Longitudinal plasma proteomic profiling of patients with non-small cell lung cancer undergoing immune checkpoint blockade

Michal Harel, Coren Lahav, Eyal Jacob, Nili Dahan, Itamar Sela, Yehonatan Elon, Shani Raveh Shoval, Galit Yahalom, Iris Kamer, Alona Zer, Ofer Sharon, David P. Carbone, Adam P. Dicker, Jair Bar, Yuval Shaked*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Background Immune checkpoint inhibitors (ICIs) have revolutionized the cancer therapy landscape due to long-term benefits in patients with advanced metastatic disease. However, robust predictive biomarkers for response are still lacking and treatment resistance is not fully understood. Methods We profiled approximately 800 pre-treatment and on-treatment plasma proteins from 143 ICI-treated patients with non-small cell lung cancer (NSCLC) using ELISA-based arrays. Different clinical parameters were collected from the patients including specific mutations, smoking habits, and body mass index, among others. Machine learning algorithms were used to identify a predictive signature for response. Bioinformatics tools were used for the identification of patient subtypes and analysis of differentially expressed proteins and pathways in each response group. Results We identified a predictive signature for response to treatment comprizing two proteins (CXCL8 and CXCL10) and two clinical parameters (age and sex). Bioinformatic analysis of the proteomic profiles identified three distinct patient clusters that correlated with multiple parameters such as response, sex and TNM (tumors, nodes, and metastasis) staging. Patients who did not benefit from ICI therapy exhibited significantly higher plasma levels of several proteins on-treatment, and enrichment in neutrophil-related proteins. Conclusions Our study reveals potential biomarkers in blood plasma for predicting response to ICI therapy in patients with NSCLC and sheds light on mechanisms underlying therapy resistance.

Original languageEnglish
Article numbere004582
JournalJournal for ImmunoTherapy of Cancer
Volume10
Issue number6
DOIs
StatePublished - 1 Jun 2022

Funding

FundersFunder number
OncoHost LTD
VBL
Bristol-Myers Squibb
Pfizer
AstraZeneca
Bayer
Novartis
Roche
AbbVie
Takeda Pharmaceutical Company

    Keywords

    • lung neoplasms
    • translational medical research
    • tumor biomarkers

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