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Background: KRAS and BRAF targets are involved in the epidermal growth factor receptor pathway. KRAS and BRAF targets are the most frequent driver mutations in cancer. Objective: The objective of the study was to present the recent developments in the KRAS target and the BRAF target. Method: KRAS target and BRAF target were analyzed by US patent analysis. All US granted patent documents from January 2002 to November 2021 were retrieved. Results: The results showed both KRAS and BRAF targets to be attractive targets for developing anticancer drugs. The technology of RNA interference has been developed for drug discovery related to the KRAS target. Our study indicates that the structural screening of inhibitors between the KRAS target and the BRAF target should be an inverse option. Conclusion: The chemical structures of inhibitors of BRAF target exhibited a unique classification of C07D405. The inhibitors of BRAF target could be used for the treatment of various cancers. However, the inhibitors of KRAS target did not show this feature. The present study provides new insight into drug discovery involving KRAS and BRAF targets.

Aims: To describe the health-related quality of life (HRQoL) of melanoma brain metastasis (MBM) patients throughout the first 18 weeks of ipilimumab–nivolumab or nivolumab treatment. Materials & methods: HRQoL data (European Organisation for Research and Treatment of Cancer's Core Quality of Life Questionnaire, additional Brain Neoplasm Module, and EuroQol 5-Dimension 5-Level Questionnaire) were collected as a secondary outcome of the Anti-PD1 Brain Collaboration phase II trial. Mixed linear modeling assessed changes over time, whereas the Kaplan–Meier method was used to determine median time to first deterioration. Results: Asymptomatic MBM patients treated with ipilimumab–nivolumab (n = 33) or nivolumab (n = 24) maintained baseline HRQoL. MBM patients with symptoms or leptomeningeal/progressive disease treated with nivolumab (n = 14) reported a statistically significant trend toward improvement. Conclusion: MBM patients treated with either ipilimumab–nivolumab or nivolumab did not report a significant deterioration in HRQoL within 18 weeks of treatment initiation. Clinical trial registration: NCT02374242 ( ClinicalTrials.gov )

Aims: This work was designed to identify the subgroup of advanced hepatocellular carcinoma (HCC) patients for whom treatments containing immune checkpoint blockers (ICBs) were most effective. Materials & methods: A meta-analysis was performed to explore the subgroup population with the greatest benefit of treatments containing ICBs. Results: A total of 2228 patients from four randomized control trials were included. Treatments containing ICBs had better overall survival, progression-free survival and higher objective response rate over treatment without ICBs. Subgroup analysis revealed that treatments containing ICBs were highly effective in improving the overall survival of males, patients with macrovascular invasion and/or extrahepatic spread and viral-related HCC patients. Conclusion: Treatments containing ICBs are more effective for males, patients with macrovascular invasion and/or extrahepatic spread and viral-related HCC patients.

PURPOSE Immune checkpoint inhibitors combined with antiangiogenic therapy reportedly have potential synergistic antitumor activity. We investigated the activity and safety of this regimen for recurrent/metastatic nasopharyngeal carcinoma (NPC). METHODS This single-arm, Simon two-stage study enrolled patients with recurrent/metastatic NPC who were refractory to at least first-line systemic therapy and treatment-naive to immune checkpoint inhibitors. The patients received camrelizumab 200 mg once every 3 weeks and apatinib 250 mg once per day. The primary end point was the objective response rate. Key secondary end points included disease control rate, progression-free survival, duration of response, overall survival, and safety. RESULTS Between October 14, 2020, and December 23, 2021, 58 patients were enrolled, and all were included in the efficacy and safety analysis set. The objective response rate was 65.5% (95% CI, 51.9 to 77.5), and the disease control rate was 86.2% (95% CI, 74.6 to 93.9). The median duration of response was not reached, and the median progression-free survival was 10.4 months (95% CI, 7.2 to 13.6), with a median follow-up duration of 12.4 months (range, 2.1-19.9 months). Treatment-related adverse events (TRAEs) of grade 3 or higher were reported in 34 (58.6%) patients, with the most common being hypertension (19.0%), nasopharyngeal necrosis (15.5%), headache (12.1%), AST elevation (10.3%), and creatine phosphokinase elevation (10.3%). Sixteen (27.6%) patients discontinued apatinib treatment before progression because of unbearable TRAEs, and the most common complication was nasopharyngeal necrosis (9/16; 56.3%). Recurrent nasopharyngeal lesions (odds ratio, 5.94 [95% CI, 1.45 to 24.24]) and reirradiation (odds ratio, 5.33 [95% CI, 1.15 to 24.79]) were significantly positively correlated with nasopharyngeal necrosis. CONCLUSION Camrelizumab plus apatinib had promising antitumor activity in patients with refractory recurrent/metastatic NPC who failed first-line therapy. Moderate to severe TRAEs were experienced by 58.6%, including nasopharyngeal necrosis associated with local recurrence and a history of reirradiation.

To solve the problem of poor face recognition performance in unrestricted environments. A face recognition algorithm based on improved residual IR-ResNet-SE is designed. Firstly, the IR structure is added to the 34-layer residual network to reduce the variability of different features; Secondly, we add the channel attention module to increase the weight of important channel features; Finally, the Arcface loss function is used to improve the classification ability of the model. The LFW, AgeDB, and AR datasets reflect unrestricted factors such as pose, age, expression, occlusion, and illumination. The algorithm proposed in this paper is experimented on these three datasets. The experimental results show that the IR-ResNet-SE algorithm proposed in this paper can achieve 99.74% accuracy in the dataset LFW. And it has excellent robustness in face recognition under unrestricted conditions. &nbsp

In image segmentation, FCM clustering algorithm can not find the optimal initial clustering center and fall into local extremum, which leads to the decrease of image segmentation accuracy. The PSO algorithm has strong optimization ability, so a new method based on improved PSO algorithm is proposed to optimize the FCM clustering center selection. Firstly, the optimization performance of the PSO algorithm is improved. The distance difference between each particle and the optimal particle is calculated, and the maximum distance difference is selected. The ratio of the distance difference to the maximum distance difference and the aggregation degree of particles are used to construct the natural exponential function. This natural exponential function is used to improve the calculation method of inertia weight value of PSO algorithm, so that the farther the particle is away from the optimal position, the larger the inertia weight value it will get, the stronger the global search ability of particle; on the contrary, the smaller the inertia weight value, the stronger the local search ability of particle, so as to improve the optimization ability of PSO algorithm. The improved PSO algorithm is called DDPSO (Distance Difference PSO). Then the optimized FCM algorithm is applied to the segmentation of standard image and eggshell damaged image to improve the accuracy of image segmentation. Finally, the experimental results show that the FCM algorithm optimized by DDPSO has higher segmentation accuracy than the traditional method. &nbsp