Estrogen Related Receptor Alpha (ERRα) a Bridge between Metabolism and Adrenocortical Cancer Progression

A Review on Mitotane: A Target Therapy in Adrenocortical Carcinoma

Adrenocortical carcinomas (ACCs) are rare and aggressive malignancies of adrenal cortex, associated with largely unknown mechanisms of biological development and poor prognosis. Currently, mitotane is the sole approved drug for treating advanced adrenocortical carcinomas (ACCs) and is being utilized more frequently as postoperative adjuvant therapy. Although it is understood that mitotane targets the adrenal cortex and disrupts steroid production, its precise mechanism of action requires further exploration. Additionally, mitotane affects cytochrome P450 enzymes, causes the depolarization of mitochondrial membranes, and leads to an accumulation of free cholesterol, ultimately resulting in cell death. Many patients treated with mitotane develop disease progression over time, underlying the need to understand the mechanisms of primary and acquired resistance. In this manuscript, we provide an overview on the intracellular mechanisms of action of mitotane, exploring data regarding predictive factors of response and evidence associated with the development of primary and acquired resistance mechanisms. In this discussion, mitotane is considered a real target therapy.

Development and Characterization of 3-Dimensional Cell Culture Models of Adrenocortical Carcinoma

Adrenocortical carcinoma (ACC) is a rare malignancy of the adrenal cortex that is associated with a poor prognosis. Developing effective treatment options for ACC is challenging owing to the current lack of representative preclinical models. This study addressed this limitation by developing and characterizing 3-dimensional (3D) cell cultures incorporating the ACC cell lines, MUC-1, HAC15, and H295R in a type I collagen matrix. ACC tissue samples were analyzed by immunohistochemistry to determine the presence of type I collagen in the tumor microenvironment. Cell viability and proliferation were assessed using flow cytometry and confocal microscopy. mRNA expression of steroidogenic enzymes and steroid secretion was analyzed by comparing the 3D and monolayer cell culture models. All cells were successfully cultured in a type I collagen matrix, which is highly expressed in the ACC tumor microenvironment and showed optimal viability until day 7. All 3 models showed increased metabolic and proliferative activity over time. Three-dimensional cell cultures were steroidogenic and demonstrated increased resistance to the gold standard chemotherapy, mitotane, compared with monolayer. The use of these models may lead to an improved understanding of disease pathology and provide a better representative platform for testing and screening of potential therapies.

Molecular Subtypes Defined by Cuproptosis-Associated Genes, Prognostic Model Development, and Tumor Immune Microenvironment Characterization in Adrenocortical Carcinoma

Introduction

This study aims to explore the role of cuproptosis-related genes in ACC, utilizing data from TCGA and GEO repositories, and to develop a predictive model for patient stratification.

Methods

A cohort of 123 ACC patients with survival data was analyzed. RNA-seq data of 17 CRGs were examined, and univariate Cox regression identified prognostic CRGs. A cuproptosis-related network was constructed to show interactions between CRGs. Consensus clustering classified ACC into three subtypes, with transcriptional and survival differences assessed by PCA and survival analysis. Gene set variation analysis (GSVA) and ssGSEA evaluated functional and immune infiltration characteristics across subtypes. Differentially expressed genes (DEGs) were identified, and gene clusters were established. A risk score (CRG_score) was generated using LASSO and multivariate Cox regression, validated across datasets. Tumor microenvironment, stem cell index, mutation status, drug sensitivity, and hormone synthesis were examined in relation to the CRG_score. Protein expression of key genes was validated, and functional studies on ASF1B and NDRG4 were performed.

Results

Three ACC subtypes were identified with distinct survival outcomes. Subtype B showed the worst prognosis, while subtype C had the best. We identified 214 DEGs linked to cell proliferation and classified patients into three gene clusters, confirming their prognostic value. The CRG_score predicted patient outcomes, with high-risk patients demonstrating worse survival and possible resistance to immunotherapy. Drug sensitivity analysis suggested higher responsiveness to doxorubicin and etoposide in high-risk patients.

Conclusion

This study suggests the potential prognostic value of CRGs in ACC. The CRG_score model provides a robust tool for risk stratification, with implications for treatment strategies.

