Gut-liver axis: Potential mechanisms of action of food-derived extracellular vesicles.

Food-derived extracellular vesicles (FEVs) are nanoscale membrane vesicles obtained from dietary materials such as breast milk, plants and probiotics. Distinct from other EVs, FEVs can survive the harsh degrading conditions in the gastrointestinal tract and reach the intestines. This unique feature allows FEVs to be promising prebiotics in health and oral nanomedicine for gut disorders, such as inflammatory bowel disease. Interestingly, therapeutic effects of FEVs have recently also been observed in non-gastrointestinal diseases. However, the mechanisms remain unclear or even mysterious. It is speculated that orally administered FEVs could enter the bloodstream, reach remote organs, and thus exert therapeutic effects therein. However, emerging evidence suggests that the amount of FEVs reaching organs beyond the gastrointestinal tract is marginal and may be insufficient to account for the significant therapeutic effects achieved regarding diseases involving remote organs such as the liver. Thus, we herein propose that FEVs primarily act locally in the intestine by modulating intestinal microenvironments such as barrier integrity and microbiota, thereby eliciting therapeutic impact remotely on the liver in non-gastrointestinal diseases via the gut-liver axis. Likewise, drugs delivered to the gastrointestinal system through FEVs may act via the gut-liver axis. As the liver is the main metabolic hub, the intestinal microenvironment may be implicated in other metabolic diseases. In fact, many patients with non-alcoholic fatty liver disease, obesity, diabetes and cardiovascular disease suffer from a leaky gut and dysbiosis. In this review, we provide an overview of the recent progress in FEVs and discuss their biomedical applications as therapeutic agents and drug delivery systems, highlighting the pivotal role of the gut-liver axis in the mechanisms of action of FEVs for the treatment of gut disorders and metabolic diseases.

Exploring Clinical Remission in Moderate Asthma - Perspectives from Asia, the Middle East, and South America.

INTRODUCTION: Clinical remission is a relatively new concept in asthma but recent research initiatives suggest it could be an ambitious and achievable therapeutic target for patients with asthma. METHODS: In this modified Delphi study (comprising two online surveys, completed either side of a virtual scientific workshop), the opinions of a panel of respiratory physicians were evaluated to summarize perspective statements on key therapeutic outcomes and criteria for on-treatment clinical remission in patients with moderate asthma. An agreement threshold was pre-defined as agreement by ≥ 75% of participants. RESULTS: Surveys 1 and 2 were completed by 20 and 18 participants, respectively. Most participants (95%) agreed with the concept of clinical remission in moderate asthma and that this should be a desirable treatment goal (90%). Based on a composite measure of 4-6 desirable therapeutic outcomes, current understanding of clinical remission was considered as 12 months with no exacerbations, no oral corticosteroids, no daytime or night-time asthma symptoms (Asthma Control Test score ≥ 20 or Asthma Control Questionnaire score ≤ 0.75), stable lung function, and no treatment-related adverse events. No agreement was reached on the role of relievers in defining therapeutic outcomes or on the wider use of biomarkers and airway hyperresponsiveness for defining asthma remission in clinical practice. CONCLUSIONS: In line with recent consensus statements from the United States and Europe, there was a high level of agreement on the elements of clinical remission among a panel of respiratory physicians from Asia, the Middle East, and South America. Extension of the concept of clinical remission to patients with moderate asthma was considered aligned with the potential of clinical remission as a goal of therapy.

Real-world outcomes of pemetrexed-platinum chemotherapy plus osimertinib after progression on first-line osimertinib in advanced EGFR-mutated NSCLC.

