Table 2 Application of proteomics in studies on antitumor mechanisms of TCM
From: Application of omics technologies in studies on antitumor effects of Traditional Chinese Medicine
TCM type | Research object | Cancer type | Main technology | Main anti-tumor mechanism | References |
|---|---|---|---|---|---|
Traditional Chinese medicine formulas | Pien Tze Huang | Liver cancer | Protein chip | Modulating the secretion of inflammation-related cytokines, tumor growth pathways, and ↑ G2/M phase arrest | [76] |
Aidi injection optimal formula | Liver cancer/Colorectal cancer | TMT-based quantitative proteomics | Chen medicine can antagonize the activity of UPS lead by Jun medicine | [77] | |
Traditional Chinese herbs/monomers | Camellia nitidissima Chi | Colon Cancer | Label-free quantitative proteomics | Regulating iron death pathway-associated proteins such as GPX4 and HMOX1 | [78] |
Salvia chinensia Benth | Esophageal cancer | TMT-based quantitative proteomics | ↑ P-AMPK, P-ULK1, LC3 II/I and AMPK/ULK1 pathway | [79] | |
Antrodia Cinnamomea | Liver cancer | 2D-DIGE/MALDI-TOF MS proteomics | Regulating pathways related to protein folding, cellular cytoskeleton, and oxidation–reduction | [80] | |
Dendrobium nobile | Lung cancer and liver cancer | SILAC quantitative proteomics | ↑ ROS, ER stress and UPR and leading to autophagy and apoptosis | [81] | |
Lindera obtusiloba Blume | Tumor angiogenesis | Protein chip | ↑ Nibrin/NBS, ↓ Plk-1 and Cyclin E | [82] | |
Celastrus Orbiculatus Vine | liver cancer | TMT / iTRAQ quantitative proteomics | ↓ EphA2, tumor growth and angiogenesis | [83] | |
Astragalus polysaccharide (from Astragali Radix) | Lung cancer | Label-free quantitative proteomics | Regulating the tumor microenvironment through the TLR4/MyD88/NF-κB signaling pathway | [84] | |
Corilagin (from Phyllanthus niruri L) | Ovarian cancer | Protein chip and iTRAQ quantitative proteomics | ↑ Apoptosis-related protein expression, ↓ CD44, STAT3 and glycolysis | [85] | |
Triptolide (from Tripterygium wilfordii) | Lung cancer | iTRAQ quantitative proteomics | ↑ MTA2 and EIF4A3, ↓ PHB, CDH1 and AIFM1, and regulating PARP1/AIF and Akt signaling pathways | [86] | |
Celastrol (from Tripterygium wilfordii) | Cervical cancer | TMT-based quantitative proteomics | Confirming that GSTO1 and PDI are the targets | [87] | |
Plectranthoic acid (from Ficus microcarpa) | Prostate cancer | Label-free quantitative proteomics | Through signaling pathways such as granulin A, endoplasmic reticulum stress, and mTOR | [88] | |
Curcumin (from Curcuma longa) | Chronic myelogenous leukemia | SWATH quantitative proteomics | Through the miR-22/IPO7/HIF-1α axis | [89] | |
SANT (monomer combination) | Breast cancer | Protein chip | ↓ Blood vessel formation-related proteins (such as HB-EGF and IGFBP-9) | [90] |