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hgsoc cell lines sk ov 3  (ATCC)


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    ATCC hgsoc cell lines sk ov 3
    Genome-wide landscape and locus-specific analyses of EOC GWAS signals. Manhattan plots of subtype-specific GWAS signals in EOC from the Dareng et al. (A) and Phelan et al. (B) studies. In each panel, Manhattan plots are ordered from top to bottom for <t>HGSOC,</t> LGSOC, ENOC, OCCC, and MOC. The horizontal dashed line denotes the genome-wide significance threshold ( P < 5 × 10⁻⁸). (C) Cross-cohort genetic landscape. Circos plot displays lead risk loci and mapped genes from the Dareng et al. (inner ring) and Phelan et al. (middle ring) GWAS. Colors represent EOC subtypes. The outer ring shows chromosome ideograms. For each subtype, the top five genes, selected by a multi-step prioritization ( P < 1 × 10⁻⁵ and pLI > 0.9), are labeled. Cross-subtype genes are highlighted in black. (D) Upset plot showing the number of genome-wide significant lead risk loci identified by FUMA across cohorts and EOC subtypes. (E) Regional association plot for HGSOC on chromosome 22. The -log 10 ( P- value) for each SNP (left Y-axis) is plotted against chromosomal position (X-axis); points are colored by pairwise LD (r²) with lead SNP rs6005807 (1000 Genomes EUR, EUR panel). Annotated genes are shown below. (F) LocusCompare plot illustrating colocalization between GWAS and cis-pQTL signals around rs6005807. Each point represents an SNP, with –log 10 ( P- value) for GWAS on the X-axis and for cis-pQTL on the Y-axis; points are colored by LD (r²) with the lead SNP.
    Hgsoc Cell Lines Sk Ov 3, supplied by ATCC, used in various techniques. Bioz Stars score: 99/100, based on 7604 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/hgsoc+cell+lines+sk+ov+3/pmc13089033-32-1-5?v=ATCC
    Average 99 stars, based on 7604 article reviews
    hgsoc cell lines sk ov 3 - by Bioz Stars, 2026-08
    99/100 stars

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    1) Product Images from "Unmasking FCGR2B as a high-grade serous ovarian cancer specific marker of immune suppression and tumor progression through multi-omics mining"

    Article Title: Unmasking FCGR2B as a high-grade serous ovarian cancer specific marker of immune suppression and tumor progression through multi-omics mining

    Journal: Translational Oncology

    doi: 10.1016/j.tranon.2026.102748

    Genome-wide landscape and locus-specific analyses of EOC GWAS signals. Manhattan plots of subtype-specific GWAS signals in EOC from the Dareng et al. (A) and Phelan et al. (B) studies. In each panel, Manhattan plots are ordered from top to bottom for HGSOC, LGSOC, ENOC, OCCC, and MOC. The horizontal dashed line denotes the genome-wide significance threshold ( P < 5 × 10⁻⁸). (C) Cross-cohort genetic landscape. Circos plot displays lead risk loci and mapped genes from the Dareng et al. (inner ring) and Phelan et al. (middle ring) GWAS. Colors represent EOC subtypes. The outer ring shows chromosome ideograms. For each subtype, the top five genes, selected by a multi-step prioritization ( P < 1 × 10⁻⁵ and pLI > 0.9), are labeled. Cross-subtype genes are highlighted in black. (D) Upset plot showing the number of genome-wide significant lead risk loci identified by FUMA across cohorts and EOC subtypes. (E) Regional association plot for HGSOC on chromosome 22. The -log 10 ( P- value) for each SNP (left Y-axis) is plotted against chromosomal position (X-axis); points are colored by pairwise LD (r²) with lead SNP rs6005807 (1000 Genomes EUR, EUR panel). Annotated genes are shown below. (F) LocusCompare plot illustrating colocalization between GWAS and cis-pQTL signals around rs6005807. Each point represents an SNP, with –log 10 ( P- value) for GWAS on the X-axis and for cis-pQTL on the Y-axis; points are colored by LD (r²) with the lead SNP.
    Figure Legend Snippet: Genome-wide landscape and locus-specific analyses of EOC GWAS signals. Manhattan plots of subtype-specific GWAS signals in EOC from the Dareng et al. (A) and Phelan et al. (B) studies. In each panel, Manhattan plots are ordered from top to bottom for HGSOC, LGSOC, ENOC, OCCC, and MOC. The horizontal dashed line denotes the genome-wide significance threshold ( P < 5 × 10⁻⁸). (C) Cross-cohort genetic landscape. Circos plot displays lead risk loci and mapped genes from the Dareng et al. (inner ring) and Phelan et al. (middle ring) GWAS. Colors represent EOC subtypes. The outer ring shows chromosome ideograms. For each subtype, the top five genes, selected by a multi-step prioritization ( P < 1 × 10⁻⁵ and pLI > 0.9), are labeled. Cross-subtype genes are highlighted in black. (D) Upset plot showing the number of genome-wide significant lead risk loci identified by FUMA across cohorts and EOC subtypes. (E) Regional association plot for HGSOC on chromosome 22. The -log 10 ( P- value) for each SNP (left Y-axis) is plotted against chromosomal position (X-axis); points are colored by pairwise LD (r²) with lead SNP rs6005807 (1000 Genomes EUR, EUR panel). Annotated genes are shown below. (F) LocusCompare plot illustrating colocalization between GWAS and cis-pQTL signals around rs6005807. Each point represents an SNP, with –log 10 ( P- value) for GWAS on the X-axis and for cis-pQTL on the Y-axis; points are colored by LD (r²) with the lead SNP.

