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    Home > Active Ingredient News > Antitumor Therapy > Huazhong University of Science and Technology and other organizations cooperated with Chen Gang/Zhang Qinghua and others to develop new classification methods to better treat cervical cancer

    Huazhong University of Science and Technology and other organizations cooperated with Chen Gang/Zhang Qinghua and others to develop new classification methods to better treat cervical cancer

    • Last Update: 2021-04-28
    • Source: Internet
    • Author: User
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    iNature cervical cancer is still the most common cancer among women worldwide, with approximately 570,000 newly diagnosed patients and 311,000 deaths each year.

    Neoadjuvant chemotherapy (NACT) is still an attractive alternative to control locally advanced cervical cancer.

    However, approximately 15–34% of women do not respond to induction therapy, thus unnecessarily delaying effective topical treatment.

    On March 18, 2021, Chen Gang, Zhang Qinghua and Hu Zheng of Huazhong University of Science and Technology jointly published an online publication titled "A Fifteen-Gene Classifier to Predict Neoadjuvant Chemotherapy Responses in Patients with Stage IB to IIB Squamous Cervical" in Advanced Science (IF=16) Cancer" research paper, the study identified patient-specific somatic mutations that caused NACT non-response through whole exome sequencing.

    Next, CRISPR/Cas9-based library screening based on these genes was performed to confirm their biological contribution to drug resistance.

    Through the combination of generalized linear regression analysis and logistic regression model, a classifier of 15 genes was developed.

    In an independently verified cohort of 102 patients, the classifier showed good predictive power with an area under the curve of 0.
    80.

    In addition, in univariate (odds ratio, 10.
    8;) and multivariate analysis (odds ratio, 17.
    34), all 15 gene classifiers were significantly correlated with patients' responsiveness to NACT.

    In short, the use of 15 gene classifiers can accurately predict the clinical response to NACT before treatment, which is a promising method to guide the selection of treatment strategies suitable for locally advanced cervical cancer.

    Cervical cancer remains the most common cancer among women worldwide, with approximately 570,000 newly diagnosed patients and 311,000 deaths each year.

    Patients with stage IB to IIB cervical cancer can be treated with concurrent radiotherapy and chemotherapy (CCRT) or radical hysterectomy (RH), including pelvic lymph node dissection.

    In most developed countries, CCRT is preferred.

    However, pelvic radiation therapy may cause side effects, including ovarian failure in premenopausal women, radiation cystitis, rectal bleeding, and vaginal stricture.

    Another treatment recommendation is RH with pelvic lymph node dissection.

    However, in addition to the fact that large tumors are difficult to remove by surgery, the large number of vascular cancer emboli found in patients with locally advanced tumors means that it is more likely to spread throughout the body.

    Therefore, it is necessary to explore more effective treatment methods for stage IB to stage IIB cervical cancer.

    Neoadjuvant chemotherapy (NACT) followed by RH is considered an attractive strategy for patients with stage IB to stage IIB cervical cancer.

    Cervical cancer has a high response rate to taxane and platinum chemotherapy.

    The potential advantages of NACT include: i) reducing tumor size and eradicating micrometastasis, providing better local control for subsequent RH; ii) compared with CCRT, it has better toxicity and does not affect survival benefits.

    Although NACT should be used as a better method for the treatment of locally advanced cervical cancer (LACC) is still to be discussed, but even in areas where radiotherapy is available, NACT may still become the standard treatment.

    Different experiences from Europe, Asia and South America show that the use of NACT followed by RH or chemoradiation in LACC cases can improve the 5-year survival rate.

    Despite the advantages, a major problem with NACT is that approximately 15–34% of patients do not respond to induction therapy, thus unnecessarily delaying effective local treatment.

    These findings emphasize the need to establish selection criteria for patients who are willing to receive treatment to benefit the most from NACT.

    With the development of next-generation high-throughput sequencing technology, a comprehensive genome map has been obtained and systematically analyzed to characterize tumor-related mutations that can predict treatment response.

    This is expected to predict the benefits of chemotherapy for breast cancer, gastric cancer and chronic myelogenous leukemia.

    In this study, the development and validation of a multi-genome is reported, which is used to predict the clinical response of patients with stage IB to stage IIB cervical cancer to NACT.

    The predictive model allows the selection of patients who will benefit most from NACT, while avoiding the side effects of other patients and the delay of CCRT or RH.

    In addition to current clinical parameters, this also provides a more careful and personalized risk assessment.

    The study used whole-exome sequencing to identify patient-specific somatic mutations that caused NACT non-response.

    Next, CRISPR/Cas9-based library screening based on these genes was performed to confirm their biological contribution to drug resistance.

    Through the combination of generalized linear regression analysis and logistic regression model, a classifier of 15 genes was developed.

    In an independently validated cohort of 102 patients, the classifier showed good predictive power with an area under the curve of 0.
    80.

    In addition, in univariate (odds ratio, 10.
    8;) and multivariate analysis (odds ratio, 17.
    34), all 15 gene classifiers were significantly correlated with patients' responsiveness to NACT.

    In short, the use of 15 gene classifiers can accurately predict the clinical response to NACT before treatment, which is a promising method to guide the selection of treatment strategies suitable for locally advanced cervical cancer.

    Reference message: https://onlinelibrary.
    wiley.
    com/doi/10.
    1002/advs.
    202001978
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