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Gene networks and expression quantitative trait loci associated with adjuvant chemotherapy response in high-grade
Jihoon Choi1, Danai G Topouza1, Anastasiya Tarnouskaya2
1Department of Biomedical and Molecular Sciences, Queen's University, Kingston, Ontario, Canada.
Background:
A major impediment in the treatment of ovarian cancer is the relapse of chemotherapy-resistant tumors, which occurs in approximately 25% of patients. A better understanding of the biological mechanisms underlying chemotherapy resistance will improve treatment efficacy through genetic testing and novel therapies.
Methods:
Using data from high-grade serous ovarian carcinoma (HGSOC) patients in the Cancer Genome Atlas (TCGA), we classified those who remained progression-free for 12 months following platinum-taxane combination chemotherapy as "chemo-sensitive" (N = 160) and those who had recurrence within 6 months as "chemo-resistant" (N = 110). Univariate and multivariate analysis of expression microarray data were used to identify differentially expressed genes and co-expression gene networks associated with chemotherapy response. Moreover, we integrated genomics data to determine expression quantitative trait loci (eQTL).
Results:
Differential expression of the Valosin-containing protein (VCP) gene and five co-expression gene networks were significantly associated with chemotherapy response in HGSOC. VCP and the most significant co-expression network module contribute to protein processing in the endoplasmic reticulum, which has been implicated in chemotherapy response. Both univariate and multivariate analysis findings were successfully replicated in an independent ovarian cancer cohort. Furthermore, we identified 192 cis-eQTLs associated with the expression of network genes and 4 cis-eQTLs associated with BRCA2 expression.
Conclusion:
This study implicates both known and novel genes as well as biological processes underlying response to platinum-taxane-based chemotherapy among HGSOC patients.
Insights
Chemotherapy resistance in ovarian cancer is a major challenge. This study identified key genes and biological processes, including Valosin-containing protein (VCP), linked to platinum-taxane chemotherapy response in high-grade serous ovarian carcinoma (HGSOC).
Area of Science:
- Oncology
- Genomics
- Molecular Biology
Background:
- Chemotherapy resistance leads to relapse in approximately 25% of ovarian cancer patients.
- Understanding resistance mechanisms is crucial for improving treatment efficacy.
- Genetic testing and novel therapies can enhance treatment outcomes.
Purpose of the Study:
- To identify genes and biological pathways associated with chemotherapy response in high-grade serous ovarian carcinoma (HGSOC).
- To investigate the role of gene expression and networks in predicting response to platinum-taxane chemotherapy.
- To explore expression quantitative trait loci (eQTLs) related to chemotherapy response.
Main Methods:
- Analysis of gene expression microarray data from HGSOC patients (TCGA).
- Classification of patients into chemo-sensitive and chemo-resistant groups based on treatment outcomes.
- Univariate and multivariate analyses to identify differentially expressed genes and co-expression networks.
- Integration of genomics data to determine eQTLs.
Main Results:
- Differential expression of Valosin-containing protein (VCP) and five co-expression gene networks significantly correlated with chemotherapy response.
- VCP and a key network module are involved in endoplasmic reticulum protein processing, a pathway linked to chemotherapy response.
- Findings were validated in an independent ovarian cancer cohort.
- 192 cis-eQTLs associated with network gene expression and 4 cis-eQTLs with BRCA2 expression were identified.
Conclusions:
- The study identified known and novel genes and biological processes underlying response to platinum-taxane chemotherapy in HGSOC.
- These findings contribute to a better understanding of chemotherapy resistance mechanisms.
- The results may inform the development of targeted therapies and genetic testing strategies.
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