Siegel RL, Miller KD, Fuchs HE, Jemal A. Cancer statistics, 2022. CA Cancer J Clin. 2022;72(1):7–33.
Siegel RL, Miller KD, Wagle NS, Jemal A. Cancer statistics, 2023. CA Cancer J Clin. 2023;73(1):17–48.
Kobayashi Y, Banno K, Aoki D. Current status and future directions of ovarian cancer prognostic models. J Gynecol Oncol. 2021;32(2):e34.
Article CAS PubMed PubMed Central Google Scholar
Peng F, Liao M, Qin R, Zhu S, Peng C, Fu L, et al. Regulated cell death (RCD) in cancer: key pathways and targeted therapies. Signal Transduct Target Ther. 2022;7(1):286.
Article CAS PubMed PubMed Central Google Scholar
Su Z, Yang Z, Xu Y, Chen Y, Yu Q. Apoptosis, autophagy, necroptosis, and cancer metastasis. Mol Cancer. 2015;14:1–14.
Ye Y, Dai Q, Qi H. A novel defined pyroptosis-related gene signature for predicting the prognosis of ovarian cancer. Cell death discovery. 2021;7(1):71.
Article CAS PubMed PubMed Central Google Scholar
Vos JR, Fakkert IE, de Hullu JA, van Altena AM, Sie AS, Ouchene H, et al. Universal tumor DNA BRCA1/2 testing of ovarian cancer: prescreening PARPi treatment and genetic predisposition. J Natl Cancer Inst. 2020;112(2):161–9.
Ihlow J, Monjé N, Hoffmann I, Bischoff P, Sinn BV, Schmitt WD, et al. Low expression of RGS2 promotes poor prognosis in high-grade serous ovarian cancer. Cancers (Basel). 2022;14(19):4620.
Article CAS PubMed Google Scholar
Marusyk A, Almendro V, Polyak K. Intra-tumour heterogeneity: a looking glass for cancer? Nat Rev Cancer. 2012;12(5):323–34.
Article CAS PubMed Google Scholar
Izar B, Tirosh I, Stover EH, Wakiro I, Cuoco MS, Alter I, et al. A single-cell landscape of high-grade serous ovarian cancer. Nat Med. 2020;26(8):1271–9.
Article CAS PubMed PubMed Central Google Scholar
Zhao H, Gao Y, Miao J, Chen S, Li J, Li Z, et al. Single-cell RNA-seq highlights a specific carcinoembryonic cluster in ovarian cancer. Cell Death Dis. 2021;12(11):1–11.
Lim B, Lin Y, Navin N. Advancing cancer research and medicine with single-cell genomics. Cancer Cell. 2020;37(4):456–70.
Article CAS PubMed PubMed Central Google Scholar
Guruprasad P, Lee YG, Kim KH, Ruella M. The current landscape of single-cell transcriptomics for cancer immunotherapy. J Exp Med. 2021;218(1): e20201574.
Article CAS PubMed Google Scholar
Andrews TS, Hemberg M. Identifying cell populations with scRNASeq. Mol Aspects Med. 2018;59:114–22.
Article CAS PubMed Google Scholar
Liu C, Zhang Y, Li X, Wang D. Ovarian cancer-specific dysregulated genes with prognostic significance: scRNA-Seq with bulk RNA-Seq data and experimental validation. Ann N Y Acad Sci. 2022;1512(1):154–73.
Article CAS PubMed Google Scholar
Tan Z, Chen X, Zuo J, Fu S, Wang H, Wang J. 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. J Transl Med. 2023;21(1):1–20.
Sumitani N, Ishida K, Sawada K, Kimura T, Kaneda Y, Nimura K. Identification of malignant cell populations associated with poor prognosis in high-grade serous ovarian cancer using single-cell RNA sequencing. Cancers (Basel). 2022;14(15):3580.
Article CAS PubMed Google Scholar
Yu S, Yang R, Xu T, Li X, Wu S, Zhang J. Cancer-associated fibroblasts-derived FMO2 as a biomarker of macrophage infiltration and prognosis in epithelial ovarian cancer. Gynecol Oncol. 2022;167(2):342–53.
Article CAS PubMed Google Scholar
Zhu J, Sanborn JZ, Benz S, Szeto C, Hsu F, Kuhn RM, et al. The UCSC cancer genomics browser. Nat Methods. 2009;6(4):239–40.
