognosis of adrenocortical carcinoma

DESIGN

Molecular classification is important for the diagnosis and prognosis of adrenocortical tumors (ACT). Transcriptome profiles separate adrenocortical adenomas 'C2' from carcinomas, and identify two groups of carcinomas 'C1A' and 'C1B', of poor and better prognosis respectively. However, many ACT cannot be profiled because of improper or absent freezing procedures, a mandatory requirement so far. The main aim was to determine transcriptome profiles on formalin-fixed paraffin-embedded (FFPE) samples, using the new 3'-end RNA-sequencing technology. A secondary aim was to demonstrate the ability of this technique to explore large FFPE archives, by focusing on the rare oncocytic ACT variants.

METHODS

We included 131 ACT: a training cohort from Cochin hospital and an independent validation cohort from Wuerzburg hospital. The 3' transcriptome was generated from FFPE samples using QuantSeq (Lexogen, Vienna, Austria) and NextSeq500 (Illumina, San Diego, CA, USA).

RESULTS

In the training cohort, unsupervised clustering identified three groups: 'C1A' aggressive carcinomas (n = 28, 29%), 'C1B' more indolent carcinomas (n = 28, 29%), and 'C2' adenomas (n = 39, 41%). The prognostic value of FFPE transcriptome was confirmed in the validation cohort (5-year OS: 26% in 'C1A' (n = 26) and 100% in 'C1B' (n = 10), P = 0.003). FFPE transcriptome was an independent prognostic factor in a multivariable model including tumor stage and Ki-67 (OS HR: 7.5, P = 0.01). Oncocytic ACT (n = 19) did not form any specific cluster. Oncocytic carcinomas (n = 6) and oncocytic ACT of uncertain malignant potential (n = 4) were all in 'C1B'.

CONCLUSIONS

The 3' RNA-sequencing represents a convenient solution for determining ACT molecular class from FFPE samples. This technique should facilitate routine use and large retrospective studies.

Spindle and Kinetochore-Associated Complex is Associated With Poor Prognosis in Adrenocortical Carcinoma

INTRODUCTION

The spindle and kinetochore-associated (SKA) complex, composed of three subunits (SKA1, SKA2, and SKA3), stabilizes spindle microtubule attachment to the kinetochore (KT) in the middle stage of mitosis. High expression of this complex is associated with poor prognosis for several tumors. However, the potential role of SKA complex overexpression in rare malignant diseases, such as adrenocortical carcinoma (ACC), has not been well investigated.

MATERIALS AND METHODS

In this study, we used several databases to explore the relationship between SKA subunit expression and prognosis in ACC patients. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genome (KEGG) databases were used to analyze enriched pathways in ACC.

RESULTS

The results suggest that each of the three SKA subunits are overexpressed in ACC and that high expression is correlated with poor patient prognosis. Overexpression of the SKA complex is associated with the expression of organelle fission, nuclear division, and chromosome segregation pathways. Furthermore, differential expression of hub genes for proteins that interact physically or functionally with the SKA complex (CCNB2, UBE2C, BUB1B, TPX2, CCNA2, CDCA8, CCNB1, MELK, TOP2A, and KIF2C) revealed additional potential biomarkers for ACC.

CONCLUSIONS

Our findings provide additional understanding of the mechanisms of ACC and suggest an approach for biomarker discovery using publicly available resources.

Pathological and Genetic Stratification for Management of Adrenocortical Carcinoma

CONTEXT

Adrenocortical carcinoma (ACC) is a rare endocrine malignancy that affects patients across the age spectrum. Although the overall survival in patients with ACC is poor, there is significant heterogeneity in terms of outcomes, presentation, and underlying genetic drivers.

EVIDENCE ACQUISITION

This review is based on the evidence collected from primary research studies, expert reviews, and published guidelines. The studies were identified through PubMed search with key words "adrenocortical carcinoma," "prognosis," "pathology," and "genetics." The PubMed search was complemented by authors' expertise, research, and clinical experience in the field of ACC.

EVIDENCE SYNTHESIS

Identification of biomarkers has been critical to gain better insight into tumor behavior and to guide therapeutic approach to patients. Tumor stage, resection status, and Ki67 are pathological tumor characteristics that have been identified as prognosticators in patients with ACC. Cortisol excess also correlates with worse prognosis. Clinical and histopathological characteristics help stratify patient outcomes, yet still up to 25% of patients have a different outcome than predicted. To bridge this gap, comprehensive genomic profiling studies have characterized additional profiles that correlate with clinical outcomes. In addition, studies of clinically applicable molecular markers are under way to further stratify outcomes in patients with ACC tumors.

CONCLUSIONS

Clinical predictors in combination with pathological markers play a critical role in the approach to patients with ACC. Recent advances in genetic prognosticators will help extend the stratification of these tumors and contribute to a personalized therapeutic approach to patients with ACC.

