Journal ArticleDOI
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
Roger Sun,Roger Sun,Elaine Johanna Limkin,Elaine Johanna Limkin,Maria Vakalopoulou,Maria Vakalopoulou,Laurent Dercle,Laurent Dercle,Stéphane Champiat,Shan Rong Han,Loic Verlingue,David Brandao,Andrea Lancia,Andrea Lancia,Andrea Lancia,Samy Ammari,Antoine Hollebecque,Jean-Yves Scoazec,Jean-Yves Scoazec,Aurélien Marabelle,Christophe Massard,Jean-Charles Soria,Jean-Charles Soria,Charlotte Robert,Nikos Paragios,Nikos Paragios,Eric Deutsch,Charles Ferté,Charles Ferté +28 more
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TLDR
A radiomic signature predictive of immunotherapy response by combining contrast-enhanced CT images and RNA-seq genomic data from tumour biopsies to assess CD8 cell tumour infiltration was developed and validated.Abstract:
Summary Background Because responses of patients with cancer to immunotherapy can vary in success, innovative predictors of response to treatment are urgently needed to improve treatment outcomes. We aimed to develop and independently validate a radiomics-based biomarker of tumour-infiltrating CD8 cells in patients included in phase 1 trials of anti-programmed cell death protein (PD)-1 or anti-programmed cell death ligand 1 (PD-L1) monotherapy. We also aimed to evaluate the association between the biomarker, and tumour immune phenotype and clinical outcomes of these patients. Methods In this retrospective multicohort study, we used four independent cohorts of patients with advanced solid tumours to develop and validate a radiomic signature predictive of immunotherapy response by combining contrast-enhanced CT images and RNA-seq genomic data from tumour biopsies to assess CD8 cell tumour infiltration. To develop the radiomic signature of CD8 cells, we used the CT images and RNA sequencing data of 135 patients with advanced solid malignant tumours who had been enrolled into the MOSCATO trial between May 1, 2012, and March 31, 2016, in France (training set). The genomic data, which are based on the CD8B gene, were used to estimate the abundance of CD8 cells in the samples and data were then aligned with the images to generate the radiomic signatures. The concordance of the radiomic signature (primary endpoint) was validated in a Cancer Genome Atlas [TGCA] database dataset including 119 patients who had available baseline preoperative imaging data and corresponding transcriptomic data on June 30, 2017. From 84 input variables used for the machine-learning method (78 radiomic features, five location variables, and one technical variable), a radiomics-based predictor of the CD8 cell expression signature was built by use of machine learning (elastic-net regularised regression method). Two other independent cohorts of patients with advanced solid tumours were used to evaluate this predictor. The immune phenotype internal cohort (n=100), were randomly selected from the Gustave Roussy Cancer Campus database of patient medical records based on previously described, extreme tumour-immune phenotypes: immune-inflamed (with dense CD8 cell infiltration) or immune-desert (with low CD8 cell infiltration), irrespective of treatment delivered; these data were used to analyse the correlation of the immune phenotype with this biomarker. Finally, the immunotherapy-treated dataset (n=137) of patients recruited from Dec 1, 2011, to Jan 31, 2014, at the Gustave Roussy Cancer Campus, who had been treated with anti-PD-1 and anti-PD-L1 monotherapy in phase 1 trials, was used to assess the predictive value of this biomarker in terms of clinical outcome. Findings We developed a radiomic signature for CD8 cells that included eight variables, which was validated with the gene expression signature of CD8 cells in the TCGA dataset (area under the curve [AUC]=0·67; 95% CI 0·57–0·77; p=0·0019). In the cohort with assumed immune phenotypes, the signature was also able to discriminate inflamed tumours