Human airway macrophages are metabolically reprogrammed by IFN-γ resulting in glycolysis-dependent functional plasticity.
Airway macrophages (AM) are the predominant immune cell in the lung and play a crucial role in preventing infection, making them a target for host directed therapy. Macrophage effector functions are associated with cellular metabolism. A knowledge gap remains in understanding metabolic reprogramming and functional plasticity of distinct human macrophage subpopulations, especially in lung resident AM. We examined tissue-resident AM and monocyte-derived macrophages (MDM; as a model of blood derived macrophages) in their resting state and after priming with IFN-γ or IL-4 to model the Th1/Th2 axis in the lung. Human macrophages, regardless of origin, had a strong induction of glycolysis in response to IFN-γ or upon stimulation. IFN-γ significantly enhanced cellular energetics in both AM and MDM by upregulating both glycolysis and oxidative phosphorylation. Upon stimulation, AM do not decrease oxidative phosphorylation unlike MDM which shift to 'Warburg'-like metabolism. IFN-γ priming promoted cytokine secretion in AM. Blocking glycolysis with 2-deoxyglucose significantly reduced IFN-γ driven cytokine production in AM, indicating that IFN-γ induces functional plasticity in human AM, which is mechanistically mediated by glycolysis. Directly comparing responses between macrophages, AM were more responsive to IFN-γ priming and dependent on glycolysis for cytokine secretion than MDM. Interestingly, TNF production was under the control of glycolysis in AM and not in MDM. MDM exhibited glycolysis-dependent upregulation of HLA-DR and CD40, whereas IFN-γ upregulated HLA-DR and CD40 on AM independently of glycolysis. These data indicate that human AM are functionally plastic and respond to IFN-γ in a manner distinct from MDM. These data provide evidence that human AM are a tractable target for inhalable immunomodulatory therapies for respiratory diseases.
Cox DJ
，Connolly SA
，Ó Maoldomhnaigh C
，Brugman AAI
，Sandby Thomas O
，Duffin E
，Gogan KM
，Ó Gallchobhair O
，Murphy DM
，O'Rourke SA
，O'Connell F
，Nadarajan P
，Phelan JJ
，Gleeson LE
，Basdeo SA
，Keane J
... -
《eLife》
Luteolin alleviates airway remodeling in asthma by inhibiting the epithelial-mesenchymal transition via β-catenin regulation.
Asthma is a prevalent long-term inflammatory condition that causes airway inflammation and remodeling. Increasing evidence indicates that epithelial-mesenchymal transition (EMT) holds a prominent implication in airway reconstruction in patients with asthma. Flavonoids obtained from Chinese Materia Medica (CMM), such as Luteolin (Lut), exhibit various beneficial effects in various asthma models. Lut has been shown to mitigate various asthma symptoms, including airway inflammation, hyperresponsiveness, bronchoconstriction, excessive mucus production, pulmonary autophagy, and neutrophilic asthma. However, whether flavonoids can suppress EMT-associated airway remodeling in asthma and the fundamental mechanisms involved remain unclear, with no studies specifically addressing Lut in this context.
To evaluate the inhibition of airway remodeling in asthma by Lut and its potential mechanisms, while examining the significance of β-catenin in this process through cellular and animal studies.
A BEAS-2B cell model stimulated by lipopolysaccharide (LPS) was established in vitro. Wound closure and Transwell assays were utilized to assess the cellular migratory ability. EMT- and fibrosis-related markers in LPS-stimulated cells were evaluated using RT-qPCR and western blotting. The status of the β-catenin/E-cadherin and β-catenin destruction complexes was evaluated using western blotting, immunofluorescence (IF) staining, and co-immunoprecipitation (Co-IP) analysis. The regulatory function of Lut in β-catenin-dependent EMT was further validated by β-catenin overexpression with adenovirus transduction and siRNA-mediated knockdown of β-catenin. Moreover, the counts of different types of bronchoalveolar lavage fluid (BALF) inflammatory cells from mice with asthma induced by ovalbumin (OVA) were evaluated in vivo using Congo red staining. Hematoxylin and eosin (H&E), Masson's trichrome, and periodic acid-Schiff (PAS) staining were used to evaluate collagen deposition, mucus production, and inflammation in murine lung tissues. Western blotting and immunohistochemistry (IHC) assays were used to assess EMT- and fibrosis-related markers in the lung tissues in vivo.