    Techniques Used: Genome Wide, Labeling

    FCGR2B expression correlates with poor prognosis and aggressive phenotypes in HGSOC. (A) Expression of FCGR2B in TCGA ovarian tumors (TCGA-OV, n = 426) versus normal ovarian tissues from GTEx (n = 88), shown as log2(TPM + 1). (B) Kaplan–Meier curves for PFS in GEO-derived HGSOC cohorts (n = 102), stratified by median expression. (C) Validation of PFS in a meta-cohort of 1435 OC samples. (D–F) Clinical associations of FCGR2B expression with tumor grade (D), lymph node invasion (E), and venous invasion (F) using the BEST database. (G) GSEA identifies the five pathways that are significantly enriched in samples with high FCGR2B expression.
    Figure Legend Snippet: FCGR2B expression correlates with poor prognosis and aggressive phenotypes in HGSOC. (A) Expression of FCGR2B in TCGA ovarian tumors (TCGA-OV, n = 426) versus normal ovarian tissues from GTEx (n = 88), shown as log2(TPM + 1). (B) Kaplan–Meier curves for PFS in GEO-derived HGSOC cohorts (n = 102), stratified by median expression. (C) Validation of PFS in a meta-cohort of 1435 OC samples. (D–F) Clinical associations of FCGR2B expression with tumor grade (D), lymph node invasion (E), and venous invasion (F) using the BEST database. (G) GSEA identifies the five pathways that are significantly enriched in samples with high FCGR2B expression.