from immune-desert tumours (0·76; 0·66–0·86; p Interpretation The radiomic signature of CD8 cells was validated in three independent cohorts. This imaging predictor provided a promising way to predict the immune phenotype of tumours and to infer clinical outcomes for patients with cancer who had been treated with anti-PD-1 and PD-L1. Our imaging biomarker could be useful in estimating CD8 cell count and predicting clinical outcomes of patients treated with immunotherapy, when validated by further prospective randomised trials. Funding Fondation pour la Recherche Medicale, and SIRIC-SOCRATE 2.0, French Society of Radiation Oncology.read more
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The Image Biomarker Standardization Initiative: Standardized Quantitative Radiomics for High-Throughput Image-based Phenotyping
Alex Zwanenburg,Alex Zwanenburg,Martin Vallières,Mahmoud A. Abdalah,Hugo J.W.L. Aerts,Hugo J.W.L. Aerts,Vincent Andrearczyk,Aditya Apte,Saeed Ashrafinia,Spyridon Bakas,Roelof J. Beukinga,Ronald Boellaard,Marta Bogowicz,Luca Boldrini,Irène Buvat,Gary Cook,Christos Davatzikos,Adrien Depeursinge,Marie-Charlotte Desseroit,Nicola Dinapoli,Cuong V. Dinh,Sebastian Echegaray,Issam El Naqa,Issam El Naqa,Andriy Fedorov,Roberto Gatta,Robert J. Gillies,Vicky Goh,Michael Götz,Matthias Guckenberger,Sung Min Ha,Mathieu Hatt,Fabian Isensee,Philippe Lambin,Stefan Leger,Stefan Leger,Ralph T.H. Leijenaar,Jacopo Lenkowicz,Fiona Lippert,Are Losnegård,Klaus H. Maier-Hein,Olivier Morin,Henning Müller,Sandy Napel,Christophe Nioche,Fanny Orlhac,Sarthak Pati,Elisabeth Pfaehler,Arman Rahmim,Arman Rahmim,Arvind Rao,Jonas Scherer,Muhammad Siddique,Nanna M. Sijtsema,Jairo Socarras Fernandez,Emiliano Spezi,Roel J H M Steenbakkers,Stephanie Tanadini-Lang,Daniela Thorwarth,Esther G.C. Troost,Esther G.C. Troost,Taman Upadhaya,Vincenzo Valentini,Lisanne V. van Dijk,Joost J. M. van Griethuysen,Floris H. P. van Velden,Philip Whybra,Christian Richter,Christian Richter,Steffen Löck,Steffen Löck +70 more
TL;DR: A set of 169 radiomics features was standardized, which enabled verification and calibration of different radiomics software and could be excellently reproduced.
Journal ArticleDOI
Artificial intelligence in cancer imaging: Clinical challenges and applications.
Wenya Linda Bi,Ahmed Hosny,Matthew B. Schabath,Maryellen L. Giger,Nicolai Juul Birkbak,Nicolai Juul Birkbak,Alireza Mehrtash,Alireza Mehrtash,Tavis Allison,Tavis Allison,Omar Arnaout,Christopher Abbosh,Christopher Abbosh,Ian F. Dunn,Raymond H. Mak,Rulla M. Tamimi,Clare M. Tempany,Charles Swanton,Charles Swanton,Udo Hoffmann,Lawrence H. Schwartz,Lawrence H. Schwartz,Robert J. Gillies,Raymond Y. Huang,Hugo J.W.L. Aerts,Hugo J.W.L. Aerts +25 more
TL;DR: The authors review the current state of AI as applied to medical imaging of cancer and describe advances in 4 tumor types to illustrate how common clinical problems are being addressed.
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Neoadjuvant checkpoint blockade for cancer immunotherapy
TL;DR: The development of neoadjuvant immunotherapies in the era of PD-1 pathway blockade is focused on, highlighting particular considerations for immunological mechanisms, clinical development, and pathologic response assessments.
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The Applications of Radiomics in Precision Diagnosis and Treatment of Oncology: Opportunities and Challenges.
Zhenyu Liu,Shuo Wang,Di Dong,Jingwei Wei,Cheng Fang,Xuezhi Zhou,Kai Sun,Longfei Li,Bo Li,Meiyun Wang,Jie Tian,Jie Tian +11 more
TL;DR: The recent methodological developments in radiomics are reviewed, including data acquisition, tumor segmentation, feature extraction, and modelling, as well as the rapidly developing deep learning technology.
Journal ArticleDOI
Radiomics of Multiparametric MRI for Pretreatment Prediction of Pathologic Complete Response to Neoadjuvant Chemotherapy in Breast Cancer: A Multicenter Study.
