Background High grade serous ovarian cancer (HGSOC) is among the deadliest human cancers and its prognosis remains extremely poor. Tumor heterogeneity and rapid acquisition of resistance to conventional chemotherapeutic approaches strongly contribute to poor outcome of patients. The clinical landscape of ...
1Vol.:(0123456789)Scientif i c Reports | (2022) 12:3041 | https://doi.org/10.1038/s41598-022-06788-2www.nature.com/scientificreportsMachine Learning analysis of high‑grade serous ovarian cancer proteomic dataset reveals novel candidate biomarkersFederica Farinella 1,8 , Mario Merone 2,8* ,...
Validation analysis of the novel imaging-based prognostic radiomic signature in patients undergoing primary surgery for advanced high-grade serous ovarian cancer (HGSOC) ArticleOpen access18 December 2021 A multimodal radiomic machine learning approach to predict the LCK expression and clinical prognosis in...
High-grade serous ovarian cancer (HGSOC) is an aggressive disease known to develop resistance to chemotherapy. We investigated the prognostic significance of tumor cell states and potential mechanisms underlying chemotherapy resistance in HGSOC. Transcri
Malignant abdominal fluid (ascites) frequently develops in women with advanced high-grade serous ovarian cancer (HGSOC) and is associated with drug resistance and a poor prognosis1. To comprehensively characterize the HGSOC ascites ecosystem, we used single-cell RNA sequencing to profile ~11,000 ce...
The clinicopathological parameters such as residual tumor, grade, the International Federation of Gynecology and Obstetrics (FIGO) score are often used to predict the survival of ovarian cancer patients, but the 5-year survival of high grade serous ovari
High-grade serous tubo-ovarian cancer (HGSTOC) is characterised by extensive inter- and intratumour heterogeneity, resulting in persistent therapeutic resistance and poor disease outcome. Molecular subtype classification based on bulk RNA sequencing facilitates a more accurate characterisation of this heterog...
However, the role and mechanism of ETV5 in high-grade serous ovarian cancer (HGSOC) have not been elucidated. Methods Quantitative real-time polymerase chain reaction (qRT-PCR) assay was used to detect ETV5 messenger ribonucleic acid (mRNA) expression in 87 HGSOC tissues and 35 normal ...
Deep learning High-grade serous ovarian cancer Recurrence Prognosis Computed tomography Artificial intelligence Semi-supervised learning Auto encoder Unsupervised learning Ovarian cancer (OC) is the leading cause of gynecologic cancer deaths and high-grade serous ovarian cancer (HGSOC) is the most common ...
High-grade serous ovarian carcinoma (HGSOC) is generally associated with a very dismal prognosis. Nevertheless, patients with similar clinicopathological characteristics can have markedly different clinical outcomes. Our aim was the identification of novel molecular determinants influencing survival. Methods Ge...