Early Diagnosis and Prognosis Prediction of Pancreatic Cancer Using Engineered Hybrid Core-Shells in Laser Desorption/Ionization Mass Spectrometry

Juxiang Zhang; Fei Teng; Beiyuan Hu; Wanshan Liu; Yida Huang; Jiao Wu; Yuning Wang; Haiyang Su; Shouzhi Yang; Lumin Zhang; Lingchuan Guo; Zhe Lei; Meng Yan; Xiaoyu Xu; Ruimin Wang; Qingui Bao; Qiongzhu Dong; Jiang Long; Kun Qian

doi:10.1002/adma.202311431

Early Diagnosis and Prognosis Prediction of Pancreatic Cancer Using Engineered Hybrid Core-Shells in Laser Desorption/Ionization Mass Spectrometry

Adv Mater. 2024 May;36(18):e2311431. doi: 10.1002/adma.202311431. Epub 2024 Jan 29.

Authors

Juxiang Zhang^{1

2}, Fei Teng^{3

4}, Beiyuan Hu⁵, Wanshan Liu^{1

2}, Yida Huang^{1

2}, Jiao Wu^{1

2}, Yuning Wang^{1

2}, Haiyang Su^{1

2}, Shouzhi Yang^{1

2}, Lumin Zhang⁴, Lingchuan Guo⁶, Zhe Lei⁶, Meng Yan⁶, Xiaoyu Xu^{1

2}, Ruimin Wang^{1

2}, Qingui Bao⁷, Qiongzhu Dong⁴, Jiang Long⁵, Kun Qian^{1

2}

Affiliations

¹ State Key Laboratory of Systems Medicine for Cancer, School of Biomedical Engineering, Institute of Medical Robotics and Shanghai Academy of Experimental Medicine, Shanghai Jiao Tong University, Shanghai, 200030, China.
² Division of Cardiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, China.
³ Department of Gastrointestinal Surgery, Minhang Hospital, Fudan University, Shanghai, 201199, China.
⁴ Key Laboratory of Whole-Period Monitoring and Precise Intervention of Digestive Cancer, Shanghai Municipal Health Commission, Minhang Hospital, Fudan University, Shanghai, 201199, China.
⁵ Department of Pancreatic Surgery, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200080, China.
⁶ Department of Pathology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, 215006, China.
⁷ Fosun Diagnostics (Shanghai) Co., Ltd, Shanghai, 200435, China.

PMID: 38241281
DOI: 10.1002/adma.202311431

Abstract

Effective detection of bio-molecules relies on the precise design and preparation of materials, particularly in laser desorption/ionization mass spectrometry (LDI-MS). Despite significant advancements in substrate materials, the performance of single-structured substrates remains suboptimal for LDI-MS analysis of complex systems. Herein, designer Au@SiO₂@ZrO₂ core-shell substrates are developed for LDI-MS-based early diagnosis and prognosis of pancreatic cancer (PC). Through controlling Au core size and ZrO₂ shell crystallization, signal amplification of metabolites up to 3 orders is not only achieved, but also the synergistic mechanism of the LDI process is revealed. The optimized Au@SiO₂@ZrO₂ enables a direct record of serum metabolic fingerprints (SMFs) by LDI-MS. Subsequently, SMFs are employed to distinguish early PC (stage I/II) from controls, with an accuracy of 92%. Moreover, a prognostic prediction scoring system is established with enhanced efficacy in predicting PC survival compared to CA19-9 (p < 0.05). This work contributes to material-based cancer diagnosis and prognosis.

Keywords: diagnosis; metabolic biomarkers; nanomaterials; pancreatic cancer; prognosis.

MeSH terms

Early Detection of Cancer* / methods
Gold* / chemistry
Humans
Pancreatic Neoplasms* / diagnosis
Prognosis
Silicon Dioxide* / chemistry
Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization* / methods
Zirconium* / chemistry

Substances

Zirconium
Gold
zirconium oxide
Silicon Dioxide

Abstract

MeSH terms

Substances

Grants and funding