Evidence map›Paper›PMID 42314966›Full record

ArticleCancer letters2026

Deep learning of CT imaging predicts PD-L1 expression and immunotherapy response in metastatic NSCLC: A multi-center study.

Amgad Muneer, Eman Showkatian, Maliazurina B Saad, Lingzhi Hong, Shenduo Li, Morteza Salehjahromi, Muhammad Aminu, Sheeba J Sujit, Hui Xu, Muhammad Waqas and 21 more

Abstract readMulticenter Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Cancer letters, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

31 authors.

Amgad MuneerDepartment of Imaging Physics, MD Anderson Cancer Center, Houston, TX, USA.
Eman ShowkatianDepartment of Imaging Physics, MD Anderson Cancer Center, Houston, TX, USA.
Maliazurina B SaadDepartment of Imaging Physics, MD Anderson Cancer Center, Houston, TX, USA.
Lingzhi HongDepartment of Imaging Physics, MD Anderson Cancer Center, Houston, TX, USA; Department of Thoracic/Head and Neck Medical Oncology, MD Anderson Cancer Center, Houston, TX, USA.
Shenduo LiDivision of Hematology and Oncology, Mayo Clinic, Jacksonville, FL, USA.
Morteza SalehjahromiDepartment of Imaging Physics, MD Anderson Cancer Center, Houston, TX, USA.
Muhammad AminuDepartment of Imaging Physics, MD Anderson Cancer Center, Houston, TX, USA.
Sheeba J SujitDepartment of Imaging Physics, MD Anderson Cancer Center, Houston, TX, USA.
Hui XuDepartment of Imaging Physics, MD Anderson Cancer Center, Houston, TX, USA.
Muhammad WaqasDepartment of Imaging Physics, MD Anderson Cancer Center, Houston, TX, USA.
Anas ZafarDepartment of Imaging Physics, MD Anderson Cancer Center, Houston, TX, USA.
Girish S ShroffDepartment of Thoracic Imaging, MD Anderson Cancer Center, Houston, TX, USA.
Carol C WuDepartment of Thoracic Imaging, MD Anderson Cancer Center, Houston, TX, USA.
Brett W CarterDepartment of Thoracic Imaging, MD Anderson Cancer Center, Houston, TX, USA.
Joe Y ChangDepartment of Radiation Oncology, MD Anderson Cancer Center, Houston, TX, USA.
Zhongxing LiaoDepartment of Radiation Oncology, MD Anderson Cancer Center, Houston, TX, USA.
Mehmet AltanDepartment of Thoracic/Head and Neck Medical Oncology, MD Anderson Cancer Center, Houston, TX, USA.
Natalie I VokesDepartment of Thoracic/Head and Neck Medical Oncology, MD Anderson Cancer Center, Houston, TX, USA.
Tina CasconeDepartment of Thoracic/Head and Neck Medical Oncology, MD Anderson Cancer Center, Houston, TX, USA.
Xiuning LeDepartment of Thoracic/Head and Neck Medical Oncology, MD Anderson Cancer Center, Houston, TX, USA.
Cara L HaymakerDepartment of Translational Molecular Pathology, MD Anderson Cancer Center, Houston, TX, USA.
Ignacio I WistubaDepartment of Translational Molecular Pathology, MD Anderson Cancer Center, Houston, TX, USA.
Caroline ChungDepartment of Radiation Oncology, MD Anderson Cancer Center, Houston, TX, USA; Institute for Data Science in Oncology, MD Anderson Cancer Center, Houston, TX, USA.
David JaffrayDepartment of Imaging Physics, MD Anderson Cancer Center, Houston, TX, USA; Institute for Data Science in Oncology, MD Anderson Cancer Center, Houston, TX, USA.
Don L GibbonsDepartment of Thoracic/Head and Neck Medical Oncology, MD Anderson Cancer Center, Houston, TX, USA.
Ara VaporciyanDepartment of Thoracic and Cardiovascular Surgery, MD Anderson Cancer Center, Houston, TX, USA.
J Jack LeeDepartment of Biostatistics, MD Anderson Cancer Center, Houston, TX, USA.
Yanyan LouDivision of Hematology and Oncology, Mayo Clinic, Jacksonville, FL, USA.
John V HeymachDepartment of Thoracic/Head and Neck Medical Oncology, MD Anderson Cancer Center, Houston, TX, USA.
Jianjun ZhangDepartment of Thoracic/Head and Neck Medical Oncology, MD Anderson Cancer Center, Houston, TX, USA; Department of Genomic Medicine, MD Anderson Cancer Center, Houston, TX, USA.
Jia WuDepartment of Imaging Physics, MD Anderson Cancer Center, Houston, TX, USA; Department of Thoracic/Head and Neck Medical Oncology, MD Anderson Cancer Center, Houston, TX, USA; Institute for Data Science in Oncology, MD Anderson Cancer Center, Houston, TX, USA. Electronic address: jwu11@mdanderson.org.