OBJECTIVES: First-line pemetrexed-platinum chemotherapy + osimertinib(Pem-Plat-Osi) improves progression-free survival as compared to osimertinib alone in advanced epidermal growth factor (EGFR)-mutated non-small cell lung cancer (NSCLC). However, many patients are hesitant to commence chemotherapy upfront. We describe outcomes to Pem-Plat-Osi after first-line osimertinib failure. MATERIALS AND METHODS: Patients with advanced EGFR-mutated (ex19del/L858R) NSCLC who had Pem-Plat-Osi between 1/7/2018-30/9/2023 after progression on first-line osimertinib at National Cancer Centre Singapore, Prince of Wales Hospital and Chinese University of Hong Kong were identified. Key endpoints were time to treatment failure (TTF) and overall survival (OS). RESULTS: A total of 60 patients were included. Median age at diagnosis was 62, 53.3 % (32/60) were male and 76.7 % (46/60) were never smokers. Ex19del comprised 56.7 % (34/60) and L858R 43.3 % (26/60). Baseline central nervous system (CNS) metastases were present in 66.7 % (40/60). Median TTF on osimertinib (TTF1) was 14.4 months(m) and median time to initiation of Pem-Plat-Osi was 41 days(d) (range 0-652) after progression on osimertinib. Partial response (PR) or stable disease to Pem-Plat-Osi was achieved in 81.7 %(49/60). Intracranial disease control was achieved in 90.6 % (29/32) of patients with measurable CNS metastases, including those who did not undergo brain radiotherapy. At median follow up of 31.2 m, median TTF on Pem-Plat-Osi (TTF2) was 6.6 m. Median TTF1 + TTF2 was 23.4 m and median OS was 34.2 m. Survival outcomes were similar comparing ex19del and L858R (median TTF1 + TTF2 21.8 m vs 23.5 m, p = 0.90; median OS 34.2 m vs 36.8 m, p = 0.37) and in patients without/with baseline CNS metastases (median TTF1 + TTF2 21.8 m vs 23.4 m, p = 0.44; median OS 36.2 m vs 31.9 m, p = 0.65). TTF1 duration was not significantly associated with TTF2 (p = 0.76). Patients who started Pem-Plat-Osi within 20d of progression on osimertinib had significantly longer TTF2 as compared to patients who started after 20d (median 8.4 m versus 6.0 months, p = 0.03), which remained statistically significant on multivariable analysis. CONCLUSIONS: Our real-world data supports the efficacy of Pem-Plat-Osi after progression on first-line osimertinib, including L858R and baseline CNS metastases. Chemotherapy initiation within 20d of Osi progression was predictive of superior TTF2.

Transcriptome Deconvolution Reveals Absence of Cancer Cell Expression Signature in Immune Checkpoint Blockade Response.

Immune checkpoint therapy (ICB) has conferred significant and durable clinical benefit to some patients with cancer. However, most patients do not respond to ICB, and reliable biomarkers of ICB response are needed to improve patient stratification. Here, we performed a transcriptome-wide meta-analysis across 1,486 tumors from ICB-treated patients and tumors with expected ICB outcomes based on microsatellite status. Using a robust transcriptome deconvolution approach, we inferred cancer- and stroma-specific gene expression differences and identified cell-type specific features of ICB response across cancer types. Consistent with current knowledge, stromal expression of CXCL9, CXCL13, and IFNG were the top determinants of favorable ICB response. In addition, we identified a group of potential immune-suppressive genes, including FCER1A, associated with poor response to ICB. Strikingly, PD-L1 expression in stromal cells, but not cancer cells, is correlated with ICB response across cancer types. Furthermore, the unbiased transcriptome-wide analysis failed to identify cancer-cell intrinsic expression signatures of ICB response conserved across tumor types, suggesting that cancer cells lack tissue-agnostic transcriptomic features of ICB response. SIGNIFICANCE: Our results challenge the prevailing dogma that cancer cells present tissue-agnostic molecular markers that modulate immune activity and ICB response, which has implications on the development of improved ICB diagnostics and treatments.

Capmatinib plus nivolumab in pretreated patients with EGFR wild-type advanced non-small cell lung cancer.

