AIMC Topic: Immune Checkpoint Inhibitors

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A deep learning model and human-machine fusion for prediction of EBV-associated gastric cancer from histopathology.

Nature communications May 19, 2022
Epstein-Barr virus-associated gastric cancer (EBVaGC) shows a robust response to immune checkpoint inhibitors. Therefore, a cost-efficient and accessible tool is needed for discriminating EBV status in patients with gastric cancer. Here we introduce ...
Stomach Neoplasms Deep Learning Immune Checkpoint Inhibitors Epstein-Barr Virus Infections Herpesvirus 4, Human Humans
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A Pan-Cancer Analysis of Predictive Methylation Signatures of Response to Cancer Immunotherapy.

Frontiers in immunology Dec 9, 2021
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...
Humans Biomarkers, Tumor Neoplasms Transcriptome Immunotherapy Immune Checkpoint Inhibitors Treatment Outcome Support Vector Machine DNA Methylation
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Predicting response to immunotherapy plus chemotherapy in patients with esophageal squamous cell carcinoma using non-invasive Radiomic biomarkers.

BMC cancer Oct 30, 2021
OBJECTIVES: To develop and validate a radiomics model for evaluating treatment response to immune-checkpoint inhibitor plus chemotherapy (ICI + CT) in patients with advanced esophageal squamous cell carcinoma (ESCC).
Humans Tomography, X-Ray Computed Female Support Vector Machine Nomograms Carboplatin Antineoplastic Combined Chemotherapy Protocols Docetaxel Biomarkers, Tumor Bias Treatment Outcome Esophageal Squamous Cell Carcinoma Male Esophageal Neoplasms Antibodies, Monoclonal, Humanized Middle Aged Combined Modality Therapy Immune Checkpoint Inhibitors
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Raman Spectroscopy and Machine Learning Reveals Early Tumor Microenvironmental Changes Induced by Immunotherapy.

Cancer research Oct 13, 2021
Cancer immunotherapy provides durable clinical benefit in only a small fraction of patients, and identifying these patients is difficult due to a lack of reliable biomarkers for prediction and evaluation of treatment response. Here, we demonstrate th...
Mice Immunotherapy Spectrum Analysis, Raman Mice, Inbred BALB C Tumor Microenvironment Animals Immune Checkpoint Inhibitors B7-H1 Antigen Colonic Neoplasms Tumor Cells, Cultured CTLA-4 Antigen Machine Learning
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Systems biology informed neural networks (SBINN) predict response and novel combinations for PD-1 checkpoint blockade.

Communications biology Jul 15, 2021
Anti-PD-1 immunotherapy has recently shown tremendous success for the treatment of several aggressive cancers. However, variability and unpredictability in treatment outcome have been observed, and are thought to be driven by patient-specific biology...
Humans Neural Networks, Computer Female Aged Systems Biology Programmed Cell Death 1 Receptor Adult Male Middle Aged Immune Checkpoint Inhibitors
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Clinical decision support algorithm based on machine learning to assess the clinical response to anti-programmed death-1 therapy in patients with non-small-cell lung cancer.

European journal of cancer (Oxford, England : 1990) Jun 26, 2021
OBJECTIVE: Anti-programmed death (PD)-1 therapy confers sustainable clinical benefits for patients with non-small-cell lung cancer (NSCLC), but only some patients respond to the treatment. Various clinical characteristics, including the PD-ligand 1 (...
Middle Aged Immune Checkpoint Inhibitors Lung Neoplasms Carcinoma, Non-Small-Cell Lung Humans Machine Learning Female Aged Aged, 80 and over Adult Male
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Analysis of Tumor Microenvironment Characteristics in Bladder Cancer: Implications for Immune Checkpoint Inhibitor Therapy.

Frontiers in immunology Apr 15, 2021
The tumor microenvironment (TME) plays a crucial role in cancer progression and recent evidence has clarified its clinical significance in predicting outcomes and efficacy. However, there are no studies on the systematic analysis of TME characteristi...
Tumor Microenvironment Biomarkers, Tumor Humans Immune Checkpoint Inhibitors Immunophenotyping Urinary Bladder Neoplasms Machine Learning Algorithms Prognosis
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Assessing PD-L1 expression in non-small cell lung cancer and predicting responses to immune checkpoint inhibitors using deep learning on computed tomography images.

Theranostics Jan 1, 2021
This study aimed to use computed tomography (CT) images to assess PD-L1 expression in non-small cell lung cancer (NSCLC) and predict response to immunotherapy. We retrospectively analyzed a PD-L1 expression dataset that consisted of 939 consecutive...
Carcinoma, Non-Small-Cell Lung Retrospective Studies Immune Checkpoint Inhibitors Tomography, X-Ray Computed Lung Neoplasms Aged Female B7-H1 Antigen Male Immunotherapy Humans Middle Aged Deep Learning
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Using Machine Learning Algorithms to Predict Immunotherapy Response in Patients with Advanced Melanoma.

Clinical cancer research : an official journal of the American Association for Cancer Research Nov 18, 2020
PURPOSE: Several biomarkers of response to immune checkpoint inhibitors (ICI) show potential but are not yet scalable to the clinic. We developed a pipeline that integrates deep learning on histology specimens with clinical data to predict ICI respon...
Skin Humans Immune Checkpoint Inhibitors Middle Aged Machine Learning Image Processing, Computer-Assisted Skin Neoplasms Progression-Free Survival Risk Assessment Prospective Studies Follow-Up Studies Aged Drug Resistance, Neoplasm Disease Progression Prognosis Neoplasm Staging Adult ROC Curve Female Male Melanoma
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Biomarkers of the Response to Immune Checkpoint Inhibitors in Metastatic Urothelial Carcinoma.

Frontiers in immunology Aug 25, 2020
The mechanisms underlying the resistance to immune checkpoint inhibitors (ICIs) therapy in metastatic urothelial carcinoma (mUC) patients are not clear. It is of great significance to discern mUC patients who could benefit from ICI therapy in clinica...
Drug Resistance, Neoplasm Risk Assessment Urothelium Female Gene Expression Profiling Humans Immune Checkpoint Inhibitors Antibodies, Monoclonal, Humanized Risk Factors Transcriptome Machine Learning B7-H1 Antigen Urinary Bladder Neoplasms Biomarkers, Tumor Time Factors Decision Support Techniques Nomograms Predictive Value of Tests Clinical Decision-Making Male Treatment Outcome Carcinoma
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