A multiparametric approach to improve the prediction of response to immunotherapy in patients with metastatic NSCLC

[1]  Dorit Merhof,et al.  Radiomics feature reproducibility under inter-rater variability in segmentations of CT images , 2020, Scientific Reports.

[2]  S. Fröhling,et al.  Harmonization and Standardization of Panel-Based Tumor Mutational Burden (TMB) Measurement: Real-World Results and Recommendations of the QuIP Study. , 2020, Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer.

[3]  T. Jiang,et al.  Pan-cancer analysis of ARID1A Alterations as Biomarkers for Immunotherapy Outcomes , 2020, Journal of Cancer.

[4]  A. Madabhushi,et al.  Changes in CT Radiomic Features Associated with Lymphocyte Distribution Predict Overall Survival and Response to Immunotherapy in Non–Small Cell Lung Cancer , 2019, Cancer Immunology Research.

[5]  J. E. van Timmeren,et al.  Can radiomics help to predict skeletal muscle response to chemotherapy in stage IV non-small cell lung cancer? , 2019, European journal of cancer.

[6]  S. Digumarthy,et al.  Outcomes to first-line pembrolizumab in patients with non-small cell lung cancer and very high PD-L1 expression. , 2019, Annals of oncology : official journal of the European Society for Medical Oncology.

[7]  S. Fröhling,et al.  Optimizing panel-based tumor mutational burden (TMB) measurement. , 2019, Annals of oncology : official journal of the European Society for Medical Oncology.

[8]  Luca Mazzarella,et al.  Tumor mutational burden quantification from targeted gene panels: major advancements and challenges , 2019, Journal of Immunotherapy for Cancer.

[9]  Jianying Zhou,et al.  Pembrolizumab versus chemotherapy for previously untreated, PD-L1-expressing, locally advanced or metastatic non-small-cell lung cancer (KEYNOTE-042): a randomised, open-label, controlled, phase 3 trial , 2019, The Lancet.

[10]  H. Aerts,et al.  Predicting response to cancer immunotherapy using noninvasive radiomic biomarkers , 2019, Annals of oncology : official journal of the European Society for Medical Oncology.

[11]  Jing Zhao,et al.  Assessment of Blood Tumor Mutational Burden as a Potential Biomarker for Immunotherapy in Patients With Non–Small Cell Lung Cancer With Use of a Next-Generation Sequencing Cancer Gene Panel , 2019, JAMA oncology.

[12]  K. Kerr,et al.  Comparing and contrasting predictive biomarkers for immunotherapy and targeted therapy of NSCLC , 2019, Nature Reviews Clinical Oncology.

[13]  Z. Zeng,et al.  Role of the tumor microenvironment in PD-L1/PD-1-mediated tumor immune escape , 2019, Molecular Cancer.

[14]  M. Zaidi,et al.  The Interferon-Gamma Paradox in Cancer. , 2019, Journal of interferon & cytokine research : the official journal of the International Society for Interferon and Cytokine Research.

[15]  L. Sequist,et al.  24‐Month Overall Survival from KEYNOTE‐021 Cohort G: Pemetrexed and Carboplatin with or without Pembrolizumab as First‐Line Therapy for Advanced Nonsquamous Non–Small Cell Lung Cancer , 2019, Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer.

[16]  Massimo Bellomi,et al.  Radiomics: the facts and the challenges of image analysis , 2018, European Radiology Experimental.

[17]  E. Neri,et al.  Radiomics and liquid biopsy in oncology: the holons of systems medicine , 2018, Insights into Imaging.

[18]  P. Hofman,et al.  Tumor mutational burden assessment as a predictive biomarker for immunotherapy in lung cancer patients: getting ready for prime-time or not? , 2018, Translational lung cancer research.

[19]  A. Tafreshi,et al.  Pembrolizumab plus Chemotherapy for Squamous Non–Small‐Cell Lung Cancer , 2018, The New England journal of medicine.

[20]  N. Paragios,et al.  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, The Lancet. Oncology.

[21]  C. Peng,et al.  Epidermal growth factor induces STAT1 expression to exacerbate the IFNr‐mediated PD‐L1 axis in epidermal growth factor receptor‐positive cancers , 2018, Molecular carcinogenesis.

