Predictive model for BNT162b2 vaccine response in cancer patients based on blood cytokines and growth factors.

ABSTRACT:

Background

Patients with cancer, especially hematological cancer, are at increased risk for breakthrough COVID-19 infection. So far, a predictive biomarker that can assess compromised vaccine-induced anti-SARS-CoV-2 immunity in cancer patients has not been proposed.

Methods

We employed machine learning approaches to identify a biomarker signature based on blood cytokines, chemokines, and immune- and non-immune-related growth factors linked to vaccine immunogenicity in 199 cancer patients receiving the BNT162b2 vaccine.

Results

C-reactive protein (general marker of inflammation), interleukin (IL)-15 (a pro-inflammatory cytokine), IL-18 (interferon-gamma inducing factor), and placental growth factor (an angiogenic cytokine) correctly classified patients with a diminishe

SUBMITTER: Konnova A 

PROVIDER: S-EPMC9813584 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature