Background: Monoclonal antibodies, as the targeted therapeutic strategies, provide huge clinical benefits for tumor patients. However, after undergoing several times treatment, patients developed drug resistance which is a major bottleneck in clinical cancer therapy. In this study, we aimed to explore the potential molecular mechanism of trastuzumab-resistant and cancer progression, and identify valuable diagnosis biomarkers for gastric cancer.
View Article and Find Full Text PDFBackground: This study aimed to investigate the tumor-related infiltrating lymphocytes (TILs) affecting the response of trastuzumab and identify potential biomarkers based on immune-related genes to improve prognosis and clinical outcomes of targeted therapies in breast cancer.
Methods: Estimation of stromal and immune cells in malignant tumors using expression data (ESTIMATE) was adopted to infer the fraction of stromal and immune cells through utilizing gene expression signatures in breast tumor samples. Cell-type identification by estimating relative subsets of RNA transcript (CIBERSORT) algorithm was applied to characterize cell composition of 22 lymphocytes from breast cancer tissues using their gene expression profiles.
Antibody-drug conjugates (ADCs) combining potent cytotoxicity of small-molecule drugs with the selectivity and excellent pharmacokinetic profile of monoclonal antibody (mAb) are promising therapeutic modalities for a diverse range of cancers. Owing to overexpression in a wide range of tumors, human epidermal growth factor receptor 2 (Her2) is one of the most utilized targeting antigens for ADCs to treat Her2-positive cancers. Owing to the high density of Her2 antigens on the tumor cells and high affinity and high internalization capacity of corresponding antibodies, 56 anti-Her2 ADCs which applied >10 different types of novel payloads had entered preclinical or clinical trials.
View Article and Find Full Text PDFIn this study, we developed a rapid strategy to screen a serum-free medium for culturing the anchorage-dependent PC-3 prostate cancer cells, which was going to be prepared in large scale to generate GM-CSF/TNFα-surface-modified whole cell prostate cancer vaccine. Automated real-time cellular analysis as a rapid and non-invasive technology was used to monitor the growth of PC-3 cells in 16-well plates. At the same time, Plackett-Burman design was employed to identify the most influential formulation by integrating relevant information statistically.
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