Trial reportScientific reports2019
A combined gene expression tool for parallel histological prediction and gene fusion detection in non-small cell lung cancer.
Trial report in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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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.
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Who cites it
12 citing papers in PubMed, 22 citations in OpenAlex.
- Integrated prediction of lung cancer histology and molecular profiles from small bronchoscopic tumor specimens.NPJ precision oncology · 2026Article
- Single-cell transcriptomic landscape of keratinocyte transformation from actinic keratosis to skin carcinoma.iScience · 2025Article
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- Identification and validation of a five apoptosis-related genes signature for prediction of disease-free survival for testicular germ cell tumors.Translational andrology and urology · 2021Article
- Simultaneous analysis ofTranslational lung cancer research · 2021Article
- The Regulators Associated With N6-Methyladenosine in Lung Adenocarcinoma and Lung Squamous Cell Carcinoma Reveal New Clinical and Prognostic Markers.Frontiers in cell and developmental biology · 2021Article
- RNA-Based Multiplexing Assay for Routine Testing of Fusion and Splicing Variants in Cytological Samples of NSCLC Patients.Diagnostics (Basel, Switzerland) · 2020Article
- Prediction of Non-small Cell Lung Cancer Histology by a Deep Ensemble of Convolutional and Bidirectional Recurrent Neural Network.Journal of digital imaging · 2020Article
- Article
- Molecular identification of bronchopulmonary neuroendocrine tumours and neuroendocrine genotype in lung neoplasia using the NETest liquid biopsy.European journal of cardio-thoracic surgery : official journal of the European Association for Cardio-thoracic Surgery · 2020Article
- Practical Considerations Relating to Routine Clinical Biomarker Testing for Non-small Cell Lung Cancer: Focus on Testing forFrontiers in medicine · 2020Review
- KRT6A Promotes EMT and Cancer Stem Cell Transformation in Lung Adenocarcinoma.Technology in cancer research & treatmentArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
20 authors at 7 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Accurate histological classification and identification of fusion genes represent two cornerstones of clinical diagnostics in non-small cell lung cancer (NSCLC). Here, we present a NanoString gene expression platform and a novel platform-independent, single sample predictor (SSP) of NSCLC histology for combined, simultaneous, histological classification and fusion gene detection in minimal formalin fixed paraffin embedded (FFPE) tissue. The SSP was developed in 68 NSCLC tumors of adenocarcinoma (AC), squamous cell carcinoma (SqCC) and large-cell neuroendocrine carcinoma (LCNEC) histology, based on NanoString expression of 11 (CHGA, SYP, CD56, SFTPG, NAPSA, TTF-1, TP73L, KRT6A, KRT5, KRT40, KRT16) relevant genes for IHC-based NSCLC histology classification. The SSP was combined with a gene fusion detection module (analyzing ALK, RET, ROS1, MET, NRG1, and NTRK1) into a multicomponent NanoString assay. The histological SSP was validated in six cohorts varying in size (n = 11-199), tissue origin (early or advanced disease), histological composition (including undifferentiated cancer), and gene expression platform. Fusion gene detection revealed five EML4-ALK fusions, four KIF5B-RET fusions, two CD74-NRG1 fusion and three MET exon 14 skipping events among 131 tested cases. The histological SSP was successfully trained and tested in the development cohort (mean AUC = 0.96 in iterated test sets). The SSP proved successful in predicting histology of NSCLC tumors of well-defined subgroups and difficult undifferentiated morphology irrespective of gene expression data platform. Discrepancies between gene expression prediction and histologic diagnosis included cases with mixed histologies, true large cell carcinomas, or poorly differentiated adenocarcinomas with mucin expression. In summary, we present a proof-of-concept multicomponent assay for parallel histological classification and multiplexed fusion gene detection in archival tissue, including a novel platform-independent histological SSP classifier. The assay and SSP could serve as a promising complement in the routine evaluation of diagnostic lung cancer biopsies.
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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.