Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

Predicting Durable Responses to Immune Checkpoint Inhibitors in Non-Small-Cell Lung Cancer Using a Multi-Feature Model.

Frontiers in immunology - 1 Jan 2022

Wang Lei, Zhang Hongbing, Pan Chaohu, Yi Jian, Cui Xiaoli, Li Na, Wang Jiaqian, Gao Zhibo, Wu Dongfang, Chen Jun, Jiang Jizong, Chu Qian

Abstract excerpt

Due to the complex mechanisms affecting anti-tumor immune response, a single biomarker is insufficient to identify patients who will benefit from immune checkpoint inhibitors (ICIs) treatment. Therefore, a comprehensive predictive model is urgently required to predict the response to ICIs. A total of 162 non-small-cell lung cancer (NSCLC) patients undergoing ICIs treatment from three independent cohorts were...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Biomarkers, Tumor
Share to Carcinoma, Non-Small-Cell Lung

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Immune Checkpoint Inhibitors

Share to Lung Neoplasms

Share to Mutation

Source

Open in PubMed Open full text

Identifiers

PMID: 35529874
DOI: 10.3389/fimmu.2022.829634
PMCID: PMC9072668

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Predicting Durable Responses to Immune Checkpoint Inhibitors in Non-Small-Cell Lung Cancer Using a Multi-Feature Model.PMID 35529874Read ↗

Robust Prediction of Immune Checkpoint Inhibition Therapy for Non-Small Cell Lung Cancer.Semantic proximity Read ↗

Robust prediction of patient outcomes with immune checkpoint blockade therapy for cancer using common clinical, pathologic, and genomic featuresSemantic proximity Read ↗

A Predictive Model for Evaluating Efficacy of Immunotherapy in Non-small-cell Lung Cancer PatientsSemantic proximity Read ↗

Prediction of 2-Year Mortality in Patients with Advanced Non-Small Cell Lung Cancer Treated with Immune Checkpoint Inhibitors Based on a Machine Learning AlgorithmSemantic proximity Read ↗

Robust prediction of patient outcomes with immune checkpoint blockade therapy for cancer using common clinical, pathologic, and genomic featuresSemantic proximity Read ↗

A Combination of Biomarkers Predict Response to Immune Checkpoint Blockade Therapy in Non-Small Cell Lung Cancer.Semantic proximity Read ↗

Multimodal genomic features predict outcome of immune checkpoint blockade in non-small-cell lung cancerSemantic proximity Read ↗

Using machine learning modeling to explore new immune-related prognostic markers in non-small cell lung cancerSemantic proximity Read ↗

PTPRD mutation is a prognostic biomarker for sensitivity to ICIs treatment in advanced non-small cell lung cancer.Semantic proximity Read ↗

Mutational variant allele frequency profile as a biomarker of response to immune checkpoint blockade in non-small cell lung Cancer.Semantic proximity Read ↗

Radiomics combined with clinical characteristics predicted the progression-free survival time in first-line targeted therapy for advanced non-small cell lung cancer with EGFR mutationSemantic proximity Read ↗

Prediction performance comparison of biomarkers for response to immune checkpoint inhibitors in advanced non-small cell lung cancer.Semantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.