Urolithin / Warburg Cancer Research Results

Uro, Urolithin: Click to Expand ⟱
Features:
Urolithins are gut microbiota–derived dibenzopyran-6-one metabolites formed from ellagitannins → ellagic acid. They are the bioactive, systemically relevant forms responsible for most of the anticancer, mitochondrial, and signaling effects attributed to pomegranate and berry consumption.
Ellagic acid itself is largely confined to the gut lumen; urolithins are what reach circulation and tissues.

Urolithin A (UA), Most studied; mitophagy, anticancer, anti-inflammatory
Humans fall into urolithin metabotypes:
Metabotype	Description	            Approx. Population
A	        Produces UA (best profile)	~40%
B	        Produces UB ± UA	       ~25–30%
0	        Non-producer	                ~30%

ROS Modulation (Context-Dependent)
Cancer cells:
-Mild ROS ↑ or redox stress → apoptosis, growth arrest
Normal cells:
-ROS ↓, improved mitochondrial efficiency

This duality is why urolithins are less chemo-antagonistic than classic antioxidants.

Anticancer Signaling
↓ PI3K/AKT/mTOR
↓ Wnt/β-catenin
↓ NF-κB, STAT3
Cell-cycle arrest (G1/S)

Unlike sulforaphane or NAC, urolithins:
-Do not strongly upregulate NRF2 in cancer cells
-May normalize NRF2 signaling in normal cells
Direct Urolithin A Supplements: Bypass microbiome dependency

Urolithin A–type activity — Cancer vs Normal Cell Effects
Rank Pathway / Axis Cancer Cells Normal Cells Label Primary Interpretation Notes
1 Mitophagy / mitochondrial quality control (PINK1–Parkin axis) ↑ mitophagy → loss of mitochondrial reserve ↑ mitophagy → improved mitochondrial fitness Driver Mitochondrial pruning and quality enforcement Urolithins selectively stress cancer cells by removing dysfunctional mitochondria while rejuvenating normal-cell mitochondrial pools
2 Mitochondrial metabolism / bioenergetics ↓ metabolic flexibility; ↓ ATP resilience ↑ oxidative efficiency Driver Energy stress vs optimization Cancer cells are less able to compensate for enforced mitochondrial turnover
3 Reactive oxygen species (ROS) ↑ ROS (secondary to mitochondrial stress) ↓ ROS Secondary Metabolism-linked redox shift ROS changes arise from altered mitochondrial populations, not direct redox cycling
4 AMPK / mTOR nutrient-sensing axis ↑ AMPK; ↓ mTOR signaling ↑ AMPK (adaptive) Secondary Catabolic pressure and growth restraint Energy-sensing pathways reinforce growth suppression in metabolically stressed tumor cells
5 Cell cycle regulation ↓ proliferation / ↑ arrest ↔ spared Phenotypic Cytostatic growth limitation Growth inhibition reflects bioenergetic insufficiency rather than direct CDK inhibition
6 Inflammatory signaling (NF-κB / cytokines) ↓ pro-tumor inflammation ↓ inflammatory tone Secondary Anti-inflammatory modulation Reduced inflammation contributes to chemopreventive and microenvironmental effects
7 NRF2 antioxidant response ↑ NRF2 (adaptive, secondary) ↑ NRF2 (protective) Adaptive Redox homeostasis reinforcement NRF2 activation reflects improved mitochondrial quality and reduced oxidative burden rather than a cytotoxic mechanism
8 Apoptosis sensitivity ↑ sensitivity to apoptosis (stress-context dependent) ↓ apoptosis Phenotypic Threshold-dependent cell death Apoptosis occurs when mitochondrial and energetic stress exceed adaptive capacity


Warburg, Warburg Effect: Click to Expand ⟱
Source:
Type: effect

The Warburg effect (aerobic glycolysis) is a metabolic phenotype where many cancer cells use high glycolytic flux and lactate production even when oxygen is available. Tumors often contain hypoxic regions that further drive glycolysis, but Warburg metabolism can also occur under normoxic conditions (“pseudo-hypoxia”) via oncogenic signaling and metabolic rewiring.

Hypoxia-inducible factor 1 alpha (HIF-1α) is one important driver in hypoxic tumor regions. HIF-1α upregulates glycolytic genes (e.g., GLUT1, HK2, LDHA) and promotes reduced mitochondrial pyruvate oxidation in part through induction of PDK (which inhibits PDH), shifting carbon toward lactate.

