基于前列腺癌肿瘤相关成纤维细胞的单细胞转录组的生物信息学分析
Bioinformatics Analysis of Single-Cell Transcriptome Based on Prostate Cancer Cancer-Associated Fibroblasts
DOI: 10.12677/hjbm.2024.143040, PDF,    科研立项经费支持
作者: 李 洋*：吉林工商学院工学院，吉林 长春；李延春：吉林大学化学学院理论化学研究所，吉林 长春
关键词: 前列腺癌；单细胞；差异基因分析；生物信息学分析；Prostate Cancer； Single-Cell； Differential Gene Analysis； Bioinformatics Analysis
摘要: 本研究运用生物信息学分析方法对前列腺癌(PCa)相关的单细胞数据进行了深入研究。首先，我们从GEO数据库中筛选出了1035个与肿瘤相关成纤维细胞(CAFs)相关的差异表达基因。然后，我们选取了其中最显著的Top100个基因，通过蛋白质相互作用网络分析得到了10个核心差异表达基因。进一步利用GEPIA2工具进行生存预后分析，发现MYLK、MYH11、COL18A1和CALD1可能与前列腺癌的预后显著相关。这些结果为我们深入探究前列腺癌的发病机制提供了重要的信息，有助于制定个体化的治疗策略。
Abstract: This study utilized bioinformatics analysis methods to conduct in-depth research on single-cell data related to prostate cancer (PCa). Initially, we screened 1035 differentially expressed genes related to cancer-associated fibroblasts (CAFs) from the GEO database. Subsequently, we selected the most significant Top 100 genes and identified 10 core differentially expressed genes through protein-protein interaction network analysis. Further, using GEPIA2 tool, we performed survival prognosis analysis and found that MYLK, MYH11, COL18A1, and CALD1 may be significantly associated with the prognosis of prostate cancer. These results provide important information for further exploration of the pathogenesis of prostate cancer and contribute to the development of personalized treatment strategies.
文章引用：李洋, 李延春. 基于前列腺癌肿瘤相关成纤维细胞的单细胞转录组的生物信息学分析[J]. 生物医学, 2024, 14(3): 359-368. https://doi.org/10.12677/hjbm.2024.143040

参考文献

[1] Ji, D., Lu, S., Zhang, H., Li, Z., Wang, S., Miao, T., Jiang, Z. and Ao, L. (2024) Bulk and Single-Cell Transcriptome Reveal the Immuno-Prognostic Subtypes and Tumour Microenvironment Heterogeneity in HCC. Liver International, 44, 979-995. [Google Scholar] [CrossRef] [PubMed]
[2] Kang, Z., Zhao, Y.X., Qiu, R.S.Q., Chen, D.N., Zheng, Q.S., Xue, X.Y., Xu, N. and Wei, Y. (2024) Identification Macrophage Signatures in Prostate Cancer by Single-Cell Sequencing and Machine Learning. Cancer Immunology, Immunotherapy, 73, Article No. 41. [Google Scholar] [CrossRef] [PubMed]
[3] Wang, W., Li, T., Xie, Z., Zhao, J., Zhang, Y., Ruan, Y. and Han, B. (2024) Integrating Single-Cell and Bulk RNA Sequencing Data Unveils Antigen Presentation and Process-Related CAFS and Establishes A Predictive Signature in Prostate Cancer. Journal of Translational Medicine, 22, Article No. 57. [Google Scholar] [CrossRef] [PubMed]
[4] Yu, T., Cheng, W., Zhang, J., Wang, T., Liu, Y., Duan, Y., Hu, A., Feng, J., Li, M., Li, Y., et al. (2024) Identification of a PANoptosis-Related Gene Signature for Predicting the Prognosis, Tumor Microenvironment and Therapy Response in Breast Cancer. Journal of Cancer, 15, 428-443. [Google Scholar] [CrossRef] [PubMed]
[5] He, X. and Feng, W. (2023) Identification and Validation of NK Marker Genes in Ovarian Cancer by ScRNA-Seq Combined with WGCNA Algorithm. Mediators of Inflammation, 2023, Article ID: 6845701. [Google Scholar] [CrossRef] [PubMed]
[6] Tan, Z., Chen, X., Zuo, J., Fu, S., Wang, H. and Wang, J. (2023) Comprehensive Analysis of ScRNA-Seq and Bulk RNA-Seq Reveals Dynamic Changes in the Tumor Immune Microenvironment of Bladder Cancer and Establishes a Prognostic Model. Journal of Translational Medicine, 21, Article No. 223. [Google Scholar] [CrossRef] [PubMed]
