Database Query Results : Silymarin (Milk Thistle) silibinin, , HK2

SIL, Silymarin (Milk Thistle) silibinin: Click to Expand ⟱
Features:
Silymarin (Milk Thistle) Flowering herb related to daisy and ragweed family.
Silibinin (INN), also known as silybin is the major active constituent of silymarin, a standardized extract of the milk thistle seeds.
-a flavonoid combination of 65–80% of seven flavolignans; the most important of these include silybin, isosilybin, silychristin, isosilychristin, and silydianin. Silybin is the most abundant compound in around 50–70% in isoforms silybin A and silybin B

-Note half-life 6hrs?.
BioAv not soluble in water, low bioAv (1%). 240mg yielded only 0.34ug/ml plasma level. oral administration of SM (equivalent to 120 mg silibinin), total (unconjugated + conjugated) silibinin concentration in plasma was 1.1–1.3 μg/mL, so can not achieve levels used in most in-vitro studies.
Pathways:
- results for both inducing and reducing ROS in cancer cells. In normal cell seems to consistently lower ROS. Reports show both ROS↑ and ROS↓ in cancer models; systemic pro-oxidant effects may require higher exposures than typical oral dosing, but local or combination contexts may differ. (level in GUT could be much higher (800uM).
- ROS↑ related: MMP↓(ΔΨm), Ca+2↑, Cyt‑c↑, Caspases↑, DNA damage↑, cl-PARP↑,
- Raises AntiOxidant defense in Normal Cells: ROS↓, NRF2↑, SOD↑, GSH↑, Catalase↑,
- lowers Inflammation : NF-kB↓, COX2↓, p38↓(context-dependent; often stress-activated), Pro-Inflammatory Cytokines : NLRP3↓, IL-1β↓, TNF-α↓, IL-6↓, IL-8↓
- inhibit Growth/Metastases : TumMeta↓, TumCG↓, EMT↓, MMPs↓, MMP2↓, MMP9↓, TIMP2, uPA↓, VEGF↓, FAK↓, NF-κB↓, CXCR4↓, TGF-β↓, α-SMA↓, ERK↓
- reactivate genes thereby inhibiting cancer cell growth : HDAC↓, DNMTs↓, P53↑, HSP↓,
- cause Cell cycle arrest : TumCCA↑, cyclin D1↓, cyclin E↓, CDK2↓, CDK4↓,
- inhibits Migration/Invasion : TumCMig↓, TumCI↓, TNF-α↓, FAK↓, ERK↓, EMT↓,
- inhibits glycolysis and ATP depletion : HIF-1α↓, PKM2↓, cMyc↓, GLUT1↓, LDH↓, LDHA↓, HK2, PFKs↓, GRP78↑(ER stress), Glucose↓, GlucoseCon↓
- inhibits angiogenesis↓ : VEGF↓, HIF-1α↓, Notch↓, PDGF↓, EGFR↓,
- inhibits Cancer Stem Cells : CSC↓, Hh↓, GLi1↓, β-catenin↓, Notch2↓, OCT4↓,
- Others: PI3K↓, AKT↓, JAK↓, STAT↓, Wnt↓, β-catenin↓, AMPK, ERK↓, JNK, - SREBP (related to cholesterol).
- Synergies: chemo-sensitization, chemoProtective, RadioSensitizer, RadioProtective, Others(review target notes), Neuroprotective, Cognitive, Renoprotection, Hepatoprotective, CardioProtective,

