Clinical and radiological presentation of parasellar ectopic pituitary adenomas: case series and systematic review of the literature

Clival ectopic pituitary prolactinoma was successfully managed by transsphenoidal surgery: A rare case report

Key Clinical Message

Ectopic pituitary adenoma is a rare neoplasm located in the clivus and could mimic other clival tumors. Diagnosis and treatment could be challenging. It should be considered in the differential diagnosis of clival tumors.

Abstract

Ectopic pituitary adenomas (EPAs) are isolated adenomas that can be located in variable locations outside the sella turcica and have a normal-appearing pituitary gland. These tumors are rare and are thought to often arise from embryological remnants along the route of Rathke's pouch migration. EPAs are associated with a wide range of clinical manifestations depending on hormonal activity and involvement of adjacent structures, which can represent a challenge in making the diagnosis and deciding on the most appropriate management. In this case study, we report a 47-year-old male who presented with visual disturbances, a headache, and generalized weakness. Magnetic resonance imaging showed a 2 cm mass located in the clivus invading the sphenoid sinus with an intact pituitary gland. The patient underwent endoscopic transsphenoidal surgery to eradicate the mass while maintaining the integrity of the pituitary gland, which was successful and uneventful. Pathological studies were consistent with prolactinoma, with no cytological malignant features. Post-surgery, symptoms notably improved, and serum prolactin levels significantly dropped, The patient's condition was satisfactory on follow-up with no long-term complications reported. This paper contributes to the existing literature by sharing the clinical management of a challenging and uncommon case.

Prediction of intraoperative cerebrospinal fluid leaks in endoscopic endonasal transsphenoidal pituitary surgery based on a deep neural network model trained with MRI images: a pilot study

Objective

This study aimed to investigate the reliability of a deep neural network (DNN) model trained only on contrast-enhanced T1 (T1CE) images for predicting intraoperative cerebrospinal fluid (ioCSF) leaks in endoscopic transsphenoidal surgery (EETS).

Methods

396 pituitary adenoma (PA) cases were reviewed, only primary PAs with Hardy suprasellar Stages A, B, and C were included in this study. The T1CE images of these patients were collected, and sagittal and coronal T1CE slices were selected for training the DNN model. The model performance was evaluated and tested, and its interpretability was explored.

Results

A total of 102 PA cases were enrolled in this study, 51 from the ioCSF leakage group, and 51 from the non-ioCSF leakage group. 306 sagittal and 306 coronal T1CE slices were collected as the original dataset, and data augmentation was applied before model training and testing. In the test dataset, the DNN model provided a single-slice prediction accuracy of 97.29%, a sensitivity of 98.25%, and a specificity of 96.35%. In clinical test, the accuracy of the DNN model in predicting ioCSF leaks in patients reached 84.6%. The feature maps of the model were visualized and the regions of interest for prediction were the tumor roof and suprasellar region.

Conclusion

In this study, the DNN model could predict ioCSF leaks based on preoperative T1CE images, especially in PAs in Hardy Stages A, B, and C. The region of interest in the model prediction-making process is similar to that of humans. DNN models trained with preoperative MRI images may provide a novel tool for predicting ioCSF leak risk for PA patients.

Epigenomic and transcriptomic landscaping unraveled candidate repositioned therapeutics for non-functioning pituitary neuroendocrine tumors

PURPOSE

Non-functioning pituitary neuroendocrine tumors are challengingly diagnosed tumors in the clinic. Transsphenoidal surgery remains the first-line treatment. Despite the development of state-of-the-art techniques, no drug therapy is currently approved for the treatment. There are also no randomized controlled trials comparing therapeutic strategies or drug therapy for the management after surgery. Therefore, novel therapeutic interventions for the therapeutically challenging NF-PitNETs are urgently needed.

METHODS

We integrated epigenome and transcriptome data (both coding and non-coding) that elucidate disease-specific signatures, in addition to biological and pharmacological data, to utilize rational pathway and drug prioritization in NF-PitNETs. We constructed an epigenome- and transcriptome-based PPI network and proposed hub genes. The signature-based drug repositioning based on the integration of multi-omics data was performed.

RESULTS

The construction of a disease-specific network based on three different biological levels revealed DCC, DLG5, ETS2, FOXO1, HBP1, HMGA2, PCGF3, PSME4, RBPMS, RREB1, SMAD1, SOCS1, SOX2, YAP1, ZFHX3 as hub proteins. Signature-based drug repositioning using hub proteins yielded repositioned drug candidates that were confirmed in silico via molecular docking. As a result of molecular docking simulations, palbociclib, linifanib, trametinib, eplerenone, niguldipine, and zuclopenthixol showed higher binding affinities with hub genes compared to their inhibitors and were proposed as potential repositioned therapeutics for the management of NF-PitNETs.

CONCLUSION

The proposed systems' biomedicine-oriented multi-omics data integration for drug repurposing to provide promising results for the construction of effective clinical therapeutics. To the best of our knowledge, this is the first study reporting epigenome- and transcriptome-based drug repositioning for NF-PitNETs using in silico confirmations.

Emerging Roles of miRNA, lncRNA, circRNA, and Their Cross-Talk in Pituitary Adenoma

Pituitary adenoma (PA) is a common intracranial tumor without specific biomarkers for diagnosis and treatment. Non-coding RNAs (ncRNAs), including microRNAs (miRNA), long non-coding RNA (lncRNA), and circular RNA (circRNA), regulate a variety of cellular processes, such as cell proliferation, differentiation, and apoptosis. Increasing studies have shown that the dysregulation of ncRNAs, especially the cross-talk between lncRNA/circRNA and miRNA, is related to the pathogenesis, diagnosis, and prognosis of PA. Therefore, ncRNAs can be considered as promising biomarkers for PA. In this review, we summarize the roles of ncRNAs from different specimens (i.e., tissues, biofluids, cells, and exosomes) in multiple subtypes of PA and highlight important advances in understanding the contribution of the cross-talk between ncRNAs (e.g., competing endogenous RNAs) to PA disease.