murine tumor cell lines b16 melanoma  (ATCC)

Journal: Bioactive Materials

Article Title: pH-neutralization strategy to suppress GPCR68 spatiotemporally activates T cells and enhances anti-tumor immunity

doi: 10.1016/j.bioactmat.2026.02.039

Figure Lengend Snippet: Physicochemical properties of BOLT, and BOLT reduces the growth of tumor cells. (A) Schematic of surface double-layer formation and ion release. (B) Negative zeta potential (−1.365 mV) and high conductivity (1.334 mS/cm), confirming colloidal stability and ion release. (C) Uniform particle size (∼1478 nm) across batches. (D) Interfacial pH buffering in PBS. (E) Naïve CD4 + T cells were isolated and activated using anti-CD3 and anti-CD28 using the culture media with 6.0 pH and treated with various doses of BOLT. RT-qPCR was performed to determine the expression of Gpcr68 at various BOLT doses in activated T cells at acidic pH. (F) Anti-CD3 and anti-CD28 activated CD4 + T cells were treated with different doses of BOLT to determine the protein expression of GPCR68 using Western blot. (G-J) CCK8 assay was performed to analyze the effect of various pH on B16, MC38, 143B, and MG63 cell proliferation. (K-L) Effect of various doses of BOLT on the B16 and K7M2 cell growth to determine the IC-50 of BOLT. Error bars represent mean ± SEM. ∗∗ p < 0.01 and ∗ p < 0.05.

Article Snippet: Murine tumor cell lines B16 melanoma (RRID: CVCL_0159), MC38 colon cancer (RRID: CVCL_B288), and 4T1 (RRID: CRL_2539) were purchased from the ATCC and cultured in RPMI 1640 medium (Gibco) or DMEM medium (Gibco) with 10% FBS as well as 1% penicillin/streptomycin.

Techniques: Zeta Potential Analyzer, Isolation, Quantitative RT-PCR, Expressing, Western Blot, CCK-8 Assay

Journal: Bioactive Materials

Article Title: pH-neutralization strategy to suppress GPCR68 spatiotemporally activates T cells and enhances anti-tumor immunity

doi: 10.1016/j.bioactmat.2026.02.039

Figure Lengend Snippet: Anti-tumor effects of borate bioactive glass (BOLT) in B16 tumor. (A) Schematic illustration depicting the induction of B16 melanoma tumors, followed by treatment with BOLT at various time points, and tumor harvesting for subsequent analysis. (B) Tumor growth curves showing tumor volume in Control and BOLT-treated B16 melanoma tumors in mice. (C) Tumor weight at the time of harvesting in the BOLT-treated group compared to the Control. (D) Representative images of excised tumors from Control and BOLT-treated mice. (E) In vivo imaging of tumor-bearing mice in both the Control and BOLT-treated groups. (F) Flow cytometry analysis showing IFN-γ production in CD4 + and CD8 + T cells following BOLT treatment compared to Control. (G) Flow cytometry analysis demonstrated TNF-α production in CD4 + and CD8 + T cells in the BOLT-treated group, with a significant increase observed in CD8 + T cells. Student t-test was performed for comparison between the two groups. Two-way ANOVA was used for multiple comparisons. Data represent the mean ± SEM (n = 5). ∗ p < 0.05, ∗∗ p < 0.01.

Article Snippet: Murine tumor cell lines B16 melanoma (RRID: CVCL_0159), MC38 colon cancer (RRID: CVCL_B288), and 4T1 (RRID: CRL_2539) were purchased from the ATCC and cultured in RPMI 1640 medium (Gibco) or DMEM medium (Gibco) with 10% FBS as well as 1% penicillin/streptomycin.

