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. 2023 Sep 7;115(9):1060-1070.
doi: 10.1093/jnci/djad122.

Circulating proteome for pulmonary nodule malignancy

Elham Khodayari Moez  1 , Matthew T Warkentin  1   2 , Yonathan Brhane  1 , Stephen Lam  3 , John K Field  4 , Geoffrey Liu  5 , Javier J Zulueta  6 , Karmele Valencia  7   8   9 , Miguel Mesa-Guzman  10 , Andrea Pasquier Nialet  7   8   9 , Sukhinder Atkar-Khattra  3 , Michael P A Davies  4 , Benjamin Grant  5 , Kiera Murison  1 , Luis M Montuenga  7   8   9 , Christopher I Amos  11 , Hilary A Robbins  12 , Mattias Johansson  12 , Rayjean J Hung  1   2
Affiliations

Circulating proteome for pulmonary nodule malignancy

Elham Khodayari Moez et al. J Natl Cancer Inst. .

Abstract

Background: Although lung cancer screening with low-dose computed tomography is rolling out in many areas of the world, differentiating indeterminate pulmonary nodules remains a major challenge. We conducted one of the first systematic investigations of circulating protein markers to differentiate malignant from benign screen-detected pulmonary nodules.

Methods: Based on 4 international low-dose computed tomography screening studies, we assayed 1078 protein markers using prediagnostic blood samples from 1253 participants based on a nested case-control design. Protein markers were measured using proximity extension assays, and data were analyzed using multivariable logistic regression, random forest, and penalized regressions. Protein burden scores (PBSs) for overall nodule malignancy and imminent tumors were estimated.

Results: We identified 36 potentially informative circulating protein markers differentiating malignant from benign nodules, representing a tightly connected biological network. Ten markers were found to be particularly relevant for imminent lung cancer diagnoses within 1 year. Increases in PBSs for overall nodule malignancy and imminent tumors by 1 standard deviation were associated with odds ratios of 2.29 (95% confidence interval: 1.95 to 2.72) and 2.81 (95% confidence interval: 2.27 to 3.54) for nodule malignancy overall and within 1 year of diagnosis, respectively. Both PBSs for overall nodule malignancy and for imminent tumors were substantially higher for those with malignant nodules than for those with benign nodules, even when limited to Lung Computed Tomography Screening Reporting and Data System (LungRADS) category 4 (P < .001).

Conclusions: Circulating protein markers can help differentiate malignant from benign pulmonary nodules. Validation with an independent computed tomographic screening study will be required before clinical implementation.

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Conflict of interest statement

Authors declared no conflict of interest.

Figures

Figure 1.
Figure 1.
The overall analytical pipeline, by number of markers. GO-BP = Gene Ontology–Biological Process; LASSO = least absolute shrinkage and selection operator.
Figure 2.
Figure 2.
Volcano plot for single-marker analyses of nodule malignancy. The results of individual markers based on multivariable logistic regression adjusted for Brock/PanCan score. OR = odds ratio.
Figure 3.
Figure 3.
The results of Gene Ontology–Biological Process pathway enrichment analysis and network analysis based on the 36 informative markers. (A) The bar plot of the enriched pathway with statistical significance (FDR < 0.01) ordered by FDR levels, with fold enrichment value and pathway size (ie, number of genes) annotated. (B) The network of the significantly enriched pathways (FDR < 0.01), depicting the pathway size (circle), the significance level (gradient), and the connections between pathways (line types). FDR = false discovery rate.
Figure 4.
Figure 4.
Forest plots of protein burden scores illustrating the association with nodule malignancy, stratified by time to diagnosis; LungRADS, version 1.1, categories; nodule sizes; and smoking status. The odds ratios and 95% confidence intervals per 1 SD increase are presented. (A) PBS-overall: PBSs are calculated based on the top 36 markers associated with nodule malignancy. (B) PBS-imminent: PBSs are calculated based on the top 10 markers associated with lung cancer diagnosis within 1 year after blood sample collection. CI = confidence interval; LungRADS = Lung Computed Tomography Reporting & Data System; OR = odds ratio; PBS-imminent = protein burden scores for imminent tumors; PBS-overall = protein burden scores for overall nodule malignancy.
Figure 5.
Figure 5.
The differential expression of the top protein markers quantified by PBS in patients with benign and malignant nodules in LungRADS, version 1.1, category 4 vs other categories. (A) PBS-overall calculated based on the top 36 informative protein markers. (B) PBS-imminent calculated for the 10 markers relevant for lung cancer diagnosis within 1 year after blood collection. LungRADS = Lung Computed Tomography Reporting & Data System; PBS = protein burden score; PBS-imminent = protein burden scores for imminent tumors; PBS-overall = protein burden scores for overall nodule malignancy.
Figure 6.
Figure 6.
Time trend of PBS by lead time from blood collection to lung cancer diagnosis or end of follow-up in individuals with benign vs malignant nodules. (A) PBS-overall calculated based on the top 36 informative protein markers. (B) PBS-imminent calculated for the 10 markers relevant for lung cancer diagnosis within 1 year after blood collection. PBS = protein burden score; PBS-imminent = protein burden scores for imminent tumors; PBS-overall = protein burden scores for overall nodule malignancy.
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