Evidence map›Paper›PMID 41145733›Full record

ArticleScientific reports2025

Clinical utility of comprehensive genomic profiling versus Oncomine Dx target test in pathological stage II-III non-small cell lung cancer.

Kaito Yano, Kaoru Kaseda, Kohei Nakamura, Yu Okubo, Kyohei Masai, Tomoyuki Hishida, Shigenari Nukaga, Keiko Ohgino, Hideki Terai, Hiroyuki Yasuda and 4 more

Abstract read
In one paragraph

Article in Scientific reports, 2025. 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

14 authors.

Kaito YanoDivision of Thoracic Surgery, Department of Surgery, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo, 160-8582, Japan.ORCID http://orcid.org/0000-0002-8013-6981
Kaoru KasedaDivision of Thoracic Surgery, Department of Surgery, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo, 160-8582, Japan. kaorukaseda@keio.jp.ORCID http://orcid.org/0000-0003-3022-9060
Kohei NakamuraCenter for Cancer Genomics, Keio University School of Medicine, Tokyo, Japan.ORCID http://orcid.org/0000-0002-5162-7132
Yu OkuboDivision of Thoracic Surgery, Department of Surgery, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo, 160-8582, Japan.
Kyohei MasaiDivision of Thoracic Surgery, Department of Surgery, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo, 160-8582, Japan.
Tomoyuki HishidaDivision of Thoracic Surgery, Department of Surgery, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo, 160-8582, Japan.
Shigenari NukagaDivision of Pulmonary Medicine, Department of Internal Medicine, Keio University School of Medicine, Tokyo, Japan.
Keiko OhginoDivision of Pulmonary Medicine, Department of Internal Medicine, Keio University School of Medicine, Tokyo, Japan.ORCID http://orcid.org/0000-0002-1118-1930
Hideki TeraiDivision of Pulmonary Medicine, Department of Internal Medicine, Keio University School of Medicine, Tokyo, Japan.
Hiroyuki YasudaDivision of Pulmonary Medicine, Department of Internal Medicine, Keio University School of Medicine, Tokyo, Japan.
Yutaka KurebayashiDepartment of Pathology, Keio University School of Medicine, Tokyo, Japan.
Koichi FukunagaDivision of Pulmonary Medicine, Department of Internal Medicine, Keio University School of Medicine, Tokyo, Japan.
Hiroshi NishiharaCenter for Cancer Genomics, Keio University School of Medicine, Tokyo, Japan.ORCID http://orcid.org/0000-0002-5460-8703
Keisuke AsakuraDivision of Thoracic Surgery, Department of Surgery, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo, 160-8582, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The next-generation sequencing (NGS)-based Oncomine Dx Target Test (ODxTT) is the standard tool for guiding postoperative adjuvant therapy in patients with non-small cell lung cancer (NSCLC) in Japan. To advance precision oncology, we evaluated the clinical utility of an in-house comprehensive genomic profiling (CGP) assay, Rapid-Neo, as a complementary approach to ODxTT in surgically resected NSCLC. Patients with pathological stage II-III NSCLC who underwent anatomical surgical resection between December 2019 and May 2024 were included. Resected specimens underwent genomic analysis using both ODxTT and Rapid-Neo CGP. We evaluated the mutational concordance and the frequency of additional actionable alterations identified by CGP. Among 68 eligible patients, driver mutation results were concordant in 64 (94.1%) cases. Crucially, CGP rescued one patient for targeted therapy by detecting an EGFR mutation where ODxTT failed due to insufficient DNA. CGP also identified rare EGFR variants not covered by ODxTT in two cases, although it failed to detect a RET fusion in one patient. Furthermore, CGP revealed additional actionable alterations, such as tumor suppressor gene mutations, in 57 patients (83.8%). Our in-house CGP shows high concordance with ODxTT and serves as a powerful complementary tool. These findings support a strategic testing algorithm where CGP is incorporated for patients with negative or inconclusive ODxTT results, or at the time of recurrence, to maximize opportunities for individualized therapy in resected NSCLC.

Indexed as

Carcinoma, Non-Small-Cell LungLung NeoplasmsAdultAgedAged, 80 and overBiomarkers, TumorErbB ReceptorsFemaleGenomicsHigh-Throughput Nucleotide SequencingHumansMaleMiddle AgedMutationNeoplasm StagingBiomarkers, TumorErbB ReceptorsAdjuvant therapyComprehensive genomic profilingDriver gene mutationsNon-small cell lung cancerPathological stage

Identifiers

PMID41145733
PMCPMC12559205

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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.