The LEF1/TCF transcription factor family is related to the development of diverse tissue types, including the mammary tissue, and dysregulation of its expression and function has been described to favor breast tumorigenesis. However, the clinical and biological relevance of this gene family in breast cancer is still poorly understood. Here, we used bioinformatics approaches aiming to reduce this gap. We investigated its expression patterns in molecular and immune breast cancer subtypes; its correlation with immune cell infiltration, and its prognostic values in predicting outcomes. Also, through regulons construction, we determined the genes whose expression is influenced by these transcription factors, and the pathways in which they are involved. We found that LEF1 and TCF3 are over-expressed in breast tumors regarding non-tumor samples, while TCF4 and TCF7 are down-expressed, with the gene’s methylation status being associated with its expression dysregulation. All four transcription factors presented significance at the diagnostic and prognostic levels. LEF1, TCF4, and TCF7 presented a significant correlation with immune cell infiltration, being associated with the immune subtypes of less favorable outcomes. Altogether, this research contributes to a more accurate understanding of the expression and clinical and biomarker significance of the LEF1/TCF transcription factors in breast cancer.

Introduction: Long non-coding RNAs (LncRNA) represent a heterogeneous family of RNAs that have emerged as regulators of various biological processes through their association with proteins in ribonucleoproteins complexes. The dynamic of these interactions can affect cell metabolism, including cancer development. Annually, breast cancer causes thousands of deaths worldwide, and searching for new biomarkers is pivotal for better diagnosis and treatment. Methods: Based on in silico prediction analysis, we focus on LncRNAs that have binding sites for PUMILIO, an RBP family involved in post-transcriptional regulation and associated with cancer progression. We compared the expression levels of these LncRNAs in breast cancer and non-tumor samples from the TCGA database. We analyzed the impact of overall and disease-free survival associated with the expression of the LncRNAs and co-expressed genes and targets of PUMILIO proteins. Results: Our results found NORAD as the most relevant LncRNA with a PUMILIO binding site in breast cancer, differently expressed between Luminal A and Basal subtypes. Additionally, NORAD was co-expressed in a Basal-like subtype (0.55) with the RALGAPB gene, a target gene of PUMILIO related to chromosome stability during cell division. Conclusion: These data suggest that this molecular axis may provide insights for developing novel therapeutic strategies for breast cancer.

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/Objectives: Adrenocortical carcinoma (ACC) is a rare malignancy in which overexpression of steroidogenic factor-1 (SF-1/NR5A1) and aberrant activation of canonical Wnt/β-catenin signaling are important oncogenic events. However, the extent to which these regulatory axes converge or interact at the transcriptional level remains unclear. We investigated their relationship using bulk transcriptomic and regulatory-network approaches. Methods: Regulatory network inference using RTN/ARACNe was applied to the TCGA-ACC cohort. NR5A1 and β-catenin-associated TCF/LEF regulon activities were evaluated in perturbation datasets and tested for associations with CpG island methylator phenotype (CIMP), overall survival, and gene-level interaction effects. Candidate modulators of NR5A1 activity were assessed using the MINDy algorithm. The effects of cBAF inhibition on NR5A1 regulon activity were also evaluated in H295R and CU-ACC1 cells. Results: NR5A1 knockdown repressed steroidogenic pathways, whereas β-catenin knockdown predominantly suppressed Wnt/β-catenin signaling. In TCGA-ACC, NR5A1 regulon activity was associated with CIMP-high status and overall survival. In contrast, β-catenin-related regulons were not significantly associated with CIMP-high status after adjustment for NR5A1 activity, and no significant multiplicative interaction effects were identified. Fewer than 3% of protein-coding genes showed improved fit in models including NR5A1 × TCF/LEF interaction terms, without enrichment for steroidogenic or Wnt/β-catenin-related pathways. CTNNB1 was identified as a statistically significant but low-ranking positive modulator of NR5A1 activity, whereas CTNNBIP1 was a top-decile negative modulator. cBAF inhibition was associated with NR5A1 regulon repression in both cell models. Conclusions: These findings indicate limited detectable global transcriptional convergence between NR5A1 and canonical β-catenin-related regulons in the evaluated bulk transcriptomic frameworks. Potential relationships between these pathways may depend on more localized, chromatin-dependent, protein-level, or context-specific regulatory mechanisms. NR5A1 regulon activity showed more consistent associations with CIMP-high status and clinical outcome than the β-catenin/TCF-LEF regulons in the evaluated TCGA-ACC models. The modulation patterns associated with CTNNB1 and CTNNBIP1, together with the repression of NR5A1 regulon activity following cBAF inhibition, raise the possibility that NR5A1 acts as a context-dependent regulatory node connecting oncogenic signaling and chromatin-remodeling mechanisms in ACC. These findings support further investigation into the role of chromatin-remodeling complexes in sustaining NR5A1-driven transcriptional programs in ACC.