murine cancer cell lines  (ATCC)

Journal: Cancers

Article Title: An Integrated Immunometabolic Signature Predicts Prognosis and Immunotherapy Response in ccRCC and Identifies UCN -Mediated Immune Evasion as a Therapeutic Vulnerability: Evidence from In Vitro and In Vivo Studies

doi: 10.3390/cancers18091373

Figure Lengend Snippet: The process of identifying differentially expressed IMRGs and molecular subtypes in ccRCC: ( A ) IMRGs that were differentially expressed were denoted by red dots for upregulation and blue dots for downregulation. ( B ) Heatmaps were used to visually represent the top differentially expressed genes. ( C ) A heatmap of the nsNMF consensus matrix was generated to classify ccRCC into two molecular subtypes. ( D ) A PCA plot was applied to show significant differences between clusters. ( E ) The gene expression heatmap shows how the identified IMRGs were expressed across the two molecular subtypes. ( F , G ) In order to make a comparison between the two molecular subtypes, the researcher employed the Kaplan–Meier curve to assess and contrast the OS and PFS.

Article Snippet: Human ccRCC cell line 786-O (Accession Number: CVCL_1051) and mouse ccRCC cell line Renca (CVCL_2174) were obtained from American Type Culture Collection (ATCC) (Manassas, Virginia) and cultured in RPMI 1640 medium (Procell, Wuhan, China) containing 10% fetal bovine serum (Procell, China) and Penicillin–Streptomycin (Procell, China).

Techniques: Generated, Gene Expression, Comparison

Journal: Cancers

Article Title: An Integrated Immunometabolic Signature Predicts Prognosis and Immunotherapy Response in ccRCC and Identifies UCN -Mediated Immune Evasion as a Therapeutic Vulnerability: Evidence from In Vitro and In Vivo Studies

doi: 10.3390/cancers18091373

Figure Lengend Snippet: Comparison of genomic alteration landscapes between the two molecular subtypes. ( A ) Oncoplot demonstrated the 30 most frequently mutated genes in Cluster 1. ( B ) Oncoplot demonstrated the 30 most frequently mutated genes in Cluster 2. ( C ) Heatmap illustrating the co-mutated states of the commonly mutated genes in Cluster 1. ( D ) Heatmap illustrating the co-mutated states of the commonly mutated genes in Cluster 2. ( E ) The boxplot illustrates the distinct tumor mutation frequencies between Cluster 1 and Cluster 2. ( F ) The Kaplan–Meier curve shows the overall survival rates of patients with high and low tumor mutation burdens. ( G ) Multivariate Cox regression analysis of tumor mutation burden (TMB) and immunometabolic clusters. ( H ) Kaplan–Meier survival curves for ccRCC patients stratified by both TMB status (high vs. low) and immunometabolic clusters (C1 vs. C2).

Article Snippet: Human ccRCC cell line 786-O (Accession Number: CVCL_1051) and mouse ccRCC cell line Renca (CVCL_2174) were obtained from American Type Culture Collection (ATCC) (Manassas, Virginia) and cultured in RPMI 1640 medium (Procell, Wuhan, China) containing 10% fetal bovine serum (Procell, China) and Penicillin–Streptomycin (Procell, China).

Techniques: Comparison, Mutagenesis

Journal: Cancers

Article Title: An Integrated Immunometabolic Signature Predicts Prognosis and Immunotherapy Response in ccRCC and Identifies UCN -Mediated Immune Evasion as a Therapeutic Vulnerability: Evidence from In Vitro and In Vivo Studies

doi: 10.3390/cancers18091373

Figure Lengend Snippet: Assessment and confirmation of the predictive performance of the signature in ccRCC. ( A – C ) Scatter plots illustrating the survival status and IMI scores of ccRCC patients in the TCGA training group ( A ), the TCGA testing group ( B ), and the E-MATB-1980 external validation group ( C ). ( D – F ) Kaplan–Meier curves displaying the overall survival situation per IMI scores of the high-IMI group and low-IMI group in the TCGA training group ( D ), the TCGA testing group ( E ), and the E-MATB-1980 external validation group ( F ). ( G – I ) ROC curves demonstrating the predictive performance of IMI with AUC values for 1-year, 3-year, and 5-year OS in ccRCC patients from the TCGA training group ( G ), the TCGA testing group ( H ), and the E-MATB-1980 external validation group ( I ).

Article Snippet: Human ccRCC cell line 786-O (Accession Number: CVCL_1051) and mouse ccRCC cell line Renca (CVCL_2174) were obtained from American Type Culture Collection (ATCC) (Manassas, Virginia) and cultured in RPMI 1640 medium (Procell, Wuhan, China) containing 10% fetal bovine serum (Procell, China) and Penicillin–Streptomycin (Procell, China).

