Table 2.
Summary of Key Papers on Spatial Metabolomics in Cancer Study.
| Type of cancer | Authors | Tissue and tumor type | Key metabolites | Major ions and m/z values | Metabolic pathways or biological processes | Clinical relevance | Technique used |
|---|---|---|---|---|---|---|---|
| Breast Cancer: | Calligaris et al., 2014 (49) | Invasive ductal carcinoma tissues and surrounding non-neoplastic tissues | Fatty acids and lipids, especially oleic acid | Oleic acid (281.2), isobaric lipids (391.4, 655.6), PI18:0/20:4 (885.7) | G-protein coupled receptors signaling pathways; migration, proliferation, and invasion | Possible development of rapid detection of cancer residual | DESI-MSI |
| Guenther et al., 2015 (50) | Invasive ductal and lobular carcinoma; tumor tissue, tumor-associated stroma, normal glandular and stromal tissue | Free fatty acids and phospholipids | Lactate 2M+Na (201.04), lactate M+Na4Cl4 (320.86), calcidiol M-2H+Na (421.32) | De novo lipogenesis; immune response and inflammation | Distinguish tumor grade and HR status; separate tumor-related tissues from normal tissues within samples | DESI-MSI | |
| Sun et al., 2020 (51) | Breast cancer tissue, normal stromal and adipose tissues | L-carnitine & acylcarnitine | L-carnitine (162.11), acylcarnitine (204.12), acylcarnitine C3:0 (218.14), C4:0 (232.15), C5:0 (246.17), C6:0 (260.19) | B-oxidation; carnitine-dependent transport system | Demonstrate carnitine reprograming in breast cancer; relate CPT 1A, CPT 2, and CRAT to altered carnitine metabolism and distribution gradient | MALDI-MSI | |
| Esophageal Cancer: | Abbassi-Ghadi et al., 2020 (52) | esophageal adenocarcinoma and healthy esophageal epithelium tissue | glycerophospholipids | PG 36:4 (769.5025), PG 38:6 (793.5025), PG 40:8 (817.5025), PI 34:1 (835.5342), | De novo lipogenesis | Rapid categorization of premalignant tissues; provide possible ways for early diagnosis of the cancer and quick tumor margin detection | DESI-MSI |
| Sun et al., 2019 (45) | Esophageal squamous cell carcinoma tissues (ESCC) and surrounding non-cancerous tissues | Amino acids, uridine, polyamines, fatty acids | Uracil (111.0200), histamine (112.0870), glutamate (146.0459), uridine (243.0624), FA-22:4 (331.2624), PE 36:4 (72.5146), | Amino acid metabolism (proline and glutamine), uridine metabolism, fatty acid and polyamine biosynthesis; membrane synthesis, cellular signaling, and energy consumption | Identify metabolic enzymes that are possibly involved in carcinogenesis; provide a possible way of rapidly testing large numbers of metabolites without specific targets | AFADESI-MSI | |
| He et al., 2018 (46) | ESCC tissue and surrounding non-cancerous tissue | polyamines, nitrogenous base, nucleoside, glutamine, carnitines, and lipids | Aspartate (132.0296), Adenine (134.0468), spermidine (146.1650), glutamate (169.0584), inosine (267.0739), adenosine (302.0669) | Polyamine catabolism, glutamine metabolism, TCA cycle | Rapidly tell apart various classes of molecules with similar masses can be helpful in specifying fine intra-regional heterogeneity | AFADESI-MSI | |
| Zang et al., 2021 (53) | Human esophageal cancer cell line KYSE-30 spheroid, ESCC tissue and surrounding non-cancerous tissue | Amino acids, choline, fatty acids, creatine | Creatine (132.08), malic acid (133.01), glutamine (145.06), inosine (267.07), FA 20:3 (305.25), PG 38:4 (797.53), PI 38:3 (887.56), PI 38:4 (885.55) | Fatty acid synthesis, de novo synthesis of choline and ethanolamine, glutamine metabolism, TCA cycle | Enable detailed study of MCTS as a cancer model; expand future usage of MCTS combined with MALDI for biomarker discovery and in situ drug and metabolomic study | MALDI-MSI | |
| Glioblastoma: | Kampa et al., 2020 (54) | Glioblastoma tissue and surrounding non-cancerous tissue | Antioxidants, fatty acids, purine and pyrimidine metabolites, 2-HG, etc. | No specification of observed m/z
Arachidonic acid (20:4), adrenic acid (22:4), oleic acid (18:1), ADP, AMPUDP, UMP, uridine, lactate, glutamine, citrate, NAA |
Purine and pyrimidine metabolism, arachidonic acid synthesis, energy consumption (hydrolysis), TCA cycle | Distinguish glioblastoma subtypes; defining infiltrative tumor borders; possible use in examining therapeutic effects | MALDI-TOF-MSI |
| Randall et al., 2019 (55) | Glioblastoma xenograft tissue | ATP, Heme, acylcarnitine | 9-Hexadecenoylcarnitine (398.3265), palmitoylcarnitine (400.3422), myristoylcarnitine (410.2666), stearoylcarnitine (428.3734), ATP (508.0030), heme (616.1766), | Fatty acid metabolism, glycolysis; antioxidant and anti-apoptotic functions | Establish xenograft for glioblastoma therapeutic testing; understand relationship between drug efficiency and tumor metabolism | MALDI-FTICR-MSI | |
| Calligaris et al., 2013 (56) | Glioblastoma surgical samples that contain viable and necrotic tumor tissues | N/A | Molecules not specified. Ions with observed m/z of 279.0, 391.3, 544.5, 626.6, 650.6, 437.3, 491.3, 572.7 | N/A | Help in real-time surgical decision-making; determine tumor border; distinguishing viable from nonviable tumor tissues | DESI-MSI | |
| Lung Cancer: | Neumann et al., 2022 (57) | AC and SqCC tissues with tumor and stroma regions | Phospholipids, antioxidants, glutamine, 2HG | Taurine (124), [M + Cl]− ion of oxalic acid (125), 2HG (147), chloride adduct of glutamine (181), phosphatidylserine (502), phospholipid (742) | Lipogenesis, tricarboxylic acid cycle, 2HG metabolism | Distinguish tumor and stroma areas; classify ADC and SqCC subtypes for more accurate diagnosis; identify IDH mutant from wild-type cases | MALDI-MSI |
| Bensussan et al., 2020 (58) | AC and SqCC tissues and FNA samples | Glycerophospholipids | FA (20:4) (303.233), PG (34:1) (747.560), PG (36:2) (773.533), PI (38:4), (788.544), PI (34:1) (835.534), PS (36:1) (885.550) | N/A | Quick discrimination of normal vs. tumor tissues for diagnosis; classification of ADC and SqCC subtypes with tissues and FNA samples | DESI-MSI |