[22]  L. Ni,et al.  Interferon gamma in cancer immunotherapy , 2018, Cancer medicine.

[23]  Isabelle Salmon,et al.  Methods of measurement for tumor mutational burden in tumor tissue. , 2018, Translational lung cancer research.

[24]  T. Nakajima,et al.  Changes in programmed death ligand 1 expression in non-small cell lung cancer patients who received anticancer treatments , 2018, International Journal of Clinical Oncology.

[25]  Arun Ahuja,et al.  Genomic Features of Response to Combination Immunotherapy in Patients with Advanced Non-Small-Cell Lung Cancer , 2018, Cancer cell.

[26]  M. Oliveira,et al.  Interferon-Gamma at the Crossroads of Tumor Immune Surveillance or Evasion , 2018, Front. Immunol..

[27]  G. Mills,et al.  ARID1A deficiency promotes mutability and potentiates therapeutic antitumor immunity unleashed by immune checkpoint blockade , 2018, Nature Medicine.

[28]  J. Canales‐Vázquez,et al.  Radiomics of CT Features May Be Nonreproducible and Redundant: Influence of CT Acquisition Parameters. , 2018, Radiology.

[29]  S. Novello,et al.  Pembrolizumab plus Chemotherapy in Metastatic Non–Small‐Cell Lung Cancer , 2018, The New England journal of medicine.

[30]  A. Anichini,et al.  The non-small cell lung cancer immune landscape: emerging complexity, prognostic relevance and prospective significance in the context of immunotherapy , 2018, Cancer Immunology, Immunotherapy.

[31]  E. Vasile,et al.  PD-L1 mRNA expression in plasma-derived exosomes is associated with response to anti-PD-1 antibodies in melanoma and NSCLC , 2018, British Journal of Cancer.

[32]  Ahmet Zehir,et al.  Molecular Determinants of Response to Anti-Programmed Cell Death (PD)-1 and Anti-Programmed Death-Ligand 1 (PD-L1) Blockade in Patients With Non-Small-Cell Lung Cancer Profiled With Targeted Next-Generation Sequencing. , 2018, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[33]  Yoshiyuki Suzuki,et al.  PD‐L1 expression is mainly regulated by interferon gamma associated with JAK‐STAT pathway in gastric cancer , 2017, Cancer science.

[34]  T. Nagayasu,et al.  Intratumoral heterogeneity of programmed cell death ligand-1 expression is common in lung cancer , 2017, PloS one.

[35]  Kyung-Hee Kim,et al.  Association of PD-L1 expression and PD-L1 gene polymorphism with poor prognosis in lung adenocarcinoma and squamous cell carcinoma. , 2017, Human pathology.

[36]  Ying Sun,et al.  Genomic Analysis of Tumor Microenvironment Immune Types across 14 Solid Cancer Types: Immunotherapeutic Implications , 2017, Theranostics.

[37]  Seokjin Kim,et al.  Constructing a Watts-Strogatz network from a small-world network with symmetric degree distribution , 2017, PloS one.

[38]  Levi Garraway,et al.  Analysis of 100,000 human cancer genomes reveals the landscape of tumor mutational burden , 2017, Genome Medicine.

[39]  G. Jenster,et al.  The Detection of Androgen Receptor Splice Variant 7 in Plasma-derived Exosomal RNA Strongly Predicts Resistance to Hormonal Therapy in Metastatic Prostate Cancer Patients. , 2017, European urology.

[40]  Young Hak Kim,et al.  Clinical Impact of Single Nucleotide Polymorphism in PD-L1 on Response to Nivolumab for Advanced Non-Small-Cell Lung Cancer Patients , 2017, Scientific Reports.

[41]  L. Martí-Bonmatí,et al.  Development of imaging biomarkers and generation of big data , 2017, La radiologia medica.

[42]  J. Park,et al.  Functional polymorphisms in PD-L1 gene are associated with the prognosis of patients with early stage non-small cell lung cancer. , 2017, Gene.

[43]  H. Ishwaran,et al.  Tumor Interferon Signaling Regulates a Multigenic Resistance Program to Immune Checkpoint Blockade , 2016, Cell.

[44]  P. Park,et al.  ARID1A loss impairs enhancer-mediated gene regulation and drives colon cancer in mice , 2016, Nature Genetics.