Six naturally derived flavonoids, including Lut, attenuated cell migration and prevented EMT in LPS-treated BEAS-2B cells. Moreover, Lut suppressed TGF-β1, MMP-9, fibronectin (FN), and α-smooth muscle actin (α-SMA) levels in LPS-stimulated BEAS-2B cells. Additionally, Lut downregulated the levels of β-catenin by modulating the β-catenin/E-cadherin and β-catenin destruction complexes, highlighting the pivotal role of β-catenin in EMT inhibition by Lut in LPS-stimulated BEAS-2B cells. Furthermore, Lut suppressed airway inflammation and attenuated EMT-associated airway remodeling through β-catenin blockade in OVA-induced asthmatic mice. The bronchial wall thickness notably reduced from 37.24 ± 4.00 μm in the asthmatic model group to 30.06 ± 4.40 μm in the Lut low-dose group and 24.69 ± 2.87 μm in the Lut high-dose group.
According to our current understanding, this research is the first to reveal that Lut diminishes airway remodeling in asthma by inhibiting EMT via β-catenin regulation, thereby filling a research gap concerning Lut and flavonoids. These results provide a theoretical basis for treating asthma with anti-asthmatic CMM, as well as a candidate and complementary therapeutic approach to treat asthma.
Quan J
，Xie D
，Li Z
，Yu X
，Liang Z
，Chen Y
，Wu L
，Huang D
，Lin L
，Fan L
... -
《-》
Comparison of Two Modern Survival Prediction Tools, SORG-MLA and METSSS, in Patients With Symptomatic Long-bone Metastases Who Underwent Local Treatment With Surgery Followed by Radiotherapy and With Radiotherapy Alone.
Survival estimation for patients with symptomatic skeletal metastases ideally should be made before a type of local treatment has already been determined. Currently available survival prediction tools, however, were generated using data from patients treated either operatively or with local radiation alone, raising concerns about whether they would generalize well to all patients presenting for assessment. The Skeletal Oncology Research Group machine-learning algorithm (SORG-MLA), trained with institution-based data of surgically treated patients, and the Metastases location, Elderly, Tumor primary, Sex, Sickness/comorbidity, and Site of radiotherapy model (METSSS), trained with registry-based data of patients treated with radiotherapy alone, are two of the most recently developed survival prediction models, but they have not been tested on patients whose local treatment strategy is not yet decided.
(1) Which of these two survival prediction models performed better in a mixed cohort made up both of patients who received local treatment with surgery followed by radiotherapy and who had radiation alone for symptomatic bone metastases? (2) Which model performed better among patients whose local treatment consisted of only palliative radiotherapy? (3) Are laboratory values used by SORG-MLA, which are not included in METSSS, independently associated with survival after controlling for predictions made by METSSS?
Between 2010 and 2018, we provided local treatment for 2113 adult patients with skeletal metastases in the extremities at an urban tertiary referral academic medical center using one of two strategies: (1) surgery followed by postoperative radiotherapy or (2) palliative radiotherapy alone. Every patient's survivorship status was ascertained either by their medical records or the national death registry from the Taiwanese National Health Insurance Administration. After applying a priori designated exclusion criteria, 91% (1920) were analyzed here. Among them, 48% (920) of the patients were female, and the median (IQR) age was 62 years (53 to 70 years). Lung was the most common primary tumor site (41% [782]), and 59% (1128) of patients had other skeletal metastases in addition to the treated lesion(s). In general, the indications for surgery were the presence of a complete pathologic fracture or an impending pathologic fracture, defined as having a Mirels score of ≥ 9, in patients with an American Society of Anesthesiologists (ASA) classification of less than or equal to IV and who were considered fit for surgery. The indications for radiotherapy were relief of pain, local tumor control, prevention of skeletal-related events, and any combination of the above. In all, 84% (1610) of the patients received palliative radiotherapy alone as local treatment for the target lesion(s), and 16% (310) underwent surgery followed by postoperative radiotherapy. Neither METSSS nor SORG-MLA was used at the point of care to aid clinical decision-making during the treatment period. Survival was retrospectively estimated by these two models to test their potential for providing survival probabilities. We first compared SORG to METSSS in the entire population. Then, we repeated the comparison in patients who received local treatment with palliative radiation alone. We assessed model performance by area under the receiver operating characteristic curve (AUROC), calibration analysis, Brier score, and decision curve analysis (DCA). The AUROC measures