Radioresistant Pulmonary Oligometastatic and Oligoprogressive Lesions From Nonlung Primaries: Impact of Histology and Dose-Fractionation on Local Control After Radiation Therapy.

Purpose: We investigated whether pulmonary metastases from historically considered radioresistant primaries would have inferior local control after radiation therapy than those from nonradioresistant nonlung primaries, and whether higher biologically effective dose assuming alpha/beta=10 (BED10) would be associated with superior local control. Methods and Materials: We identified patients treated with radiation therapy for oligometastatic or oligoprogressive pulmonary disease to 1 to 5 lung metastases from nonlung primaries in 2013 to 2020 at a single health care system. Radioresistant primary cancers included colorectal carcinoma, endometrial carcinoma, renal cell carcinoma, melanoma, and sarcoma. Nonradioresistant primary cancers included breast, bladder, esophageal, pancreas, and head and neck carcinomas. The Kaplan-Meier estimator, log-rank test, and multivariable Cox proportional hazards regression were used to compare local recurrence-free survival (LRFS), new metastasis-free survival, progression-free survival, and overall survival. Results: Among 114 patients, 73 had radioresistant primary cancers. The median total dose was 50 Gy (IQR, 50-54 Gy) and the median number of fractions was 5 (IQR, 3-5). Median follow-up time was 59.6 months. One of 41 (2.4%) patients with a nonradioresistant metastasis experienced local failure compared with 18 of 73 (24.7%) patients with radioresistant metastasis (log-rank P = .004). Among radioresistant metastases, 12 of 41 (29.2%) patients with colorectal carcinoma experienced local failure compared with 6 of 32 (18.8%) with other primaries (log-rank P = .018). BED10 ≥100 Gy was associated with decreased risk of local recurrence. On univariable analysis, BED10 ≥100 Gy (hazard ratio [HR], 0.263; 95% CI, 0.105-0.656; P = .004) was associated with higher LRFS, and colorectal primary (HR, 3.060; 95% CI, 1.204-7.777; P = .019) was associated with lower LRFS, though these were not statistically significant on multivariable analysis. Among colorectal primary patients, BED10 ≥100 Gy was associated with higher LRFS (HR, 0.266; 95% CI, 0.072-0.985; P = .047) on multivariable analysis. Conclusions: Local control after radiation therapy was encouraging for pulmonary metastases from most nonlung primaries, even for many of those classically considered to be radioresistant. Those from colorectal primaries may benefit from testing additional strategies, such as resection or systemic treatment concurrent with radiation.

Recombinant human DNase-I improves acute respiratory distress syndrome via neutrophil extracellular trap degradation.

BACKGROUND: Respiratory failure is the primary cause of death in patients with COVID-19, whereas coagulopathy is associated with excessive inflammation and multiorgan failure. Neutrophil extracellular traps (NETs) may exacerbate inflammation and provide a scaffold for thrombus formation. OBJECTIVES: The goal of this study was to determine whether degradation of NETs by recombinant human DNase-I (rhDNase), a safe, Food and Drug Administration-approved drug, reduces excessive inflammation, reverses aberrant coagulation, and improves pulmonary perfusion after experimental acute respiratory distress syndrome (ARDS). METHODS: Intranasal poly(I:C), a synthetic double-stranded RNA, was administered to adult mice for 3 consecutive days to simulate a viral infection, and these subjects were randomized to treatment arms, which received either an intravenous placebo or rhDNase. The effects of rhDNase on immune activation, platelet aggregation, and coagulation were assessed in mice and donor human blood. RESULTS: NETs were observed in bronchoalveolar lavage fluid and within regions of hypoxic lung tissue after experimental ARDS. The administration of rhDNase mitigated peribronchiolar, perivascular, and interstitial inflammation induced by poly(I:C). In parallel, rhDNase degraded NETs, attenuated platelet-NET aggregates, reduced platelet activation, and normalized the clotting time to improve regional perfusion, as observed using gross morphology, histology, and microcomputed tomographic imaging in mice. Similarly, rhDNase reduced NETs and attenuated platelet activation in human blood. CONCLUSION: NETs exacerbate inflammation and promote aberrant coagulation by providing a scaffold for aggregated platelets after experimental ARDS. Intravenous administration of rhDNase degrades NETs and attenuates coagulopathy in ARDS, providing a promising translational approach to improve pulmonary structure and function after ARDS.

Bladder Cancer Radiation Oncology of the Future: Prognostic Modelling, Radiomics, and Treatment Planning With Artificial Intelligence.

