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Identification of Malignant Cell Populations Associated with Poor Prognosis in High-Grade Serous Ovarian Cancer Using Single-Cell RNA Sequencing.

ABSTRACT: To reveal tumor heterogeneity in ovarian cancer, we performed single-cell RNA sequencing (RNA-seq). We obtained The Cancer Genome Atlas (TCGA) survival data and TCGA gene expression data for a Kaplan-Meier plot showing the association of each tumor population with poor prognosis. As a result, we found two malignant tumor cell subtypes associated with poor prognosis. Next, we performed trajectory analysis using scVelo and Monocle3 and cell-cell interaction analysis using CellphoneDB. We found that one malignant population included the earliest cancer cells and cancer stem-like cells. Furthermore, we identified SLC3A1 and PEG10 as the marker genes of cancer-initiating cells. The other malignant population expressing CA125 (MUC16) is associated with a decrease in the number of tumor-infiltrating cytotoxic T lymphocytes (CTLs). Moreover, cell-cell interaction analysis implied that interactions mediated by LGALS9 and GAS6, expressed by this malignant population, caused the CTL suppression. The results of this study suggest that two tumor cell populations, including a cancer-initiating cell population and a population expressing CA125, survive the initial treatment and suppress antitumor immunity, respectively, and are associated with poor prognosis. Our findings offer a new understanding of ovarian cancer heterogeneity and will aid in the development of diagnostic tools and treatments.

SUBMITTER: Sumitani N

PROVIDER: S-EPMC9331511 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundPrimary or acquired chemoresistance is a key link in the high mortality rate of ovarian cancer. There is no reliable method to predict chemoresistance in ovarian cancer. We hypothesized that specific methylation characteristics could distinguish chemoresistant and chemosensitive ovarian cancer patients.MethodsIn this study, we used 450 K Infinium Methylation BeadChip to detect the different methylation CpGs between ovarian cancer patients. The differential methylation genes were analyzed by GO and KEGG Pathway bioinformatics analysis. The candidate CpGs were confirmed by pyrosequencing. The expression of abnormal methylation gene was identified by QRT-PCR and IHC. ROC analysis confirmed the ability to predict chemotherapy outcomes. Prognosis was evaluated using Kaplan-Meier.ResultsIn advanced high-grade serous ovarian cancer, 8 CpGs (ITGB6:cg21105318, cg07896068, cg18437633; NCALD: cg27637873, cg26782361, cg16265707; LAMA3: cg20937934, cg13270625) remained hypermethylated in chemoresistant patients. The sensitivity, specificity and AUC of 8 CpGs (ITGB6:cg21105318, cg07896068, cg18437633; NCALD: cg27637873, cg26782361, cg16265707; LAMA3: cg20937934, cg13270625) methylation to predict chemotherapy sensitivity were 63.60-97.00%, 46.40-89.30% and 0.774-0.846. PFS of 6 candidate genes (ITGB6:cg21105318, cg07896068; NCALD: cg27637873, cg26782361, cg16265707; LAMA3: cg20937934) hypermethylation patients was significantly shorter. The expression of NCALD and LAMA3 in chemoresistant patients was lower than that of chemosensitive patients. Spearman analysis showed that NCALD and LAMA3 methylations were negatively correlated with their expression.ConclusionsAs a new biomarker of chemotherapy sensitivity, hypermethylation of NCALD and LAMA3 is associated with poor PFS in advanced high-grade serous ovarian cancer. In the future, further research on NCALD and LAMA3 will be needed to provide guidance for clinical stratification of demethylation therapy.

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Identification of Malignant Cell Populations Associated with Poor Prognosis in High-Grade Serous Ovarian Cancer Using Single-Cell RNA Sequencing.

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