AIMC Topic: CD8-Positive T-Lymphocytes

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MIST: An interpretable and flexible deep learning framework for single-T cell transcriptome and receptor analysis.

Science advances
Joint analysis of transcriptomic and T cell receptor (TCR) features at single-cell resolution provides a powerful approach for in-depth T cell immune function research. Here, we introduce a deep learning framework for single-T cell transcriptome and ...

Immune profile and routine laboratory indicator-based machine learning for prediction of lung cancer.

Computers in biology and medicine
INTRODUCTION: Early diagnosis of lung cancer is still a challenge by using current diagnostic methods.

High density of TCF1+ stem-like tumor-infiltrating lymphocytes is associated with favorable disease-specific survival in NSCLC.

Frontiers in immunology
INTRODUCTION: Tumor-infiltrating lymphocytes are both prognostic and predictive biomarkers for immunotherapy response. However, less is known about the survival benefits oftheir subpopulations.

Machine learning-enhanced immunopeptidomics applied to T-cell epitope discovery for COVID-19 vaccines.

Nature communications
Next-generation T-cell-directed vaccines for COVID-19 focus on establishing lasting T-cell immunity against current and emerging SARS-CoV-2 variants. Precise identification of conserved T-cell epitopes is critical for designing effective vaccines. He...

Identification of gene and protein signatures associated with long-term effects of COVID-19 on the immune system after patient recovery by analyzing single-cell multi-omics data using a machine learning approach.

Vaccine
Viral infections significantly impact the immune system, and impact will persist until recovery. However, the influence of severe acute respiratory syndrome coronavirus 2 infection on the homeostatic immune status and secondary immune response in rec...

Integration of Bioinformatics and Machine Learning to Identify CD8+ T Cell-Related Prognostic Signature to Predict Clinical Outcomes and Treatment Response in Breast Cancer Patients.

Genes
UNLABELLED: The incidence of breast cancer (BC) continues to rise steadily, posing a significant burden on the public health systems of various countries worldwide. As a member of the tumor microenvironment (TME), CD8+ T cells inhibit cancer progress...

Prediction of CD8+T lymphocyte infiltration levels in gastric cancer from contrast-enhanced CT and clinical factors using machine learning.

Medical physics
BACKGROUND: CD8+ T lymphocyte infiltration is closely associated with the prognosis and immunotherapy response of gastric cancer (GC). For now, the examination of CD8 infiltration levels relies on endoscopic biopsy, which is invasive and unsuitable f...

Glycosylphosphatidylinositol anchor biosynthesis pathway-based biomarker identification with machine learning for prognosis and T cell exhaustion status prediction in breast cancer.

Frontiers in immunology
As the primary component of anti-tumor immunity, T cells are prone to exhaustion and dysfunction in the tumor microenvironment (TME). A thorough understanding of T cell exhaustion (TEX) in the TME is crucial for effectively addressing TEX in clinical...