INTRODUCTION: Dysregulated MET is an established oncogenic driver in non-small cell lung cancer (NSCLC). MET signaling may also suppress anticancer immune responses. Concomitant MET inhibition with capmatinib (a MET inhibitor) synergistically enhanced the efficacy of immunotherapies in murine cancer models, regardless of tumor dependency to MET signaling. Here, we report results of a multicenter, open-label, phase 2 study of capmatinib plus nivolumab (a PD-1 inhibitor) in patients with EGFR wild-type advanced NSCLC, previously treated with platinum-based chemotherapy. METHODS: Patients were allocated into high-MET or low-MET groups according to MET expression determined by immunohistochemistry, MET gene copy number as assessed by fluorescence in-situ hybridization, and presence of MET exon 14 skipping mutation, then received capmatinib 400 mg, oral, twice daily in combination with nivolumab 3 mg/kg intravenously every 2 weeks. The primary endpoint was investigator-assessed 6-month progression-free survival (PFS) rate per RECIST v1.1. RESULTS: The primary endpoint was met in both the high-MET (N = 16) and low-MET (N = 30) groups. In the high-MET and low-MET groups, respectively, the estimated mean 6-month PFS rate (95 % credible interval) by Bayesian analysis was 68.9 % (48.5-85.7) and 50.9 % (35.6-66.4). The Kaplan-Meier median PFS (95 % CI) was 6.2 months (3.5-19.2) and 4.2 months (1.8-7.4). The overall response rate (95 % CI) was 25.0 % (7.3-52.4) and 16.7 % (5.6-34.7). Most frequent treatment-related adverse events (≥30 % any grade, N = 46) were nausea (52.2 %), peripheral edema (34.8 %), and increased blood creatinine (30.4 %). CONCLUSIONS: Capmatinib plus nivolumab showed clinical activity and manageable safety in pretreated patients with advanced EGFR wild-type NSCLC, independent of MET status. TRIAL REGISTRATION: ClinicalTrials.gov NCT02323126.

Use of Natural Language Processing to Infer Sites of Metastatic Disease From Radiology Reports at Scale.

PURPOSE: To evaluate natural language processing (NLP) methods to infer metastatic sites from radiology reports. METHODS: A set of 4,522 computed tomography (CT) reports of 550 patients with 14 types of cancer was used to fine-tune four clinical large language models (LLMs) for multilabel classification of metastatic sites. We also developed an NLP information extraction (IE) system (on the basis of named entity recognition, assertion status detection, and relation extraction) for comparison. Model performances were measured by F1 scores on test and three external validation sets. The best model was used to facilitate analysis of metastatic frequencies in a cohort study of 6,555 patients with 53,838 CT reports. RESULTS: The RadBERT, BioBERT, GatorTron-base, and GatorTron-medium LLMs achieved F1 scores of 0.84, 0.87, 0.89, and 0.91, respectively, on the test set. The IE system performed best, achieving an F1 score of 0.93. F1 scores of the IE system by individual cancer type ranged from 0.89 to 0.96. The IE system attained F1 scores of 0.89, 0.83, and 0.81, respectively, on external validation sets including additional cancer types, positron emission tomography-CT ,and magnetic resonance imaging scans, respectively. In our cohort study, we found that for colorectal cancer, liver-only metastases were higher in de novo stage IV versus recurrent patients (29.7% v 12.2%; P < .001). Conversely, lung-only metastases were more frequent in recurrent versus de novo stage IV patients (17.2% v 7.3%; P < .001). CONCLUSION: We developed an IE system that accurately infers metastatic sites in multiple primary cancers from radiology reports. It has explainable methods and performs better than some clinical LLMs. The inferred metastatic phenotypes could enhance cancer research databases and clinical trial matching, and identify potential patients for oligometastatic interventions.

Towards proactive palliative care in oncology: developing an explainable EHR-based machine learning model for mortality risk prediction.

