Steroidogenic factor-1 (SF-1, also termed Ad4BP; NR5A1 in the official nomenclature) is a nuclear receptor transcription factor that plays a crucial role in the regulation of adrenal and gonadal development, function and maintenance. In addition to its classical role in regulating the expression of P450 steroid hydroxylases and other steroidogenic genes, involvement in other key processes such as cell survival/proliferation and cytoskeleton dynamics have also been highlighted for SF-1. SF-1 has a restricted pattern of expression, being expressed along the hypothalamic-pituitary axis and in steroidogenic organs since the time of their establishment. Reduced SF-1 expression affects proper gonadal and adrenal organogenesis and function. On the other hand, SF-1 overexpression is found in adrenocortical carcinoma and represents a prognostic marker for patients’ survival. This review is focused on the current knowledge about SF-1 and the crucial importance of its dosage for adrenal gland development and function, from its involvement in adrenal cortex formation to tumorigenesis. Overall, data converge towards SF-1 being a key player in the complex network of transcriptional regulation within the adrenal gland in a dosage-dependent manner.

We reconstructed a transcriptional regulatory network for adrenocortical carcinoma (ACC) using transcriptomic and clinical data from The Cancer Genome Atlas (TCGA)-ACC cohort. We investigated the association of transcriptional regulatory units (regulons) with overall survival, molecular phenotypes, and immune signatures. We annotated the ACC regulons with cancer hallmarks and assessed single sample regulon activities in the European Network for the Study of Adrenal Tumors (ENSAT) cohort. We found 369 regulons associated with overall survival and subdivided them into four clusters: RC1 and RC2, associated with good prognosis, and RC3 and RC4, associated with worse outcomes. The RC1 and RC3 regulons were highly correlated with the ‘Steroid Phenotype,’ while the RC2 and RC4 regulons were highly correlated with a molecular proliferation signature. We selected two regulons, NR5A1 (steroidogenic factor 1, SF-1) and CENPA (Centromeric Protein A), that were consistently associated with overall survival for further downstream analyses. The CENPA regulon was the primary regulator of MKI-67 (a marker of proliferation KI-67), while the NR5A1 regulon is a well-described transcription factor (TF) in ACC tumorigenesis. We also found that the ZBTB4 (Zinc finger and BTB domain-containing protein 4) regulon, which is negatively associated with CENPA in our transcriptional regulatory network, is also a druggable anti-tumorigenic TF. We anticipate that the ACC regulons may be used as a reference for further investigations concerning the complex molecular interactions in ACC tumors.

Background: Adrenocortical carcinoma (ACC) is a rare, aggressive malignancy where endogenous steroid excess may foster immune evasion. However, whether this hormonal axis directly modulates the antigen presentation machinery remains unclear. Methods: We applied an immunoinformatics approach to the TCGA-ACC cohort (n = 79) to investigate relationships among steroid phenotype, HLA expression, tumor microenvironment (TME), and patient outcome. Key findings were assessed in an independent validation cohort (ENSAT-ACC, n = 44) using C1A/C1B molecular subtypes corresponding to the steroid phenotypes. Results: Stratification by steroid phenotype revealed two distinct immunological profiles. The high steroid production (HSP) phenotype was associated with suppressed HLA expression and a lymphocyte-depleted “cold” TME. In contrast, the low steroid production (LSP) phenotype displayed elevated HLA expression, enriched T-cell infiltration, and upregulation of immune checkpoints (e.g., PDCD1, CTLA4), consistent with an inflamed but exhausted TME. The core signature of HLA downregulation in the HSP-like phenotype (C1A) and the significant survival advantage of the LSP-like phenotype (C1B) were confirmed in the validation cohort, demonstrating biological robustness despite platform and sample size differences. Conclusions: These findings identify the steroid phenotype as a critical regulator of immune escape in ACC. Our results support incorporating this stratification as a biomarker for patient selection, identifying LSP tumors as the subgroup most likely to benefit from immune checkpoint blockade due to their “hot” yet exhausted microenvironment.

Background: The TP53 p.R337H variant is a well-characterized founder mutation with an unusually high prevalence in Brazil, particularly in the South and Southeast regions, where it affects approximately one in 300 individuals. It is recurrently associated with pediatric adrenocortical tumors and malignancies within the Li–Fraumeni syndrome spectrum but exhibits markedly incomplete penetrance, suggesting the influence of additional genetic and/or environmental modifiers. Although TP53 p.R337H occurs at low frequencies in the Iberian Peninsula, its origin, timing, and dissemination pattern within Brazil have remained unresolved. Methods: We integrated population–genetic inference with historical demographic modeling to reconstruct the introduction and expansion of the TP53 p.R337H in Brazil. Results: Our analyses support a founder effect arising from a single founding event of European origin during the early Portuguese colonization period. The subsequent geographic dissemination of the variant parallels historical population growth, particularly in southern Brazil. The striking regional enrichment can be explained without invoking multiple introduction events or complex migratory scenarios. Conclusions: These findings clarify the evolutionary and demographic history of TP53 p.R337H in Brazil and underscore its founder effect origin during European colonization. Impact: This study highlights the value of integrating population genetics with historical data to elucidate the spread of medically relevant founder variants. Understanding the dissemination of TP53 p.R337H will enhance public health planning and genetic counseling strategies in Brazil. See related In the Spotlight, p. 187

Supplementary Figure 1. Posterior distribution of the Time to the Most Recent Common Ancestor (TMRCA), in years, derived from 1,000,000 Monte Carlo simulations assuming 2, 4, or 6 initial founders.