[45]  M. A. Alonso,et al.  Biogenesis and Function of T Cell-Derived Exosomes , 2016, Front. Cell Dev. Biol..

[46]  Wei Qian,et al.  Fusion of Quantitative Image and Genomic Biomarkers to Improve Prognosis Assessment of Early Stage Lung Cancer Patients , 2016, IEEE Transactions on Biomedical Engineering.

[47]  Y. Shentu,et al.  Pembrolizumab versus docetaxel for previously treated, PD-L1-positive, advanced non-small-cell lung cancer (KEYNOTE-010): a randomised controlled trial , 2016, The Lancet.

[48]  R. Kalluri The biology and function of exosomes in cancer. , 2016, The Journal of clinical investigation.

[49]  N. Matsumura,et al.  Dual Faces of IFNγ in Cancer Progression: A Role of PD-L1 Induction in the Determination of Pro- and Antitumor Immunity , 2016, Clinical Cancer Research.

[50]  James R. Eshleman,et al.  Microsatellite Instability as a Biomarker for PD-1 Blockade , 2016, Clinical Cancer Research.

[51]  E. Vasile,et al.  Contribution of KRAS mutations and c.2369C > T (p.T790M) EGFR to acquired resistance to EGFR-TKIs in EGFR mutant NSCLC: a study on circulating tumor DNA , 2016, Oncotarget.

[52]  Richard Torres,et al.  Computational Approach to Annotating Variants of Unknown Significance in Clinical Next Generation Sequencing. , 2015, Laboratory medicine.

[53]  L. Crinò,et al.  Nivolumab versus Docetaxel in Advanced Squamous-Cell Non-Small-Cell Lung Cancer. , 2015, The New England journal of medicine.

[54]  Martin L. Miller,et al.  Mutational landscape determines sensitivity to PD-1 blockade in non–small cell lung cancer , 2015, Science.

[55]  N. Matsumura,et al.  IFN-γ from lymphocytes induces PD-L1 expression and promotes progression of ovarian cancer , 2015, British Journal of Cancer.

[56]  N. Ready,et al.  Surrogate clinical endpoints to predict overall survival in non-small cell lung cancer trials-are we in a new era? , 2015, Translational lung cancer research.

[57]  Clotilde Théry,et al.  Biogenesis and secretion of exosomes. , 2014, Current opinion in cell biology.

[58]  P. Lambin,et al.  Robust Radiomics Feature Quantification Using Semiautomatic Volumetric Segmentation , 2014, PloS one.

[59]  Samuel H. Hawkins,et al.  Reproducibility and Prognosis of Quantitative Features Extracted from CT Images. , 2014, Translational oncology.

[60]  M. Socinski,et al.  The Clinical Viewpoint: Definitions, Limitations of RECIST, Practical Considerations of Measurement , 2013, Clinical Cancer Research.

[61]  Andre Dekker,et al.  Radiomics: the process and the challenges. , 2012, Magnetic resonance imaging.

[62]  Qiao Li,et al.  Tumor cell-derived exosomes: a message in a bottle. , 2012, Biochimica et biophysica acta.

[63]  Timo Kohlberger,et al.  Multi-stage Learning for Robust Lung Segmentation in Challenging CT Volumes , 2011, MICCAI.

[64]  R. Vile Faculty Opinions recommendation of IFNgamma and lymphocytes prevent primary tumour development and shape tumour immunogenicity. , 2001 .

[65]  R. Schreiber,et al.  IFNγ and lymphocytes prevent primary tumour development and shape tumour immunogenicity , 2001, Nature.

[66]  A. Karantanas,et al.  CT Measurement of Lung Density , 1999, Acta radiologica.

[67]  B. H. Cooper,et al.  A serological comparison of Phialophora verrucosa, Fonsecaea pedrosoi and Cladosporium carrionii using immunodiffusion and immunoelectrophoresis. , 1970, Sabouraudia.

[68]  J. Brenton,et al.  Unravelling tumour heterogeneity using next-generation imaging: radiomics, radiogenomics, and habitat imaging. , 2017, Clinical radiology.

[69]  Christopher B Wilson,et al.  Regulation of interferon-gamma during innate and adaptive immune responses. , 2007, Advances in immunology.

[70]  Sharon L. Milgram,et al.  The Small World Problem , 1967 .