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DNA damage signaling following DNA double-strand breaks (DSBs) involves numerous regulating proteins, which dynamically recognize ('read') and alter ('write' or 'erase') histone post-translational modifications (PTMs). Among these PTMs, the ubiquitin syste ...
Ex-vivo drug sensitivity screening (DSS) allows the prediction of cancer treatment effectiveness in a personalized fashion. However, it only provides a readout on mixtures of cells, potentially occulting important information on clinically relevant cell su ...
The last two decades have seen the development of organoid models for many different tissues and organs. Organoids are three-dimensional organ-mimetics derived from stem or progenitor cells comprising various specialized cell types, resembling the architec ...
Aims: Understanding the correlations between underlying medical and personal characteristics of a patient with cancer and the risk of lung metastasis may improve clinical management and outcomes. We used machine learning methodologies to predict the risk o ...
Immune checkpoint blockade (ICB) with antibodies has shown durable clinical responses in a wide range of cancer types, but the overall response rate is still limited. Other effective therapeutic modalities to increase the ICB response rates are urgently ne ...
The mechanisms underlying the multistep process of tumorigenesis can be distilled into a logical framework involving the acquisition of functional capabilities, the so-called hallmarks of cancer, which are collectively envisaged to be necessary for maligna ...
Synthetic messenger RNA (mRNA)-based therapeutics have emerged as promising candidates for the prevention and treatment of a wide range of diseases and disorders. mRNA possesses notable advantages, including exceptional safety, the capacity to replace vari ...
Pulmonary nodules and masses are crucial imaging features in lung cancer screening that require careful management in clinical diagnosis. Despite the success of deep learning-based medical image segmentation, the robust performance on various sizes of lesi ...
Objectives To evaluate the performance of automatic deep learning (DL) algorithm for size, mass, and volume measurements in predicting prognosis of lung adenocarcinoma (LUAD) and compared with manual measurements. Methods A total of 542 patients with clini ...
Adoptive T cell therapyhas successfully been implementedfor thetreatment of cancer. Nevertheless, ex vivo expansion of T cells byartificial antigen-presenting cells (aAPCs) remains cumbersome andcan compromise T cell functionality, thereby limiting their t ...