Bioengineered in vitro three-dimensional tumor models in endocrine cancers

Graphical abstract

Abstract

Endocrine tumors are a heterogeneous cluster of malignancies that originate from cells that can secrete hormones. Examples include, but are not limited to, thyroid cancer, adrenocortical carcinoma, and neuroendocrine tumors. Many endocrine tumors are relatively slow to proliferate, and as such, they often do not respond well to common antiproliferative chemotherapies. Therefore, increasing attention has been given to targeted therapies and immunotherapies in these diseases. However, in contrast to other cancers, many endocrine tumors are relatively rare, and as a result, less is understood about their biology, including specific targets for intervention. Our limited understanding of such tumors is in part due to a limitation in model systems that accurately recapitulate and enable mechanistic exploration of these tumors. While mouse models and 2D cell cultures exist for some endocrine tumors, these models often may not accurately model nuances of human endocrine tumors. Mice differ from human endocrine physiology and 2D cell cultures fail to recapitulate the heterogeneity and 3D architectures of in vivo tumors. To complement these traditional cancer models, bioengineered 3D tumor models, such as organoids and tumor-on-a-chip systems, have advanced rapidly in the past decade. However, these technologies have only recently been applied to most endocrine tumors. In this review we provide descriptions of these platforms, focusing on thyroid, adrenal, and neuroendocrine tumors and how they have been and are being applied in the context of endocrine tumors.

ERRα: unraveling its role as a key player in cell migration

Cell migration is essential throughout the life of multicellular organisms, and largely depends on the spatial and temporal regulation of cytoskeletal dynamics, cell adhesion and signal transduction. Interestingly, Estrogen-related receptor alpha (ERRα) has been identified as a major regulator of cell migration in both physiological and pathological conditions. ERRα is an orphan member of the nuclear hormone receptor superfamily of transcription factors and displays many biological functions. ERRα is a global regulator of energy metabolism, and it is also highly involved in bone homeostasis, development, differentiation, immunity and cancer progression. Importantly, in some instances, the regulation of these biological processes relies on the ability to orchestrate cell movements. Therefore, this review describes how ERRα-mediated cell migration contributes not only to tissue homeostasis but also to tumorigenesis and metastasis, and highlights the molecular and cellular mechanisms by which ERRα finely controls the cell migratory potential.

Three Dimensional Models of Endocrine Organs and Target Tissues Regulated by the Endocrine System

Immortalized cell lines originating from tumors and cultured in monolayers in vitro display consistent behavior and response, and generate reproducible results across laboratories. However, for certain endpoints, these cell lines behave quite differently from the original solid tumors. Thereby, the homogeneity of immortalized cell lines and two-dimensionality of monolayer cultures deters from the development of new therapies and translatability of results to the more complex situation in vivo. Organoids originating from tissue biopsies and spheroids from cell lines mimic the heterogeneous and multidimensional characteristics of tumor cells in 3D structures in vitro. Thus, they have the advantage of recapitulating the more complex tissue architecture of solid tumors. In this review, we discuss recent efforts in basic and preclinical cancer research to establish methods to generate organoids/spheroids and living biobanks from endocrine tissues and target organs under endocrine control while striving to achieve solutions in personalized medicine.

Preclinical Models of Adrenocortical Cancer

Adrenocortical cancer is an aggressive endocrine malignancy with an incidence of 0.72 to 1.02 per million people/year, and a very poor prognosis with a five-year survival rate of 22%. As an orphan disease, clinical data are scarce, meaning that drug development and mechanistic research depend especially on preclinical models. While a single human ACC cell line was available for the last three decades, over the last five years, many new in vitro and in vivo preclinical models have been generated. Herein, we review both in vitro (cell lines, spheroids, and organoids) and in vivo (xenograft and genetically engineered mouse) models. Striking leaps have been made in terms of the preclinical models of ACC, and there are now several modern models available publicly and in repositories for research in this area.

Adrenocortical Carcinoma (ACC) Cells Rewire Their Metabolism to Overcome Curcumin Antitumoral Effects Opening a Window of Opportunity to Improve Treatment

Extensive research suggests that curcumin interferes with multiple cell signaling pathways involved in cancer development and progression. This study aimed to evaluate curcumin effects on adrenocortical carcinoma (ACC), a rare but very aggressive tumor. Curcumin reduced growth, migration and activated apoptosis in three different ACC cell lines, H295R, SW13, MUC-1. This event was related to a decrease in estrogen-related receptor-α (ERRα) expression and cholesterol synthesis. More importantly, curcumin changed ACC cell metabolism, increasing glycolytic gene expression. However, pyruvate from glycolysis was only minimally used for lactate production and the Krebs cycle (TCA). In fact, lactate dehydrogenase, extracellular acidification rate (ECAR), TCA genes and oxygen consumption rate (OCR) were reduced. We instead found an increase in Glutamic-Pyruvic Transaminase (GPT), glutamine antiport transporter SLC1A5 and glutaminase (GLS1), supporting a metabolic rewiring toward glutamine metabolism. Targeting this mechanism, curcumin effects were improved. In fact, in a low glutamine-containing medium, the growth inhibitory effects elicited by curcumin were observed at a concentration ineffective in default growth medium. Data from this study prove the efficacy of curcumin against ACC growth and progression and point to the concomitant use of inhibitors for glutamine metabolism to improve its effects.