Database Query Results : Magnetic Fields, , Warburg

MF, Magnetic Fields: Click to Expand ⟱
Features: Therapy
Magnetic Fields can be Static, or pulsed. The most common therapy is a pulsed magnetic field in the uT or mT range.
The main pathways affected are:
Calcium Signaling: -influence the activity of voltage-gated calcium channels.
Oxidative Stress and Reactive Oxygen Species (ROS) Pathways
Heat Shock Proteins (HSPs) and Cellular Stress Responses
Cell Proliferation and Growth Signaling: MAPK/ERK pathway.
Gene Expression and Epigenetic Modifications: NF-κB
Angiogenesis Pathways: VEGF (improving VEGF for normal cells)
PEMF was found to have a 2-fold increase in drug uptake compared to traditional electrochemotherapy in rat melanoma models

Pathways:
- most reports have ROS production increasing in cancer cells , while decreasing in normal cells.
- ROS↑ related: MMP↓(ΔΨm), ER Stress↑, UPR↑, GRP78↑, Ca+2↑, Cyt‑c↑, Caspases↑, DNA damage↑, cl-PARP↑, HSP↓, Prx,
- Raises AntiOxidant defense in Normal Cells: ROS↓, NRF2↑, SOD↑, GSH↑, Catalase↑,
- lowers Inflammation : NF-kB↓, COX2↓, Pro-Inflammatory Cytokines : NLRP3↓, IL-1β↓, TNF-α↓, IL-6↓, IL-8↓
- inhibit Growth/Metastases : TumMeta↓, TumCG↓, VEGF↓(mostly regulated up in normal cells),
- cause Cell cycle arrest : TumCCA↑,
- inhibits Migration/Invasion : TumCMig↓, TumCI↓, TNF-α↓,
- inhibits glycolysis /Warburg Effect and ATP depletion : HIF-1α↓, PKM2↓, GLUT1↓, LDH↓, HK2↓, PFKs↓, PDKs↓, ECAR↓, OXPHOS↓, GRP78↑, Glucose↓, GlucoseCon↓
- inhibits angiogenesis↓ : VEGF↓, HIF-1α↓, Notch↓, FGF↓, PDGF↓, EGFR↓, Integrins↓,
- Others: PI3K↓, AKT↓, STAT↓, Wnt↓, β-catenin↓, ERK↓, JNK, - SREBP (related to cholesterol).
- Synergies: chemo-sensitization, chemoProtective, cytoProtective, RadioSensitizer, RadioProtective, Others(review target notes), Neuroprotective, Hepatoprotective, CardioProtective,