Techniques: Control, In Vivo Imaging, Flow Cytometry, Comparison

Journal: Bioactive Materials

Article Title: pH-neutralization strategy to suppress GPCR68 spatiotemporally activates T cells and enhances anti-tumor immunity

doi: 10.1016/j.bioactmat.2026.02.039

Figure Lengend Snippet: BOLT treatment induces ferroptosis in tumor cells. (A) RNA was extracted from Control and BOLT-treated tumors, and RNA sequencing (RNAseq) was performed to identify differentially expressed genes. (B) KEGG pathway analysis was conducted to assess the biological functions of the differentially expressed genes. (C) Heatmap displaying the differential expression of ferroptosis-related genes in BOLT-treated versus Control cells. (D) qRT-PCR analysis showing dose-dependent downregulation of Nrf2 in BOLT-treated cells. (E) qRT-PCR analysis of Duox1 expression in B16 cells following BOLT treatment. (F) Transmission electron microscopy (TEM) images showing mitochondrial shrinkage, increased membrane density, and loss of cristae in BOLT-treated cells. (G) Heatmap showing the dysregulated genes involved in ROS-chemical carcinogenesis in B16 cells treated with BOLT. (H) Flow cytometry analysis revealing reactive oxygen species (ROS) production in B16 cells treated with BOLT (0.25 μg/mL) compared to Control. (I) Histogram overlays and bar graph confirm elevated bodipy levels in BOLT-treated cells versus Control. (J) Annexin V/PI staining shows no significant apoptosis in B16 cells following BOLT treatment. (K) Western blot analysis showing the expression of genes involved in downregulating ferroptosis (SLC7A11, FACL4, and GPX4) in BOLT-treated B16 cells. Student t-test was performed for comparison between 2 groups. Two-way ANOVA was used for multiple comparisons. In-vitro experiments were performed in triplicate. Data are mean ± SEM, ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001, and ∗∗∗∗ p < 0.0001.

Article Snippet: Murine tumor cell lines B16 melanoma (RRID: CVCL_0159), MC38 colon cancer (RRID: CVCL_B288), and 4T1 (RRID: CRL_2539) were purchased from the ATCC and cultured in RPMI 1640 medium (Gibco) or DMEM medium (Gibco) with 10% FBS as well as 1% penicillin/streptomycin.

Techniques: Control, RNA Sequencing, RNA sequencing, Quantitative Proteomics, Quantitative RT-PCR, Expressing, Transmission Assay, Electron Microscopy, Membrane, Flow Cytometry, Staining, Western Blot, Comparison, In Vitro

Journal: Bioactive Materials

Article Title: pH-neutralization strategy to suppress GPCR68 spatiotemporally activates T cells and enhances anti-tumor immunity

doi: 10.1016/j.bioactmat.2026.02.039

Figure Lengend Snippet: Combinational treatment of BOLT and anti-CTLA-4 blockade enhances anti-tumor immune response in B16 melanoma. (A) C57BL/6 mice were subcutaneously injected with 1 × 10 5 B16 melanoma cells on day 0 to induce tumors. On day 7, mice were randomly divided into groups and treated with either BOLT alone (intratumoral injection administered on alternate days starting from day 7), anti-CTLA-4 (intraperitoneal injection administered on days 9, 11, 13, and 15), or a combination of both treatments. PBS was used as a vehicle Control, while IgG was used as anti-CTLA-4 Control. Tumor growth was monitored throughout the treatment period, and tumors were harvested for analysis on day 21. (B-C) Tumor growth curves and area under the curve (AUC) analysis for WT mice treated with BOLT, with or without anti-CTLA-4 antibody, following subcutaneous injection of B16 melanoma cells. Tumor growth was monitored, and analysis was conducted on day 21. (D) Representative images of excised tumors at day 21, showed reduced tumor size in combination-treated mice. (E, F) Flow cytometry analysis of IFN-γ production by tumor-infiltrating CD4 + and CD8 + T cells. (G, H) Flow cytometry analysis of TNF-α production by tumor-infiltrating CD4 + and CD8 + T cells. Two-way ANOVA was used for multiple comparisons. Data are mean ± SEM (n = 5), ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001, and ∗∗∗∗ p < 0.0001.

Article Snippet: Murine tumor cell lines B16 melanoma (RRID: CVCL_0159), MC38 colon cancer (RRID: CVCL_B288), and 4T1 (RRID: CRL_2539) were purchased from the ATCC and cultured in RPMI 1640 medium (Gibco) or DMEM medium (Gibco) with 10% FBS as well as 1% penicillin/streptomycin.