Article CAS PubMed PubMed Central Google Scholar
Lonsdale J, Thomas J, Salvatore M, Phillips R, Lo E, Shad S, et al. The genotype-tissue expression (GTEx) project. Nat Genet. 2013;45(6):580–5.
Lisowska KM, Olbryt M, Student S, Kujawa KA, Cortez AJ, Simek K, et al. Unsupervised analysis reveals two molecular subgroups of serous ovarian cancer with distinct gene expression profiles and survival. J Cancer Res Clin Oncol. 2016;142(6):1239–52.
Article CAS PubMed PubMed Central Google Scholar
Stelzer G, Rosen N, Plaschkes I, Zimmerman S, Twik M, Fishilevich S, et al. The GeneCards suite: from gene data mining to disease genome sequence analyses. Curr Protoc Bioinformatics. 2016;54(1):1.30. 1-1.30. 33.
Xu J, Fang Y, Chen K, Li S, Tang S, Ren Y, et al. Single-cell RNA sequencing reveals the tissue architecture in human high-grade serous ovarian cancer. Clin Cancer Res. 2022;28(16):3590–602.
Article CAS PubMed PubMed Central Google Scholar
Shu J, Yang L, Wei W, Zhang L. Identification of programmed cell death-related gene signature and associated regulatory axis in cerebral ischemia/reperfusion injury. Front Genet. 2022;13: 934154.
Article CAS PubMed PubMed Central Google Scholar
Zhang G, Fan W, Wang H, Wen J, Tan J, Xue M, et al. Non-apoptotic programmed cell death-related gene signature correlates with stemness and immune status and predicts the responsiveness of transarterial chemoembolization in hepatocellular carcinoma. Frontiers in Cell and Developmental Biology. 2022;10: 844013.
Article PubMed PubMed Central Google Scholar
Chin L, Hahn WC, Getz G, Meyerson M. Making sense of cancer genomic data. Genes Dev. 2011;25(6):534–55.
Article CAS PubMed PubMed Central Google Scholar
Ritchie ME, Phipson B, Wu D, Hu Y, Law CW, Shi W, et al. limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res. 2015;43(7):e47–e47.
Article PubMed PubMed Central Google Scholar
Mi H, Muruganujan A, Ebert D, Huang X, Thomas PD. PANTHER version 14: more genomes, a new PANTHER GO-slim and improvements in enrichment analysis tools. Nucleic Acids Res. 2019;47(D1):D419–26.
Article CAS PubMed Google Scholar
Kanehisa M, Goto S. KEGG: kyoto encyclopedia of genes and genomes. Nucleic Acids Res. 2000;28(1):27–30.
Article CAS PubMed PubMed Central Google Scholar
Yu G, Wang L-G, Han Y, He Q-Y. clusterProfiler: an R package for comparing biological themes among gene clusters. OMICS. 2012;16(5):284–7.
Article CAS PubMed PubMed Central Google Scholar
Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J Roy Stat Soc: Ser B (Methodol). 1995;57(1):289–300.
Therneau TM, Grambsch PM. The cox model. In: Modeling survival data: extending the cox model. Statistics for biology and health. New York: Springer; 2000. https://doi.org/10.1007/978-1-4757-3294-8_3.
Hao Y, Hao S, Andersen-Nissen E, Mauck WM III, Zheng S, Butler A, et al. Integrated analysis of multimodal single-cell data. Cell. 2021;184(13):3573-3587.e29.
Article CAS PubMed PubMed Central Google Scholar
Etherington GJ, Soranzo N, Mohammed S, Haerty W, Davey RP, Palma FD. A Galaxy-based training resource for single-cell RNA-sequencing quality control and analyses. GigaScience. 2019;8(12):giz144.
Article PubMed PubMed Central Google Scholar
Becht E, McInnes L, Healy J, Dutertre C-A, Kwok IW, Ng LG, et al. Dimensionality reduction for visualizing single-cell data using UMAP. Nat Biotechnol. 2019;37(1):38–44.
Huang Q, Liu Y, Du Y, Garmire LX. Evaluation of cell type annotation R packages on single-cell RNA-seq data. Genomics Proteomics Bioinformatics. 2021;19(2):267–81.
Newman AM, Liu CL, Green MR, Gentles AJ, Feng W, Xu Y, et al. Robust enumeration of cell subsets from tissue expression profiles. Nat Methods. 2015;12(5):453–7.
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