Conclusion

In summary, using comprehensive discovery proteomics analysis followed by target proteomics validation at a large scale sample size, we performed a system-based high throughput analysis to better understand the biological response induced by cryo-thermal therapy and reveal the stimulation of tumor-specific immunity at the molecular level. The cryo-thermal therapy induced strongest “acute” response helped boost systematic anti-tumor immune response in the host for a stronger immunogenicity environment, which enabled more effective cure of metastatic tumor.

Supplementary Material

Additional File 1:

Supplementary Table 1.

http://www.thno.org/v06p0773s1.xlsx

Additional File 2:

Supplementary Table 2.

http://www.thno.org/v06p0773s2.xlsx

Additional File 3:

Supplementary Table 3.

http://www.thno.org/v06p0773s3.xlsx

Additional File 4:

Supplementary Table 4.

http://www.thno.org/v06p0773s4.xlsx

Additional File 5:

Supplementary Table 5.

http://www.thno.org/v06p0773s5.xlsx

Additional File 6:

Supplementary Table 6.

http://www.thno.org/v06p0773s6.xlsx

Additional File 7:

Supplementary Figures.

http://www.thno.org/v06p0773s7.pdf

Abbreviations

A1BG: Alpha-1-B glycoprotein; APCs: Antigen presenting cells; APCS: Serum amyloid P-component; APPs: Acute phase proteins; C2: Complement component 2; C8B: Complement component 8, beta polypeptide; CFP: Complement factor properdin; CST6: Cystatin E/M; CTSL: Cathepsin L1; DDA: Data-dependent acquisition; DC: Dendritic cell; DKK3: Dickkopf-related protein 3; DMEM: Dulbecco’s Modified Eagle’s Medium; DPP4: Dipeptidyl-peptidase 4; FBS: Fetal bovine serum; FDR: False discovery rate; HCD: Higher-energy collisional dissociation; HP: Haptoglobin; ICOSL: ICOS ligand; IL-4: Interleukin 4; IL-5: Interleukin 5; IL-6: Interleukin 6; IL-12: Interleukin 12; IL-13: Interleukin 13; IFN-γ: Interferon gamma; IPA: Ingenuity Pathway Analysis; iTRAQ: Isobaric tags for relative and absolute quantitation; MDSC: Myeloid-derived suppressor cells; MFAP4: Microfibrillar-associated protein 4; MGAM: Maltase-glucoamylase; MUP3: Major urinary protein 3; NAPSA: Napsin-A; ORM1: Alpha-1-acid glycoprotein 1; ORM2: Alpha-1-acid glycoprotein 2; ORM3: Alpha-1-acid glycoprotein 3; PON1: Serum paraoxonase/arylesterase 1; PRG4: Proteoglycan 4; PRM: Parallel reaction monitoring; SELL: L-selectin; sLIFR: Soluble leukemia inhibitory factor receptor; SRM: Selected reaction monitoring; TAMs: Tumor associated macrophages; TFE: Trifluoroethanol; Th1: T-helper 1; TPP: Trans-Proteomic Pipeline; Tregs: T regulatory cells

Acknowledgements

The authors wish to thank Wei Zhang (Thermo Fisher Scientific), ChengPin Shen (Shanghai

CloudScientific Technology Co., Ltd), Samuel Bader, Luis Mendoza, Kristian Swearingen and Patrick Flores (Institute for System Biology) for their support of mass spectrometer’s operation and data analysis. We also would like to acknowledge Dr. Jie Hao (Shanghai Center for Systems Biomedicine) for help with statistical and bioinformatics data analysis and Dr. Xin Ku for critical comments during manuscript preparation. This work was funded in part by the American Recovery and Reinvestment Act (ARRA) funds through National Institutes of Health from the NHGRI grant RC2HG005805, the NIGMS grants R01GM087221, S10RR027584 and 2P50GM076547 to the Center for Systems Biology, the National Science Foundation MRI grant 0923536. This work was also supported by the National Natural Science Foundation of China (11275126, U1532116) and China Scholarship Council.

Author contributions

TX, PL, WY, and RLM conceived and designed the research. LXX was the project leader. TX conducted the experiments and data analysis. TX and WY wrote the manuscript. YZ and LY helped design and modify the glycocapture and iTRAQ experiments. LY helped analysis the MS data. KL performed the RT-PCR experiments.

Competing Interests

The authors have declared that no competing interest exists.