BACKGROUND: Ex-ante identification of the last year in life facilitates a proactive palliative approach. Machine learning models trained on electronic health records (EHR) demonstrate promising performance in cancer prognostication. However, gaps in literature include incomplete reporting of model performance, inadequate alignment of model formulation with implementation use-case, and insufficient explainability hindering trust and adoption in clinical settings. Hence, we aim to develop an explainable machine learning EHR-based model that prompts palliative care processes by predicting for 365-day mortality risk among patients with advanced cancer within an outpatient setting. METHODS: Our cohort consisted of 5,926 adults diagnosed with Stage 3 or 4 solid organ cancer between July 1, 2017, and June 30, 2020 and receiving ambulatory cancer care within a tertiary center. The classification problem was modelled using Extreme Gradient Boosting (XGBoost) and aligned to our envisioned use-case: "Given a prediction point that corresponds to an outpatient cancer encounter, predict for mortality within 365-days from prediction point, using EHR data up to 365-days prior." The model was trained with 75% of the dataset (n = 39,416 outpatient encounters) and validated on a 25% hold-out dataset (n = 13,122 outpatient encounters). To explain model outputs, we used Shapley Additive Explanations (SHAP) values. Clinical characteristics, laboratory tests and treatment data were used to train the model. Performance was evaluated using area under the receiver operating characteristic curve (AUROC) and area under the precision-recall curve (AUPRC), while model calibration was assessed using the Brier score. RESULTS: In total, 17,149 of the 52,538 prediction points (32.6%) had a mortality event within the 365-day prediction window. The model demonstrated an AUROC of 0.861 (95% CI 0.856-0.867) and AUPRC of 0.771. The Brier score was 0.147, indicating slight overestimations of mortality risk. Explanatory diagrams utilizing SHAP values allowed visualization of feature impacts on predictions at both the global and individual levels. CONCLUSION: Our machine learning model demonstrated good discrimination and precision-recall in predicting 365-day mortality risk among individuals with advanced cancer. It has the potential to provide personalized mortality predictions and facilitate earlier integration of palliative care.

Oncogene-Driven Non-Small Cell Lung Cancers in Patients with a History of Smoking Lack Smoking-Induced Mutations.

Non-small cell lung cancers (NSCLC) in nonsmokers are mostly driven by mutations in the oncogenes EGFR, ERBB2, and MET and fusions involving ALK and RET. In addition to occurring in nonsmokers, alterations in these "nonsmoking-related oncogenes" (NSRO) also occur in smokers. To better understand the clonal architecture and genomic landscape of NSRO-driven tumors in smokers compared with typical-smoking NSCLCs, we investigated genomic and transcriptomic alterations in 173 tumor sectors from 48 NSCLC patients. NSRO-driven NSCLCs in smokers and nonsmokers had similar genomic landscapes. Surprisingly, even in patients with prominent smoking histories, the mutational signature caused by tobacco smoking was essentially absent in NSRO-driven NSCLCs, which was confirmed in two large NSCLC data sets from other geographic regions. However, NSRO-driven NSCLCs in smokers had higher transcriptomic activities related to the regulation of the cell cycle. These findings suggest that, whereas the genomic landscape is similar between NSRO-driven NSCLC in smokers and nonsmokers, smoking still affects the tumor phenotype independently of genomic alterations. SIGNIFICANCE: Non-small cell lung cancers driven by nonsmoking-related oncogenes do not harbor genomic scars caused by smoking regardless of smoking history, indicating that the impact of smoking on these tumors is mainly nongenomic.

Spontaneous pneumomediastinum and pneumopericardium in a young male with asthma.

INTRODUCTION: Spontaneous pneumomediastinum with pneumopericardium is an uncommon clinical entity. CASE STUDY: Here, we report the case of a 23-year-old male with asthma who presented with acute chest pain and shortness of breath after an episode of coughing and sneezing. CT scans of the chest and neck revealed pneumomediastinum and pneumopericardium with extensive subcutaneous emphysema extending into the axilla and neck. RESULTS: The patient was admitted for observation and analgesia. No other interventions were administered. Interval scans performed on day five of the admission demonstrated an interval reduction in the degree of air within the mediastinum, pericardium and subcutaneous tissues, and the patient was subsequently discharged home. CONCLUSION: This case outlines the presentation, diagnosis, and management of concurrent spontaneous pneumomediastinum and pneumopericardium.

