IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v14y2023i1d10.1038_s41467-023-42327-x.html
   My bibliography  Save this article

Inflammation in the tumor-adjacent lung as a predictor of clinical outcome in lung adenocarcinoma

Author

Listed:
  • Igor Dolgalev

    (NYU Grossman School of Medicine
    NYU Grossman School of Medicine
    NYU Grossman School of Medicine)

  • Hua Zhou

    (NYU Grossman School of Medicine
    NYU Grossman School of Medicine)

  • Nina Murrell

    (NYU Grossman School of Medicine
    NYU Grossman School of Medicine
    NYU Grossman School of Medicine)

  • Hortense Le

    (NYU Grossman School of Medicine
    NYU Grossman School of Medicine)

  • Theodore Sakellaropoulos

    (NYU Grossman School of Medicine)

  • Nicolas Coudray

    (NYU Grossman School of Medicine
    NYU Grossman School of Medicine
    NYU Grossman School of Medicine)

  • Kelsey Zhu

    (NYU Grossman School of Medicine)

  • Varshini Vasudevaraja

    (NYU Grossman School of Medicine)

  • Anna Yeaton

    (The Optical Profiling Platform at The Broad Institute of MIT And Harvard)

  • Chandra Goparaju

    (NYU Grossman School of Medicine)

  • Yonghua Li

    (NYU Grossman School of Medicine)

  • Imran Sulaiman

    (NYU Grossman School of Medicine)

  • Jun-Chieh J. Tsay

    (NYU Grossman School of Medicine)

  • Peter Meyn

    (NYU Grossman School of Medicine)

  • Hussein Mohamed

    (NYU Grossman School of Medicine)

  • Iris Sydney

    (NYU Grossman School of Medicine)

  • Tomoe Shiomi

    (NYU Grossman School of Medicine)

  • Sitharam Ramaswami

    (NYU Grossman School of Medicine
    NYU Grossman School of Medicine)

  • Navneet Narula

    (NYU Grossman School of Medicine)

  • Ruth Kulicke

    (Celsius Therapeutics, Cambridge)

  • Fred P. Davis

    (Celsius Therapeutics, Cambridge)

  • Nicolas Stransky

    (Celsius Therapeutics, Cambridge)

  • Gromoslaw A. Smolen

    (Celsius Therapeutics, Cambridge)

  • Wei-Yi Cheng

    (Roche Innovation Center New York)

  • James Cai

    (Roche Innovation Center New York)

  • Salman Punekar

    (New York University Langone Health)

  • Vamsidhar Velcheti

    (New York University Langone Health)

  • Daniel H. Sterman

    (NYU Grossman School of Medicine
    New York University Langone Health)

  • J. T. Poirier

    (New York University Langone Health)

  • Ben Neel

    (New York University Langone Health)

  • Kwok-Kin Wong

    (New York University Langone Health)

  • Luis Chiriboga

    (NYU Grossman School of Medicine)

  • Adriana Heguy

    (NYU Grossman School of Medicine
    NYU Grossman School of Medicine
    New York University Langone Health)

  • Thales Papagiannakopoulos

    (NYU Grossman School of Medicine
    New York University Langone Health)

  • Bettina Nadorp

    (NYU Grossman School of Medicine
    NYU Grossman School of Medicine
    NYU Grossman School of Medicine)

  • Matija Snuderl

    (NYU Grossman School of Medicine
    New York University Langone Health)

  • Leopoldo N. Segal

    (NYU Grossman School of Medicine
    New York University Langone Health)

  • Andre L. Moreira

    (NYU Grossman School of Medicine
    New York University Langone Health)

  • Harvey I. Pass

    (NYU Grossman School of Medicine
    New York University Langone Health)

  • Aristotelis Tsirigos

    (NYU Grossman School of Medicine
    NYU Grossman School of Medicine
    NYU Grossman School of Medicine
    New York University Langone Health)

Abstract

Approximately 30% of early-stage lung adenocarcinoma patients present with disease progression after successful surgical resection. Despite efforts of mapping the genetic landscape, there has been limited success in discovering predictive biomarkers of disease outcomes. Here we performed a systematic multi-omic assessment of 143 tumors and matched tumor-adjacent, histologically-normal lung tissue with long-term patient follow-up. Through histologic, mutational, and transcriptomic profiling of tumor and adjacent-normal tissue, we identified an inflammatory gene signature in tumor-adjacent tissue as the strongest clinical predictor of disease progression. Single-cell transcriptomic analysis demonstrated the progression-associated inflammatory signature was expressed in both immune and non-immune cells, and cell type-specific profiling in monocytes further improved outcome predictions. Additional analyses of tumor-adjacent transcriptomic data from The Cancer Genome Atlas validated the association of the inflammatory signature with worse outcomes across cancers. Collectively, our study suggests that molecular profiling of tumor-adjacent tissue can identify patients at high risk for disease progression.