    Techniques Used: Expressing, Derivative Assay, Biomarker Discovery

    FCGR2B expression defines an immunosuppressive TME in HGSOC. (A) ssGSEA-based immune infiltration analysis across 28 immune cell types. Δ = High - Low. (B) CIBERSORT-based macrophage-focused immune deconvolution reveals distinct immune landscapes between FCGR2B -High and FCGR2B -Low tumors. (C) Fluorescence images (scale bar, 50 μm) of FCGR2B (red), CD14 (green), CD68 (yellow), and the corresponding merged image. (D-E) Quantitative analysis of FCGR2B co-localization with CD14 (D) and CD68 (E). Left: box plots comparing co-localization levels between FCGR2B-High and FCGR2B-Low tumors (defined by the median FCGR2B H-score; Wilcoxon rank-sum test). Right: scatter plots showing correlations between FCGR2B and marker H-scores across all HGSOC samples (Spearman’s rho). (F) FCGR2B protein expression in HGSOC cell lines (SKOV3 and OVCAR3) and the cell line THP-1, as detected by WB assays. (G) FCGR2B protein expression in THP-1 cells transfected with Si-FCGR2B or control siRNA, as detected by WB assays. (H) Effect of FCGR2B knockdown on macrophage M2 polarization (CD206⁺/CD68⁺) under SKOV3 (HGSOC) co-culture conditions, assessed by flow cytometry. (I) Effect of FCGR2B knockdown on macrophage phagocytosis (CD68⁺/CFSE⁺) of SKOV3 cells under co-culture conditions, analyzed by flow cytometry. Statistical significance was determined using a two-tailed unpaired Student’s t -test; exact P values are indicated within the figure ( P = 0.0001, t = 14.35 for H; P = 0.0013, t = 7.976 for I; n =3, df = 4).
    Figure Legend Snippet: FCGR2B expression defines an immunosuppressive TME in HGSOC. (A) ssGSEA-based immune infiltration analysis across 28 immune cell types. Δ = High - Low. (B) CIBERSORT-based macrophage-focused immune deconvolution reveals distinct immune landscapes between FCGR2B -High and FCGR2B -Low tumors. (C) Fluorescence images (scale bar, 50 μm) of FCGR2B (red), CD14 (green), CD68 (yellow), and the corresponding merged image. (D-E) Quantitative analysis of FCGR2B co-localization with CD14 (D) and CD68 (E). Left: box plots comparing co-localization levels between FCGR2B-High and FCGR2B-Low tumors (defined by the median FCGR2B H-score; Wilcoxon rank-sum test). Right: scatter plots showing correlations between FCGR2B and marker H-scores across all HGSOC samples (Spearman’s rho). (F) FCGR2B protein expression in HGSOC cell lines (SKOV3 and OVCAR3) and the cell line THP-1, as detected by WB assays. (G) FCGR2B protein expression in THP-1 cells transfected with Si-FCGR2B or control siRNA, as detected by WB assays. (H) Effect of FCGR2B knockdown on macrophage M2 polarization (CD206⁺/CD68⁺) under SKOV3 (HGSOC) co-culture conditions, assessed by flow cytometry. (I) Effect of FCGR2B knockdown on macrophage phagocytosis (CD68⁺/CFSE⁺) of SKOV3 cells under co-culture conditions, analyzed by flow cytometry. Statistical significance was determined using a two-tailed unpaired Student’s t -test; exact P values are indicated within the figure ( P = 0.0001, t = 14.35 for H; P = 0.0013, t = 7.976 for I; n =3, df = 4).

    Techniques Used: Expressing, Fluorescence, Marker, Transfection, Control, Knockdown, Co-Culture Assay, Flow Cytometry, Two Tailed Test

    FCGR2B-mediated transcriptomic alterations and its impact on HGSOC cell survival. (A) Myeloid-lineage-specific drug sensitivity analysis across DepMap cell lines. The volcano plot shows compounds whose sensitivity (AUC) significantly correlates with FCGR2B expression ( P < 0.05, r < -0.3). The top negatively correlated drug is labeled. (B) Correlation between FCGR2B mRNA expression (log 2 [TPM + 1]) and sensitivity (AUC) to the ARRY-886 (GDSC1:1062) across 24 myeloid-derived cell lines. (C) Volcano plot showing differentially expressed genes in FCGR2B-knockdown versus control macrophages. Upregulated and downregulated genes are highlighted. (D) KEGG pathway enrichment analysis of differentially expressed genes. (E) GSEA of the TNF-α signaling via NF-κB hallmark pathway in FCGR2B-knockdown versus control macrophages. (F) Proliferation assay of SKOV3 cells treated with CM derived from Si-NC or Si-FCGR2B transfected macrophages, assessed by CCK-8 assay. (G) Flow cytometric analysis and quantification of SKOV3 cell apoptosis following treatment with the indicated macrophage CM. *** P < 0.001, **** P < 0.0001 by ANOVA (F) or Student's t -test (G).
    Figure Legend Snippet: FCGR2B-mediated transcriptomic alterations and its impact on HGSOC cell survival. (A) Myeloid-lineage-specific drug sensitivity analysis across DepMap cell lines. The volcano plot shows compounds whose sensitivity (AUC) significantly correlates with FCGR2B expression ( P < 0.05, r < -0.3). The top negatively correlated drug is labeled. (B) Correlation between FCGR2B mRNA expression (log 2 [TPM + 1]) and sensitivity (AUC) to the ARRY-886 (GDSC1:1062) across 24 myeloid-derived cell lines. (C) Volcano plot showing differentially expressed genes in FCGR2B-knockdown versus control macrophages. Upregulated and downregulated genes are highlighted. (D) KEGG pathway enrichment analysis of differentially expressed genes. (E) GSEA of the TNF-α signaling via NF-κB hallmark pathway in FCGR2B-knockdown versus control macrophages. (F) Proliferation assay of SKOV3 cells treated with CM derived from Si-NC or Si-FCGR2B transfected macrophages, assessed by CCK-8 assay. (G) Flow cytometric analysis and quantification of SKOV3 cell apoptosis following treatment with the indicated macrophage CM. *** P < 0.001, **** P < 0.0001 by ANOVA (F) or Student's t -test (G).