Precision Endpoints for Contemporary Precision Oncology Trials.

SUMMARY: Traditional endpoints such as progression-free survival and overall survival do not fully capture the pharmacologic and pharmacodynamic effects of a therapeutic intervention. Incorporating mechanism-driven biomarkers and validated surrogate proximal endpoints can provide orthogonal readouts of anti-tumor activity and delineate the relative contribution of treatment components on an individual level, highlighting the limitation of solely relying on aggregated readouts from clinical trials to facilitate go/no-go decisions for precision therapies.

Chain-Like Semiconductive Fillers for Dielectric Enhancement and Loss Reduction of Polymer Composites.

Dielectric loss is a crucial factor in determining the long-term endurance for security and energy loss of dielectric composites. Here, chain-like semiconductive fibers of titanium oxide, indium, and niobium-doped titanium oxide are used for enhancing the complex dielectric properties of a polymer through composite construction, which involves significant interface enhancements. The chain-like fibers significantly enhance the dielectric constant owing to the special morphology of the fillers and their interfacial polarization, especially at higher temperatures. The dielectric loss and electrical conductivity of the composites are substantially reduced across the entire investigated temperature range, achieved by passivating the fiber surface with an alumina shell using atomic layer deposition. The as-deposited alumina shell transformed from an amorphous to a crystalline phase through thermal annealing results in a porous shell and more effective suppression of the loss tangent and electrical conductivity. A plausible mechanism for loss suppression is associated with carrier movement along the surface of the fibers and bulk, leading to a higher loss tangent. The alumina shell blocks the carrier transport path, particularly at the interfaces, resulting in a reduced interfacial polarization contribution and energy storage loss. This study provides a method for inhibiting dielectric loss by fabricating fillers with special surfaces.

A comprehensive review on Gossypium hirsutum resistance against cotton leaf curl virus.

Cotton (Gossypium hirsutum L.) is a significant fiber crop. Being a major contributor to the textile industry requires continuous care and attention. Cotton is subjected to various biotic and abiotic constraints. Among these, biotic factors including cotton leaf curl virus (CLCuV) are dominant. CLCuV is a notorious disease of cotton and is acquired, carried, and transmitted by the whitefly (Bemisia tabaci). A cotton plant affected with CLCuV may show a wide range of symptoms such as yellowing of leaves, thickening of veins, upward or downward curling, formation of enations, and stunted growth. Though there are many efforts to protect the crop from CLCuV, long-term results are not yet obtained as CLCuV strains are capable of mutating and overcoming plant resistance. However, systemic-induced resistance using a gene-based approach remained effective until new virulent strains of CLCuV (like Cotton Leaf Curl Burewala Virus and others) came into existence. Disease control by biological means and the development of CLCuV-resistant cotton varieties are in progress. In this review, we first discussed in detail the evolution of cotton and CLCuV strains, the transmission mechanism of CLCuV, the genetic architecture of CLCuV vectors, and the use of pathogen and nonpathogen-based approaches to control CLCuD. Next, we delineate the uses of cutting-edge technologies like genome editing (with a special focus on CRISPR-Cas), next-generation technologies, and their application in cotton genomics and speed breeding to develop CLCuD resistant cotton germplasm in a short time. Finally, we delve into the current obstacles related to cotton genome editing and explore forthcoming pathways for enhancing precision in genome editing through the utilization of advanced genome editing technologies. These endeavors aim to enhance cotton's resilience against CLCuD.

Investigating the Association Between Dynamic Driving Pressure and Mortality in COVID-19-Related Acute Respiratory Distress Syndrome: A Joint Modeling Approach Using Real-Time Continuously-Monitored Ventilation Data.

