Table 4.

Summary of metabolomic-based multi-omic integration studies for PCa within the last decade (2011–2021) ^1,2.

Reference	Experimental Condition	Sample/ n Samples	Analytical Tool	Altered Metabolites (+/−)	dysregulated Metabolic Pathways	Combined Modality/Main Findings
Kiebish et al., 2020 [100]	PCa prognostic markers identification	382 pre-surgical serum samples from PCa patients 267 = training set (validation) 115 = testing set (validation)	MS-MS HILC-MS LC-MS GC-TOF-MS	1-methyladenosine (+)	Cholesterol metabolism	Proteomics + Lipidomics + Metabolomics: Linear regression + Bayesian method + multi-omics → Tenascin C (TNC) and Apolipoprotein A1V (Apo-AIV), 1-Methyladenosine (1-MA), and phosphatidic acid (PA) 18:0–22:0, AUC = 0.78 (OR (95% CI) = 6.56 (2.98–14.40), P < 0.05) → high differentiating ability w/ and w/o BCR.
Oberhuber et al., 2020 [241]	Signal transducer and activator of transcription 3 (STAT3) expression	84 = PCa from prostatectomy patients	LC-MS-MS LC-HRMS	Pyruvate dehydrogenase kinase 4 (+)	Oxidative phosphorylation TCA cycle Pyruvate oxidation	Transcriptomics + Proteomics + Metabolomics: High STAT3 expression → OXPHOS downregulated (Transcriptomics). High STAT3 expression → TCA cycle/OXPHOS downregulated (Proteomics). High PDK4 expression → inhibited PCa tumor growth.
Itkonen et al., 2019 [242]	Cyclin-dependent kinase 9 (CDK9) inhibition	LNCaP PC3	Seahorse metabolic flux analysis	Acyl-carnitines (+)	Oxidative phosphorylation ATP synthesis AMP-activated protein kinase (AMPK) phosphorylation	Lipidomics + Fluxomics + Metabolomics: CDK9 inhibition → acute metabolic stress in PCa cells. CDK9 inhibition → downregulated oxidative phosphorylation, ATP depletion, and sustained AMPK phosphorylation. CDK9 inhibition → increased levels of acyl-carnitines
Gao et al., 2019 [243]	LASCPC-01 and LNCaP differentiation	LASCPC-01 LNCaP	GC-TOF-MS LC-MS	25 metabolites altered from control Carnitine (−)	Glycolysis One-carbon metabolism	Transcriptomics + Lipidomics + Metabolomics: 62 genes upregulated in LSCPC-01, 112 genes upregulated in LNCaP (Transcriptomics). 25 genes significantly altered from control (Lipidomics + Metabolomics). LASCPC-01: high glycolytic rate, low-level triglycerides. LNCaP: high 1C metabolism rate, low carnitine.
Kregel et al., 2019 [244]	Bromodomain/ extraterminal (BET)- containing proteins (BRD2/3/4) inhibitor analysis	22RV1 LNCaP VCaP PC3 DU145	LC-MS	Polyunsaturated fatty acids (+) Thioredoxin-interacting protein Interferon regulatory transcription factor (−)	Cyclin-dependent kinase 9 inhibition CDK9 hyperphosporylation Polycomb repressive complex 2 activity	Proteomics + Lipidomics + Metabolomics: BET inhibitors: affected AR+ PCa (22RV1, LNCaP, VCaP) more than AR- PCa (PC3, DU145). BET inhibitors → disrupted AR and MYC signaling at concentrations: (BET) < (BET inhibitors) (Proteomics).
Zadra et al., 2019 [245]	Fatty acid synthase (FASN) suppression via IPI-9119	LNCaP 22RV1 HeK293T RWPE-1	UPLC-MS-MS LC-MS GC-MS 14C-labeling	91 of the 418 metabolites modulated Malonyl-coA carnitine (+) Carnitine palmitoyltransferase 1 (−)	De novo fatty acid synthesis and neutral lipid accumulation ER stress response signaling Amino acid synthesis TCA cycle Carbohydrate metabolism Nucleotide metabolism	Lipidomics + Metabolomics: IPI-9119, a selective inhibitor of FASN altered the PCa metabolome by inhibiting fatty acid oxidation via accumulating malonyl-coA carnitine. Malonyl-coA carnitine accumulation → inhibited carnitine palmitoyltransferase 1 → FAO suppression. FA synthesis suppression → inhibited AR and AR-V7 expression. IPI-9119 → induced ER stress, inhibited AR/AR-V7 translation.
Murphy et al., 2018 [246]	PCa biomarker identification	158 = PCa prostatectomy patients	LC-MS-MS Statistical modeling	13 glycosylation metabolites (+) including tetraantennary tetrasialylated structures and A3G3S3	Glycosylation	Genomics + Transcriptomics + Proteomics +Lipidomics + Metabolomics: Integration of data across 5 omic platforms from tissue and serum → single AUC value that better differentiates aggressive PCa from the indolent type compared to AUCs obtained from single omics.
Hansen et al., 2016 [247]	TMPRSS2-ERG expression	129 = PCa samples from 41 patients 40 = PCa samples from 40 patients	HR-MAS-MRSI	Out of 23 metabolites, citrate and spermine (−)	TCA cycle Nucleic acid synthesis Citrate metabolism Polyamines metabolism	Transcriptomics + Metabolomics: ERGhigh = low citrate and spermine concentrations → increased PCa aggressiveness (Metabolomics). Metabolomic alterations for ERGhigh vs. ERGlow → more pronounced in low Gleason samples → implication: potential risk stratification tool.

¹ The list is non-exhaustive, tabulated as of the writing of this review article. ² Total of 82 queries trimmed down to 8 metabolomic-based integrated multi-omic PCa studies.