AIMC Topic: Immunotherapy

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Applicability analysis of immunotherapy for lung cancer patients based on deep learning.

Methods (San Diego, Calif.)
According to global and Chinese cancer statistics, lung cancer is the second most common cancer globally with the highest mortality rate and a severe threat to human life and health. In recent years, immunotherapy has made significant breakthroughs i...

Deep learning using bulk RNA-seq data expands cell landscape identification in tumor microenvironment.

Oncoimmunology
The tumor microenvironment (TME) profoundly influences tumor progression and affects immunotherapy responses and resistance. Understanding its heterogeneity is the key for developing immunotherapy. However, the available methods can only partially po...

Integrated Machine Learning and Bioinformatic Analyses Constructed a Novel Stemness-Related Classifier to Predict Prognosis and Immunotherapy Responses for Hepatocellular Carcinoma Patients.

International journal of biological sciences
Immunotherapy has made great progress in hepatocellular carcinoma (HCC), yet there is still a lack of biomarkers for predicting response to it. Cancer stem cells (CSCs) are the primary cause of the tumorigenesis, metastasis, and multi-drug resistance...

DeepTI: A deep learning-based framework decoding tumor-immune interactions for precision immunotherapy in oncology.

SLAS discovery : advancing life sciences R & D
BACKGROUND: Increasing evidence suggests the immunomodulatory potential of genes in oncology. But the identification of immune attributes of genes is costly and time-consuming, which leads to an urgent demand to develop a prediction model.

A Pan-Cancer Analysis of Predictive Methylation Signatures of Response to Cancer Immunotherapy.

Frontiers in immunology
Recently, tumor immunotherapy based on immune checkpoint inhibitors (ICI) has been introduced and widely adopted for various tumor types. Nevertheless, tumor immunotherapy has a few drawbacks, including significant uncertainty of outcome, the possibi...

Deep learning model enables the discovery of a novel immunotherapeutic agent regulating the kynurenine pathway.

Oncoimmunology
Kynurenine (Kyn) is a key inducer of an immunosuppressive tumor microenvironment (TME). Although indoleamine 2,3-dioxygenase (IDO)-selective inhibitors have been developed to suppress the Kyn pathway, the results were not satisfactory due to the pres...

Methodological advances in the discovery of novel neuroblastoma therapeutics.

Expert opinion on drug discovery
INTRODUCTION: Neuroblastoma is a cancer of the sympathetic nervous system that causes up to 15% of cancer-related deaths among children. Among the ~1,000 newly diagnosed cases per year in Europe, more than half are classified as high-risk, with a 5-y...

Detecting immunotherapy-sensitive subtype in gastric cancer using histologic image-based deep learning.

Scientific reports
Immune checkpoint inhibitor (ICI) therapy is widely used but effective only in a subset of gastric cancers. Epstein-Barr virus (EBV)-positive and microsatellite instability (MSI) / mismatch repair deficient (dMMR) tumors have been reported to be high...