Database Query Results : Ashwagandha(Withaferin A), , Warburg

Ash, Ashwagandha(Withaferin A): Click to Expand ⟱
Features:

Ashwagandha (Withaferin A) — Withaferin A (WA; WFA) is a bioactive steroidal lactone (a “withanolide”) found in Withania somnifera (ashwagandha/Indian ginseng), with most translational oncology discussion centered on WA as a small-molecule electrophile rather than the whole-herb supplement. It is best classified as a natural-product small molecule (steroidal lactone/withanolide) with pleiotropic proteostasis, cytoskeletal, redox-stress, and inflammatory signaling effects; in supplements, WA exposure depends strongly on extract standardization (root vs leaf, % withanolides) and formulation.

Primary mechanisms (ranked):

  1. Hsp90-axis disruption (incl. client protein destabilization) leading to proteostasis stress and multi-client oncoprotein depletion
  2. Covalent targeting of intermediate filaments (notably vimentin) with downstream effects on adhesion/migration, EMT programs, and angiogenic endothelium
  3. Pro-oxidative stress signaling in cancer cells with mitochondrial dysfunction, ER stress/UPR engagement, and apoptosis execution
  4. Inflammation and survival signaling suppression (notably NF-κB-centric programs; context-dependent immune modulation)
  5. Contextual transcriptional/epigenetic modulation (e.g., HDAC/DNMT-related signals) contributing to anti-proliferative phenotypes
  6. Metabolic stress signaling (glycolysis/HIF-1α/ATP depletion) as a secondary vulnerability in susceptible models

Bioavailability / PK relevance: WA shows measurable systemic exposure in animals (reported oral bioavailability in rats), but PK is variable across species, doses, and extract matrices; human exposure data exist from a phase I osteosarcoma study and from healthy-volunteer PK work on standardized Withania extracts measuring circulating withanolides (including WA). WA is lipophilic and subject to first-pass metabolism; typical pharmacodynamic in-vitro micromolar concentrations may exceed achievable unbound plasma levels depending on formulation and dosing.

In-vitro vs systemic exposure relevance: Many mechanistic cancer studies use ~1–10 µM WA; translation requires caution because free (unbound) systemic concentrations and tumor penetration are not well-constrained in humans, and whole-extract products can have low/variable WA content (model- and formulation-dependent).

Clinical evidence status: Limited human oncology evidence: a phase I study in advanced high-grade osteosarcoma reported feasibility/safety and proposed a daily dose level; an active clinical trial evaluates an ashwagandha/withaferin-A strategy with liposomal doxorubicin in recurrent ovarian cancer. Most anticancer support remains preclinical, while non-oncology human data for ashwagandha primarily address stress/sleep and are not evidence of anticancer efficacy.

The main active constituents of Ashwagandha leaves are alkaloids and steroidal lactones (commonly known as Withanolides).
-The main constituents of ashwagandha are withanolides such as withaferin A, alkaloids, steroidal lactones, tropine, and cuscohygrine.
Ashwagandha is an herb that may reduce stress, anxiety, and insomnia.
*-Ashwagandha is often characterized as an antioxidant.
-Some studies suggest that while ashwagandha may protect normal cells from oxidative damage, it can simultaneously stress cancer cells by tipping their redox balance toward cytotoxicity.
Pathways:
-Induction of Apoptosis and ROS Generation
-Hsp90 Inhibition and Proteasomal Degradation

Cell culture studies vary widely, typically ranging from low micromolar (e.g., 1–10 µM).
In animal models (commonly mice), Withaferin A has been administered in doses ranging from approximately 2 to 10 mg/kg body weight.
- General wellness, Ashwagandha supplements are sometimes taken in doses ranging from 300 mg to 600 mg of an extract (often standardized to contain a certain percentage of withanolides) once or twice daily.
- 400mg of WS extract was given 3X/day to schizophrenia patients. report#2001.
- Ashwagandha Pure 400mg/capsule is available from mcsformulas.com.