IMPORTANCE AND OBJECTIVES: COVID-19-related acute respiratory distress syndrome (ARDS) is associated with high mortality and often necessitates invasive mechanical ventilation (IMV). Previous studies on non-COVID-19 ARDS have shown driving pressure to be robustly associated with ICU mortality; however, those studies relied on "static" driving pressure measured periodically and manually. As "continuous" automatically monitored driving pressure is becoming increasingly available and reliable with more advanced mechanical ventilators, we aimed to examine the effect of this "dynamic" driving pressure in COVID-19 ARDS throughout the entire ventilation period. DESIGN SETTING AND PARTICIPANTS: This retrospective, observational study cohort study evaluates the association between driving pressure and ICU mortality in patients with concurrent COVID-19 and ARDS using multivariate joint modeling. The study cohort (n = 544) included all adult patients (≥ 18 yr) with COVID-19 ARDS between March 1, 2020, and April 30, 2021, on volume-control mode IMV for 12 hours or more in a Mass General Brigham, Boston, MA ICU. MEASUREMENTS AND MAIN RESULTS: Of 544 included patients, 171 (31.4%) died in the ICU. Increased dynamic ΔP was associated with increased risk in the hazard of ICU mortality (hazard ratio [HR] 1.035; 95% credible interval, 1.004-1.069) after adjusting for other relevant dynamic respiratory biomarkers. A significant increase in risk in the hazard of death was found for every hour of exposure to high intensities of driving pressure (≥ 15 cm H2O) (HR 1.002; 95% credible interval 1.001-1.003). CONCLUSIONS: Limiting patients' exposure to high intensities of driving pressure even while under lung-protective ventilation may represent a critical step in improving ICU survival in patients with COVID-19 ARDS. Time-series IMV data could be leveraged to enhance real-time monitoring and decision support to optimize ventilation strategies at the bedside.

A Phase I Study of Acapatamab, a Half-life Extended, PSMA-Targeting Bispecific T-cell Engager for Metastatic Castration-Resistant Prostate Cancer.

PURPOSE: Safety and efficacy of acapatamab, a prostate-specific membrane antigen (PSMA) x CD3 bispecific T-cell engager were evaluated in a first-in-human study in metastatic castration-resistant prostate cancer (mCRPC). PATIENTS AND METHODS: Patients with mCRPC refractory to androgen receptor pathway inhibitor therapy and taxane-based chemotherapy received target acapatamab doses ranging from 0.003 to 0.9 mg in dose exploration (seven dose levels) and 0.3 mg (recommended phase II dose) in dose expansion intravenously every 2 weeks. Safety (primary objective), pharmacokinetics, and antitumor activity (secondary objectives) were assessed. RESULTS: In all, 133 patients (dose exploration, n = 77; dose expansion, n = 56) received acapatamab. Cytokine release syndrome (CRS) was the most common treatment-emergent adverse event seen in 97.4% and 98.2% of patients in dose exploration and dose expansion, respectively; grade ≥ 3 was seen in 23.4% and 16.1%, respectively. Most CRS events were seen in treatment cycle 1; incidence and severity decreased at/beyond cycle 2. In dose expansion, confirmed prostate-specific antigen (PSA) responses (PSA50) were seen in 30.4% of patients and radiographic partial responses in 7.4% (Response Evaluation Criteria in Solid Tumors 1.1). Median PSA progression-free survival (PFS) was 3.3 months [95% confidence interval (CI): 3.0-4.9], radiographic PFS per Prostate Cancer Clinical Trials Working Group 3 was 3.7 months (95% CI: 2.0-5.4). Acapatamab induced T-cell activation and increased cytokine production several-fold within 24 hours of initiation. Treatment-emergent antidrug antibodies were detected in 55% and impacted serum exposures in 36% of patients in dose expansion. CONCLUSIONS: Acapatamab was safe and tolerated and had a manageable CRS profile. Preliminary signs of efficacy with limited durable antitumor activity were observed. Acapatamab demonstrated pharmacokinetic and pharmacodynamic activity.

