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Whilst survival benefits of thoracic radiotherapy (TRT) followed by immune checkpoint inhibitor (ICI) have been reported in patients with lung cancer, the potential high risk of treatment-related pneumonitis remains a concern. Asians may be more sensitive to lung toxicity than other races. This retrospective study intended to provide a comprehensive pneumonitis profile of TRT followed by ICI and investigate the risk factors from a Chinese cohort of lung cancer. From January 2016 to July 2021, 196 patients with lung cancer who received TRT prior to ICI were retrospectively analyzed. Treatment-related pneumonitis, including checkpoint inhibitor pneumonitis (CIP), radiation pneumonitis (RP), and radiation recall pneumonitis (RRP), were recorded and graded through medical records and chest computed tomography. Characteristics predictive of pneumonitis were assessed using logistic regression models, and the receiver operating characteristic analyses were performed to identify optimal cut points for quantitative variables. With a median follow-up of 18 months, a total of 108 patients (55.1%) developed treatment-related pneumonitis during ICI therapy, with an incidence of 25.5% for grade 2 or higher (G2+) and 4.1% for G3+. The overall rates of CIP, RP and RRP were 8.2% (n=16), 46.9% (n=92) and 7.1% (n=14), respectively. With a total mortality rate of 1.5%, vast majority of the patients recovered from pneumonitis or remained stable. No patients died of RRP. Half of the patients with G2+ RP who withheld ICI therapy restarted ICI safely after resolution of RP. The history of chronic pulmonary diseases ( =0.05), mean lung dose (MLD, =0.038), percent volume of lung receiving ≥5 Gy (V5, =0.012) and percent volume of lung receiving ≥20 Gy (V20, =0.030) predicted the occurrence of RRP in univariate analyses. Interval between TRT and ICI less than 3 months was an independent predictor for G2+ treatment-related pneumonitis in a multivariate model (Odds ratio OR=2.787, =0.004). Treatment-related pneumonitis, especially RRP, is acceptable and manageable in the setting of TRT followed by ICI in this Asian population. Dosimetric parameters MLD, V5 and V20 may improve the predictions of RRP in clinical practice.

Radiotherapy can be limited by pneumonitis, which is impacted by innate immunity, including pathways regulated by TRAIL death receptor DR5. We investigated whether DR5 agonists could rescue mice from toxic effects of radiation and found that 2 different agonists, parenteral PEGylated trimeric TRAIL (TLY012) and oral TRAIL-inducing compound (TIC10/ONC201), could reduce pneumonitis, alveolar wall thickness, and oxygen desaturation. Lung protection extended to late effects of radiation including less fibrosis at 22 weeks in TLY012-rescued survivors versus unrescued surviving irradiated mice. Wild-type orthotopic breast tumor-bearing mice receiving 20 Gy thoracic radiation were protected from pneumonitis with disappearance of tumors. At the molecular level, radioprotection appeared to be due to inhibition of CCL22, a macrophage-derived chemokine previously associated with radiation pneumonitis and pulmonary fibrosis. Treatment with anti-CCL22 reduced lung injury in vivo but less so than TLY012. Pneumonitis severity was worse in female versus male mice, and this was associated with increased expression of X-linked TLR7. Irradiated mice had reduced esophagitis characterized by reduced epithelial disruption and muscularis externa thickness following treatment with the ONC201 analog ONC212. The discovery that short-term treatment with TRAIL pathway agonists effectively rescues animals from pneumonitis, dermatitis, and esophagitis following high doses of thoracic radiation exposure has important translational implications.