Overview of the 2022 WHO Classification of Adrenal Cortical Tumors

The new WHO classification of adrenal cortical proliferations reflects translational advances in the fields of endocrine pathology, oncology and molecular biology. By adopting a question-answer framework, this review highlights advances in knowledge of histological features, ancillary studies, and associated genetic findings that increase the understanding of the adrenal cortex pathologies that are now reflected in the 2022 WHO classification. The pathological correlates of adrenal cortical proliferations include diffuse adrenal cortical hyperplasia, adrenal cortical nodular disease, adrenal cortical adenomas and adrenal cortical carcinomas. Understanding germline susceptibility and the clonal-neoplastic nature of individual adrenal cortical nodules in primary bilateral macronodular adrenal cortical disease, and recognition of the clonal-neoplastic nature of incidentally discovered non-functional subcentimeter benign adrenal cortical nodules has led to redefining the spectrum of adrenal cortical nodular disease. As a consequence, the most significant nomenclature change in the field of adrenal cortical pathology involves the refined classification of adrenal cortical nodular disease which now includes (a) sporadic nodular adrenocortical disease, (b) bilateral micronodular adrenal cortical disease, and (c) bilateral macronodular adrenal cortical disease (formerly known primary bilateral macronodular adrenal cortical hyperplasia). This group of clinicopathological entities are reflected in functional adrenal cortical pathologies. Aldosterone producing cortical lesions can be unifocal or multifocal, and may be bilateral with no imaging-detected nodule(s). Furthermore, not all grossly or radiologically identified adrenal cortical lesions may be the source of aldosterone excess. For this reason, the new WHO classification endorses the nomenclature of the HISTALDO classification which uses CYP11B2 immunohistochemistry to identify functional sites of aldosterone production to help predict the risk of bilateral disease in primary aldosteronism. Adrenal cortical carcinomas are subtyped based on their morphological features to include conventional, oncocytic, myxoid, and sarcomatoid subtypes. Although the classic histopathologic criteria for diagnosing adrenal cortical carcinomas have not changed, the 2022 WHO classification underscores the diagnostic and prognostic impact of angioinvasion (vascular invasion) in these tumors. Microscopic angioinvasion is defined as tumor cells invading through a vessel wall and forming a thrombus/fibrin-tumor complex or intravascular tumor cells admixed with platelet thrombus/fibrin. In addition to well-established Weiss and modified Weiss scoring systems, the new WHO classification also expands on the use of other multiparameter diagnostic algorithms (reticulin algorithm, Lin-Weiss-Bisceglia system, and Helsinki scoring system) to assist the workup of adrenal cortical neoplasms in adults. Accordingly, conventional carcinomas can be assessed using all multiparameter diagnostic schemes, whereas oncocytic neoplasms can be assessed using the Lin-Weiss-Bisceglia system, reticulin algorithm and Helsinki scoring system. Pediatric adrenal cortical neoplasms are assessed using the Wieneke system. Most adult adrenal cortical carcinomas show > 5 mitoses per 10 mm² and > 5% Ki67. The 2022 WHO classification places an emphasis on an accurate assessment of tumor proliferation rate using both the mitotic count (mitoses per 10 mm²) and Ki67 labeling index which play an essential role in the dynamic risk stratification of affected patients. Low grade carcinomas have mitotic rate of ≤ 20 mitoses per 10 mm², whereas high-grade carcinomas show > 20 mitoses per 10 mm². Ki67-based tumor grading has not been endorsed in the new WHO classification, since the proliferation indices are continuous variables rather than being static thresholds in tumor biology. This new WHO classification emphasizes the role of diagnostic and predictive biomarkers in the workup of adrenal cortical neoplasms. Confirmation of the adrenal cortical origin of a tumor remains a critical requirement when dealing with non-functional lesions in the adrenal gland which may be mistaken for a primary adrenal cortical neoplasm. While SF1 is the most reliable biomarker in the confirmation of adrenal cortical origin, paranuclear IGF2 expression is a useful biomarker in the distinction of malignancy in adrenal cortical neoplasms. In addition to adrenal myelolipoma, the new classification of adrenal cortical tumors has introduced new sections including adrenal ectopia, based on the potential role of such ectopic tissue as a possible source of neoplastic proliferations as well as a potential mimicker of metastatic disease. Adrenal cysts are also discussed in the new classification as they may simulate primary cystic adrenal neoplasms or even adrenal cortical carcinomas in the setting of an adrenal pseudocyst.

Overexpression of SKA Complex Is Associated With Poor Prognosis in Gliomas

The spindle and kinetochore-associated complex is composed of three members: SKA1, SKA2, and SKA3. It is necessary for stabilizing spindle microtubules attaching to kinetochore (KT) in the middle stage of mitosis. The SKA complex is associated with poor prognosis in several human cancers. However, the role of SKA complex in rare malignant diseases, such as gliomas, has not been fully investigated. We investigated several databases, including Oncomine, UALCAN, and cBioPortal to explore the expression profile and prognostic significance of SKA complex in patients with gliomas. Gene ontology and Kyoto Encyclopedia of Genes and Genome pathways were used to analyze the potential enriched pathways. The genes co-expressed with SKA complex were identified and used for developing a protein-protein interaction (PPI) network using the STRING database. We found a significant overexpression of the mRNA levels of SKA1, SKA2, and SKA3 in patients with glioma patients. Higher expression of SKA1 and SKA3, but not SKA2, was significantly correlated with shorter overall survival of patients with glioma. In glioma, SKA complex was found to be involved in nuclear division, chromosome segregation, and DNA replication. The results of PPI network identified 10 hub genes (CCNB2, UBE2C, BUB1B, TPX2, CCNA2, CCNB1, MELK, TOP2A, PBK, and KIF11), all of which were overexpressed and negatively associated with prognosis of patients with glioma. In conclusion, our study sheds new insights into the biological role and prognostic significance of SKA complex in glioma.

