MicroRNA-Mediated Drug Repurposing Unveiled Potential Candidate Drugs for Prolactinoma Treatment

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.

Is prolactin receptor signaling a target in dopamine-resistant prolactinomas?

The hypothalamic neuroendocrine catecholamine dopamine regulates the lactotroph function, including prolactin (PRL) secretion, proliferation, and apoptosis. The treatment of PRL-secreting tumors, formerly known as prolactinomas, has relied mainly on this physiological characteristic, making dopamine agonists the first therapeutic alternative. Nevertheless, the group of patients that do not respond to this treatment has few therapeutical options. Prolactin is another physiological regulator of lactotroph function, acting as an autocrine/paracrine factor that controls PRL secretion and cellular turnover, inducing apoptosis and decreasing proliferation. Furthermore, the signaling pathways related to these effects, mainly JAK/STAT and PI3K/Akt, and MAPK, have been extensively studied in prolactinomas and other tumors as therapeutic targets. In the present work, the relationship between PRL pathophysiology and prolactinoma development is explored, aiming to comprehend the value of PRL and PRLR-associated pathways as exploratory fields alternative to dopamine-related approaches, which are worth physiological characteristics that might be impaired and can be potentially restored or upregulated to provide more options to the patients.

Past, Present, and Future of Therapies for Pituitary Neuroendocrine Tumors: Need for Omics and Drug Repositioning Guidance

Innovation roadmaps are important, because they encourage the actors in an innovation ecosystem to creatively imagine multiple possible science future(s), while anticipating the prospects and challenges on the innovation trajectory. In this overarching context, this expert review highlights the present unmet need for therapeutic innovations for pituitary neuroendocrine tumors (PitNETs), also known as pituitary adenomas. Although there are many drugs used in practice to treat PitNETs, many of these drugs can have negative side effects and show highly variable outcomes in terms of overall recovery. Building innovation roadmaps for PitNETs' treatments can allow incorporation of systems biology approaches to bring about insights at multiple levels of cell biology, from genes to proteins to metabolites. Using the systems biology techniques, it will then be possible to offer potential therapeutic strategies for the convergence of preventive approaches and patient-centered disease treatment. Here, we first provide a comprehensive overview of the molecular subtypes of PitNETs and therapeutics for these tumors from the past to the present. We then discuss examples of clinical trials and drug repositioning studies and how multi-omics studies can help in discovery and rational development of new therapeutics for PitNETs. Finally, this expert review offers new public health and personalized medicine approaches on cases that are refractory to conventional treatment or recur despite currently used surgical and/or drug therapy.

Molecular Pathways in Prolactinomas: Translational and Therapeutic Implications

Prolactinoma has the highest incidence rate among patients with functional pituitary tumours. Although mostly benign, there is a subgroup that can be aggressive. Some clinical, radiological and pathology features have been associated with a poor prognostic. Therefore, it can be considered as a group of heterogeneous tumours. The aim of this paper is to give an overview of the molecular pathways involved in the behaviour of prolactinoma in order to improve our approach and gain deeper insight into the better understanding of tumour development and its management. This is essential for identifying patients harbouring aggressive prolactinoma and to establish personalised therapeutics options.

Overview of omics biomarkers in pituitary neuroendocrine tumors to design future diagnosis and treatment strategies

