IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v14y2023i1d10.1038_s41467-023-39570-7.html
   My bibliography  Save this article

Proteogenomic analysis reveals RNA as a source for tumor-agnostic neoantigen identification

Author

Listed:
  • Celina Tretter

    (German Cancer Consortium (DKTK), partner site Munich and German Cancer Research Center (DKFZ)
    Technical University of Munich, TUM School of Medicine, Klinikum rechts der Isar, IIIrd Medical Department)

  • Niklas Andrade Krätzig

    (Technical University of Munich, TUM School of Medicine, Klinikum rechts der Isar, IInd Medical Department
    Technical University of Munich, TUM School of Medicine, Center for Translational Cancer Research (TranslaTUM)
    Technical University of Munich, TUM School of Medicine, Institute of Molecular Oncology and Functional Genomics)

  • Matteo Pecoraro

    (Max Plank Institute of Biochemistry
    Università della Svizzera italiana)

  • Sebastian Lange

    (Technical University of Munich, TUM School of Medicine, Klinikum rechts der Isar, IInd Medical Department
    Technical University of Munich, TUM School of Medicine, Center for Translational Cancer Research (TranslaTUM)
    Technical University of Munich, TUM School of Medicine, Institute of Molecular Oncology and Functional Genomics)

  • Philipp Seifert

    (Technical University of Munich, TUM School of Medicine, Klinikum rechts der Isar, IIIrd Medical Department)

  • Clara Frankenberg

    (Technical University of Munich, TUM School of Medicine, Klinikum rechts der Isar, IIIrd Medical Department)

  • Johannes Untch

    (Technical University of Munich, TUM School of Medicine, Klinikum rechts der Isar, IIIrd Medical Department)

  • Gabriela Zuleger

    (Technical University of Munich, TUM School of Medicine, Klinikum rechts der Isar, IIIrd Medical Department)

  • Mathias Wilhelm

    (Technical University of Munich, TUM School of Life Sciences, Chair of Proteomics and Bioanalytics
    Technical University of Munich, TUM School of Life Sciences, Computational Mass Spectrometry)

  • Daniel P. Zolg

    (Technical University of Munich, TUM School of Life Sciences, Chair of Proteomics and Bioanalytics)

  • Florian S. Dreyer

    (Technical University of Munich, TUM School of Medicine, Klinikum rechts der Isar, IIIrd Medical Department)

  • Eva Bräunlein

    (Technical University of Munich, TUM School of Medicine, Klinikum rechts der Isar, IIIrd Medical Department)

  • Thomas Engleitner

    (Technical University of Munich, TUM School of Medicine, Center for Translational Cancer Research (TranslaTUM)
    Technical University of Munich, TUM School of Medicine, Institute of Molecular Oncology and Functional Genomics)

  • Sebastian Uhrig

    (German Cancer Consortium (DKTK), partner site Heidelberg and German Cancer Research Center (DKFZ)
    Molecular Precision Oncology Program, NCT Heidelberg)

  • Melanie Boxberg

    (German Cancer Consortium (DKTK), partner site Munich and German Cancer Research Center (DKFZ)
    Technical University of Munich, TUM School of Medicine, Klinikum rechts der Isar, Institute of Pathology)

  • Katja Steiger

    (German Cancer Consortium (DKTK), partner site Munich and German Cancer Research Center (DKFZ)
    Technical University of Munich, TUM School of Medicine, Klinikum rechts der Isar, Institute of Pathology)

  • Julia Slotta-Huspenina

    (Technical University of Munich, TUM School of Medicine, Klinikum rechts der Isar, Institute of Pathology)

  • Sebastian Ochsenreither

    (German Cancer Consortium (DKTK), partner site Berlin and German Cancer Research Center (DKFZ)
    Charité – Universitätsmedizin Berlin
    Charité – Universitätsmedizin Berlin)

  • Nikolas Bubnoff

    (German Cancer Consortium (DKTK), partner site Freiburg and German Cancer Research Center (DKFZ)
    University of Freiburg
    University of Schleswig Holstein, Campus Lübeck)

  • Sebastian Bauer

    (German Cancer Consortium (DKTK), partner site Essen and German Cancer Research Center (DKFZ)
    University Hospital Essen)