[7] Wang, Q.W., Zhao, Y.A., Wang, F. and Tan, G.L. (2023) Clustering and Machine Learning-Based Integration Identify Cancer Associated Fibroblasts Genes’ Signature in Head and Neck Squamous Cell Carcinoma. Frontiers in Genetics, 14, Article 1111816. [Google Scholar] [CrossRef] [PubMed]
[8] Zhang, D., Li, D., Shen, L., Hu, D., Tang, B., Guo, W., Wang, Z., Zhang, Z., Wei, G. and He, D. (2022) Exosomes Derived from Piwil2-Induced Cancer Stem Cells Transform Fibroblasts into Cancer-Associated Fibroblasts. Oncology Reports, 47, 1125-1132. [Google Scholar] [CrossRef] [PubMed]
[9] Zheng, S., Zou, Y., Tang, Y., Yang, A., Liang, J.Y., Wu, L., Tian, W., Xiao, W., Xie, X., Yang, L., et al. (2022) Landscape of Cancer-Associated Fibroblasts Identifies the Secreted Biglycan as a Protumor and Immunosuppressive Factor in Triple-Negative Breast Cancer. Oncoimmunology, 11, Article ID: 2020984. [Google Scholar] [CrossRef] 
[10] Zhong, B., Cheng, B., Huang, X., Xiao, Q., Niu, Z., Chen, Y.F., Yu, Q., Wang, W. and Wu, X.J. (2022) Colorectal Cancer-Associated Fibroblasts Promote Metastasis by Up-Regulating LRG1 through Stromal IL-6/STAT3 Signaling. Cell Death & Disease, 13, Article No. 16. [Google Scholar] [CrossRef] [PubMed]
[11] Zhou, Y., Tang, W., Zhuo, H., Zhu, D., Rong, D., Sun, J. and Song, J. (2022) Cancer-Associated Fibroblast Exosomes Promote Chemoresistance to Cisplatin in Hepatocellular Carcinoma through CircZFR Targeting Signal Transducers and Activators of Transcription (STAT3)/Nuclear Factor-κB (NF-κB) Pathway. Bioengineered, 13, 4786-4797. [Google Scholar] [CrossRef] [PubMed]
[12] Li, Z., Sun, C. and Qin, Z. (2021) Metabolic Reprogramming of Cancer-Associated Fibroblasts and Its Effect on Cancer Cell Reprogramming. Theranostics, 11, 8322-8336. [Google Scholar] [CrossRef] [PubMed]
[13] Liu, W., Wang, M., Wang, M. and Liu, M. (2023) Single-Cell and Bulk RNA Sequencing Reveal Cancer-Associated Fibroblast Heterogeneity and a Prognostic Signature in Prostate Cancer. Medicine, 102, e34611. [Google Scholar] [CrossRef] 
[14] Pan, J., Ma, Z., Liu, B., Qian, H., Shao, X., Liu, J., Wang, Q. and Xue, W. (2023) Identification of Cancer-Associated Fibroblasts Subtypes in Prostate Cancer. Frontiers in Immunology, 14, Article 1133160. [Google Scholar] [CrossRef] [PubMed]
[15] Butler, A., Hoffman, P., Smibert, P., Papalexi, E. and Satija, R. (2018) Integrating Single-Cell Transcriptomic Data across Different Conditions, Technologies, and Species. Nature Biotechnology, 36, 411-420. [Google Scholar] [CrossRef] [PubMed]
[16] Huang, S., Chaudhary, K. and Garmire, L.X. (2017) More Is Better: Recent Progress in Multi-Omics Data Integration Methods. Frontiers in Genetics, 8, Article 84. [Google Scholar] [CrossRef] [PubMed]
[17] Stuart, T., Butler, A., Hoffman, P., Hafemeister, C., Papalexi, E., Mauck III, W.M., Hao, Y., Stoeckius, M., Smibert, P. and Satija, R. (2019) Comprehensive Integration of Single-Cell Data. Cell, 177, 1888-1902.E21. [Google Scholar] [CrossRef] [PubMed]
[18] Zhang, Y., Fan, A., Li, Y., Liu, Z., Yu, L., Guo, J., Hou, J., Li, X. and Chen, W. (2023) Single-Cell RNA Sequencing Reveals That HSD17B2 in Cancer-Associated Fibroblasts Promotes the Development and Progression of Castration-Resistant Prostate Cancer. Cancer Letters, 566, Article ID: 216244. [Google Scholar] [CrossRef] [PubMed]
[19] Zhou, H., Zhang, T., Chen, L., Cui, F., Xu, C., Peng, J., Ma, W., Huang, J., Sheng, X., Liu, M., et al. (2023) The Functional Implication of ATF6α in Castration-Resistant Prostate Cancer Cells. FASEB Journal, 37, e22758. [Google Scholar] [CrossRef] 
