A liquid biomarker signature of inflammatory proteins accurately predicts early pancreatic cancer progression during FOLFIRINOX chemotherapy

被引:3
|
作者
van Eijck, Casper W. F. [6 ]
Sabroso-Lasa, Sergio [2 ,3 ]
Strijk, Gaby J. [1 ]
Mustafa, Dana A. M. [4 ]
Fellah, Amine [1 ]
Koerkamp, Bas Groot [5 ]
Malats, Nuria [2 ,3 ]
van Eijck, Casper H. J. [1 ,2 ,6 ]
机构
[1] Erasmus MC, Erasmus MC Canc Inst, Rotterdam, Netherlands
[2] Spanish Natl Canc Res Ctr, Genet & Mol Epidemiol Grp, Madrid, Spain
[3] Ctr Invest Biomed Red Canc CIBERONC, Madrid, Spain
[4] Erasmus MC, Dept Clin Bioinformat, Rotterdam, Netherlands
[5] Erasmus MC, Dept Surg, Rotterdam, Netherlands
[6] Erasmus MC, Erasmus MC Canc Inst, Dr Molewaterplein 40, NL-3015 GD Rotterdam, Netherlands
来源
NEOPLASIA | 2024年 / 49卷
关键词
Biomarkers; Gene Expression Profiling; folfirinox; Pancreatic Neoplasms; Precision Medicine; Protein Array Analysis; DUCTAL ADENOCARCINOMA; FACTOR-RECEPTOR; EMERGING ROLES; FCRL FAMILY; RESISTANCE; METASTASIS; ALPHA; OVEREXPRESSION; GEMCITABINE; REGRESSION;
D O I
10.1016/j.neo.2024.100975
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Background: Pancreatic ductal adenocarcinoma (PDAC) is often treated with FOLFIRINOX, a chemotherapy associated with high toxicity rates and variable efficacy. Therefore, it is crucial to identify patients at risk of early progression during treatment. This study aims to explore the potential of a multi-omics biomarker for predicting early PDAC progression by employing an in-depth mathematical modeling approach. Methods: Blood samples were collected from 58 PDAC patients undergoing FOLFIRINOX before and after the first cycle. These samples underwent gene (GEP) and inflammatory protein expression profiling (IPEP). We explored the predictive potential of exclusively IPEP through Stepwise (Backward) Multivariate Logistic Regression modeling. Additionally, we integrated GEP and IPEP using Bayesian Kernel Regression modeling, aiming to enhance predictive performance. Ultimately, the FOLFIRINOX IPEP (FFX-IPEP) signature was developed. Results: Our findings revealed that proteins exhibited superior predictive accuracy than genes. Consequently, the FFX-IPEP signature consisted of six proteins: AMN, BANK1, IL1RL2, ITGB6, MYO9B, and PRSS8. The signature effectively identified patients transitioning from disease control to progression early during FOLFIRINOX, achieving remarkable predictive accuracy with an AUC of 0.89 in an independent test set. Importantly, the FFXIPEP signature outperformed the conventional CA19-9 tumor marker. Conclusions: Our six-protein FFX-IPEP signature holds solid potential as a liquid biomarker for the early prediction of PDAC progression during toxic FOLFIRINOX chemotherapy. Further validation in an external cohort is crucial to confirm the utility of the FFX-IPEP signature. Future studies should expand to predict progression under different chemotherapies to enhance the guidance of personalized treatment selection in PDAC.
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页数:12
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