Machine learning (ML) and artificial intelligence (AI) have demonstrated potential to improve the care of radiation oncology patients. Here we review recent advances applicable to the care of bladder cancer, with an eye towards studies that may suggest next steps in clinical implementation. Algorithms have been applied to clinical records, pathology, and radiology data to generate accurate predictive models for prognosis and clinical outcomes. AI has also shown increasing utility for auto-contouring and efficient creation of workflows involving multiple treatment plans. As technologies progress towards routine clinical use for bladder cancer patients, we also discuss emerging methods to improve interpretability and reliability of algorithms.

Rapid expansion and extinction of antibiotic resistance mutations during treatment of acute bacterial respiratory infections.

Acute bacterial infections are often treated empirically, with the choice of antibiotic therapy updated during treatment. The effects of such rapid antibiotic switching on the evolution of antibiotic resistance in individual patients are poorly understood. Here we find that low-frequency antibiotic resistance mutations emerge, contract, and even go to extinction within days of changes in therapy. We analyzed Pseudomonas aeruginosa populations in sputum samples collected serially from 7 mechanically ventilated patients at the onset of respiratory infection. Combining short- and long-read sequencing and resistance phenotyping of 420 isolates revealed that while new infections are near-clonal, reflecting a recent colonization bottleneck, resistance mutations could emerge at low frequencies within days of therapy. We then measured the in vivo frequencies of select resistance mutations in intact sputum samples with resistance-targeted deep amplicon sequencing (RETRA-Seq), which revealed that rare resistance mutations not detected by clinically used culture-based methods can increase by nearly 40-fold over 5-12 days in response to antibiotic changes. Conversely, mutations conferring resistance to antibiotics not administered diminish and even go to extinction. Our results underscore how therapy choice shapes the dynamics of low-frequency resistance mutations at short time scales, and the findings provide a possibility for driving resistance mutations to extinction during early stages of infection by designing patient-specific antibiotic cycling strategies informed by deep genomic surveillance.

Critical Effects on Akt Signaling in Adult Zebrafish Brain Following Alterations in Light Exposure.

Evidence from human and animal studies indicate that disrupted light cycles leads to alterations of the sleep state, poor cognition, and the risk of developing neuroinflammatory and generalized health disorders. Zebrafish exhibit a diurnal circadian rhythm and are an increasingly popular model in studies of neurophysiology and neuropathophysiology. Here, we investigate the effect of alterations in light cycle on the adult zebrafish brain: we measured the effect of altered, unpredictable light exposure in adult zebrafish telencephalon, homologous to mammalian hippocampus, and the optic tectum, a significant visual processing center with extensive telencephalon connections. The expression of heat shock protein-70 (HSP70), an important cell stress mediator, was significantly decreased in optic tectum of adult zebrafish brain following four days of altered light exposure. Further, pSer473-Akt (protein kinase B) was significantly reduced in telencephalon following light cycle alteration, and pSer9-GSK3ß (glycogen synthase kinase-3ß) was significantly reduced in both the telencephalon and optic tectum of light-altered fish. Animals exposed to five minutes of environmental enrichment showed significant increase in pSer473Akt, which was significantly attenuated by four days of altered light exposure. These data show for the first time that unpredictable light exposure alters HSP70 expression and dysregulates Akt-GSK3ß signaling in the adult zebrafish brain.

Integrating molecular profiles into clinical frameworks through the Molecular Oncology Almanac to prospectively guide precision oncology.

Tumor molecular profiling of single gene-variant ('first-order') genomic alterations informs potential therapeutic approaches. Interactions between such first-order events and global molecular features (for example, mutational signatures) are increasingly associated with clinical outcomes, but these 'second-order' alterations are not yet accounted for in clinical interpretation algorithms and knowledge bases. We introduce the Molecular Oncology Almanac (MOAlmanac), a paired clinical interpretation algorithm and knowledge base to enable integrative interpretation of multimodal genomic data for point-of-care decision making and translational-hypothesis generation. We benchmarked MOAlmanac to a first-order interpretation method across multiple retrospective cohorts and observed an increased number of clinical hypotheses from evaluation of molecular features and profile-to-cell line matchmaking. When applied to a prospective precision oncology trial cohort, MOAlmanac nominated a median of two therapies per patient and identified therapeutic strategies administered in 47% of patients. Overall, we present an open-source computational method for integrative clinical interpretation of individualized molecular profiles.