Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

Multifactor assessment of ovarian cancer reveals immunologically interpretable molecular subtypes with distinct prognoses

7 Dec 2023

Abstract excerpt

Background Ovarian cancer (OC) is a highly heterogeneous and malignant gynecological cancer, thereby leading to poor clinical outcomes. The study aims to identify and characterize clinically relevant subtypes in OC and develop a diagnostic model that can precisely stratify OC patients, providing more diagnostic clues for OC patients to access focused therapeutic and preventative strategies. Methods Gene...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Ferroptosis and cancer prognosis
Share to Kruppel-like factors research
Share to Ovarian cancer diagnosis and treatment

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Source

Identifiers

PMID: 38143770
DOI: 10.3389/fimmu.2023.1326018

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Multifactor assessment of ovarian cancer reveals immunologically interpretable molecular subtypes with distinct prognosesPMID 38143770Read ↗

Identification of three subtypes of ovarian cancer and construction of prognostic models based on immune-related genes.Semantic proximity Read ↗

Single-sample gene set enrichment analysis reveals the clinical implications of immune-related genes in ovarian cancerSemantic proximity Read ↗

Immunogenic cell death-related gene landscape predicts the overall survival and immune infiltration status of ovarian cancerSemantic proximity Read ↗

Identification of the immune subtype of ovarian cancer patients by integrated analyses of transcriptome and single-cell sequencing dataSemantic proximity Read ↗

A Risk Model Based on Tumor Microenvironment to Predict Survival and Immunotherapy Efficacy for Ovarian CancerSemantic proximity Read ↗

Comprehensive analysis of prognostic gene signatures based on immune infiltration of ovarian cancerSemantic proximity Read ↗

Identification of a Novel Model for Predicting the Prognosis and Immune Response Based on Genes Related to Cuproptosis and Ferroptosis in Ovarian CancerSemantic proximity Read ↗

A Novel Immune-Related Prognostic Model Based on Chemosensitivity Predicts the Outcome of Ovarian CancerSemantic proximity Read ↗

Development and Verification of an Immune-Related Gene Pairs Prognostic Signature in Ovarian CancerSemantic proximity Read ↗

Prognostic Risk Model of Immune-Related Genes In Ovarian CancerSemantic proximity Read ↗

Identifying the Role of Oxidative Stress‐Related Genes as Prognostic Biomarkers and Predicting the Response of Immunotherapy and Chemotherapy in Ovarian CancerSemantic proximity Read ↗

Development and validation of an immune gene-set based Prognostic signature in ovarian cancerSemantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.