Artificial Intelligence for predictive biomarker discovery in immuno-oncology: a systematic review

Converging on a Cure: The Roads to Predictive Immunotherapy

(2023) Genevieve L. Stein-O'Brien et al.   Cancer Discovery

Detection of oral squamous cell carcinoma in clinical photographs using a vision transformer

(2023) Tabea Flügge et al.   Scientific Reports

Machine learning and bioinformatics analysis revealed classification and potential treatment strategy in stage 3–4 NSCLC patients

(2022) Chang Li et al.   BMC Medical Genomics

Artificial intelligence predicts immune and inflammatory gene signatures directly from hepatocellular carcinoma histology

(2022) Qinghe Zeng et al.   JOURNAL OF HEPATOLOGY

A short-term follow-up CT based radiomics approach to predict response to immunotherapy in advanced non-small-cell lung cancer

(2022) Jing Gong et al.   OncoImmunology

Machine Learning of Single Cell Transcriptomic Data From anti-PD-1 Responders and Non-responders Reveals Distinct Resistance Mechanisms in Skin Cancers and PDAC

(2022) Ryan Liu et al.   Frontiers in Genetics

Early Readout on Overall Survival of Patients With Melanoma Treated With Immunotherapy Using a Novel Imaging Analysis

(2022) Laurent Dercle et al.   JAMA Oncology

Machine Learning Using Real-World and Translational Data to Improve Treatment Selection for NSCLC Patients Treated with Immunotherapy

(2022) Arsela Prelaj et al.   Cancers

Radiomics-Based Machine Learning for Outcome Prediction in a Multicenter Phase II Study of Programmed Death-Ligand 1 Inhibition Immunotherapy for Glioblastoma

(2022) E. George et al.   AMERICAN JOURNAL OF NEURORADIOLOGY

Dynamic microbiome and metabolome analyses reveal the interaction between gut microbiota and anti‐PD ‐1 based immunotherapy in hepatocellular carcinoma

(2022) Hewei Wu et al.   INTERNATIONAL JOURNAL OF CANCER

Artificial Intelligence–Powered Spatial Analysis of Tumor-Infiltrating Lymphocytes as Complementary Biomarker for Immune Checkpoint Inhibition in Non–Small-Cell Lung Cancer

(2022) Sehhoon Park et al.   JOURNAL OF CLINICAL ONCOLOGY

Pembrolizumab versus chemotherapy for microsatellite instability-high or mismatch repair-deficient metastatic colorectal cancer (KEYNOTE-177): final analysis of a randomised, open-label, phase 3 study

(2022) Luis A Diaz et al.   LANCET ONCOLOGY

Typical tumor immune microenvironment status determine prognosis in lung adenocarcinoma

(2022) Caixia Ren et al.   Translational Oncology

Integrated analysis of single-cell and bulk RNA sequencing data reveals a pan-cancer stemness signature predicting immunotherapy response

(2022) Zhen Zhang et al.   Genome Medicine

Deep learning for predicting immunotherapeutic efficacy in advanced non-small cell lung cancer patients: a retrospective study combining progression-free survival risk and overall survival risk

(2022) Bing-Xi He et al.   Translational Lung Cancer Research

Dynamic peripheral blood immune cell markers for predicting the response of patients with metastatic cancer to immune checkpoint inhibitors

(2022) Chen Wei et al.   CANCER IMMUNOLOGY IMMUNOTHERAPY

Artificial intelligence–powered programmed death ligand 1 analyser reduces interobserver variation in tumour proportion score for non–small cell lung cancer with better prediction of immunotherapy response

(2022) Sangjoon Choi et al.   EUROPEAN JOURNAL OF CANCER

Machine learning models in the prediction of 1-year mortality in patients with advanced hepatocellular cancer on immunotherapy: a proof-of-concept study

(2022) Thomas Ka Luen Lui et al.   Hepatology International

Association of artificial intelligence-powered and manual quantification of programmed death-ligand 1 (PD-L1) expression with outcomes in patients treated with nivolumab ± ipilimumab

(2022) Vipul Baxi et al.   MODERN PATHOLOGY

Network-based machine learning approach to predict immunotherapy response in cancer patients

(2022) JungHo Kong et al.   Nature Communications

Predicting cancer immunotherapy response from gut microbiomes using machine learning models

(2022) Hai Liang et al.   Oncotarget

Using machine learning for mortality prediction and risk stratification in atezolizumab‐treated cancer patients: Integrative analysis of eight clinical trials

(2022) Yougen Wu et al.   Cancer Medicine

Longitudinal plasma proteomic profiling of patients with non-small cell lung cancer undergoing immune checkpoint blockade

(2022) Michal Harel et al.   Journal for ImmunoTherapy of Cancer

Combination of Whole-Body Baseline CT Radiomics and Clinical Parameters to Predict Response and Survival in a Stage-IV Melanoma Cohort Undergoing Immunotherapy