Funding

Tumor Evolution and Metastasis ProgramP30CA016672 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI DIANE BODURKA · 1985 to 2026
$290.8M
Radioimmunogenomic Habitat Phenotypes to Predict Efficacy of Neoadjuvant Immunotherapies in Non-Small Cell Lung CancerR01CA262425 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI CASCONE, TINA, WU, JIA · 2021 to 2025
$3.2M
Integrated blood and radiomic subtyping to guide immunotherapy treatment selection and early response assessment in metastatic non-small cell lung cancerR01CA276178 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Natalie Vokes, Jia Wu · 2023 to 2026
$2.6M
NCI NIH HHS P30 CA016672NCI NIH HHS R01 CA262425NCI NIH HHS R01 CA276178
6 · The paper itself

Abstract

Immune checkpoint inhibitors (ICIs) benefit only a subset of patients with metastatic non-small cell lung cancer (NSCLC), but current selection relies on tissue PD-L1 immunohistochemistry (IHC), which is invasive and prone to sampling bias. We developed and validated SCENT (Scalable Ensemble Transformer), a CT-based deep learning model for noninvasive prediction of PD-L1 status and immunotherapy outcomes. In this retrospective study, 972 stage IV NSCLC patients treated with ICIs at MD Anderson were analyzed; SCENT was developed and validated in 640 patients with paired CT and PD-L1 IHC, and clinical applicability was assessed in an additional 332 CT-only patients. Generalizability was evaluated in independent cohorts from Mayo Clinic (n = 72) and the phase III LONESTAR trial (n = 116), where paired baseline and 3-month CT enabled longitudinal assessment. SCENT classified PD-L1 status (50% or higher vs lower) in the MD Anderson cohort with AUC 0.84 (95% CI 0.785 to 0.887), specificity 83.9%, and sensitivity 85.3%, outperforming clinical and radiomics models; external validation achieved AUC 0.80 (Mayo) and 0.78 (LONESTAR). SCENT-derived PD-L1 stratified progression-free survival (HR 1.49, p < 0.001) and overall survival (HR 1.40, p = 0.009), comparable to IHC, and provided complementary prognostic value when combined with IHC, with concordant low-low patients showing the poorest survival (OS HR 1.45, p = 0.008). In LONESTAR, serial SCENT-inferred PD-L1 status showed a borderline association with 3-month progression without paired post-treatment tissue confirmation. SCENT is a generalizable CT-based virtual biopsy for baseline PD-L1 prediction and complementary tissue IHC stratification, with longitudinal use requiring prospective validation.

Indexed as

B7-H1 AntigenCarcinoma, Non-Small-Cell LungDeep LearningImmune Checkpoint InhibitorsLung NeoplasmsTomography, X-Ray ComputedAgedFemaleHumansImmunotherapyMaleMiddle AgedPrognosisRetrospective StudiesB7-H1 AntigenCD274 protein, humanImmune Checkpoint InhibitorsBiomarkersCT imagingDeep learningImmunotherapyNSCLCPD-L1

Identifiers

PMID42314966
PMCPMC13525624

What OpenQuestion holds

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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.