Suggested Citation

  • Igor Dolgalev & Hua Zhou & Nina Murrell & Hortense Le & Theodore Sakellaropoulos & Nicolas Coudray & Kelsey Zhu & Varshini Vasudevaraja & Anna Yeaton & Chandra Goparaju & Yonghua Li & Imran Sulaiman &, 2023. "Inflammation in the tumor-adjacent lung as a predictor of clinical outcome in lung adenocarcinoma," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
  • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-42327-x
    DOI: 10.1038/s41467-023-42327-x
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-023-42327-x
    File Function: Abstract
    Download Restriction: no

    File URL: https://libkey.io/10.1038/s41467-023-42327-x?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. Kun-Hsing Yu & Ce Zhang & Gerald J. Berry & Russ B. Altman & Christopher Ré & Daniel L. Rubin & Michael Snyder, 2016. "Predicting non-small cell lung cancer prognosis by fully automated microscopic pathology image features," Nature Communications, Nature, vol. 7(1), pages 1-10, November.
    2. Ludo Waltman & Nees Eck, 2013. "A smart local moving algorithm for large-scale modularity-based community detection," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 86(11), pages 1-14, November.
    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. Nayoung Kim & Hong Kwan Kim & Kyungjong Lee & Yourae Hong & Jong Ho Cho & Jung Won Choi & Jung-Il Lee & Yeon-Lim Suh & Bo Mi Ku & Hye Hyeon Eum & Soyean Choi & Yoon-La Choi & Je-Gun Joung & Woong-Yang, 2020. "Single-cell RNA sequencing demonstrates the molecular and cellular reprogramming of metastatic lung adenocarcinoma," Nature Communications, Nature, vol. 11(1), pages 1-15, December.
    5. Dvir Aran & Roman Camarda & Justin Odegaard & Hyojung Paik & Boris Oskotsky & Gregor Krings & Andrei Goga & Marina Sirota & Atul J. Butte, 2017. "Comprehensive analysis of normal adjacent to tumor transcriptomes," Nature Communications, Nature, vol. 8(1), pages 1-14, 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. Gregor Werba & Daniel Weissinger & Emily A. Kawaler & Ende Zhao & Despoina Kalfakakou & Surajit Dhara & Lidong Wang & Heather B. Lim & Grace Oh & Xiaohong Jing & Nina Beri & Lauren Khanna & Tamas Gond, 2023. "Single-cell RNA sequencing reveals the effects of chemotherapy on human pancreatic adenocarcinoma and its tumor microenvironment," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    2. Lutz Bornmann & Robin Haunschild & Sven E. Hug, 2018. "Visualizing the context of citations referencing papers published by Eugene Garfield: a new type of keyword co-occurrence analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 114(2), pages 427-437, February.
    3. Vincent Michaud & Eulalie Lasseaux & David J. Green & Dave T. Gerrard & Claudio Plaisant & Tomas Fitzgerald & Ewan Birney & Benoît Arveiler & Graeme C. Black & Panagiotis I. Sergouniotis, 2022. "The contribution of common regulatory and protein-coding TYR variants to the genetic architecture of albinism," Nature Communications, Nature, vol. 13(1), pages 1-8, December.
    4. Nina Sakinah Ahmad Rofaie & Seuk Wai Phoong & Muzalwana Abdul Talib & Ainin Sulaiman, 2023. "Light-emitting diode (LED) research: A bibliometric analysis during 2003–2018," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(1), pages 173-191, February.
    5. Natalie DeForest & Yuqi Wang & Zhiyi Zhu & Jacqueline S. Dron & Ryan Koesterer & Pradeep Natarajan & Jason Flannick & Tiffany Amariuta & Gina M. Peloso & Amit R. Majithia, 2024. "Genome-wide discovery and integrative genomic characterization of insulin resistance loci using serum triglycerides to HDL-cholesterol ratio as a proxy," Nature Communications, Nature, vol. 15(1), pages 1-17, December.
    6. Giovanni Matteo & Pierfrancesco Nardi & Stefano Grego & Caterina Guidi, 2018. "Bibliometric analysis of Climate Change Vulnerability Assessment research," Environment Systems and Decisions, Springer, vol. 38(4), pages 508-516, December.
    7. Loredana Canfora & Corrado Costa & Federico Pallottino & Stefano Mocali, 2021. "Trends in Soil Microbial Inoculants Research: A Science Mapping Approach to Unravel Strengths and Weaknesses of Their Application," Agriculture, MDPI, vol. 11(2), pages 1-21, February.
    8. Evi Sachini & Nikolaos Karampekios & Pierpaolo Brutti & Konstantinos Sioumalas-Christodoulou, 2020. "Should I stay or should I go? Using bibliometrics to identify the international mobility of highly educated Greek manpower," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(1), pages 641-663, October.