Zhenyu Liu,Zhuolin Li,Jinrong Qu,Renzhi Zhang,Xuezhi Zhou,Longfei Li,Kai Sun,Zhenchao Tang,Hui Jiang,Hailiang Li,Qianqian Xiong,Yingying Ding,Xinming Zhao,Kun Wang,Zaiyi Liu,Jie Tian +15 more
TL;DR: There is a possibility that RMM provided a potential tool to develop a model for predicting pCR to NAC in breast cancer, and was significantly higher than that of clinical model in two of the three external validation cohorts.
References
More filters
Journal ArticleDOI
Regularization and variable selection via the elastic net
Hui Zou,Trevor Hastie +1 more
TL;DR: It is shown that the elastic net often outperforms the lasso, while enjoying a similar sparsity of representation, and an algorithm called LARS‐EN is proposed for computing elastic net regularization paths efficiently, much like algorithm LARS does for the lamba.
Journal ArticleDOI
Pembrolizumab versus Chemotherapy for PD-L1–Positive Non–Small-Cell Lung Cancer
Martin Reck,Delvys Rodriguez-Abreu,Andrew G. Robinson,Rina Hui,Tibor Csőszi,Andrea Fülöp,Maya Gottfried,Nir Peled,Ali Tafreshi,Sinead Cuffe,Mary O'Brien,Suman Rao,Katsuyuki Hotta,Melanie A. Leiby,Gregory M. Lubiniecki,Yue Shentu,Reshma A. Rangwala,Julie R. Brahmer +17 more
TL;DR: Pembrolizumab is a humanized monoclonal antibody against programmed death 1 (PD-1) that has antitumor activity in advanced non-small-cell lung cancer (NSCLC), with increased activity in tumors that express PD-L1 as mentioned in this paper.
Journal ArticleDOI
Salmon provides fast and bias-aware quantification of transcript expression
TL;DR: Salmon is the first transcriptome-wide quantifier to correct for fragment GC-content bias, which substantially improves the accuracy of abundance estimates and the sensitivity of subsequent differential expression analysis.
Journal ArticleDOI
The cancer genome atlas pan-cancer analysis project
John N. Weinstein,John N. Weinstein,Eric A. Collisson,Gordon B. Mills,Kenna R. Mills Shaw,Kenna R. Mills Shaw,Brad Ozenberger,Kyle Ellrott,Kyle Ellrott,Chris Sander,Joshua M. Stuart,Joshua M. Stuart,Kyle Chang,Chad J. Creighton,Caleb F. Davis,Lawrence A. Donehower,Jennifer Drummond,David A. Wheeler,Adrian Ally,Miruna Balasundaram,Inanc Birol,Inanc Birol,Inanc Birol,Yaron S.N. Butterfield,Andy Chu,Eric Chuah,Hye Jung E. Chun,Noreen Dhalla,Ranabir Guin,Martin Hirst,Carrie Hirst,Robert A. Holt,Steven J.M. Jones,Darlene Lee,Haiyan I. Li,Marco A. Marra,Michael Mayo,Richard A. Moore,Andrew J. Mungall,A. Gordon Robertson,Jacqueline E. Schein,Payal Sipahimalani,Angela Tam,Nina Thiessen,Richard Varhol,Rameen Beroukhim,Ami S. Bhatt,Angela N. Brooks,Andrew D. Cherniack,Samuel S. Freeman,Stacey Gabriel,Elena Helman,Joonil Jung,Matthew Meyerson,Akinyemi I. Ojesina,Chandra Sekhar Pedamallu,Gordon Saksena,Steven E. Schumacher,Barbara Tabak,Travis I. Zack,Travis I. Zack,Eric S. Lander,Christopher