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By implementing dynamic circulating tumor DNA (ctDNA) analysis, we explored the impact of TP53 mutations on tumor evolution and resistance mechanisms to ensartinib in patients with ALK-positive NSCLC.In a multicenter phase 2 trial, patients with ALK-positive NSCLC who progressed on crizotinib were treated with ensartinib. Blood samples for ctDNA analysis were collected at baseline, cycle 3 day 1, and progression disease (PD) and analyzed with a 212-gene panel.A total of 440 samples were collected from 168 patients. Baseline TP53 mutations (20.2%) significantly correlated with inferior progression-free survival (4.2 mo versus 11.7 mo, p0.0001). Patients with TP53 mutations had higher mutation load than those without TP53 mutations at baseline (13.79 ± 3.72 versus 4.67 ± 0.39, p0.001). Although there was no significant difference in mutation load between these groups at cycle 3 day 1 (5.89 ± 2.25 versus 3.72 ± 0.62, p = 0.425), patients with mutated TP53 developed more mutations at PD (7.07 ± 1.25 versus 3.20 ± 0.33, p = 0.003). Frequency and abundance of secondary ALK mutations G1269A, G1202R, and E1210K increased markedly at PD than baseline. In patients without secondary ALK mutations, we identified ALK-independent resistance mechanisms including bypass signaling activation, downstream effector protein reactivation, epithelial-mesenchymal transformation, and epigenetic dysregulation.Our study highlighted the advantage of ctDNA analysis for monitoring tumor evolution. TP53 mutations promoted genetic evolution and accelerated occurrence of resistance. We also unveiled ALK-dependent resistance mechanisms, mainly by G1269A, G1202R, and E1210K mutations, and ALK-independent resistance mechanisms to ensartinib.

Summary Background Ensartinib is a potent new-generation ALK inhibitor with high activity against a broad range of known crizotinib-resistant ALK mutations and CNS metastases. We aimed to assess the efficacy and safety of ensartinib in ALK-positive patients with non-small-cell lung cancer (NSCLC), in whom crizotinib therapy was unsuccessful. The associations between ensartinib efficacy and crizotinib-resistant mutations were also explored. Methods We did a single-arm, open-label, phase 2 study at 27 centres in China. Patients were aged 18 years or older, had stage IIIb or stage IV ALK-positive NSCLC that had progressed while they were on crizotinib therapy, an Eastern Cooperative Oncology Group performance status of 2 or less, had measurable disease, and had received fewer than three previous treatments. Patients with CNS metastases were included if these metastases were asymptomatic and did not require steroid therapy. All patients received 225 mg ensartinib orally once daily on a continuous dosing schedule. The primary outcome was the proportion of patients with an objective response according to the Response Evaluation Criteria in Solid Tumors (version 1.1), as assessed by an independent review committee in all patients who received at least one dose of ensartinib with no major violations of the inclusion criteria (ie, the full analysis set). Safety was assessed in all enrolled patients who received at least one dose of ensartinib. This trial was registered with ClinicalTrials.gov , NCT03215693 . Findings Between Sept 28, 2017, and April 11, 2018, 160 patients were enrolled and had at least one dose of ensartinib (safety analysis set). Four patients had inclusion violations and were excluded from the efficacy analysis, which thus included 156 patients (full analysis set). 97 (62%) patients in the full analysis set had brain metastases. 76 (52% [95% CI 43–60]) of 147 patients in the full analysis set, with responses that could be assessed by the independent review committee, had an objective response. 28 (70% [53–83]) of 40 patients with measurable brain metastases as assessed by the independent review committee had an intracranial objective response. 145 (91%) of 160 patients had at least one treatment-related adverse event, which were mostly grade 1 or 2. The most common treatment-related adverse events were rash (89 [56%]), increased alanine aminotransferase concentrations (74 [46%]), and increased aspartate aminotransferase concentrations (65 [41%]). Interpretation Ensartinib has activity and is well tolerated in patients with crizotinib-refractory, ALK-positive NSCLC, including those with brain metastases. The role of ensartinib in patients in whom other second-generation ALK inhibitors have been unsuccessful warrants further studies. Funding Betta Pharmaceuticals.

Acute lung injury (ALI) is a life-threatening condition characterized by rapid-onset alveolar-capillary damage mediated by pathogenic proinflammatory immune responses. Since exposure to airway particulate matter (PM) could significantly change the inflammatory status of the individual, we investigated whether PM instillation in the airway could alter the course of ALI, using a murine model with experimental lung injury induced by intratracheal LPS challenge. We found that PM-treated mice presented significantly aggravated lung injury, which was characterized by further reductions in body weight, increased protein concentration in the bronchoalveolar lavage (BAL), and higher mortality rate, compared to control saline-treated mice. The PM-treated mice also presented elevated lung and systemic type 1 T helper cell (Th1) frequency as well as reduced lung regulatory T cell (Treg) frequency, which was associated with severity of lung injury. Further examinations revealed that the Treg function was impaired in PM-treated mice, characterized by significantly repressed transforming growth factor beta production. Adoptive transfer of functional Tregs from control mice to PM-treated mice significantly improved their prognosis after intratracheal LPS challenge. Together, these results demonstrated that first, PM in the airway aggravated lung injury; second, severity of lung injury was associated with T cell subset imbalance in PM-treated mice; and third, PM treatment induced quantitative as well as qualitative changes in the Tregs.

Reliable urban land-use maps are essential for urban analysis because the spatial distribution of land use reflects the complex environment of cities under the combined effects of nature and socio-economics. In recent years, very high resolution (VHR) remote sensing imagery interpretation has resolved the “semantic gap” between the low-level data and the high-level semantic scenes, and has been used to map urban land use. Nevertheless, the existing frameworks cannot easily be applied to practical urban analysis, which can be attributed to three main reasons: 1) the indistinguishable socio-economic attributes of the same ground object layouts; 2) the weak transferability of the supervised frameworks and the time-consuming training sample annotation; and 3) the category system inconsistency between the data source and the urban land-use application. In this paper, to achieve an “application gap” breakthrough for urban land-use mapping, a data-driven point, line, and polygon semantic object mapping (PLPSOM) framework is proposed, which makes full use of open-source VHR images and multi-source geospatial data. In the PLPSOM framework, point, line, and polygon semantic objects are represented by the points of interest (POIs), OpenStreetMap (OSM) data, and VHR images corresponding to the scenes in the land-use mapping units, respectively. OSM line semantic objects are utilized to supply the boundaries of the land-use mapping units for the POIs and VHR images, forming urban land parcels (street blocks). To reduce the cost of the data annotation, the training dataset is constructed using multiple open-source data sources. An enhanced deep adaptation network (EDAN) is then proposed to acquire the categories of the VHR scene images in the case of partial transfer learning. Finally, in order to meet the actual needs, a rule-based category mapping (RCM) model is applied to integrate the categories of the POIs and VHR images into the urban land-use category system, allowing us to acquire the land-use maps of the cities. The effectiveness of the proposed method was tested in four cities of China, including six specific areas: Beijing and Wuhan city centers; the Hanyang District of Wuhan; the Hannan District of Wuhan; Macao; and the Wan Chai area of Hong Kong, achieving a high classification accuracy. The “urban image” analysis confirmed the practicality of the obtained urban land-use maps.