Transcriptomic Analysis Reveals Receptor Subclass-Specific Immune Regulation of CD8+ T Cells by Opioids

Melatonin, BAG-1 and cortisol circadian interactions in tumor pathogenesis and patterned immune responses

A dysregulated circadian rhythm is significantly associated with cancer risk, as is aging. Both aging and circadian dysregulation show suppressed pineal melatonin, which is indicated in many studies to be linked to cancer risk and progression. Another independently investigated aspect of the circadian rhythm is the cortisol awakening response (CAR), which is linked to stress-associated hypothalamus-pituitary-adrenal (HPA) axis activation. CAR and HPA axis activity are primarily mediated via activation of the glucocorticoid receptor (GR), which drives patterned gene expression via binding to the promotors of glucocorticoid response element (GRE)-expressing genes. Recent data shows that the GR can be prevented from nuclear translocation by the B cell lymphoma-2 (Bcl-2)-associated athanogene 1 (BAG-1), which translocates the GR to mitochondria, where it can have diverse effects. Melatonin also suppresses GR nuclear translocation by maintaining the GR in a complex with heat shock protein 90 (Hsp90). Melatonin, directly and/or epigenetically, can upregulate BAG-1, suggesting that the dramatic 10-fold decrease in pineal melatonin from adolescence to the ninth decade of life will attenuate the capacity of night-time melatonin to modulate the effects of the early morning CAR. The interactions of pineal melatonin/BAG-1/Hsp90 with the CAR are proposed to underpin how aging and circadian dysregulation are associated with cancer risk. This may be mediated via differential effects of melatonin/BAG-1/Hsp90/GR in different cells of microenvironments across the body, from which tumors emerge. This provides a model of cancer pathogenesis that better integrates previously disparate bodies of data, including how immune cells are regulated by cancer cells in the tumor microenvironment, at least partly via the cancer cell regulation of the tryptophan-melatonin pathway. This has a number of future research and treatment implications.

Opioids and immune checkpoint inhibitors differentially regulate a common immune network in triple-negative breast cancer

Background

Opioids are the primary analgesics for cancer pain. Recent clinical evidence suggests opioids may counteract the effect of immune checkpoint inhibition (ICI) immunotherapy, but the mechanism for this interaction is unknown. The following experiments study how opioids and immunotherapy modulate a common RNA expression pathway in triple negative breast cancer (TNBC), a cancer subtype in which immunotherapy is increasingly used. This study identifies a mechanism by which opioids may decrease ICI efficacy, and compares ketamine, a non-opioid analgesic with emerging use in cancer pain, for potential ICI interaction.

Methods

Tumor RNA expression and clinicopathologic data from a large cohort with TNBC (N=286) was used to identify RNA expression signatures of disease. Various drug-induced RNA expression profiles were extracted from multimodal RNA expression datasets and analyzed to estimate the RNA expression effects of ICI, opioids, and ketamine on TNBC.

Results

We identified a RNA expression network in CD8+ T-cells that was relevant to TNBC pathogenesis and prognosis. Both opioids and anti-PD-L1 ICI regulated RNA expression in this network, suggesting a nexus for opioid-ICI interaction. Morphine and anti-PD-L1 therapy regulated RNA expression in opposing directions. By contrast, there was little overlap between the effect of ketamine and anti-PD-L1 therapy on RNA expression.

Conclusions

Opioids and ICI may target a common immune network in TNBC and regulate gene expression in opposing fashion. No available evidence supports a similar interaction between ketamine and ICI.

Multi-omic molecular profiling and network biology for precision anaesthesiology: a narrative review

Technological advancement, data democratisation, and decreasing costs have led to a revolution in molecular biology in which the entire set of DNA, RNA, proteins, and various other molecules - the 'multi-omic' profile - can be measured in humans. Sequencing 1 million bases of human DNA now costs US$0.01, and emerging technologies soon promise to reduce the cost of sequencing the whole genome to US$100. These trends have made it feasible to sample the multi-omic profile of millions of people, much of which is publicly available for medical research. Can anaesthesiologists use these data to improve patient care? This narrative review brings together a rapidly growing literature in multi-omic profiling across numerous fields that points to the future of precision anaesthesiology. Here, we discuss how DNA, RNA, proteins, and other molecules interact in molecular networks that can be used for preoperative risk stratification, intraoperative optimisation, and postoperative monitoring. This literature provides evidence for four fundamental insights: (1) Clinically similar patients have different molecular profiles and, as a consequence, different outcomes. (2) Vast, publicly available, and rapidly growing molecular datasets have been generated in chronic disease patients and can be repurposed to estimate perioperative risk. (3) Multi-omic networks are altered in the perioperative period and influence postoperative outcomes. (4) Multi-omic networks can serve as empirical, molecular measurements of a successful postoperative course. With this burgeoning universe of molecular data, the anaesthesiologist-of-the-future will tailor their clinical management to an individual's multi-omic profile to optimise postoperative outcomes and long-term health.