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Semi-automatic PD-L1 Characterization and Enumeration of Circulating Tumor Cells from Non-small Cell Lung Cancer Patients by Immunofluorescence
Published on: August 14, 2019
Dissecting non-small cell lung cancer (NSCLC) with blood proteomics-from surgical to immunotherapeutic responses
Vahid Yaghoubi Naei1,2, Aaron Kilgallon2,3, Gwendoline Mendes4
1School of Biomedical Engineering, University of Technology Sydney, Sydney, NSW, Australia.
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.
Insights
This study identifies key plasma protein biomarkers in non-small cell lung cancer (NSCLC) to predict surgical recurrence and immunotherapy response. These proteomic signatures offer new insights for guiding NSCLC treatment strategies.
Area of Science:
- Proteomics
- Oncology
- Biomarker Discovery
Background:
- Non-small cell lung cancer (NSCLC) presents a significant challenge in cancer mortality due to limited predictive biomarkers.
- Effective guidance for surgical and immunotherapeutic interventions in NSCLC is hindered by a lack of reliable prognostic and predictive markers.
Purpose of the Study:
- To identify plasma protein signatures associated with surgical recurrence and immune checkpoint inhibitor (ICI) therapy response in NSCLC patients.
- To leverage complementary proteomics platforms for comprehensive biomarker discovery and validation.
Main Methods:
- Utilized SomaScan and NULISA proteomics platforms to analyze 87 plasma timepoints from 56 NSCLC patients.
- Employed adaptive Lasso regression and the Stabl algorithm for robust biomarker selection.
- Validated findings using orthogonal nELISA proteomics for inter- and intra-cohort confirmation.
Main Results:
- Identified 21 differentially detectable plasma proteins across treatment contexts.
- Found distinct proteomic changes post-surgery correlating with recurrence (e.g., MUC16, IL36G).
- Revealed baseline inflammatory and immune regulatory proteins (e.g., IL-6, CCL19) associated with ICI response and prognosis (e.g., CEACAM5, PTX3).
Conclusions:
- Plasma proteomic profiling can reveal signatures predictive of NSCLC surgical recurrence and ICI response.
- The integrated proteomic approach highlights the complementary utility of broad and targeted platforms.
- Identified biomarkers offer potential for improved patient stratification and treatment selection in NSCLC management.