  • Melanie Boerries

    (German Cancer Consortium (DKTK), partner site Freiburg and German Cancer Research Center (DKFZ)
    University of Freiburg)

  • Philipp J. Jost

    (German Cancer Consortium (DKTK), partner site Munich and German Cancer Research Center (DKFZ)
    Technical University of Munich, TUM School of Medicine, Klinikum rechts der Isar, IIIrd Medical Department
    Medical University of Graz
    University Comprehensive Cancer Center Graz, Medical University of Graz)

  • Kristina Schenck

    (German Cancer Consortium (DKTK), partner site Munich and German Cancer Research Center (DKFZ)
    Technical University of Munich, TUM School of Medicine, Klinikum rechts der Isar, IIIrd Medical Department)

  • Iska Dresing

    (German Cancer Consortium (DKTK), partner site Munich and German Cancer Research Center (DKFZ)
    Technical University of Munich, TUM School of Medicine, Klinikum rechts der Isar, IIIrd Medical Department)

  • Florian Bassermann

    (German Cancer Consortium (DKTK), partner site Munich and German Cancer Research Center (DKFZ)
    Technical University of Munich, TUM School of Medicine, Klinikum rechts der Isar, IIIrd Medical Department
    Technical University of Munich, TUM School of Medicine, Center for Translational Cancer Research (TranslaTUM))

  • Helmut Friess

    (Technical University of Munich, TUM School of Medicine, Klinikum rechts der Isar, Department of Surgery)

  • Daniel Reim

    (Technical University of Munich, TUM School of Medicine, Klinikum rechts der Isar, Department of Surgery)

  • Konrad Grützmann

    (German Cancer Consortium (DKTK), partner site Dresden and German Cancer Research Center (DKFZ)
    Core Unit Molecular Tumor Diagnostics (CMTD), NCT Dresden
    Faculty of Medicine, TU Dresden)

  • Katrin Pfütze

    (German Cancer Consortium (DKTK), partner site Heidelberg and German Cancer Research Center (DKFZ))

  • Barbara Klink

    (German Cancer Consortium (DKTK), partner site Dresden and German Cancer Research Center (DKFZ)
    Institute for Clinical Genetics, University Hospital Carl Gustav Carus at the Technische Universität Dresden)

  • Evelin Schröck

    (German Cancer Consortium (DKTK), partner site Dresden and German Cancer Research Center (DKFZ)
    Institute for Clinical Genetics, University Hospital Carl Gustav Carus at the Technische Universität Dresden
    ERN GENTURIS, Hereditary Cancer Syndrome Center Dresden
    National Center for Tumor Diseases Dresden (NCT/UCC))

  • Bernhard Haller

    (Technical University of Munich, TUM School of Medicine, Klinikum rechts der Isar, Institute of AI and Informatics in Medicine)

  • Bernhard Kuster

    (German Cancer Consortium (DKTK), partner site Munich and German Cancer Research Center (DKFZ)
    Technical University of Munich, TUM School of Life Sciences, Chair of Proteomics and Bioanalytics
    Technical University of Munich, TUM School of Life Sciences, Bavarian Biomolecular Mass Spectrometry Center (BayBioMS))

  • Matthias Mann

    (Max Plank Institute of Biochemistry)

  • Wilko Weichert

    (German Cancer Consortium (DKTK), partner site Munich and German Cancer Research Center (DKFZ)
    Technical University of Munich, TUM School of Medicine, Klinikum rechts der Isar, Institute of Pathology)

  • Stefan Fröhling

    (German Cancer Consortium (DKTK), partner site Heidelberg and German Cancer Research Center (DKFZ)
    German Cancer Research Center (DKFZ))

  • Roland Rad

    (German Cancer Consortium (DKTK), partner site Munich and German Cancer Research Center (DKFZ)
    Technical University of Munich, TUM School of Medicine, Klinikum rechts der Isar, IInd Medical Department
    Technical University of Munich, TUM School of Medicine, Center for Translational Cancer Research (TranslaTUM)
    Technical University of Munich, TUM School of Medicine, Institute of Molecular Oncology and Functional Genomics)

