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pmid:39684640

Integrated Analysis of Single-Cell and Bulk RNA Sequencing Reveals HSD3B7 as a Prognostic Biomarker and Potential Therapeutic Target in ccRCC.

Guicen Liu · Qichen Liu · Jiawei Zhao · Ruyue Luo · Yuan Wan · Zhongli Luo

International journal of molecular sciences · 2024 doi:10.3390/ijms252312929

Paper

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Experiment

complete

Data

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title
Integrated Analysis of Single-Cell and Bulk RNA Sequencing Reveals HSD3B7 as a Prognostic Biomarker and Potential Therapeutic Target in ccRCC.
doi
10.3390/ijms252312929
pmid
39684640
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Guicen Liu
[1]
Qichen Liu
[2]
Jiawei Zhao
[3]
Ruyue Luo
[4]
Yuan Wan
[5]
Zhongli Luo
journal
International journal of molecular sciences
year
2024
abstract
Clear cell renal cell carcinoma (ccRCC) is the most common kidney malignancy, with a poor prognosis for advanced-stage patients. Identifying key biomarkers involved in tumor progression is crucial for improving treatment outcomes. In this study, we employed an integrated approach combining single-cell RNA sequencing (scRNA-seq) and bulk RNA sequencing (bulk RNA-seq) to identify biomarkers associated with ccRCC progression and prognosis. Single-cell transcriptomic data were obtained from publicly available datasets, and genes related to tumor progression were screened using Monocle2. Bulk RNA-seq data for ccRCC were retrieved from The Cancer Genome Atlas (TCGA) and integrated with scRNA-seq data to explore tumor heterogeneity. We identified 3 beta-hydroxy steroid dehydrogenase type 7 (HSD3B7) as a candidate biomarker for ccRCC, associated with poor overall survival, disease-specific survival, and progression-free interval. Elevated HSD3B7 expression correlated with aggressive clinical features such as advanced TNM stages, histologic grades, and metastasis. Functional studies demonstrated that HSD3B7 promotes cell proliferation, migration, and invasion in vitro, while its silencing significantly inhibits tumor growth in vivo. Our findings reveal that HSD3B7 is a novel biomarker for ccRCC, providing insights into its role in tumor progression and potential as a target for therapy. This study highlights the value of integrating scRNA-seq and bulk RNA-seq data to uncover key regulators of tumor biology and lays the foundation for developing personalized therapeutic strategies for ccRCC patients.
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Univariate Cox regression analysis was performed using the R package “survival” (v3.3.1, https://cran.r-project.org/web/packages/survival/index.html, accessed on 24 November 2023) and “survminer” (v0.4.9, https://cran.r-project.org/web/packages/survminer/index.html, accessed on 24 November 2023) to evaluate and visualize the association between patient survival and gene expression.
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sections[12] "4.3. Processing of Bulk RNA-seq Data" paragraph 2
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Univariate Cox regression analysis was performed using the R package “survival” (v3.3.1, https://cran.r-project.org/web/packages/survival/index.html, accessed on 24 November 2023) and “survminer” (v0.4.9, https://cran.r-project.org/web/packages/survminer/index.html, accessed on 24 November 2023) to evaluate and visualize the association between patient survival and gene expression.
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Publicly available datasets were analyzed in this study. scRNA-seq datasets (GSE131685, GSE152938, GSE156632, and GSE159115) were obtained from the Gene Expression Omnibus (GEO; https://www.ncbi.nlm.nih.gov/geo (accessed on 28 October 2024)). The ccRCC bulk RNA-seq and clinical data were retrieved from the Genomic Data Commons (GDC) data portal (https://portal.gdc.cancer.gov/ (accessed on 28 October 2024)).
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Figure 4A shows that patients with high HSD3B7 expression had significantly poorer overall survival (OS; HR = 1.71, 95% CI: 1.25–2.32, p < 0.001), disease-specific survival (DSS; HR = 1.75, 95% CI: 1.18–2.59, p = 0.005), and progress free interval (PFI; HR = 1.70, 95% CI: 1.23–2.34, p = 0.001).
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Figure 4A shows that patients with high HSD3B7 expression had significantly poorer overall survival (OS; HR = 1.71, 95% CI: 1.25–2.32, p < 0.001), disease-specific survival (DSS; HR = 1.75, 95% CI: 1.18–2.59, p = 0.005), and progress free interval (PFI; HR = 1.70, 95% CI: 1.23–2.34, p = 0.001).
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sections[5] "2.3. HSD3B7 as a Novel Biomarker for Prognosis and Clinical Features" paragraph 2
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Figure 4A shows that patients with high HSD3B7 expression had significantly poorer overall survival (OS; HR = 1.71, 95% CI: 1.25–2.32, p < 0.001), disease-specific survival (DSS; HR = 1.75, 95% CI: 1.18–2.59, p = 0.005), and progress free interval (PFI; HR = 1.70, 95% CI: 1.23–2.34, p = 0.001).
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Figure 4A shows that patients with high HSD3B7 expression had significantly poorer overall survival (OS; HR = 1.71, 95% CI: 1.25–2.32, p < 0.001), disease-specific survival (DSS; HR = 1.75, 95% CI: 1.18–2.59, p = 0.005), and progress free interval (PFI; HR = 1.70, 95% CI: 1.23–2.34, p = 0.001).
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Single-Cell RNA Sequencing in Multiple Pathologic Types of Renal Cell Carcinoma Revealed Novel Potential Tumor-Specific Markers
