New Tool K2Taxonomer Boosts Breast Cancer Survival Prediction
A groundbreaking study published in Nucleic Acids Research has shed new light on breast cancer survival rates. Researchers from the German Cancer Research Center (DKFZ) and Heidelberg University, supported by various foundations, have developed a new computational tool called K2Taxonomer. This tool, now publicly available, has shown remarkable accuracy in analyzing single-cell data from breast tumor-infiltrating lymphocytes (TILs).
K2Taxonomer was employed to characterize a transcriptional signature common to multiple immune T cell subsets. This signature was found to be associated with better survival in breast cancer patients. The study also revealed key signaling pathways, such as PI3K-AKT and MAPK, involved in the aggressiveness and targeted therapy response of head and neck cancer. Collaborators are now using K2Taxonomer to analyze single cell transcriptomics data from head and neck cancer, aiming to identify important signaling pathways related to tumor aggressiveness and response to targeted treatment.
The methodology, which can be applied to analyze other components of a tumor, including different types of malignant cells, tumor stroma, and cancer-associated adipocytes, expands upon previous findings. It was used to analyze the transcriptome of breast TILs on a single-cell basis, suggesting features of an effective cancer immune response. This could enable better prediction of breast cancer patient outcomes and identification of specific immune programs to enhance.
The study demonstrates the high accuracy and superior performance of K2Taxonomer compared to other methods, and its ability to (re)discover known nested molecular classifications. With its public availability, K2Taxonomer promises to be a valuable tool for cancer research, potentially improving patient outcomes through better understanding and prediction of cancer immune responses.
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