    Techniques Used: Expressing, Labeling, Derivative Assay, Knockdown, Control, Proliferation Assay, Transfection, CCK-8 Assay



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    ATCC hgsoc cell lines sk ov 3
    Genome-wide landscape and locus-specific analyses of EOC GWAS signals. Manhattan plots of subtype-specific GWAS signals in EOC from the Dareng et al. (A) and Phelan et al. (B) studies. In each panel, Manhattan plots are ordered from top to bottom for <t>HGSOC,</t> LGSOC, ENOC, OCCC, and MOC. The horizontal dashed line denotes the genome-wide significance threshold ( P < 5 × 10⁻⁸). (C) Cross-cohort genetic landscape. Circos plot displays lead risk loci and mapped genes from the Dareng et al. (inner ring) and Phelan et al. (middle ring) GWAS. Colors represent EOC subtypes. The outer ring shows chromosome ideograms. For each subtype, the top five genes, selected by a multi-step prioritization ( P < 1 × 10⁻⁵ and pLI > 0.9), are labeled. Cross-subtype genes are highlighted in black. (D) Upset plot showing the number of genome-wide significant lead risk loci identified by FUMA across cohorts and EOC subtypes. (E) Regional association plot for HGSOC on chromosome 22. The -log 10 ( P- value) for each SNP (left Y-axis) is plotted against chromosomal position (X-axis); points are colored by pairwise LD (r²) with lead SNP rs6005807 (1000 Genomes EUR, EUR panel). Annotated genes are shown below. (F) LocusCompare plot illustrating colocalization between GWAS and cis-pQTL signals around rs6005807. Each point represents an SNP, with –log 10 ( P- value) for GWAS on the X-axis and for cis-pQTL on the Y-axis; points are colored by LD (r²) with the lead SNP.
    Hgsoc Cell Lines Sk Ov 3, supplied by ATCC, used in various techniques. Bioz Stars score: 99/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/hgsoc+cell+lines+sk+ov+3/pmc13089033-32-1-5?v=ATCC
    Average 99 stars, based on 1 article reviews
    hgsoc cell lines sk ov 3 - by Bioz Stars, 2026-08
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    99
    ATCC human hgsoc cell lines
    Genome-wide landscape and locus-specific analyses of EOC GWAS signals. Manhattan plots of subtype-specific GWAS signals in EOC from the Dareng et al. (A) and Phelan et al. (B) studies. In each panel, Manhattan plots are ordered from top to bottom for <t>HGSOC,</t> LGSOC, ENOC, OCCC, and MOC. The horizontal dashed line denotes the genome-wide significance threshold ( P < 5 × 10⁻⁸). (C) Cross-cohort genetic landscape. Circos plot displays lead risk loci and mapped genes from the Dareng et al. (inner ring) and Phelan et al. (middle ring) GWAS. Colors represent EOC subtypes. The outer ring shows chromosome ideograms. For each subtype, the top five genes, selected by a multi-step prioritization ( P < 1 × 10⁻⁵ and pLI > 0.9), are labeled. Cross-subtype genes are highlighted in black. (D) Upset plot showing the number of genome-wide significant lead risk loci identified by FUMA across cohorts and EOC subtypes. (E) Regional association plot for HGSOC on chromosome 22. The -log 10 ( P- value) for each SNP (left Y-axis) is plotted against chromosomal position (X-axis); points are colored by pairwise LD (r²) with lead SNP rs6005807 (1000 Genomes EUR, EUR panel). Annotated genes are shown below. (F) LocusCompare plot illustrating colocalization between GWAS and cis-pQTL signals around rs6005807. Each point represents an SNP, with –log 10 ( P- value) for GWAS on the X-axis and for cis-pQTL on the Y-axis; points are colored by LD (r²) with the lead SNP.
    Human Hgsoc Cell Lines, supplied by ATCC, used in various techniques. Bioz Stars score: 99/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/hgsoc+cell+lines+sk+ov+3/pm38388849-40-0-10?v=ATCC
    Average 99 stars, based on 1 article reviews
    human hgsoc cell lines - by Bioz Stars, 2026-08
    99/100 stars
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    Image Search Results