(2022) Felix Peisen et al.   Cancers

Assessing the robustness of radiomics/deep learning approach in the identification of efficacy of anti–PD-1 treatment in advanced or metastatic non-small cell lung carcinoma patients

(2022) Qianqian Ren et al.   Frontiers in Oncology

Artificial intelligence for multimodal data integration in oncology

(2022) Jana Lipkova et al.   CANCER CELL

Machine learning algorithm-generated and multi-center validated melanoma prognostic signature with inspiration for treatment management

(2022) Zaoqu Liu et al.   CANCER IMMUNOLOGY IMMUNOTHERAPY

Machine learning-based exceptional response prediction of nivolumab monotherapy with circulating microRNAs in non-small cell lung cancer

(2022) Yifan Zhang et al.   LUNG CANCER

Artificial intelligence‐driven consensus gene signatures for improving bladder cancer clinical outcomes identified by multi‐center integration analysis

(2022) Hui Xu et al.   Molecular Oncology

Multimodal biomedical AI

(2022) Julián N. Acosta et al.   NATURE MEDICINE

Predicting response to immunotherapy in gastric cancer via multi-dimensional analyses of the tumour immune microenvironment

(2022) Yang Chen et al.   Nature Communications

Deep learning reveals predictive sequence concepts within immune repertoires to immunotherapy

(2022) John-William Sidhom et al.   Science Advances

Pan-cancer landscape of T-cell exhaustion heterogeneity within the tumor microenvironment revealed a progressive roadmap of hierarchical dysfunction associated with prognosis and therapeutic efficacy

(2022) Zicheng Zhang et al.   EBioMedicine

The integrated landscape of eRNA in gastric cancer reveals distinct immune subtypes with prognostic and therapeutic relevance

(2022) Xin Hu et al.   iScience

Deep learning-based image analysis predicts PD-L1 status from H&E-stained histopathology images in breast cancer

(2022) Gil Shamai et al.   Nature Communications

A CT-based Radiomics Signature Is Associated with Response to Immune Checkpoint Inhibitors in Advanced Solid Tumors

(2021) Marta Ligero et al.   RADIOLOGY

Comprehensive Analysis of Ferroptosis Regulators in Lung Adenocarcinomas Identifies Prognostic and Immunotherapy-Related Biomarkers

(2021) Sijin Sun et al.   Frontiers in Molecular Biosciences

Pemetrexed Plus Platinum With or Without Pembrolizumab in Patients With Previously Untreated Metastatic Nonsquamous NSCLC: Protocol-Specified Final Analysis From KEYNOTE-189

(2021) D. Rodríguez-Abreu et al.   ANNALS OF ONCOLOGY

Machine learning revealed stemness features and a novel stemness-based classification with appealing implications in discriminating the prognosis, immunotherapy and temozolomide responses of 906 glioblastoma patients

(2021) Zihao Wang et al.   BRIEFINGS IN BIOINFORMATICS

Five-Year Outcomes With Pembrolizumab Versus Chemotherapy for Metastatic Non–Small-Cell Lung Cancer With PD-L1 Tumor Proportion Score ≥ 50%

(2021) Martin Reck et al.   JOURNAL OF CLINICAL ONCOLOGY

Machine Learning for Prediction of Survival Outcomes with Immune-Checkpoint Inhibitors in Urothelial Cancer

(2021) Ahmad Y. Abuhelwa et al.   Cancers

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

(2021) Beung-Chul Ahn et al.   EUROPEAN JOURNAL OF CANCER

Current status and quality of radiomic studies for predicting immunotherapy response and outcome in patients with non-small cell lung cancer: a systematic review and meta-analysis

(2021) Qiuying Chen et al.   EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING

AI in medicine must be explainable

(2021) Shinjini Kundu   NATURE MEDICINE

Prediction of outcome in patients with non-small cell lung cancer treated with second line PD-1/PDL-1 inhibitors based on clinical parameters: Results from a prospective, single institution study

(2021) Konstantinos Rounis et al.   PLoS One

LAG-3 expression on peripheral blood cells identifies patients with poorer outcomes after immune checkpoint blockade

(2021) Ronglai Shen et al.   Science Translational Medicine

DNA methylation-based prediction of response to immune checkpoint inhibition in metastatic melanoma

(2021) Katharina Filipski et al.   Journal for ImmunoTherapy of Cancer

Non-invasive measurement of PD-L1 status and prediction of immunotherapy response using deep learning of PET/CT images

(2021) Wei Mu et al.   Journal for ImmunoTherapy of Cancer

Clinical Categorization Algorithm (CLICAL) and Machine Learning Approach (SRF-CLICAL) to Predict Clinical Benefit to Immunotherapy in Metastatic Melanoma Patients: Real-World Evidence from the Istituto Nazionale Tumori IRCCS Fondazione Pascale, Napoli, Italy