  • Michael Hiltensperger

    (German Cancer Consortium (DKTK), partner site Munich and German Cancer Research Center (DKFZ)
    Technical University of Munich, TUM School of Medicine, Klinikum rechts der Isar, IIIrd Medical Department)

  • Angela M. Krackhardt

    (German Cancer Consortium (DKTK), partner site Munich and German Cancer Research Center (DKFZ)
    Technical University of Munich, TUM School of Medicine, Klinikum rechts der Isar, IIIrd Medical Department
    Technical University of Munich, TUM School of Medicine, Center for Translational Cancer Research (TranslaTUM)
    Malteser Krankenhaus St. Franziskus-Hospital)

Abstract

Systemic pan-tumor analyses may reveal the significance of common features implicated in cancer immunogenicity and patient survival. Here, we provide a comprehensive multi-omics data set for 32 patients across 25 tumor types for proteogenomic-based discovery of neoantigens. By using an optimized computational approach, we discover a large number of tumor-specific and tumor-associated antigens. To create a pipeline for the identification of neoantigens in our cohort, we combine DNA and RNA sequencing with MS-based immunopeptidomics of tumor specimens, followed by the assessment of their immunogenicity and an in-depth validation process. We detect a broad variety of non-canonical HLA-binding peptides in the majority of patients demonstrating partially immunogenicity. Our validation process allows for the selection of 32 potential neoantigen candidates. The majority of neoantigen candidates originates from variants identified in the RNA data set, illustrating the relevance of RNA as a still understudied source of cancer antigens. This study underlines the importance of RNA-centered variant detection for the identification of shared biomarkers and potentially relevant neoantigen candidates.

Suggested Citation

  • Celina Tretter & Niklas Andrade Krätzig & Matteo Pecoraro & Sebastian Lange & Philipp Seifert & Clara Frankenberg & Johannes Untch & Gabriela Zuleger & Mathias Wilhelm & Daniel P. Zolg & Florian S. Dr, 2023. "Proteogenomic analysis reveals RNA as a source for tumor-agnostic neoantigen identification," Nature Communications, Nature, vol. 14(1), pages 1-22, December.
  • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-39570-7
    DOI: 10.1038/s41467-023-39570-7
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-023-39570-7
    File Function: Abstract
    Download Restriction: no

