Silymarin (Milk Thistle) silibinin / NOTCH Cancer Research Results

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">Notch↓, PDGF↓, EGFR↓,
- inhibits Cancer Stem Cells : CSC↓, Hh↓, GLi1↓, β-catenin↓, NOTCH">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)
NOTCH, : Click to Expand ⟱
Source: HalifaxProj(block) CGL-CF TCGA
Type:
Notch signaling pathway is a regulator of self-renewal and differentiation in several tissues and cell types.; Notch hyperactivation has been implicated as oncogenic in several cancers including breast cancer and T-cell acute lymphoblastic leukemia (T-ALL).
Due to its dual roles, NOTCH signaling is being explored as a therapeutic target. Inhibitors of NOTCH signaling are being investigated in clinical trials for various cancers, particularly those with aberrant NOTCH activation.
The abnormal activation of the NOTCH pathway has been linked to increased cancer cell growth, survival, invasion, and resistance to chemotherapy and radiation therapy. On the other hand, blocking the NOTCH pathway has been shown to trigger cancer cell differentiation and cell death, and it makes them more responsive to therapy. Hence, inhibiting the NOTCH pathway has become a promising approach for treating cancer, and various NOTCH pathway inhibitors are currently under development for cancer treatment.
Scientific Papers found: Click to Expand⟱
3282- SIL,    Role of Silymarin in Cancer Treatment: Facts, Hypotheses, and Questions
- Review, NA, NA
hepatoP↑, AntiCan↑, TumCMig↓, Hif1a↓, selectivity↑, toxicity∅, *antiOx↑, *Inflam↓, TumCCA↑, P21↑, CDK4↓, NF-kB↓, ERK↓, PSA↓, TumCG↓, p27↑, COX2↓, IL1↓, VEGF↓, IGFBP3↑, AR↓, STAT3↓, Telomerase↓, Cyt‑c↑, Casp↑, eff↝, HDAC↓, HATs↑, Zeb1↓, E-cadherin↑, miR-203↑, NHE1↓, MMP2↓, MMP9↓, PGE2↓, Vim↓, Wnt↓, angioG↓, VEGF↓, *TIMP1↓, EMT↓, TGF-β↓, CD44↓, EGFR↓, PDGF↓, *IL8↓, SREBP1↓, MMP↓, ATP↓, uPA↓, PD-L1↓, NOTCH↓, *SIRT1↑, SIRT1↓, CA↓, Ca+2↑, chemoP↑, cardioP↑, Dose↝, Half-Life↝, BioAv↓, BioAv↓, BioAv↓, toxicity↝, Half-Life↓, ROS↓, FAK↓,

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:


Redox & Oxidative Stress ⓘ

ROS↓, 1,  

Mitochondria & Bioenergetics ⓘ

ATP↓, 1,   MMP↓, 1,  

Core Metabolism/Glycolysis ⓘ

SIRT1↓, 1,   SREBP1↓, 1,  

Cell Death ⓘ

Casp↑, 1,   Cyt‑c↑, 1,   p27↑, 1,   Telomerase↓, 1,  

Transcription & Epigenetics ⓘ

HATs↑, 1,  

Cell Cycle & Senescence ⓘ

CDK4↓, 1,   P21↑, 1,   TumCCA↑, 1,  

Proliferation, Differentiation & Cell State ⓘ

CD44↓, 1,   EMT↓, 1,   ERK↓, 1,   HDAC↓, 1,   IGFBP3↑, 1,   NOTCH↓, 1,   STAT3↓, 1,   TumCG↓, 1,   Wnt↓, 1,  

Migration ⓘ

CA↓, 1,   Ca+2↑, 1,   E-cadherin↑, 1,   FAK↓, 1,   miR-203↑, 1,   MMP2↓, 1,   MMP9↓, 1,   PDGF↓, 1,   TGF-β↓, 1,   TumCMig↓, 1,   uPA↓, 1,   Vim↓, 1,   Zeb1↓, 1,  

Angiogenesis & Vasculature ⓘ

angioG↓, 1,   EGFR↓, 1,   Hif1a↓, 1,   VEGF↓, 2,  

Barriers & Transport ⓘ

NHE1↓, 1,  

Immune & Inflammatory Signaling ⓘ

COX2↓, 1,   IL1↓, 1,   NF-kB↓, 1,   PD-L1↓, 1,   PGE2↓, 1,   PSA↓, 1,  

Hormonal & Nuclear Receptors ⓘ

AR↓, 1,  

Drug Metabolism & Resistance ⓘ

BioAv↓, 3,   Dose↝, 1,   eff↝, 1,   Half-Life↓, 1,   Half-Life↝, 1,   selectivity↑, 1,  

Clinical Biomarkers ⓘ

AR↓, 1,   EGFR↓, 1,   PD-L1↓, 1,   PSA↓, 1,  

Functional Outcomes ⓘ

AntiCan↑, 1,   cardioP↑, 1,   chemoP↑, 1,   hepatoP↑, 1,   toxicity↝, 1,   toxicity∅, 1,  
Total Targets: 63

Pathway results for Effect on Normal Cells:


Redox & Oxidative Stress ⓘ

antiOx↑, 1,  

Core Metabolism/Glycolysis ⓘ

SIRT1↑, 1,  

Migration ⓘ

TIMP1↓, 1,  

Immune & Inflammatory Signaling ⓘ

IL8↓, 1,   Inflam↓, 1,  
Total Targets: 5

Scientific Paper Hit Count for: NOTCH, 
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#:220  State#:%  Dir#:%
  wNotes=0  sortOrder:rid,rpid

 

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