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Integrated Analysis of Single-Cell and Bulk RNA Sequencing Reveals HSD3B7 as a Prognostic Biomarker and
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ng (scRNA-seq) and bulk RNA sequencing (bulk RNA-seq) to identify biomarkers associated with ccRC
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the value of integrating scRNA-seq and bulk RNA-seq data to uncover key regulators of tumor biol
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[0]
ilencing significantly inhibits tumor growth in vivo. Our findings reveal that HSD3B7 is a novel
[1]
Center of Chongqing Medical University. The mice were acclimated for two weeks under specific path
[2]
r measurement. After 4 weeks post-injection, mice were administered D-luciferin potassium salt, whi
[3]
and luciferase activity. After imaging, the mice were euthanized to excise the tumors, which were
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Materials and Methods 4.4. Cell Culture and Transfection All cell lines used in this study, including
[1]
down experiments, siRNA targeting HSD3B7 was transfected into 769-P cells using Lipofectamine 3000 (T
[2]
vector, and the overexpression plasmids were transfected into A498 cells using the same transfection
[3]
e transfected into A498 cells using the same transfection protocol. The siRNAs and HSD3B7 overexpressi
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10% FBS and 1% penicillin–streptomycin. All cell lines were maintained in a humidified incubator at 37 °C with 5% C
[1]
cell lines. A498, ACHN, and HK-2 cells were cultured in Dulbecco’s Modified Eagle Medium (DMEM, Gibc
[2]
cin (Gibco, MA, USA), while 769-P cells were cultured in RPMI-1640 medium (Gibco, MA, USA) containing
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cox_ph
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Univariate Cox regression analysis was performed using the R package “survival” (v3.3.1, https://cran.r-project.org/web/packages/survival/index.html, accessed on 24 November 2023) and “survminer” (v0.4.9, https://cran.r-project.org/web/packages/survminer/index.html, accessed on 24 November 2023) to evaluate and visualize the association between patient survival and gene expression.
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Complete file
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Bulk RNA-seq data for ccRCC were retrieved from The Cance", "the value of integrating scRNA-seq and bulk RNA-seq data to uncover key regulators of tumor biol"], "order_basis": "paper_text_order:0", "id": "assay:1"}, {"role": "data_generation", "definition_id": "scrna_seq", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "unsupported", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["we employed an integrated approach combining single-cell RNA sequencing (scRNA-seq) and bulk RNA sequencing (bulk RN", "proach combining single-cell RNA sequencing (scRNA-seq) and bulk RNA sequencing (bulk RNA-seq) to i", "is study highlights the value of integrating scRNA-seq and bulk RNA-seq data to uncover key regulat", "ncer Genome Atlas (TCGA) and integrated with scRNA-seq data to explore tumor heterogeneity. We iden"], "order_basis": "paper_text_order:389", "id": "assay:2"}, {"role": "data_generation", "definition_id": "animal_model", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["ilencing significantly inhibits tumor growth in vivo. Our findings reveal that HSD3B7 is a novel", "Center of Chongqing Medical University. The mice were acclimated for two weeks under specific path", "r measurement. After 4 weeks post-injection, mice were administered D-luciferin potassium salt, whi", "and luciferase activity. After imaging, the mice were euthanized to excise the tumors, which were"], "order_basis": "paper_text_order:1333", "id": "assay:3"}, {"role": "data_generation", "definition_id": "transfection", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["Materials and Methods 4.4. Cell Culture and Transfection All cell lines used in this study, including", "down experiments, siRNA targeting HSD3B7 was transfected into 769-P cells using Lipofectamine 3000 (T", "vector, and the overexpression plasmids were transfected into A498 cells using the same transfection", "e transfected into A498 cells using the same transfection protocol. The siRNAs and HSD3B7 overexpressi"], "order_basis": "paper_text_order:1764", "id": "assay:4"}, {"role": "data_generation", "definition_id": "cell_culture", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["10% FBS and 1% penicillin–streptomycin. All cell lines were maintained in a humidified incubator at 37 °C with 5% C", "cell lines. A498, ACHN, and HK-2 cells were cultured in Dulbecco’s Modified Eagle Medium (DMEM, Gibc", "cin (Gibco, MA, USA), while 769-P cells were cultured in RPMI-1640 medium (Gibco, MA, USA) containing"], "order_basis": "paper_text_order:2480", "id": "assay:5"}, {"role": "analysis", "definition_id": "survival_analysis", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["cox_ph"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["Univariate Cox regression analysis was performed using the R package “survival” (v3.3.1, https://cran.r-project.org/web/packages/survival/index.html, accessed on 24 November 2023) and “survminer” (v0.4.9, https://cran.r-project.org/web/packages/survminer/index.html, accessed on 24 November 2023) to evaluate and visualize the association between patient survival and gene expression."], "order_basis": "consumes_earlier_output", "id": "assay:6"}]}