Purpose: Radiotherapy is a crucial treatment approach for many types of cancer. Radiation pneumonitis (RP) is one of the major complications in chest irradiation. Fucoidan is a sulfated polysaccharide found mainly in various species of brown seaweed. Recent studies have demonstrated the anti-inflammatory effects of fucoidan. However, no study has reported a well-established prophylactic agent for RP. Therefore, we investigated the effects of fucoidan on RP and radiotherapy (RT)-induced lung fibrosis. Materials and Methods: We compared RP and RT-induced fibrosis in lung tissue specimens obtained from irradiated (10 Gy/shot) C57BL/6 mice with or without fucoidan administration (200 mg/kg/day, oral gavage for 14 days). The expression patterns of cytokines in the pleural fluid were determined using a cytokine array and confirmed through enzyme immunoassays. Results: Fucoidan administration attenuated RP and RT-induced fibrosis in lung tissues. Decreased neutrophil and macrophage accumulation was observed in irradiated lung tissues, and radiation-induced lung fibrosis, as demonstrated by Masson trichrome staining, was attenuated. We investigated the expression patterns of inflammatory cytokines in the irradiated lung pleural fluid through the protein array; results revealed that fucoidan administration changed the expression patterns of inflammatory cytokines in irradiated lung tissues. Furthermore, the expression levels of TIMP-1, CXCL1, MCP-1, MIP-2, and interleukin-1Ra were substantially enhanced in the pleural fluid, but fucoidan administration significantly reduced their expression. Conclusions: Fucoidan changes the expression patterns of inflammatory cytokines, which may consequently attenuate RP and RT-induced lung fibrosis.

Purpose To predict the risk of radiation pneumonitis (RP), a multiomics model was built to stratify lung cancer patients. Our study also investigated the impact of RP on survival. Methods This study retrospectively collected 100 RP and 99 matched non-RP lung cancer patients treated with radiotherapy from two independent centres. They were divided into training (n = 175) and validation cohorts (n = 24). The radiomics, dosiomics and clinical features were extracted from planning CT and electronic medical records and were analysed by LASSO Cox regression. A multiomics prediction model was developed by the optimal algorithm. Overall survival (OS) between the RP, non-RP, mild RP, and severe RP groups was analysed by the Kaplan‒Meier method. Results Sixteen radiomics features, two dosiomics features, and one clinical feature were selected to build the best multiomics model. The optimal performance for predicting RP was the area under the receiver operating characteristic curve (AUC) of the testing set (0.94) and validation set (0.92). The RP patients were divided into mild (≤ 2 grade) and severe (> 2 grade) RP groups. The median OS was 31 months for the non-RP group compared with 49 months for the RP group (HR = 0.53, p = 0.0022). Among the RP subgroup, the median OS was 57 months for the mild RP group and 25 months for the severe RP group (HR = 3.72, p < 0.0001). Conclusions The multiomics model contributed to improving the accuracy of RP prediction. Compared with the non-RP patients, the RP patients displayed longer OS, especially the mild RP patients.

Radiation‐induced lung injury (RILI) is one of the most common and fatal complications of thoracic radiotherapy. It is characterized with two main features including early radiation pneumonitis and fibrosis in later phase. This study was to investigate the potential radioprotective effects of polydatin (PD), which was shown to exert anti‐inflammation and anti‐oxidative capacities in other diseases. In this study, we demonstrated that PD‐mitigated acute inflammation and late fibrosis caused by irradiation. PD treatment inhibited TGF‐β1‐Smad3 signalling pathway and epithelial–mesenchymal transition. Moreover, radiation‐induced imbalance of Th1/Th2 was also alleviated by PD treatment. Besides its free radical scavenging capacity, PD induced a huge increase of Sirt3 in culture cells and lung tissues. The level of Nrf2 and PGC1α in lung tissues was also elevated. In conclusion, our data showed that PD attenuated radiation‐induced lung injury through inhibiting epithelial–mesenchymal transition and increased the expression of Sirt3, suggesting PD as a novel potential radioprotector for RILI.