Techniques: Biomarker Discovery

Journal: Cancers

Article Title: An Integrated Immunometabolic Signature Predicts Prognosis and Immunotherapy Response in ccRCC and Identifies UCN -Mediated Immune Evasion as a Therapeutic Vulnerability: Evidence from In Vitro and In Vivo Studies

doi: 10.3390/cancers18091373

Figure Lengend Snippet: Identification of expression trends of nine IMRGs. ( A ) Differences in signature gene expression between high and low IMI groups in the TCGA database. ns, not significant; * p < 0.05; ** p < 0.01; *** p < 0.001; **** p < 0.0001. ( B ) Differences in signature gene expression between normal kidney tissue samples and ccRCC samples in the TCGA database. ( C – K ) The relative expression levels of signature genes between three ccRCC cell lines (786-O, A498, ACHN) and normal renal tubular epithelial cells, HK2. ( L ) The IHC images compared the expression levels of four signature genes between normal renal tissue samples and ccRCC samples in the HPA database ( https://www.proteinatlas.org , accessed on 1 January 2024).

Article Snippet: Human ccRCC cell line 786-O (Accession Number: CVCL_1051) and mouse ccRCC cell line Renca (CVCL_2174) were obtained from American Type Culture Collection (ATCC) (Manassas, Virginia) and cultured in RPMI 1640 medium (Procell, Wuhan, China) containing 10% fetal bovine serum (Procell, China) and Penicillin–Streptomycin (Procell, China).

Techniques: Expressing, Gene Expression

Journal: Cancers

Article Title: An Integrated Immunometabolic Signature Predicts Prognosis and Immunotherapy Response in ccRCC and Identifies UCN -Mediated Immune Evasion as a Therapeutic Vulnerability: Evidence from In Vitro and In Vivo Studies

doi: 10.3390/cancers18091373

Figure Lengend Snippet: Verification of UCN promoting proliferation, migration, and invasion of ccRCC. ( A ) Knockdown of the UCN gene in 786-O and ACHN cells, relative mRNA levels in the negative control (NC) group and three siRNA knockdown groups, respectively. **** p < 0.0001 ( B ) The knockdown effect of three siRNAs on the UCN gene at the protein level in two cell lines. The uncropped blots are shown in . ( C ) The proliferation curves of CCK8 in the control group and the knockdown groups of the two cell lines. Any siRNA group has significant statistical differences from the NC group. ( D , E ) Wound-healing assays in control and knockdown groups of the two cell lines. ( F , G ) Transwell invasion assays in control and knockdown groups of the two cell lines.

Article Snippet: Human ccRCC cell line 786-O (Accession Number: CVCL_1051) and mouse ccRCC cell line Renca (CVCL_2174) were obtained from American Type Culture Collection (ATCC) (Manassas, Virginia) and cultured in RPMI 1640 medium (Procell, Wuhan, China) containing 10% fetal bovine serum (Procell, China) and Penicillin–Streptomycin (Procell, China).

Techniques: Migration, Knockdown, Negative Control, Control

Journal: Cancers

Article Title: An Integrated Immunometabolic Signature Predicts Prognosis and Immunotherapy Response in ccRCC and Identifies UCN -Mediated Immune Evasion as a Therapeutic Vulnerability: Evidence from In Vitro and In Vivo Studies

doi: 10.3390/cancers18091373

Figure Lengend Snippet: UCN regulates the immune microenvironment and promotes ccRCC progression. ( A ) Schematic illustration of the mouse xenograft tumor model experimental design. ( B – E ) Tumor growth analyses demonstrate reduced tumor volume and weight across different experimental groups, with notable suppression in sh UCN +IgG2a and sh UCN +PD-1 groups. ( F ) Gating strategy for tumor-infiltrating lymphocytes. Representative flow plots showing the identification of Live/CD45+ cells, T cells (CD3+), CD4+ and CD8+ subsets, as well as Tregs and PD-1+ cells. ( G ) Flow cytometry analysis unveils substantial alterations in immune cell subsets in the tumor immune microenvironment. ( H , I ) Representative mIHC staining of tumors (green: CD8, red: Foxp3, blue: DAPI; scale bar, 50 μm.) ( I ) The column diagram showing the counts of spots with CD8+ T cells and Tregs in tumor slides. Data presented as Mean ± SEM. One-way ANOVA was used in ( E , G , I ). * p < 0.05; ** p < 0.01; *** p < 0.001; **** p < 0.0001.

Article Snippet: Human ccRCC cell line 786-O (Accession Number: CVCL_1051) and mouse ccRCC cell line Renca (CVCL_2174) were obtained from American Type Culture Collection (ATCC) (Manassas, Virginia) and cultured in RPMI 1640 medium (Procell, Wuhan, China) containing 10% fetal bovine serum (Procell, China) and Penicillin–Streptomycin (Procell, China).

Techniques: Flow Cytometry, Staining