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A multi-omics approach to blood-based biomarker discovery in pancreatic cancer with a focus on biomarkers for early disease detection
No full text© 2025 Belinda LeePancreatic ductal adenocarcinoma (PDAC) incidence and mortality is rising globally [1-4]. With no reliable early detection screening tool for PDAC, it is commonly detected at an advanced incurable stage. Identifying cancer-specific aberrations in blood-based “liquid biopsies” from patients with PDAC could provide a useful and non-invasive companion biomarker tool that supports earlier cancer detection, guides cancer management, and could potentially unlock the keys to finding benefit from immunotherapies in this poor prognosis disease.
As part of the first aim, a stepwise examination of various blood-based markers was undertaken using samples from patients enrolled in the PURPLE pancreatic cancer registry. Firstly, by correlating baseline and clinical outcome data of 2507 PDAC patients, It was demonstrated that a simple immune inflammatory index, namely the neutrophil lymphocyte ratio (NLR), correlates with disease stage and overall survival in PDAC. Next, a longitudinal analysis of tracked pre-operative and post-operative circulating tumour DNA (ctDNA) collected via a registry-based clinical trial revealed that ctDNA is a disease specific biomarker in PDAC and is a sensitive independent prognostic marker for recurrence free survival and overall survival in early-stage PDAC.
For the second aim, an in-depth comprehensive characterisation of circulating immune biomarkers was undertaken using mass cytometry time of flight (CyTOF) and multiplex cytokine analysis performed on patient samples. Parallel examination of matched peripheral blood and clinical data from a cohort of 277 participants that included early-stage and late-stage PDAC, non-PDAC pancreatic pathologies and healthy controls demonstrated that chemokines are significantly upregulated in the serum in PDAC patients, with CTACK, RANTES and IL-8 each shown to be prognostic biomarkers. CyTOF analysis demonstrated marked changes in expression of TOX, CD57, PD-1, CTLA-4, T-BET, and EOMES on gamma delta T cells, CD8+ and CD4+ T cells in the PDAC cohort compared to healthy controls, suggesting a greater degree of immune exhaustion, chronic immune cell activation, and senescence in PDAC. With advancing PDAC status (early versus late-stage), reduction in expression of TCF-1, and increased expression of VISTA and TIGIT were observed in gamma delta T cells. This provides further evidence of immune exhaustion and immune tolerance in the systemic circulation in PDAC patients, alongside higher proportional representation of myeloid subpopulations including CD68+ macrophages, MDSCs and double negative T cells.
In the last aim, in a cohort of 203 participants, a unique protein signature compromised of 246 differentially expressed proteins was observed in PDAC patients when compared to healthy controls and non-PDAC pancreatic pathologies when using an unbiased comparative proteomic approach. Upregulation of immunoglobulins including Immunoglobulin kappa variable 2D-29 (IGKV2D-29), Immunoglobulin lambda variable 4-3 (IGLV4-3) and Immunoglobulin kappa variable 2D-30 (IGKV2D-30) were demonstrated alongside significant down-regulation of metabolic pathway proteins including Fatty acid-binding protein 1 (FABP1), Aldehyde dehydrogenase 1 family member A1 (ALDH1A1), Beta-1,4-galactosyltransferase-1 (B4GALT1), Proteasome subunit alpha type-1 (PSMA1), and Glutathione synthetase (GSS) in patients with PDAC. Comparison of early-stage to late-stage PDAC samples led to the identification of 13 potential early detection biomarkers, including increased expression of Insulin like growth factor binding protein 2 (IGFBP2), Complement 9 (C9), Leucine rich alpha-2-glycoprotein-1 (LRG1), Immunoglobulin lambda constant 7 (IGLC7), Serglycin (SRGN), Immunoglobulin lambda variable 2-23 (IGLV2-23), SERPINE1, and reduced expression of Cell division cycle 5 like protein (CDC5L), N-acetly-alpha-glucosaminidase (NAGLU), Factor-VIII (F8), FABP1, Complement subcomponent C1q (C1QB) and Afamin (AFM). Subsequent, Log-Log analysis identified 22 unique altered proteins in PDAC when compared with either healthy controls or non-PDAC pancreatic pathologies such as intra papillary mucinous neoplasms (IPMN), including GSS, B4GALT1, solute carrier family 3 member 2 (SLC3A2), and Secreted protein acidic and cysteine rich (SPARC).
