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human colorectal cancer cell lines  (MedChemExpress)


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    Structured Review

    MedChemExpress human colorectal cancer cell lines
    Study overview. Step 1 illustrates the causal relationship between metabolites and <t>colorectal</t> cancer (CRC). The results show that some metabolites are causes of CRC occurrence, while CRC has no causal effect on metabolites. Step 2 illustrates the causal relationship between cytokines and CRC. The results show that some cytokines are causes of CRC occurrence, while CRC has no causal effect on cytokines. Step 3 illustrates the mediation analysis of cytokines in the pathway from metabolites to CRC: path c represents the total effect of metabolites on colorectal cancer; path b represents the causal effect of cytokines on colorectal cancer; path a represents the causal effect of metabolites on cytokines
    Human Colorectal Cancer Cell Lines, supplied by MedChemExpress, used in various techniques. Bioz Stars score: 94/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/human+colorectal+cancer+organoids/Human+Colorectal+Cancer+Organoid+Complete+Culture+Medium/pmc12870534-134-0-18
    Average 94 stars, based on 1 article reviews
    human colorectal cancer cell lines - by Bioz Stars, 2026-09
    94/100 stars

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    1) Product Images from "Multi-omics and machine learning reveal DPPC as a key contributor to colorectal cancer progression and tumor immune microenvironment remodeling"

    Article Title: Multi-omics and machine learning reveal DPPC as a key contributor to colorectal cancer progression and tumor immune microenvironment remodeling

    Journal: Journal of Translational Medicine

    doi: 10.1186/s12967-025-07576-y

    Study overview. Step 1 illustrates the causal relationship between metabolites and colorectal cancer (CRC). The results show that some metabolites are causes of CRC occurrence, while CRC has no causal effect on metabolites. Step 2 illustrates the causal relationship between cytokines and CRC. The results show that some cytokines are causes of CRC occurrence, while CRC has no causal effect on cytokines. Step 3 illustrates the mediation analysis of cytokines in the pathway from metabolites to CRC: path c represents the total effect of metabolites on colorectal cancer; path b represents the causal effect of cytokines on colorectal cancer; path a represents the causal effect of metabolites on cytokines
    Figure Legend Snippet: Study overview. Step 1 illustrates the causal relationship between metabolites and colorectal cancer (CRC). The results show that some metabolites are causes of CRC occurrence, while CRC has no causal effect on metabolites. Step 2 illustrates the causal relationship between cytokines and CRC. The results show that some cytokines are causes of CRC occurrence, while CRC has no causal effect on cytokines. Step 3 illustrates the mediation analysis of cytokines in the pathway from metabolites to CRC: path c represents the total effect of metabolites on colorectal cancer; path b represents the causal effect of cytokines on colorectal cancer; path a represents the causal effect of metabolites on cytokines

    Techniques Used:

    Annotation of scRNA-seq datasets. ( A ) UMAP of scRNA-seq. ( B ) Proportion diagram of scRNA-seq of colorectal cancer patients and healthy individuals. ( C ) The expression of metabolism in different cells. ( D ) The expression of TNFSF14 in different cells. ( E ) The expression of TNFSF14 in metabolism_ high and metabolism_ low. ( F ) GSEA analysis of intersection genes. ( G ) Analysis of metabolic groups and other cells interactions. ( H ) Pathway analysis of metabolic groups and immune cell differentiation signals. ( I ) Identification of transcription factors in metabolism high and metabolism_low. Metabolism_ high: Epithelial_cell with high DPPC metabolism; metabolism low: epithelial cell with low DPPC metabolism; CRC: colorectal cancer; CT: healthy subjects
    Figure Legend Snippet: Annotation of scRNA-seq datasets. ( A ) UMAP of scRNA-seq. ( B ) Proportion diagram of scRNA-seq of colorectal cancer patients and healthy individuals. ( C ) The expression of metabolism in different cells. ( D ) The expression of TNFSF14 in different cells. ( E ) The expression of TNFSF14 in metabolism_ high and metabolism_ low. ( F ) GSEA analysis of intersection genes. ( G ) Analysis of metabolic groups and other cells interactions. ( H ) Pathway analysis of metabolic groups and immune cell differentiation signals. ( I ) Identification of transcription factors in metabolism high and metabolism_low. Metabolism_ high: Epithelial_cell with high DPPC metabolism; metabolism low: epithelial cell with low DPPC metabolism; CRC: colorectal cancer; CT: healthy subjects

    Techniques Used: Expressing, Cell Differentiation

    Related Articles

    Cell Culture:

    Article Title: Visual-Servo Micromanipulation Platform for Patterned and Complex Organoid Biofabrication
    Article Snippet: Materials and methods Cell lines and human Colorectal Cancer organoids culture. iPSCs were purchased from Cellapy (Cat# 4027106), HUVECs (Human Umbilical Vein Endothelial Cells) and human Colorectal Cancer organoid were gifts from the Dr. Ming Liu lab in The Fourth A liated Hospital of Harbin Medical University. iPSCs and HUVECs were cultured in TeSRTM1 (StemCell, Cat#85850) and DMEM/F12 GlutaMAXTM (ThermoFisher, Cat# 10565018) with 10% FBS (ThermoFisher, Cat#A5669701) separately for 48 hrs before seeding in microwells array. .. Human Colorectal Cancer Organoids were cultured in DMEM/F12 GlutaMAXTM (ThermoFisher, Cat# 10565018) contained 1 × B27 supplement (Gibco, Cat#17504-044), 1.25 mM N-acetylcysteine (Sigma-Aldrich, Cat#1009005), 100 ng ml−1 EGF (Peprotech, Cat# AF-100-15), 500 nM A83-01 (MCE, HY-10432), R-spondin1 (MCE, Cat#HYP7114), Noggin (MCE, Cat#HY-P70558), 10 nM Gastrin I (MCE, Cat# HY-P1097), 5 mM Nicotinamide (Sigma-Aldrich, Cat#N0636). .. 10 μM Y-27632 (MCE, Cat#HY-10071) was used in the rst 24 hours after cell seeding to prevent cells from anoikic.