Regulatory T cells (Tregs), which have long been recognized as essential regulators of both inflammation and autoimmunity, also impede effective antitumor immune response due to their immunosuppressive properties. Combined radiotherapy and immunotherapeutic interventions focusing on the removal of Tregs have recently garnered interest as a promising strategy to reverse immunosuppression. Meanwhile, Tregs are emerging as a key player in the pathogenesis of radiation-induced lung injury (RILI), a frequent and potentially life-threatening complication of thoracic radiotherapy. Recognition of the critical role of Tregs in RILI raises the important question of whether radiotherapy combined with Treg-targeting immunotherapy offers any beneficial effects in the protection of normal lung tissue. This present review focuses on the contributions of Tregs to RILI, with particular emphasis on the suspected differential role of Tregs in the pneumonitic phase and fibrotic phase of RILI. We also introduce recent progress on the potential mechanisms by which Tregs modulate RILI and the crosstalk among Tregs, other infiltrating T cells, fibrocytes, and resident epithelial cells driving disease pathogenesis. Finally, we discuss whether Tregs also hold promise as a potential target for immunotherapeutic interventions for RILI.

Radiation pneumonitis (RP) is a prevalent complication associated with lung cancer radiotherapy; nonetheless, its effects on lung cancer immunotherapy and the underlying biological mechanisms remain inadequately elucidated. Utilizing mouse models of RP and orthotopically lung cancer, we witnessed immunotherapy-enhanced liver metastasis of lung cancer within the context of RP, accompanied by increased neutrophil infiltration of the primary tumor. Analysis of metabolic adaptations driven by the inflammatory microenvironment during treatment revealed that RP and immunotherapy act synergistically to exacerbate lipid metabolic dysregulation and oxidative stress. Integrating clinical validation with single-cell RNA sequencing data from a multicenter lung adenocarcinoma cohort, we demonstrated that elevated oxidative stress scores within tumor tissue were significantly associated with both diminished response to immunotherapy and unfavorable clinical outcomes. These findings coincided with alterations in the tumor immune microenvironment, notably a marked increase in neutrophils and activated mast cells. This investigation highlights that RP is not merely a toxicity but an active modulator of the tumor-immune-metabolism landscape. By dissecting the RP-ICB-metabolism axis, we have elucidated a novel mechanism underlying immunotherapy resistance, offering new insights into the rational design of optimized radioimmunotherapy.

Introduction Durvalumab after concurrent chemoradiation (cCRT) is now standard of care for unresected stage III non–small cell lung cancer (NSCLC). However, there is limited data on radiation pneumonitis (RP) with this regimen. Therefore, we assessed RP and evaluated previously validated toxicity models in predicting for RP in patients treated with cCRT and durvalumab. Methods Patients treated with cCRT and ≥ 1 dose of durvalumab were evaluated to identify cases of ≥ grade 2 RP. The validity of previously published RP models was assessed in this cohort as well a reference cohort treated with cCRT alone. The timing and incidence of RP was compared between cohorts. Results In total, 11 (18%) of the 62 patients who received cCRT and durvalumab developed ≥ grade 2 RP a median of 3.4 months after cCRT. The onset of RP among patients treated with cCRT and durvalumab was significantly longer vs the reference cohort (3.4 vs 2.1 months; P = .01). Numerically more patients treated with cCRT and durvalumab developed RP than patients in the reference cohort (18% vs 9%, P = .09). Among patients treated with cCRT and durvalumab, 82% (n = 9) were responsive to treatment with high‐dose glucocorticoids. Previously published RP models widely underestimated the rate of RP in patients treated with cCRT and durvalumab [AUC ~ 0.50; p(Hosmer‐Lemeshow): 0.98‐1.00]. Conclusions Our data suggest a delayed onset of RP in patients treated with cCRT and durvalumab vs cCRT alone, and for RP to develop in a greater number of patients treated with cCRT and durvalumab. Previously published RP models significantly underestimate the rate of symptomatic RP among patients treated with cCRT and durvalumab. Radiation pneumonitis (RP) is a significant toxicity of thoracic radiation, yet little is known regarding RP in lung cancer patients treated with definitive chemoradiation (cCRT) and durvalumab. We found patients treated with cCRT and durvalumab to have a significantly later onset of RP and a greater frequency of RP compared to patients treated with cCRT alone, we also found previously published toxicity models to be unsuccessful in predicting for RP among patients treated with cCRT and durvalumab.

