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Score based on gene expression helped predict response to platinum therapy
A score calculated based on the expression of genes associated with DNA repair may help to predict which patients with ovarian cancer will respond well to platinum-based chemotherapy and have positive outcomes.
“This score has the potential to become an important prognostic tool to determine whether advanced-stage ovarian cancer patients will benefit from first-line platinum-based chemotherapy,” researchers wrote.
The researchers hypothesized that a molecular score based on the expression of genes involved in platinum- induced DNA damage repair would predict response in patients with ovarian cancer.
To test this theory, they gathered data from The Cancer Genome Atlas for 151 DNA repair genes from tumors of 511 patients with serous ovarian cystadenocarcinoma. From these 151 genes, they narrowed the scope to 23 genes from four pathways (ATM, FA/HR, NER and TLS).
Based on the presence of these genes, patients were assigned a score: low for patients with scores of 0 to 10 and high for those with scores from 11 to 20.
Results indicated that low scores were associated with worse survival outcomes. Five-year survival in patients with low scores was 17% vs. 40% in patients with high scores. The median OS was 3 years for low scores vs. 4.5 years for high scores. The gene score was the only factor that was linked with OS (high vs. low scores HR=0.40; 95% CI, 0.32-0.66).
The score also was able to predict the likelihood that a patient would achieve a complete response. When patients were classified into the lowest, intermediate or highest tertiles for scores, these were associated with the lowest, intermediate and highest likelihood for complete response. Increasing likelihood for complete response was associated with increased likelihood for survival (see chart).
The researchers then validated these results in two gene expression microarray datasets.
“With additional prospective validation in clinical trials, we hope that the score can become a powerful tool that is useful in stratifying advanced-stage ovarian cancer patients toward optimal treatments incorporating new treatment regimens vs. current standard of care,” the researchers wrote.
References:
- Kang J. J Natl Cancer Inst. 2012;104:670-681.