- Selectivity: Cancer Cells vs Normal Cells

Rank Pathway / Axis Cancer Cells Normal Cells TSF Primary Effect Notes / Interpretation
1 ROS / redox buffering + mitochondrial protection Often ↑ stress susceptibility; can support apoptosis when survival signaling is blocked ↓ oxidative stress; mitochondrial protection P, R, G Context-selective redox modulation Silymarin is classically cytoprotective/antioxidant in normal tissues (notably liver), while in tumors it can weaken pro-survival adaptation and increase vulnerability to stressors and therapy.
2 Intrinsic apoptosis (mitochondria → caspases) ↑ apoptosis signaling; ↑ caspase activation ↔ minimal activation G Cell death execution Common downstream outcome in cancer models: apoptosis increases after earlier signaling/redox shifts and/or checkpoint disruption.
3 Cell-cycle control (cyclins/CDKs; checkpoints) ↑ arrest (G1/S or G2/M depending on model) G Cytostasis Typically observed as reduced proliferation with checkpoint engagement; timing usually later than kinase phosphorylation changes.
4 NF-κB inflammatory transcription ↓ NF-κB activity; ↓ inflammatory/pro-survival tone ↔ or protective anti-inflammatory effect R, G Anti-inflammatory / anti-survival transcription NF-κB suppression can reduce tumor-promoting inflammation and blunt stress-adaptive survival programs.
5 JAK/STAT3 axis (incl. PD-L1 / immune escape programs in some models) ↓ STAT3 signaling (context); may ↓ PD-L1 in certain tumor contexts R, G Reduced survival + immune-evasion signaling Reported to attenuate STAT3-driven tumor programs and, in some contexts, reduce immune-suppressive signaling (model dependent).
6 PI3K → AKT → mTOR survival / growth signaling ↓ PI3K/AKT/mTOR signaling (context) R, G Growth/survival suppression Reduced PI3K/AKT/mTOR tone increases sensitivity to apoptosis and can reinforce cell-cycle arrest.
7 MAPK re-wiring (ERK/p38/JNK balance) Stress-MAPK shifts; ERK tone often reduced or re-patterned P, R, G Signal reprogramming Early phosphorylation shifts can precede later gene-expression changes; exact ERK direction is model and dose dependent.
8 Angiogenesis (VEGF and angiogenic factors) ↓ VEGF / angiogenesis outputs G Anti-angiogenic support Typically reflected in reduced pro-angiogenic expression/secretion and angiogenesis-related phenotypes over longer windows.
9 EMT / invasion / migration programs (incl. TGF-β/Smad-associated EMT in some systems) ↓ EMT markers; ↓ migration/invasion G Anti-invasive phenotype Often presents as restoration of epithelial markers and suppression of migration/invasion assays; commonly a later phenotype-level outcome.
10 Xenobiotic handling (Phase I/II enzymes; cytoprotection / chemoprevention framing) May alter carcinogen activation/detox balance ↑ detox / cytoprotection against xenobiotics G Chemopreventive protection A key “dual strategy” theme: protection of normal tissue from toxins/therapy while modulating tumor response pathways.
11 Drug resistance / efflux (MDR phenotype; P-gp-related resistance in some models) May ↓ functional MDR and ↑ chemo sensitivity (context) R, G Chemo-sensitization support Reported synergy with chemotherapy in resistant tumor settings; transporter direction can be context-specific, so present as “reported to reduce functional resistance” rather than a universal single-transporter claim.
12 Immune microenvironment signaling (cytokines / macrophage recruitment in some models) May ↓ pro-tumor cytokine programs and recruitment signals (context) G Anti-inflammatory tumor microenvironment shift Immune-modulatory effects are increasingly discussed, but they are more model-dependent and typically show on longer time scales.

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

  • P: 0–30 min (primary/physical–chemical effects; rapid signaling / phosphorylation shifts)
  • R: 30 min–3 hr (redox signaling + acute stress-response signaling)
  • G: >3 hr (gene-regulatory adaptation and phenotype-level outcomes)


HK2, Hexokinase 2: Click to Expand ⟱
Source:
Type: enzyme
HK2 (Hexokinase 2) is an enzyme that plays a crucial role in glycolysis, the process by which cells convert glucose into energy. HK2 is a key regulatory enzyme in the glycolytic pathway, and it is primarily expressed in various tissues, including muscle, brain, and cancer cells.
HK2 has been shown to be overexpressed in many types of tumors, including breast, lung, and colon cancer. This overexpression may contribute to the development and progression of cancer by promoting glycolysis and energy production in cancer cells.
HK2 is a key regulatory enzyme in the glycolytic pathway.
HK2 plays a role in the regulation of glucose metabolism in diabetes.
HK2 is involved in the regulation of cell proliferation, apoptosis, and autophagy.