    File URL: https://libkey.io/10.1038/s41467-023-39570-7?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Minying Zhang & Jens Fritsche & Jason Roszik & Leila J. Williams & Xinxin Peng & Yulun Chiu & Chih-Chiang Tsou & Franziska Hoffgaard & Valentina Goldfinger & Oliver Schoor & Amjad Talukder & Marie A. , 2018. "RNA editing derived epitopes function as cancer antigens to elicit immune responses," Nature Communications, Nature, vol. 9(1), pages 1-10, December.
    2. Samuel Rivero-Hinojosa & Melanie Grant & Aswini Panigrahi & Huizhen Zhang & Veronika Caisova & Catherine M. Bollard & Brian R. Rood, 2021. "Proteogenomic discovery of neoantigens facilitates personalized multi-antigen targeted T cell immunotherapy for brain tumors," Nature Communications, Nature, vol. 12(1), pages 1-15, December.
    3. Konrad J. Karczewski & Laurent C. Francioli & Grace Tiao & Beryl B. Cummings & Jessica Alföldi & Qingbo Wang & Ryan L. Collins & Kristen M. Laricchia & Andrea Ganna & Daniel P. Birnbaum & Laura D. Gau, 2020. "The mutational constraint spectrum quantified from variation in 141,456 humans," Nature, Nature, vol. 581(7809), pages 434-443, May.
    4. Justina X. Caushi & Jiajia Zhang & Zhicheng Ji & Ajay Vaghasia & Boyang Zhang & Emily Han-Chung Hsiue & Brian J. Mog & Wenpin Hou & Sune Justesen & Richard Blosser & Ada Tam & Valsamo Anagnostou & Tri, 2021. "Transcriptional programs of neoantigen-specific TIL in anti-PD-1-treated lung cancers," Nature, Nature, vol. 596(7870), pages 126-132, August.
    5. Ugur Sahin & Evelyna Derhovanessian & Matthias Miller & Björn-Philipp Kloke & Petra Simon & Martin Löwer & Valesca Bukur & Arbel D. Tadmor & Ulrich Luxemburger & Barbara Schrörs & Tana Omokoko & Mathi, 2017. "Personalized RNA mutanome vaccines mobilize poly-specific therapeutic immunity against cancer," Nature, Nature, vol. 547(7662), pages 222-226, July.
    6. Michal Bassani-Sternberg & Eva Bräunlein & Richard Klar & Thomas Engleitner & Pavel Sinitcyn & Stefan Audehm & Melanie Straub & Julia Weber & Julia Slotta-Huspenina & Katja Specht & Marc E. Martignoni, 2016. "Direct identification of clinically relevant neoepitopes presented on native human melanoma tissue by mass spectrometry," Nature Communications, Nature, vol. 7(1), pages 1-16, December.
    7. Ludmil B. Alexandrov & Serena Nik-Zainal & David C. Wedge & Samuel A. J. R. Aparicio & Sam Behjati & Andrew V. Biankin & Graham R. Bignell & Niccolò Bolli & Ake Borg & Anne-Lise Børresen-Dale & Sandri, 2013. "Correction: Corrigendum: Signatures of mutational processes in human cancer," Nature, Nature, vol. 502(7470), pages 258-258, October.
    8. Chloe Chong & Markus Müller & HuiSong Pak & Dermot Harnett & Florian Huber & Delphine Grun & Marion Leleu & Aymeric Auger & Marion Arnaud & Brian J. Stevenson & Justine Michaux & Ilija Bilic & Antje H, 2020. "Integrated proteogenomic deep sequencing and analytics accurately identify non-canonical peptides in tumor immunopeptidomes," Nature Communications, Nature, vol. 11(1), pages 1-21, December.
    9. Ludmil B. Alexandrov & Serena Nik-Zainal & David C. Wedge & Samuel A. J. R. Aparicio & Sam Behjati & Andrew V. Biankin & Graham R. Bignell & Niccolò Bolli & Ake Borg & Anne-Lise Børresen-Dale & Sandri, 2013. "Signatures of mutational processes in human cancer," Nature, Nature, vol. 500(7463), pages 415-421, August.
    10. Mathias Wilhelm & Daniel P. Zolg & Michael Graber & Siegfried Gessulat & Tobias Schmidt & Karsten Schnatbaum & Celina Schwencke-Westphal & Philipp Seifert & Niklas Andrade Krätzig & Johannes Zerweck &, 2021. "Deep learning boosts sensitivity of mass spectrometry-based immunopeptidomics," Nature Communications, Nature, vol. 12(1), pages 1-12, December.
    11. Justina X. Caushi & Jiajia Zhang & Zhicheng Ji & Ajay Vaghasia & Boyang Zhang & Emily Han-Chung Hsiue & Brian J. Mog & Wenpin Hou & Sune Justesen & Richard Blosser & Ada Tam & Valsamo Anagnostou & Tri, 2021. "Author Correction: Transcriptional programs of neoantigen-specific TIL in anti-PD-1-treated lung cancers," Nature, Nature, vol. 598(7881), pages 1-1, October.