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    human colorectal cancer cell lines  (MedChemExpress)
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    Study overview. Step 1 illustrates the causal relationship between metabolites and <t>colorectal</t> cancer (CRC). The results show that some metabolites are causes of CRC occurrence, while CRC has no causal effect on metabolites. Step 2 illustrates the causal relationship between cytokines and CRC. The results show that some cytokines are causes of CRC occurrence, while CRC has no causal effect on cytokines. Step 3 illustrates the mediation analysis of cytokines in the pathway from metabolites to CRC: path c represents the total effect of metabolites on colorectal cancer; path b represents the causal effect of cytokines on colorectal cancer; path a represents the causal effect of metabolites on cytokines
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    human colorectal cancer organoids  (MedChemExpress)
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    Study overview. Step 1 illustrates the causal relationship between metabolites and <t>colorectal</t> cancer (CRC). The results show that some metabolites are causes of CRC occurrence, while CRC has no causal effect on metabolites. Step 2 illustrates the causal relationship between cytokines and CRC. The results show that some cytokines are causes of CRC occurrence, while CRC has no causal effect on cytokines. Step 3 illustrates the mediation analysis of cytokines in the pathway from metabolites to CRC: path c represents the total effect of metabolites on colorectal cancer; path b represents the causal effect of cytokines on colorectal cancer; path a represents the causal effect of metabolites on cytokines
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    Image Search Results


    Study overview. Step 1 illustrates the causal relationship between metabolites and colorectal cancer (CRC). The results show that some metabolites are causes of CRC occurrence, while CRC has no causal effect on metabolites. Step 2 illustrates the causal relationship between cytokines and CRC. The results show that some cytokines are causes of CRC occurrence, while CRC has no causal effect on cytokines. Step 3 illustrates the mediation analysis of cytokines in the pathway from metabolites to CRC: path c represents the total effect of metabolites on colorectal cancer; path b represents the causal effect of cytokines on colorectal cancer; path a represents the causal effect of metabolites on cytokines

    Journal: Journal of Translational Medicine

    Article Title: Multi-omics and machine learning reveal DPPC as a key contributor to colorectal cancer progression and tumor immune microenvironment remodeling

    doi: 10.1186/s12967-025-07576-y

    Figure Lengend Snippet: Study overview. Step 1 illustrates the causal relationship between metabolites and colorectal cancer (CRC). The results show that some metabolites are causes of CRC occurrence, while CRC has no causal effect on metabolites. Step 2 illustrates the causal relationship between cytokines and CRC. The results show that some cytokines are causes of CRC occurrence, while CRC has no causal effect on cytokines. Step 3 illustrates the mediation analysis of cytokines in the pathway from metabolites to CRC: path c represents the total effect of metabolites on colorectal cancer; path b represents the causal effect of cytokines on colorectal cancer; path a represents the causal effect of metabolites on cytokines

    Article Snippet: Human colorectal cancer cell lines were cultured in suspension until the logarithmic growth phase under treatment with DPPC (MCE, HY-109506) at varying concentrations.

    Techniques:

    Annotation of scRNA-seq datasets. ( A ) UMAP of scRNA-seq. ( B ) Proportion diagram of scRNA-seq of colorectal cancer patients and healthy individuals. ( C ) The expression of metabolism in different cells. ( D ) The expression of TNFSF14 in different cells. ( E ) The expression of TNFSF14 in metabolism_ high and metabolism_ low. ( F ) GSEA analysis of intersection genes. ( G ) Analysis of metabolic groups and other cells interactions. ( H ) Pathway analysis of metabolic groups and immune cell differentiation signals. ( I ) Identification of transcription factors in metabolism high and metabolism_low. Metabolism_ high: Epithelial_cell with high DPPC metabolism; metabolism low: epithelial cell with low DPPC metabolism; CRC: colorectal cancer; CT: healthy subjects

    Journal: Journal of Translational Medicine

    Article Title: Multi-omics and machine learning reveal DPPC as a key contributor to colorectal cancer progression and tumor immune microenvironment remodeling

    doi: 10.1186/s12967-025-07576-y

    Figure Lengend Snippet: Annotation of scRNA-seq datasets. ( A ) UMAP of scRNA-seq. ( B ) Proportion diagram of scRNA-seq of colorectal cancer patients and healthy individuals. ( C ) The expression of metabolism in different cells. ( D ) The expression of TNFSF14 in different cells. ( E ) The expression of TNFSF14 in metabolism_ high and metabolism_ low. ( F ) GSEA analysis of intersection genes. ( G ) Analysis of metabolic groups and other cells interactions. ( H ) Pathway analysis of metabolic groups and immune cell differentiation signals. ( I ) Identification of transcription factors in metabolism high and metabolism_low. Metabolism_ high: Epithelial_cell with high DPPC metabolism; metabolism low: epithelial cell with low DPPC metabolism; CRC: colorectal cancer; CT: healthy subjects

    Article Snippet: Human colorectal cancer cell lines were cultured in suspension until the logarithmic growth phase under treatment with DPPC (MCE, HY-109506) at varying concentrations.

    Techniques: Expressing, Cell Differentiation