Pediatric adrenocortical carcinoma

Adrenocortical carcinoma (ACC) is a rare endocrine malignancy of the adrenal gland with an unfavorable prognosis. It is rare in the pediatric population, with an incidence of 0.2-0.3 patients per million in patients under 20 years old. It is primarily associated with Li-Fraumeni and Beckwith-Wiedemann tumor predisposition syndromes in children. The incidence of pediatric ACC is 10-15fold higher in southern Brazil due to a higher prevalence of TP53 mutation associated with Li-Fraumeni syndrome in that population. Current treatment protocols are derived from adult ACC and consist of surgery and/or chemotherapy with etoposide, doxorubicin, and cisplatin (EDP) with mitotane. Limited research has been reported on other treatment modalities for pediatric ACC, including mitotane, pembrolizumab, cabozantinib, and chimeric antigen receptor autologous cell (CAR-T) therapy.

Whole Transcriptome Profiling of Adrenocortical Tumors Using Formalin-Fixed Paraffin-Embedded Samples

Whole transcriptome profiling is a promising technique in adrenal studies; however, whole transcriptome profiling of adrenal disease using formalin-fixed paraffin-embedded (FFPE) samples has to be further explored. The aim of this study was to evaluate the utility of transcriptome data from FFPE samples of adrenocortical tumors. We performed whole transcriptome profiling of FFPE and fresh frozen samples of adrenocortical carcinoma (ACC, n = 3), aldosterone-producing adenoma (APA, n = 3), and cortisol-producing adenoma (CPA, n = 3), and examined the similarity between the transcriptome data. We further examined whether the transcriptome data of FFPE samples could be used to distinguish tumor types and detect marker genes. The number of read counts was smaller in FFPE samples than in fresh frozen samples (P < 0.01), while the number of genes detected was similar (P = 0.39). The gene expression profiles of FFPE and fresh frozen samples were highly correlated (r = 0.93, P < 0.01). Tumor types could be distinguished by consensus clustering and principal component analysis using transcriptome data from FFPE samples. In the differential expression analysis between ACC and APA-CPA, known marker genes of ACC (e.g., CCNB2, TOP2A, and MAD2L1) were detected in FFPE samples of ACC. In the differential expression analysis between APA and CPA, known marker genes of APA (e.g., CYP11B2, VSNL1, and KCNJ5) were detected in the APA of FFPE samples. The results suggest that FFPE samples may be a reliable alternative to fresh frozen samples for whole transcriptome profiling of adrenocortical tumors.

[Multifactorial assessment of prognostic features of adrenocortical cancer]

OBJECTIVE

To determine the predictors of the aggressive course of adrenocortical cancer (ACC). ACC is a rare malignant neoplasm of the adrenal cortex with a variable prognosis. At present, predicting the course of the disease and clinical outcome in patients presents significant difficulties, since many aspects of the treatment of ACC have not been studied or require clarification. In particular, the prognostic value of markers that are used in clinical practice has not been fully determined.

MATERIAL AND METHODS

Histological and immunohistochemical studies of the surgical material of adrenal neoplasms were performed. The study included 73 patients with a histologically confirmed diagnosis of ACC: 51 (69.9%) women and 22 (30.1%) men aged 17 to 82 years. Cox regression model was used for survival analysis. Statistically significant factors (p<0.05) according to the results of independent regression analysis were included in the Kaplan-Meier analysis followed by pairwise comparison using the log-rank test.

RESULTS

An increased risk of recurrence is associated with the presence of pathological mitoses and excessive secretion of aldosterone, death - with stage IV according to the classification of the European Network for the Study of Adrenal Tumors (ENSAT), relapse and death - the value of mitotic activity more than 20, the Ki-67 index more than 12, the classic variant. Mitotic activity and hormonal activity were independent predictors of recurrence-free survival, mitotic activity and ENSAT stage were independent predictors of overall survival.

CONCLUSIONS

In the present work, potential predictors of the course of ACC are identified, which are available for use in routine practice. Based on the totality of clinical, morphological, immunohistochemical data used in the diagnosis of ACC, a conception of the patient's survival can be obtained.

Expression of glucocorticoid receptor (GR) and clinical significance in adrenocortical carcinoma

Adrenocortical carcinoma (ACC) is a rare endocrine tumor, and most cases present with hormone excess with poor prognosis. Our research aims to determine the clinical and biological significance of glucocorticoid receptor (GR) expression using large cohorts of ACC patients. Immunohistochemistry was used to assess the expression of GR in 78 ACC cases from the West China Hospital (WCH) cohort. RNA-seq data were retrieved from The Cancer Genome Atlas database (TCGA, n=79). Clinicopathological and follow-up data were obtained from two cohorts. The correlation between the GR gene and tumor immune status was estimated using TIMER and GEPIA2. Kaplan-Meier analysis was performed to identify the prognostic value of GR in ACC. In the WCH cohort, positive nuclear GR staining was identified in 90% of the primary ACC cases. Cortisol-secreting ACCs demonstrated significantly lower GR protein expression than did nonfunctioning tumors (P<0.001). This finding was validated by the mRNA data analysis of the TCGA cohort (P = 0.030). GR expression was found to be positively correlated with the immune cell infiltration level and immune-checkpoint-related gene expression in ACC. Survival comparison and multivariate analysis showed that GR expression is an independent prognostic predictor of disease-free survival and overall survival in ACC patients in both cohorts. Our findings suggest that low GR expression is significantly correlated with excess cortisol, immune signatures and poor survival in ACC patients. We propose that GR signaling may play an important role in ACC behavior and thus may be a therapeutic target, which deserves further research.

