Baseline differences in metabolic profiles of patients with lung squamous cell carcinoma responding or not responding to treatment with nanoparticle albumin-bound paclitaxel (nab-paclitaxel)

Author:

Cao Peng,Zhang Qilin,Wu Sanlan,Sullivan Mitchell A.,Huang Yifei,Gong Weijing,Lv Yongning,Zhai Xuejia,Zhang Yu

Abstract

Background: Nanoparticle albumin-bound paclitaxel (nab-paclitaxel) is a preparation widely used in chemotherapy for cancers. However, only some patients benefit from this treatment. Therefore, identifying which patients will respond to nab-paclitaxel therapy is crucial. Methods: A cohort of 32 patients with lung squamous cell carcinoma (LUSC) treated with nab-paclitaxel were enrolled in this study. Plasma samples were collected before chemotherapy and used to perform metabolomic and lipidomic analyses. Tumor response to two cycles of chemotherapy was evaluated. Metabolites differentially present among populations were screened and analyzed. Results: According to the RECIST criteria, one-third of patients had a significant response to nab-paclitaxel, whereas one-fifth showed no discernible benefit. According to the criteria of variable importance in projection >1 and fold change >2, we identified 61, 81 and 54 differential metabolites between the progressive disease (PD) vs partial response (PR), PD vs stable disease (SD), and SD vs PR groups, respectively. Moreover, we used three variation in logistic regression models and ROC diagnostic curves to identify optimal metabolites for stratifying patients with differing chemotherapeutic responses. The PD vs SD, SD vs PR, and PD vs PR groups were well separated on the basis of cis-9,10-epoxystearic acid/octapentaenoic acid (AUC 0.9330), salicyluric acid/DG (18:1/20:5/0:0) (AUC 1.0000) and D-glyceric acid/9,12-octadecadienoic acid (AUC 1.0000), respectively. Conclusion: The baseline metabolic profiles significantly differed between responder and non-responder patients with LUSC treated with nab-paclitaxel. These differential metabolites have the potential to predict the outcomes of patients with LUSC before chemotherapy.

Publisher

Compuscript, Ltd.

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