A. Bristow,Angela Hadjipanayis,Psalm Haseley,Raju Kucherlapati,Semin Lee,Eunjung Lee,Lovelace J. Luquette,Harshad S. Mahadeshwar,Angeliki Pantazi,Michael Parfenov,Michael Parfenov,Peter J. Park,Alexei Protopopov,Xiaojia Ren,Netty Santoso,Jonathan G. Seidman,Sahil Seth,Xingzhi Song,Jiabin Tang,Ruibin Xi,Ruibin Xi,Ruibin Xi,Andrew Wei Xu,Lixing Yang,Dong Zeng,J. Todd Auman,Saianand Balu,Elizabeth Buda,Cheng Fan,Katherine A. Hoadley,Corbin D. Jones,Shaowu Meng,Piotr A. Mieczkowski,Joel S. Parker,Charles M. Perou,Jeffrey Roach,Yan Shi,Grace O. Silva,Donghui Tan,Umadevi Veluvolu,Scot Waring,Matthew D. Wilkerson,Junyuan Wu,Wei Zhao,Tom Bodenheimer,D. Neil Hayes,D. Neil Hayes,Alan P. Hoyle,Stuart R. Jeffreys,Lisle E. Mose,Janae V. Simons,Mathew G. Soloway,Stephen B. Baylin,Benjamin P. Berman,Moiz S. Bootwalla,Ludmila Danilova,James G. Herman,Toshinori Hinoue,Peter W. Laird,Suhn K. Rhie,Hui Shen,Timothy J. Triche,Daniel J. Weisenberger,Scott L. Carter,Kristian Cibulskis,Lynda Chin,Jianhua Zhang,Carrie Sougnez,Min Wang,Gad Getz,Gad Getz,Huyen Dinh,Harshavardhan Doddapaneni,Richard A. Gibbs,Preethi Gunaratne,Preethi Gunaratne,Yi Han,Divya Kalra,Christie Kovar,Lora Lewis,Margaret B. Morgan,Donna Morton,Donna Muzny,Jeffrey G. Reid,Liu Xi,Juok Cho,Daniel DiCara,Scott Frazer,Nils Gehlenborg,David I. Heiman,Jaegil Kim,Michael S. Lawrence,Pei Lin,Yingchun Liu,Michael S. Noble,Petar Stojanov,Doug Voet,Hailei Zhang,Lihua Zou,Chip Stewart,Brady Bernard,Ryan Bressler,Andrea Eakin,Lisa Iype,Theo A. Knijnenburg,Roger Kramer,Richard Kreisberg,Kalle Leinonen,Jake Lin,Yuexin Liu,Michael Miller,Sheila M. Reynolds,Hector Rovira,Ilya Shmulevich,Vesteinn Thorsson,Da Yang,Wei Zhang,Samirkumar B. Amin,Chang-Jiun Wu,Chia Chin Wu,Rehan Akbani,Kenneth Aldape,Keith A. Baggerly,Bradley McIntosh Broom,Tod D. Casasent,James Cleland,Deepti Dodda,Mary Elizabeth Edgerton,Leng Han,Shelley M. Herbrich,Zhenlin Ju,Hoon Kim,Hoon Kim,Seth Lerner,Jun Li,Han Liang,Wenbin Liu,Philip L. Lorenzi,Yiling Lu,James M. Melott,Lam Nguyen,Lam Nguyen,Xiaoping Su,Roeland Verhaak,Wenyi Wang,Andrew J. Wong,Andrew J. Wong,Yang Yang,Jun Yao,Rong Yao,Kosuke Yoshihara,Yuan Yuan,Yuan Yuan,W. K. Alfred Yung,Nianxiang Zhang,Siyuan Zheng,Michael B. Ryan,Michael B. Ryan,David W. Kane,David W. Kane,B. Arman Aksoy,Giovanni Ciriello,Gideon Dresdner,Jianjiong Gao,Benjamin Gross,Anders Jacobsen,André Kahles,Marc Ladanyi,William Lee,Kjong-Van Lehmann,Martin L. Miller,Ricardo Ramirez,Gunnar Rätsch,Boris Reva,Nikolaus Schultz,Yasin Senbabaoglu,Ronglai Shen,Rileen Sinha,S. Onur Sumer,Yichao Sun,Barry S. Taylor,Barry S. Taylor,Barry S. Taylor,Nils Weinhold,Suzanne S. Fei,Paul T. Spellman,Christopher C. Benz,Christopher C. Benz,Daniel E. Carlin,Daniel E. Carlin,Melisssa Cline,Melisssa Cline,Brian Craft,Brian Craft,Mary Goldman,David Haussler,David Haussler,David