    Genome-wide landscape and locus-specific analyses of EOC GWAS signals. Manhattan plots of subtype-specific GWAS signals in EOC from the Dareng et al. (A) and Phelan et al. (B) studies. In each panel, Manhattan plots are ordered from top to bottom for HGSOC, LGSOC, ENOC, OCCC, and MOC. The horizontal dashed line denotes the genome-wide significance threshold ( P < 5 × 10⁻⁸). (C) Cross-cohort genetic landscape. Circos plot displays lead risk loci and mapped genes from the Dareng et al. (inner ring) and Phelan et al. (middle ring) GWAS. Colors represent EOC subtypes. The outer ring shows chromosome ideograms. For each subtype, the top five genes, selected by a multi-step prioritization ( P < 1 × 10⁻⁵ and pLI > 0.9), are labeled. Cross-subtype genes are highlighted in black. (D) Upset plot showing the number of genome-wide significant lead risk loci identified by FUMA across cohorts and EOC subtypes. (E) Regional association plot for HGSOC on chromosome 22. The -log 10 ( P- value) for each SNP (left Y-axis) is plotted against chromosomal position (X-axis); points are colored by pairwise LD (r²) with lead SNP rs6005807 (1000 Genomes EUR, EUR panel). Annotated genes are shown below. (F) LocusCompare plot illustrating colocalization between GWAS and cis-pQTL signals around rs6005807. Each point represents an SNP, with –log 10 ( P- value) for GWAS on the X-axis and for cis-pQTL on the Y-axis; points are colored by LD (r²) with the lead SNP.

    Journal: Translational Oncology

    Article Title: Unmasking FCGR2B as a high-grade serous ovarian cancer specific marker of immune suppression and tumor progression through multi-omics mining

    doi: 10.1016/j.tranon.2026.102748

    Figure Lengend Snippet: Genome-wide landscape and locus-specific analyses of EOC GWAS signals. Manhattan plots of subtype-specific GWAS signals in EOC from the Dareng et al. (A) and Phelan et al. (B) studies. In each panel, Manhattan plots are ordered from top to bottom for HGSOC, LGSOC, ENOC, OCCC, and MOC. The horizontal dashed line denotes the genome-wide significance threshold ( P < 5 × 10⁻⁸). (C) Cross-cohort genetic landscape. Circos plot displays lead risk loci and mapped genes from the Dareng et al. (inner ring) and Phelan et al. (middle ring) GWAS. Colors represent EOC subtypes. The outer ring shows chromosome ideograms. For each subtype, the top five genes, selected by a multi-step prioritization ( P < 1 × 10⁻⁵ and pLI > 0.9), are labeled. Cross-subtype genes are highlighted in black. (D) Upset plot showing the number of genome-wide significant lead risk loci identified by FUMA across cohorts and EOC subtypes. (E) Regional association plot for HGSOC on chromosome 22. The -log 10 ( P- value) for each SNP (left Y-axis) is plotted against chromosomal position (X-axis); points are colored by pairwise LD (r²) with lead SNP rs6005807 (1000 Genomes EUR, EUR panel). Annotated genes are shown below. (F) LocusCompare plot illustrating colocalization between GWAS and cis-pQTL signals around rs6005807. Each point represents an SNP, with –log 10 ( P- value) for GWAS on the X-axis and for cis-pQTL on the Y-axis; points are colored by LD (r²) with the lead SNP.

    Article Snippet: The HGSOC cell lines SK-OV-3 (ATCC® HTB-77TM) and OVCAR-3 (ATCC® HTB-161TM), as well as the human monocytic cell line THP-1 (ATCC® TIB-202TM), were obtained from the American Type Culture Collection and cultured under standard conditions at 37 °C with 5% CO2.

    Techniques: Genome Wide, Labeling

    FCGR2B expression correlates with poor prognosis and aggressive phenotypes in HGSOC. (A) Expression of FCGR2B in TCGA ovarian tumors (TCGA-OV, n = 426) versus normal ovarian tissues from GTEx (n = 88), shown as log2(TPM + 1). (B) Kaplan–Meier curves for PFS in GEO-derived HGSOC cohorts (n = 102), stratified by median expression. (C) Validation of PFS in a meta-cohort of 1435 OC samples. (D–F) Clinical associations of FCGR2B expression with tumor grade (D), lymph node invasion (E), and venous invasion (F) using the BEST database. (G) GSEA identifies the five pathways that are significantly enriched in samples with high FCGR2B expression.

