Relevance of Mu-Opioid Receptor Splice Variants and Plasticity of Their Signaling Sequelae to Opioid Analgesic Tolerance

Histamine H3 Receptor Isoforms: Insights from Alternative Splicing to Functional Complexity

Alternative splicing significantly enhances the diversity of the G protein-coupled receptor (GPCR) family, including the histamine H3 receptor (H3R). This post-transcriptional modification generates multiple H3R isoforms with potentially distinct pharmacological and physiological profiles. H3R is primarily involved in the presynaptic inhibition of neurotransmitter release in the central nervous system. Despite the approval of pitolisant for narcolepsy (Wakix®) and daytime sleepiness in adults with obstructive sleep apnea (Ozawade®) and ongoing clinical trials for other H3R antagonists/inverse agonists, the functional significance of the numerous H3R isoforms remains largely enigmatic. Recent publicly available RNA sequencing data have confirmed the expression of multiple H3R isoforms in the brain, with some isoforms exhibiting unique tissue-specific distribution patterns hinting at isoform-specific functions and interactions within neural circuits. In this review, we discuss the complexity of H3R isoforms with a focus on their potential roles in central nervous system (CNS) function. Comparative analysis across species highlights evolutionary conservation and divergence in H3R splicing, suggesting species-specific regulatory mechanisms. Understanding the functionality of H3R isoforms is crucial for the development of targeted therapeutics. This knowledge will inform the design of more precise pharmacological interventions, potentially enhancing therapeutic efficacy and reducing adverse effects in the treatment of neurological and psychiatric disorders.

How do opioids control pain circuits in the brainstem during opioid-induced disorders and in chronic pain? Implications for the treatment of chronic pain

ABSTRACT

Brainstem areas involved in descending pain modulation are crucial for the analgesic actions of opioids. However, the role of opioids in these areas during tolerance, opioid-induced hyperalgesia (OIH), and in chronic pain settings remains underappreciated. We conducted a revision of the recent studies performed in the main brainstem areas devoted to descending pain modulation with a special focus on the medullary dorsal reticular nucleus (DRt), as a distinctive pain facilitatory area and a key player in the diffuse noxious inhibitory control paradigm. We show that maladaptive processes within the signaling of the µ-opioid receptor (MOR), which entail desensitization and a switch to excitatory signaling, occur in the brainstem, contributing to tolerance and OIH. In the context of chronic pain, the alterations found are complex and depend on the area and model of chronic pain. For example, the downregulation of MOR and δ-opioid receptor (DOR) in some areas, including the DRt, during neuropathic pain likely contributes to the inefficacy of opioids. However, the upregulation of MOR and DOR, at the rostral ventromedial medulla, in inflammatory pain models, suggests therapeutic avenues to explore. Mechanistically, the rationale for the diversity and complexity of alterations in the brainstem is likely provided by the alternative splicing of opioid receptors and the heteromerization of MOR. In conclusion, this review emphasizes how important it is to consider the effects of opioids at these circuits when using opioids for the treatment of chronic pain and for the development of safer and effective opioids.

Involvement of the Opioid Peptide Family in Cancer Progression

Peptides mediate cancer progression favoring the mitogenesis, migration, and invasion of tumor cells, promoting metastasis and anti-apoptotic mechanisms, and facilitating angiogenesis/lymphangiogenesis. Tumor cells overexpress peptide receptors, crucial targets for developing specific treatments against cancer cells using peptide receptor antagonists and promoting apoptosis in tumor cells. Opioids exert an antitumoral effect, whereas others promote tumor growth and metastasis. This review updates the findings regarding the involvement of opioid peptides (enkephalins, endorphins, and dynorphins) in cancer development. Anticancer therapeutic strategies targeting the opioid peptidergic system and the main research lines to be developed regarding the topic reviewed are suggested. There is much to investigate about opioid peptides and cancer: basic information is scarce, incomplete, or absent in many tumors. This knowledge is crucial since promising anticancer strategies could be developed alone or in combination therapies with chemotherapy/radiotherapy.

Understanding Opioid Actions, Pain and Analgesia: A Tribute to Dr. Gavril Pasternak

This special issue is a tribute to our mentor, colleague and friend, Gavril W. Pasternak, MD, PhD. Homage to the breadth and depth of his work (~ 450 publications) over a 40 career in pharmacology and medicine cannot be captured fully in one special issue, but the 22 papers collected herein represent seven of the topics near and dear to Gav's heart, and the colleagues, friends and mentees who held him near to theirs. The seven themes include: (1) sites and mechanisms of opioid actions in vivo; (2) development of novel analgesic agents; (3) opioid tolerance, withdrawal and addiction: mechanisms and treatment; (4) opioid receptor splice variants; (5) novel research tools and approaches; (6) receptor signaling and crosstalk in vitro; and (7) mentorship. This introduction to the issue summarizes contributions and includes formal and personal remembrances of Gav that illustrate his personality, warmth, and dedication to making a difference in patient care and people's lives.

Enhanced Understanding of Molecular Interactions and Function Underlying Pain Processes Through Networks of Transcript Isoforms, Genes, and Gene Families

Introduction

Molecular networks based on the abundance of mRNA at the gene level and pathway networks that relate families or groups of paralog genes have supported the understanding of interactions between molecules. However, multiple molecular mechanisms underlying health and behavior, such as pain signal processing, are modulated by the abundances of the transcript isoforms that originate from alternative splicing, in addition to gene abundances. Alternative splice variants of growth factors, ion channels, and G-protein-coupled receptors can code for proteoforms that can have different effects on pain and nociception. Therefore, networks inferred using abundance from more agglomerative molecular units (eg, gene family, or gene) have limitations in capturing interactions at a more granular level (eg, gene, or transcript isoform, respectively) do not account for changes in the abundance at the transcript isoform level.

Objective

The objective of this study was to evaluate the relative benefits of network inference using abundance patterns at various aggregate levels.

Methods

Sparse networks were inferred using Gaussian Markov random fields and a novel aggregation criterion was used to aggregate network edges. The relative advantages of network aggregation were evaluated on two molecular systems that have different dimensions and connectivity, circadian rhythm and Toll-like receptor pathways, using RNA-sequencing data from mice representing two pain level groups, opioid-induced hyperalgesia and control, and two central nervous system regions, the nucleus accumbens and the trigeminal ganglia.

Results

The inferred networks were benchmarked against the Kyoto Encyclopedia of Genes and Genomes reference pathways using multiple criteria. Networks inferred using more granular information performed better than networks inferred using more aggregate information. The advantage of granular inference varied with the pathway and data set used.

Discussion

The differences in inferred network structure between data sets highlight the differences in OIH effect between central nervous system regions. Our findings suggest that inference of networks using alternative splicing variants can offer complementary insights into the relationship between genes and gene paralog groups.