Detection of circulating tumor DNA with ultradeep sequencing of plasma cell-free DNA for monitoring minimal residual disease and early detection of recurrence in early-stage lung cancer.

BACKGROUND: In early-stage non-small cell lung cancer (NSCLC), recurrence is frequently observed. Circulating tumor DNA (ctDNA) has emerged as a noninvasive tool to risk stratify patients for recurrence after curative intent therapy. This study aimed to risk stratify patients with early-stage NSCLC via a personalized, tumor-informed multiplex polymerase chain reaction (mPCR) next-generation sequencing assay. METHODS: This retrospective cohort study included patients with stage I-III NSCLC. Recruited patients received standard-of-care management (surgical resection with or without adjuvant chemotherapy, followed by surveillance). Whole-exome sequencing of NSCLC resected tissue and matched germline DNA was used to design patient-specific mPCR assays (Signatera, Natera, Inc) to track up to 16 single-nucleotide variants in plasma samples. RESULTS: The overall cohort with analyzed plasma samples consisted of 57 patients. Stage distribution was 68% for stage I and 16% each for stages II and III. Presurgery (i.e., at baseline), ctDNA was detected in 15 of 57 patients (26%). ctDNA detection presurgery was significantly associated with shorter recurrence-free survival (RFS; hazard ratio [HR], 3.54; 95% confidence interval [CI], 1.00-12.62; p = .009). In the postsurgery setting, ctDNA was detected in seven patients, of whom 100% experienced radiological recurrence. ctDNA positivity preceded radiological findings by a median lead time of 2.8 months (range, 0-12.9 months). Longitudinally, ctDNA detection at any time point was associated with shorter RFS (HR, 16.1; 95% CI, 1.63-158.9; p < .0001). CONCLUSIONS: ctDNA detection before surgical resection was strongly associated with a high risk of relapse in early-stage NSCLC in a large unique Asian cohort. Prospective studies are needed to assess the clinical utility of ctDNA status in this setting.

Can We Use Lung Function Thresholds and Respiratory Symptoms to Identify Pre-Chronic Obstructive Pulmonary Disease? A Prospective, Population-based Cohort Study.

Rationale: The term "pre-chronic obstructive pulmonary disease" ("pre-COPD") refers to individuals at high risk of developing COPD who do not meet conventional spirometric criteria for airflow obstruction. New approaches to identifying these individuals are needed, particularly in younger populations. Objectives: To determine whether lung function thresholds and respiratory symptoms can be used to identify individuals at risk of developing COPD. Methods: The Tasmanian Longitudinal Health Study comprises a population-based cohort first studied in 1968 (at age 7 yr). Respiratory symptoms, pre- and post-bronchodilator (BD) spirometry, diffusing capacity, and static lung volumes were measured in a subgroup at age 45, and the incidence of COPD was assessed at age 53. For each lung function measure, z-scores were calculated using Global Lung Function Initiative references. The optimal threshold for best discrimination of COPD incidence was determined by the unweighted Youden index. Measurements and Main Results: Among 801 participants who did not have COPD at age 45, the optimal threshold for COPD incidence by age 53 was pre-BD FEV1/FVC z-score less than -1.264, corresponding to the lowest 10th percentile. Those below this threshold had a 36-fold increased risk of developing COPD over an 8-year follow-up period (risk ratio, 35.8; 95% confidence interval, 8.88 to 144), corresponding to a risk difference of 16.4% (95% confidence interval, 3.7 to 67.4). The sensitivity was 88%, and the specificity was 87%. Positive and negative likelihood ratios were 6.79 and 0.14, respectively. Respiratory symptoms, post-BD spirometry, diffusing capacity, and static lung volumes did not improve on the classification achieved by pre-BD FEV1/FVC alone. Conclusions: This is the first study, to our knowledge, to evaluate the discriminatory accuracy of spirometry, diffusing capacity, and static lung volume thresholds for COPD incidence in middle-aged adults. Our findings support the inclusion of pre-BD spirometry in the physiological definition of pre-COPD and indicate that pre-BD FEV1/FVC at the 10th percentile accurately identifies individuals at high risk of developing COPD in community-based settings.