    Journal: Translational Oncology

    Article Title: Unmasking FCGR2B as a high-grade serous ovarian cancer specific marker of immune suppression and tumor progression through multi-omics mining

    doi: 10.1016/j.tranon.2026.102748

    Figure Lengend Snippet: FCGR2B expression correlates with poor prognosis and aggressive phenotypes in HGSOC. (A) Expression of FCGR2B in TCGA ovarian tumors (TCGA-OV, n = 426) versus normal ovarian tissues from GTEx (n = 88), shown as log2(TPM + 1). (B) Kaplan–Meier curves for PFS in GEO-derived HGSOC cohorts (n = 102), stratified by median expression. (C) Validation of PFS in a meta-cohort of 1435 OC samples. (D–F) Clinical associations of FCGR2B expression with tumor grade (D), lymph node invasion (E), and venous invasion (F) using the BEST database. (G) GSEA identifies the five pathways that are significantly enriched in samples with high FCGR2B expression.

    Article Snippet: The HGSOC cell lines SK-OV-3 (ATCC® HTB-77TM) and OVCAR-3 (ATCC® HTB-161TM), as well as the human monocytic cell line THP-1 (ATCC® TIB-202TM), were obtained from the American Type Culture Collection and cultured under standard conditions at 37 °C with 5% CO2.

    Techniques: Expressing, Derivative Assay, Biomarker Discovery

    FCGR2B expression defines an immunosuppressive TME in HGSOC. (A) ssGSEA-based immune infiltration analysis across 28 immune cell types. Δ = High - Low. (B) CIBERSORT-based macrophage-focused immune deconvolution reveals distinct immune landscapes between FCGR2B -High and FCGR2B -Low tumors. (C) Fluorescence images (scale bar, 50 μm) of FCGR2B (red), CD14 (green), CD68 (yellow), and the corresponding merged image. (D-E) Quantitative analysis of FCGR2B co-localization with CD14 (D) and CD68 (E). Left: box plots comparing co-localization levels between FCGR2B-High and FCGR2B-Low tumors (defined by the median FCGR2B H-score; Wilcoxon rank-sum test). Right: scatter plots showing correlations between FCGR2B and marker H-scores across all HGSOC samples (Spearman’s rho). (F) FCGR2B protein expression in HGSOC cell lines (SKOV3 and OVCAR3) and the cell line THP-1, as detected by WB assays. (G) FCGR2B protein expression in THP-1 cells transfected with Si-FCGR2B or control siRNA, as detected by WB assays. (H) Effect of FCGR2B knockdown on macrophage M2 polarization (CD206⁺/CD68⁺) under SKOV3 (HGSOC) co-culture conditions, assessed by flow cytometry. (I) Effect of FCGR2B knockdown on macrophage phagocytosis (CD68⁺/CFSE⁺) of SKOV3 cells under co-culture conditions, analyzed by flow cytometry. Statistical significance was determined using a two-tailed unpaired Student’s t -test; exact P values are indicated within the figure ( P = 0.0001, t = 14.35 for H; P = 0.0013, t = 7.976 for I; n =3, df = 4).

    Journal: Translational Oncology

    Article Title: Unmasking FCGR2B as a high-grade serous ovarian cancer specific marker of immune suppression and tumor progression through multi-omics mining

    doi: 10.1016/j.tranon.2026.102748

    Figure Lengend Snippet: FCGR2B expression defines an immunosuppressive TME in HGSOC. (A) ssGSEA-based immune infiltration analysis across 28 immune cell types. Δ = High - Low. (B) CIBERSORT-based macrophage-focused immune deconvolution reveals distinct immune landscapes between FCGR2B -High and FCGR2B -Low tumors. (C) Fluorescence images (scale bar, 50 μm) of FCGR2B (red), CD14 (green), CD68 (yellow), and the corresponding merged image. (D-E) Quantitative analysis of FCGR2B co-localization with CD14 (D) and CD68 (E). Left: box plots comparing co-localization levels between FCGR2B-High and FCGR2B-Low tumors (defined by the median FCGR2B H-score; Wilcoxon rank-sum test). Right: scatter plots showing correlations between FCGR2B and marker H-scores across all HGSOC samples (Spearman’s rho). (F) FCGR2B protein expression in HGSOC cell lines (SKOV3 and OVCAR3) and the cell line THP-1, as detected by WB assays. (G) FCGR2B protein expression in THP-1 cells transfected with Si-FCGR2B or control siRNA, as detected by WB assays. (H) Effect of FCGR2B knockdown on macrophage M2 polarization (CD206⁺/CD68⁺) under SKOV3 (HGSOC) co-culture conditions, assessed by flow cytometry. (I) Effect of FCGR2B knockdown on macrophage phagocytosis (CD68⁺/CFSE⁺) of SKOV3 cells under co-culture conditions, analyzed by flow cytometry. Statistical significance was determined using a two-tailed unpaired Student’s t -test; exact P values are indicated within the figure ( P = 0.0001, t = 14.35 for H; P = 0.0013, t = 7.976 for I; n =3, df = 4).