(2021) Gabriele Madonna et al.   Cancers

Epigenome signature as an immunophenotype indicator prompts durable clinical immunotherapy benefits in lung adenocarcinoma

(2021) Xu Pan et al.   BRIEFINGS IN BIOINFORMATICS

Improved prediction of immune checkpoint blockade efficacy across multiple cancer types

(2021) Diego Chowell et al.   NATURE BIOTECHNOLOGY

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

(2021) Bingxiang Xu et al.   Frontiers in Immunology

Construction and Validation of an Immune Cell Signature Score to Evaluate Prognosis and Therapeutic Efficacy in Hepatocellular Carcinoma

(2021) Linfeng Xu et al.   Frontiers in Genetics

A Machine learning model trained on dual-energy CT radiomics significantly improves immunotherapy response prediction for patients with stage IV melanoma

(2021) Andreas Stefan Brendlin et al.   Journal for ImmunoTherapy of Cancer

Machine Learning for Prediction of Immunotherapy Efficacy in Non-Small Cell Lung Cancer from Simple Clinical and Biological Data

(2021) Sébastien Benzekry et al.   Cancers

Geometric network analysis provides prognostic information in patients with high grade serous carcinoma of the ovary treated with immune checkpoint inhibitors

(2021) Rena Elkin et al.   npj Genomic Medicine

Multifactorial deep learning reveals pan-cancer genomic tumor clusters with distinct immunogenomic landscape and response to immunotherapy

(2020) Feng Xie et al.   CLINICAL CANCER RESEARCH

Deep neural network classification based on somatic mutations potentially predicts clinical benefit of immune checkpoint blockade in lung adenocarcinoma

(2020) Jie Peng et al.   OncoImmunology

Computational recognition of lncRNA signature of tumor-infiltrating B lymphocytes with potential implications in prognosis and immunotherapy of bladder cancer

(2020) Meng Zhou et al.   BRIEFINGS IN BIOINFORMATICS

Radiomics, tumor volume and blood biomarkers for early prediction of pseudoprogression in metastatic melanoma patients treated with immune checkpoint inhibition

(2020) Lucas Basler et al.   CLINICAL CANCER RESEARCH

Identification of Non–Small Cell Lung Cancer Sensitive to Systemic Cancer Therapies Using Radiomics

(2020) Laurent Dercle et al.   CLINICAL CANCER RESEARCH

The FDA approval of pembrolizumab for adult and pediatric patients with tumor mutational burden (TMB) ≥10: a decision centered on empowering patients and their physicians

(2020) V. Subbiah et al.   ANNALS OF ONCOLOGY

A serum protein classifier identifying patients with advanced non-small cell lung cancer who derive clinical benefit from treatment with immune checkpoint inhibitors

(2020) Mirte Muller et al.   CLINICAL CANCER RESEARCH

Predicting response to immunotherapy in advanced non-small-cell lung cancer using tumor mutational burden radiomic biomarker

(2020) Bingxi He et al.   Journal for ImmunoTherapy of Cancer

Tumor mutational burden related classifier is predictive of response to PD-L1 blockade in locally advanced and metastatic urothelial carcinoma

(2020) Yejinpeng Wang et al.   INTERNATIONAL IMMUNOPHARMACOLOGY

Welcoming new guidelines for AI clinical research

(2020) Eric J. Topol   NATURE MEDICINE

Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI extension

(2020) Xiaoxuan Liu et al.   NATURE MEDICINE

Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI extension

(2020) Samantha Cruz Rivera et al.   NATURE MEDICINE

Non-invasive decision support for NSCLC treatment using PET/CT radiomics

(2020) Wei Mu et al.   Nature Communications

Deep learning to estimate RECIST in patients with NSCLC treated with PD-1 blockade

(2020) Kathryn C. Arbour et al.   Cancer Discovery

Novel, non-invasive imaging approach to identify patients with advanced non-small cell lung cancer at risk of hyperprogressive disease with immune checkpoint blockade

(2020) Pranjal Vaidya et al.   Journal for ImmunoTherapy of Cancer

Using Machine Learning Algorithms to Predict Immunotherapy Response in Patients with Advanced Melanoma

(2020) Paul Johannet et al.   CLINICAL CANCER RESEARCH

Systematic review of radiomic biomarkers for predicting immune checkpoint inhibitor treatment outcomes

(2020) Chong Zhang et al.   METHODS

Using deep learning to predict anti-PD-1 response in melanoma and lung cancer patients from histopathology images

(2020) Jing Hu et al.   Translational Oncology

Novel clinical and radiomic predictors of rapid disease progression phenotypes among lung cancer patients treated with immunotherapy: An early report

