Multi-Omic Approaches to Breast Cancer Metabolic Phenotyping: Applications in Diagnosis, Prognosis, and the Development of Novel Treatments
Abstract
:Simple Summary
Abstract
1. Introduction
2. BC Diagnosis
2.1. BC Metabolic Markers
2.2. BC Metabolic Subtyping
3. Multi-Omics Studies of BC Prognosis
4. Multi-Omics Studies and Novel BC Treatment Strategies
5. Future Perspectives and Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Acknowledgments
Conflicts of Interest
References
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Study | Sample | Omics Data | Major Findings * |
---|---|---|---|
Iqbal et al. [59] | Tissue | M+T | ↑ glucose-6-phosphate, 3-phosphoglycerate, and fructose-6-phosphate ↑ CBX2 and ↓ CBX7 |
Hilvo et al. [60] | Tissue | L+T | ↑ ACACA, FASN, INSIG1, and SREBP1 ↑ phospholipids, sphingomyelins, and ceramides |
Luo et al. [61] | Plasma + Tissue | M+T | ↓ guanine and hypoxanthine ↓ PNP and HPRT1 |
Huang et al. [57] | Plasma + Serum + Tissue | M+T | ↑ hypotaurine, glutamate and ↓ oxoglutarate ↑ GAD1, CSAD and ↓ GPT, GPT2, GLUD1 |
Dowling et al. [62] | Serum | M+P | ↑ glutamate, 12-hydroxyeicosatetraenoic acid, andβ-hydroxybutyrate ↑ coagulation factor V and matrix metalloproteinase 1 |
Study | Sample | Omics Data | Group Comparison | Major Findings * |
---|---|---|---|---|
Moestue et al. [63] | Tissue | M+T | Basal- vs. luminal-like | ↑ GPC/PCho and glycine ↓ CHKA/B ↑ PLA2G4A, PLB1, CHDH and SARDH |
Grinde et al. [64] | Tissue | M+T | Basal- vs. luminal-like | ↓ PCho/GPC |
Putluri et al. [65] | Cell lines + Tissue | M+T | Basal- vs. luminal-like | ↓ phenylalanine, tryptophan, tyrosine, BCAA, lauric acid and oleic acid ↑ guanine, adenine, thymine, uracil, xanthine, and guanosine |
Mahendralingam et al. [66] | Tissue | P+T | Basal- vs. luminal-like | ↑ glycolysis (PFKM, ALDOC, GAPDH, and PKM) and ↓ OXPHOS |
Tang et al. [67] | Tissue | G+M+T | ER+ vs. ER- | ↓ carnitine derivates and short- and medium-chain fatty acids ↑ long-chain fatty acids and monoacylglycerols |
Barupal et al. [68] | Tissue | M+P+T | ER+ vs. ER- | ↑ R5P, adenine, guanosine, guanine, xanthine, and hypoxanthine and β-alanine ↑ G6PD, PGD, TKT, PGM1, RPIA, DERA |
Hilvo et al. [60] | Tissue | L+T | ER+ vs. ER- | ↑ palmitate and myristic acid |
Haukaas et al. [48] | Tissue | M+T+P | Primary BC subtyping | MC1: ↑ GPC, PCho ↓ acetate and glutamine ↑ CHKA ↓ ALDH and GLS MC2: ↑ glucose MC3: ↑ lactate and alanine |
Gong et al. [69] | Tissue | M+T | TNBC subtyping | MPS1: ↑ myristic, palmitoleic, oleic, and arachidonic acid ↑ ACACA, HMGCR, FASN, SCD MPS2: ↑ glucose 1-phosphate, dihydroxyacetone phosphate, lactate and adenosine 3′ 5′ -diphosphate and ↓ glucose ↑ PFKP, ENO2, TYMS, CTPS1, SLC2A1, SLC16A1 |
Study | Sample | Omics Data | Major Findings * |
---|---|---|---|
Putluri et al. [65] | Cell lines + Tissue | M+T | ↑ RRM2 (pyrimidine metabolism) |
Luo et al. [61] | Blood + Tissue | M+T | ↑ RRM2 (pyrimidine metabolism) and ↓ AMPD1 (de novo purine metabolism) |
Iqbal et al. [59] | Tissue | M+T | ↑ CBX2 and ↓ CBX7 (glycolysis) |
Camarda et al. [102] | Cell lines + Tissue | M+T | ↓ ACC2 (FAO) |
Kang et al. [116] | Cell lines | L+T | ↓ ELOVL2 (lipid synthesis) |
Terunuma et al. [107] | Tissue | M+T+P+E | ↑ 2HG, SAM and SAH ↑ IDH2 (glutamine metabolism) |
Budczies et al. [106] | Tissue | M+T | ↓ ABAT, ↑ β-alanine (β-alanine metabolism) |
Study | Omics Data | BC Subtype | Potential Targets |
---|---|---|---|
Iqbal et al. [59] | M+T | TNBC and luminal-like | CBX2 and CBX7 |
Gong et al. [69] | M+T | TNBC | FASN and LDH |
Mahendralingam et al. [66] | P+T | Basal- and luminal-like | GLUT1, HK, LDH, and PDC |
Putluri et al. [65] | M+T | Basal- and luminal-like | RRM2 |
Terunuma et al. [107] | M+T+P+E | TNBC and basal-like | ADHFE1 |
Hilvo et al. [60] | L+T | TNBC, luminal- and basal-like | ACACA, ELOVL1, FASN, INSIG1, SCAP, SCD and THRSP |
Kang et al. [116] | L+T | Luminal-like | ELOVL2 |
Camarda et al. [102] | M+T | TNBC and HER2 + | CPT1 and CPT2 |
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Gómez-Cebrián, N.; Domingo-Ortí, I.; Poveda, J.L.; Vicent, M.J.; Puchades-Carrasco, L.; Pineda-Lucena, A. Multi-Omic Approaches to Breast Cancer Metabolic Phenotyping: Applications in Diagnosis, Prognosis, and the Development of Novel Treatments. Cancers 2021, 13, 4544. https://doi.org/10.3390/cancers13184544
Gómez-Cebrián N, Domingo-Ortí I, Poveda JL, Vicent MJ, Puchades-Carrasco L, Pineda-Lucena A. Multi-Omic Approaches to Breast Cancer Metabolic Phenotyping: Applications in Diagnosis, Prognosis, and the Development of Novel Treatments. Cancers. 2021; 13(18):4544. https://doi.org/10.3390/cancers13184544
Chicago/Turabian StyleGómez-Cebrián, Nuria, Inés Domingo-Ortí, José Luis Poveda, María J. Vicent, Leonor Puchades-Carrasco, and Antonio Pineda-Lucena. 2021. "Multi-Omic Approaches to Breast Cancer Metabolic Phenotyping: Applications in Diagnosis, Prognosis, and the Development of Novel Treatments" Cancers 13, no. 18: 4544. https://doi.org/10.3390/cancers13184544