AIMC Topic: Immunotherapy

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Artificial intelligence-based digital pathology using H&E-stained whole slide images in immuno-oncology: from immune biomarker detection to immunotherapy response prediction.

Journal for immunotherapy of cancer
Immuno-oncology and the advent of immunotherapies, in particular immune checkpoint inhibitors (ICIs), have fundamentally altered the way we treat cancer. Yet only a small subset of patients actually responds to ICIs, and many face significant adverse...

Mitochondrial Pathway Signature (MitoPS) predicts immunotherapy response and reveals NDUFB10 as a key immune regulator in lung adenocarcinoma.

Journal for immunotherapy of cancer
BACKGROUND: Lung adenocarcinoma (LUAD) is the most common subtype of non-small cell lung cancer. Although immune checkpoint inhibitors (ICIs) have brought new treatment options for advanced patients, a considerable proportion still shows limited resp...

Analysis of liquid biopsy by Raman spectroscopy to facilitate prediction of response to immunotherapy in non-small-cell lung cancer (NSCLC) patients.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Immunotherapy has revolutionized lung cancer treatment, yet predicting patient response remains a challenge. This study used Raman spectroscopy to differentiate between non-small-cell lung cancer patients with short-lasting and long-lasting responses...

The evolving role of multimodal imaging, artificial intelligence and radiomics in the radiologic assessment of immune related adverse events.

Clinical imaging
Immunotherapy, in particular checkpoint blockade, has revolutionized the treatment of many advanced cancers. Imaging plays a critical role in assessing both treatment response and the development of immune toxicities. Both conventional imaging and mo...

Gut microbiota and SCFAs improve the treatment efficacy of chemotherapy and immunotherapy in NSCLC.

NPJ biofilms and microbiomes
The role of gut dysbiosis in shaping immunotherapy responses is well-recognized, yet its effect on the therapeutic efficacy of chemotherapy and immunotherapy combinations remains poorly understood. We analyzed gut microbiota in non-small cell lung ca...

Leveraging readily available clinical data with machine learning to predict first-line immunotherapy outcomes in non-small cell lung cancer.

International immunopharmacology
BACKGROUND: Immune checkpoint inhibitors (ICIs) are essential first-line treatments for recurrent or metastatic non-small cell lung cancer (NSCLC). However, predicting their effectiveness and the occurrence of immunotherapy-related adverse events (ir...

Comparative analysis of the tumor microenvironment in primary CNS and testicular large B-cell lymphomas using digital image analysis and its implications for immunotherapy.

Human pathology
Primary large B-cell lymphomas of immune-privileged sites, including primary central nervous system lymphoma (PCNSL) and primary testicular lymphoma (PTL), exhibit distinct clinicopathologic features contributing to aggressive behavior and immune eva...

Machine-learning driven strategies for adapting immunotherapy in metastatic NSCLC.

Nature communications
Immune checkpoint inhibitors (ICIs), either as monotherapy (ICI-Mono) or combined with chemotherapy (ICI-Chemo), improves survival in advanced non-small cell lung cancer (NSCLC). However, prospective guidance for choosing between these options remain...

Beyond the native repertoire.

Science (New York, N.Y.)
Design of T cell receptors by artificial intelligence is poised to accelerate cancer immunotherapy.

Integrative habitat analysis and multi-instance deep learning for predictive model of PD-1/PD-L1 immunotherapy efficacy in NSCLC patients: a dual-center retrospective study.

BMC medical imaging
BACKGROUND: PD-1/PD-L1 immunotherapy represents the primary treatment for advanced NSCLC patients; however, response rates to this therapy vary among individuals. This dual-center study aimed to integrate habitat radiomics and multi-instance deep lea...