Haussler,Singer Ma,Singer Ma,Sam Ng,Sam Ng,Evan O. Paull,Evan O. Paull,Amie Radenbaugh,Amie Radenbaugh,Sofie R. Salama,Sofie R. Salama,Sofie R. Salama,Artem Sokolov,Artem Sokolov,Teresa Swatloski,Teresa Swatloski,Vladislav Uzunangelov,Vladislav Uzunangelov,Peter Waltman,Peter Waltman,Christina Yau,Jing Zhu,Jing Zhu,Stanley R. Hamilton,Scott Abbott,Rachel Abbott,Nathan D. Dees,Kim D. Delehaunty,Li Ding,David J. Dooling,James M. Eldred,Catrina Fronick,Robert S. Fulton,Lucinda Fulton,Joelle Kalicki-Veizer,Krishna L. Kanchi,Cyriac Kandoth,Daniel C. Koboldt,David E. Larson,Timothy J. Ley,Ling Lin,Charles Lu,Vincent Magrini,Elaine R. Mardis,Michael D. McLellan,Joshua F. McMichael,Christopher A. Miller,Michelle O'Laughlin,Craig Pohl,Heather Schmidt,Scott M. Smith,Jason Walker,John W. Wallis,Michael C. Wendl,Michael C. Wendl,Richard K. Wilson,Todd Wylie,Qunyuan Zhang,Robert A. Burton,Mark A. Jensen,Ari B. Kahn,Todd Pihl,David A. Pot,Yunhu Wan,Douglas A. Levine,Aaron D. Black,Jay Bowen,Jessica Frick,Julie M. Gastier-Foster,Julie M. Gastier-Foster,Hollie A. Harper,Carmen Helsel,Kristen M. Leraas,Tara M. Lichtenberg,Cynthia McAllister,Nilsa C. Ramirez,Nilsa C. Ramirez,Samantha Sharpe,Lisa Wise,Erik Zmuda,Stephen J. Chanock,Tanja Davidsen,John A. Demchok,Greg Eley,Ina Felau,Margi Sheth,Heidi J. Sofia,Louis M. Staudt,Roy Tarnuzzer,Zhining Wang,Liming Yang,Jiashan Zhang,Larsson Omberg,Adam Margolin,Benjamin J. Raphael,Fabio Vandin,Hsin-Ta Wu,Mark D.M. Leiserson,Stephen C. Benz,Charles J. Vaske,Houtan Noushmehr,Houtan Noushmehr,Denise M. Wolf,Laura van 't Veer,Dimitris Anastassiou,Tai Hsien Ou Yang,Nuria Lopez-Bigas,Abel Gonzalez-Perez,David Tamborero,Zheng Xia,Wei Li,Dong Yeon Cho,Teresa M. Przytycka,Mark P. Hamilton,Sean E. McGuire,Sven Nelander,Sven Nelander,Patrik Johansson,Rebecka Jörnsten,Rebecka Jörnsten,Teresia Kling +379 more
TL;DR: The Pan-Cancer initiative compares the first 12 tumor types profiled by TCGA with a major opportunity to develop an integrated picture of commonalities, differences and emergent themes across tumor lineages.
Journal ArticleDOI
PD-1 blockade induces responses by inhibiting adaptive immune resistance
Paul C. Tumeh,Christina L. Harview,Jennifer H. Yearley,I. Peter Shintaku,Emma Taylor,Lidia Robert,Bartosz Chmielowski,Marko Spasic,Gina Henry,Voicu Ciobanu,Alisha N. West,Manuel Carmona,Christine Kivork,Elizabeth Seja,Grace Cherry,Antonio Gutierrez,Tristan Grogan,Christine Mateus,Gorana Tomasic,John A. Glaspy,Ryan O. Emerson,Harlan Robins,Robert H. Pierce,David Elashoff,Caroline Robert,Antoni Ribas +25 more
TL;DR: It is shown that pre-existing CD8+ T cells distinctly located at the invasive tumour margin are associated with expression of the PD-1/PD-L1 immune inhibitory axis and may predict response to therapy.
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