AIMC Topic: Antigens, Neoplasm

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Machine learning for the identification of neoantigen-reactive CD8 + T cells in gastrointestinal cancer using single-cell sequencing.

British journal of cancer
BACKGROUND: It appears that tumour-infiltrating neoantigen-reactive CD8 + T (Neo T) cells are the primary driver of immune responses to gastrointestinal cancer in patients. However, the conventional method is very time-consuming and complex for ident...

Artificial intelligence and neoantigens: paving the path for precision cancer immunotherapy.

Frontiers in immunology
Cancer immunotherapy has witnessed rapid advancement in recent years, with a particular focus on neoantigens as promising targets for personalized treatments. The convergence of immunogenomics, bioinformatics, and artificial intelligence (AI) has pro...

Sa-TTCA: An SVM-based approach for tumor T-cell antigen classification using features extracted from biological sequencing and natural language processing.

Computers in biology and medicine
Accurately predicting tumor T-cell antigen (TTCA) sequences is a crucial task in the development of cancer vaccines and immunotherapies. TTCAs derived from tumor cells, are presented to immune cells (T cells) through major histocompatibility complex ...

GraphMHC: Neoantigen prediction model applying the graph neural network to molecular structure.

PloS one
Neoantigens are tumor-derived peptides and are biomarkers that can predict prognosis related to immune checkpoint inhibition by estimating their binding to major histocompatibility complex (MHC) proteins. Although deep neural networks have been prima...

CanVaxKB: a web-based cancer vaccine knowledgebase.

NAR cancer
Cancer vaccines have been increasingly studied and developed to prevent or treat various types of cancers. To systematically survey and analyze different reported cancer vaccines, we developed CanVaxKB (https://violinet.org/canvaxkb), the first web-b...

A facile approach to preparing personalized cancer vaccines using iron-based metal organic framework.

Frontiers in immunology
BACKGROUND: Considering the diversity of tumors, it is of great significance to develop a simple, effective, and low-cost method to prepare personalized cancer vaccines.

Groundwork for AI: Enforcing a benchmark for neoantigen prediction in personalized cancer immunotherapy.

Social studies of science
This article expands on recent studies of machine learning or artificial intelligence (AI) algorithms that crucially depend on benchmark datasets, often called 'ground truths.' These ground-truth datasets gather input-data and output-targets, thereby...

T Cell Epitope Prediction and Its Application to Immunotherapy.

Frontiers in immunology
T cells play a crucial role in controlling and driving the immune response with their ability to discriminate peptides derived from healthy as well as pathogenic proteins. In this review, we focus on the currently available computational tools for ep...

Improvement of Neoantigen Identification Through Convolution Neural Network.

Frontiers in immunology
Accurate prediction of neoantigens and the subsequent elicited protective anti-tumor response are particularly important for the development of cancer vaccine and adoptive T-cell therapy. However, current algorithms for predicting neoantigens are lim...

TAP 1.0: A robust immunoinformatic tool for the prediction of tumor T-cell antigens based on AAindex properties.

Computational biology and chemistry
Immunotherapy is a research area with great potential in drug discovery for cancer treatment. Because of the capacity of tumor antigens to activate the immune response and promote the destruction of tumor cells, they are considered excellent immunoth...