    9. Alexendar R. Perez & Laura Sala & Richard K. Perez & Joana A. Vidigal, 2021. "CSC software corrects off-target mediated gRNA depletion in CRISPR-Cas9 essentiality screens," Nature Communications, Nature, vol. 12(1), pages 1-11, December.
    10. Magnus Zethoven & Luciano Martelotto & Andrew Pattison & Blake Bowen & Shiva Balachander & Aidan Flynn & Fernando J. Rossello & Annette Hogg & Julie A. Miller & Zdenek Frysak & Sean Grimmond & Lauren , 2022. "Single-nuclei and bulk-tissue gene-expression analysis of pheochromocytoma and paraganglioma links disease subtypes with tumor microenvironment," Nature Communications, Nature, vol. 13(1), pages 1-18, December.
    11. Michel S. Naslavsky & Marilia O. Scliar & Guilherme L. Yamamoto & Jaqueline Yu Ting Wang & Stepanka Zverinova & Tatiana Karp & Kelly Nunes & José Ricardo Magliocco Ceroni & Diego Lima Carvalho & Carlo, 2022. "Whole-genome sequencing of 1,171 elderly admixed individuals from Brazil," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
    12. Nicole Deflaux & Margaret Sunitha Selvaraj & Henry Robert Condon & Kelsey Mayo & Sara Haidermota & Melissa A. Basford & Chris Lunt & Anthony A. Philippakis & Dan M. Roden & Joshua C. Denny & Anjene Mu, 2023. "Demonstrating paths for unlocking the value of cloud genomics through cross cohort analysis," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
    13. Andrea Wilderman & Eva D’haene & Machteld Baetens & Tara N. Yankee & Emma Wentworth Winchester & Nicole Glidden & Ellen Roets & Jo Dorpe & Sandra Janssens & Danny E. Miller & Miranda Galey & Kari M. B, 2024. "A distant global control region is essential for normal expression of anterior HOXA genes during mouse and human craniofacial development," Nature Communications, Nature, vol. 15(1), pages 1-23, December.
    14. Ruoyu Tian & Tian Ge & Hyeokmoon Kweon & Daniel B. Rocha & Max Lam & Jimmy Z. Liu & Kritika Singh & Daniel F. Levey & Joel Gelernter & Murray B. Stein & Ellen A. Tsai & Hailiang Huang & Christopher F., 2024. "Whole-exome sequencing in UK Biobank reveals rare genetic architecture for depression," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
    15. Mary-Ellen Lynall & Blagoje Soskic & James Hayhurst & Jeremy Schwartzentruber & Daniel F. Levey & Gita A. Pathak & Renato Polimanti & Joel Gelernter & Murray B. Stein & Gosia Trynka & Menna R. Clatwor, 2022. "Genetic variants associated with psychiatric disorders are enriched at epigenetically active sites in lymphoid cells," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
    16. Adrienne Tin & Pascal Schlosser & Pamela R. Matias-Garcia & Chris H. L. Thio & Roby Joehanes & Hongbo Liu & Zhi Yu & Antoine Weihs & Anselm Hoppmann & Franziska Grundner-Culemann & Josine L. Min & Vic, 2021. "Epigenome-wide association study of serum urate reveals insights into urate co-regulation and the SLC2A9 locus," Nature Communications, Nature, vol. 12(1), pages 1-18, December.
    17. Tzuhua D. Lin & Nimrod D. Rubinstein & Nicole L. Fong & Megan Smith & Wendy Craft & Baby Martin-McNulty & Rebecca Perry & Martha A. Delaney & Margaret A. Roy & Rochelle Buffenstein, 2024. "Evolution of T cells in the cancer-resistant naked mole-rat," Nature Communications, Nature, vol. 15(1), pages 1-20, December.
    18. Oriol Pich & Iker Reyes-Salazar & Abel Gonzalez-Perez & Nuria Lopez-Bigas, 2022. "Discovering the drivers of clonal hematopoiesis," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    19. Han Luo & Xuyang Xia & Li-Bin Huang & Hyunsu An & Minyuan Cao & Gyeong Dae Kim & Hai-Ning Chen & Wei-Han Zhang & Yang Shu & Xiangyu Kong & Zhixiang Ren & Pei-Heng Li & Yang Liu & Huairong Tang & Rongh, 2022. "Pan-cancer single-cell analysis reveals the heterogeneity and plasticity of cancer-associated fibroblasts in the tumor microenvironment," Nature Communications, Nature, vol. 13(1), pages 1-17, December.
    20. Chuyou Fu & Jun Wang & Ziyi Qu & Martin Skitmore & Jiaxin Yi & Zhengjie Sun & Jianli Chen, 2024. "Structural Equation Modeling in Technology Adoption and Use in the Construction Industry: A Scientometric Analysis and Qualitative Review," Sustainability, MDPI, vol. 16(9), pages 1-23, May.

    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_s41467-023-42327-x. 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.