Evidence map›Paper›PMID 36647832›Full record

ArticleThe Journal of clinical investigation2023

Features of tumor-microenvironment images predict targeted therapy survival benefit in patients with EGFR-mutant lung cancer.

Shidan Wang, Ruichen Rong, Donghan M Yang, Junya Fujimoto, Justin A Bishop, Shirley Yan, Ling Cai, Carmen Behrens, Lynne D Berry, Clare Wilhelm and 10 more

Open access · goldAbstract read
In one paragraph

Article in The Journal of clinical investigation, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
5.2field-weighted citation impact, top 4% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

15 citing papers in PubMed, 20 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Article
  5. A CMTM6 Nanobody Overcomes EGFR-TKI Resistance in Non-Small Cell Lung Cancer.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    Article
  6. Article
  7. Article
  8. Review
  9. Review
  10. Fusion of shallow and deep features fromQuantitative imaging in medicine and surgery · 2024
    Article
  11. Review
  12. Article
  13. Article
  14. Article
  15. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

20 authors at 10 institutions in 1 country.

Shidan WangQuantitative Biomedical Research Center, The Peter O'Donnell Jr. School of Public Health, University of Texas Southwestern Medical Center, Dallas, Texas, USA.
Ruichen RongQuantitative Biomedical Research Center, The Peter O'Donnell Jr. School of Public Health, University of Texas Southwestern Medical Center, Dallas, Texas, USA.
Donghan M YangQuantitative Biomedical Research Center, The Peter O'Donnell Jr. School of Public Health, University of Texas Southwestern Medical Center, Dallas, Texas, USA.
Junya FujimotoDepartment of Translational Molecular Pathology, Division of Pathology/Lab Medicine, University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Justin A BishopDepartment of Pathology, University of Texas Southwestern Medical Center, Dallas, Texas, USA.
Shirley YanDepartment of Pathology, University of Texas Southwestern Medical Center, Dallas, Texas, USA.
Ling CaiQuantitative Biomedical Research Center, The Peter O'Donnell Jr. School of Public Health, University of Texas Southwestern Medical Center, Dallas, Texas, USA.
Carmen BehrensDepartment of Translational Molecular Pathology, Division of Pathology/Lab Medicine, University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Lynne D BerryDepartment of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
Clare WilhelmDepartment of Thoracic Oncology, Memorial Sloan Kettering Cancer Center, New York, New York, USA.
Dara AisnerDepartment of Pathology, University of Colorado, Denver, Colorado, USA.
Lynette ShollDepartment of Pathology, Brigham and Women's Hospital, Harvard University, Boston, Massachusetts, USA.
Bruce E JohnsonDepartment of Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA.
David J KwiatkowskiDepartment of Medical Oncology, Dana-Farber Cancer Institute, Harvard University, Boston, Massachusetts, USA.
Ignacio I WistubaDepartment of Translational Molecular Pathology, Division of Pathology/Lab Medicine, University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Paul A BunnDivision of Medical Oncology, School of Medicine, University of Colorado, Aurora, Colorado, USA.
John MinnaHamon Center for Therapeutic Oncology Research.
Guanghua XiaoQuantitative Biomedical Research Center, The Peter O'Donnell Jr. School of Public Health, University of Texas Southwestern Medical Center, Dallas, Texas, USA.
Mark G KrisDepartment of Thoracic Oncology, Memorial Sloan Kettering Cancer Center, New York, New York, USA.
Yang XieQuantitative Biomedical Research Center, The Peter O'Donnell Jr. School of Public Health, University of Texas Southwestern Medical Center, Dallas, Texas, USA.
The University of Texas Southwestern Medical Center · USThe University of Texas MD Anderson Cancer Center · USBrigham and Women's Hospital · USMemorial Sloan Kettering Cancer Center · USSouthwestern Medical Center · USDana-Farber Cancer Institute · USHarold C. Simmons Comprehensive Cancer CenterUniversity of Colorado Anschutz Medical Campus · USUniversity of Colorado Denver · USVanderbilt University Medical Center · US

