Evidence map›Paper›PMID 42120924›Full record

ArticleNPJ precision oncology2026

Dissecting non-small cell lung cancer (NSCLC) with blood proteomics-from surgical to immunotherapeutic responses.

Vahid Yaghoubi Naei, Aaron Kilgallon, Gwendoline Mendes, Akila Wijerathna-Yapa, Sanjay Dutta, Clara Lawler, Connor O'Leary, William Mullally, James Monkman, James Mansfield and 5 more

Abstract read
In one paragraph

Article in NPJ precision oncology, 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

15 authors.

Vahid Yaghoubi Naei *School of Biomedical Engineering, University of Technology Sydney, Sydney, NSW, Australia.
Aaron Kilgallon *Frazer Institute, Faculty of Health, Medicine and Behavioural Sciences, The University of Queensland, Brisbane, QLD, Australia.
Gwendoline MendesSurgeCare SAS, Illkirch-Graffenstaden, France.
Akila Wijerathna-YapaFrazer Institute, Faculty of Health, Medicine and Behavioural Sciences, The University of Queensland, Brisbane, QLD, Australia.
Sanjay DuttaThe Princess Alexandra Hospital, Brisbane, QLD, Australia.
Clara LawlerFrazer Institute, Faculty of Health, Medicine and Behavioural Sciences, The University of Queensland, Brisbane, QLD, Australia.
Connor O'LearyThe Princess Alexandra Hospital, Brisbane, QLD, Australia.
William MullallyThe Princess Alexandra Hospital, Brisbane, QLD, Australia.
James MonkmanFrazer Institute, Faculty of Health, Medicine and Behavioural Sciences, The University of Queensland, Brisbane, QLD, Australia.
James MansfieldStandard BioTools Canada Inc, Markham, ON, Canada.
Julien HedouSurgeCare SAS, Illkirch-Graffenstaden, France.
Mark N AdamsQueensland University of Technology, Brisbane, QLD, Australia.
Ken O'ByrneThe Princess Alexandra Hospital, Brisbane, QLD, Australia.
Majid E WarkianiDepartment of Mechanical Engineering, College of Engineering, American University of Sharjah, Sharjah, United Arab Emirates.
Arutha KulasingheFrazer Institute, Faculty of Health, Medicine and Behavioural Sciences, The University of Queensland, Brisbane, QLD, Australia. arutha.kulasinghe@uq.edu.au.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

NSCLC remains a leading cause of cancer-related mortality, with limited biomarkers to guide surgical and immunotherapeutic intervention. This study leveraged two complementary plasma proteomics platforms, SomaScan (7596 proteins) and NULISA (250 inflammation-related proteins) to profile 87 timepoints from 56 NSCLC patients, collected pre- and post-surgery and pre- and post-ICI therapy. Robust biomarker selection used adaptive Lasso regression and the Stabl algorithm, with inter- and intra-cohort validation via orthogonal nELISA proteomics. Twenty-one differentially detectable plasma proteins were identified across treatment contexts. Surgical resection induced measurable proteomic changes: non-recurrent patients had higher circulating MUC16 and lower IL36G post-surgery, while recurrent patients showed elevated COX7A2L, FGF19, and SPOCK2, alongside lower FCER2, FCRLA, and SLITRK2. Among ICI-treated patients, responders had lower baseline levels of IL-6, CCL19, IL-2RA, CD200R1, CRP, LIF, PDCD1, CCL7, and SPP1, implicating systemic inflammation and immune regulation in treatment sensitivity. CEACAM5, PTX3, FGF23, and AREG were elevated in patients with worse clinical outcomes and poorer overall survival. MUC16, IL36G, CCL19, and IL-6 were independently validated by nELISA. Cross-platform comparison highlighted the complementary strengths of SomaScan's broad proteomic coverage and NULISA's sensitivity for low-abundance proteins. This integrated approach reveals distinct plasma signatures associated with surgical recurrence, ICI response, and prognosis in NSCLC.

Identifiers

PMID42120924
PMCPMC13269880

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LicenceCC BY-NC-ND
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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.