Cancer science
-
Cancer is characterized by an accumulation of somatic mutations that represent a source of neoantigens for targeting by antigen-specific T cells. Head and neck squamous cell carcinoma (HNSCC) has a relatively high mutation burden across all cancer types, and cellular immunity to neoantigens likely plays a key role in HNSCC clinical outcomes. Immune checkpoint inhibitors (CPIs) have brought new treatment options and hopes to patients with recurrent and/or metastatic HNSCC. ⋯ One such approach is personalized cancer vaccination targeting tumor-associated antigens and tumor-specific antigens, either as single agents or in combination with other therapies. Recent advances in next-generation genomic sequencing technologies and computational algorithms have enabled efficient identification of somatic mutation-derived neoantigens and are anticipated to facilitate the development of cancer vaccine strategies. Here, we review cancer vaccine approaches against HNSCC, including fundamental mechanisms of a cancer vaccine, considerations for selecting appropriate antigens, and combination therapies.
-
Artificial intelligence (AI) has contributed substantially to the resolution of a variety of biomedical problems, including cancer, over the past decade. Deep learning, a subfield of AI that is highly flexible and supports automatic feature extraction, is increasingly being applied in various areas of both basic and clinical cancer research. ⋯ We also highlight resources and datasets that can help harness the power of AI for cancer research. The development of innovative approaches to and applications of AI will yield important insights in oncology in the coming decade.
-
Review Meta Analysis
MicroRNAs as potential biomarkers for the diagnosis of glioma: A systematic review and meta-analysis.
Glioma is the most common central nervous system tumor and associated with poor prognosis. Identifying effective diagnostic biomarkers for glioma is particularly important in order to guide optimizing treatment. MicroRNAs (miRNAs) have drawn much attention because of their diagnostic value in diverse cancers, including glioma. ⋯ Moreover, AUC of miR-21 was 0.88, with 86% sensitivity and 94% specificity. This study demonstrated that miRNAs could function as potential diagnosis markers in glioma. Detection of miRNAs in CSF and brain tissue displays high accuracy in the diagnosis of glioma.
-
Review Meta Analysis
MicroRNAs as potential biomarkers for the diagnosis of glioma: A systematic review and meta-analysis.
Glioma is the most common central nervous system tumor and associated with poor prognosis. Identifying effective diagnostic biomarkers for glioma is particularly important in order to guide optimizing treatment. MicroRNAs (miRNAs) have drawn much attention because of their diagnostic value in diverse cancers, including glioma. ⋯ Moreover, AUC of miR-21 was 0.88, with 86% sensitivity and 94% specificity. This study demonstrated that miRNAs could function as potential diagnosis markers in glioma. Detection of miRNAs in CSF and brain tissue displays high accuracy in the diagnosis of glioma.
-
Reprogramming technology has enabled the fate conversion of terminally differentiated somatic cells into pluripotent stem cells or into another differentiated state. A dynamic reorganization of epigenetic regulation takes place during cellular reprogramming. Given that reprogramming does not require changes in the underlying genome, the technology can be used to actively modify epigenetic regulation. ⋯ Notably, recent studies using in vivo reprogramming technology to alter epigenetic regulation at organismal levels have revealed unappreciated epigenetic mechanisms in various biological phenomena, including cancer development, tissue regeneration, aging, and rejuvenation in mammals. Moreover, in vivo reprogramming technology can be applied to abrogate epigenetic aberrations associated with aging and cancer, which raises the possibility that the technology could provide a potential strategy to control the fate of detrimental cells such as senescent cells and cancer cells in vivo. Here, we review recent progress and future perspectives of in vivo reprogramming.