HK2 Inhibitors:
-2DG
-Curcumin
-Resveratrol
-EGCG
-Berberine
-Methyl Jasmonate (MJ)
-Honokiol


Scientific Papers found: Click to Expand⟱
2410- SIL,    Autophagy activated by silibinin contributes to glioma cell death via induction of oxidative stress-mediated BNIP3-dependent nuclear translocation of AIF
- in-vitro, GBM, U87MG - in-vitro, GBM, U251 - in-vivo, NA, NA
TumAuto↑, Mechanistically, silibinin activates autophagy through depleting ATP by suppressing glycolysis.
ATP↓,
Glycolysis↓, Silibinin suppressed glycolysis in glioma cells
H2O2↑, Then, autophagy improves intracellular H2O2 via promoting p53-mediated depletion of GSH and cysteine and downregulation of xCT
P53↑,
GSH↓,
xCT↓,
BNIP3↝, The increased H2O2 promotes silibinin-induced BNIP3 upregulation and translocation to mitochondria
MMP↑, silibinin-induced mitochondrial depolarization, accumulation of mitochondrial superoxide
mt-ROS↑,
mtDam↑, Autophagy contributed to silibinin-induced mitochondria damage
HK2↓, protein levels of HK II, PFKP, and PKM2 were all downregulated time-dependently by silibinin in U87, U251, SHG-44, and C6 glioma cells
PFKP↓,
PKM2↓, silibinin suppressed glycolysis via downregulation of HK II, PFKP, and PKM2.
TumCG↓, Silibinin inhibited glioma cell growth in vivo

1140- SIL,    Silibinin-mediated metabolic reprogramming attenuates pancreatic cancer-induced cachexia and tumor growth
- in-vitro, PC, AsPC-1 - in-vivo, PC, NA - in-vitro, PC, MIA PaCa-2 - in-vitro, PC, PANC1 - in-vitro, PC, Bxpc-3
TumCG↓,
Glycolysis↓,
cMyc↓,
STAT3↓,
TumCP↓,
Weight∅, prevents the loss of body weight and muscle.
Strength↑,
DNAdam↑,
Casp3↑,
Casp9↑,
GLUT1↓,
HK2↓,
LDHA↓,
GlucoseCon↓, silibinin inhibits glucose uptake and lactate release
lactateProd↓,
PPP↓, significant reduction in pentose phosphate pathway (PPP) metabolites, including 6-phosphogluconate (~50%), erythrose-4-phosphate (~40%), sedoheptulose-7-phosphate and sedoheptulose bis-phosphate (~ 70%)
Ki-67↓, reduced Ki67-positive cells
p‑STAT3↓,
cachexia↓,


* indicates research on normal cells as opposed to diseased cells
Total Research Paper Matches: 2

Pathway results for Effect on Cancer / Diseased Cells:


Redox & Oxidative Stress

GSH↓, 1,   H2O2↑, 1,   mt-ROS↑, 1,   xCT↓, 1,  

Mitochondria & Bioenergetics

ATP↓, 1,   MMP↑, 1,   mtDam↑, 1,  

Core Metabolism/Glycolysis

cMyc↓, 1,   GlucoseCon↓, 1,   Glycolysis↓, 2,   HK2↓, 2,   lactateProd↓, 1,   LDHA↓, 1,   PFKP↓, 1,   PKM2↓, 1,   PPP↓, 1,  

Cell Death

Casp3↑, 1,   Casp9↑, 1,  

Autophagy & Lysosomes

BNIP3↝, 1,   TumAuto↑, 1,  

DNA Damage & Repair

DNAdam↑, 1,   P53↑, 1,  

Proliferation, Differentiation & Cell State

STAT3↓, 1,   p‑STAT3↓, 1,   TumCG↓, 2,  

Migration

Ki-67↓, 1,   TumCP↓, 1,  

Barriers & Transport

GLUT1↓, 1,  

Clinical Biomarkers

Ki-67↓, 1,  

Functional Outcomes

cachexia↓, 1,   Strength↑, 1,   Weight∅, 1,  
Total Targets: 32

Pathway results for Effect on Normal Cells:


Total Targets: 0

Scientific Paper Hit Count for: HK2, Hexokinase 2
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#:154  Target#:773  State#:%  Dir#:%
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