Pituitary neuroendocrine tumors (PitNETs) are the second most common type of intracranial neoplasia. Since their manifestation usually causes hormone hypersecretion, effective management of PitNETs is indisputably necessary. Most of the non-functioning PitNETs pose a real challenge in diagnosis as they grow without giving any signs. Despite the good response of prolactinomas to dopamine agonist therapy, some of these tumors persist or recur; also, about 20% are resistant and 10% behave aggressively. The silent corticotropinomas may not cause symptoms until the tumor mass causes a complication. In somatotropinomas, the possibility of recurrence after transsphenoidal resection is more common in pediatric patients than in adult patients. Therefore, detection of tumors at early stages or identification of recurrence and remission after transsphenoidal surgery would allow wiser management of the disease. Extensive studies have been performed to uncover potential signatures that can be used for preventive diagnosis and/or prognosis of PitNETs as well as for targeted therapy. These molecular signatures at multiple biological levels hold promise for the convergence of preventive approaches and patient-centered disease management and offer potential therapeutic strategies. In this review, we provide an overview of the omics-based biomarker research and highlight the multi-omics signatures that have been proposed as pitNET biomarkers. In addition, understanding the multi-omics data integration of current biomarker discovery strategies was discussed in terms of preventive, predictive, and personalized medicine. The topics discussed in this review will help to develop broader visions for pitNET research, diagnosis, and therapy, particularly in the context of personalized medicine.

Treatment Strategies for Dopamine Agonist-Resistant and Aggressive Prolactinomas: A Comprehensive Analysis of the Literature

Despite most of the prolactinomas can be treated with endocrine therapy and/or surgery, a significant percentage of these tumors can be resistant to endocrine treatments and/or recur with prominent invasion into the surrounding anatomical structures. Hence, clinical, pathological, and molecular definitions of aggressive prolactinomas are important to guide for classical and novel treatment modalities. In this review, we aimed to define molecular endocrinological features of dopamine agonist-resistant and aggressive prolactinomas for designing future multimodality treatments. Besides surgery, temozolomide chemotherapy and radiotherapy, peptide receptor radionuclide therapy, estrogen pathway modulators, progesterone antagonists or agonists, mTOR/akt inhibitors, pasireotide, gefitinib/lapatinib, everolimus, and metformin are tested in preclinical models, anecdotal cases, and in small case series. Moreover, chorionic gonadotropin, gonadotropin releasing hormone, TGFβ and PRDM2 may seem like possible future targets for managing aggressive prolactinomas. Lastly, we discussed our management of a unique prolactinoma case by asking which tumors' proliferative index (Ki67) increased from 5-6% to 26% in two subsequent surgeries performed in a 2-year period, exerted massive invasive growth, and secreted huge levels of prolactin leading up to levels of 1 605 671 ng/dl in blood.

Therapeutic Targeting of Repurposed Anticancer Drugs in Alzheimer's Disease: Using the Multiomics Approach

AIM/HYPOTHESIS

The complexity and heterogeneity of multiple pathological features make Alzheimer's disease (AD) a major culprit to global health. Drug repurposing is an inexpensive and reliable approach to redirect the existing drugs for new indications. The current study aims to study the possibility of repurposing approved anticancer drugs for AD treatment. We proposed an in silico pipeline based on "omics" data mining that combines genomics, transcriptomics, and metabolomics studies. We aimed to validate the neuroprotective properties of repurposed drugs and to identify the possible mechanism of action of the proposed drugs in AD.

RESULTS

We generated a list of AD-related genes and then searched DrugBank database and Therapeutic Target Database to find anticancer drugs related to potential AD targets. Specifically, we researched the available approved anticancer drugs and excluded the information of investigational and experimental drugs. We developed a computational pipeline to prioritize the anticancer drugs having a close association with AD targets. From data mining, we generated a list of 2914 AD-related genes and obtained 49 potential druggable targets by functional enrichment analysis. The protein-protein interaction (PPI) studies for these genes revealed 641 interactions. We found that 15 AD risk/direct PPI genes were associated with 30 approved oncology drugs. The computational validation of candidate drug-target interactions, structural and functional analysis, investigation of related molecular mechanisms, and literature-based analysis resulted in four repurposing candidates, of which three drugs were epidermal growth factor receptor (EGFR) inhibitors.

CONCLUSION

Our computational drug repurposing approach proposed EGFR inhibitors as potential repurposing drugs for AD. Consequently, our proposed framework could be used for drug repurposing for different indications in an economical and efficient way.