ENABLE-SG (Educate, Nurture, Advise, Before Life Ends for Singapore) as a proactive palliative care model: protocol for a hybrid type 1 effectiveness-implementation randomized wait-list controlled trial.

BACKGROUND: Specialist palliative care is often provided late in the patient's disease trajectory in response to uncontrolled symptoms. Shifting from this reactionary illness-stress paradigm to a proactive health-wellness approach, the ENABLE (Educate, Nurture, Advise, Before Life Ends) telehealth model aims to enhance the coping, stress and symptom management, self-care, and advance care planning skills of patients with advanced cancers and their caregivers. The ENABLE model has been culturally adapted to Singapore (ENABLE-SG) and pilot-tested. A hybrid type 1 effectiveness-implementation design will be used to evaluate the effectiveness of ENABLE-SG while collecting real-world implementation data. METHODS: This single-centre, assessor-blind, wait-list (immediately vs. 6 months) randomized controlled trial will recruit 300 adult patients within 60 days of an advanced cancer diagnosis and their family caregivers from the National Cancer Centre of Singapore. ENABLE-SG comprises structured psychoeducational sessions with a telehealth coach, covering essential topics of early palliative care. Participants will be assessed at baseline and every 3 months until patient's death, 12 months (caregivers), or end of study (patients). The primary outcome is patient quality of life 6 months after baseline. Secondary patient-reported outcomes include mood, coping, palliative care concerns, and health status. Secondary caregiver-reported outcomes include caregiver quality of life, mood, coping, and care satisfaction. Mixed-effects regression modelling for repeated measurements will be used. To assess the effectiveness of ENABLE-SG versus usual care, patient and caregiver outcomes at 6 months will be compared. To compare earlier versus delayed ENABLE-SG, patient and caregiver outcomes at 12 months will be compared. Within the hybrid type 1 effectiveness-implementation design, implementation outcomes will be evaluated in both the early and delayed groups. Acceptability, adoption, appropriateness, and feasibility will be assessed using a feedback survey and semi-structured interviews with a purposive sample of patients, caregivers, and healthcare providers. Transcribed interviews will be analysed thematically. Other implementation outcomes of penetration, fidelity, and cost will be assessed using records of study-related processes and summarized using descriptive statistics. A cost-effectiveness analysis will also be conducted. DISCUSSION: This study will assess both effectiveness and implementation of ENABLE-SG. Insights into implementation processes can facilitate model expansion and upscaling. TRIAL REGISTRATION: Registered prospectively on ClinicalTrials.gov, NCT06044441. Registered on 21/09/2023.

Bioengineered hydrogels enhance ex vivo preservation of patient-derived tumor explants for drug evaluation.

Ex vivo patient-derived tumor slices (PDTS) are currently limited by short-term viability in culture. Here, we show how bioengineered hydrogels enable the identification of key matrix parameters that significantly enhance PDTS viability compared to conventional culture systems. As demonstrated using single-cell RNA sequencing and high-dimensional flow cytometry, hydrogel-embedded PDTS tightly preserved cancer, cancer-associated fibroblast, and various immune cell populations and subpopulations in the corresponding original tumor. Cell-cell communication networks within the tumor microenvironment, including immune checkpoint ligand-receptor interactions, were also maintained. Remarkably, our results from a co-clinical trial suggest hydrogel-embedded PDTS may predict sensitivity to immune checkpoint inhibitors (ICIs) in head and neck cancer patients. Further, we show how these longer term-cultured tumor explants uniquely enable the sampling and detection of temporal evolution in molecular readouts when treated with ICIs. By preserving the compositional heterogeneity and complexity of patient tumors, hydrogel-embedded PDTS provide a valuable tool to facilitate experiments targeting the tumor microenvironment.