Background: There have been no comprehensive large-scale studies that have evaluated the benefits of chemotherapy-based regimens in addressing HER2-altered advanced non-small-cell lung cancer (NSCLC) in a first-line setting. Data on HER2 alteration subtypes and concomitant alterations are also limited. Accordingly, our retrospective, real-world POLISH study assesses the efficacy of first-line chemotherapy alone (C) as well as combinations with immune checkpoint inhibitors (C + I) or angiogenesis inhibitors (C + A) for HER2-altered NSCLC; molecular features are also reported. Methods: HER2-altered NSCLC patients who received a first-line treatment between November 2015 and September 2021 were screened. Patients treated with C, C + I, or C + A were included in our final efficacy analysis. Progression-free survival (PFS) was compared between the subgroups. A Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis was performed to evaluate concomitant alterations. Results: A total of 293 patients were screened, with an identification of HER2 amplification and 37 distinct HER2 mutations, and 210 cases treated with C, C + I, or C + A were ultimately included. C + A achieved longer PFS than C (5.63 vs 4.03 months, hazard ratio: 0.64, 95% confidence interval [CI]: 0.46–0.88, p = 0.006). C + I did not improve median PFS compared to C + A or C (both p > 0.05), despite the programmed cell death ligand-1 (PD-L1) expression or tumor mutational burden. KEGG analysis revealed that concomitant upregulation of PI3 K/AKT pathway signaling was common in HER2-altered NSCLC. Conclusion: Chemotherapy plus angiogenesis inhibitors may yield a greater survival benefit than chemotherapy alone in a first-line setting for HER2-altered NSCLC, whereas an immune-based combination therapy may not be superior to a sole chemotherapy regimen. Activation of PI3 K/AKT signaling may mediate immunosuppression in HER2-altered NSCLC.
Rock burst disasters occurring in underground high-stress rock mass mining and excavation engineering seriously threaten the safety of workers and hinders the progress of engineering construction. Rock burst classification prediction is the basis of reducing and even eliminating rock burst hazards. Currently, most of mainstream discriminant models for rock burst grade prediction are based on small samples. Comprehensive selection according to many pieces of literature, the maximum tangential stress of surrounding rock and rock uniaxial compressive strength ratio coefficient (stress state parameter), rock uniaxial compressive strength and uniaxial tensile strength ratio (brittleness modulus), and the elastic energy index are used as a grading evaluation index of rock burst based on the collection of different construction engineering instances of rock burst in 114 groups of extensive sample data in different regions of the world, which are used to carry out the training study. The representativeness and accuracy of the index selection were verified by the indicator variance analysis and Spearman correlation coefficient hypothesis test. The Intelligent Rock burst Identification System (IRIS) based on an optimizable SVM model was established using data set samples. After extensive data cross-validation training, the accuracy of the SVM discriminant analysis model can reach 95.6%, which is significantly better than the prediction accuracy of the traditional SVM model of 71.9%. The model is used to classify and predict the rock burst intensity of 10 typical projects at home and abroad. The prediction results are consistent with the actual rock burst intensity, which is better than the discriminant model based on small sample data and other existing prediction models. The application of engineering examples shows that the results of the rock burst intensity classification prediction model based on extensive sample data processing analysis and the SVM discriminant method are in good agreement with the actual rock burst intensity, which can effectively provide a reference for the prediction of rock burst intensity grade in a construction area.
Background:HER2 exon 20 insertions remain a subset heterogeneous alterations in lung cancer, with currently unmet need for precision targeted therapy. G776delinsVC, a typical HER2 exon 20 deletion-insertion at codon Gly776, was reported to respond discrepantly to afatinib compared with the predominant insertion A775_G776insYVMA (YVMA). However, it lacks structural evidence to illustrate the possible mechanism and predict the binding activities of its similar variants over YVMA insertion to HER2-targered tyrosine kinase inhibitors (TKIs).Methods: Real-world cohort study was performed to investigate clinical outcomes with HER2-targeted TKI afatinib and pyrotinib, and structural analysis for exon 20 Gly776 deletion-insertions G776delinsVC, G776delinsLC and G776delinsVV, and YVMA by molecular dynamics simulation and cellular kinase inhibition assay were provided for full exploration.Results: Afatinib revealed low objective response rate (ORR) of 0–9.5% and short median progression-free survival (mPFS) of 2.8–3.2 months for YVMA, but with higher ORR of 20–28.6% and longer mPFS of 4.3–7.1 months for G776delinsVC. Pyrotinib presented significantly improved PFS benefit than afatinib for G776delinsVC and YVMA as first-line (median, 6.8 vs. 3.4 months, p = 0.010) or second-line therapy (median, 5.8 vs. 2.8 months, p < 0.001). No significant difference was observed on drug binding pocket and TKI binding activity between G776delinsVC, G776delinsLC and G776delinsVV, and both afatinib and pyrotinib showed favorable binding activity. YVMA insertion significantly affected the loop region with altering HER2 protein secondary structure and forming steric hindrance to binding of afatinib. Pyrotinib showed the best selectivity to HER2, with more favorable activity to YVMA than afatinib indicated by cellular inhibition assay.Conclusion: Both afatinib and pyrotinib showed favorable activity for NSCLC patients with HER2 exon 20 Gly776 deletion-insertions. Pyrotinib revealed more potent activity to A775_G776insYVMA insertion than afatinib due to the steric binding hindrance induced by YVMA.
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