Development and Validation of Hub Genes for Adrenal Aldosterone-Producing Adenoma by Integrated Bioinformatics Analysis

OBJECTIVE

To develop and validate hub genes involving in the development and progression of primary aldosteronism (PA) and adrenal aldosterone-producing adenoma (APA).

MATERIALS AND METHODS

A total of four datasets of gene expression profiles related to APA were downloaded from GEO datasets. GSE60042 and GSE8514 were used to identify DEGs. Weighted gene co-expression network analysis (WGCNA) and protein-protein interaction (PPI) network module analysis were conducted. GO and KEGG enrichment analysis was performed. GSE10927 and GSE33371 were used for further external validation.

RESULTS

We identified a total of 892 DEGs from GSE60042 and 1167 DEGs from GSE8514. WGCNA analysis demonstrated that the blue module (255 genes) and turquoise module (303 genes) were significantly correlated with APA. PPI networks were then constructed. GO term enrichment analysis suggested that cellular divalent inorganic cation homeostasis, calcium ion homeostasis, collagen-containing extracellular matrix, transport vesicle and metal ion transmembrane transporter activity were the vital annotations. KEGG pathway analysis found that these genes were significantly enriched in neuroactive ligand-receptor interaction, calcium signaling pathway. Finally, we identified a total of 11 candidate genes involving in the development and progression of APA and PA. Besides, two independent datasets (GSE10927 and GSE33371) were used for external validation, and there were seven hub genes successfully verified, including C3, GRM3, AVPR1A, WFS1, PTGFR, NTSR2, and JUN.

CONCLUSION

These newly identified genes could contribute to the understanding of potential mechanism in APA and PA and might be promising targets for the treatment of APA and PA.

In Silico Analysis of the Gene Expression Patterns between Aldosterone-Producing Adenoma and Nonfunctional Adrenocortical Adenoma

Primary aldosteronism is the most common form of secondary hypertension, and aldosteronoma makes up a significant proportion of primary aldosteronism cases. Aldosteronoma is also called aldosterone-producing adenoma (APA). Although there have been many studies about APA, the pathogenesis of this disease is not yet fully understood. In this study, we aimed to find out the difference of gene expression patterns between APA and nonfunctional adrenocortical adenoma (NFAA) using a weighted gene coexpression network (WGCNA) and differentially expressed gene (DEG) analysis; only the genes that meet the corresponding standards of both methods were defined as real hub genes and then used for further analysis. Twenty-nine real hub genes were found out, most of which were enriched in the phospholipid metabolic process. WISP2, S100A10, SSTR5-AS1, SLC29A1, APOC1, and SLITRK4 are six real hub genes with the same gene expression pattern between the combined and validation datasets, three of which indirectly or directly participate in lipid metabolism including WISP2, S100A10, and APOC1. According to the gene expression pattern of DEGs, we speculated five candidate drugs with potential therapeutic value for APA, one of which is cycloheximide, an inhibitor for phospholipid biosynthesis. All the evidence suggests that phospholipid metabolism may be an important pathophysiological mechanism for APA. Our study provides a new perspective regarding the pathophysiological mechanism of APA and offers some small molecules that may possibly be effective drugs against APA.

Identifying New Potential Biomarkers in Adrenocortical Tumors Based on mRNA Expression Data Using Machine Learning

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.

Management of Patients With Glucocorticoid-Related Diseases and COVID-19

The ongoing coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is a global health crisis affecting millions of people worldwide. SARS-CoV-2 enters the host cells by binding to angiotensin-converting enzyme 2 (ACE2) after being cleaved by the transmembrane protease serine 2 (TMPRSS2). In addition to the lung, gastrointestinal tract and kidney, ACE2 is also extensively expressed in endocrine tissues, including the pituitary and adrenal glands. Although glucocorticoids could play a central role as immunosuppressants during the cytokine storm, they can have both stimulating and inhibitory effects on immune response, depending on the timing of their administration and their circulating levels. Patients with adrenal insufficiency (AI) or Cushing's syndrome (CS) are therefore vulnerable groups in relation to COVID-19. Additionally, patients with adrenocortical carcinoma (ACC) could also be more vulnerable to COVID-19 due to the immunosuppressive state caused by the cancer itself, by secreted glucocorticoids, and by anticancer treatments. This review comprehensively summarizes the current literature on susceptibility to and outcome of COVID-19 in AI, CS and ACC patients and emphasizes potential pathophysiological mechanisms of susceptibility to COVID-19 as well as the management of these patients in case of SARS-CoV-2. Finally, by performing an in silico analysis, we describe the mRNA expression of ACE2, TMPRSS2 and the genes encoding their co-receptors CTSB, CTSL and FURIN in normal adrenal and adrenocortical tumors (both adenomas and carcinomas).

How to Differentiate Benign from Malignant Adrenocortical Tumors?

Simple Summary

Adrenocortical carcinoma is a rare cancer with a poor prognosis. Adrenal tumors are, however, commonly identified in clinical practice. Discrimination between benign and malignant adrenal tumors is of great importance to determine the appropriate treatment and follow-up strategy. This review summarizes the current diagnostic strategies and challenges to distinguish benign from malignant adrenal lesions. We will focus both on radiological and biochemical assessments, enabling diagnosis of the adrenal lesion preoperatively, and on histopathological and a wide variety of molecular assessments that can be done after surgical removal of the adrenal lesion. Furthermore, new non-invasive strategies such as liquid biopsies, in which blood samples are used to study circulating tumor cells, tumor DNA and microRNA, will be addressed in this review.