discrimination, which is the ability to distinguish patients with the event of interest (such as death at a particular time point) from those without. AUROC typically ranges from 0.5 to 1.0, with 0.5 indicating random guessing and 1.0 a perfect prediction, and in general, an AUROC of ≥ 0.7 indicates adequate discrimination for clinical use. Calibration refers to the agreement between the predicted outcomes (in this case, survival probabilities) and the actual outcomes, with a perfect calibration curve having an intercept of 0 and a slope of 1. A positive intercept indicates that the actual survival is generally underestimated by the prediction model, and a negative intercept suggests the opposite (overestimation). When comparing models, an intercept closer to 0 typically indicates better calibration. Calibration can also be summarized as log(O:E), the logarithm scale of the ratio of observed (O) to expected (E) survivors. A log(O:E) > 0 signals an underestimation (the observed survival is greater than the predicted survival); and a log(O:E) < 0 indicates the opposite (the observed survival is lower than the predicted survival). A model with a log(O:E) closer to 0 is generally considered better calibrated. The Brier score is the mean squared difference between the model predictions and the observed outcomes, and it ranges from 0 (best prediction) to 1 (worst prediction). The Brier score captures both discrimination and calibration, and it is considered a measure of overall model performance. In Brier score analysis, the "null model" assigns a predicted probability equal to the prevalence of the outcome and represents a model that adds no new information. A prediction model should achieve a Brier score at least lower than the null-model Brier score to be considered as useful. The DCA was developed as a method to determine whether using a model to inform treatment decisions would do more good than harm. It plots the net benefit of making decisions based on the model's predictions across all possible risk thresholds (or cost-to-benefit ratios) in relation to the two default strategies of treating all or no patients. The care provider can decide on an acceptable risk threshold for the proposed treatment in an individual and assess the corresponding net benefit to determine whether consulting with the model is superior to adopting the default strategies. Finally, we examined whether laboratory data, which were not included in the METSSS model, would have been independently associated with survival after controlling for the METSSS model's predictions by using the multivariable logistic and Cox proportional hazards regression analyses.
Between the two models, only SORG-MLA achieved adequate discrimination (an AUROC of > 0.7) in the entire cohort (of patients treated operatively or with radiation alone) and in the subgroup of patients treated with palliative radiotherapy alone. SORG-MLA outperformed METSSS by a wide margin on discrimination, calibration, and Brier score analyses in not only the entire cohort but also the subgroup of patients whose local treatment consisted of radiotherapy alone. In both the entire cohort and the subgroup, DCA demonstrated that SORG-MLA provided more net benefit compared with the two default strategies (of treating all or no patients) and compared with METSSS when risk thresholds ranged from 0.2 to 0.9 at both 90 days and 1 year, indicating that using SORG-MLA as a decision-making aid was beneficial when a patient's individualized risk threshold for opting for treatment was 0.2 to 0.9. Higher albumin, lower alkaline phosphatase, lower calcium, higher hemoglobin, lower international normalized ratio, higher lymphocytes, lower neutrophils, lower neutrophil-to-lymphocyte ratio, lower platelet-to-lymphocyte ratio, higher sodium, and lower white blood cells were independently associated with better 1-year and overall survival after adjusting for the predictions made by METSSS.
Based on these discoveries, clinicians might choose to consult SORG-MLA instead of METSSS for survival estimation in patients with long-bone metastases presenting for evaluation of local treatment. Basing a treatment decision on the predictions of SORG-MLA could be beneficial when a patient's individualized risk threshold for opting to undergo a particular treatment strategy ranged from 0.2 to 0.9. Future studies might investigate relevant laboratory items when constructing or refining a survival estimation model because these data demonstrated prognostic value independent of the predictions of the METSSS model, and future studies might also seek to keep these models up to date using data from diverse, contemporary patients undergoing both modern operative and nonoperative treatments.
Level III, diagnostic study.
Lee CC
，Chen CW
，Yen HK
，Lin YP
，Lai CY
，Wang JL
，Groot OQ
，Janssen SJ
，Schwab JH
，Hsu FM
，Lin WH
... -
《-》
ResearchGate
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钛学术
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