Towards a System Level Understanding of Non-Model Organisms Sampled from the Environment: A Network Biology Approach

The acquisition and analysis of datasets including multi-level omics and physiology from non-model species, sampled from field populations, is a formidable challenge, which so far has prevented the application of systems biology approaches. If successful, these could contribute enormously to improving our understanding of how populations of living organisms adapt to environmental stressors relating to, for example, pollution and climate. Here we describe the first application of a network inference approach integrating transcriptional, metabolic and phenotypic information representative of wild populations of the European flounder fish, sampled at seven estuarine locations in northern Europe with different degrees and profiles of chemical contaminants. We identified network modules, whose activity was predictive of environmental exposure and represented a link between molecular and morphometric indices. These sub-networks represented both known and candidate novel adverse outcome pathways representative of several aspects of human liver pathophysiology such as liver hyperplasia, fibrosis, and hepatocellular carcinoma. At the molecular level these pathways were linked to TNF alpha, TGF beta, PDGF, AGT and VEGF signalling. More generally, this pioneering study has important implications as it can be applied to model molecular mechanisms of compensatory adaptation to a wide range of scenarios in wild populations

The UK Divide: Does having a Pembrolizumab-Chemotherapy option in head and neck cancer matter? Real-world experience of first-line palliative pembrolizumab monotherapy and pembrolizumab-chemotherapy combination in Scotland

Aims: The Scottish Medical Consortium recently approved first-line pembrolizumab monotherapy or in combination with chemotherapy for head and neck squamous cell carcinoma in the palliative setting, contrasting with the decision made by the National Institute for Health and Care Excellence, who approved monotherapy alone in England and Wales. The aim of this study was to provide real-world performance data for first-line pembrolizumab-containing treatments for head and neck squamous cell carcinoma in the palliative setting in Scotland. Materials and methods: We analysed the electronic records of patients who started pembrolizumab-containing treatment between 1 March 2020 and 30 September 2021. Outcomes included overall survival, progression-free survival (PFS), the duration of response and the disease control rate. Data were compared with the KEYNOTE-048 study and clinical factors were evaluated for association with survival. Results: Our cohort included 91 patients (median follow-up 10.8 months). Patient characteristics were similar to those in the KEYNOTE-048 study, although our cohort had a higher proportion of patients with newly diagnosed, non-metastatic disease. For patients receiving monotherapy (n = 76), 12- and 24-month overall survival were 45% and 27%, respectively. For patients receiving pembrolizumab–chemotherapy (n = 15), 12-month overall survival was 60% (24-month overall survival had not yet been reached). Experiencing one or more immune-related adverse event (irAE; versus no irAEs), of any grade, was associated with favourable overall survival and PFS for patients receiving monotherapy in both univariable Log-rank analysis (median overall survival 17.4 months versus 8.6 months, respectively, P = 0.0033; median PFS 10.9 months versus 3.0 months, respectively, P < 0.0001) and multivariable analysis (Cox proportional hazards regression: overall survival hazard ratio 0.31, P = 0.0009; PFS hazard ratio 0.17, P < 0.0001). Conclusion: Our real-world data support the KEYNOTE-048 study findings and the value of combination treatment options. Additionally, our data show that irAEs of any grade, as reported in routine clinical records, are associated with better outcomes in this patient group, adding to the growing body of evidence showing that irAEs are generally a positive marker of programmed death-ligand 1 (PD-L1) inhibitor response