[20] Zhou, Y., Li, H., Yu, D.E., Zhang, C., Yang, H., Wang, C., Zhang, Y., Deng, W., Li, B. and Zhang, S. (2023) Developing High-Resolution Metastasis Signatures for Improved Cancer Prognosis and Drug Sensitivity Prediction Using Single-Cell RNA Sequencing Data: A Case Study in Lung Adenocarcinoma. Journal of Computational Biophysics and Chemistry. [Google Scholar] [CrossRef] 
[21] Di, Z., Zhou, S., Xu, G., Ren, L., Li, C., Ding, Z., Huang, K., Liang, L. and Yuan, Y. (2022) Single-Cell and WGCNA Uncover a Prognostic Model and Potential Oncogenes in Colorectal Cancer. Biological Procedures Online, 24, Article No. 13. [Google Scholar] [CrossRef] [PubMed]
[22] Hu, J., Jiang, Y., Wei, Q., Li, B., Xu, S., Wei, G., Li, P., Chen, W., Lv, W., Xiao, X., et al. (2022) Development of a Cancer-Associated Fibroblast-Related Prognostic Model in Breast Cancer via Bulk and Single-Cell RNA Sequencing. BioMed Research International, 2022, Article ID: 2955359. [Google Scholar] [CrossRef] [PubMed]
[23] Wang, Q., Zhang, X., Du, K., Wu, X., Zhou, Y., Chen, D. and Zeng, L. (2022) Machine Learning Identifies Characteristics Molecules of Cancer Associated Fibroblasts Significantly Correlated with the Prognosis, Immunotherapy Response and Immune Microenvironment in Lung Adenocarcinoma. Frontiers in Oncology, 12, Article 1059253. [Google Scholar] [CrossRef] [PubMed]
[24] Zhao, Z., Li, W., Zhu, L., Xu, B., Jiang, Y., Ma, N., Liu, L., Qiu, J. and Zhang, M. (2022) Construction and Verification of a Fibroblast-Related Prognostic Signature Model for Colon Cancer. Frontiers in Genetics, 13, Article 908957. [Google Scholar] [CrossRef] [PubMed]
[25] Wen, X.Y., Wang, R.Y., Yu, B., Yang, Y., Yang, J. and Zhang, H.C. (2023) Integrating Single-Cell and Bulk RNA Sequencing to Predict Prognosis and Immunotherapy Response in Prostate Cancer. Scientific Reports, 13, Article No. 15597. [Google Scholar] [CrossRef] [PubMed]
[26] Wu, F., Ning, H., Sun, Y., Wu, H. and Lyu, J. (2023) Integrative Exploration of the Mutual Gene Signatures and Immune Microenvironment between Benign Prostate Hyperplasia and Castration-Resistant Prostate Cancer. Aging Male, 26, Article ID: 2183947. [Google Scholar] [CrossRef] [PubMed]
[27] Xiao, C. and Liang, W. (2023) Bulk RNA-Seq Combined with Single-Cell Transcriptome Sequencing Reveals the Possible Mechanisms by Which HDGFL3 Involves in Prostate Cancer Growth and Metastasis. Archivos Espanoles de Urologia, 76, 425-438. [Google Scholar] [CrossRef] [PubMed]
[28] Lyu, F., Gao, X., Ma, M., Xie, M., Shang, S., Ren, X., Liu, M. and Chen, J. (2023) Crafting a Personalized Prognostic Model for Malignant Prostate Cancer Patients Using Risk Gene Signatures Discovered through TCGA-PRAD Mining, Machine Learning, and Single-Cell RNA-Sequencing. Diagnostics, 13, Article 1997. [Google Scholar] [CrossRef] [PubMed]
[29] Qian, Y., Feng, D., Wang, J., Wei, W., Wei, Q., Han, P. and Yang, L. (2023) Establishment of Cancer-Associated Fibroblasts-Related Subtypes and Prognostic Index for Prostate Cancer through Single-Cell and Bulk RNA Transcriptome. Scientific Reports, 13, Article No. 9016. [Google Scholar] [CrossRef] [PubMed]