Abstract

Adrenocortical carcinoma (ACC) is a rare cancer with a poor prognosis. Adrenal incidentalomas are, however, commonly identified in clinical practice. Discrimination between benign and malignant adrenal tumors is of great importance considering the large differences in clinical behavior requiring different strategies. Diagnosis of ACC starts with a thorough physical examination, biochemical evaluation, and imaging. Computed tomography is the first-level imaging modality in adrenal tumors, with tumor size and Hounsfield units being important features for determining malignancy. New developments include the use of urine metabolomics, also enabling discrimination of ACC from adenomas preoperatively. Postoperatively, the Weiss score is used for diagnosis of ACC, consisting of nine histopathological criteria. Due to known limitations as interobserver variability and lack of accuracy in borderline cases, much effort has been put into new tools to diagnose ACC. Novel developments vary from immunohistochemical markers and pathological scores, to markers at the level of DNA, methylome, chromosome, or microRNA. Molecular studies have provided insights into the most promising and most frequent alterations in ACC. The use of liquid biopsies for diagnosis of ACC is studied, although in a small number of patients, requiring further investigation. In this review, current diagnostic modalities and challenges in ACC will be addressed.

Novel Insights into the Molecular Regulation of Ribonucleotide Reductase in Adrenocortical Carcinoma Treatment

Simple Summary

The current clinical gold standard etoposide, doxorubicin, cisplatin, and mitotane (EDP-M) is not satisfying for the treatment of adrenocortical carcinoma (ACC). However, clinical translation of novel, preclinically promising therapies were unfortunately disappointing in recent years, indicating that utilized tumor models inadequately predicted clinical applicability of novel pharmacological approaches. In an attempt to optimize the current preclinical armamentarium, our workgroup initiated a comparative drug screen of clinically relevant chemotherapies and therapies targeting IGF, EGF, and Wnt signaling pathways in the classical NCI-H295R cell line and, for the first time, in the recently developed highly drug-resistant MUC-1 cell line. These testings revealed gemcitabine and cisplatin as a promising combination, but further investigations also indicated developing drug resistance mechanisms on the molecular level. We aimed to decipher underlying resistance mechanisms, identified ribonucleotide reductase as an important player, and successfully targeted the involved DNA damage/repair mechanism.

Abstract

Current systemic treatment options for patients with adrenocortical carcinomas (ACCs) are far from being satisfactory. DNA damage/repair mechanisms, which involve, e.g., ataxia-telangiectasia-mutated (ATM) and ataxia-telangiectasia/Rad3-related (ATR) protein signaling or ribonucleotide reductase subunits M1/M2 (RRM1/RRM2)-encoded ribonucleotide reductase (RNR) activation, commonly contribute to drug resistance. Moreover, the regulation of RRM2b, the p53-induced alternative to RRM2, is of unclear importance for ACC. Upon extensive drug screening, including a large panel of chemotherapies and molecular targeted inhibitors, we provide strong evidence for the anti-tumoral efficacy of combined gemcitabine (G) and cisplatin (C) treatment against the adrenocortical cell lines NCI-H295R and MUC-1. However, accompanying induction of RRM1, RRM2, and RRM2b expression also indicated developing G resistance, a frequent side effect in clinical patient care. Interestingly, this effect was partially reversed upon addition of C. We confirmed our findings for RRM2 protein, RNR-dependent dATP levels, and modulations of related ATM/ATR signaling. Finally, we screened for complementing inhibitors of the DNA damage/repair system targeting RNR, Wee1, CHK1/2, ATR, and ATM. Notably, the combination of G, C, and the dual RRM1/RRM2 inhibitor COH29 resulted in previously unreached total cell killing. In summary, we provide evidence that RNR-modulating therapies might represent a new therapeutic option for ACC.

Mass Spectrometry-Based Proteomic Discovery of Prognostic Biomarkers in Adrenal Cortical Carcinoma

Adrenal cortical carcinoma (ACC) is an extremely rare disease with a variable prognosis. Current prognostic markers have limitations in identifying patients with a poor prognosis. Herein, we aimed to investigate the prognostic protein biomarkers of ACC using mass-spectrometry-based proteomics. We performed the liquid chromatography-tandem mass spectrometry (LC-MS/MS) using formalin-fixed paraffin-embedded (FFPE) tissues of 45 adrenal tumors. Then, we selected 117 differentially expressed proteins (DEPs) among tumors with different stages using the machine learning algorithm. Next, we conducted a survival analysis to assess whether the levels of DEPs were related to survival. Among 117 DEPs, HNRNPA1, C8A, CHMP6, LTBP4, SPR, NCEH1, MRPS23, POLDIP2, and WBSCR16 were significantly correlated with the survival of ACC. In age- and stage-adjusted Cox proportional hazard regression models, only HNRNPA1, LTBP4, MRPS23, POLDIP2, and WBSCR16 expression remained significant. These five proteins were also validated in TCGA data as the prognostic biomarkers. In this study, we found that HNRNPA1, LTBP4, MRPS23, POLDIP2, and WBSCR16 were protein biomarkers for predicting the prognosis of ACC.