    Article Snippet: The HGSOC cell lines SK-OV-3 (ATCC® HTB-77TM) and OVCAR-3 (ATCC® HTB-161TM), as well as the human monocytic cell line THP-1 (ATCC® TIB-202TM), were obtained from the American Type Culture Collection and cultured under standard conditions at 37 °C with 5% CO2.

    Techniques: Expressing, Fluorescence, Marker, Transfection, Control, Knockdown, Co-Culture Assay, Flow Cytometry, Two Tailed Test

    FCGR2B-mediated transcriptomic alterations and its impact on HGSOC cell survival. (A) Myeloid-lineage-specific drug sensitivity analysis across DepMap cell lines. The volcano plot shows compounds whose sensitivity (AUC) significantly correlates with FCGR2B expression ( P < 0.05, r < -0.3). The top negatively correlated drug is labeled. (B) Correlation between FCGR2B mRNA expression (log 2 [TPM + 1]) and sensitivity (AUC) to the ARRY-886 (GDSC1:1062) across 24 myeloid-derived cell lines. (C) Volcano plot showing differentially expressed genes in FCGR2B-knockdown versus control macrophages. Upregulated and downregulated genes are highlighted. (D) KEGG pathway enrichment analysis of differentially expressed genes. (E) GSEA of the TNF-α signaling via NF-κB hallmark pathway in FCGR2B-knockdown versus control macrophages. (F) Proliferation assay of SKOV3 cells treated with CM derived from Si-NC or Si-FCGR2B transfected macrophages, assessed by CCK-8 assay. (G) Flow cytometric analysis and quantification of SKOV3 cell apoptosis following treatment with the indicated macrophage CM. *** P < 0.001, **** P < 0.0001 by ANOVA (F) or Student's t -test (G).

    Journal: Translational Oncology

    Article Title: Unmasking FCGR2B as a high-grade serous ovarian cancer specific marker of immune suppression and tumor progression through multi-omics mining

    doi: 10.1016/j.tranon.2026.102748

    Figure Lengend Snippet: FCGR2B-mediated transcriptomic alterations and its impact on HGSOC cell survival. (A) Myeloid-lineage-specific drug sensitivity analysis across DepMap cell lines. The volcano plot shows compounds whose sensitivity (AUC) significantly correlates with FCGR2B expression ( P < 0.05, r < -0.3). The top negatively correlated drug is labeled. (B) Correlation between FCGR2B mRNA expression (log 2 [TPM + 1]) and sensitivity (AUC) to the ARRY-886 (GDSC1:1062) across 24 myeloid-derived cell lines. (C) Volcano plot showing differentially expressed genes in FCGR2B-knockdown versus control macrophages. Upregulated and downregulated genes are highlighted. (D) KEGG pathway enrichment analysis of differentially expressed genes. (E) GSEA of the TNF-α signaling via NF-κB hallmark pathway in FCGR2B-knockdown versus control macrophages. (F) Proliferation assay of SKOV3 cells treated with CM derived from Si-NC or Si-FCGR2B transfected macrophages, assessed by CCK-8 assay. (G) Flow cytometric analysis and quantification of SKOV3 cell apoptosis following treatment with the indicated macrophage CM. *** P < 0.001, **** P < 0.0001 by ANOVA (F) or Student's t -test (G).

    Article Snippet: The HGSOC cell lines SK-OV-3 (ATCC® HTB-77TM) and OVCAR-3 (ATCC® HTB-161TM), as well as the human monocytic cell line THP-1 (ATCC® TIB-202TM), were obtained from the American Type Culture Collection and cultured under standard conditions at 37 °C with 5% CO2.

    Techniques: Expressing, Labeling, Derivative Assay, Knockdown, Control, Proliferation Assay, Transfection, CCK-8 Assay