Journal
ADVANCED SCIENCE
Volume 8, Issue 10, Pages -Publisher
WILEY
DOI: 10.1002/advs.202001978
Keywords
CRISPR/Cas9-based library screening; neoadjuvant chemotherapy; precision medicine; whole exon sequencing
Categories
Funding
- National Science and Technology Major Project of the Ministry of Science and Technology of China [2018ZX10301402]
- National Natural Science Foundation of China [81630060, 81472783, 81830074]
- Wuhan Science and Technology Bureau [2020020601012324]
- Foundation of Health Commission of Hubei Province of China [WJ2019Q008]
- Funds for International Cooperation and Exchange of the National Natural Science Foundation of China [81761148025]
- National Postdoctoral Program for Innovative Talent [BX20200398]
- China Postdoctoral Science Foundation [2020M672995]
- Guangdong Basic and Applied Basic Research Foundation [2020A1515110170,2114050001278]
- Characteristic Innovation Research Project of University Teachers [2020SWYY07]
Ask authors/readers for more resources
A 15-gene classifier has been developed to accurately predict the clinical response to neoadjuvant chemotherapy in cervical cancer patients, offering a promising approach for guiding the selection of appropriate treatment strategies.
Neoadjuvant chemotherapy (NACT) remains an attractive alternative for controlling locally advanced cervical cancer. However, approximately 15-34% of women do not respond to induction therapy. To develop a risk stratification tool, 56 patients with stage IB-IIB cervical cancer are included in 2 research centers from the discovery cohort. Patient-specific somatic mutations led to NACT non-responsiveness are identified by whole-exome sequencing. Next, CRISPR/Cas9-based library screenings are performed based on these genes to confirm their biological contribution to drug resistance. A 15-gene classifier is developed by generalized linear regression analysis combined with the logistic regression model. In an independent validation cohort of 102 patients, the classifier showed good predictive ability with an area under the curve of 0.80 (95% confidence interval (CI), 0.69-0.91). Furthermore, the 15-gene classifier is significantly associated with patient responsiveness to NACT in both univariate (odds ratio, 10.8; 95% CI, 3.55-32.86; p = 2.8 x 10(-5)) and multivariate analysis (odds ratio, 17.34; 95% CI, 4.04-74.40; p = 1.23 x 10(-4)) in the validation set. In conclusion, the 15-gene classifier can accurately predict the clinical response to NACT before treatment, representing a promising approach for guiding the selection of appropriate treatment strategies for locally advanced cervical cancer.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available