The role of regulated necrosis in endocrine diseases

The death of endocrine cells is involved in type 1 diabetes mellitus, autoimmunity, adrenopause and hypogonadotropism. Insights from research on basic cell death have revealed that most pathophysiologically important cell death is necrotic in nature, whereas regular metabolism is maintained by apoptosis programmes. Necrosis is defined as cell death by plasma membrane rupture, which allows the release of damage-associated molecular patterns that trigger an immune response referred to as necroinflammation. Regulated necrosis comes in different forms, such as necroptosis, pyroptosis and ferroptosis. In this Perspective, with a focus on the endocrine environment, we introduce these cell death pathways and discuss the specific consequences of regulated necrosis. Given that clinical trials of necrostatins for the treatment of autoimmune conditions have already been initiated, we highlight the therapeutic potential of such novel therapeutic approaches that, in our opinion, should be tested in endocrine disorders in the future.

Upregulation of TCF21 inhibits migration of adrenocortical carcinoma cells

BACKGROUND

Adrenocortical carcinomas (ACC) are rare and aggressive cancer. Our previous study has revealed that the transcription factor 21, TCF21, is downregulated in ACC and regulates steroidogenic factor 1 (SF-1) binding to the SF-1 E-box promoter. In addition, it could be found that TCF21 is a predictor of overall survival (OS) in adult carcinomas.

METHODS

In this study, it was investigated the correlation between TCF21 expression and the promoter methylation status in adrenocortical tumor cells, carcinomas and adenoma. The biological function and potential molecular mechanism of TCF21 restoration in migration and invasion of ACC cells was examined.

RESULTS

We could be demonstrated a negative correlation between the level of TCF21 expression and methylation of its promoter in adenoma and carcinoma cells indicating the epigenetic control of TCF21 expression. It was also demonstrated that the expression of TCF21 inhibits migration and invasion in the ACC cell line, H295R cells, using plasmid transfection to express TCF21. Furthermore, it could be investigated the TCF21 function as tumor suppressor probably through Kisspeptin 1 (KISS-1) expression and epithelial-mesenchymal transition (EMT) reversion, as well as the modulation of several metalloproteinases in ACC cells.

CONCLUSIONS

Our results suggest that enhancement of TCF21 expression levels may be a potential strategy to revert invasive abilities in adrenocortical carcinomas.

Adrenocortical carcinoma: current state of the art, ongoing controversies, and future directions in diagnosis and treatment

Adrenocortical carcinoma (ACC) is a rare, aggressive malignancy with an annual incidence of ~1 case per million population. Differentiating between ACC and benign adrenocortical tumors can be challenging in patients who present with an incidentally discovered adrenal mass, due to the limited specificity of standard diagnostic imaging. Recently, urine steroid metabolite profiling has been prospectively validated as a novel diagnostic tool for the detection of malignancy with improved accuracy over current modalities. Surgery represents the only curative treatment for ACC, although local recurrence and metastases are common, even after a margin-negative resection is performed. Unlike other intra-abdominal cancers, the role of minimally invasive surgery and lymphadenectomy in ACC is controversial. Adjuvant therapy with the adrenolytic drug mitotane is used to reduce the risk of recurrence after surgery, although evidence supporting its efficacy is limited; it is also currently unclear whether all patients or a subset with the highest risk of recurrence should receive this treatment. Large-scale pan-genomic studies have yielded insights into the pathogenesis of ACC and have defined distinct molecular signatures associated with clinical outcomes that may be used to improve prognostication. For patients with advanced ACC, palliative combination chemotherapy with mitotane is the current standard of care; however, this is associated with poor response rates (RR). Knowledge from molecular profiling studies has been used to guide the development of novel targeted therapies; however, these have shown limited efficacy in early phase trials. As a result, there is an urgent unmet need for more effective therapies for patients with this devastating disease.

Histological scores and tumor size on stage II in adrenocortical carcinomas

Adrenocortical carcinomas (ACC) are aggressive tumors with a poor prognosis. Histological scores are advised for the diagnosis, however, there are borderline cases that may be misjudged as adrenocortical adenomas (ACA). The three main scores used are: Weiss Modified System (WMS), Reticulin Algorithm (RA), and Helsinki Score (HS). We intend to compare the accuracy of the three scores in ACC diagnosis and to identify predictive factors of overall survival (OS). Retrospective study (2004–2016) at Centro Hospitalar e Universitário de Coimbra of the adrenal tumors, classified as ACC or ACA, with a history of posterior tumor relapse/metastases, without lesions in the contralateral adrenal gland: 13F and 6M, with a median age of 51 ± 12.41 years. Nodules’ median size was 9.20 ± 6.2 cm. Patients had a median OS of 52 ± 18.6 months, with 57.9% and 46.3%, at 3 and 5 years. Seven patients had local recurrence and nine had metastases. Thirteen cases were in stage II. The WMS and the HS allowed a diagnosis of ACC in 15 cases and the RA defined ACC in 17 cases. All cases had, at least, focal disruption of the reticulin framework. More than 5 mitosis/50 HPF was associated with worse OS: 49.67 ± 21.43 versus 108.86 ± 14.02 months (p = 0.026). In patients with stage II, tumor size ⩾10 cm was associated with worse OS: 19.25 ± 7.15 versus 96.11 ± 16.7 months (p = 0.007), confirmed by multivariate analysis (p = 0.031). The correct diagnosis of ACC is a pathologist responsibility. The RA seems the most accurate. Any loss of the reticulin framework should raise awareness for malignancy. In patients on stage II, a size ⩾10 cm is a predictor of worse prognosis.