Techniques: Injection, Control, Flow Cytometry

Journal: bioRxiv

Article Title: ME1 Programs Latent Effector Capacity and Grounds a Mathematical Model of Reversible T Cell Exhaustion

doi: 10.64898/2026.05.05.722814

Figure Lengend Snippet: (A) Schematic illustrating the generation of CD8-specific ME1 transgenic (ME1 Tg) mice. (B) Representative flow cytometry showing tdTomato expression as a surrogate for ME1 overexpression in CD8 + tumor-infiltrating lymphocytes (TILs). (C–D) Average growth curves of B16F10 tumors in control and CD8-ME1 Tg mice treated with PBS (C) or combined anti-PD-1/anti-PD-L1 antibodies (100 μg each per dose) administered every other day starting on day 6 (arrow) after tumor implantation. Tumor growth was analyzed by two-way ANOVA (D, n = 6, **P < 0.01). (E) Tumor sizes were measured at endpoint. Data were analyzed using an unpaired two-tailed t test (n = 4–8, ***P < 0.001). One of two independent experiments is shown. (F) Flow cytometric analysis of granzyme B (GZMB) protein expression in CD8 + TILs cells from B16F10 tumors in ME1 Tg and control mice on day 12. Data were analyzed using an unpaired two-tailed Student’s t test ( * P< 0.05; n = 5 mice per group).

Article Snippet: B16F10 murine melanoma cell line was purchased from ATCC (CRL-6475) and cultured using DMEM complete medium.

Techniques: Transgenic Assay, Flow Cytometry, Expressing, Over Expression, Control, Tumor Implantation, Two Tailed Test

Journal: Future Science OA

Article Title: Integrative analysis of adiponectin-related genes reveals immune subtypes and prognostic significance in melanoma

doi: 10.1080/20565623.2026.2664611

Figure Lengend Snippet: ALB regulates immune-related gene expression at the transcriptional level in melanoma cells. (A) qRT-PCR analysis of ALB mRNA levels in A375 and SK-MEL-28 cells transfected with control (oe-NC/si-NC), ALB overexpression plasmid (oe-ALB), or ALB-targeting siRNA (si-ALB). (B) Relative mRNA expression of IL-6, TNF-α, TGF-β, IL-17A, and RORγt in A375 cells after ALB modulation. (C) Corresponding mRNA expression profiles in SK-MEL-28 cells. Data were presented as mean ± SD (n = 3). ** P < 0.01 vs. oe-NC group; ## P < 0.01 vs. si-NC group.

Article Snippet: Human melanoma cell lines A375 (#CRL-1619) and SK-MEL-28 (#HTB-72) were obtained from ATCC and cultured in Dulbecco’s Modified Eagle Medium (DMEM; Gibco, USA) supplemented with 10% fetal bovine serum (FBS; Gibco, USA) and 1% penicillin–streptomycin at 37 °C in a humidified incubator with 5% CO 2 .

Techniques: Gene Expression, Quantitative RT-PCR, Transfection, Control, Over Expression, Plasmid Preparation, Expressing

Journal: Journal of Extracellular Vesicles

Article Title: Lipidome Analysis of Cancer Cells and Their Extracellular Vesicles Reveals Cancer‐Type‐Specific Lipid Signatures and Enables the Design of EV‐Mimetic Liposomes

doi: 10.1002/jev2.70265

Figure Lengend Snippet: Characterization of EVs derived from different cell lines. Figure presents the strategy for isolating and characterizing EVs from six human cell models, illustrating their morphological diversity, homogeneous size (130–160 nm), negative surface charge, and expression of the syntenin marker. These results validate the quality and comparability of the EVs used for lipidomic analysis. (A) Schematic representation of the cell lines used for EV isolation. Created in https://BioRender.com . (B) TEM images of EVs isolated from MP41 (primary tumor), OMM2.5 (metastatic tumor) and BJ (non‐cancer) cells, showing the spherical morphology and nanometric size of EVs. Scale bars: 500 nm. (C) Normalized distribution (min–max normalization) of EV size, measured by NTA. The Y ‐axis values represent relative proportions between 0 and 1, calculated based on the minima and maxima of each sample. This representation allows for comparison of the shapes of the distributions regardless of differences in initial particle concentration. (D) Mean size (in nm) of EVs measured by NTA. (E) Zeta potential of EVs measured in millivolts (mV), indicating the surface charge of the particles. The zeta potential was negative for all EV samples, as expected. (F) Reconstituted western blots showing the presence of syntenin (detected at ∼35 kDa) in EVs isolated from four cancer cell lines (HT29, MP41, MEL270 and OMM2.5) and two non‐cancer cell lines (BJ, CCD‐18Co). The antibody was used at a 1:1,000 dilution. All experiments were performed in triplicates. Note: syntenin was selected as an EV marker due to its abundance and conservation in small EVs, in line with recent proteomic studies and MISEV2023 guidelines. Furthermore, our previous work (Lopez et al. ; Tsering et al. ) confirmed the presence of other canonical EV markers, including TSG101 and CD81, in a subset of these cell lines.