[30] Sun, Z., Wang, J., Zhang, Q., Meng, X., Ma, Z., Niu, J., Guo, R., Tran, L.J., Zhang, J., Liu, Y., et al. (2023) Coordinating Single-Cell and Bulk RNA-Seq in Deciphering the Intratumoral Immune Landscape and Prognostic Stratification of Prostate Cancer Patients. Environmental Toxicology, 39, 657-668. [Google Scholar] [CrossRef] [PubMed]
[31] Wang, Z., Wei, D., Li, S., Tang, Q., Lu, G., Gu, S., Lu, L., Liang, F., Teng, J., Lin, J., et al. (2023) Healing Mechanism of Diabetic Foot Ulcers Using Single-Cell RNA-Sequencing. Annals of Translational Medicine, 11, Article 210. [Google Scholar] [CrossRef] [PubMed]
[32] Han, J., Zhou, Y., Zhang, C., Feng, J., Wang, J., Guo, K., Chen, W. and Li, Y. (2023) Intratumoral Immune Heterogeneity of Prostate Cancer Characterized by Typing and Hub Genes. Journal of Cellular and Molecular Medicine, 27, 101-112. [Google Scholar] [CrossRef] [PubMed]
[33] Huang, J., Liu, D., Li, J., Xu, J., Dong, S. and Zhang, H. (2023) A 12-Gene Panel in Estimating Hormone-Treatment Responses of Castration-Resistant Prostate Cancer Patients Generated Using a Combined Analysis of Bulk and Single-Cell Sequencing Data. Annals of Medicine, 55, Article ID: 2260387. [Google Scholar] [CrossRef] [PubMed]
[34] Kang, K., Wu, Y., Han, C., Wang, L., Wang, Z. and Zhao, A. (2023) Homologous Recombination Deficiency in Triple-Negative Breast Cancer: Multi-Scale Transcriptomics Reveals Distinct Tumor Microenvironments and Limitations in Predicting Immunotherapy Response. Computers in Biology and Medicine, 158, Article ID: 106836. [Google Scholar] [CrossRef] [PubMed]
[35] Chen, K., Wang, Q., Liu, X., Tian, X., Dong, A. and Yang, Y. (2023) Immune Profiling and Prognostic Model of Pancreatic Cancer Using Quantitative Pathology and Single-Cell RNA Sequencing. Journal of Translational Medicine, 21, Article No. 210. [Google Scholar] [CrossRef] [PubMed]
[36] Chen, X., Peng, C., Chen, Y., Ding, B., Liu, S., Song, Y., Li, Y., Sun, B. and Yang, R. (2023) A T-Cell-Related Signature for Prognostic Stratification and Immunotherapy Response in Hepatocellular Carcinoma Based on Transcriptomics and Single-Cell Sequencing. BMC Bioinformatics, 24, Article No. 216. [Google Scholar] [CrossRef] [PubMed]
[37] Feriz, A.M., Khosrojerdi, A., Lotfollahi, M., Shamsaki, N., Ghasemigol, M., Hosseinigol, E., Fereidouni, M., Rohban, M.H., Sebzari, A.R., Saghafi, S., et al. (2023) Single-Cell RNA Sequencing Uncovers Heterogeneous Transcriptional Signatures in Tumor-Infiltrated Dendritic Cells in Prostate Cancer. Heliyon, 9, E15694. [Google Scholar] [CrossRef] [PubMed]
[38] Hong, Y.C., Hu, T.Y., Hsu, C.S., Yeh, W.W., Wong, W.Z., Shen, T.W., Chang, C.H., Hua, K., Tung, C.Y., Peng, Y.C., et al. (2023) Single-Cell Analysis of Castration-Resistant Prostate Cancers to Identify Potential Biomarkers for Diagnosis and Prognosis of Neuroendocrine Prostate Cancer. American Journal of Cancer Research, 13, 4560-4578.
[39] Qin, C., Liu, S., Zhou, S., Wang, Q., Xia, X., Hu, J., Yuan, X., Wang, Z., Yu, Y. and Ma, D. (2023) PIK3C2A Is A Prognostic Biomarker That Is Linked to Immune Infiltrates in Kidney Renal Clear Cell Carcinoma. Frontiers in Immunology, 14, Article 1114572. [Google Scholar] [CrossRef] [PubMed]
[40] Wang, S., Fan, G., Li, L., He, Y., Lou, N., Xie, T., Dai, L., Gao, R., Yang, M., Shi, Y., et al. (2023) Integrative Analyses of Bulk and Single-Cell RNA-Seq Identified Cancer-Associated Fibroblasts-Related Signature as a Prognostic Factor for Immunotherapy in NSCLC. Cancer Immunology, Immunotherapy, 72, 2423-2442. [Google Scholar] [CrossRef] [PubMed]

为你推荐