A Critical Appraisal of Contemporary and Novel Biomarkers in Pheochromocytomas and Adrenocortical Tumors

Simple Summary

Pheochromocytomas/paragangliomas (PPGLs) and adrenocortical tumors are neoplasms that originate from different regions of the adrenal gland and display significant heterogeneity with respect to their biological and clinical behavior. They may be sporadic or develop in the context of hereditary syndromes. Adrenocortical tumors are mostly benign but less than 2% are carcinomas associated with a poor outcome when diagnosed in advanced disease. The majority of PPGLS are benign, but a subset may develop metastatic disease. In particular, for PPGLs, it is mandatory to identify biomarkers of high sensitivity and specificity that lead to accurate diagnosis and predict patients with a malignant potential that would benefit from aggressive surveillance and administration of early treatment. Current biomarkers include mostly histopathological and genetic parameters but none of them can be considered independent predictive factors. Recent genomic studies have implemented new molecular biomarkers of high accuracy for the diagnosis and management of PPGLs and adrenocortical tumors. In this review, we summarize the current and novel biomarkers that may be considered valuable tools for diagnosis and prediction of malignancy in patients with PPGLs and adrenocortical tumors.

Abstract

Pheochromocytomas/Paragangliomas (PPGLs) and adrenocortical tumors are rare neoplasms with significant heterogeneity in their biologic and clinical behavior. Current diagnostic and predictive biomarkers include hormone secretion, as well as histopathological and genetic features. PPGL diagnosis is based on biochemical measurement of catecholamines/metanephrines, while histopathological scoring systems have been proposed to predict the risk of malignancy. Adrenocortical tumors are mostly benign, but some can be malignant. Currently, the stage of disease at diagnosis and tumor grade, appear to be the most powerful prognostic factors. However, recent genomic and proteomic studies have identified new genetic and circulating biomarkers, including genes, immunohistochemical markers and micro-RNAs that display high specificity and sensitivity as diagnostic or prognostic tools. In addition, new molecular classifications have been proposed that divide adrenal tumors in distinct subgroups with different clinical outcomes.

Emerging drugs for the treatment of adrenocortical carcinoma

Introduction: Adrenocortical cancer (ACC) is a rare and aggressive disease with a median survival of 14-17 months and 5-year survival of around 20% for advanced disease. Emerging evidence of sub-groups of ACC with specific molecular drivers indicate ACC may be amenable to inhibition of receptor tyrosine kinases involved in growth and angiogenic signaling. A significant subset of patients may also be responsive to immune strategies.Areas covered: This review outlines approaches of targeting upregulated growth pathways including Insulin-like Growth Factor, Vascular Endothelial Growth Factor, Fibroblast Growth Factor and Epidermal Growth Factor Receptor in ACC. Data of immune checkpoint blockade with nivolumab, ipilimumab, pembrolizumab and avelumab is explored in detail. Genomic studies indicate that up to 40% of ACC are driven by dysregulated WNT and glucocorticoid signaling, special focus is placed on emerging drugs in these pathways.Expert opinion: Progress in the treatment of ACC has faced challenges stemming from the rarity of the disease. Given recent advances in the understanding of the molecular pathogenesis of ACC, a window of opportunity has now opened to make significant progress in developing therapeutic options that target key pathways such as excessive glucocorticoid signaling, WNT signaling, cell cycle and immune checkpoints.

Discovery of CASP8 as a potential biomarker for high-risk prostate cancer through a high-multiplex immunoassay

Prostate cancer remains the most common non-cutaneous malignancy among men in the United States. To discover potential serum-based biomarkers for high-risk prostate cancer, we performed a high-multiplex immunoassay utilizing patient-matched pre-operative and post-operative serum samples from ten men with high-grade and high-volume prostate cancer. Our study identified six (CASP8, MSLN, FGFBP1, ICOSLG, TIE2 and S100A4) out of 174 proteins that were significantly decreased after radical prostatectomy. High levels of CASP8 were detected in pre-operative serum samples when compared to post-operative serum samples and serum samples from patients with benign prostate hyperplasia (BPH). By immunohistochemistry, CASP8 protein was expressed at higher levels in prostate cancer tissues compared to non-cancerous and BPH tissues. Likewise, CASP8 mRNA expression was significantly upregulated in prostate cancer when compared to benign prostate tissues in four independent clinical datasets. In addition, mRNA levels of CASP8 were higher in patients with recurrent prostate cancer when compared to patients with non-recurrent prostate cancer and high expression of CASP8 was associated with worse disease-free survival and overall survival in renal cancer. Together, our results suggest that CASP8 may potentially serve as a biomarker for high-risk prostate cancer and possibly renal cancer.

Epithelial and Mesenchymal Markers in Adrenocortical Tissues: How Mesenchymal Are Adrenocortical Tissues?

A clinically relevant proportion of adrenocortical carcinoma (ACC) cases shows a tendency to metastatic spread. The objective was to determine whether the epithelial to mesenchymal transition (EMT), a mechanism associated with metastasizing in several epithelial cancers, might play a crucial role in ACC. 138 ACC, 29 adrenocortical adenomas (ACA), three normal adrenal glands (NAG), and control tissue samples were assessed for the expression of epithelial (E-cadherin and EpCAM) and mesenchymal (N-cadherin, SLUG and SNAIL) markers by immunohistochemistry. Using real-time RT-PCR we quantified the alternative isoform splicing of FGFR 2 and 3, another known indicator of EMT. We also assessed the impact of these markers on clinical outcome. Results show that both normal and neoplastic adrenocortical tissues lacked expression of epithelial markers but strongly expressed mesenchymal markers N-cadherin and SLUG. FGFR isoform splicing confirmed higher similarity of adrenocortical tissues to mesenchymal compared to epithelial tissues. In ACC, higher SLUG expression was associated with clinical markers indicating aggressiveness, while N-cadherin expression inversely associated with these markers. In conclusion, we could not find any indication of EMT as all adrenocortical tissues lacked expression of epithelial markers and exhibited closer similarity to mesenchymal tissues. However, while N-cadherin might play a positive role in tissue structure upkeep, SLUG seems to be associated with a more aggressive phenotype.