    12. Meng How Tan & Qin Li & Raghuvaran Shanmugam & Robert Piskol & Jennefer Kohler & Amy N. Young & Kaiwen Ivy Liu & Rui Zhang & Gokul Ramaswami & Kentaro Ariyoshi & Ankita Gupte & Liam P. Keegan & Cyril , 2017. "Dynamic landscape and regulation of RNA editing in mammals," Nature, Nature, vol. 550(7675), pages 249-254, October.
    13. Mathias Wilhelm & Daniel P. Zolg & Michael Graber & Siegfried Gessulat & Tobias Schmidt & Karsten Schnatbaum & Celina Schwencke-Westphal & Philipp Seifert & Niklas Andrade Krätzig & Johannes Zerweck &, 2021. "Author Correction: Deep learning boosts sensitivity of mass spectrometry-based immunopeptidomics," Nature Communications, Nature, vol. 12(1), pages 1-1, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hanqing Liao & Carolina Barra & Zhicheng Zhou & Xu Peng & Isaac Woodhouse & Arun Tailor & Robert Parker & Alexia Carré & Persephone Borrow & Michael J. Hogan & Wayne Paes & Laurence C. Eisenlohr & Rob, 2024. "MARS an improved de novo peptide candidate selection method for non-canonical antigen target discovery in cancer," Nature Communications, Nature, vol. 15(1), pages 1-16, December.
    2. Lei Xin & Rui Qiao & Xin Chen & Hieu Tran & Shengying Pan & Sahar Rabinoviz & Haibo Bian & Xianliang He & Brenton Morse & Baozhen Shan & Ming Li, 2022. "A streamlined platform for analyzing tera-scale DDA and DIA mass spectrometry data enables highly sensitive immunopeptidomics," Nature Communications, Nature, vol. 13(1), pages 1-9, December.
    3. Charlotte Adams & Wassim Gabriel & Kris Laukens & Mario Picciani & Mathias Wilhelm & Wout Bittremieux & Kurt Boonen, 2024. "Fragment ion intensity prediction improves the identification rate of non-tryptic peptides in timsTOF," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
    4. Daniela Klaproth-Andrade & Johannes Hingerl & Yanik Bruns & Nicholas H. Smith & Jakob Träuble & Mathias Wilhelm & Julien Gagneur, 2024. "Deep learning-driven fragment ion series classification enables highly precise and sensitive de novo peptide sequencing," Nature Communications, Nature, vol. 15(1), pages 1-14, December.
    5. Jurica Levatić & Marina Salvadores & Francisco Fuster-Tormo & Fran Supek, 2022. "Mutational signatures are markers of drug sensitivity of cancer cells," Nature Communications, Nature, vol. 13(1), pages 1-19, December.
    6. Wen-Feng Zeng & Xie-Xuan Zhou & Sander Willems & Constantin Ammar & Maria Wahle & Isabell Bludau & Eugenia Voytik & Maximillian T. Strauss & Matthias Mann, 2022. "AlphaPeptDeep: a modular deep learning framework to predict peptide properties for proteomics," Nature Communications, Nature, vol. 13(1), pages 1-14, December.
    7. Kevin L. Yang & Fengchao Yu & Guo Ci Teo & Kai Li & Vadim Demichev & Markus Ralser & Alexey I. Nesvizhskii, 2023. "MSBooster: improving peptide identification rates using deep learning-based features," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
    8. Mischan Vali-Pour & Solip Park & Jose Espinosa-Carrasco & Daniel Ortiz-Martínez & Ben Lehner & Fran Supek, 2022. "The impact of rare germline variants on human somatic mutation processes," Nature Communications, Nature, vol. 13(1), pages 1-21, December.
    9. Xing Cheng & Jing An & Jitong Lou & Qisheng Gu & Weimin Ding & Gaith Nabil Droby & Yilin Wang & Chenghao Wang & Yanzhe Gao & Jay Ramanlal Anand & Abigail Shelton & Andrew Benson Satterlee & Breanna Ma, 2024. "Trans-lesion synthesis and mismatch repair pathway crosstalk defines chemoresistance and hypermutation mechanisms in glioblastoma," Nature Communications, Nature, vol. 15(1), pages 1-20, December.
    10. Michelle Dietzen & Haoran Zhai & Olivia Lucas & Oriol Pich & Christopher Barrington & Wei-Ting Lu & Sophia Ward & Yanping Guo & Robert E. Hynds & Simone Zaccaria & Charles Swanton & Nicholas McGranaha, 2024. "Replication timing alterations are associated with mutation acquisition during breast and lung cancer evolution," Nature Communications, Nature, vol. 15(1), pages 1-23, December.