By taking on a broader systems-based parallel multi-omics approach, these studies expand our knowledge about key changes in the peripheral blood in patients with PDAC, revealing correlative cytokine, immune and proteomic interactions. These findings define a protein signature that could potentially be developed for early detection of PDAC and to develop models to personalise and stratify care in patients with an established diagnoses. The registry-based translational framework set-up by this study has established a training dataset and sustainable framework for future research in pancreatic cancer. This translational framework is critical to enabling the integration of multiple complex datasets that can be harnessed for future artificial intelligence (AI)-driven models to predict treatment responses, disease and explore biomarker discovery
Infrared camouflage in leaf-sitting frogs: A cautionary tale on adaptive convergence
No full textMany cryptic green animals match leaves in invisible near-infrared (NIR) wavelengths. This observation is an enduring puzzle because animals do not see NIR light, so NIR background matching is unlikely to contribute to visual camouflage. Two alternative explanations have been proposed - infrared camouflage (i.e. matching the temperature of the background) and thermoregulation - but neither hypothesis has been experimentally tested. To test these hypotheses, we developed bilayer coatings that mimicked the reflectivity of green leaf-sitting frogs with high NIR (HNIR) or low NIR (LNIR) reflectance. Under a solar simulator in the laboratory, agar model frogs with LNIR reflectance heated up more quickly and reached higher temperatures than those with HNIR reflectance. However, when placed in a tropical rainforest (natural habitat of leaf-sitting frogs), HNIR and LNIR models did not significantly differ in the similarity of surface temperature to the adjacent leaves or in core temperature, thus failing to support the infrared camouflage and thermoregulation hypotheses, respectively. The lack of difference between treatments is probably due to the limited exposure of frogs to direct solar radiation in their natural habitats. We propose an explanation for NIR background matching based on specific mechanisms underlying green coloration and translucence in frogs and caution against assuming adaptive convergence
Capturing the emergent dynamical structure in biophysical neural models
No full textComplex neural systems can display structured emergent dynamics. Capturing this structure remains a significant scientific challenge. Using information theory, we apply Dynamical Independence (DI) to uncover the emergent dynamical structure in a minimal 5-node biophysical neural model, shaped by the interplay of two key aspects of brain organisation: integration and segregation. In our study, functional integration within the biophysical neural model is modulated by a global coupling parameter, while functional segregation is influenced by adding dynamical noise, which counteracts global coupling. Leveraging transfer entropy, DI defines a dimensionally-reduced macroscopic variable (e.g., a coarse-graining) as emergent to the extent that it behaves as an independent dynamical process, distinct from the micro-level dynamics. Dynamical dependence (a departure from dynamical independence) is measured by minimising the transfer entropy from microlevel variables to macroscopic variables across spatial scales. Our results indicate that the degree of emergence of macroscopic variables is relatively minimised at balanced points of integration and segregation and maximised at the extremes. Additionally, our method identifies to which degree the macroscopic dynamics are localised across microlevel nodes, thereby elucidating the emergent dynamical structure through the relationship between microscopic and macroscopic processes. We find that deviation from a balanced point between integration and segregation results in a less localised, more distributed emergent dynamical structure as identified by DI. This finding suggests that a balance of functional integration and segregation is associated with lower levels of emergence (higher dynamical dependence), which may be crucial for sustaining coherent, localised emergent macroscopic dynamical structures. This work also provides a complete computational implementation for the identification of emergent neural dynamics that could be applied both in silico and in vivo
Rapid Patient-Specific Simulation of Revision Hip Arthroplasty involving Acetabular Defects
No full text© 2025 Daniel Charles HopkinsThe acetabulum, the pelvic articular surface of the hip joint, is essential for maintaining mobility. Degeneration of the soft tissue of the acetabulum can lead to loss of mobility and a reduction in health and quality of life. Total hip arthroplasty (THA) is the established treatment for end-stage pathologies of the hip joint, and involves replacement of the femoral head and acetabulum with prosthetic components. While mostly successful, complications of THA such as infection, dislocation and implant loosening can occur and ultimately may require revision of THA implants, known as revision total hip arthroplasty (rTHA). rTHA is often associated with acetabular defects, which can reduce the volume and quality of bone in the acetabulum, complicating the reconstruction of the hip joint. Due to this, the re-revision rates of rTHA involving acetabular defects are over 5 times higher than revision rates of primary THA. Computational modelling has played an increasing role in the diagnosis, planning, treatment, and post-operative assessment of acetabular reconstruction in the presence of defects, but current methods are largely manual and time consuming to perform. This has limited their role to the development of custom implants for large acetabular defects and to the research environment.
The objective of this thesis was to develop and validate automated computational tools that enable rapid estimation of optimal implant configurations to reduce re-revision rates in rTHA. In the research setting, such tools could enable virtual clinical trials in which large cohort finite element studies are carried out, simulating the full range of defect anatomy and implant configurations seen within the general population.