Warburg effect (GLUT1, LDHA, HK2, and PKM2).
Classic HIF-Warburg axis: PDK1 and MCT4 (SLC16A3) (pyruvate gate + lactate export).

Here are some of the key pathways and potential targets:

Note: use database Filter to find inhibitors: Ex pick target HIF1α, and effect direction ↓

1.Glycolysis Inhibitors:(2-DG, 3-BP)
- HK2 Inhibitors: such as 2-deoxyglucose, can reduce glycolysis
-PFK1 Inhibitors: such as PFK-158, can reduce glycolysis
-PFKFB Inhibitors:
- PKM2 Inhibitors: (Shikonin)
-Can reduce glycolysis
- LDH Inhibitors: (Gossypol, FX11)
-Reducing the conversion of pyruvate to lactate.
-Inhibiting the production of ATP and NADH.
- GLUT1 Inhibitors: (phloretin, WZB117)
-A key transporter involved in glucose uptake.
-GLUT3 Inhibitors:
- PDK1 Inhibitors: (dichloroacetate)
- A key enzyme involved in the regulation of glycolysis. PDK inhibitors (e.g., DCA) activate PDH and shift pyruvate into TCA/OXPHOS, reducing lactate pressure.

2.Pentose phosphate pathway:
- G6PD Inhibitors: can reduce the pentose phosphate pathway

3.Hypoxia-inducible factor 1 alpha (HIF1α) pathway:
- HIF1α inhibitors: (PX-478,Shikonin)
-Reduce expression of glycolytic genes and inhibit cancer cell growth.

4.AMP-activated protein kinase (AMPK) pathway:
-AMPK activators: (metformin,AICAR,berberine)
-Can increase AMPK activity and inhibit cancer cell growth.

5.mTOR pathway:
- mTOR inhibitors:(rapamycin,everolimus)
-Can reduce mTOR activity and inhibit cancer cell growth.

Warburg Targeting Matrix (Cancer Metabolism)