-Note half-life 4-6 hrs?.
BioAv
Pathways:
- well-recognized for promoting ROS in cancer cells, while no effect(or reduction) on normal cells.
- ROS↑ related: MMP↓(ΔΨm), ER Stress↑, UPR↑, GRP78↑, Cyt‑c↑, Caspases↑, DNA damage↑, cl-PARP↑, HSP↓, Prx,
- Confusing results about Lowering AntiOxidant defense in Cancer Cells: NRF2↓, TrxR↓**, SOD↓, GSH↓ Catalase↓ HO1↓ GPx↓
- Raises AntiOxidant defense in Normal Cells: ROS↓, NRF2↑, SOD↑, GSH↑, Catalase↑,
- lowers Inflammation : NF-kB↓, COX2↓, p38↓, Pro-Inflammatory Cytokines : NLRP3↓, IL-1β↓, TNF-α↓, IL-6↓, IL-8↓
- inhibit Growth/Metastases : TumMeta↓, TumCG↓, EMT↓, MMPs↓, MMP2↓, MMP9↓, TIMP2, uPA↓, VEGF↓, ROCK1↓, NF-κB↓, CXCR4↓, SDF1↓, TGF-β↓, α-SMA↓, ERK↓
- reactivate genes thereby inhibiting cancer cell growth : HDAC↓(combined with sulfor), DNMT1↓, DNMT3A↓, P53↑, HSP↓, Sp proteins↓, TET↑
- cause Cell cycle arrest : TumCCA↑, cyclin E↓, CDK2↓, CDK4↓,
- inhibits Migration/Invasion : TumCMig↓, TumCI↓, TNF-α↓, ERK↓, EMT↓, TOP1↓,
- inhibits glycolysis /Warburg Effect and ATP depletion : HIF-1α↓, PKM2↓, cMyc↓, GLUT1↓, LDH↓, LDHA↓, HK2↓, OXPHOS↓, GRP78↑, GlucoseCon↓
- inhibits angiogenesis↓ : VEGF↓, HIF-1α↓, Notch↓, PDGF↓, EGFR↓, Integrins↓,
- inhibits Cancer Stem Cells : CSC↓, β-catenin↓, sox2↓,
- Others: PI3K↓, AKT↓, JAK↓, STAT↓, Wnt↓, β-catenin↓, AMPK, α↓, ERK↓, JNK,
- Synergies: chemo-sensitization, chemoProtective, RadioSensitizer, RadioProtective, Others(review target notes), Neuroprotective, Cognitive, Renoprotection, Hepatoprotective, CardioProtective,

