Adrenocortical Carcinoma

Estrogen receptor beta expression and role in cancers

Estrogen drives the growth of some cancers, such as breast cancer, via estrogen receptor alpha (ERα). Estrogen also activates ERβ, but whether ERβ is expressed and has a role in different cancers is debated. The use of nonspecific antibodies has contributed to the confusion, and this review delves into ERβ's controversial role in cancer and focuses on tumor expression that can be supported by non-antibody-dependent assays. We discuss its expression at the transcript level and focus on its potential role in lymphoma, granulosa cell tumors, testicular, and adrenal cancers, emphasizing recent findings and the complexities that necessitate further research.

Construction and validation of a prognostic model for predicting overall survival of primary adrenal malignant tumor patients: A population-based study with 1,080 patients

Objective

Primary adrenal malignant tumor is rare. The factors affecting the prognosis remain poorly defined. This study targeted to construct and corroborate a model for predicting the overall survival of adrenal malignant tumor patients.

Methods

We investigated the SEER database for patients with primary adrenal malignant tumor. 1,080 patients were divided into a construction cohort (n = 756) and a validation cohort (n = 324), randomly. The prognostic factors for overall survival were evaluated using univariate and multivariate Cox analyses. The nomogram was constructed and then validated with C-index, calibration curve, time-dependent ROC curve, and decision curve analysis in both cohorts. Then we divided the patients into 3 different risk groups according to the total points of the nomogram and analyzed their survival status by Kaplan-Meier curve with log-rank test.

Results

The baseline characteristics of these two cohorts were not statistically different (P > 0.05). Using univariate and multivariate Cox analyses, 5 variables, including age, tumor size, histological type, tumor stage, and surgery of primary site, were distinguished as prognostic factors (P < 0.05). Based on these variables, we constructed a nomogram to predict the 3- year, 5- year, and 10-year overall survival. The C-indexes were 0.780 (0.760–0.800) in the construction cohort and 0.780 (0.751–0.809) in the validation cohort. In both cohorts, the AUC reached a fairly high level at all time points. The internal and external calibration curves and ROC analysis showed outstanding accuracy and discrimination. The decision curves indicated excellent clinical usefulness. The best cut-off values for the total points of the nomogram were 165.4 and 243.1, and the prognosis was significantly different for the three different risk groups (P < 0.001).

Conclusion

We successfully constructed a model to predict the overall survival of primary adrenal malignant tumor patients. This model was validated to perform brilliantly internally and externally, which can assist us in individualized clinical management.

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.