Immunotherapy in Adrenocortical Carcinoma: Predictors of Response, Efficacy, Safety, and Mechanisms of Resistance

Adrenocortical carcinoma (ACC) is a rare endocrine malignancy with limited treatment options in the advanced stages. Immunotherapy offers hope for altering the orthodox management of cancer, and its role in advanced ACC has been investigated in different studies. With the aim clarifying the role of immunotherapy in ACC we performed a comprehensive review about this topic focusing on the predictors of response, efficacy, safety, and the mechanisms of resistance. Five clinical trials with four immune checkpoint inhibitors (pembrolizumab, avelumab, nivolumab, and ipilimumab) have investigated the role of immunotherapy in advanced ACC. Despite, the different primary endpoints used in these studies, the reported rates of overall response rate and progression free survival were generally poor. Three main potential markers of response to immunotherapy in ACC have been described: Expression of PD-1 and PD-L1, microsatellite instability and tumor mutational burden. However, none of them has been validated in prospective studies. Several mechanisms of ACC immunoevasion may be responsible of immunotherapy failure, and a greater knowledge of these mechanisms might lead to the development of new strategies to overcome the immunotherapy resistance. In conclusion, although currently the role of immunotherapy is limited, the identification of immunological markers of response and the implementation of strategies to avoid immunotherapy resistance could improve the efficacy of this therapy.

What Did We Learn from the Molecular Biology of Adrenal Cortical Neoplasia? From Histopathology to Translational Genomics

Approximately one-tenth of the general population exhibit adrenal cortical nodules, and the incidence has increased. Afflicted patients display a multifaceted symptomatology-sometimes with rather spectacular features. Given the general infrequency as well as the specific clinical, histological, and molecular considerations characterizing these lesions, adrenal cortical tumors should be investigated by endocrine pathologists in high-volume tertiary centers. Even so, to distinguish specific forms of benign adrenal cortical lesions as well as to pinpoint malignant cases with the highest risk of poor outcome is often challenging using conventional histology alone, and molecular genetics and translational biomarkers are therefore gaining increased attention as a possible discriminator in this context. In general, our understanding of adrenal cortical tumorigenesis has increased tremendously the last decade, not least due to the development of next-generation sequencing techniques. Comprehensive analyses have helped establish the link between benign aldosterone-producing adrenal cortical proliferations and ion channel mutations, as well as mutations in the protein kinase A (PKA) signaling pathway coupled to cortisol-producing adrenal cortical lesions. Moreover, molecular classifications of adrenal cortical tumors have facilitated the distinction of benign from malignant forms, as well as the prognostication of the individual patients with verified adrenal cortical carcinoma, enabling high-resolution diagnostics that is not entirely possible by histology alone. Therefore, combinations of histology, immunohistochemistry, and next-generation multi-omic analyses are all needed in an integrated fashion to properly distinguish malignancy in some cases. Despite significant progress made in the field, current clinical and pathological challenges include the preoperative distinction of non-metastatic low-grade adrenal cortical carcinoma confined to the adrenal gland, adoption of individualized therapeutic algorithms aligned with molecular and histopathologic risk stratification tools, and histological confirmation of functional adrenal cortical disease in the context of multifocal adrenal cortical proliferations. We herein review the histological, genetic, and epigenetic landscapes of benign and malignant adrenal cortical neoplasia from a modern surgical endocrine pathology perspective and highlight key mechanisms of value for diagnostic and prognostic purposes.

Construction of a robust prognostic model for adult adrenocortical carcinoma: Results from bioinformatics and real-world data

This study aims to construct a robust prognostic model for adult adrenocortical carcinoma (ACC) by large‐scale multiomics analysis and real‐world data. The RPPA data, gene expression profiles and clinical information of adult ACC patients were obtained from The Cancer Proteome Atlas (TCPA), Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA). Integrated prognosis‐related proteins (IPRPs) model was constructed. Immunohistochemistry was used to validate the prognostic value of the IPRPs model in Fudan University Shanghai Cancer Center (FUSCC) cohort. 76 ACC cases from TCGA and 22 ACC cases from GSE10927 in NCBI’s GEO database with full data for clinical information and gene expression were utilized to validate the effectiveness of the IPRPs model. Higher FASN (P = .039), FIBRONECTIN (P < .001), TFRC (P < .001), TSC1 (P < .001) expression indicated significantly worse overall survival for adult ACC patients. Risk assessment suggested significantly a strong predictive capacity of IPRPs model for poor overall survival (P < .05). IPRPs model showed a little stronger ability for predicting prognosis than Ki‐67 protein in FUSCC cohort (P = .003, HR = 3.947; P = .005, HR = 3.787). In external validation of IPRPs model using gene expression data, IPRPs model showed strong ability for predicting prognosis in TCGA cohort (P = .005, HR = 3.061) and it exhibited best ability for predicting prognosis in GSE10927 cohort (P = .0898, HR = 2.318). This research constructed IPRPs model for predicting adult ACC patients’ prognosis using proteomic data, gene expression data and real‐world data and this prognostic model showed stronger predictive value than other biomarkers (Ki‐67, Beta‐catenin, etc) in multi‐cohorts.