- Selectivity: Cancer Cells vs Normal Cells

Non-Static Magnetic Fields (AC / Pulsed / Oscillating MF)
Rank Pathway / Axis Cancer Cells Normal Cells TSF Primary Effect Notes / Interpretation
1 Reactive oxygen species (ROS) ↑ ROS (P→R); often sustained (G) ↑ ROS (P); ↔/↓ net ROS (R→G) P, R, G Upstream redox perturbation MF perturbs electron/radical dynamics: normal cells often adapt (ROS setpoint ↓), cancer cells less so
2 NRF2 antioxidant response ↔ / insufficient NRF2 induction (R→G) ↑ NRF2 activation (R→G) R, G Adaptive redox defense Explains mixed ROS direction in normal cells (initial ↑ then adaptive ↓)
3 Glutathione (GSH) homeostasis ↓ GSH (R→G) ↔ or transient ↓ (R) with recovery (G) R, G Redox buffering capacity GSH depletion reflects sustained oxidative load; recovery indicates successful adaptation
4 Superoxide dismutase (SOD) / antioxidant enzymes ↔ or inadequate enzyme upshift (G) ↑ SOD/GPx/CAT capacity (G) G Longer-term antioxidant remodeling Often the “endpoint” readout that correlates with ROS-normalization in normal tissue
5 Mitochondrial ETC / respiration ↓ ETC efficiency; ↑ electron leak (P→R) ↔ mild, reversible ETC perturbation (P→R) P, R Bioenergetic destabilization ETC perturbation is a mechanistic bridge between MF exposure and ROS/ΔΨm changes
6 Mitochondrial membrane potential (ΔΨm / MMP) ↓ ΔΨm (R); may progress (G) ↔ preserved or reversible dip (R) R, G Mitochondrial dysfunction thresholding ΔΨm loss typically follows ROS/ETC disruption rather than preceding it
7 Ca²⁺ signaling (VGCC / ER–mitochondria Ca²⁺ flux) ↑ dysregulated Ca²⁺ influx/transfer (P→R); overload may persist (G) ↑ transient Ca²⁺ signaling (P); homeostasis restored (R→G) P, R, G Stress signal amplification Ca²⁺ dysregulation links ROS/ETC perturbation to ER stress and mitochondrial dysfunction (amplifies ΔΨm loss and UPR commitment)
8 Mitochondrial permeability transition pore (MPTP) ↑ MPTP opening propensity (R); sustained opening possible (G) ↔ transient or closed (R→G) P, R, G Commitment point for mitochondrial failure MPTP opening integrates ROS, Ca²⁺ overload, and ΔΨm loss; acts as a threshold event converting reversible stress into irreversible mitochondrial dysfunction
9 ER stress / UPR ↑ ER stress (R); CHOP-commitment possible (G) ↑ adaptive UPR (R); resolves (G) R, G Proteostasis stress Often downstream of ROS + Ca²⁺ handling perturbations
10 DNA damage (oxidative) ↑ damage markers (R→G) ↔ or repaired (G) R, G Checkpoint pressure Generally secondary to ROS; interpret as stress consequence not “direct genotoxicity”
11 LDH / glycolytic flux ↓ glycolytic performance (R→G) ↔ flexible substrate switching (R→G) R, G Metabolic vulnerability Redox imbalance can destabilize high-rate glycolysis in cancer-biased contexts
12 Thioredoxin system (Trx / TrxR) ↓ functional reserve / overload (R→G) ↔ preserved capacity (G) R, G Parallel antioxidant system stress Useful when GSH-only does not explain redox phenotype
Time-Scale Flag: TSF = P / R / G
  P: 0–30 min (physical / electron / radical effects)
  R: 30 min–3 hr (redox signaling & stress response)
  G: >3 hr (gene-regulatory adaptation)
MPTP: opening represents a mitochondrial commitment event integrating ROS and Ca²⁺ stress; sustained opening indicates irreversible bioenergetic failure.


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⟱
2245- MF,    Quantum based effects of therapeutic nuclear magnetic resonance persistently reduce glycolysis
- in-vitro, Nor, NIH-3T3
Warburg↓, tNMR might have the potential to counteract the Warburg effect known from many cancer cells which are prone to glycolysis even under aerobic conditions.
Hif1a↓, combined treatment of tNMR and hypoxia (tNMR hypoxia) led to significantly altered HIF-1α protein levels, namely a further overall reduction in protein amounts
*Hif1a∅, Under normoxic conditions we did not find significant differences in Hif-1α mRNA and protein expression
Glycolysis↓, hypoxic tNMR treatment, driving cellular metabolism to a reduced glycolysis while mitochondrial respiration is kept constant even during reoxygenation.
*lactateProd↓, tNMR reduces lactate production and decreases cellular ADP levels under normoxic conditions
*ADP:ATP↓,
Pyruv↓, Intracellular pyruvate, which was as well decreased in hypoxic control cells, appeared to be further decreased after tNMR under hypoxia
ADP:ATP↓, tNMR under hypoxia further decreased the hypoxia induced decrease of the intracellular ADP/ATP ratio
*PPP↓, pentose phosphate pathway (PPP) is throttled after tNMR treatment, while cell proliferation is enhanced
*mt-ROS↑, tNMR under hypoxia increases mitochondrial and extracellular, but reduces cytosolic ROS
*ROS↓, but reduces cytosolic ROS
RPM↑, Because EMFs are known to affect ROS levels via the radical pair mechanism (RPM)
*ECAR↓, tNMR under normoxic conditions reduces the extracellular acidification rate (ECAR)


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

Pathway results for Effect on Cancer / Diseased Cells:


Redox & Oxidative Stress

RPM↑, 1,  

Mitochondria & Bioenergetics

ADP:ATP↓, 1,  

Core Metabolism/Glycolysis

Glycolysis↓, 1,   Pyruv↓, 1,   Warburg↓, 1,  

Angiogenesis & Vasculature

Hif1a↓, 1,  
Total Targets: 6

Pathway results for Effect on Normal Cells:


Redox & Oxidative Stress

ROS↓, 1,   mt-ROS↑, 1,  

Mitochondria & Bioenergetics

ADP:ATP↓, 1,  

Core Metabolism/Glycolysis

ECAR↓, 1,   lactateProd↓, 1,   PPP↓, 1,  

Angiogenesis & Vasculature

Hif1a∅, 1,  
Total Targets: 7

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#:172  Target#:947  State#:%  Dir#:%
wNotes=on sortOrder:rid,rpid

 

Home Page