About this Research Topic
Gynecological cancers, including endometrial, ovarian, and cervical cancers, present significant global health challenges, affecting millions of women annually. Despite advances in diagnosis and treatment, prognosis and survival rates can vary widely. Identifying reliable prognostic biomarkers is crucial for improving patient outcomes by enabling personalized treatment strategies.
Recent studies have identified and validated several promising gene signatures and biomarkers in these cancers. In endometrial cancer (EC), the discovery of a four-EMT-related gene signature, linked to the process of epithelial-mesenchymal transition (EMT), shows promise for predicting patient outcomes and enhancing prognostic accuracy in clinical settings.
Similarly, integrated bioinformatics methods have been effective in identifying significant gene signatures and prognostic biomarkers in cervical cancer through gene expression profiling, meta-analysis, WGCNA, survival analysis, and pathway enrichment.
Research in uterine and ovarian cancers has also highlighted the importance of immune-related gene signatures, with the tumor immune microenvironment playing a crucial role in cancer development and progression. For uterine cancer, various prognostic models, such as a seven-gene immune infiltration signature, an immune gene signature from TCGA data, and a ferroptosis-related gene signature, have shown strong correlations with patient outcomes. In ovarian cancer, WGCNA and comprehensive tumor microenvironment analyses have led to effective prognostic models based on immune-related gene signatures.
These studies collectively underscore the importance of immune-related gene signatures in understanding gynecological cancers, aiding prognostic predictions, and informing treatment strategies. Reviews of tumor markers in cervical, ovarian, and endometrial carcinomas further emphasize their significance in diagnosis, prognosis, and treatment, highlighting the necessity of integrating these markers into clinical practice.
The primary goal of this research proposal is to validate and integrate novel and existing prognostic biomarkers into clinical practice for endometrial, ovarian, and cervical cancers, improving patient care and outcomes.
• Prognostic Biomarkers in Endometrial Cancer: Validate and integrate the four-EMT-related gene signature to improve prognostic accuracy and therapeutic decision-making.
• Bioinformatics in Cervical Cancer: Use bioinformatics methods (gene expression profiling, meta-analysis, WGCNA, survival analysis, pathway enrichment) to identify and validate significant gene signatures and prognostic biomarkers.
• Immune-Related Gene Signatures in Uterine and Ovarian Cancers: Investigate immune-related gene signatures and their role in the tumor microenvironment and develop prognostic models for these cancers.
• Clinical Integration of Tumor Markers: Integrate validated tumor markers for cervical, ovarian, and endometrial cancers into clinical practice to enhance diagnosis, prognosis, and treatment strategies.
Recent studies have identified and validated several promising gene signatures and biomarkers in these cancers. In endometrial cancer (EC), the discovery of a four-EMT-related gene signature, linked to the process of epithelial-mesenchymal transition (EMT), shows promise for predicting patient outcomes and enhancing prognostic accuracy in clinical settings.
Similarly, integrated bioinformatics methods have been effective in identifying significant gene signatures and prognostic biomarkers in cervical cancer through gene expression profiling, meta-analysis, WGCNA, survival analysis, and pathway enrichment.
Research in uterine and ovarian cancers has also highlighted the importance of immune-related gene signatures, with the tumor immune microenvironment playing a crucial role in cancer development and progression. For uterine cancer, various prognostic models, such as a seven-gene immune infiltration signature, an immune gene signature from TCGA data, and a ferroptosis-related gene signature, have shown strong correlations with patient outcomes. In ovarian cancer, WGCNA and comprehensive tumor microenvironment analyses have led to effective prognostic models based on immune-related gene signatures.
These studies collectively underscore the importance of immune-related gene signatures in understanding gynecological cancers, aiding prognostic predictions, and informing treatment strategies. Reviews of tumor markers in cervical, ovarian, and endometrial carcinomas further emphasize their significance in diagnosis, prognosis, and treatment, highlighting the necessity of integrating these markers into clinical practice.
The primary goal of this research proposal is to validate and integrate novel and existing prognostic biomarkers into clinical practice for endometrial, ovarian, and cervical cancers, improving patient care and outcomes.
• Prognostic Biomarkers in Endometrial Cancer: Validate and integrate the four-EMT-related gene signature to improve prognostic accuracy and therapeutic decision-making.
• Bioinformatics in Cervical Cancer: Use bioinformatics methods (gene expression profiling, meta-analysis, WGCNA, survival analysis, pathway enrichment) to identify and validate significant gene signatures and prognostic biomarkers.
• Immune-Related Gene Signatures in Uterine and Ovarian Cancers: Investigate immune-related gene signatures and their role in the tumor microenvironment and develop prognostic models for these cancers.
• Clinical Integration of Tumor Markers: Integrate validated tumor markers for cervical, ovarian, and endometrial cancers into clinical practice to enhance diagnosis, prognosis, and treatment strategies.
Keywords: Biomarkers, Gene Signature, endometrial cancer, ovarian cancer, cervical Cancer
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