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Analysis of Spatial Transcriptomics for Unveiling the novel molecular characteristics of Recurrent and Non-Recurrent High-Grade Serous Ovarian Cancer

ABSTRACT: Our study utilized spatial transcriptomics (ST) to interpret the tumor microenvironment to examine spatial characteristics across different sites in eight patients with HGSOC divided into recurrent (R, n = 5) and non-recurrent (NR, n = 3) groups based on a 60-month recurrence criterion. This study identified diagnostic and therapeutic targets for HGSOC, marking a step towards personalized medicine.

ORGANISM(S): Homo sapiens

PROVIDER: GSE263920 | GEO | 2024/04/18

REPOSITORIES: GEO

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Project description:Introduction/ Background: The epigenome represents and adds another facet of complexity to cancer that needs to be understood to categorize patients into those at risk of disease, recurrence, or treatment failure. Our goal is to compare DNA methylation status between controls vs HGSOC, and relate it with clinical outcomes. Methodology: A retrospective review of our institution’s advanced/ recurrent HGSOC patients yielded 99 cases with good quality DNA and RNA. 12 normal fallopian tubes were also collected and used as controls. Infinium Illumina methylationEPIC was used to characterize DNA methylation status and RNA seq to evaluate gene expression. T- tests were used to compare methylation patterns between controls vs HGSOC, primary vs recurrent, and optimal vs suboptimal surgical outcomes. Spearman’s rank correlation was used to evaluate association between degree of methylation and expression of identified genes. Validation of our findings used the cancer genome atlas (TCGA) database followed by C-statistics to assess degree of agreement. Results: Out of 66,069 methylation probes that interrogate known genes, 5,852 probes were significantly different between normal and HGSOC. This includes genes that are enriched in several pathways such as the RAS signaling pathway. A similar analysis of the TCGA database showed 2,075 differentially methylated probes. 1,891 probes were significant in both datasets giving a 70.1% degree of agreement. When comparing differential DNA methylation between primary and recurrent disease, there were 57 probes which represent 17 genes that were significantly different. When comparing optimal vs suboptimal surgical outcomes, 99 probes were significantly different wherein 29 genes show expected inverse correlation between methylation status and gene expression. Conclusions: There are significant differences in methylation patterns between HGSOC and fallopian tubes, primary vs recurrent tissues, and optimal vs sub-optimal surgical outcomes. Cataloging these phenomena in a well characterized clinical population will aid in determining groupings for precision medicine treatment cohorts in the future.

Dataset Information

Analysis of Spatial Transcriptomics for Unveiling the novel molecular characteristics of Recurrent and Non-Recurrent High-Grade Serous Ovarian Cancer

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