A systematic review was conducted to investigate current computational methods used in all clinical stages of rTHA involving acetabular defects, including defect identification, reconstruction and classification; implant selection and placement; acetabular implant design; and quantifying implant functional performance. Manual image segmentation from computed tomography (CT) scans, which is time consuming, remains the primary method used to generate 3D models of pelvis, while statistical shape models (SSMs) can be used to rapidly estimate pre-defect anatomy accurately. Finite element modelling has seen much use to estimate the post-operative mechanical interactions between implant and bone. However, advanced methods such as neural network segmentation of CT images have yet to be applied to acetabular defects in the setting of rTHA.
An artificial neural network and statistical shape modelling based pipeline was then developed that automatically reconstructed the acetabulum and quantified acetabular defect volumes and depth, comparing these values with clinically assessed acetabular defect classifications. This pipeline was then extended to automatically perform a realistic virtual rTHA procedure on the pathological hemipelvis model. The virtual surgery aimed to recreate native acetabular parameters such as centre of rotation, acetabular inclination and anteversion, while also minimising bone loss and calculating potential screw trajectories. Finally, an automated post-operative finite element simulation algorithm was developed and used to compare and estimate implant stability indicators of four different screw configurations across a large cohort of 60 subjects. Validation of the finite element modelling results was attempted via two cadaveric experiments. These experiments represent the first attempt to measure acetabular trabecular bone strains adjacent to a revision acetabular cup.
The results of these studies showed that automated diagnosis, preoperative planning, virtual surgery and post-operative simulation of rTHA involving acetabular defects is possible. The automated modelling pipeline reconstructed acetabular defect anatomy with a mean accuracy of 82.7%, but alignment of bone loss volumes and defect depths with clinical classifications was poor. Finite element estimations of implant stability indicated micromotion in the acetabulum is highly regional and that additional inferior fixation into ischium and superior pubic ramus can significantly reduce micromotion in the posterior and anterior acetabulum following rTHA. Validation of trabecular bone strains against experimental values was not possible, although similar trends in response to increased load and decreasing distance from the bone-implant interface were observed in experimental and finite element estimated values.
This thesis presents new methodologies and data regarding the treatment and post-operative assessment of rTHA involving acetabular defects. The results may be useful in both the clinical and research settings. Automation of these methods may allow easier translation of these methods into the clinical space, bringing the most advance research methods to everyday treatment. The virtual clinical trials framework presented, and subsequent results may be useful in guiding new surgical reconstruction strategies, improved revision acetabular implant design and reducing re-revision rates of rTHA involving acetabular defects
Gene content of seawater microbes is a strong predictor of water chemistry across the Great Barrier Reef
No full textBACKGROUND: Seawater microbes (bacteria and archaea) play essential roles in coral reefs by facilitating nutrient cycling, energy transfer, and overall reef ecosystem functioning. However, environmental disturbances such as degraded water quality and marine heatwaves, can impact these vital functions as seawater microbial communities experience notable shifts in composition and function when exposed to stressors. This sensitivity highlights the potential of seawater microbes to be used as indicators of reef health. Microbial indicator analysis has centered around measuring the taxonomic composition of seawater microbial communities, but this can obscure heterogeneity of gene content between taxonomically similar microbes, and thus, microbial functional genes have been hypothesized to have more scope for predictive potential, though empirical validation for this hypothesis is still pending. Using a metagenomics study framework, we establish a functional baseline of seawater microbiomes across offshore Great Barrier Reef (GBR) sites to compare the diagnostic value between taxonomic and functional information in inferring continuous physico-chemical metrics in the surrounding reef. RESULTS: Integrating gene-centric metagenomics analyses with 17 physico-chemical variables (temperature, salinity, and particulate and dissolved nutrients) across 48 reefs revealed that associations between microbial functions and environmental parameters were twice as stable compared to taxonomy-environment associations. Distinct seasonal variations in surface water chemistry were observed, with nutrient concentrations up to threefold higher during austral summer, explained by enhanced production of particulate organic matter (POM) by photoautotrophic picocyanobacteria, primarily Synechococcus. In