Longitudinal plasma proteomic analysis identifies biomarkers and combinational targets for anti-PD1-resistant cancer patients.

The response rate of anti-PD1 therapy is limited, and the influence of anti-PD1 therapy on cancer patients is unclear. To address these challenges, we conducted a longitudinal analysis of plasma proteomic changes with anti-PD1 therapy in non-small cell lung cancer (NSCLC), alveolar soft part sarcoma (ASPS), and lymphoma patients. We included 339 plasma samples before and after anti-PD1 therapy from 193 patients with NSCLC, ASPS, or lymphoma. The plasma proteins were detected using data-independent acquisition-mass spectrometry and customable antibody microarrays. Differential proteomic characteristics in responders (R) and non-responders (NR) before and after anti-PD1 therapy were elucidated. A total of 1019 proteins were detected using our in-depth proteomics platform and distributed across 10-12 orders of abundance. By comparing the differential plasma proteome expression between R and NR groups, 50, 206, and 268 proteins were identified in NSCLC, ASPS, and lymphoma patients, respectively. Th17, IL-17, and JAK-STAT signal pathways were identified upregulated in NR group, while cellular senescence and transcriptional misregulation pathways were activated in R group. Longitudinal proteomics analysis revealed the IL-17 signaling pathway was downregulated after treatment. Consistently, many proteins were identified as potential combinatorial therapeutic targets (e.g., IL-17A and CD22). Five noninvasive biomarkers (FLT4, SFTPB, GNPTG, F5, and IL-17A) were further validated in an independent lymphoma cohort (n = 39), and another three noninvasive biomarkers (KIT, CCL3, and TNFSF1) were validated in NSCLC cohort (n = 76). Our results provide molecular insights into the anti-PD1 therapy in cancer patients and identify new therapeutic strategies for anti-PD1-resistant patients.

Study on the Adsorption of Trace Water in N-Methyl-pyrrolidone Solvents by A-Type Molecular Sieves.

N-Methyl-pyrrolidone (NMP) is an important coating solvent for the production of lithium batteries, and its water content will greatly affect the coating quality and energy density of lithium batteries, which needs to be reduced to 200 ppm. The current vacuum distillation technology suffers from high operating costs and high energy consumption, whereas the pervaporation technology only achieves solvent dehydration up to 99.5%. Therefore, it is of great significance to carry out the study of trace water removal from NMP solvents. In this paper, the A-type molecular sieve adsorption method was used to remove trace water from the NMP solvent, and the effects of molecular sieve type, particle size, adsorption temperature, feeding amount, and contact time on the dehydration performance of NMP system were first investigated. Adsorbed at 25 °C for 240 min at a feeding amount of 120 g/L, 3A molecular sieves were able to reduce the water content of the NMP solvent from 5000 to 140 ppm. Second, Langmuir and Freundlich equations were used to fit the static isothermal adsorption data, and the results showed a better correlation of the Langmuir equation. Then, the adsorption kinetics and diffusion mechanism were analyzed by the kinetic model and the Crank single-pore diffusion model. The R2 of the pseudo-first-order kinetic model was 0.9993, which was more suitable for describing the process of adsorption of water from the NMP solvent by 3A molecular sieves, and the effective diffusion coefficient De = 2.986 × 10-8 cm2/s was calculated for the Crank single-pore adsorption model, which proved water molecules on the 3A molecular sieve. The diffusion of water molecules on the inner surface of the pores is the controlling step of the adsorption process. Finally, the fixed-bed dynamic penetration curves were investigated to obtain the experimental data of fixed-bed adsorption, and the experimental data were fitted using the Thomas and Yoon-Nelson models, which showed that both models could describe the adsorption behavior of trace water in NMP solvents on 3A molecular sieves. This study provides a new idea for the removal of trace water in NMP systems, and a series of model fitting parameters provide basic data for industrial scale-up.