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Browsing by Subject "Tumor-infiltrating lymphocytes"
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Item Deep-Learning–Based Characterization of Tumor-Infiltrating Lymphocytes in Breast Cancers From Histopathology Images and Multiomics Data(American Society of Clinical Oncology, 2020-05) Lu, Zixiao; Xu, Siwen; Shao, Wei; Wu, Yi; Zhang, Jie; Han, Zhi; Feng, Qianjin; Huang, Kun; Medicine, School of MedicinePurpose: Tumor-infiltrating lymphocytes (TILs) and their spatial characterizations on whole-slide images (WSIs) of histopathology sections have become crucial in diagnosis, prognosis, and treatment response prediction for different cancers. However, fully automatic assessment of TILs on WSIs currently remains a great challenge because of the heterogeneity and large size of WSIs. We present an automatic pipeline based on a cascade-training U-net to generate high-resolution TIL maps on WSIs. Methods: We present global cell-level TIL maps and 43 quantitative TIL spatial image features for 1,000 WSIs of The Cancer Genome Atlas patients with breast cancer. For more specific analysis, all the patients were divided into three subtypes, namely, estrogen receptor (ER)-positive, ER-negative, and triple-negative groups. The associations between TIL scores and gene expression and somatic mutation were examined separately in three breast cancer subtypes. Both univariate and multivariate survival analyses were performed on 43 TIL image features to examine the prognostic value of TIL spatial patterns in different breast cancer subtypes. Results: The TIL score was in strong association with immune response pathway and genes (eg, programmed death-1 and CLTA4). Different breast cancer subtypes showed TIL score in association with mutations from different genes suggesting that different genetic alterations may lead to similar phenotypes. Spatial TIL features that represent density and distribution of TIL clusters were important indicators of the patient outcomes. Conclusion: Our pipeline can facilitate computational pathology-based discovery in cancer immunology and research on immunotherapy. Our analysis results are available for the research community to generate new hypotheses and insights on breast cancer immunology and development.Item Metabolic interventions: A new insight into the cancer immunotherapy(Elsevier, 2021) Yu, Tao; Dong, Tianhan; Eyvani, Haniyeh; Fang, Yuanzhang; Wang, Xiyu; Zhang, Xinna; Lu, Xiongbin; Medical and Molecular Genetics, School of MedicineMetabolic reprogramming confers cancer cells plasticity and viability under harsh conditions. Such active alterations lead to cell metabolic dependency, which can be exploited as an attractive target in development of effective antitumor therapies. Similar to cancer cells, activated T cells also execute global metabolic reprogramming for their proliferation and effector functions when recruited to the tumor microenvironment (TME). However, the high metabolic activity of rapidly proliferating cancer cells can compete for nutrients with immune cells in the TME, and consequently, suppressing their anti-tumor functions. Thus, therapeutic strategies could aim to restore T cell metabolism and anti-tumor responses in the TME by targeting the metabolic dependence of cancer cells. In this review, we highlight current research progress on metabolic reprogramming and the interplay between cancer cells and immune cells. We also discuss potential therapeutic intervention strategies for targeting metabolic pathways to improve cancer immunotherapy efficacy.Item Tumor-infiltrating lymphocytes: Streamlining a complex manufacturing process(Elsevier, 2019-03) Hopewell, Emily L.; Cox, Cheryl; Pilon-Thomas, Shari; Kelley, Linda L.; Medical and Molecular Genetics, School of MedicineAdoptive cell therapy of tumor-infiltrating lymphocytes has shown promise for treatment of refractory melanoma and other solid malignancies; however, challenges to manufacturing have limited its widespread use. Traditional manufacturing efforts were lengthy, cumbersome and used open culture systems. We describe changes in testing and manufacturing that decreased the process cycle time, enhanced the robustness of critical quality attribute testing and facilitated a functionally closed system. These changes have enabled export of the manufacturing process to support multi-center clinical trials.