contrast, nutrient levels were lower in winter, and POM production was also attributed to Prochlorococcus. Additionally, heterotrophic microbes (e.g., Rhodospirillaceae, Burkholderiaceae, Flavobacteriaceae, and Rhodobacteraceae) were enriched in reefs with elevated dissolved organic carbon (DOC) and phytoplankton-derived POM, encoding functional genes related to membrane transport, sugar utilization, and energy metabolism. These microbes likely contribute to the coral reef microbial loop by capturing and recycling nutrients derived from Synechococcus and Prochlorococcus, ultimately transferring nutrients from picocyanobacterial primary producers to higher trophic levels. CONCLUSION: This study reveals that functional information in reef-associated seawater microbes more robustly associates with physico-chemical variables than taxonomic data, highlighting the importance of incorporating microbial function in reef monitoring initiatives. Our integrative approach to mine for stable seawater microbial biomarkers can be expanded to include additional continuous metrics of reef health (e.g., benthic cover of corals and macroalgae, fish counts/biomass) and may be applicable to other large-scale reef metagenomics datasets beyond the GBR. Video Abstract
A common form of dominant human IFNAR1 deficiency impairs IFN-α and -ω but not IFN-β-dependent immunity
No full textAutosomal recessive deficiency of the IFNAR1 or IFNAR2 chain of the human type I IFN receptor abolishes cellular responses to IFN-α, -β, and -ω, underlies severe viral diseases, and is globally very rare, except for IFNAR1 and IFNAR2 deficiency in Western Polynesia and the Arctic, respectively. We report 11 human IFNAR1 alleles, the products of which impair but do not abolish responses to IFN-α and -ω without affecting responses to IFN-β. Ten of these alleles are rare in all populations studied, but the remaining allele (P335del) is common in Southern China (minor allele frequency ≈2%). Cells heterozygous for these variants display a dominant phenotype in vitro with impaired responses to IFN-α and -ω, but not -β, and viral susceptibility. Negative dominance, rather than haploinsufficiency, accounts for this dominance. Patients heterozygous for these variants are prone to viral diseases, attesting to both the dominance of these variants clinically and the importance of IFN-α and -ω for protective immunity against some viruses
Mapping immune checkpoint inhibitor side effects to item libraries for use in real-time side effect monitoring systems
No full textBackground: Monitoring for the side effects of novel therapies using patient-reported outcomes (PROs) is critical for ensuring patient safety. Existing static patient-reported outcome measures may not provide adequate coverage of novel side effects. Item libraries provide a flexible approach to monitoring for side effects using customized item lists, but the ideal process for matching side effects to items sourced from multiple item libraries is yet to be established. We sought to develop a pragmatic process for mapping side effects to items from three major item libraries using immune checkpoint inhibitor (ICI) side effects as an example. Methods: Using a consumer- and clinician-driven list of 36 ICI side effects, two authors independently mapped side effects to Common Terminology Criteria for Adverse Event (CTCAE) terms, and then to three item libraries: the Patient-Reported Outcome version of the Common Terminology Criteria for Adverse Events (PRO-CTCAE), the European Organisation for Research and Treatment of Cancer (EORTC) Item Library, and the Functional Assessment of Chronic Illness Therapy (FACIT) searchable library. The rates of inter-rater agreement were recorded. Following item collation from the item libraries, we devised criteria for selecting the optimal item for each side effect for inclusion in a future electronic PRO system based on guidance from the above groups. Results: All 36 side effects mapped to at least one CTCAE term, with eight mapping to more than one term. Twenty-three side effects mapped to at least one PRO-CTCAE term, 35 side effects mapped to at least one EORTC item, and 31 side effects mapped to at least one FACIT item. The inter-rater agreement rate was 100% (PRO-CTCAE), 83% (EORTC) and 75% (FACIT). Pre-determined criteria were applied to select the optimal item for each side effect from the three item libraries, producing a final 61-item list. Conclusion: Using ICI side effects as an example, we developed a pragmatic approach to creating customized item lists from three major item libraries to monitor for side effects of novel therapies in routine care. This process highlighted the challenges of using item libraries and priorities for future work to improve their usability
Enzalutamide in metastatic hormone-sensitive prostate cancer: A plain language summary of the ARCHES and ENZAMET follow-up studies