    11. Marjan M. Naeini & Felicity Newell & Lauren G. Aoude & Vanessa F. Bonazzi & Kalpana Patel & Guy Lampe & Lambros T. Koufariotis & Vanessa Lakis & Venkateswar Addala & Olga Kondrashova & Rebecca L. John, 2023. "Multi-omic features of oesophageal adenocarcinoma in patients treated with preoperative neoadjuvant therapy," Nature Communications, Nature, vol. 14(1), pages 1-17, December.
    12. David Gomez-Zepeda & Danielle Arnold-Schild & Julian Beyrle & Arthur Declercq & Ralf Gabriels & Elena Kumm & Annica Preikschat & Mateusz Krzysztof Łącki & Aurélie Hirschler & Jeewan Babu Rijal & Chris, 2024. "Thunder-DDA-PASEF enables high-coverage immunopeptidomics and is boosted by MS2Rescore with MS2PIP timsTOF fragmentation prediction model," Nature Communications, Nature, vol. 15(1), pages 1-18, December.
    13. Ambrocio Sanchez & Pedro Ortega & Ramin Sakhtemani & Lavanya Manjunath & Sunwoo Oh & Elodie Bournique & Alexandrea Becker & Kyumin Kim & Cameron Durfee & Nuri Alpay Temiz & Xiaojiang S. Chen & Reuben , 2024. "Mesoscale DNA features impact APOBEC3A and APOBEC3B deaminase activity and shape tumor mutational landscapes," Nature Communications, Nature, vol. 15(1), pages 1-16, December.
    14. Henry Webel & Lili Niu & Annelaura Bach Nielsen & Marie Locard-Paulet & Matthias Mann & Lars Juhl Jensen & Simon Rasmussen, 2024. "Imputation of label-free quantitative mass spectrometry-based proteomics data using self-supervised deep learning," Nature Communications, Nature, vol. 15(1), pages 1-15, December.
    15. Brittany N. Vandenberg & Marian F. Laughery & Cameron Cordero & Dalton Plummer & Debra Mitchell & Jordan Kreyenhagen & Fatimah Albaqshi & Alexander J. Brown & Piotr A. Mieczkowski & John J. Wyrick & S, 2023. "Contributions of replicative and translesion DNA polymerases to mutagenic bypass of canonical and atypical UV photoproducts," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    16. Wojciech Barczak & Simon M. Carr & Geng Liu & Shonagh Munro & Annalisa Nicastri & Lian Ni Lee & Claire Hutchings & Nicola Ternette & Paul Klenerman & Alexander Kanapin & Anastasia Samsonova & Nicholas, 2023. "Long non-coding RNA-derived peptides are immunogenic and drive a potent anti-tumour response," Nature Communications, Nature, vol. 14(1), pages 1-17, December.
    17. Anna Luiza Silva Almeida Vicente & Alexei Novoloaca & Vincent Cahais & Zainab Awada & Cyrille Cuenin & Natália Spitz & André Lopes Carvalho & Adriane Feijó Evangelista & Camila Souza Crovador & Rui Ma, 2022. "Cutaneous and acral melanoma cross-OMICs reveals prognostic cancer drivers associated with pathobiology and ultraviolet exposure," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
    18. Teresa Maria Rosaria Noviello & Anna Maria Giacomo & Francesca Pia Caruso & Alessia Covre & Roberta Mortarini & Giovanni Scala & Maria Claudia Costa & Sandra Coral & Wolf H. Fridman & Catherine Sautès, 2023. "Guadecitabine plus ipilimumab in unresectable melanoma: five-year follow-up and integrated multi-omic analysis in the phase 1b NIBIT-M4 trial," Nature Communications, Nature, vol. 14(1), pages 1-18, December.
    19. Qi Zhao & Feng Wang & Yan-Xing Chen & Shifu Chen & Yi-Chen Yao & Zhao-Lei Zeng & Teng-Jia Jiang & Ying-Nan Wang & Chen-Yi Wu & Ying Jing & You-Sheng Huang & Jing Zhang & Zi-Xian Wang & Ming-Ming He & , 2022. "Comprehensive profiling of 1015 patients’ exomes reveals genomic-clinical associations in colorectal cancer," Nature Communications, Nature, vol. 13(1), pages 1-17, December.
    20. Ankur Chakravarthy & Ian Reddin & Stephen Henderson & Cindy Dong & Nerissa Kirkwood & Maxmilan Jeyakumar & Daniela Rothschild Rodriguez & Natalia Gonzalez Martinez & Jacqueline McDermott & Xiaoping Su, 2022. "Integrated analysis of cervical squamous cell carcinoma cohorts from three continents reveals conserved subtypes of prognostic significance," Nature Communications, Nature, vol. 13(1), pages 1-17, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-39570-7. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.