Radiation therapy is widely used for thoracic cancers. However, it occasionally causes radiation-induced lung injuries, including pneumonitis and fibrosis. Chung-Sang-Bo-Ha-Tang (CSBHT) has been traditionally used to treat chronic pulmonary disease in Korea. PM014, a modified herbal formula derived from CSBHT, contains medicinal herbs of seven species. In our previous studies, PM014 exhibited anti-inflammatory effects in a chronic obstructive pulmonary disease model. In this study, we have evaluated the effects of PM014 on radiation-induced lung inflammation. Mice in the treatment group were orally administered PM014 six times for 2 weeks. Effects of PM014 on radiation pneumonitis were evaluated based on histological findings and differential cell count in bronchoalveolar lavage fluid. PM014 treatment significantly inhibited immune cell recruitment and collagen deposition in lung tissue. Normal lung volume, evaluated by radiological analysis, in PM014-treated mice was higher compared to that in irradiated control mice. PM014-treated mice exhibited significant changes in inspiratory capacity, compliance and tissue damping and elastance. Additionally, PM014 treatment resulted in the downregulation of inflammatory cytokines, chemokines, and fibrosis-related genes and a reduction in the transforming growth factor-β1-positive cell population in lung tissue. Thus, PM014 is a potent therapeutic agent for radiation-induced lung fibrosis and inflammation.

Objectives To evaluate quantitative computed tomography (QCT) features and QCT feature-based machine learning (ML) models in classifying interstitial lung diseases (ILDs). To compare QCT-ML and deep learning (DL) models’ performance. Methods We retrospectively identified 1085 patients with pathologically proven usual interstitial pneumonitis (UIP), nonspecific interstitial pneumonitis (NSIP), and chronic hypersensitivity pneumonitis (CHP) who underwent peri-biopsy chest CT. Kruskal-Wallis test evaluated QCT feature associations with each ILD. QCT features, patient demographics, and pulmonary function test (PFT) results trained eXtreme Gradient Boosting (training/validation set n = 911) yielding 3 models: M1 = QCT features only; M2 = M1 plus age and sex; M3 = M2 plus PFT results. A DL model was also developed. ML and DL model areas under the receiver operating characteristic curve (AUC) and 95% confidence intervals (CIs) were compared for multiclass (UIP vs. NSIP vs. CHP) and binary (UIP vs. non-UIP) classification performances. Results The majority (69/78 [88%]) of QCT features successfully differentiated the 3 ILDs (adjusted p ≤ 0.05). All QCT-ML models achieved higher AUC than the DL model (multiclass AUC micro-averages 0.910, 0.910, 0.925, and 0.798 and macro-averages 0.895, 0.893, 0.925, and 0.779 for M1, M2, M3, and DL respectively; binary AUC 0.880, 0.899, 0.898, and 0.869 for M1, M2, M3, and DL respectively). M3 demonstrated statistically significant better performance compared to M2 (∆AUC: 0.015, CI: [0.002, 0.029]) for multiclass prediction. Conclusions QCT features successfully differentiated pathologically proven UIP, NSIP, and CHP. While QCT-based ML models outperformed a DL model for classifying ILDs, further investigations are warranted to determine if QCT-ML, DL, or a combination will be superior in ILD classification. Key Points • Quantitative CT features successfully differentiated pathologically proven UIP, NSIP, and CHP. • Our quantitative CT-based machine learning models demonstrated high performance in classifying UIP, NSIP, and CHP histopathology, outperforming a deep learning model. • While our quantitative CT-based machine learning models performed better than a DL model, additional investigations are needed to determine whether either or a combination of both approaches delivers superior diagnostic performance.