No full textWHAT IS THIS SUMMARY ABOUT?: This summary includes information from the ARCHES and ENZAMET follow-up studies. Both studies looked at enzalutamide treatment for people with metastatic hormone-sensitive prostate cancer (known as mHSPC). In ARCHES, researchers compared the medications enzalutamide + androgen deprivation therapy (known as ADT) with placebo + ADT. In ENZAMET, researchers compared enzalutamide + ADT with standard treatment + ADT. Some people in ENZAMET also took enzalutamide with docetaxel (a chemotherapy treatment). In both studies, researchers wanted to find out if enzalutamide helps people with mHSPC live longer. WHAT ARE THE KEY TAKEAWAYS?: In both studies, researchers found that people with mHSPC who took enzalutamide lived longer than people who did not. People who took enzalutamide also lived longer without their cancer getting worse. The results were mostly similar in groups of people dependingon when and where their cancer was found. Researchers did not find any new safety concerns. WHAT WERE THE MAIN CONCLUSIONS?: People with mHSPC may benefit from long-term treatment with enzalutamide + ADT. They may also benefit from taking enzalutamide with other treatments, like docetaxel. It may be better for people with mHSPC to have enzalutamide treatment before their cancer gets worse, rather than waiting. These people and their doctors should carefully consider the benefits and risks of each treatment to make a joint decision for treating mHSPC.Clinical Trial Registration: NCT02677896 (ARCHES), NCT02446405 (ENZAMET) (ClinicalTrials.gov)
Impact of socioeconomic status on utilisation of a Virtual Emergency Department: An exploratory analysis
No full textObjective: To explore whether utilisation of a Virtual Emergency Department (VVED) differs according to socioeconomic status (SES). Methods: A retrospective analysis was undertaken of data from the VVED – a telehealth service that provides care for patients across Victoria, Australia with non-life-threatening emergencies. The study included all individuals who presented to the VVED between July 2022 and June 2023 through the two most common referral pathways (self-referral and ambulance referral). Area-level SES was ascertained by matching residential postcodes to the corresponding Australian Bureau of Statistics (ABS) Index of Relative Socioeconomic Advantage and Disadvantage (IRSAD) decile. IRSAD scores were divided into quintiles (1 = lowest SES, 5 = highest SES) and multivariable logistic regression modelling was used to analyse associations between the SES quintile and referral pathway, presented as odds ratios (ORs) with 95% confidence intervals (CIs). Results: There were 68 598 participants included in the analyses (mean age: 36.6 years; 58.4% female). Compared to SES quintile 3, higher odds of self-referral to the VVED were observed in the two most advantaged SES groups (Quintile 4; adjusted OR [aOR] = 1.16; 95% CI: 1.06–1.26; P = 0.001) (Quintile 5; aOR = 1.38; 95% CI: 1.25–1.52; P < 0.001). Conversely, lower odds of self-referral were observed in the most disadvantaged SES group (Quintile 1; aOR = 0.82; 95% CI: 0.75–0.90; P < 0.001). Conclusions: The present study demonstrated a relatively even utilisation of the VVED service across SES population groups. The use of healthcare provider pathways, such as ambulance paramedics, may increase equitable access to telehealth. Clinical attention should be directed toward specific social groups in the emergency care setting
ASA Class Is a Stronger Predictor of Early Revision Risk Following Primary Total Knee Arthroplasty than BMI
No full textBACKGROUND: Although there is a known correlation between obesity and revision risk following total knee arthroplasty (TKA), there is an ongoing debate regarding the appropriateness of denying TKA solely based on the body mass index (BMI) of a patient. Our aim was to determine whether a patient's American Society of Anesthesiologists (ASA) class predicts their risks of early all-cause revision and revision for periprosthetic joint infection (PJI) following primary TKA, independent of their BMI. METHODS: Data from the Australian Orthopaedic Association National Joint Replacement Registry (AOANJRR) were obtained regarding all patients who underwent primary TKA for osteoarthritis in Australia from January 1, 2015, to December 31, 2022. Estimated hazard ratios of all-cause revision and revision for PJI, as well as predicted risks of revision within 3 months, 1 year, and 2 years, as a function of patient ASA class and BMI, were calculated with use of multivariable Cox proportional hazards models. RESULTS: A total of 274,786 primary TKAs (54.5% female; mean age, 68.3 years) were included in the study, of which 5,401 were revised during the study period. Compared with BMI, ASA class was a stronger predictor of the risks of all-cause revision and revision for PJI following primary TKA. Patients with an ASA class of 3 to 4 had higher risks of all-cause revision and revision for PJI at multiple time points after TKA compared with patients with an ASA class of 1 to 2, regardless of BMI. CONCLUSIONS: Although ASA class and BMI are theoretically interrelated variables, we found that a patient's ASA class was more strongly associated with their risks of early all-cause revision and revision for PJI following primary TKA than their BMI. Employing a BMI threshold in isolation when assessing fitness for TKA may be inappropriate, and surgeons should give greater weight to the other medical comorbidities and general perioperative fitness of the patient. Patients with poorly controlled comorbidities should be referred for medical optimization prior to TKA. LEVEL OF EVIDENCE: Prognostic Level III. See Instructions for Authors for a complete description of levels of evidence