2026-10-08T08:29:01Z https://api.figshare.com/v2/oai

oai:figshare.com:article/34052868 2026-10-02T03:48:50Z category_24193 item_type_3 month_year_10_2026

Spatial transcriptomics reveals tumour cell-intrinsic and microenvironmental features associated with survival in high-grade serous ovarian carcinoma Kamran Khan (25160922) Weitao Lin (23576959) Paul A. Cohen (15048690) Alistair R.R. Forrest (15076761) Genomics and transcriptomics High-grade serous ovarian carcinoma (HGSOC) Xenium In Situ Spatial transcriptomics Survival analysis Cancer biology <p dir="ltr">High-grade serous ovarian carcinoma (HGSOC) is the most lethal form of gynaecological cancer, with patient outcomes influenced by both tumour-intrinsic biology and the surrounding tumour microenvironment. Bulk transcriptomic approaches capture these features as a composite signal, limiting the ability to resolve their cellular and spatial origins. We therefore used <b>Xenium spatial transcriptomics to profile 122 treatment-naïve HGSOC tumours</b> using a <b>custom 480-gene panel</b> designed to characterise tumour-intrinsic expression and immune and stromal cell populations. The study integrates spatial transcriptomic profiling, cell-type annotation, tumour pseudobulk analysis, tumour-centric spatial neighbourhood analysis, and survival modelling to investigate relationships between tumour biology, the microenvironment, and clinical outcomes.</p><p dir="ltr">This repository contains a consolidated <b>processed AnnData object</b> generated from the 10x Genomics Xenium spatial transcriptomic data used in this study. The deposited object includes the processed expression matrix, cell-level annotations, and spatial coordinates following preprocessing, quality control, and cell-type annotation. Spatial coordinates have been adjusted between TMA sections to position the complete TMA5 and TMA6 sections together within a common coordinate space for visualisation.</p><p dir="ltr">Representative Python and R scripts used for Xenium data processing, transcript reassignment, quality control, annotation, spatial neighbourhood analysis, and survival analyses are available at https://github.com/Kamran-Khan96/Xenium_HGSOC_spatial (The scripts are provided as representative analysis workflows and may require adaptation for different datasets, directory structures, or computational environments).</p> 2026-10-02T03:48:50Z Dataset Dataset 10.6084/m9.figshare.34052868.v1 https://figshare.com/articles/dataset/Spatial_transcriptomics_reveals_tumour_cell-intrinsic_and_microenvironmental_features_associated_with_survival_in_high-grade_serous_ovarian_carcinoma/34052868 CC BY 4.0