(2019) Ilke Tunali et al.   LUNG CANCER

Predicting Response to Cancer Immunotherapy using Non-invasive Radiomic Biomarkers

(2019) S Trebeschi et al.   ANNALS OF ONCOLOGY

Randomized phase III KEYNOTE-045 trial of pembrolizumab versus paclitaxel, docetaxel, or vinflunine in recurrent advanced urothelial cancer: results of >2 years of follow-up

(2019) Y Fradet et al.   ANNALS OF ONCOLOGY

Automated image analysis of NSCLC biopsies to predict response to anti-PD-L1 therapy

(2019) Sonja Althammer et al.   Journal for ImmunoTherapy of Cancer

Deep learning can predict microsatellite instability directly from histology in gastrointestinal cancer

(2019) Jakob Nikolas Kather et al.   NATURE MEDICINE

Automatic discovery of image-based signatures for ipilimumab response prediction in malignant melanoma

(2019) Nathalie Harder et al.   Scientific Reports

Pembrolizumab alone or with chemotherapy versus cetuximab with chemotherapy for recurrent or metastatic squamous cell carcinoma of the head and neck (KEYNOTE-048): a randomised, open-label, phase 3 study

(2019) Barbara Burtness et al.   LANCET

Definitions, methods, and applications in interpretable machine learning

(2019) W. James Murdoch et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Changes in CT Radiomic Features Associated with Lymphocyte Distribution Predict Overall Survival and Response to Immunotherapy in Non–Small Cell Lung Cancer

(2019) Mohammadhadi Khorrami et al.   Cancer Immunology Research

The role of PD-L1 expression as a predictive biomarker: an analysis of all US Food and Drug Administration (FDA) approvals of immune checkpoint inhibitors

(2019) Andrew A. Davis et al.   Journal for ImmunoTherapy of Cancer

Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI

(2019) Alejandro Barredo Arrieta et al.   Information Fusion

Machine Learning for Integrating Data in Biology and Medicine: Principles, Practice, and Opportunities

(2018) Marinka Zitnik et al.   Information Fusion

A radiomics approach to assess tumour-infiltrating CD8 cells and response to anti-PD-1 or anti-PD-L1 immunotherapy: an imaging biomarker, retrospective multicohort study

(2018) Roger Sun et al.   LANCET ONCOLOGY

Nivolumab plus ipilimumab or nivolumab alone versus ipilimumab alone in advanced melanoma (CheckMate 067): 4-year outcomes of a multicentre, randomised, phase 3 trial

(2018) Frank Stephen Hodi et al.   LANCET ONCOLOGY

CheckMate 025 Randomized Phase 3 Study: Outcomes by Key Baseline Factors and Prior Therapy for Nivolumab Versus Everolimus in Advanced Renal Cell Carcinoma

(2017) Bernard Escudier et al.   EUROPEAN UROLOGY

Pembrolizumab as Second-Line Therapy for Advanced Urothelial Carcinoma

(2017) Joaquim Bellmunt et al.   NEW ENGLAND JOURNAL OF MEDICINE

Pan-cancer Immunogenomic Analyses Reveal Genotype-Immunophenotype Relationships and Predictors of Response to Checkpoint Blockade

(2017) Pornpimol Charoentong et al.   Cell Reports

A Serum Protein Signature Associated with Outcome after Anti–PD-1 Therapy in Metastatic Melanoma

(2017) Jeffrey S. Weber et al.   Cancer Immunology Research

Pembrolizumab versus Chemotherapy for PD-L1–Positive Non–Small-Cell Lung Cancer

(2016) Martin Reck et al.   NEW ENGLAND JOURNAL OF MEDICINE

The International Metastatic Renal Cell Carcinoma Database Consortium model as a prognostic tool in patients with metastatic renal cell carcinoma previously treated with first-line targeted therapy: a population-based study

(2015) Jenny J Ko et al.   LANCET ONCOLOGY

Deep learning

(2015) Yann LeCun et al.   NATURE

Nivolumab versus Docetaxel in Advanced Squamous-Cell Non–Small-Cell Lung Cancer

(2015) Julie Brahmer et al.   NEW ENGLAND JOURNAL OF MEDICINE

Nivolumab versus Docetaxel in Advanced Nonsquamous Non–Small-Cell Lung Cancer

(2015) Hossein Borghaei et al.   NEW ENGLAND JOURNAL OF MEDICINE

Integrative Analysis of Complex Cancer Genomics and Clinical Profiles Using the cBioPortal

(2013) J. Gao et al.   Science Signaling

The cBio Cancer Genomics Portal: An Open Platform for Exploring Multidimensional Cancer Genomics Data: Figure 1.

(2012) Ethan Cerami et al.   Cancer Discovery

Random survival forests

(2008) Hemant Ishwaran et al.   Annals of Applied Statistics