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI Hongbiao Carl Lekaye · 1985 to 2026
$347.4M
UNIVERSITY OF TEXAS--SPORE IN LUNG CANCERP50CA070907 · NCI · UT SOUTHWESTERN MEDICAL CENTER · PI HEYMACH, JOHN V., MINNA, JOHN D. · 1996 to 2024
$57.4M
UT Southwestern Medical Center Simmons Comprehensive Cancer CenterP30CA142543 · NCI · UT SOUTHWESTERN MEDICAL CENTER · PI MELANIE H. COBB · 2010 to 2026
$53.7M
The Role of Focal Oncogene Amplifications in Lung CancerP01CA129243 · NCI · SLOAN-KETTERING INST CAN RESEARCH · PI Marc Ladanyi · 2007 to 2026
$31.2M
Deep Learning Image Analysis Algorithms to Improve Oral Cancer Risk Assessment for Oral Potentially Malignant DisordersR01DE030656 · NIDCR · YALE UNIVERSITY · PI PICKERING, CURTIS, XIAO, GUANGHUA · 2021 to 2025
$3.4M
Finding the optimal balance of immunotherapy efficacy and toxicity.U01AI156189 · NIAID · UT SOUTHWESTERN MEDICAL CENTER · PI GERBER, DAVID ERIC, WAKELAND, EDWARD K. · 2020 to 2024
$3.1M
Novel computational approaches to predict drug response and combination effectsR35GM136375 · NIGMS · UT SOUTHWESTERN MEDICAL CENTER · PI XIE, YANG · 2020 to 2024
$2.0M
Developing computational algorithms for histopathological image analysisR01GM140012 · NIGMS · UT SOUTHWESTERN MEDICAL CENTER · PI XIAO, GUANGHUA · 2021 to 2024
$1.6M
Informatics Tools To Analyze And Model Whole Slide Image Data At The Single Cell LevelU01CA249245 · NCI · UT SOUTHWESTERN MEDICAL CENTER · PI XIAO, GUANGHUA · 2021 to 2023
$1.5M
Developing novel algorithms for spatial molecular profiling technologiesR01GM141519 · NIGMS · UT SOUTHWESTERN MEDICAL CENTER · PI XIAO, GUANGHUA · 2021 to 2024
$1.4M
NCI NIH HHS P01 CA129243NCI NIH HHS P30 CA008748NCI NIH HHS P30 CA142543NCI NIH HHS P50 CA070907NCI NIH HHS U01 CA249245NIAID NIH HHS U01 AI156189NIGMS NIH HHS R01 GM140012NIGMS NIH HHS R01 GM141519NIGMS NIH HHS R35 GM136375
6 · The paper itself

Abstract

Tyrosine kinase inhibitors (TKIs) targeting epidermal growth factor receptor (EGFR) are effective for many patients with lung cancer with EGFR mutations. However, not all patients are responsive to EGFR TKIs, including even those harboring EGFR-sensitizing mutations. In this study, we quantified the cells and cellular interaction features of the tumor microenvironment (TME) using routine H&E-stained biopsy sections. These TME features were used to develop a prediction model for survival benefit from EGFR TKI therapy in patients with lung adenocarcinoma and EGFR-sensitizing mutations in the Lung Cancer Mutation Consortium 1 (LCMC1) and validated in an independent LCMC2 cohort. In the validation data set, EGFR TKI treatment prolonged survival in the predicted-to-benefit group but not in the predicted-not-to-benefit group. Among patients treated with EGFR TKIs, the predicted-to-benefit group had prolonged survival outcomes compared with the predicted not-to-benefit group. The EGFR TKI survival benefit positively correlated with tumor-tumor interaction image features and negatively correlated with tumor-stroma interaction. Moreover, the tumor-stroma interaction was associated with higher activation of the hepatocyte growth factor/MET-mediated PI3K/AKT signaling pathway and epithelial-mesenchymal transition process, supporting the hypothesis of fibroblast-involved resistance to EGFR TKI treatment.

Indexed as

Lung NeoplasmsPhosphatidylinositol 3-KinasesDrug Resistance, NeoplasmErbB ReceptorsHumansMutationProtein Kinase InhibitorsTumor MicroenvironmentEGFR protein, humanErbB ReceptorsPhosphatidylinositol 3-KinasesProtein Kinase InhibitorsLung cancerOncology

Identifiers

PMID36647832
PMCPMC9843059
OpenAlexW4316661350

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.