Ovarian cancer diagnosis and treatment

This study identifies ARID1A mutation and low CD3+ TIL levels as prognostic markers for relapse in low-stage clear cell ovarian carcinoma.

This study shows that integrin-β4 upregulation suppresses ovarian cancer cell proliferation and protects cells from cisplatin, suggesting a role in chemoresistance.

This study identifies high-risk mesenchymal stem cells (hrMSCs) that drive DNA damage and promote high-grade serous ovarian cancer initiation in fallopian tube epithelium.

This study shows APOBEC3A promotes ovarian cancer metastasis by altering epithelial-to-mesenchymal transition in high-grade serous ovarian cancer.

This study combines histopathology and proteomics with a multimodal deep learning framework to improve platinum response prediction in HGSOC, outperforming HRD scores.

This study identifies HSF1 and MYC co-amplification in ovarian cancer and shows that targeting PLK1 is more effective in these cells, suggesting a potential precision medicine approach.

This study uses CRISPR to eliminate the FOXL2 c.402C>G mutation in granulosa tumor cells, reducing malignancy and identifying anti-tumoral compounds.

This study uses spatial profiling to show immune suppression and microenvironment changes in fallopian tube precursors of high-grade serous ovarian cancer.

This paper shows that claudin-4 remodels nucleus-cell cycle interactions to maintain genome stability and resist genomic instability-inducing agents in ovarian cancer.

The paper shows that intraperitoneal administration of β-glucan and IFNγ clears ascites and induces IL27-dependent tumor regression in metastatic ovarian cancer models.

The paper identifies pre-ciliated tubal epithelial cells as a cancer-prone state in high-grade serous ovarian carcinoma by analyzing mouse uterine tube cell states and lineage dynamics.

This paper shows that combining MYC and p53-R270H mutations in a mouse model generates high-grade serous ovarian and uterine serous carcinomas with human-like genetic and transcriptomic features.

The paper uses spatial data from ovarian cancer tumors to show that spatial organization of the immune microenvironment correlates with patient outcomes and can predict treatment response.

This study shows that high ploidy and whole genome duplication in ovarian high-grade serous carcinoma originate in STIC lesions, indicating early determination of the tumor's genomic trajectory.

This study shows GPX3 is necessary for ovarian cancer growth in vivo and promotes GDF15 expression, linking it to immune checkpoint inhibitor response.

This study identifies genomic subgroups in ovarian cancer associated with distinct treatment responses and survival outcomes using whole genome sequencing data.

This study identifies nine potential biomarkers for epithelial ovarian cancer subtypes through gene expression analysis and survival analysis of differentially expressed genes.

This paper develops a genetic risk score for ovarian cancer using chromosomal-scale length variation, showing it can stratify risk with high accuracy.

This paper shows that molecular subtypes and gene signatures in ovarian cancer are influenced by stromal cell content, suggesting that bulk tissue analysis may be unreliable without accounting for cell admixture.