Node What It Does (Warburg role) Representative Inhibitors / Modulators Mechanism Snapshot Typical Tumor Effects Best-Fit Tumor Context Common Constraints / Gotchas TSF Combination Logic
GLUT (glucose uptake)
GLUT1 (SLC2A1) focus		 Controls glucose entry; sets the upper bound on glycolytic flux. Research/repurposing: WZB117 (GLUT1), BAY-876 (GLUT1), STF-31 (GLUT1 tool), Fasentin (GLUT), Phloretin (broad, weak)
Dietary/indirect: some polyphenols reported to lower GLUT1 expression (context) 		Blocks glucose transport or reduces GLUT1 expression → less substrate for glycolysis & PPP. ATP stress (in highly glycolytic tumors), lactate ↓, growth slowdown; can sensitize to stressors. High-GLUT1 tumors; hypoxic / glycolysis-addicted phenotypes. Systemic glucose handling and glucose-dependent tissues; tumor compensation via alternate fuels. P, R Pairs with ROS/ETC stressors or LDH/MCT blockade; beware compensatory glutaminolysis/fatty acid oxidation.
Hexokinase (HK2)
first committed glycolysis step		 Traps glucose as G-6-P; HK2 often upregulated and mitochondria-associated in tumors. Clinical/adjunct interest: 2-Deoxyglucose (2-DG; glycolysis + glycosylation stress)
Research: Lonidamine-class glycolysis axis drugs (not “pure HK2”), 3-bromopyruvate (hazardous research agent; not for casual use) 		Competitive substrate mimic (2-DG) → 2-DG-6P accumulation; HK flux ↓; ER glycosylation stress ↑. ATP ↓, AMPK ↑, ER stress/UPR ↑, autophagy ↑, apoptosis (context); radiosensitization reported. Highly glycolytic tumors; tumors with strong HK2 dependence; hypoxic cores. Normal glucose-dependent tissues; ER-stress toxicities; dosing/tolerability limits in practice. P, R, G Pairs with radiation, pro-oxidant stress, or MCT/LDH blockade; watch systemic glucose effects.
LDH (LDHA/LDHB)
pyruvate ⇄ lactate		 Regenerates NAD+ to sustain glycolysis; LDHA supports lactate production and acidification. Tier A direct inhibitors: FX11, (R)-GNE-140, NCI-006, Oxamate, Galloflavin, Gossypol
Tier B indirect: polyphenols (often lactate/LDH expression ↓ rather than catalytic inhibition) 		Blocks LDH catalysis → NAD+ recycling ↓ → glycolysis throttles; pyruvate handling shifts; redox pressure ↑. Lactate ↓, glycolytic flux ↓, oxidative stress ↑ (often secondary), growth inhibition; immune microenvironment may improve if lactate decreases. LDHA-high tumors; lactate-driven immunosuppression; glycolysis-addicted phenotypes. Metabolic plasticity: tumors switch fuels; some LDH inhibitors have PK liabilities; “LDH release” ≠ LDH inhibition. R, G Pairs with MCT inhibition (trap lactate), NAD+ axis inhibitors, immune therapy (lactate suppression logic), and OXPHOS stressors (context).
MCT (lactate transport)
MCT1 (SLC16A1), MCT4 (SLC16A3)		 Exports lactate + H+ (acidifies TME); enables lactate shuttling between tumor subclones. Clinical-stage: AZD3965 (MCT1 inhibitor; clinical trials)
Research: AR-C155858 (MCT1/2), Syrosingopine (MCT1/4; repurposed), Lonidamine (MCT + MPC axis) 		Blocks lactate export/import → intracellular acid stress ↑ (in glycolytic cells) and lactate shuttling ↓. Acid stress, growth inhibition; may improve immune function by reducing lactate/acidic suppression (context). MCT1-high tumors; oxidative “lactate-using” tumor fractions; tumors with lactate shuttling. MCT4-driven export can bypass MCT1-only inhibitors; hypoxia upregulates MCT4; need target matching. P, R Pairs strongly with LDH inhibitors (cut production + block export), and with immune therapy rationale (lactate/acid microenvironment).
PDK (PDK1-4)
PDH gatekeeper		 PDK inhibits PDH → keeps pyruvate out of mitochondria; supports Warburg by favoring lactate. Prototype: Dichloroacetate (DCA; pan-PDK inhibitor “classic”)
Research: AZD7545 (PDK2 inhibitor; tool), newer PDK inhibitor series (research) 		Inhibits PDK → PDH active ↑ → pyruvate into TCA/OXPHOS ↑; lactate pressure ↓. Warburg reversal pressure (context), lactate ↓, mitochondrial flux ↑; can increase ROS in some settings (secondary). PDK-high tumors; tumors with suppressed PDH flux; “glycolysis locked” metabolic phenotype. Requires functional mitochondrial capacity; hypoxia can limit OXPHOS shift; effect is often modulatory rather than directly cytotoxic. R, G Pairs with therapies that exploit mitochondrial dependence or redox stress; can complement LDH/MCT strategies by reducing lactate drive.

Time-Scale Flag (TSF): P / R / G

  • P: 0–30 min (direct transport/enzyme flux effects begin)
  • R: 30 min–3 hr (acute ATP/NAD+/acid stress and signaling changes)
  • G: >3 hr (gene adaptation, phenotype outcomes, immune/TME effects)
Scientific Papers found: Click to Expand⟱
4846- Uro,    Urolithin A exerts anti-tumor effects on gastric cancer via activating autophagy-Hippo axis and modulating the gut microbiota
- in-vivo, GC, NA
TumCG↓, Hippo↑, Warburg↓, Apoptosis↑, GutMicro↑,

Showing Research Papers: 1 to 1 of 1

* indicates research on normal cells as opposed to diseased cells
Total Research Paper Matches: 1

Pathway results for Effect on Cancer / Diseased Cells:


Core Metabolism/Glycolysis ⓘ

Warburg↓, 1,  

Cell Death ⓘ

Apoptosis↑, 1,   Hippo↑, 1,  

Proliferation, Differentiation & Cell State ⓘ

TumCG↓, 1,  

Clinical Biomarkers ⓘ

GutMicro↑, 1,  
Total Targets: 5

Pathway results for Effect on Normal Cells:


Total Targets: 0

Scientific Paper Hit Count for: Warburg, Warburg Effect
Query results interpretion may depend on "conditions" listed in the research papers.
Such Conditions may include : 
  -low or high Dose
  -format for product, such as nano of lipid formations
  -different cell line effects
  -synergies with other products 
  -if effect was for normal or cancerous cells

Filter Conditions: Pro/AntiFlg:%  IllCat:%  CanType:%  Cells:%  prod#:383  Target#:947  State#:%  Dir#:1
  wNotes=0  sortOrder:rid,rpid

 

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