- Selectivity: Cancer Cells vs Normal Cells

Mechanistic pathway map for Ashwagandha (Withaferin A) in cancer biology

Rank Pathway / Axis Cancer Cells Normal Cells TSF Primary Effect Notes / Interpretation
1 Hsp90 proteostasis axis Hsp90 functional inhibition → client proteins ↓ (Akt/EGFR/HER2/Raf/Cdk etc.) → growth/survival signaling ↓ Stress-response engagement possible; tolerability is dose/formulation dependent R Multi-node oncogenic network destabilization Often presented as ATP-independent Hsp90 inhibition with downstream proteasomal degradation of clients; mechanistically central because it collapses multiple driver pathways at once.
2 Vimentin and intermediate filament remodeling Vimentin function/organization ↓ → migration/invasion ↓, EMT programs ↓ (context-dependent) Endothelial and stromal cytoskeleton can be affected; may underlie anti-angiogenic activity P Anti-motility / anti-metastatic leverage WA behaves as a reactive small molecule with reported covalent interaction with vimentin; cytoskeletal perturbation can be rapid and not strictly transcription-driven.
3 Mitochondrial ROS increase ROS ↑ → ΔΨm ↓, cyt-c ↑, caspase cascade ↑ → apoptosis ↑ Often ROS ↔ or ↓ with antioxidant response ↑ (model-dependent) P/R Selective redox toxicity in susceptible tumors Frequently paired with ER stress/UPR activation; selectivity is commonly framed as “push cancer over its redox limit,” but this is highly dose- and context-dependent.
4 ER stress and UPR axis ER stress ↑, UPR ↑ → proteotoxic stress → apoptosis/autophagy shifts (model-dependent) Adaptive UPR may occur; excessive dosing can stress normal tissues R Proteotoxic stress amplification Mechanistically synergistic with Hsp90 disruption and ROS signaling; can manifest as GRP78/BiP and related markers ↑ in some systems.
5 NF-κB inflammatory survival signaling NF-κB ↓ → cytokine/pro-survival programs ↓, invasion-associated signaling ↓ Anti-inflammatory signaling ↓ may be beneficial in some contexts; immune effects can be mixed G Survival/inflammation program suppression Often aligned with COX-2 and inflammasome-related readouts in inflammatory models; oncology relevance is strongest where NF-κB is a core survival node.
6 EMT and metastasis signaling EMT ↓, MMPs ↓, uPA ↓, CXCR4/SDF1 axis ↓ (model-dependent) Wound-healing programs can be affected (context-dependent) G Anti-invasive phenotype Partly downstream of cytoskeletal (vimentin) effects and NF-κB/TGF-β-linked programs; directionality can vary by tumor lineage and assay.
7 Glycolysis and HIF-1α HIF-1α ↓, glycolysis flux ↓, ATP ↓ (susceptible models) Usually ↔ at low exposure; metabolic stress possible at higher exposure G Metabolic vulnerability unmasking Often secondary to upstream stress (ROS/proteostasis) rather than a primary enzymatic inhibitor; interpret as (context-dependent).
8 Cell cycle checkpoint control Cell-cycle arrest ↑ (often G2/M reported), CDK/cyclin signaling ↓ Proliferating normal cells may also be sensitive at higher exposure G Anti-proliferative enforcement Common phenotype readout across WA studies; mechanistic “why” may differ by model (proteostasis vs ROS vs mitotic machinery/cytoskeleton).
9 NRF2 and antioxidant defense NRF2 ↓ and antioxidant enzymes ↓ reported in some cancer models; sometimes mixed ↔ NRF2 ↑ and antioxidant enzymes ↑ reported in some normal-tissue protection contexts G Redox buffering divergence Highly model-dependent; WA can behave as a stressor that either suppresses or activates NRF2-linked programs depending on timing, dose, and baseline redox state.
10 Clinical Translation Constraint Micromolar in-vitro dosing common; human oncology exposure/target engagement remains sparsely defined Supplement heterogeneity (WA content), drug-interaction risk, and organ-specific toxicity signals (notably liver; thyroid) constrain use Formulation + PK + safety gating Human data exist (phase I osteosarcoma; ongoing ovarian combo), but WA is not an approved anticancer drug and standardized products/target engagement biomarkers are not yet mature.

TSF legend: P: 0–30 min    R: 30 min–3 hr    G: >3 hr



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⟱
2388- Ash,    Withaferin A decreases glycolytic reprogramming in breast cancer
- in-vitro, BC, MDA-MB-231 - in-vitro, BC, MDA-MB-468 - in-vitro, BC, MCF-7 - in-vitro, BC, MDA-MB-453
GlucoseCon↓, WA decreases the glucose uptake, lactate production and ATP generation by inhibiting the expression of key glycolytic enzymes i.e., GLUT1, HK2 and PKM2.
lactateProd↓,
ATP↓,
Glycolysis↓,
GLUT1↓,
HK2↓,
PKM2↓,
cMyc↓, WA decreases the protein expression of key glycolytic enzymes via downregulation of c-myc expression
Warburg↓, WA decreases protein expression of key glycolytic enzymes and Warburg effect via c-myc inhibition
cMyc↓,


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

Pathway results for Effect on Cancer / Diseased Cells:


Mitochondria & Bioenergetics

ATP↓, 1,  

Core Metabolism/Glycolysis

cMyc↓, 2,   GlucoseCon↓, 1,   Glycolysis↓, 1,   HK2↓, 1,   lactateProd↓, 1,   PKM2↓, 1,   Warburg↓, 1,  

Barriers & Transport

GLUT1↓, 1,  
Total Targets: 9

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

 

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