Related Experiment Video
Updated: Dec 20, 2025
Author Spotlight: Unveiling the Role of TMOD3 in Platinum Resistance and Immune Infiltration in Ovarian Cancer
Published on: August 2, 2024
Identification of the key genes associated with chemotherapy sensitivity in ovarian cancer patients
Hui Zheng1,2, Meiqin Zhang2,3, Shuang Ma4
1Department of Clinical Laboratory, Fudan University Shanghai Cancer Center, Shanghai, China.
Background:
Ovarian cancer (OC) is the deadliest gynecological cancer. The absence of biomarkers in early detection and chemotherapy resistance is a principal cause of treatment failure in OC.
Methods:
In this study, next generation sequencing (NGS) was used to sequence the mRNA of 44 OC patients including 14 chemotherapy insensitive and 18 sensitive patients. Differentially expressed genes (DEGs) from OC patients (compared with healthy controls) and chemotherapy sensitive patients (compared with chemotherapy insensitive patients) were identified by edgeR v3.12.0 in R v3.2.2, which were enriched using Gene Ontology (GO) database and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG). The common DEGs in cancer occurring and chemotherapy sensitivity were further screened. Among them, genes participating in chemotherapy sensitivity associated pathways were regarded as chemotherapy sensitivity-related key genes. Quantitative real-time PCR (qPCR) and immunohistochemistry (IHC) were used to verify the expression of the key genes.
Results:
We found 1588 DEGs between OC patients and healthy controls (HCs), which were mainly enriched in cell cycle pathway. Meanwhile, 249 DEGs were identified between chemotherapy sensitive and insensitive OC patients, which were mainly enriched in MAPK signaling pathway, ERBB signaling pathway, TNF signaling pathway, and IL-17 signaling pathway. Thirty-five DEGs were shared in chemotherapy sensitivity group and cancer occurring group. Among them, there are five genes (JUND, JUNB, MUC5B, NRG1, and NR4A1) participating in the above four chemotherapy sensitivity-related pathways. It is remarkable that JUND is in the upstream of MUC5B in IL-17 signaling pathway and their expressions were verified by qPCR and IHC.
Conclusions:
The expression levels of the key genes related to chemotherapy sensitivity might be used as biomarkers to predict the treatment outcome and as a target to improve prognosis.
Insights
This study identifies key genes related to ovarian cancer chemotherapy resistance. These gene expression levels could serve as biomarkers for predicting treatment success and improving patient outcomes.
Area of Science:
- Gynecological Oncology
- Molecular Biology
- Genomics
Background:
- Ovarian cancer (OC) is a leading cause of cancer death among women.
- Lack of early detection biomarkers and chemotherapy resistance contribute to poor OC treatment outcomes.
Purpose of the Study:
- To identify differentially expressed genes (DEGs) associated with ovarian cancer occurrence and chemotherapy sensitivity.
- To screen for key genes involved in chemotherapy sensitivity pathways for potential biomarker development.
Main Methods:
- Next-generation sequencing (NGS) of mRNA from 44 ovarian cancer patients.
- Differential gene expression analysis using edgeR and enrichment analysis with GO and KEGG.
- Validation of key gene expression using quantitative real-time PCR (qPCR) and immunohistochemistry (IHC).
Main Results:
- 1588 DEGs identified between OC patients and healthy controls, enriched in cell cycle pathways.
- 249 DEGs found between chemotherapy-sensitive and insensitive OC patients, enriched in MAPK, ERBB, TNF, and IL-17 signaling pathways.
- Five key genes (JUND, JUNB, MUC5B, NRG1, NR4A1) identified, with JUND and MUC5B validated in the IL-17 pathway.
Conclusions:
- The identified key genes are significantly associated with ovarian cancer chemotherapy sensitivity.
- Expression levels of these genes may serve as predictive biomarkers for treatment response.
- Targeting these genes could offer novel therapeutic strategies to improve ovarian cancer prognosis.
More Related Videos
09:08Integration of Bioinformatics Approaches and Experimental Validations to Understand the Role of Notch Signaling in Ovarian Cancer
Published on: January 12, 2020
10:27Testing Targeted Therapies in Cancer using Structural DNA Alteration Analysis and Patient-Derived Xenografts
Published on: July 25, 2020
