A research team by Prof. Yang Wulin and Dai Haiming from the Hefei Institutes of Physical Science (HFIPS) of the Chinese Academy of Sciences recently proposed a generic classifier that can predict the sensitivity of neoadjuvant chemotherapy for breast cancer in the field of tumor molecular markers.
Breast cancer is a kind of malignant tumor with high clinical and biological heterogeneity. Different subtypes respond to chemotherapy with different clinical characteristics. Therefore, it is important to develop methods to predict treatment sensitivity, which is the basis of precision medicine for breast cancer, so that patients can choose the best treatment strategy and avoid overtreatment.
In this study, the researchers built a prediction model with a 25-gene signature using the least absolute shrinkage and selection operator (LASSO) logistic regression with the help of patient drug response data.
Yang Wulin, who led the research team said, the model has many advantages, it can predict pathologic complete response to paclitaxel and anthracycline-based neoadjuvant chemotherapy with high accuracy and is applicable to various subtypes of breast cancer, demonstrating an important contribution of the immune ecosystem to chemotherapeutic sensitivity.
Having shown good predictive abilities for different batches of data and various breast cancer subtypes, and displaying good generalization ability, this gene signature is expected to be promoted as a new diagnostic scheme to predict the sensitive one to chemotherapy in clinical practice.
Yang said, it can therefore select the optimal scheme for breast cancer and provide patients with chances of precise treatment.
The results have been published in Frontiers in Immunology.
Journal Information: Changfang Fu et al, An Immune-Associated Genomic Signature Effectively Predicts Pathologic Complete Response to Neoadjuvant Paclitaxel and Anthracycline-Based Chemotherapy in Breast Cancer, Frontiers in Immunology (2021). DOI: 10.3389/fimmu.2021.704655