Article Snippet: Human uveal melanoma (UM) cell line MP41 (CRL‐3297) was purchased from ATCC (Manassas, Va, USA).

Techniques: Derivative Assay, Expressing, Marker, Isolation, Comparison, Concentration Assay, Zeta Potential Analyzer, Western Blot

Journal: Journal of Extracellular Vesicles

Article Title: Lipidome Analysis of Cancer Cells and Their Extracellular Vesicles Reveals Cancer‐Type‐Specific Lipid Signatures and Enables the Design of EV‐Mimetic Liposomes

doi: 10.1002/jev2.70265

Figure Lengend Snippet: Individual lipidomic profiling of cells and their EVs. Figure highlights the diversity of lipid families and saturation levels in each cell line and their EVs. The profiles reveal distinct lipid signatures depending on the cell type, with a predominance of phospholipids and marked differences between cancerous and non‐cancerous cells. (A) Schematic representation that presents the type of analysis (a descriptive characterization of the lipid profile of each sample) and key information. Created in https://BioRender.com . (B) Pie charts showing the relative proportions of lipid classes (lysophospholipids, phospholipids, sphingolipids and sterols) for each cell line and their EVs: MP41, MEL270, OMM2.5, HT29, CCD‐18Co and BJ. (C) Line graphs depict the relative abundance of individual lipid species within each family for cells and EVs from each sample type. The X ‐axis represents lipid families, while the Y ‐axis indicates the percentage of lipid species. (D) Pie charts showing the overall proportions of saturated, monounsaturated and polyunsaturated lipids in cells and EVs for each sample.

Article Snippet: Human uveal melanoma (UM) cell line MP41 (CRL‐3297) was purchased from ATCC (Manassas, Va, USA).

Techniques:

Journal: Journal of Extracellular Vesicles

Article Title: Lipidome Analysis of Cancer Cells and Their Extracellular Vesicles Reveals Cancer‐Type‐Specific Lipid Signatures and Enables the Design of EV‐Mimetic Liposomes

doi: 10.1002/jev2.70265

Figure Lengend Snippet: Cell‐EV lipid profile comparison. Figure compares the lipid profiles of cells and their EVs, showing that nearly half of the lipid species are shared, but that each cell type exhibits specific enrichments or depletions in its EVs. These differences highlight lipid sorting mechanisms specific to each cellular context. (A) Schematic representation that presents the type of analysis (cell‐EV lipid profile comparison) and key information. Created in https://BioRender.com . (B) Venn diagrams illustrating the overlap of identified lipid species between cells and EVs for each sample type: MP41, MEL270, OMM2.5, HT29, CCD‐18Co and BJ. The numbers represent the total lipid species unique to cells, unique to EVs, and shared between both. (C) Bar graphs summarize the proportions of different lipid families in EVs for each cell line. The Y ‐axis represents lipid families, while the X ‐axis indicates the percentage of lipid species in EVs, compared to their cells. (D,E) Volcano plots showing the differential abundance of lipid species shared between cells and their corresponding EVs. Panel (D) Highlights the underexpressed (green) and overexpressed (red) lipids in cells compared to their EVs, while panel (E) Presents the underexpressed (green) and overexpressed (red) lipids in EVs compared to their corresponding cells. The X ‐axis represents the log 2 fold change (log 2 FC), while the Y ‐axis indicates statistical significance (−log 10 p ‐value). Dashed lines indicate significance thresholds ( p < 0.05). (F,G) Pie charts display the relative proportions of lipid classes (lysophospholipids, phospholipids, sphingolipids and sterols) among the lipids identified as significantly up‐regulated in cells (F) or in EVs (G) based on panels (D) and (E) . These charts provide a focused view of the lipid family composition within the subsets of over‐expressed lipids.

