Related Experiment Video
Updated: Aug 22, 2025
Integration of Bioinformatics Approaches and Experimental Validations to Understand the Role of Notch Signaling in Ovarian Cancer
Published on: January 12, 2020
A comprehensive pan-cancer analysis of necroptosis molecules in four gynecologic cancers
Jianfeng Zheng1, Xintong Cai1, Yu Zhang2
1Department of Gynecology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, No.420, Fuma Road, Jin 'an District, Fuzhou City, 350014, Fujian Province, People's Republic of China.
Background:
In recent years, it has been proved that necroptosis plays an important role in the occurrence, development, invasion, metastasis and drug resistance of malignant tumors. Hence, further evaluation and targeting of necroptosis may be of clinical benefit for gynecologic cancers (GCs).
Methods:
To compare consistency and difference, we explored the expression pattern and prognostic value of necroptosis-related genes (NRGs) in pan-GC analysis through Linear regression and Empirical Bayesian, Univariate Cox analysis, and public databases from TCGA and Genotype-Tissue Expression (GTEx), including CESC, OV, UCEC, and UCS. We explored the copy number variation (CNV), methylation level and enrichment pathways of NRGs in the four GCs. Based on LASSO Cox regression analysis or principal component analysis, we established the prognostic NRG-signature or necroptosis-score for the four GCs. In addition, we predicted and compared functional pathways, tumor mutational burden (TMB), somatic mutation features, immunity status, immunotherapy, chemotherapeutic drug sensitivity of the NRG-signature based on NRGs. We also examined the expression level of several NRGs in OV samples that we collected using Quantitative Real-time PCR.
Results:
We confirmed the presence of NRGs in expression, prognosis, CNV, and methylation for four GCs, thus comparing the consistency and difference among the four GCs. The prognosis and independent prognostic value of the risk signatures based on NRGs were determined. Through the results of subclass mapping, we found that GC patients with lower risk score may be more sensitive to PDL1 response and more sensitive to immune checkpoint blockade therapy. Drug susceptibility analysis showed that, 51, 45, 64, and 29 drugs with differences between risk groups were yielded in CESC, OV, UCEC, and UCS respectively. For OV, the expression differences of several NRGs in the tissues we collected were similar to that in TCGA.
Conclusion:
Our comprehensive analysis of NRGs and NRG-signature demonstrated their similarity and difference, as well as their potential roles in prognosis and could guide therapeutic strategies, thus improving the outcome of GC patients.
Insights
Necroptosis-related genes (NRGs) show distinct expression and prognostic value across gynecologic cancers (GCs). Understanding these NRGs can guide targeted therapies and improve patient outcomes for cancers like ovarian cancer.
Area of Science:
- Oncology
- Molecular Biology
- Genetics
Background:
- Necroptosis is increasingly recognized for its role in malignant tumor development, progression, and drug resistance.
- Targeting necroptosis pathways presents a potential therapeutic avenue for gynecologic cancers (GCs).
Purpose of the Study:
- To comprehensively analyze the expression patterns and prognostic significance of necroptosis-related genes (NRGs) across multiple gynecologic cancers.
- To develop and validate a prognostic signature based on NRGs for GCs.
Main Methods:
- Utilized public databases (TCGA, GTEx) and statistical analyses (Linear regression, Empirical Bayesian, Cox analysis) to explore NRG expression, copy number variation (CNV), and methylation.
- Developed prognostic NRG-signatures and necroptosis-scores using LASSO Cox regression or principal component analysis.
- Assessed tumor mutational burden, immune status, and drug sensitivity associated with the NRG-signatures. Validated NRG expression in ovarian cancer (OV) tissues via Quantitative Real-time PCR.
Main Results:
- Confirmed significant roles of NRGs in expression, prognosis, CNV, and methylation across four GCs (CESC, OV, UCEC, UCS), highlighting both consistencies and differences.
- Established prognostic NRG-signatures with independent prognostic value.
- Identified potential sensitivity to PDL1 response and immune checkpoint blockade therapy in patients with lower risk scores. Revealed differential drug sensitivities between risk groups for each GC type.
Conclusions:
- The comprehensive analysis of NRGs and the developed NRG-signature reveal similarities and differences across GCs.
- NRGs and the NRG-signature hold potential for guiding prognostic assessment and therapeutic strategies in gynecologic cancers.
- Further investigation into NRGs could lead to improved treatment outcomes for GC patients.
