AIMC Topic: T-Lymphocytes

Clear Filters Showing 21 to 30 of 76 articles

Inference of Developmental Hierarchy and Functional States of Exhausted T Cells from Epigenetic Profiles with Deep Learning.

Journal of chemical information and modeling
Exhausted T cells are a key component of immune cells that play a crucial role in the immune response against cancer and influence the efficacy of immunotherapy. Accurate assessment and measurement of T-cell exhaustion (TEX) are critical for understa...

An integrative machine learning model for the identification of tumor T-cell antigens.

Bio Systems
The escalating global incidence of cancer poses significant health challenges, underscoring the need for innovative and more efficacious treatments. Cancer immunotherapy, a promising approach leveraging the body's immune system against cancer, emerge...

iTTCA-MVL: A multi-view learning model based on physicochemical information and sequence statistical information for tumor T cell antigens identification.

Computers in biology and medicine
Immunotherapy is an emerging treatment method aimed at activating the human immune system and relying on its own immune function to kill cancer cells and tumor tissues. It has the advantages of wide applicability and minimal side effects. Effective i...

Broadening the horizon: potential applications of CAR-T cells beyond current indications.

Frontiers in immunology
Engineering immune cells to treat hematological malignancies has been a major focus of research since the first resounding successes of CAR-T-cell therapies in B-ALL. Several diseases can now be treated in highly therapy-refractory or relapsed condit...

Prediction of lymphoma response to CAR T cells by deep learning-based image analysis.

PloS one
Clinical prognostic scoring systems have limited utility for predicting treatment outcomes in lymphomas. We therefore tested the feasibility of a deep-learning (DL)-based image analysis methodology on pre-treatment diagnostic computed tomography (dCT...

RCMNet: A deep learning model assists CAR-T therapy for leukemia.

Computers in biology and medicine
Acute leukemia is a type of blood cancer with a high mortality rate. Current therapeutic methods include bone marrow transplantation, supportive therapy, and chemotherapy. Although a satisfactory remission of the disease can be achieved, the risk of ...

CD147-specific chimeric antigen receptor T cells effectively inhibit T cell acute lymphoblastic leukemia.

Cancer letters
T cell acute lymphoblastic leukemia (T-ALL) is invasive and heterogeneous, and existing therapies are sometimes unsuccessful. Chimeric antigen receptor (CAR) T cell therapy is a breakthrough tumor treatment method, particularly for B cell acute lymph...

T cell immune responses deciphered.

Science (New York, N.Y.)
A machine-learning approach reveals antigen encoding that predicts T cell responses.

Cross-tissue immune cell analysis reveals tissue-specific features in humans.

Science (New York, N.Y.)
Despite their crucial role in health and disease, our knowledge of immune cells within human tissues remains limited. We surveyed the immune compartment of 16 tissues from 12 adult donors by single-cell RNA sequencing and VDJ sequencing generating a ...

iTTCA-MFF: identifying tumor T cell antigens based on multiple feature fusion.

Immunogenetics
Cancer is a terrible disease, recent studies reported that tumor T cell antigens (TTCAs) may play a promising role in cancer treatment. Since experimental methods are still expensive and time-consuming, it is highly desirable to develop automatic com...