Article Snippet: Human uveal melanoma (UM) cell line MP41 (CRL‐3297) was purchased from ATCC (Manassas, Va, USA).

Techniques: Comparison

Journal: Journal of Extracellular Vesicles

Article Title: Lipidome Analysis of Cancer Cells and Their Extracellular Vesicles Reveals Cancer‐Type‐Specific Lipid Signatures and Enables the Design of EV‐Mimetic Liposomes

doi: 10.1002/jev2.70265

Figure Lengend Snippet: Global comparison of lipid profiles across all samples. Figure shows, through clustering and heatmap analyses, a clear separation between cells and EVs, as well as between cancer and non‐cancer models. Each line and its EVs exhibit unique lipid signatures, illustrating the specific metabolic adaptation to each biological context. Brown box (cells and EVs) : (A) Schematic representation that presents the analysis of all samples. Created in https://BioRender.com . (B) PCA illustrating the distribution of all the samples based on their lipidomic profiles. Each point represents a sample, with clustering reflecting the overall lipid composition of cells and EVs. Orange box (cells) : (C) Schematic representation that presents the cell analysis and key information. Created in https://BioRender.com . ( D) PCA plot showing the separation of cancer cells (MP41, MEL270, OMM2.5 and HT29) and non‐cancer cells (CCD‐18Co, BJ) based on lipid profiles. Each point represents a sample, and clustering reflects differences in lipid composition. (E) Venn diagram showing the overlap of lipid species identified in the six cell lines: MP41, MEL270, OMM2.5, HT29 and CCD‐18Co, and BJ. Numbers indicate lipid species unique to each cell line and those shared across multiple cell types. (F) Heatmaps depicting the relative abundance of lipid species shared among the six cell lines. Green indicates lower abundance, while red indicates higher abundance. (G) Pie charts illustrating the relative proportions of lipid classes (lysophospholipids, phospholipids, sphingolipids and sterols) and saturation levels (saturated, monounsaturated and polyunsaturated lipids) among the unique lipid species identified in each cell line. (H) Lists of unique lipids in cells. Blue box (EVs) : (I) Schematic representation that presents the EV analysis and key information. Created in https://BioRender.com . (J) PCA plot showing the separation of EVs derived from cancer cells and non‐cancer cells based on lipid profiles. Each point represents a sample, with clustering indicating compositional differences. (K) Venn diagram showing the overlap of lipid species identified in EVs derived from the six cell lines. Numbers indicate lipid species unique to each EV sample and those shared across multiple EV types. (L) Heatmaps depicting the relative abundance of lipid species shared among EVs from the six cell lines. Green indicates lower abundance, while red indicates higher abundance. (M) Pie charts illustrate the relative proportions of lipid classes and saturation levels among the unique lipid species identified in EVs derived from each cell line. (N) Lists of unique lipids in EVs.

Article Snippet: Human uveal melanoma (UM) cell line MP41 (CRL‐3297) was purchased from ATCC (Manassas, Va, USA).

Techniques: Comparison, Cell Analysis, Derivative Assay

Journal: PLOS Computational Biology

Article Title: CASER: A semi-supervised model with multi-omics data integration prioritizes cancer-associated epigenetic regulator genes

doi: 10.1371/journal.pcbi.1014253

Figure Lengend Snippet: (A) Six predicted cER genes were investigated in SK-mel-2 cell line ( n = 4). (B) Six predicted cER genes were investigated in Caki-1 cell line ( n = 4). Statistical analysis was performed between si-NC and si-Genes. P -values are calculated by One-way analysis of variance followed by Dunnett’s corrections and indicated by star symbols, *, P < 0.05; **, P < 0.01; ***, P < 0.001; ****, P < 0.0001; ns, P > 0.05.

Article Snippet: The human melanoma cell line SK-mel-2, clear cell renal cell carcinoma cell line Caki-1, breast cancer cell line MDA-MB-231, and prostate cancer cell line LNCaP, along with their corresponding complete median, were purchased from Procell Life Science & Technology Co., Ltd. (Wuhan, China).

Techniques: